Abstract
Earth observation satellites (EOS) have been continuously observing and monitoring the globe and its physical, chemical, and biological characteristics since the late 1950s. EOS has been providing an enormous quantity of spatial data, and it is predicted that the global satellite data market will expand exponentially. Processing such vast and unique data in an efficient manner is necessary. Google Earth Engine (GEE) is an example of a cloud-based geospatial platform that revolutionized the way users store, process, analyze, and visualize spatial data. This chapter delves into the fundamentals of digital image processing, employing cutting-edge techniques to process, analyze, and visualize remotely sensed data through the use of Google Earth Engine (GEE) and JavaScript API. This chapter presents an in-depth exploration of digital image processing, specifically focusing on remotely sensed data. It highlights advanced techniques and includes two case studies that demonstrate practical applications in preprocessing and detailed analysis of land use and land cover (LULC) changes.
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