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Showing items 1 through 9 of 4.
  1. Library Resource
    Journal Articles & Books
    December, 2011
    Kenya, Africa

    To assess the potential of high-resolution satellite data for land-cover monitoring in the Greater Horn of Africa, we used a regular sampling grid of 170 sites (each measuring 20 km × 20 km) located at the confluence of the latitudes and meridians across the study area. For each of these sites, Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) satellite data were acquired for the years 1990 and 2000. A dot grid visual interpretation was used to assess land-cover change between the two dates in each of the sites.

  2. Library Resource
    Journal Articles & Books
    December, 2011
    Kenya, Africa

    This study presents a predictive modelling technique to map population distribution and abundance for rural areas in Africa. Prediction models were created using a generalized regression analysis and spatial prediction (GRASP) method that uses the generalized additive model (GAM) regression technique. Dwelling unit presence–absence was mapped from airborne images covering 98 km² (30% of the study area) and used as a response variable. Remote-sensing-based (reflectance, texture and land cover) and geospatial (topography, climate and distance) data were used as predictors.

  3. Library Resource
    Journal Articles & Books
    December, 2011
    Kenya

    Characterisation and mapping of land cover/land use within forest areas over long-multitemporal intervals is a complex task. This complexity is mainly due to the location and extent of such areas and, as a consequence, to the lack of full continuous cloud-free coverage of those large regions by one single remote sensing instrument. In order to provide improved long-multitemporal forest change detection using Landsat MSS and ETM + in part of Mt.

  4. Library Resource
    Journal Articles & Books
    December, 2011
    Kenya, Africa

    In sub-Saharan Africa, natural vegetation is being transformed into agricultural lands at a fast rate, endangering ecosystem services and increasing soil-loss potential, which may trigger land degradation. For the Taita Hills study area in Kenya, multi-temporal land-cover models of 1987, 1999 and 2003, derived from Satellite Pour l'Observation de la Terre (SPOT) imagery using a multi-scale segmentation/object relationship modelling (MSS/ORM) methodology and a rainfall layer, a digital elevation model (DEM) and a digital soil map were applied to model potential soil loss.

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