TITLE:
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
AUTHORS:
Nguyen Thi Quynh Trang, Le Quang Toan, Tong Thi Huyen Ai, Nguyen Vu Giang, Pham Viet Hoa
KEYWORDS:
Object-Based Classification, Pixel-Based Classification, VNREDSat-1, Mangrove Forest, Ca Mau
JOURNAL NAME:
Advances in Remote Sensing,
Vol.5 No.4,
December
2,
2016
ABSTRACT: 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.