Land cover change monitoring in rapidly urbanizing environments based on spaceborne remotely sensed data and measurable indicators is essential for quantifying and evaluating the spatial patterns of urban landscape change dynamics and for sustainable urban ecosystems management. The objectives of the study are to analyse the spatio-temporal evolution of urbanization patterns of Kigali, Rwanda over the last three decades (from 1984 to 2016) using multi-temporal Landsat data and to assess the associated environmental impact using landscape metrics and ecosystem services. Visible and infrared bands of Landsat images were combined with derived Normalized Difference Vegetation Index (NDVI), Gray Level Co-occurrence Matrix (GLCM) variance texture and digital elevation model (DEM) data for pixel-based classification using a support vector machine (SVM) classifier. Seven land cover classes were derived with an overall accuracy exceeding 87% with Kappa coefficients around 0.8. As most prominent changes, cropland was reduced considerably in favour of built-up areas that increased from 2.13 km2 to 100.17 km2 between 1984 and 2016. During those 32 years, landscape fragmentation could be observed, especially for forest and cropland. The landscape configuration indices demonstrate that in general the land cover pattern remained stable for cropland, but that it was highly changed for built-up areas. Ecosystem services considered include regulating, provisioning and support services. Estimated changes in ecosystem services amount to a loss of 69 million US dollars (USD) as a result of cropland degradation in favour of urban areas and in a gain of 52.5 million USD within urban areas. Multi-temporal remote sensing is found as a cost-effective method for analysis and quantification of urbanization and its effects using landscape metrics and ecosystem services.