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This research aims to develop a remote sensing framework to analyze and predict solid waste generation in tropical highland agroecosystems.

March 7, 2026Scientific ReportsOpen Access

A remote sensing framework for predicting and managing waste generation in tropical highland agroecosystems: case study of land use transitions in cameron highlands, Malaysia

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Framework predicts waste generation in tropical agroecosystems, suggesting strategies for sustainable management.

This research aims to develop a remote sensing framework to analyze and predict solid waste generation in tropical highland agroecosystems.
Utilized multi-temporal satellite-derived land use and land cover (LULC) data
Performed supervised classification of Sentinel-2 and Landsat-8 imagery
Linked waste data to land use zones using overlay analysis in ArcGIS Pro 3.2
Conducted correlation and regression analyses to identify relationships between land use changes and waste generation
Developed a spatio-temporal model to predict waste-intensive zones.
Found a strong positive correlation (r = 0.89, p < 0.05) between cropland expansion and waste generation
Noted a significant negative correlation (r = − 0.95, p < 0.05) with forest cover
Identified high-waste areas within 500 m of urban and agricultural zones
Achieved 92% accuracy in predicting waste-intensive zones
Observed waste generation peak in 2023, coinciding with land conversion trends.

HARUN et al. (2026) studied this question.

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