What are the most effective remote sensing techniques and algorithms for detecting and analyzing land use and land cover (LULC) changes in rapidly urbanizing areas, and how do their accuracies and results compare when applied to Dhaka's urban landscape?
Muhammad Shareef Shazil
Use of Landsat imagery in Google Earth Engine with machine learning-based supervised classification algorithms (RF, SVM, CART) is highly effective for land use and land cover change detection, even without field data. You can achieve compartively accurate results by splitting your data into training and validation samples but if you have field data it would be of more help.
While Sentinel-2 offers a higher temporal resolution, we prefer Landsat data for its longer historical record.
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