Remote Sensing Application in Forest Monitoring: An Object Based Approach (Published)
Object-based methods for image analysis have the advantage of incorporating spatial context and mutual relationships between objects. Few studies have explored the application of object-based approaches to forest classification. This paper introduced an object based method to SPOT5 image to map the land cover in Yen Nhan commune in 2015. This approach applied multi-resolution segmentation algorithm of eCognition Developer and an object based classification framework. In addition, forest maps from 2000 to 2015 were used to analyze the change in forest cover in each 5 years period. The object based method clearly discriminated the different land cover classes in Yen Nhan. The overall kappa value was 0.73 was achieved. The estimation of forest area was 89.05 % of forest cover in 2015. By overlaying achieve forest maps of 2000, 2005, 2010 and the classified map of 2015 shows vegetation changed during 2000-2015 remarkably.
Keywords: : GIS, Change Detection, Forest Classification, Remote Sensing, SPOT 5 Image