Monitoring Urban construction activities during covid using fusion of SAR coherence and Sentinel-2 data
Remote sensing data such as aerial photo interpretation, satellite imagery or other geospatial data, has proven to be a useful and frequent application in monitoring and mapping urban areas. In the past, satellite images in particular multispectral and SAR (Synthetic Aperture Radar) satellite remote sensing data have been effectively used for mapping and monitoring urban land use. Multispectral data has been used for classifying urban land use classes in terms of various categories. SAR sensors have been exploited for urban target mapping and change detection. In this project, we intend to use SAR characteristics like temporal correlation in conjunction with multispectral data for identifying new construction in the city area. Data fusion is the process of combining multiple image layers into a single composite image.
Image fusion is a tool to combine multisource imagery using advanced image processing techniques. It aims at the integration of disparate and complementary data to enhance the information apparent in the images as well as to increase the reliability of the interpretation. This leads to more accurate data and increased utility. It is also stated that fused data provides for robust operational performance, i.e., increased confidence, reduced ambiguity, improved reliability and improved classification
