Phân tích phân loại lớp đất che phủ của đảo núi lửa trong cung Aleutian sử dụng mạng nơ-ron nhân tạo (ANN) và máy vector hỗ trợ (SVM) từ ảnh Landsat

Springer Science and Business Media LLC - Tập 22 - Trang 653-665 - 2018
Prima Riza Kadavi1, Chang-Wook Lee1
1Division of Science Education, Kangwon National University, Chuncheon-si, Republic of Korea

Tóm tắt

Việc lập bản đồ lớp đất che phủ (LC) là một chủ đề nghiên cứu quan trọng với nhiều ứng dụng trong viễn thám. Đặc biệt, đối với các khu vực núi lửa nơi mà việc tiếp cận trực tiếp rất khó khăn, dữ liệu viễn thám là cần thiết để lập bản đồ LC. Khu vực núi lửa là các mục tiêu hấp dẫn cho việc lập bản đồ LC vì bất kỳ sự bùng phát nào của núi lửa cũng phải được giám sát. Khi tạo ra các bản đồ LC, việc giảm thiểu sai số là rất quan trọng vì những sai số này ảnh hưởng đến các phân tích sử dụng những bản đồ này. Ở đây, chúng tôi đã phân tích dữ liệu đa phổ từ núi Kanaga, núi Fourpeaked, núi Pavlof và núi Augustine bằng cách sử dụng hai bộ phân loại khác nhau, mạng nơ-ron nhân tạo (ANN) và máy vector hỗ trợ (SVM). Để đạt được điều này, chúng tôi đã sử dụng hình ảnh Landsat 8, bao gồm bốn lớp LC: đá lộ (trầm tích pyroclastic, đá núi lửa, cát, v.v.), thực vật, vùng nước và tuyết. Chúng tôi phát hiện ra rằng SVM chính xác hơn ANN. Đối với núi Kanaga, SVM mang lại độ chính xác phân loại tốt nhất (98.08%), tốt hơn 9.14% so với ANN (88.94%); đối với các núi lửa khác, độ chính xác của hai phương pháp không khác biệt đáng kể. Tổng thể, cả hai bộ phân loại đều phân biệt chính xác các sản phẩm của sự bùng phát núi lửa (đá lộ) với các lớp LC khác. Do đó, cả ANN và SVM đều có thể được sử dụng cho phân loại LC.

Từ khóa

#Lớp đất che phủ #viễn thám #mạng nơ-ron nhân tạo #máy vector hỗ trợ #đảo núi lửa #ảnh Landsat

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