Forest/Non-forest Mapping Using ENVISAT ASAR Data in Northeast China
large scale forest mapping and change detection plays a significant role in the study of global change, particularly in the research of carbon source and sink. This paper presents results from forest/non-forest classification using ENVISAT-ASAR data. Both pixel-based and object-based classification method were developed for ASAR HH/HV images acquired on a single date. For the object-based classification, two different strategies were proposed: rule-set and threshold-ratio. Using as reference a land use map derived from Landsat TM images acquired in 2000, the accuracy of the forest/non-forest map from ASAR AP data has been found to meet the requirements of mapping the Northeast Chinese forests at large scale.
SAR forest classification segmentation object-based
Yanping Huang Feilong Ling Bo Wu lina Bai Xin Tian
Key Laboratory of Spatial Data Mining &Information Sharing of Ministry of Education,Fuzhou Universit Institute of Forest Resources Information Techniques, Chinese Academy of Forestry, Beijing, 100091,C
国际会议
福州
英文
381-385
2011-06-29（万方平台首次上网日期，不代表论文的发表时间）