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Journal of Medicine and Pharmacy","Tạp chí Y Dược học Cần Thơ",{"EN":487,"VI":488},"\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">04\u002F10\u002F2015 Ministry of Information and Communications allowed Can Tho journal of medicine and pharmacy to operate (102 \u002FGP-BTTTT)\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">07\u002F16\u002F2015 Can Tho journal of medicine and pharmacy is internationally recognized: ISSN 2354-1210\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">In 2016, The journal has been included in the list of medical science journals by The State Council for professorship which is awarded a work score of 0-0.5 points for a published article.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Can Tho Journal of Medicine and Pharmacy welcome original works that haven’t been submitted or published in other medical journals. Posts must contain content related to one of the journal’s categories.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">The content published\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">The journal is divided into 3 categories:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Scientific research article: are valuable scientific works, which have been researched and accepted.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Overview of medicine, biology and pharmacy: serving the objective of continuing training in the fields of medicine, biology and pharmacy; to systematize classical and modern knowledge.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Update information on new knowledge about medicine, biology, pharmacy in the country and in the world.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Scope\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Publication and introduction of scientific research in the fields:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">+ Medicine (internal medicine, surgery, pediatrics, obstetrics and gynecology, odonto-stomatology, laboratory, oncology, traditional medicine, nursing).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">+ Biology (genetics, biotechnology).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">+ Pharmacology (pharmaceutics, drug quality analysis-control, synthetic pharmaceutical chemistry, biochemistry, pharmacognosy, botany, clinical pharmacy).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- To enhance the quality of undergraduate, postgraduate education, scientifically researching and meet the necessary treatment in hospital.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Introducing the updated domestic and oversea information about science technology to promote scientific research and exchanging technology in local, other universities.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Exchanging pharmaceutical and medical information for social health developing in the Mekong Delta and Vietnam.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">The object\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Postgraduate students, student of Can Tho University of Medicine and Pharmacy, scientists from schools, research institutes, hospitals, health centers, pharmaceutical companies of the Mekong Delta; other provinces and regions in Vietnam and other country.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Address\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Headquarters of Can Tho Journal of Medicine and Pharmacy, located Scientific Research and International Cooperation Office: 179 Nguyen Van Cu Street, An Khanh Ward, Ninh Kieu District, Can Tho City, Vietnam.\u003C\u002Fspan>\u003C\u002Fp>","\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Ngày 16\u002F7\u002F2015, Tạp chí Y Dược học Cần Thơ được cấp chỉ số quốc tế: ISSN 2354-1210.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Từ tháng 4\u002F2016, Tạp chí đã được Hội đồng Giáo sư ngành Y đưa vào danh sách các tạp chí khoa học Y học được tính điểm công trình 0-0,5 điểm cho một bài báo đăng.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Năm 2020 Tạp chí Y Dược học Cần Thơ đã được phê duyệt vào danh mục của các Hội đồng Giáo sư ngành Dược học được tính điểm công trình 0-0,5 điểm cho một bài báo đăng.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí Y Dược học Cần Thơ ra 12 số\u002Fnăm, 180-200 trang\u002Fsố.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Từ tháng 12\u002F2022 Tạp chí Y Dược học Cần Thơ là thành viên của hệ thống Crossref và từ tháng 01\u002F2023 tạp chí thực hiện bình duyệt online kín 2 chiều nhằm tăng tính minh bạch, tin cậy của các công trình nghiên cứu khoa học và đảm bảo tốt nhất chất lượng khoa học của bài viết.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tôn chỉ, mục đích và phạm vi của tạp chí\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tôn chỉ và mục đích hoạt động của tạp chí: xuất bản nhằm mục đích phổ biến kết quả từ các đề tài nghiên cứu khoa học; giao lưu trao đổi khoa học, chia sẻ kinh nghiệm, học tập, đồng thời cập nhật thông tin khoa học mới trong các lĩnh vực y, sinh, dược học trong và ngoài nước.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Phạm vi của tạp chí: Tạp chí xuất bản được chia thành 3 chuyên mục: (i) Bài báo nghiên cứu khoa học là kết quả công trình nghiên cứu khoa học có giá trị đã được triển khai nghiên cứu, (ii) Bài tổng quan y, sinh, dược học: phục vụ mục tiêu đào tạo liên tục trong lĩnh vực y, sinh, dược học; nhằm hệ thống hóa những kiến thức kinh điển và hiện đại; (iii) Thông tin cập nhật kiến thức mới về y, sinh, dược học trong nước và trên thế giới.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Chính sách truy cập mở\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí Y Dược học Cần Thơ áp dụng chính sách truy cập mở đối với các bài báo đã xuất bản đến với độc giả, nhằm mở rộng cơ hội tiếp cận các kết quả nghiên cứu chất lượng cao và tăng cường trao đổi kiến thức. Tạp chí đăng tải trực tuyến (miễn phí) toàn văn các bài báo được công bố trên website của Tạp chí (https:\u002F\u002Ftapchi.ctump.edu.vn).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Đạo đức xuất bản\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí Y Dược học Cần Thơ cam kết tuân thủ đạo đức xuất bản phù hợp với các hướng dẫn và tiêu chuẩn của the Committee on Publication Ethics (COPE), tuân thủ các nguyên tắc của COPE’s Core Practices, Best Practices Guidelines for Journal Editors và Guidelines on Good Publication Practices.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Bản thảo bài báo chỉ được chấp nhận khi được tác giả chịu trách nhiệm chính cam kết các nội dung sau: Các nội dung của bản thảo chưa được đăng tải toàn bộ hoặc một phần ở các tạp chí khác; Tất cả các tác giả đều có đóng góp một cách đáng kể vào quá trình nghiên cứu hoặc chuẩn bị bản thảo và cùng chịu trách nhiệm về các nội dung của bản thảo; Tuân thủ các biện pháp đảm bảo đạo đức nghiên cứu (ví dụ thỏa thuận đồng ý tham gia nghiên cứu).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Cam kết bảo mật\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí cam kết thực hiện và tuân thủ các quy định của luật và các văn bản hướng dẫn liên quan đến bảo mật thông tin cá nhân trên không gian mạng. Các thông tin mà người dùng (tác giả, độc giả, biên tập viên, người phản biện) nhập vào các biểu mẫu trên Hệ thống Quản lý xuất bản trực tuyến của tạp chí chỉ được sử dụng vào các mục đích đã được tuyên bố rõ ràng và sẽ không được cung cấp cho bất kỳ bên thứ ba nào khác, hay dùng vào bất kỳ mục đích nào khác.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Phí gửi bài\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Lệ phí gửi đăng bài: 1.000.000đ\u002Fbài báo\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Lệ phí gửi đăng nhanh: 1.500.000đ\u002Fbài báo\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Đối với tác giả là cán bộ viên chức thuộc Trường Đại học Y Dược Cần Thơ thì được hỗ trợ 50% lệ phí gửi đăng bài.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Đối với sinh viên thực hiện đề tài nghiên cứu khoa học cấp trường được hỗ trợ 100% lệ phí đăng bài ( Tác giả gửi đính kèm “ Quyết định về việc giao tổ chức thực hiện đề tài nghiên cứu khoa học cấp Trường của sinh viên”).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Hình thức nộp lệ phí:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">1. Tiền mặt:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Nộp trực tiếp tại Phòng Tài chính - Kế toán, Trường Đại học Y Dược Cần Thơ, số 179 Nguyễn Văn Cừ, P. An Khánh, Q. Ninh Kiều, thành phố Cần Thơ.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">2. Chuyển khoản:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tên Tài khoản: Trường ĐHYD Cần Thơ, Số TK: 0111000115668, tại ngân hàng Vietcombank chi nhánh Cần Thơ.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Thời gian: Áp dụng từ ngày 01\u002F02\u002F2023.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">* Phí gửi bài không được hoàn trả khi bài viết bị từ chối hoặc tác giả xin rút bài viết.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Quy trình phản biện bài báo\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí Y Dược học Cần Thơ thực hiện quy trình phản biện kín hai chiều nghiêm ngặt. Danh tính của những người phản biện không được tiết lộ cho các tác giả và ngược lại. Quy trình thẩm định bài báo đăng gồm các bước sau:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tiếp nhận bản thảo\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tác giả liên hệ gửi bản thảo đến Tạp chí qua hệ thống trực tuyến tại website: https:\u002F\u002Ftapchi.ctump.edu.vn. Hướng dẫn về cách đăng ký, gửi bài và chuẩn bị bản thảo được cung cấp trên website của Tạp chí.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Sàng lọc sơ bộ\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Sau khi Tòa soạn nhận được bài báo của tác giả, Ban Thư ký sẽ tiến hành kiểm tra sơ bộ bài báo (các yêu cầu về nội dung và hình thức). Những bài báo không đúng quy cách hoặc có nội dung không phù hợp hoặc vi phạm bản quyền sẽ bị từ chối (Ban Thư ký thông báo phản hồi đến tác giả trong vòng 1 tuần). Những bài báo đủ điều kiện, được Ban Thư ký tòa soạn chuyển đến Ban Biên tập có cùng chuyên môn với nội dung bài báo để đề xuất người phản biện. Thời gian kể từ khi Ban Biên tập nhận bài báo đến khi đề xuất người phản biện bài báo chậm nhất là 5 ngày.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Vòng phản biện\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">1. Ban Thư ký gửi bài và yêu cầu phản biện đến 02 phản biện độc lập.