摘要
利用1996年、2005年两个时相的Landsat-5TM数据及其冰雪指数、水体指数等,结合同时期ERS-1/2、ENVISAT ASAR的合成孔径雷达(Synthetic Aperture Radar,SAR)数据的强度信息、相干信息等特征参数引入支持向量机(Support Vector Machine,SVM)分类器,针对西藏年楚河流域的冰川信息进行了分类提取。结果表明:光学与SAR影像特征组合经过优选后,可有效区分冰川和水体,两个时相的总体识别精度分别为84%和85%。在两期分类专题图结果基础上,进一步对冰川边界、面积的变化情况进行了分析研究,结果发现,由于气候变暖的原因,1996至2005年楚河流域的冰川面积共减少了154.7km^2。
This study extracted the local glacier information over the Nianchu river basin in the Tibet in 1996 and 2005 by using ice index,snow index and water index of Landsat TM-5 multi-spectral images,and Synthetic Aperture Radar (SAR)intensity and coherence information of ERS-1/2 and Envisat ASAR.The optimized features were determined by their classification accuracies based on Support Vector Machine (SVM)classifier.The result showed that the composition of multi-spectral and SAR features could effec- tively discriminate the water and ice from other types,with overall accuracies of 84% and 85% in 1996 and 2005, respectively.Based on the thematic information of these two years ,the changes of the local glacial are- a and boundary were detected.The result showed that the glacial area of the Nianchu river basin was re- duced by 154.7 km2 ,which mainly caused by the climate warming.
出处
《遥感技术与应用》
CSCD
北大核心
2017年第6期1126-1131,共6页
Remote Sensing Technology and Application
基金
2014年西藏自治区第一批重点科技项目
国家自然地区科学基金项目"基于MODISFY-3VIRR遥感数据的藏北地区干旱遥感监测方法研究"(41465006)
西藏自治区气象局高原遥感应用技术创新团队基金资助