Monitoring and evaluation of landscape fragmentation is important in numerous research areas, such as natural resource protection and management, sustainable development, and climate change. One of the main challenges in image classification is the intricate selection of parameters, as the optimal combination significantly affects the accuracy and reliability of the final results. This research aimed to analyze landscape change and fragmentation in northwestern Peru. We utilized accurate land cover and land use (LULC) maps derived from Landsat imagery using Google Earth Engine (GEE) and ArcGIS software. For this, we identified the best dataset based on its highest overall accuracy, and kappa index; then we performed an analysis of variance (ANOVA) to assess the differences in accuracies among the datasets, finally, we obtained the LULC and fragmentation maps and analyzed them. We generat...

Careful landfill selection with minimal environmental impact is vital for urban planners. This study aims to identify suitable sites for controlled landfills using Fuzzy-AHP integrated with Remote Sensing and GIS, considering a 20-year projection of population and solid waste generation. Initially, twelve sub-criteria were identified, grouped into environmental, socio-economic, and physical categories, and then weighted using paired comparison matrices involving nine experts. The sub-criteria were rasterized and classified into four suitability levels. The weighted overlay of sub-criteria maps generated a territorial suitability model. Within the Alto Utcubamba Commonwealth (Amazonas, Peru), 0.069%, 41.70%, 66.934%, 0.20%, and 12.4% of the territory are suitable, moderately suitable, less suitable, unsuitable, and restricted, respectively, for landfill establishment. Subsequently, 16 hig...