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">2. Các phản biện gởi nhận xét cho Ban Thư ký. Thời gian từ khi gửi bài cho phản biện đến khi nhận ý kiến của phản biện tối đa là 20 ngày.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Xử ký kết quả phản biện\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">1. Nếu ý kiến đồng ý cho đăng và không cần chỉnh sửa, Ban Thư ký tiếp tục đăng bài theo qui trình.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">2. Nếu ý kiến đồng ý đăng và cần chỉnh sửa, Ban Thư ký sẽ thông tin đến tác giả chỉnh sửa theo yêu cầu của người phản biện. Thời gian chỉnh sửa và gửi lại kéo dài không quá 2 tuần, từ khi tác giả bài báo nhận được thông tin (Quá trình này có thể lặp lại tối đa 2 lần\u002F1 bài báo). Khi có sự thống nhất, đồng ý của người phản biện; bài báo được tiếp tục đăng theo qui trình.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">3. Những bài báo có chất lượng không đạt yêu cầu, cả 2 phản biện không đồng ý cho đăng sẽ bị Tòa soạn từ chối đăng.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Xuất bản\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">1. Ban Thư ký tổng hợp các bản thảo đã được tác giả hoàn thiện sau thẩm định trình Ban Biên tập xem xét, Tổng Biên tập phê duyệt, quyết định bài đăng theo các tiêu chí: sự phù hợp nội dung với tôn chỉ và mục đích, thể loại bài viết (ưu tiên các bài có bài có nghiên cứu chuyên sâu, hàm lượng khoa học cao), đóng góp mới bài báo, bài báo được ưu tiên đăng trong số gần nhất của Tạp chí theo thứ tự: tính thời sự, chất lượng bài báo và thời gian gửi bài.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">2. Ban Biên tập và Ban Thư ký biên tập bản thảo, chế bản, đọc rà soát lỗi. Thời gian hoàn thành từ 10-15 ngày.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">3. Ban Thư ký có trách nhiệm thông báo cho tác giả bài báo (bằng e-mail) về tình hình phê duyệt bài báo, thời gian, số kỳ, tập xuất bản bài báo theo qui định.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">4. Danh sách bài báo theo số Tạp chí được in ấn và phát hành trong năm định kỳ được công bố chính thức trên website: https:\u002F\u002Ftapchi.ctump.edu.vn\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>",{"VOID":490},"wcQ1uqwAAAAJ","2023-05-30T08:17:21.868+00:00",[],[494],{"id":495,"createTime":28,"updateTime":28,"relativeEntities":496,"slug":28,"properties":497,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":507,"parentIds":508,"statistic":28},"6413896b-eca9-442b-a73f-182a58a0ce40",[],{"title":498,"address":501,"country":504,"abbreviation":505},{"EN":499,"VI":500},"Can Tho University of Medicine and Pharmacy","Trường Đại học Y Dược Cần Thơ",{"EN":502,"VI":503},"No 179, Nguyen Van Cu street, An Khanh ward, Ninh Kieu district, Can Tho city, Vietnam","Số 179, đường Nguyễn Văn Cừ, phường An Khánh, quận Ninh Kiều, thành phố Cần Thơ, Việt Nam",{"VOID":15},{"VOID":506},"ctump","http:\u002F\u002Fwww.ctump.edu.vn\u002F",[],[],"https:\u002F\u002Ftapchi.ctump.edu.vn\u002Findex.php\u002Fctump",{"impactFactor":32,"impactFactorByYear":512,"i10Index":32,"i10IndexLast5Year":32,"totalPublication":514,"totalPublicationByYear":515,"totalCitation":520,"totalCitationByYear":521,"totalCitationPerPublication":108,"totalCitationPerPublicationByYear":523,"hindexLast5Year":45,"hindex":45},{"2022":513,"2023":111,"2024":106},0.01,1556,{"2020":47,"2021":516,"2022":517,"2023":518,"2024":519,"2025":122},57,306,801,358,161,{"2021":146,"2022":280,"2023":522},99,{"2021":524,"2022":318,"2023":104},0.23,{"impactFactor":28,"impactFactorByYear":28,"i10Index":123,"i10IndexLast5Year":123,"totalPublication":526,"totalPublicationByYear":527,"totalCitation":526,"totalCitationByYear":528,"totalCitationPerPublication":40,"totalCitationPerPublicationByYear":531,"hindexLast5Year":49,"hindex":49},476,{"0":205,"2019":123,"2021":139,"2022":459,"2023":451,"2024":357,"2025":49,"2026":48},{"2021":42,"2022":123,"2023":161,"2024":529,"2025":360,"2026":530},136,83,{"2021":105,"2022":513,"2023":532,"2024":127,"2025":533,"2026":534},0.62,25.43,13.83,{"id":536,"createTime":537,"updateTime":382,"relativeEntities":538,"slug":539,"properties":540,"entityType":25,"verifyStatus":26,"verifyTime":28,"verifyNote":28,"languages":552,"translateLanguages":28,"viewCount":133,"subjectFields":553,"manageAffiliations":554,"indexDatabases":555,"url":556,"thumbnailPath":557,"statistic":558,"gsStatistic":594,"type":55,"analyzePriority":28},"6984a56a-db70-403b-9cc4-4013e1ceaffa","2023-05-09T06:47:40.346+00:00",[],"T%E1%BA%A1p%20ch%C3%AD%20Nghi%C3%AAn%20c%E1%BB%A9u%20n%C6%B0%E1%BB%9Bc%20ngo%C3%A0i",{"country":541,"issn":542,"title":544,"introduce":547,"gsId":550},{"VOID":15},{"VOID":543},"25252445",{"EN":545,"VI":546},"VNU Journal of Foreign Studies","Tạp chí Nghiên cứu nước ngoài",{"EN":548,"VI":549},"{\"ops\":[{\"insert\":\"\\n\\nThe \\n\"},{\"attributes\":{\"italic\":true},\"insert\":\"VNU Journal of Science\"},{\"insert\":\"\\n was established in 1985 for the publication of national and international research papers in all fields of natural sciences and technology, social sciences and humanities. 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Trong số các UAS, những đặc điểm hứa hẹn bao gồm thời gian bay dài, độ an toàn trong nhiệm vụ được cải thiện, khả năng lặp lại chuyến bay nhờ vào việc nâng cấp hệ thống lái tự động, và giảm chi phí vận hành so với máy bay có người lái. Tuy nhiên, những lợi thế tiềm năng của một nền tảng không người lái phụ thuộc vào nhiều yếu tố, chẳng hạn như loại máy bay, loại cảm biến, mục tiêu của nhiệm vụ, và các yêu cầu quy định hiện hành dành cho hoạt động của nền tảng cụ thể. Các quy định liên quan đến việc vận hành UAS vẫn đang trong giai đoạn phát triển ban đầu và hiện tại tạo ra rào cản đáng kể cho người dùng khoa học. Trong bài viết này, chúng tôi mô tả nhiều loại nền tảng, cũng như khả năng của các cảm biến, và xác định những lợi thế của mỗi nền tảng liên quan đến các yêu cầu của người dùng trong lĩnh vực nghiên cứu khoa học. Chúng tôi cũng sẽ thảo luận ngắn gọn về tình trạng hiện tại của các quy định ảnh hưởng đến hoạt động của UAS, với mục đích thông báo cho cộng đồng khoa học về công nghệ đang phát triển này, mà tiềm năng cách mạng hóa quan sát khoa học tự nhiên tương tự như những biến đổi mà GIS và GPS đã mang lại cho cộng đồng hai thập kỷ trước.","\u003Cjats:p>Unmanned Aircraft Systems (UAS) have evolved rapidly over the past decade driven primarily by military uses, and have begun finding application among civilian users for earth sensing reconnaissance and scientific data collection purposes. Among UAS, promising characteristics are long flight duration, improved mission safety, flight repeatability due to improving autopilots, and reduced operational costs when compared to manned aircraft. The potential advantages of an unmanned platform, however, depend on many factors, such as aircraft, sensor types, mission objectives, and the current UAS regulatory requirements for operations of the particular platform. The regulations concerning UAS operation are still in the early development stages and currently present significant barriers to entry for scientific users. In this article we describe a variety of platforms, as well as sensor capabilities, and identify advantages of each as relevant to the demands of users in the scientific research sector. 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(2009, January 11–15). Unmanned Aircraft Systems for Wildland Fire Monitoring and Research. Tallahassee, FL, USA.",{},{"id":28,"text":1060,"url":28,"identifiers":1061},"Haydon, F.S. (2000). Military Ballooning During the Early Civil War, Johns Hopkins University Press.",{"doi":1062},"10.56021\u002F9780801864421",{"id":28,"text":1064,"url":28,"identifiers":1065},"Bowen, D (1977). Encyclopedia of War Machines: An Historical Survey of the World’s Great Weapons, Peerage Books.",{},{"id":28,"text":1067,"url":28,"identifiers":1068},"Hannavy, J. (2007). Encyclopedia of Nineteenth-Century Photography, Taylor & Francis Group.",{},{"id":28,"text":1070,"url":28,"identifiers":1071},"Nyquist, 1997, Unmanned aerial vehicles that even geoscience departments can afford, Geotimes, 42, 20",{},{"id":28,"text":1073,"url":28,"identifiers":1074},"Quilter, 2001, A proposed method for determining shrub utilization using LA\u002FLS imagery, J. 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Versailles, France.",{"doi":1100},"10.2514\u002F6.2002-3405",{"id":28,"text":1102,"url":28,"identifiers":1103},"Perry, J.H., Mohamed, A., El-Rahman, A.H., Bowman, W.S., Kaddoura, Y.O., and Watts, A.C. (2008, January 28–30). Precision Directly Georeferenced Unmanned Aerial Remote Sensing System: Performance Evaluation. San Diego, CA, USA.",{},{"id":28,"text":1105,"url":28,"identifiers":1106},"Wilkinson, 2009, A new approach for passpoint generation from aerial video imagery, Photogramm. Eng. Remote Sensing, 75, 1415, 10.14358\u002FPERS.75.12.1415",{"doi":1107},"10.14358\u002FPERS.75.12.1415",{"id":28,"text":1109,"url":28,"identifiers":1110},"(2007). Unmanned Aircraft Operations in the National Airspace System, Federal Register.",{},{"id":28,"text":1112,"url":28,"identifiers":1113},"Available online: http:\u002F\u002Fwww.faa.gov\u002Fabout\u002Finitiatives\u002Fuas\u002F (accessed on 15 February 2012).",{},{"id":28,"text":1115,"url":28,"identifiers":1116},"(2011). Unmanned Aircraft Operations in the National Airspace System (NAS), US Dept. of Transportation. Federal Aviation Administration Air Traffic Organization Policy Notice N JO 7210.766.",{},{"id":28,"text":1118,"url":28,"identifiers":1119},"Carey, B Small UAS rule will begin phased entry of unmanned aircraft. Available online: http:\u002F\u002Fwww.ainonline.com\u002F?q=aviation-news\u002Faviation-international-news\u002F2011-10-04\u002Fsmall-uas-rule-will-begin-phased-entry-unmanned-aircraft (accessed on 23 October 2011).",{},{"id":28,"text":1121,"url":28,"identifiers":1122},"Grady, M Coming soon: Era of UAS?. Available online: http:\u002F\u002Fwww.avweb.com\u002Favwebflash\u002Fnews\u002FComingSoonEraOfUAS_206186-1.html (accessed on 15 February 2012).",{},{"id":28,"text":1124,"url":28,"identifiers":1125},"Available online: http:\u002F\u002Fwww.pmddtc.state.gov\u002Fregulations_laws\u002Fitar.html (accessed on 15 February 