Phương pháp cây quyết định cho phân loại dữ liệu vệ tinh được thu thập từ xa sử dụng hỗ trợ mã nguồn mở

Springer Science and Business Media LLC - Tập 122 - Trang 1237-1247 - 2013
RICHA SHARMA1, ANIRUDDHA GHOSH1, P K JOSHI1
1Department of Natural Resources, TERI University, New Delhi, India

Tóm tắt

Trong nghiên cứu này, một nỗ lực đã được thực hiện để phát triển thuật toán phân loại cây quyết định (DTC) cho việc phân loại dữ liệu vệ tinh được thu thập từ xa (Landsat TM) sử dụng hỗ trợ mã nguồn mở. Cây quyết định được xây dựng bằng cách phân chia đệ quy phân phối quang phổ của tập dữ liệu huấn luyện sử dụng WEKA, phần mềm khai thác dữ liệu mã nguồn mở. Ảnh đã phân loại được so sánh với ảnh được phân loại bằng cách sử dụng thuật toán phân cụm ISODATA cổ điển và Thuật toán Phân loại xác suất tối đa (MLC). Kết quả phân loại dựa trên phương pháp DTC cung cấp hình ảnh trực quan hơn so với kết quả được tạo ra bởi phân cụm ISODATA hoặc bởi các thuật toán MLC. Độ chính xác tổng thể được tìm thấy là 90% (kappa = 0.88) sử dụng DTC, 76.67% (kappa = 0.72) sử dụng Maximum Likelihood và 57.5% (kappa = 0.49) sử dụng phương pháp phân cụm ISODATA. Dựa trên độ chính xác tổng thể và thống kê kappa, DTC được phát hiện là phương pháp phân loại ưa thích hơn so với các phương pháp khác.

Từ khóa


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