Development of geospatial analysis tools for inventory and mapping of soils of the Chongwe Region of Zambia.

Abstract

Designing a methodology for mapping and studying soils in a quick and inexpensive way is critical especially in developing countries which lack detailed soil surveys. The main aim of this research was to explore the potential of Landsat ETM data combined with various forms of ancillary data in mapping soils in Chongwe, a semi arid region in Zambia. The study also examines how spectral maps produced by digital analysis of Landsat ETM data compare with field observation data. The study area, covering 54 000 ha, is located about 45 km to the east of the capital city, Lusaka, Zambia. It encompasses five main landscapes: hilland, piedmont, plateau, alluvial plain and valley dambos (seasonally waterlogged depressions). Geospatial tools were applied in four related chapters, (1) a review and discussion on the application of geospatial tools to aid soil mapping, (2) identification and characterization of soils in different landscapes in the Chongwe region of Zambia, (3) digital analysis of Landsat ETM data and its application to soil mapping, and (4) summary of the results, conclusions and suggestions for future research. This research has shown that visual interpretation and digital analysis of Landsat images have the capacity to map soils with reasonable accuracy. It demonstrates the utility of Landsat data to delineate soil patterns, especially when acquired during the dry season when there are long periods of cloud free skies, low soil moisture and minimal vegetation cover. When the accuracy of the Landsat ETM image was tested the agreement between Landsat ETM data and field reference data was 72%, indicating a definite relationship between Landsat imagery and soils types. Furthermore, the study revealed that overall, upland areas have a better agreement with Landsat spectral data compared to lowland areas, probably due to diverse origin of sediments and low spatial extent of most geomorphic units in lowland areas. In terms of soilscape boundary delineation, the Landsat derived map was better than the conventional soil map. Landsat data delineated more areas within the conventional soil map polygons. Examining the spectral responses in different bands, it was found that spectral bands, 3, 5, and 7 provide images of optimum contrast for the delineation of soilscapes.