Abstract
Due to many factors in the physical properties of the ground surface, the corresponding interferometric coherence values change dynamically over time. Among these factors, the roles of the vegetation and its temporal variation have not yet been revealed so far. In this paper, synthetic aperture radar (Sentinel-1) data and optical remote sensing (Landsat TM) images over four whole seasons are employed to reveal the relationship between the interferometric coherence and the normalized difference vegetation index (NDVI) at five sites that have ground deformation due to mining in Henan province, China. The result showed: (1) As for the village area with few vegetation cover, the related coherence values are significantly higher than that in the farm land area with high densities of vegetation in the spring and summer, which indicates that the subsidence by mining in few vegetation cover area is easier to be monitored; (2) Linear regression coefficients ({{bf{R}}}^{{bf{2}}}) between the interfereometric coherence values and the NDVI values is 0.62, which indicate the interferometric coherence values and the NDVI values change reversely in both farm land and village areas over the year. It suggests months between November and March with lower NDVI value are more suitable for deformation detecting. Therefore, the interfereometric coherence values can be used to detect the density of vegetation, while NDVI values can be reference for elucidating when the traditional differential interferometric synthetic aperture radar (DInSAR) could be effectively used.
Highlights
The coherence is taken as the main parameter in target classification[10,11], forest change detection[12,13,14], and lake study[15,16]
The interferogram and interferometric coherence of a representative set of Sentinel-1A satellite images were computed via temporal evolution charts from June 2015 to May 2016, and multi-temporal normalized difference vegetation index (NDVI) were obtained from a time series Landsat 8 satellite images from July 2015 to May 2016
Four specific areas of farm land and one village are selected for investigation because they have been affected by mine deformation
Summary
The coherence is taken as the main parameter in target classification[10,11], forest change detection[12,13,14], and lake study[15,16]. The extent of temporal changes in the scatterers is a key factor affecting interferometric coherence[11,17]. Vegetation has a larger impact on SAR image coherence. In the seasons when vegetation is growing, the temporal decorrelation phenomena is complicated[13,18]. The objective of this work is to analyze the temporal changes of the coherence in SAR images and NDVI variation of optical remote sensing images within one year, to reveals the relationship between SAR image coherence and the vegetation density. The correlation analysis was performed to quantify the relationship between the multi-temporal interferometric coherence and NDVI throughout the year in mine deformation area
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