2012).",{},false,{"id":1128,"createTime":1129,"updateTime":1129,"relativeEntities":1130,"slug":1131,"properties":1132,"entityType":966,"verifyStatus":26,"verifyTime":1143,"verifyNote":1144,"languages":1145,"translateLanguages":28,"viewCount":32,"primaryUrl":1146,"fullTextUrl":28,"authors":1147,"publicationType":1001,"publisherRelationship":1203,"citationCount":1252,"citationInfo":1253,"publishDate":28,"publishYear":28,"citationAnalyzeStatus":878,"lastCitationAnalyze":28,"indexDatabases":1257,"openAccess":28,"references":1258,"isForceReanalyzing":1126},"b99e407b-e8c7-4e62-a52a-2c4e0c8aa364","2025-02-10T17:45:32.153+00:00",[],"Applications-of-Remote-Sensing-in-Precision-Agriculture-A-Review",{"openalex":1133,"mag":1135,"abstract":1137,"title":1139,"doi":1141},{"VOID":1134},"W3088154325",{"VOID":1136},"3088154325",{"EN":1138},"\u003Cjats:p>Agriculture provides for the most basic needs of humankind: food and fiber. The introduction of new farming techniques in the past century (e.g., during the Green Revolution) has helped agriculture keep pace with growing demands for food and other agricultural products. However, further increases in food demand, a growing population, and rising income levels are likely to put additional strain on natural resources. With growing recognition of the negative impacts of agriculture on the environment, new techniques and approaches should be able to meet future food demands while maintaining or reducing the environmental footprint of agriculture. Emerging technologies, such as geospatial technologies, Internet of Things (IoT), Big Data analysis, and artificial intelligence (AI), could be utilized to make informed management decisions aimed to increase crop production. Precision agriculture (PA) entails the application of a suite of such technologies to optimize agricultural inputs to increase agricultural production and reduce input losses. Use of remote sensing technologies for PA has increased rapidly during the past few decades. The unprecedented availability of high resolution (spatial, spectral and temporal) satellite images has promoted the use of remote sensing in many PA applications, including crop monitoring, irrigation management, nutrient application, disease and pest management, and yield prediction. In this paper, we provide an overview of remote sensing systems, techniques, and vegetation indices along with their recent (2015–2020) applications in PA. Remote-sensing-based PA technologies such as variable fertilizer rate application technology in Green Seeker and Crop Circle have already been incorporated in commercial agriculture. Use of unmanned aerial vehicles (UAVs) has increased tremendously during the last decade due to their cost-effectiveness and flexibility in obtaining the high-resolution (cm-scale) images needed for PA applications. At the same time, the availability of a large amount of satellite data has prompted researchers to explore advanced data storage and processing techniques such as cloud computing and machine learning. Given the complexity of image processing and the amount of technical knowledge and expertise needed, it is critical to explore and develop a simple yet reliable workflow for the real-time application of remote sensing in PA. Development of accurate yet easy to use, user-friendly systems is likely to result in broader adoption of remote sensing technologies in commercial and non-commercial PA applications.\u003C\u002Fjats:p>",{"EN":1140},"Applications of Remote Sensing in Precision Agriculture: A Review",{"VOID":1142},"10.3390\u002Frs12193136","2025-02-10T17:45:32.152+00:00","Auto Verify",[31],"https:\u002F\u002Fwww.mdpi.com\u002F2072-4292\u002F12\u002F19\u002F3136",[1148,1167,1184],{"id":1149,"sortIndex":32,"researcher":28,"roles":1150,"affiliations":1151,"properties":1160,"displayName":1164,"givenName":28,"familyName":28},"16f3a675-fb03-47b4-aae2-b514c13cb745",[],[1152],{"id":1153,"sortIndex":32,"affiliation":1154,"properties":28},"93d01a24-35a3-4aea-bb86-29a07fa228c5",{"id":1153,"createTime":28,"updateTime":28,"relativeEntities":1155,"slug":28,"properties":1156,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1159,"statistic":28},[],{"title":1157},{"EN":1158},"College of Agriculture and Human Sciences, Prairie View A&M University, Prairie View, TX 77446, USA",[],{"orcid":1161,"title":1163,"openalex":1165},{"VOID":1162},"https:\u002F\u002Forcid.org\u002F0000-0003-2984-5157",{"EN":1164},"Rajendra P. 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Environ., 222, 133, 10.1016\u002Fj.rse.2018.12.032",{"doi":2298},"10.1016\u002Fj.rse.2018.12.032",{"id":28,"text":2300,"url":28,"identifiers":2301},"Candiago, 2015, Evaluating multispectral images and vegetation indices for precision farming applications from UAV images, Remote Sens., 7, 4026, 10.3390\u002Frs70404026",{"doi":2302},"10.3390\u002Frs70404026",{"id":2304,"createTime":2305,"updateTime":2306,"relativeEntities":2307,"slug":2308,"properties":2309,"entityType":966,"verifyStatus":26,"verifyTime":2305,"verifyNote":1144,"languages":2324,"translateLanguages":2325,"viewCount":32,"primaryUrl":2326,"fullTextUrl":28,"authors":2327,"publicationType":1001,"publisherRelationship":2383,"citationCount":2431,"citationInfo":2432,"publishDate":28,"publishYear":28,"citationAnalyzeStatus":878,"lastCitationAnalyze":28,"indexDatabases":2436,"openAccess":28,"references":2437,"isForceReanalyzing":1126},"5fa674c4-086b-4450-8177-20a0b6663b53","2024-09-12T16:22:48.194+00:00","2024-12-25T13:31:30.650+00:00",[],"Land-Surface-Temperature-Retrieval-from-Landsat-8-TIRS-Comparison-between-Radiative-Transfer-Equation-Based-Method-Split-Window-Algorithm-and-Single-Channel-Method",{"openalex":2310,"mag":2312,"abstract":2314,"title":2317,"keywords":2320,"doi":2322},{"VOID":2311},"W2076447280",{"VOID":2313},"2076447280",{"EN":2315,"VI":2316},"\u003Cjats:p>Accurate inversion of land surface geo\u002Fbiophysical variables from remote sensing data for earth observation applications is an essential and challenging topic for the global change research. Land surface temperature (LST) is one of the key parameters in the physics of earth surface processes from local to global scales. The importance of LST is being increasingly recognized and there is a strong interest in developing methodologies to measure LST from the space. Landsat 8 Thermal Infrared Sensor (TIRS) is the newest thermal infrared sensor for the Landsat project, providing two adjacent thermal bands, which has a great benefit for the LST inversion. In this paper, we compared three different approaches for LST inversion from TIRS, including the radiative transfer equation-based method, the split-window algorithm and the single channel method. Four selected energy balance monitoring sites from the Surface Radiation Budget Network (SURFRAD) were used for validation, combining with the MODIS 8 day emissivity product. For the investigated sites and scenes, results show that the LST inverted from the radiative transfer equation-based method using band 10 has the highest accuracy with RMSE lower than 1 K, while the SW algorithm has moderate accuracy and the SC method has the lowest accuracy.\u003C\u002Fjats:p>","\u003Cjats:p>Việc đảo ngược chính xác các biến số địa\u002Fvật lý bề mặt đất từ dữ liệu viễn thám cho các ứng dụng quan sát trái đất là một chủ đề thiết yếu và đầy thách thức đối với nghiên cứu biến đổi toàn cầu. Nhiệt độ bề mặt đất (LST) là một trong những tham số chính trong vật lý của các quá trình bề mặt trái đất từ quy mô địa phương đến toàn cầu. Tầm quan trọng của LST đang ngày càng được công nhận và có một sự quan tâm mạnh mẽ trong việc phát triển các phương pháp đo LST từ không gian. Cảm biến Hồng ngoại Nhiệt (TIRS) của Landsat 8 là cảm biến hồng ngoại nhiệt mới nhất của dự án Landsat, cung cấp hai dải nhiệt kế bên nhau, điều này có lợi lớn cho việc đảo ngược LST. Trong bài báo này, chúng tôi so sánh ba phương pháp khác nhau để đảo ngược LST từ TIRS, bao gồm phương pháp dựa trên phương trình truyền bức xạ, thuật toán cửa sổ kép và phương pháp kênh đơn. Bốn địa điểm giám sát cân bằng năng lượng từ Mạng lưới Ngân sách Bức xạ Bề mặt (SURFRAD) được sử dụng để thẩm định, kết hợp với sản phẩm độ phát xạ MODIS 8 ngày. Đối với các địa điểm và cảnh quan được điều tra, kết quả cho thấy rằng LST đảo ngược từ phương pháp dựa trên phương trình truyền bức xạ sử dụng dải 10 có độ chính xác cao nhất với RMSE thấp hơn 1 K, trong khi thuật toán SW có độ chính xác trung bình và phương pháp SC có độ chính xác thấp nhất.\u003C\u002Fjats:p>",{"EN":2318,"VI":2319},"Land Surface Temperature Retrieval from Landsat 8  TIRS—Comparison between Radiative Transfer  Equation-Based Method, Split Window Algorithm  and Single Channel Method","Rút Trích Nhiệt Độ Bề Mặt Đất Từ TIRS Của Landsat 8 — So Sánh Giữa Phương Pháp Dựa Trên Phương Trình Truyền Bức Xạ, Thuật Toán Cửa Sổ Kép và Phương Pháp Kênh Đơn",{"VI":2321},"Nhiệt độ bề mặt đất, Landsat 8, cảm biến hồng ngoại nhiệt, phương trình truyền bức xạ, thuật toán cửa sổ kép, phương pháp kênh đơn, viễn thám, biến đổi toàn cầu, trái đất, độ phát xạ, SURFRAD, MODIS.",{"VOID":2323},"10.3390\u002Frs6109829",[31],[30],"https:\u002F\u002Fwww.mdpi.com\u002F2072-4292\u002F6\u002F10\u002F9829",[2328,2347,2364],{"id":2329,"sortIndex":32,"researcher":28,"roles":2330,"affiliations":2331,"properties":2340,"displayName":2344,"givenName":28,"familyName":28},"c36c12d7-0bed-4fe0-a4a1-4623e69bfe52",[],[2332],{"id":2333,"sortIndex":32,"affiliation":2334,"properties":28},"a844600c-0bf0-4fa8-a61d-561355b9d9b3",{"id":2333,"createTime":28,"updateTime":28,"relativeEntities":2335,"slug":28,"properties":2336,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":2339,"statistic":28},[],{"title":2337},{"VI":2338},"Department of Geography and Planning, University of Saskatchewan, Kirk Hall 117 Science Place, Saskatoon, SK S7N 5C8, Canada",[],{"orcid":2341,"title":2343,"openalex":2345},{"VOID":2342},"https:\u002F\u002Forcid.org\u002F0000-0001-5941-9306",{"EN":2344},"Xiaolei Yu",{"VOID":2346},"A5022317683",{"id":2348,"sortIndex":40,"researcher":28,"roles":2349,"affiliations":2350,"properties":2357,"displayName":2361,"givenName":28,"familyName":28},"a2019b46-40ac-4389-b02c-6588660acb68",[],[2351],{"id":2333,"sortIndex":32,"affiliation":2352,"properties":28},{"id":2333,"createTime":28,"updateTime":28,"relativeEntities":2353,"slug":28,"properties":2354,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":2356,"statistic":28},[],{"title":2355},{"VI":2338},[],{"orcid":2358,"title":2360,"openalex":2362},{"VOID":2359},"https:\u002F\u002Forcid.org\u002F0000-0001-9428-4267",{"EN":2361},"Xulin Guo",{"VOID":2363},"A5101401631",{"id":2365,"sortIndex":123,"researcher":28,"roles":2366,"affiliations":2367,"properties":2376,"displayName":2380,"givenName":28,"familyName":28},"0ccbb41c-e89f-4663-a57b-bc415da1c4dc",[],[2368],{"id":2369,"sortIndex":32,"affiliation":2370,"properties":28},"b4445eb8-8ebf-4d2e-bc5c-c8720dbe9417",{"id":2369,"createTime":28,"updateTime":28,"relativeEntities":2371,"slug":28,"properties":2372,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":2375,"statistic":28},[],{"title":2373},{"VI":2374},"School