TITLE:
Identifying and Mapping Municipal Solid Waste Disposal Sites in Kenya Using Remote Sensing and GIS—A Case Study of Juja and Dandora Areas
AUTHORS:
Joy Priscah Akinyi, Eunice Nduati
KEYWORDS:
LULC, Solid Waste, Geographic Information Systems, Remote Sensing, Waste Management, Circularity, Environmental Management
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.13 No.8,
August
29,
2025
ABSTRACT: Waste generation in Kenya has been increasing with the rapid urbanization (Haregu et al., 2017; Okot-Okumu, 2012). Almost 50% of the waste is generated in urban centers, and 0.5 kg per capita waste per day is produced, estimated to increase three-fold by 2030. The management of solid waste in Kenya is complicated by various factors. While the national sustainable waste management policy highlights the need for timely inventories and integrated monitoring of waste disposal, there is currently no comprehensive system in place for mapping or monitoring waste disposal sites, both legal and illegal (Ministry of Environment and Forestry, 2021). This study aims to identify waste disposal sites in Dandora in 2021 to 2024 through supervised classification, identify MSW spectral interpretation marks from multispectral satellite imagery and map the spatial distribution of MSW disposal sites using Mobile GIS in Juja in 2022. Supervised classification of the multispectral imagery was performed using training data points from planet imagery, resulting in LULC maps for 2021 to 2024. Spectral reflectance curve charts were generated. Post-classification and location of smaller dumpsites in Juja were collected using mobile GIS. The distribution characteristic of waste disposal sites is associated with densely populated areas of Juja such as areas around Gates A, B and C. Classification results show a high degree of accuracy in identifying and mapping disposal sites across all epochs. In conclusion, high LULC classification accuracy and the other results, indicates that these remote sensing techniques, combined with other GIS and field data, can significantly enhance waste management in Kenya.