Malawi’s Blantyre City faces escalating waste management challenges due to increased urbanization and inadequate waste collection services. This research utilized remote sensing (RS) and geographic information system (GIS) techniques to map potential illegal dump sites (PIDSs). MODIS and Sentinel-5P satellite imagery and GPS locations of dumpsites were used to extract environmental and spatial variables, including land surface temperature (LST), the enhanced vegetation index (EVI), Formaldehyde (HCHO), and distances from highways, rivers, and official dumps. An analytical hierarchical process (AHP) pairwise comparison matrix was used to assign weights for the six-factor variables. Further, fuzzy logic was applied, and weighted overlay analysis was used to generate the PIDS map. The results indicated that 10.27% of the study area has a “very high” probability of illegal dumping, while only 2% exhibited a “very low” probability. Validation with field data showed that the GIS and RS were effective, as about 89% of the illegal dumping sites were identified. Zonal statistics identified rivers as the most significant contributor to PIDS identification. The findings of this study underscore the significance of mapping PIDS in low-resource regions like Blantyre, Malawi, where inadequate waste management and illegal dumping are prevalent. Future studies should consider additional factors and account for seasonal variations.

Graphical abstract showing the assessment of urban water quality in Blantyre, Malawi. Urban pressures (industrialization, urbanization, and poor sanitation) influence water quality in boreholes, kiosks, and rivers. Using GIS, PCA, and WQI analyses, the study found that 44% of water sources were unsuitable for drinking, rivers had the highest contamination levels, and E. coli was detected across all sampled sources. The findings support integrated solutions linking public health, environmental management, and water systems. Rapid urbanization and climate change affect water quality in developing countries. In Blantyre, Malawi, poor sanitation, industrial discharge, and microbial contamination compromise public health. Studies of water quality on integrating Geographic Information Systems (GIS) with multivariate statistics remain limited. This study investigated the spatial variability of physicochemical and microbiological parameters in urban water sources, using GIS, Water Quality Index (WQI), and principal component analysis (PCA). 20 sites (rivers, boreholes, and kiosks) were sampled for pH, turbidity, total dissolved solids (TDS), nitrates, and Escherichia coli. Results showed spatial variation in water quality. All sources exceeded World Health Organization limits for E. coli: rivers (754.8 colony-forming units [CFU]/100 mL), boreholes (79.0 CFU/100 mL), and kiosks (1.0 CFU/100 mL). Spatial interpolation revealed TDS concentrations of 540.8 mg/L in rivers, 345.4 mg/L in kiosks, and 265.8 mg/L in boreholes. Mean turbidity was 2.0 NTU in rivers, 2.2 NTU in boreholes, and 0.5 NTU in kiosks. WQI analysis showed that 44% of sources were unsuitable for drinking, and PCA identified TDS, turbidity, and E. coli as the dominant pollution drivers. These findings highlight public health risks from microbial contamination and urban land-use pressures, requiring integrated water management strategies that link environmental protection, sanitation, and health surveillance.