of Remote Sensing and Information Engineering, Wuhan University, No. 129, Luoyu Road, Wuhan 430079, China",[],{"orcid":2377,"title":2379,"openalex":2381},{"VOID":2378},"https:\u002F\u002Forcid.org\u002F0000-0003-2435-5538",{"EN":2380},"Zhaocong Wu",{"VOID":2382},"A5062236070",{"url":28,"publisher":2384,"properties":2425},{"id":868,"createTime":869,"updateTime":870,"relativeEntities":2385,"slug":872,"properties":2386,"entityType":25,"verifyStatus":878,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":32,"subjectFields":2389,"manageAffiliations":2394,"indexDatabases":2405,"url":28,"thumbnailPath":28,"statistic":2420,"gsStatistic":28,"type":55,"analyzePriority":28},[],{"issn":2387,"title":2388},{"VOID":875},{"VOID":877},[2390],{"id":881,"createTime":28,"updateTime":28,"relativeEntities":2391,"label":2392,"description":2393,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":884},{},[2395,2400],{"id":888,"createTime":28,"updateTime":28,"relativeEntities":2396,"slug":28,"properties":2397,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":2399,"statistic":28},[],{"title":2398},{"EN":892},[],{"id":895,"createTime":28,"updateTime":28,"relativeEntities":2401,"slug":28,"properties":2402,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":2404,"statistic":28},[],{"title":2403},{"EN":899},[],[2406,2413],{"id":903,"indexDatabase":2407,"url":909,"indexYears":910,"academicFieldIds":2412,"indexDatabaseRanking":912},{"id":775,"createTime":28,"updateTime":28,"relativeEntities":2408,"label":2409,"description":2410,"key":781,"publicationTags":2411,"standard":28},[],{"EN":778,"VI":778},{"EN":778,"VI":780},[783],[787],{"id":914,"indexDatabase":2414,"url":926,"indexYears":28,"academicFieldIds":2419,"indexDatabaseRanking":28},{"id":916,"createTime":28,"updateTime":28,"relativeEntities":2415,"label":2416,"description":2417,"key":923,"publicationTags":2418,"standard":28},[],{"EN":919,"VI":919},{"EN":921,"VI":922},[925,813],[816,928,929,930],{"impactFactor":32,"impactFactorByYear":2421,"i10Index":51,"i10IndexLast5Year":45,"totalPublication":122,"totalPublicationByYear":2422,"totalCitation":934,"totalCitationByYear":2423,"totalCitationPerPublication":937,"totalCitationPerPublicationByYear":2424,"hindexLast5Year":51,"hindex":51},{"2015":40,"2016":45,"2020":40,"2021":168},{"2014":123,"2019":45,"2020":45,"2022":45},{"2014":936,"2019":328,"2020":148,"2022":278},{"2014":688,"2019":146,"2020":939,"2022":940},{"issue":2426,"pages":2428,"volume":2430},{"VOID":2427},"10",{"VOID":2429},"9829-9852",{"VOID":1046},675,{"total":2431,"publishYear":28,"statisticByYear":2433},{"2015":48,"2016":135,"2017":150,"2018":280,"2019":333,"2020":330,"2021":2434,"2022":2435,"2023":329,"2024":160},104,112,[],[2438,2441,2445,2449,2453,2457,2461,2465,2469,2473,2477,2481,2485,2489,2493,2497,2501,2505,2509,2513,2517,2521,2525,2529,2533,2536,2540,2544,2548,2552,2556,2559,2563,2567,2571,2575,2579,2583,2587,2591,2595,2599,2603,2607,2611,2615,2619,2623,2627,2631,2635,2639,2643,2647,2651,2655,2659,2663,2667,2671,2674,2678,2682,2686,2690,2694,2698,2702,2706,2710],{"id":28,"text":2439,"url":28,"identifiers":2440},"Liang, 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Environ, 142, 111, 10.1016\u002Fj.rse.2013.11.014",{"doi":2452},"10.1016\u002Fj.rse.2013.11.014",{"id":28,"text":2454,"url":28,"identifiers":2455},"Weng, 2014, Modeling annual parameters of clear-sky land surface temperature variations and evaluating the impact of cloud cover using time series of Landsat TIR data, Remote Sens. Environ, 140, 267, 10.1016\u002Fj.rse.2013.09.002",{"doi":2456},"10.1016\u002Fj.rse.2013.09.002",{"id":28,"text":2458,"url":28,"identifiers":2459},"Weng, 2014, Generating daily land surface temperature at Landsat resolution by fusing Landsat and MODIS data, Remote Sens. Environ, 145, 55, 10.1016\u002Fj.rse.2014.02.003",{"doi":2460},"10.1016\u002Fj.rse.2014.02.003",{"id":28,"text":2462,"url":28,"identifiers":2463},"Roy, 2014, Landsat-8: Science and product vision for terrestrial global change research, Remote Sens. Environ, 145, 154, 10.1016\u002Fj.rse.2014.02.001",{"doi":2464},"10.1016\u002Fj.rse.2014.02.001",{"id":28,"text":2466,"url":28,"identifiers":2467},"Markham, 2004, Landsat sensor performance: History and current status, IEEE Trans. Geosci. Remote Sens, 42, 2691, 10.1109\u002FTGRS.2004.840720",{"doi":2468},"10.1109\u002FTGRS.2004.840720",{"id":28,"text":2470,"url":28,"identifiers":2471},"Huang, 2010, An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks, Remote Sens. Environ, 114, 183, 10.1016\u002Fj.rse.2009.08.017",{"doi":2472},"10.1016\u002Fj.rse.2009.08.017",{"id":28,"text":2474,"url":28,"identifiers":2475},"Cristobal, 2009, Revision of the single-channel algorithm for land surface temperature retrieval from Landsat thermal-infrared data, IEEE Trans. Geosci. 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Remote Sens, 6, 1552, 10.1109\u002FJSTARS.2013.2259146",{"doi":2701},"10.1109\u002FJSTARS.2013.2259146",{"id":28,"text":2703,"url":28,"identifiers":2704},"Yu, 2008, Evaluation of split-window land surface temperature algorithms for generating climate data records, IEEE Trans. Geosci. Remote Sens, 46, 179, 10.1109\u002FTGRS.2007.909097",{"doi":2705},"10.1109\u002FTGRS.2007.909097",{"id":28,"text":2707,"url":28,"identifiers":2708},"Miller, R.G. (1997). Beyond Anova: Basics of Applied Statistics, CRC Press.",{"doi":2709},"10.1201\u002Fb15236",{"id":28,"text":2711,"url":28,"identifiers":2712},"Lee, E.T., and Wang, J.W. (2013). Statistical Methods for Survival Data Analysis, John Wiley & Sons.",{},{"id":2714,"createTime":2715,"updateTime":2716,"relativeEntities":2717,"slug":2718,"properties":2719,"entityType":966,"verifyStatus":26,"verifyTime":2734,"verifyNote":1144,"languages":2735,"translateLanguages":2736,"viewCount":32,"primaryUrl":2737,"fullTextUrl":28,"authors":2738,"publicationType":1001,"publisherRelationship":2932,"citationCount":2981,"citationInfo":2982,"publishDate":28,"publishYear":28,"citationAnalyzeStatus":878,"lastCitationAnalyze":28,"indexDatabases":2987,"openAccess":28,"references":2988,"isForceReanalyzing":1126},"3deb375f-8a55-4c83-836a-704a61502c0a","2024-09-12T16:23:02.536+00:00","2025-02-03T03:00:34.563+00:00",[],"Satellite-Remote-Sensing-of-Surface-Urban-Heat-Islands-Progress-Challenges-and-Perspectives",{"openalex":2720,"mag":2722,"abstract":2724,"title":2727,"keywords":2730,"doi":2732},{"VOID":2721},"W2907470085",{"VOID":2723},"2907470085",{"VI":2725,"EN":2726},"\u003Cjats:p>Các đảo nhiệt đô thị bề mặt (SUHI), đại diện cho sự khác biệt về nhiệt độ bề mặt đất (LST) trong môi trường đô thị so với các bề mặt không đô thị lân cận, thường được đo bằng dữ liệu LST vệ tinh. Trong vài thập kỷ qua, sự phát triển của công nghệ cảm biến từ xa cùng với khoa học không gian đã tăng cường đáng kể số lượng và chất lượng các nghiên cứu về SUHI, hình thành nên một khối lượng tài liệu chính yếu về đảo nhiệt đô thị (UHI). Bài báo này cung cấp một cái nhìn tổng quan có hệ thống về các nghiên cứu SUHI dựa trên vệ tinh, từ nguồn gốc của chúng vào năm 1972 cho đến hiện nay. Chúng tôi nhận thấy xu hướng nghiên cứu SUHI đã gia tăng theo cấp số nhân từ năm 2005, với những ưu tiên rõ ràng về các khu vực địa lý, thời gian trong ngày, các mùa, trọng tâm nghiên cứu và các nền tảng\u002Fcảm biến. Khu vực và thời gian nghiên cứu thường được nghiên cứu nhất là Trung Quốc và thời gian ban ngày mùa hè, tương ứng. Gần hai phần ba các nghiên cứu tập trung vào sự biến đổi SUHI\u002FLST ở quy mô cục bộ. Cảm biến vệ tinh Landsat Thematic Mapper (TM)\u002FEnhanced Thematic Mapper (ETM+)\u002FThermal Infrared Sensor (TIRS) và Terra\u002FAqua Moderate Resolution Imaging Spectroradiometer (MODIS) là hai cảm biến vệ tinh thường được sử dụng và chiếm khoảng 78% tổng số công bố. Chúng tôi đã xem xét có hệ thống các vệ tinh\u002Fcảm biến chính, phương pháp, phát hiện chính và thách thức trong nghiên cứu SUHI. Các nghiên cứu trước đây khẳng định rằng sự biến động không gian lớn (từ quy mô cục bộ đến toàn cầu) và tạm thời (theo chu kỳ ngày đêm, theo mùa và giữa các năm) của SUHI được đóng góp bởi nhiều yếu tố như diện tích bề mặt không thấm nước, độ che phủ thực vật, cấu trúc cảnh quan, albedo và khí hậu. Tuy nhiên, việc áp dụng nghiên cứu SUHI chủ yếu bị cản trở bởi hàng loạt hạn chế về dữ liệu và phương pháp. Cuối cùng, chúng tôi đề xuất những hướng đi và cơ hội quan trọng cho các nỗ lực trong tương lai. Bên cạnh việc cải thiện chất lượng và số lượng dữ liệu LST, cần tập trung nhiều hơn vào các khu vực\u002Fthành phố chưa được nghiên cứu, các phương pháp để kiểm tra cường độ SUHI, sự biến đổi liên năm và các xu hướng lâu dài của SUHI, các vấn đề về tỷ lệ của SUHI, mối quan hệ giữa UHI bề mặt và UHI dưới bề mặt, và việc tích hợp cảm biến từ xa với các quan sát thực địa và mô hình số.\u003C\u002Fjats:p>","\u003Cjats:p>The surface urban heat island (SUHI), which represents the difference of land surface temperature (LST) in urban relativity to neighboring non-urban surfaces, is usually measured using satellite LST data. Over the last few decades, advancements of remote sensing along with spatial science have considerably increased the number and quality of SUHI studies that form the major body of the urban heat island (UHI) literature. This paper provides a systematic review of satellite-based SUHI studies, from their origin in 1972 to the present. We find an exponentially increasing trend of SUHI research since 2005, with clear preferences for geographic areas, time of day, seasons, research foci, and platforms\u002Fsensors. The most frequently studied region and time period of research are China and summer daytime, respectively. Nearly two-thirds of the studies focus on the SUHI\u002FLST variability at a local scale. The Landsat Thematic Mapper (TM)\u002FEnhanced Thematic Mapper (ETM+)\u002FThermal Infrared Sensor (TIRS) and Terra\u002FAqua Moderate Resolution Imaging Spectroradiometer (MODIS) are the two most commonly-used satellite sensors and account for about 78% of the total publications. We systematically reviewed the main satellite\u002Fsensors, methods, key findings, and challenges of the SUHI research. Previous studies confirm that the large spatial (local to global scales) and temporal (diurnal, seasonal, and inter-annual) variations of SUHI are contributed by a variety of factors such as impervious surface area, vegetation cover, landscape structure, albedo, and climate. However, applications of SUHI research are largely impeded by a series of data and methodological limitations. Lastly, we propose key potential directions and opportunities for future efforts. Besides improving the quality and quantity of LST data, more attention should be focused on understudied regions\u002Fcities, methods to examine SUHI intensity, inter-annual variability and long-term trends of SUHI, scaling issues of SUHI, the relationship between surface and subsurface UHIs, and the integration of remote sensing with field observations and numeric modeling.