Title :
Object-oriented classification of rubber plantations from Landsat satellite imagery
Author :
ShengPei Dai ; Hailiang Li ; Hongxia Luo ; MaoFen Li ; JiHua Fang ; Lingling Wang ; JianHua Cao ; Wei Luo
Author_Institution :
Inst. of Sci. & Tech. Inf., Chinese Acad. of Tropical Agric. Sci., Danzhou, China
Abstract :
Due to increasing global demand for natural rubber products, rubber (Hevea brasiliensis) plantation expansion has occurred in many regions where it was originally considered unsuitable. However, accurate maps of rubber plantations are not available, which substantially constrain our understanding of the environmental and socio-economic impacts of rubber plantation expansion. In this study, the rubber plantations was accurate mapped from Landsat satellite imagery based on object-oriented classification method in Yangjiang State Farm in Hainan Island in 2010. The results show that: (1) The rubber plantation area in Yangjiang State Farm was estimated at 5866 hm2 in 2010, which was slightly higher than the stand inventory data (5190 hm2) in 2009. (2) The resulting rubber plantation map has a high accuracy according to the confusion matrix by using the ground truth ROIs. The overall accuracy is 90% and the kappa coefficient is 0.9. It showed that object-oriented classification method is suitable for mapping rubber plantation from Landsat satellite imagery.
Keywords :
artificial satellites; crops; geophysical image processing; image classification; object-oriented methods; rubber; rubber products; Hainan Island; Hevea brasiliensis; Landsat satellite imagery; ROI; Yangjiang State Farm; confusion matrix; environmental impacts; ground truth; kappa coefficient; natural rubber products; object-oriented classification method; rubber plantation expansion; rubber plantation map; socioeconomic impacts; Accuracy; Agriculture; Earth; Image segmentation; Remote sensing; Rubber; Satellites; Hainan Island; Landsat Satellite Imagery; Object-oriented Classification; Rubber (Hevea brasiliensis) plantation; Yangjiang State Farm;
Conference_Titel :
Agro-geoinformatics (Agro-geoinformatics 2014), Third International Conference on
Conference_Location :
Beijing
DOI :
10.1109/Agro-Geoinformatics.2014.6910635