Monitoring change in the spatial heterogeneity of vegetation cover in an African savanna
International Journal of Remote Sensing
Department of Geography and Environmental Science, University of Zimbabwe, Mount Pleasant, Harare, Zimbabwe; International Institute for Geo-Information Science and Earth Observation (ITC), Hengelosestraat 99, 7500 AA Enschede, Netherlands
The extent to which a new intensity-dominant scale approach to characterizing spatial heterogeneity from remote sensing imagery can be used to monitor two-dimensional changes (i.e. variability and patch size) in the spatial heterogeneity of vegetation cover (estimated from a Landsat Thematic Mapper (TM)-derived Normalized Difference Vegetation Index (NDVI)) was tested in the Sebungwe region in north-western Zimbabwe between 1984 and 1992. Intensity of spatial heterogeneity (i.e. the maximum variance obtained when a spatially distributed landscape property is measured with a successively increasing window size) was used to measure variability in vegetation cover. Dominant scale of spatial heterogeneity (i.e. the window size at which the maximum variance in the landscape property is measured) was used to measure the dominant patch dimension of vegetation cover. This approach was validated by testing whether the observed change in the dominant scale and intensity of spatial heterogeneity of vegetation cover between 1984 and 1992 was related to changes in the proportion of arable fields. The results also indicated that there was a significant relationship (p<0.05) between changes in the proportion of agricultural fields and changes in the intensity and the product of intensity and dominant scale of spatial heterogeneity (intensity × dominant scale), suggesting that the new approach captures observable changes in the landscape, and is not an artefact of the data. The results imply that the intensity-dominant scale approach to quantifying spatial heterogeneity in remote sensing imagery can be used for a comprehensive characterization and monitoring of changes in landscape condition.
Agriculture; Imaging techniques; Monitoring; Vegetation; Remote sensing imagery; Spatial heterogeneity; Remote sensing; Landsat thematic mapper; landscape change; NDVI; satellite imagery; savanna; vegetation cover; Africa; Southern Africa; Sub-Saharan Africa; Zimbabwe