\u003C\u002Fjats:p>",{"EN":2728,"VI":2729},"Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives","Giám sát từ xa bằng vệ tinh về các đảo nhiệt đô thị bề mặt: Tiến bộ, Thách thức và Triển vọng",{"VI":2731},"",{"VOID":2733},"10.3390\u002Frs11010048","2024-09-12T16:23:02.535+00:00",[31],[30],"https:\u002F\u002Fwww.mdpi.com\u002F2072-4292\u002F11\u002F1\u002F48",[2739,2758,2780,2799,2818,2837,2856,2875,2894,2913],{"id":2740,"sortIndex":32,"researcher":28,"roles":2741,"affiliations":2742,"properties":2751,"displayName":2755,"givenName":28,"familyName":28},"bbbf6386-384a-44ee-b585-1c344df02692",[],[2743],{"id":2744,"sortIndex":32,"affiliation":2745,"properties":28},"95252b1d-f8c9-49f5-8664-32022c1e7b25",{"id":2744,"createTime":28,"updateTime":28,"relativeEntities":2746,"slug":28,"properties":2747,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":2750,"statistic":28},[],{"title":2748},{"VI":2749},"Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China",[],{"orcid":2752,"title":2754,"openalex":2756},{"VOID":2753},"https:\u002F\u002Forcid.org\u002F0000-0003-0947-0853",{"EN":2755},"Decheng Zhou",{"VOID":2757},"A5043023884",{"id":2759,"sortIndex":40,"researcher":28,"roles":2760,"affiliations":2761,"properties":2773,"displayName":2777,"givenName":28,"familyName":28},"40ee26bd-b85f-401b-a735-04ddf7db128e",[],[2762],{"id":2763,"sortIndex":32,"affiliation":2764,"properties":2770},"412cbbdf-9ec5-41b4-a416-75722a7a47cb",{"id":2763,"createTime":28,"updateTime":28,"relativeEntities":2765,"slug":28,"properties":2766,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":2769,"statistic":28},[],{"title":2767},{"VI":2768},"Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, United States",[],{"title":2771},{"EN":2772},"Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA",{"orcid":2774,"title":2776,"openalex":2778},{"VOID":2775},"https:\u002F\u002Forcid.org\u002F0000-0002-0622-6903",{"EN":2777},"Jingfeng Xiao",{"VOID":2779},"A5045276244",{"id":2781,"sortIndex":123,"researcher":28,"roles":2782,"affiliations":2783,"properties":2792,"displayName":2796,"givenName":28,"familyName":28},"41ebadb5-5477-47e8-a8f2-2face4b2d04f",[],[2784],{"id":2785,"sortIndex":32,"affiliation":2786,"properties":28},"dcaa6972-f5bb-4e8d-88e7-7634bb5a2b95",{"id":2785,"createTime":28,"updateTime":28,"relativeEntities":2787,"slug":28,"properties":2788,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":2791,"statistic":28},[],{"title":2789},{"VI":2790},"Department of Engineering, University of Perugia, Via G. 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Geogr., 66, 116, 10.1016\u002Fj.jtrangeo.2017.11.016",{"doi":4051},"10.1016\u002Fj.jtrangeo.2017.11.016",{"id":4053,"createTime":4054,"updateTime":4055,"relativeEntities":4056,"slug":4057,"properties":4058,"entityType":966,"verifyStatus":26,"verifyTime":4054,"verifyNote":1144,"languages":4072,"translateLanguages":4073,"viewCount":32,"primaryUrl":4074,"fullTextUrl":28,"authors":4075,"publicationType":1001,"publisherRelationship":4159,"citationCount":4208,"citationInfo":4209,"publishDate":28,"publishYear":28,"citationAnalyzeStatus":878,"lastCitationAnalyze":28,"indexDatabases":4211,"openAccess":28,"references":4212,"isForceReanalyzing":1126},"060a900f-6aec-4826-9a75-5643785fe880","2024-10-09T18:50:31.282+00:00","2025-02-03T03:01:33.382+00:00",[],"Remote-Sensing-of-Mangrove-Ecosystems-A-Review",{"openalex":4059,"mag":4061,"abstract":4063,"title":4066,"keywords":4069,"doi":4070},{"VOID":4060},"W2126236168",{"VOID":4062},"2126236168",{"VI":4064,"EN":4065},"\u003Cjats:p>Các hệ sinh thái rừng ngập mặn chiếm ưu thế trong các vùng đất ngập nước ven biển của các khu vực nhiệt đới và cận nhiệt đới trên toàn thế giới. Chúng cung cấp nhiều dịch vụ hệ sinh thái sinh thái và kinh tế đóng góp vào việc bảo vệ chống xói mòn bờ biển, lọc nước, cung cấp khu vực cho việc sinh sản của cá và tôm, cung cấp nguyên liệu xây dựng và thành phần dược liệu, cũng như thu hút du khách, bên cạnh nhiều yếu tố khác. Đồng thời, rừng ngập mặn là một trong những hệ sinh thái bị đe dọa và dễ bị tổn thương nhất trên toàn cầu và đã trải qua sự suy giảm nghiêm trọng trong nửa thế kỷ qua. Các chương trình quốc tế, như Công ước Ramsar về Đất ngập nước hoặc Nghị định thư Kyoto, nhấn mạnh tầm quan trọng của các biện pháp bảo vệ khẩn cấp và các hoạt động bảo tồn để ngăn chặn sự mất mát tiếp theo của rừng ngập mặn. Trong bối cảnh này, giám sát từ xa là công cụ lựa chọn để cung cấp thông tin không gian-thời gian về sự phân bố của hệ sinh thái rừng ngập mặn, sự phân biệt loài, tình trạng sức khỏe và các thay đổi diễn ra trong quần thể rừng ngập mặn. Các nghiên cứu như vậy có thể được thực hiện dựa trên nhiều loại cảm biến, từ chụp ảnh hàng không đến hình ảnh quang học có độ phân giải cao và trung bình, từ dữ liệu siêu quang phổ đến dữ liệu radar sóng vi ba chủ động (SAR). Các kỹ thuật giám sát từ xa đã chứng minh tiềm năng cao trong việc phát hiện, xác định, lập bản đồ và theo dõi tình trạng và thay đổi của rừng ngập mặn trong hai thập kỷ qua, điều này được thể hiện qua số lượng lớn các bài báo khoa học được xuất bản về chủ đề này. Theo kiến thức của chúng tôi, chưa có một bài tổng quan gần đây về sự giám sát từ xa của rừng ngập mặn, mặc dù các hệ sinh thái rừng ngập mặn đã trở thành tâm điểm chú ý trong bối cảnh biến đổi khí hậu hiện nay và các cuộc thảo luận về các dịch vụ mà những hệ sinh thái này cung cấp. Hơn nữa, các nghiên cứu giám sát từ xa liên quan đến biến đổi khí hậu ở các khu vực ven biển đã tăng lên đáng kể trong những năm gần đây. Mục tiêu của bài tổng quan này là cung cấp cái nhìn tổng quát và tóm tắt có cơ sở về tất cả các công việc đã được thực hiện, đề cập đến sự đa dạng của dữ liệu được giám sát từ xa được áp dụng cho lập bản đồ hệ sinh thái rừng ngập mặn, cũng như nhiều phương pháp và kỹ thuật được sử dụng để phân tích dữ liệu, và thảo luận thêm về tiềm năng và những hạn chế của chúng.\u003C\u002Fjats:p>","\u003Cjats:p>Mangrove ecosystems dominate the coastal wetlands of tropical and subtropical regions throughout the world. They provide various ecological and economical ecosystem services contributing to coastal erosion protection, water filtration, provision of areas for fish and shrimp breeding, provision of building material and medicinal ingredients, and the attraction of tourists, amongst many other factors. At the same time, mangroves belong to the most threatened and vulnerable ecosystems worldwide and experienced a dramatic decline during the last half century. International programs, such as the Ramsar Convention on Wetlands or the Kyoto Protocol, underscore the importance of immediate protection measures and conservation activities to prevent the further loss of mangroves. In this context, remote sensing is the tool of choice to provide spatio-temporal information on mangrove ecosystem distribution, species differentiation, health status, and ongoing changes of mangrove populations. Such studies can be based on various sensors, ranging from aerial photography to high- and medium-resolution optical imagery and from hyperspectral data to active microwave (SAR) data. Remote-sensing techniques have demonstrated a high potential to detect, identify, map, and monitor mangrove conditions and changes during the last two decades, which is reflected by the large number of scientific papers published on this topic. To our knowledge, a recent review paper on the remote sensing of mangroves does not exist, although mangrove ecosystems have become the focus of attention in the context of current climate change and discussions of the services provided by these ecosystems. Also, climate change-related remote-sensing studies in coastal zones have increased drastically in recent years. The aim of this review paper is to provide a comprehensive overview and sound summary of all of the work undertaken, addressing the variety of remotely sensed data applied for mangrove ecosystem mapping, as well as the numerous methods and techniques used for data analyses, and to further discuss their potential and limitations.\u003C\u002Fjats:p>",{"EN":4067,"VI":4068},"Remote Sensing of Mangrove Ecosystems: A Review","Giám sát từ xa các hệ sinh thái rừng ngập mặn: Một bài tổng 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2001, Depletion of the mangroves of continential Asia, Wetlands Ecol. 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Manage., 46, 823, 10.1016\u002FS0964-5691(03)00062-0",{"doi":4881},"10.1016\u002FS0964-5691(03)00062-0",{"id":28,"text":4883,"url":28,"identifiers":4884},"Manson, 2003, Spatial and temporal variation in distribution of mangroves in Moreton Bay, subtropical Australia: A comparison of pattern metrics and change detection analyses based on aerial photographs, Estuar. Coast. Shelf Sci., 57, 653, 10.1016\u002FS0272-7714(02)00405-5",{"doi":4885},"10.1016\u002FS0272-7714(02)00405-5",{"id":4887,"createTime":4888,"updateTime":4889,"relativeEntities":4890,"slug":4891,"properties":4892,"entityType":966,"verifyStatus":26,"verifyTime":4888,"verifyNote":1144,"languages":4906,"translateLanguages":4907,"viewCount":32,"primaryUrl":4908,"fullTextUrl":28,"authors":4909,"publicationType":1001,"publisherRelationship":4980,"citationCount":5027,"citationInfo":5028,"publishDate":28,"publishYear":28,"citationAnalyzeStatus":878,"lastCitationAnalyze":28,"indexDatabases":5030,"openAccess":28,"references":5031,"isForceReanalyzing":1126},"1e399fb4-c287-4b06-87bc-71da91cd76b5","2024-08-31T03:35:31.313+00:00","2025-02-03T03:02:30.491+00:00",[],"Development-of-a-UAV-LiDAR-System-with-Application-to-Forest-Inventory",{"openalex":4893,"mag":4895,"abstract":4897,"title":4900,"keywords":4903,"doi":4904},{"VOID":4894},"W1983818779",{"VOID":4896},"1983818779",{"VI":4898,"EN":4899},"\u003Cjats:p>Chúng tôi trình bày sự phát triển của một hệ thống Máy bay không người lái phát hiện ánh sáng và khoảng cách (UAV-LiDAR) với chi phí thấp và quy trình đi kèm để sản xuất mây điểm 3D. Hệ thống UAV cung cấp sự kết hợp vô song của các tập dữ liệu có độ phân giải tạm thời và không gian cao. Hệ thống UAV-LiDAR TerraLuma đã được phát triển nhằm tận dụng những đặc điểm này và đồng thời khắc phục một số giới hạn hiện tại của việc sử dụng công nghệ này trong ngành lâm nghiệp. Một quy trình chế biến được sửa đổi bao gồm một thuật toán xác định quỹ đạo mới kết hợp các quan sát từ bộ thu GPS, Đơn vị Đo lường Quán tính (IMU) và một camera video Độ phân giải Cao (HD) được trình bày. Những lợi thế của quy trình này được chứng minh bằng cách sử dụng một đánh giá nghiêm ngặt về độ chính xác không gian của các mây điểm cuối cùng. Đã chứng minh rằng do việc bao gồm video, độ chính xác theo chiều ngang của mây điểm cuối cùng cải thiện từ 0.61 m xuống 0.34 m (lỗi RMS được đánh giá so với điểm kiểm soát mặt đất). Ảnh hưởng của các mây điểm với mật độ rất cao (lên tới 62 điểm mỗi m2) do hệ thống UAV-LiDAR sản xuất trên việc đo lường vị trí cây, chiều cao và chiều rộng tán cũng được đánh giá bằng cách thực hiện các cuộc khảo sát lặp lại trên các cây đơn lẻ. Độ lệch chuẩn của chiều cao cây cho thấy giảm từ 0.26 m, khi sử dụng dữ liệu có mật độ 8 điểm mỗi m2, xuống còn 0.15 m khi sử dụng dữ liệu mật độ cao hơn. Cải tiến về độ không chắc chắn trong việc đo lường vị trí cây, từ 0.80 m xuống 0.53 m, và chiều rộng tán, từ 0.69 m xuống 0.61 m cũng được chỉ ra.","\u003Cjats:p>We present the development of a low-cost Unmanned Aerial Vehicle-Light Detecting and Ranging (UAV-LiDAR) system and an accompanying workflow to produce 3D point clouds. UAV systems provide an unrivalled combination of high temporal and spatial resolution datasets. The TerraLuma UAV-LiDAR system has been developed to take advantage of these properties and in doing so overcome some of the current limitations of the use of this technology within the forestry industry. A modified processing workflow including a novel trajectory determination algorithm fusing observations from a GPS receiver, an Inertial Measurement Unit (IMU) and a High Definition (HD) video camera is presented. The advantages of this workflow are demonstrated using a rigorous assessment of the spatial accuracy of the final point clouds. It is shown that due to the inclusion of video the horizontal accuracy of the final point cloud improves from 0.61 m to 0.34 m (RMS error assessed against ground control). The effect of the very high density point clouds (up to 62 points per m2) produced by the UAV-LiDAR system on the measurement of tree location, height and crown width are also assessed by performing repeat surveys over individual isolated trees. The standard deviation of tree height is shown to reduce from 0.26 m, when using data with a density of 8 points perm2, to 0.15mwhen the higher density data was used. Improvements in the uncertainty of the measurement of tree location, 0.80 m to 0.53 m, and crown width, 0.69 m to 0.61 m are also shown.\u003C\u002Fjats:p>",{"EN":4901,"VI":4902},"Development of a UAV-LiDAR System with Application to Forest Inventory","Phát triển Hệ thống UAV-LiDAR với Ứng dụng trong Kiểm kê Rừng",{"VI":2731},{"VOID":4905},"10.3390\u002Frs4061519",[31],[30],"https:\u002F\u002Fwww.mdpi.com\u002F2072-4292\u002F4\u002F6\u002F1519",[4910,4929,4946,4963],{"id":4911,"sortIndex":32,"researcher":28,"roles":4912,"affiliations":4913,"properties":4922,"displayName":4926,"givenName":28,"familyName":28},"cf4a3f40-d4a6-479f-a0ff-d3f6cd532cf4",[],[4914],{"id":4915,"sortIndex":32,"affiliation":4916,"properties":28},"ae60ef64-4f38-4d32-854a-d30a634a3789",{"id":4915,"createTime":28,"updateTime":28,"relativeEntities":4917,"slug":28,"properties":4918,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":4921,"statistic":28},[],{"title":4919},{"EN":4920},"School of Geography and Environmental Studies, University of Tasmania, Hobart, TAS, 7001, Australia",[],{"orcid":4923,"title":4925,"openalex":4927},{"VOID":4924},"https:\u002F\u002Forcid.org\u002F0000-0002-4642-8374",{"EN":4926},"Luke 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Eng, 90, 369, 10.1016\u002Fj.biosystemseng.2004.12.011",{"doi":5066},"10.1016\u002Fj.biosystemseng.2004.12.011",{"id":28,"text":5068,"url":28,"identifiers":5069},"Laliberte, 2011, Multispectral remote sensing from unmanned aircraft: Image processing workflows and applications for rangeland environments, Remote Sens, 3, 2529, 10.3390\u002Frs3112529",{"doi":5070},"10.3390\u002Frs3112529",{"id":28,"text":5072,"url":28,"identifiers":5073},"Hunt, 2010, Acquisition of NIR-Green-Blue digital photographs from unmanned aircraft for crop monitoring, Remote Sens, 2, 290, 10.3390\u002Frs2010290",{"doi":5074},"10.3390\u002Frs2010290",{"id":28,"text":5076,"url":28,"identifiers":5077},"Tao, W., Lei, Y., and Mooney, P (July, January 29). Dense Point Cloud Extraction from UAV Captured Images in Forest Area. Fuzhou, China.",{},{"id":28,"text":5079,"url":28,"identifiers":5080},"Dandois, 2010, Remote sensing of vegetation structure using computer vision, Remote Sens, 2, 1157, 10.3390\u002Frs2041157",{"doi":5081},"10.3390\u002Frs2041157",{"id":28,"text":5083,"url":28,"identifiers":5084},"Jaakkola, 2010, A low-costmulti-sensoral mobile mapping system and its feasibility for tree measurements, ISPRS J. Photogramm, 65, 514, 10.1016\u002Fj.isprsjprs.2010.08.002",{"doi":5085},"10.1016\u002Fj.isprsjprs.2010.08.002",{"id":28,"text":5087,"url":28,"identifiers":5088},"Lin, 2011, Mini-UAV-borne LIDAR for fine-scale mapping, IEEE Geosci. Remote S, 8, 426, 10.1109\u002FLGRS.2010.2079913",{"doi":5089},"10.1109\u002FLGRS.2010.2079913",{"id":28,"text":5091,"url":28,"identifiers":5092},"Choi, 2009, Developing a UAV-based rapid mapping system for emergency response, Proc. SPIE, 7332, 733209, 10.1117\u002F12.818492",{"doi":5093},"10.1117\u002F12.818492",{"id":28,"text":5095,"url":28,"identifiers":5096},"Nagai, 2009, UAV-borne 3-D mapping system by multisensor integration, IEEE T. Geosci. Remote, 47, 701, 10.1109\u002FTGRS.2008.2010314",{"doi":5097},"10.1109\u002FTGRS.2008.2010314",{"id":28,"text":5099,"url":28,"identifiers":5100},"Miller, R., and Amidi, O (, January June). 3-D Site Mapping with the CMU Autonomous Helicopter 3-D Site Mapping with the CMU Autonomous Helicopter. Sapparo, Japan.",{},{"id":28,"text":5102,"url":28,"identifiers":5103},"Glennie, 2007, Rigorous 3D error analysis of kinematic scanning LIDAR systems, J. Appl. Geodes, 1, 147, 10.1515\u002Fjag.2007.017",{"doi":5104},"10.1515\u002Fjag.2007.017",{"id":28,"text":5106,"url":28,"identifiers":5107},"Schwarz, 2004, Mobile Mapping Systems State of the art and future trends, Int. Arch. Photogr. Remote Sens. Spat. Inf. 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Anal, 26, 756, 10.1109\u002FTPAMI.2004.17",{"doi":5176},"10.1109\u002FTPAMI.2004.17",{"id":28,"text":5178,"url":28,"identifiers":5179},"Hol, 2010, Modeling and calibration of inertial and vision sensors, Int. J. Rob. Res, 29, 231, 10.1177\u002F0278364909356812",{"doi":5180},"10.1177\u002F0278364909356812",{"id":28,"text":5182,"url":28,"identifiers":5183},"Isenberg, M Available online: http:\u002F\u002Fwww.cs.unc.edu\u002F~isenburg\u002Flastools\u002F (accessed on 15 December 2011).",{},{"id":28,"text":5185,"url":28,"identifiers":5186},"Shrestha, 2012, Estimating biophysical parameters of individual trees in an urban environment using small footprint discrete-return imaging lidar, Remote Sens, 4, 484, 10.3390\u002Frs4020484",{"doi":5187},"10.3390\u002Frs4020484",{"id":28,"text":5189,"url":28,"identifiers":5190},"Blanchard, 2011, Object-based image analysis of downed logs in disturbed forested landscapes using lidar, Remote Sens, 3, 2420, 10.3390\u002Frs3112420",{"doi":5191},"10.3390\u002Frs3112420",{"id":28,"text":5193,"url":28,"identifiers":5194},"Adams, T (2011, January 16–20). Remotely Sensed Crown Structure as an Indicator of Wood Quality. A Comparison of Metrics from Aerial and Terrestrial Laser Scanning. Hobart, Australia.",{},{"id":28,"text":5196,"url":28,"identifiers":5197},"Raber, 2007, Impact of lidar nominal post-spacing on DEM accuracy and flood zone delineation, Photogramm. Eng. Remote Sensing, 7, 793, 10.14358\u002FPERS.73.7.793",{"doi":5198},"10.14358\u002FPERS.73.7.793",{"id":28,"text":5200,"url":28,"identifiers":5201},"Goulden, 2010, The forward propagation of integrated system component errors within airborne lidar data, Photogramm. Eng. Remote Sensing, 5, 589, 10.14358\u002FPERS.76.5.589",{"doi":5202},"10.14358\u002FPERS.76.5.589",{"id":28,"text":5204,"url":28,"identifiers":5205},"Yu, 2010, Comparison of area-based and individual tree-based methods for predicting plot-level forest attributes, Remote Sens, 2, 1481, 10.3390\u002Frs2061481",{"doi":5206},"10.3390\u002Frs2061481",{"id":5208,"createTime":5209,"updateTime":5210,"relativeEntities":5211,"slug":5212,"properties":5213,"entityType":966,"verifyStatus":26,"verifyTime":5227,"verifyNote":1144,"languages":5228,"translateLanguages":5229,"viewCount":32,"primaryUrl":5230,"fullTextUrl":28,"authors":5231,"publicationType":1001,"publisherRelationship":5329,"citationCount":5377,"citationInfo":5378,"publishDate":28,"publishYear":28,"citationAnalyzeStatus":878,"lastCitationAnalyze":28,"indexDatabases":5381,"openAccess":28,"references":5382,"isForceReanalyzing":1126},"c3435ad8-3c4c-46cd-9385-19b675f354b7","2024-10-12T07:28:57.717+00:00","2025-02-03T03:03:27.875+00:00",[],"Recent-Advances-of-Hyperspectral-Imaging-Technology-and-Applications-in-Agriculture",{"openalex":5214,"mag":5216,"abstract":5218,"title":5221,"keywords":5224,"doi":5225},{"VOID":5215},"W3075397214",{"VOID":5217},"3075397214",{"VI":5219,"EN":5220},"\u003Cjats:p>Cảm biến từ xa là một công cụ hữu ích để theo dõi những biến đổi không gian-thời gian của trạng thái hình thái và sinh lý của cây trồng, hỗ trợ cho các phương pháp trong nông nghiệp chính xác. So với hình ảnh đa phổ, hình ảnh siêu phổ là một kỹ thuật tiên tiến hơn, có khả năng thu được phản hồi quang phổ chi tiết của các tính năng mục tiêu. Do tính khả dụng hạn chế bên ngoài cộng đồng khoa học, hình ảnh siêu phổ vẫn chưa được sử dụng rộng rãi trong nông nghiệp chính xác. Trong những năm gần đây, đã có sự phát triển của các cảm biến siêu phổ hàng không nhỏ gọn và chi phí thấp (ví dụ: Headwall Micro-Hyperspec, Cubert UHD 185-Firefly), và các cảm biến siêu phổ không gian tiên tiến cũng đã được hoặc sẽ được ra mắt (ví dụ: PRISMA, DESIS, EnMAP, HyspIRI). Hình ảnh siêu phổ đang trở nên dễ tiếp cận hơn với các ứng dụng trong nông nghiệp. Trong khi đó, việc thu thập, xử lý và phân tích hình ảnh siêu phổ vẫn là một chủ đề nghiên cứu thách thức (ví dụ: khối lượng dữ liệu lớn, độ chiều cao dữ liệu cao và phân tích thông tin phức tạp). Do đó, việc tiến hành một đánh giá toàn diện và sâu sắc về công nghệ hình ảnh siêu phổ (ví dụ: các nền tảng và cảm biến khác nhau), phương pháp có sẵn để xử lý và phân tích thông tin siêu phổ, và những tiến bộ gần đây trong hình ảnh siêu phổ ứng dụng trong nông nghiệp là rất cần thiết. Các công trình trong 30 năm qua về công nghệ hình ảnh siêu phổ và ứng dụng trong nông nghiệp đã được xem xét. Các nền tảng hình ảnh và cảm biến, cùng với các phương pháp phân tích được sử dụng trong tài liệu, đã được thảo luận. Hiệu suất của hình ảnh siêu phổ cho các ứng dụng khác nhau (ví dụ: lập bản đồ các thuộc tính sinh lý học và hóa sinh của cây trồng, các đặc điểm đất, và phân loại cây trồng) cũng đã được đánh giá. Bài đánh giá này nhằm mục đích hỗ trợ các nhà nghiên cứu và thực hành nông nghiệp hiểu rõ hơn về những điểm mạnh và hạn chế của hình ảnh siêu phổ trong ứng dụng nông nghiệp, và thúc đẩy việc áp dụng công nghệ giá trị này. Các khuyến nghị cho các nghiên cứu hình ảnh siêu phổ trong tương lai cho nông nghiệp chính xác cũng được trình bày.