Author(s)

Nguyen Thi Quynh Trang¹, Le Quang Toan¹, Tong Thi Huyen Ai¹, Nguyen Vu Giang¹, Pham Viet Hoa²

¹Space Technology Institute, Vietnam Academy of Science and Technology, Hanoi, Vietnam.
²Ho Chi Minh Institute of Resource Geography, Vietnam Academy of Science and Technology, Ho Chi Minh City, Vietnam.

Many researches have been performed comparing object-based classification (OBC) and pixel-based classification (PBC), particularly in classifying high-resolution satellite images. VNREDSat-1 is the first optical remote sensing satellite of Vietnam with resolution of 2.5 m (Panchromatic) and 10 m (Multispectral). The objective of this research is to compare two classification approaches using VNREDSat-1 image for mapping mangrove forest in Vien An Dong commune, Ngoc Hien district, Ca Mau province. ISODATA algorithm (in PBC method) and membership function classifier (in OBC method) were chosen to classify the same image. The results show that the overall accuracies of OBC and PBC are 73% and 62.16% respectively, and OBC solved the “salt and pepper” which is the main issue of PBC as well. Therefore, OBC is supposed to be the better approach to classify VNREDSat-1 for mapping mangrove forest in Ngoc Hien commune.

Object-Based Classification, Pixel-Based Classification, VNREDSat-1, Mangrove Forest, Ca Mau

Quynh Trang, N. , Toan, L. , Huyen Ai, T. , Vu Giang, N. and Viet Hoa, P. (2016) Object-Based vs. Pixel-Based Classification of Mangrove Forest Mapping in Vien An Dong Commune, Ngoc Hien District, Ca Mau Province Using VNREDSat-1 Images. Advances in Remote Sensing, 5, 284-295. doi: 10.4236/ars.2016.54022.