摘要
本文以江苏高邮为研究区,采用STARFM和STAVFM两种算法,以及HJ星和MODIS遥感数据,分别进行时空融合。通过对比分析,STARFM算法有更高的融合精度。进而通过STARFM时空融合技术,生成研究区时间序列影像,进行水稻种植面积提取,并利用野外采样点进行精度验证,结果显示提取精度较高,总体提取精度为83%。
This paper takes Jiangsu Gaoyou as the research area and uses STARFM and STAVFM algorithms to carry out the spatial and temporal fusion experiment with HJ and MODIS data. Detected from the comparison, STARFM algorithm has higher fusion accuracy. It is applied to generate the time series image of the study area and extract the rice planting area. Verified with field sampling points, the total extraction accuracy reaches to 83%.
作者
毕苗苗
庄齐枫
王浩
BI Miaomiao;ZHUANG Qifeng;WANG Hao(College of Geomatics Science and Technology,Nanjing Tech University,Nanjing 211816,China;Chinese Academy of Surveying and Mapping/Institute of Photogrammetry and Remote Sensing,Beijing 100073,China)
出处
《江西测绘》
2018年第4期14-18,共5页
JIANGXI CEHUI
基金
基于农田水分盈亏的渍害遥感监测方法研究
江苏省高等学校自然科学研究面上项目(17KJB420002)