\u003C\u002Fjats:p>","\u003Cjats:p>Remote sensing is a useful tool for monitoring spatio-temporal variations of crop morphological and physiological status and supporting practices in precision farming. In comparison with multispectral imaging, hyperspectral imaging is a more advanced technique that is capable of acquiring a detailed spectral response of target features. Due to limited accessibility outside of the scientific community, hyperspectral images have not been widely used in precision agriculture. In recent years, different mini-sized and low-cost airborne hyperspectral sensors (e.g., Headwall Micro-Hyperspec, Cubert UHD 185-Firefly) have been developed, and advanced spaceborne hyperspectral sensors have also been or will be launched (e.g., PRISMA, DESIS, EnMAP, HyspIRI). Hyperspectral imaging is becoming more widely available to agricultural applications. Meanwhile, the acquisition, processing, and analysis of hyperspectral imagery still remain a challenging research topic (e.g., large data volume, high data dimensionality, and complex information analysis). It is hence beneficial to conduct a thorough and in-depth review of the hyperspectral imaging technology (e.g., different platforms and sensors), methods available for processing and analyzing hyperspectral information, and recent advances of hyperspectral imaging in agricultural applications. Publications over the past 30 years in hyperspectral imaging technology and applications in agriculture were thus reviewed. The imaging platforms and sensors, together with analytic methods used in the literature, were discussed. Performances of hyperspectral imaging for different applications (e.g., crop biophysical and biochemical properties’ mapping, soil characteristics, and crop classification) were also evaluated. This review is intended to assist agricultural researchers and practitioners to better understand the strengths and limitations of hyperspectral imaging to agricultural applications and promote the adoption of this valuable technology. Recommendations for future hyperspectral imaging research for precision agriculture are also presented.\u003C\u002Fjats:p>",{"EN":5222,"VI":5223},"Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture","Những tiến bộ gần đây trong công nghệ hình ảnh siêu phổ và ứng dụng của nó trong nông nghiệp",{"VI":2731},{"VOID":5226},"10.3390\u002Frs12162659","2024-10-12T07:28:57.716+00:00",[31],[30],"https:\u002F\u002Fwww.mdpi.com\u002F2072-4292\u002F12\u002F16\u002F2659",[5232,5251,5276,5295,5312],{"id":5233,"sortIndex":32,"researcher":28,"roles":5234,"affiliations":5235,"properties":5244,"displayName":5248,"givenName":28,"familyName":28},"c2798b53-dbe5-4776-bf0e-ee863a5fb52d",[],[5236],{"id":5237,"sortIndex":32,"affiliation":5238,"properties":28},"dc9dde55-9e87-41cf-a662-b6df99cdb602",{"id":5237,"createTime":28,"updateTime":28,"relativeEntities":5239,"slug":28,"properties":5240,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":5243,"statistic":28},[],{"title":5241},{"VI":5242},"Department of Geography, Geomatics and Environment, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON, L5L 1C6, Canada",[],{"orcid":5245,"title":5247,"openalex":5249},{"VOID":5246},"https:\u002F\u002Forcid.org\u002F0000-0002-6259-1841",{"EN":5248},"Bing Lu",{"VOID":5250},"A5055319860",{"id":5252,"sortIndex":40,"researcher":28,"roles":5253,"affiliations":5254,"properties":5269,"displayName":5273,"givenName":28,"familyName":28},"5fae8e75-83a9-4dd2-ac3d-4ed8e148af6d",[],[5255,5261],{"id":5237,"sortIndex":32,"affiliation":5256,"properties":28},{"id":5237,"createTime":28,"updateTime":28,"relativeEntities":5257,"slug":28,"properties":5258,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":5260,"statistic":28},[],{"title":5259},{"VI":5242},[],{"id":5262,"sortIndex":40,"affiliation":5263,"properties":28},"91f8c082-fc6a-4151-8b4b-c950df723581",{"id":5262,"createTime":28,"updateTime":28,"relativeEntities":5264,"slug":28,"properties":5265,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":5268,"statistic":28},[],{"title":5266},{"VI":5267},"School of the Environment, University of Toronto, 33 Willcocks Street, Toronto, ON M5S 3E8, Canada",[],{"orcid":5270,"title":5272,"openalex":5274},{"VOID":5271},"https:\u002F\u002Forcid.org\u002F0000-0002-3712-9022",{"EN":5273},"Phuong D. 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2005, Variability of seasonal CASI image data products and potential application for management zone delineation for precision agriculture, Can. J. Remote Sens., 31, 400, 10.5589\u002Fm05-023",{"doi":5388},"10.5589\u002Fm05-023",{"id":28,"text":5390,"url":28,"identifiers":5391},"Jensen, J.R. (2006). Remote Sensing of the Environment: An Earth Resource Perspective, Prentice Hall.",{},{"id":28,"text":5393,"url":28,"identifiers":5394},"Sahoo, 2015, Hyperspectral remote sensing of agriculture, Curr. Sci., 108, 848",{},{"id":28,"text":5396,"url":28,"identifiers":5397},"Alonso, 1991, Comparing two methodologies for crop area estimation in Spain using Landsat TM images and ground-gathered data, Remote Sens. Environ., 35, 29, 10.1016\u002F0034-4257(91)90063-C",{"doi":5398},"10.1016\u002F0034-4257(91)90063-C",{"id":28,"text":5400,"url":28,"identifiers":5401},"McNairn, 2009, Integration of optical and Synthetic Aperture Radar (SAR) imagery for delivering operational annual crop inventories, ISPRS J. Photogramm., 64, 434, 10.1016\u002Fj.isprsjprs.2008.07.006",{"doi":5402},"10.1016\u002Fj.isprsjprs.2008.07.006",{"id":28,"text":5404,"url":28,"identifiers":5405},"Shoshany, 2013, Monitoring of agricultural soil degradation by remote-sensing methods: A review, Int. J. Remote Sens., 34, 6152, 10.1080\u002F01431161.2013.793872",{"doi":5406},"10.1080\u002F01431161.2013.793872",{"id":28,"text":5408,"url":28,"identifiers":5409},"Hunt, 2018, What good are unmanned aircraft systems for agricultural remote sensing and precision agriculture?, Int. J. Remote Sens., 39, 5345, 10.1080\u002F01431161.2017.1410300",{"doi":5410},"10.1080\u002F01431161.2017.1410300",{"id":28,"text":5412,"url":28,"identifiers":5413},"Thenkabail, 2003, Biophysical and yield information for precision farming from near-real-time and historical Landsat TM images, Int. J. 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Photogramm., 131, 121, 10.1016\u002Fj.isprsjprs.2017.07.015",{"doi":6264},"10.1016\u002Fj.isprsjprs.2017.07.015",{"id":6266,"createTime":6267,"updateTime":6268,"relativeEntities":6269,"slug":6270,"properties":6271,"entityType":966,"verifyStatus":26,"verifyTime":6267,"verifyNote":1144,"languages":6287,"translateLanguages":6288,"viewCount":32,"primaryUrl":6289,"fullTextUrl":28,"authors":6290,"publicationType":1001,"publisherRelationship":6425,"citationCount":6473,"citationInfo":6474,"publishDate":28,"publishYear":28,"citationAnalyzeStatus":6477,"lastCitationAnalyze":6478,"indexDatabases":6479,"openAccess":28,"references":6480,"isForceReanalyzing":1126},"1c275589-4048-4e8d-80a3-8b502673288c","2024-08-31T08:56:28.443+00:00","2025-12-11T02:55:36.824+00:00",[],"Evaluating-the-Ability-of-NPP-VIIRS-Nighttime-Light-Data-to-Estimate-the-Gross-Domestic-Product-and-the-Electric-Power-Consumption-of-China-at-Multiple-Scales-A-Comparison-with-DMSP-OLS-Data",{"mag":6272,"gsPaper":6274,"keywords":6276,"openalex":6277,"abstract":6279,"title":6282,"doi":6285},{"VOID":6273},"2074119918",{"VOID":6275},"[]",{"VI":2731},{"VOID":6278},"W2074119918",{"VI":6280,"EN":6281},"\u003Cjats:p>Dữ liệu ánh sáng ban đêm ghi lại ánh sáng nhân tạo trên bề mặt Trái Đất và có thể được sử dụng để ước lượng phân bố không gian của tổng sản phẩm quốc nội (GDP) và tiêu thụ điện năng (EPC). Vào đầu năm 2013, dữ liệu ánh sáng ban đêm toàn cầu NPP-VIIRS đầu tiên đã được nhóm Quan sát Trái Đất thuộc Trung tâm Dữ liệu Địa vật lý Quốc gia của Cục Khí quyển và Đại dương Quốc gia (NOAA\u002FNGDC) phát hành. Là dữ liệu thế hệ mới, dữ liệu NPP-VIIRS có độ phân giải không gian cao hơn và phạm vi phát hiện bức xạ rộng hơn so với dữ liệu ánh sáng ban đêm DMSP-OLS truyền thống. Nghiên cứu này nhằm điều tra tiềm năng của dữ liệu NPP-VIIRS trong việc mô hình hóa GDP và EPC ở nhiều quy mô thông qua một nghiên cứu điển hình tại Trung Quốc. Một loạt quy trình tiền xử lý được đề xuất để giảm độ nhiễu nền của dữ liệu gốc và tạo ra hình ảnh ánh sáng ban đêm NPP-VIIRS được hiệu chỉnh. Sau đó, hồi quy tuyến tính được sử dụng để phù hợp với mối tương quan giữa tổng ánh sáng ban đêm (TNL) (được trích xuất từ dữ liệu NPP-VIIRS đã hiệu chỉnh và dữ liệu DMSP-OLS) và GDP cũng như EPC (mà được lấy từ dữ liệu thống kê của quốc gia) ở các cấp độ tỉnh và huyện của đại lục Trung Quốc. Kết quả hồi quy tuyến tính cho thấy giá trị R2 của TNL từ NPP-VIIRS với GDP và EPC ở nhiều quy mô đều cao hơn so với dữ liệu DMSP-OLS. Nghiên cứu này cho thấy dữ liệu NPP-VIIRS có thể là một công cụ mạnh mẽ trong việc mô hình hóa các chỉ số kinh tế - xã hội; chẳng hạn như GDP và EPC.\u003C\u002Fjats:p>","\u003Cjats:p>The nighttime light data records artificial light on the Earth’s surface and can be used to estimate the spatial distribution of the gross domestic product (GDP) and the electric power consumption (EPC). In early 2013, the first global NPP-VIIRS nighttime light data were released by the Earth Observation Group of National Oceanic and Atmospheric Administration’s National Geophysical Data Center (NOAA\u002FNGDC). As new-generation data, NPP-VIIRS data have a higher spatial resolution and a wider radiometric detection range than the traditional DMSP-OLS nighttime light data. This study aims to investigate the potential of NPP-VIIRS data in modeling GDP and EPC at multiple scales through a case study of China. A series of preprocessing procedures are proposed to reduce the background noise of original data and to generate corrected NPP-VIIRS nighttime light images. Subsequently, linear regression is used to fit the correlation between the total nighttime light (TNL) (which is extracted from corrected NPP-VIIRS data and DMSP-OLS data) and the GDP and EPC (which is from the country’s statistical data) at provincial- and prefectural-level divisions of mainland China. The result of the linear regression shows that R2 values of TNL from NPP-VIIRS with GDP and EPC at multiple scales are all higher than those from DMSP-OLS data. This study reveals that the NPP-VIIRS data can be a powerful tool for modeling socioeconomic indicators; such as GDP and EPC.