ABSTRACT:Understanding the law of mining surface dynamic subsidence plays an important role in protecting the villages and other infrastructures against subsidence damage and disturbance. Unfortunately, the existed methods are mostly based on a few sparse leveling measurements, the accuracy and reliability of which are degraded when the feature points of the leveling measurements are lost in the processing of subsidence evolution. This paper presents a method to analysing the law of mining surface dynamic subsidence by fusing interferometric synthetic aperture radar (InSAR) and leveling measurements. By comparing the fitted results obtained by fusing InSAR/leveling and those only by independent leveling, it is shown that the InSAR/levelling fusion not only can make up the deficiency when the leveling measurements lost the feature points of dynamic subsidence, but also can improve the accuracy and reliability of results.
ABSTRACT:The measurement of soil total nitrogen (TN) by hyperspectral remote sensing provides an important tool for soil restoration programs in areas with subsided land caused by the extraction of natural resources. This study used the local correlation maximization-complementary superiority method (LCMCS) to establish TN prediction models by considering the relationship between spectral reflectance and TN based on spectral reflectance curves of soil samples collected from subsided land determined by synthetic aperture radar interferometry (InSAR) technology. Based on the 1655 selected effective bands of the optimal spectrum (OSP) of the first derivate differential of reciprocal logarithm ([log{1/R}]'), (correlation coefficients, P < 0.01), the optimal model of LCMCS method was obtained to determine the final model, which produced lower prediction errors
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