Spatial consistency analysis of surface water extracted from multi-source remote sensing data in lake area
To address the potential spatial differences in the extraction results of surface water from multi-source remote sensing data in the same lake area,a spatial consistency measurement index was proposed in this paper.Taking the East Dongting Lake area as an example,surface water was extracted from images of Landsat and Sentinel satellites with random forest models.The extraction accuracy was compared and spatial consistency between extraction results was measured.The relationship between spatial consistency and geographical factors was explored using correlation and importance analysis methods.The results indicated that the land surface reflectance,land surface temperature,and vegetation coverage could indicate the spatial consistency and difference in the extraction results of surface water from multi-source remote sensing data to some extent(correlation coefficient:-0.772～0.428,importance:0.106～0.697),but there were differences between periods.Therefore,in the process of monitoring spatial-temporal changes in surface water of lake area based on multi-source remote sensing data fusion or filling,this spatial consistency difference and its temporal scenario characteristics should be taken into account and the related geographical factors may improve the monitoring reliability.
lake water areaspatial differencerandom forestrelationship featuresgeographic factors
NETL
NSTL
万方数据
