SiM: Satellite Image Mixed Pixel Deforestation Analysis in Optical Satellite for Land Use Land Cover Application

Priyanka Darbari , Ankush Agarwal, Manoj Kumar

Brazil’s deforestation monitoring integrates accuracy and current monitoring for land use and land cover applications. Regular monitoring of deforestation and non-deforestation requires Sentinel-2 multispectral satellite images of several bands at various frequencies, the mix of high- and low-resolution images that make object classification difficult because of the mixed pixel problem. Accuracy is impacted by the mixed pixel problem, which occurs when pixels belong to different classes and makes detection challenging. To identify mixed pixels, Band Math is used to merge numerous bands to generate a new band NDVI. Thresholding is used to analyze the edges of deforested and non-deforested areas. Segmentation is then used to analyze the pixels which helps to identify the number of mixed pixels to compute the deforested and non-deforested areas. Segmented image pixels are used to categorize the deforestation of the Brazilian Amazon Forest between 2019 and 2023. Verify how many pixels are mixed to improve accuracy and identify mixed pixel issues; compare the mixed and pure pixels of fuzzy clustering with the subtracted morphological image pixels. With the help of segmentation and clustering researchers effectively validate mixed pixels in a specific area. The proposed methodology is easy to analyze and helpful for an appropriate calculation of deforested and non-deforested areas.