\u003C\u002Fjats:p>",{"EN":6283,"VI":6284},"Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data","Đánh giá khả năng của dữ liệu ánh sáng ban đêm NPP-VIIRS trong việc ước lượng Tổng sản phẩm quốc nội và Tiêu thụ điện năng của Trung Quốc ở nhiều quy mô: So sánh với dữ liệu 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Remote Sens, 51, 5225, 10.1109\u002FTGRS.2013.2272560",{"doi":6688},"10.1109\u002FTGRS.2013.2272560",{"id":6690,"createTime":6691,"updateTime":6692,"relativeEntities":6693,"slug":6694,"properties":6695,"entityType":966,"verifyStatus":26,"verifyTime":6691,"verifyNote":1144,"languages":6709,"translateLanguages":6710,"viewCount":32,"primaryUrl":6711,"fullTextUrl":28,"authors":6712,"publicationType":1001,"publisherRelationship":6774,"citationCount":6821,"citationInfo":6822,"publishDate":28,"publishYear":28,"citationAnalyzeStatus":878,"lastCitationAnalyze":28,"indexDatabases":6824,"openAccess":28,"references":6825,"isForceReanalyzing":1126},"96bcab8f-8ad1-4456-8a10-7d0b94ea0a52","2024-10-15T07:20:26.376+00:00","2025-02-03T03:05:21.819+00:00",[],"Ground-Filtering-Algorithms-for-Airborne-LiDAR-Data-A-Review-of-Critical-Issues",{"openalex":6696,"mag":6698,"abstract":6700,"title":6703,"keywords":6706,"doi":6707},{"VOID":6697},"W2014091167",{"VOID":6699},"2014091167",{"VI":6701,"EN":6702},"\u003Cjats:p>Bài viết này xem xét các thuật toán lọc mặt đất LiDAR được sử dụng trong quá trình tạo các Mô Hình Độ Cao Kỹ Thuật Số. Chúng tôi thảo luận về các vấn đề quan trọng trong việc phát triển và ứng dụng các thuật toán lọc mặt đất LiDAR, bao gồm các quy trình lọc cho các loại đặc trưng khác nhau, và tiêu chí chọn lựa địa điểm nghiên cứu, đánh giá độ chính xác và phân loại thuật toán. Đánh giá này nhấn mạnh ba loại đặc trưng mà các thuật toán lọc mặt đất hiện tại chưa đạt yêu cầu tối ưu, và có thể được cải thiện trong các nghiên cứu tương lai: các bề mặt có địa hình gồ ghề hoặc độ dốc không liên tục, các khu rừng dày mà tia laser không thể xuyên qua, và các vùng có thực vật thấp thường bị bỏ qua bởi các bộ lọc mặt đất.\u003C\u002Fjats:p>","\u003Cjats:p>This paper reviews LiDAR ground filtering algorithms used in the process of creating Digital Elevation Models. We discuss critical issues for the development and application of LiDAR ground filtering algorithms, including filtering procedures for different feature types, and criteria for study site selection, accuracy assessment, and algorithm classification. This review highlights three feature types for which current ground filtering algorithms are suboptimal, and which can be improved upon in future studies: surfaces with rough terrain or discontinuous slope, dense forest areas that laser beams cannot penetrate, and regions with low vegetation that is often ignored by ground filters.\u003C\u002Fjats:p>",{"EN":6704,"VI":6705},"Ground Filtering Algorithms for Airborne LiDAR Data: A Review of Critical Issues","Các Thuật Toán Lọc Mặt Đất cho Dữ Liệu LiDAR Trên Không: Một Đánh Giá Các Vấn Đề Quan 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ISPRS Working Group VIII\u002F2 ‘Laser-Scanners for Forest and Landscape Assessment’, Freiburg, Germany.",{},{"id":28,"text":7206,"url":28,"identifiers":7207},"Torres, 2006, Accuracy assessment of LiDAR saltmarsh topographic data using RTK GPS, Photogramm. Eng. Remote Sens., 72, 961, 10.14358\u002FPERS.72.8.961",{"doi":7208},"10.14358\u002FPERS.72.8.961",{"id":7210,"createTime":7211,"updateTime":7212,"relativeEntities":7213,"slug":7214,"properties":7215,"entityType":966,"verifyStatus":26,"verifyTime":7229,"verifyNote":1144,"languages":7230,"translateLanguages":7231,"viewCount":32,"primaryUrl":7232,"fullTextUrl":28,"authors":7233,"publicationType":1001,"publisherRelationship":7287,"citationCount":7335,"citationInfo":7336,"publishDate":28,"publishYear":28,"citationAnalyzeStatus":878,"lastCitationAnalyze":28,"indexDatabases":7338,"openAccess":28,"references":7339,"isForceReanalyzing":1126},"10cbcfc5-06be-467a-8cac-11a8d743122e","2024-09-25T13:58:25.792+00:00","2025-02-03T03:06:20.281+00:00",[],"UAV-Remote-Sensing-for-Urban-Vegetation-Mapping-Using-Random-Forest-and-Texture-Analysis",{"openalex":7216,"mag":7218,"abstract":7220,"title":7223,"keywords":7226,"doi":7227},{"VOID":7217},"W2066416082",{"VOID":7219},"2066416082",{"VI":7221,"EN":7222},"\u003Cjats:p>Cảm biến từ xa không người lái (UAV) có tiềm năng lớn trong việc lập bản đồ thực vật ở các cảnh quan đô thị phức tạp nhờ vào hình ảnh phân giải cực cao được thu thập ở độ cao thấp. Do hạn chế về khả năng tải trọng, các máy ảnh kỹ thuật số sẵn có thường được sử dụng trên UAV cỡ vừa và nhỏ. Hạn chế về độ phân giải phổ thấp trong các máy ảnh kỹ thuật số để lập bản đồ thực vật có thể được giảm thiểu bằng cách kết hợp các đặc trưng kết cấu và các bộ phân loại mạnh mẽ. Rừng Ngẫu Nhiên đã được sử dụng rộng rãi trong các ứng dụng cảm biến từ xa vệ tinh, nhưng việc sử dụng nó trong phân loại hình ảnh UAV chưa được tài liệu ghi chép đầy đủ. Mục tiêu của bài báo này là đề xuất một phương pháp lai sử dụng Rừng Ngẫu Nhiên và phân tích kết cấu để phân biệt chính xác các lớp đất che phủ của các khu vực thực vật đô thị, và phân tích cách độ chính xác phân loại thay đổi với kích thước cửa sổ kết cấu. Sáu phép đo kết cấu bậc hai có tương quan thấp nhất đã được tính toán ở chín kích thước cửa sổ khác nhau và được thêm vào các hình ảnh RGB (Đỏ-Xanh lá-Xanh dương) gốc như dữ liệu bổ sung. Một bộ phân loại Rừng Ngẫu Nhiên bao gồm 200 cây quyết định đã được sử dụng để phân loại trong không gian tính năng phổ-kết cấu. Kết quả cho thấy như sau: (1) Rừng Ngẫu Nhiên vượt trội hơn bộ phân loại xác suất cực đại truyền thống và cho thấy hiệu suất tương tự như phân tích hình ảnh dựa trên đối tượng trong phân loại thực vật đô thị; (2) việc đưa vào các đặc trưng kết cấu đã cải thiện đáng kể độ chính xác phân loại; (3) độ chính xác phân loại có mối quan hệ hình chữ U đảo ngược với kích thước cửa sổ kết cấu. Các kết quả chứng minh rằng UAV cung cấp một nền tảng hiệu quả và lý tưởng cho việc lập bản đồ thực vật đô thị. Phương pháp lai được đề xuất trong bài báo này cho thấy hiệu suất tốt trong việc phân biệt bản đồ thực vật đô thị. Những nhược điểm của các máy ảnh kỹ thuật số sẵn có có thể được giảm thiểu bằng cách áp dụng Rừng Ngẫu Nhiên và phân tích kết cấu cùng một lúc.\u003C\u002Fjats:p>","\u003Cjats:p>Unmanned aerial vehicle (UAV) remote sensing has great potential for vegetation mapping in complex urban landscapes due to the ultra-high resolution imagery acquired at low altitudes. Because of payload capacity restrictions, off-the-shelf digital cameras are widely used on medium and small sized UAVs. The limitation of low spectral resolution in digital cameras for vegetation mapping can be reduced by incorporating texture features and robust classifiers. Random Forest has been widely used in satellite remote sensing applications, but its usage in UAV image classification has not been well documented. The objectives of this paper were to propose a hybrid method using Random Forest and texture analysis to accurately differentiate land covers of urban vegetated areas, and analyze how classification accuracy changes with texture window size. Six least correlated second-order texture measures were calculated at nine different window sizes and added to original Red-Green-Blue (RGB) images as ancillary data. A Random Forest classifier consisting of 200 decision trees was used for classification in the spectral-textural feature space. Results indicated the following: (1) Random Forest outperformed traditional Maximum Likelihood classifier and showed similar performance to object-based image analysis in urban vegetation classification; (2) the inclusion of texture features improved classification accuracy significantly; (3) classification accuracy followed an inverted U relationship with texture window size. The results demonstrate that UAV provides an efficient and ideal platform for urban vegetation mapping. The hybrid method proposed in this paper shows good performance in differentiating urban vegetation mapping. The drawbacks of off-the-shelf digital cameras can be reduced by adopting Random Forest and texture analysis at the same time.\u003C\u002Fjats:p>",{"EN":7224,"VI":7225},"UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis","Cảm Biến Từ Xa UAV Để Phân Địa Thực Vật Đô Thị Sử Dụng Phương Pháp Rừng Ngẫu Nhiên và Phân Tích Kết Cấu",{"VI":2731},{"VOID":7228},"10.3390\u002Frs70101074","2024-09-25T13:58:25.791+00:00",[31],[30],"https:\u002F\u002Fwww.mdpi.com\u002F2072-4292\u002F7\u002F1\u002F1074",[7234,7253,7270],{"id":7235,"sortIndex":32,"researcher":28,"roles":7236,"affiliations":7237,"properties":7246,"displayName":7250,"givenName":28,"familyName":28},"1e36b9af-a74a-4f6d-9963-52f5ddcd4721",[],[7238],{"id":7239,"sortIndex":32,"affiliation":7240,"properties":28},"7e9ad494-53e6-4378-9959-bc35c03e554d",{"id":7239,"createTime":28,"updateTime":28,"relativeEntities":7241,"slug":28,"properties":7242,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":7245,"statistic":28},[],{"title":7243},{"EN":7244},"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences, No.20, Datun Road, Chaoyang District, Beijing 100101, China",[],{"orcid":7247,"title":7249,"openalex":7251},{"VOID":7248},"https:\u002F\u002Forcid.org\u002F0000-0002-0569-4131",{"EN":7250},"Quanlong Feng",{"VOID":7252},"A5078340301",{"id":7254,"sortIndex":40,"researcher":28,"roles":7255,"affiliations":7256,"properties":7263,"displayName":7267,"givenName":28,"familyName":28},"31e1d440-2ac8-4a90-8510-a3c14d592153",[],[7257],{"id":7239,"sortIndex":32,"affiliation":7258,"properties":28},{"id":7239,"createTime":28,"updateTime":28,"relativeEntities":7259,"slug":28,"properties":7260,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":7262,"statistic":28},[],{"title":7261},{"EN":7244},[],{"orcid":7264,"title":7266,"openalex":7268},{"VOID":7265},"https:\u002F\u002Forcid.org\u002F0000-0001-5836-5641",{"EN":7267},"Jiantao 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Available online:http:\u002F\u002Fwww.exelisvis.com\u002FProductsServices\u002FENVIProducts.aspx.",{},{"id":28,"text":7495,"url":28,"identifiers":7496},"Feature Extraction with Example-Based Classification Tutorial. Available online:http:\u002F\u002Fwww.exelisvis.com\u002Fdocs\u002FFXExampleBasedTutorial.html.",{}]