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Spatiotemporal analysis of urban land cover changes in Kigali, Rwanda using multitemporal landsat data and landscape metrics
KTH; University of Rwanda, Rwanda.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Environmental and Life Sciences (from 2013). (Geomatics)ORCID iD: 0000-0002-6140-2922
KTH.
2017 (English)In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3/W2, 2017, COPERNICUS GESELLSCHAFT MBH , 2017, p. 137-144Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
COPERNICUS GESELLSCHAFT MBH , 2017. p. 137-144
Series
International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750, E-ISSN 2194-9034
Keywords [en]
Landsat imagery, Urbanization, Land cover change, Landscape metrics, Kigali, Rwanda
National Category
Remote Sensing
Research subject
Geomatics
Identifiers
URN: urn:nbn:se:kau:diva-69799DOI: 10.5194/isprs-archives-XLII-3-W2-137-2017ISI: 000466925400021OAI: oai:DiVA.org:kau-69799DiVA, id: diva2:1257752
Conference
37th International Symposium on Remote Sensing of Environment, 8–12 May 2017, Tshwane, South Africa
Available from: 2018-10-22 Created: 2018-10-22 Last updated: 2019-11-13Bibliographically approved

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Haas, Jan

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