Accurate segmentation of mining subsidence areas is crucial for monitoring illegal mining activities, mine remediation, and land use planning. Addressing the segmentation issue of mining subsidence in differential interferometric phase maps, we establish a differential interferometric phase map dataset specific to mining subsidence and propose an improved algorithm EMAGUNet++ based on the UNet architecture. By integrating attention gate and efficient multiscale attention mechanisms, attention weights are focused on relevant local features to enhance segmentation accuracy. Experimental results demonstrate that EMAGUNet++ achieves an intersection over the union index of 0.756 for mining subsidence segmentation, outperforming other classic segmentation models by 1.8% to 9.2%, validating the effectiveness of the model improvements. The improved model accurately segmented mining subsidence persisting over 6 years near Fugu County, and the segmentation polygon achieved an accuracy of 89.3%, showcasing excellent performance.
In order to monitor the surface deformation of Shuping landslide in the Yangtze River Three Gorges area, the method of
differential SAR interferometry (DInSAR) using corner reflectors (CR) was applied. 12 CR, including 10 pyramidal
corner reflectors (PCR) and 2 asymmetrical cubic corner reflectors (ACCR), were designed, made, and deployed on
Shuping landslide. Based on the numerical test and the preliminary analyses of 5 ENVISAT ASAR images, we
concluded that: 1) ACCR can provide strong response signal even without the best SAR look angle and is especially fit
for the multi-angle applications of DInSAR; 2) given a simple phase model, the least square (LS) method can be used to
analyze the CR's differential phase and get the accumulative deformation value.
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