Abstract
In this work, we focused on the ocean-reclaimed lands of the Shanghai coastal region and we evidenced how, over these areas, the interferometric synthetic aperture radar (InSAR) coherence maps exhibit peculiar behavior. In particular, by analyzing a sequence of Sentinel-1 SAR InSAR coherence maps, we found a significant coherence loss over time in correspondence to the ocean-reclaimed platforms that are substantially different from the coherence loss experienced in naturally-formed regions with the same type of land cover. We have verified whether this is due to the engineering geological conditions or the soil consolidation subsidence in ocean-reclaimed region. In this work, we combine the information coming from InSAR coherence maps and the retrieved temporal decorrelation model with that obtained by using optical Sentinel-2 data, and we performed land cover classification analyses in the zone of the Pudong International Airport. To estimate the accuracy of utilizing InSAR coherence information for land cover classification, in particular, we have analyzed what causes the difference of the InSAR coherence loss with the same type of land cover. The presented results show that the coherence models can be useful to distinguish roads and buildings, thus enhancing the accuracy of land cover classification compared with that allowable by using only Sentinel-2 data. In particular, the accuracy of classification increases from 75% to 86%.
Highlights
In recent years, global change has become a research hotspot
By analyzing a sequence of Sentinel-1 Synthetic Aperture Radar (SAR) interferometric synthetic aperture radar (InSAR) coherence maps, we found a significant coherence loss over time in correspondence to the ocean-reclaimed platforms that are substantially different from the coherence loss experienced in naturally-formed regions with the same type of land cover
By analyzing a sequence of Sentinel-1 SAR coherence maps, we found a significant coherence loss over time in the reclaimed platforms that is substantially different from the coherence loss experienced in naturally-formed regions with the same type of land cover
Summary
Global change has become a research hotspot. The development and utilization of land by human beings and the study of land use and land cover (LULC) changes for global environment analyses have been deserved increasing interest. LULC research has great significance in analyzing the effects of human activities on the ecological environment and the feedback of nature [1,2,3]. Remote sensing technology has been widely used in the monitoring of LULC, because of its advantages [4,5,6,7]. Multispectral remote sensing is widely used because of its high spatial resolution and rich spectral information [7,8,9]. In some cloudy or rainy weather conditions, Sensors 2018, 18, 2939; doi:10.3390/s18092939 www.mdpi.com/journal/sensors
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