International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Download
Citation
Volume XLII-3/W2
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W2, 137–144, 2017
https://doi.org/10.5194/isprs-archives-XLII-3-W2-137-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W2, 137–144, 2017
https://doi.org/10.5194/isprs-archives-XLII-3-W2-137-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  16 Nov 2017

16 Nov 2017

SPATIOTEMPORAL ANALYSIS OF URBAN LAND COVER CHANGES IN KIGALI, RWANDA USING MULTITEMPORAL LANDSAT DATA AND LANDSCAPE METRICS

T. Mugiraneza1,2, J. Haas3, and Y. Ban1 T. Mugiraneza et al.
  • 1Division of Geoinformatics, Department of Urban Planning and Environment, KTH Royal Institute of Technology, Stockholm, Sweden
  • 2Centre for Geographic Information Systems and Remote Sensing, College of Science and Technology, University of Rwanda, Huye, Rwanda
  • 3Department of Environmental and Life Sciences, Geomatics, Faculty of Health, Science and Technology, Karlstad University, Karlstad, Sweden

Keywords: Landsat imagery, Urbanization, Land cover change, Landscape metrics, Kigali, Rwanda

Abstract. Mapping urbanization and ensuing environmental impacts using satellite data combined with landscape metrics has become a hot research topic. The objectives of the study are to analyze the spatio-temporal evolution of urbanization patterns of Kigali, Rwanda over the last three decades (from 1984 to 2015) using multitemporal Landsat data and to assess the associated environmental impact using landscape metrics. Landsat images, Normalized Difference Vegetation Index (NDVI), Grey Level Co-occurrence Matrix (GLCM) variance texture and digital elevation model (DEM) data were classified using a support vector machine (SVM). Eight landscape indices were derived from classified images for urbanization environment impact assessment. Seven land cover classes were derived with an overall accuracy exceeding 88 % with Kappa Coefficients around 0.8. As most prominent changes, cropland was reduced considerably in favour of built-up areas that increased from 2,349 ha to 11,579 ha between 1984 and 2015. During those 31 years, the increased number of patches in most land cover classes illustrated landscape fragmentation, especially for forest. The landscape configuration indices demonstrate that in general the land cover pattern remained stable for cropland but it was highly changed in built-up areas. Satellite-based analysis and quantification of urbanization and its effects using landscape metrics are found to be interesting for grassroots and provide a cost-effective method for urban information production. This information can be used for e.g. potential design and implementation of early warning systems that cater for urbanization effects.