Soil mapping approach in GIS using Landsat satellite imagery and DEM data

African journal of agricultural research (Impact Factor: 0.08). 12/2009; 4:1295-1302.

ABSTRACT The objective of this study was to create base soil survey maps of the studied lands using Landsat satellite imagery and Digital Elevation Model (DEM) data in a GIS framework. Specific goals were to generate soil maps and to test the usage probability of slope class map overlies colour composite images as a preliminary map for soil survey in a hilly terrain. Surrogate soil-landscape data layers were derived from Landsat satellite imagery and a 10 m DEM. The data were also used to produce 3D-view with slope class boundaries superimposed Landsat image and relief shaded map as a colour map in order to select possible site of soil profile pits and to define physiographic units. Six soil series formed on two different physiographic units were determined, described and sampled. Soil profiles have been classified according to Soil Taxonomy and FAO-Unesco soil map of the World legend classification systems. The methodology was adequate for soil survey and mapping of some types of soils.

  • Soil Science Society of America Journal - SSSAJ. 01/1995; 59(2).
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    ABSTRACT: demonstrated the successful implementation of quanti- tative soil-landscape modeling on a broad landscape Soil-landscape patterns result from the integration of short- and scale useful for soil resource inventory and as a frame- long-term pedogeomorphic processes. A 2-ha hillslope catena in Cali- work for understanding soil-landscape function. Moore fornia shows short-distance variation in A horizon depth from 8 to 80 cm and in soil depth from 8 to .450 cm in convex to concave et al. (1993) and Gessler et al. (1995) showed strong positions. Similar variations in net primary productivity (NPP) and correlation and predictive utility between a digital ter- soil C represent significant information often not captured by soil rain index, the compound topographic index (CTI), and survey maps. Strong correlations between these measured soil- several soil properties. The CTI, often referred to as landscape variables and explanatory digital terrain attributes are used the steady-state wetness index, is a quantification of to develop quantitative soil-landscape models. We were able to ac- catenary landscape position. It integrates both landform count for between 52 and 88% of soil property variance using easily position and context through an index defined as computed terrain variables such as slope and flow accumulation. Spa- tial implementation of the models suggest lateral redistribution pro- CTI 5 ln(As/tan b) (1) cesses resulting in differential accumulation of C and soil mass in where A s is the specific catchment area (area (m 2 ) per convergent and divergent landscape positions. The models are explicit unit width orthogonal to the flow direction) and b is and quantitative, which enables their use for testing hypotheses about the slope angle. Small values of CTI generally depict the spatial distribution of fine-scale landscape and ecosystem pro- cesses and for parameterizing spatially distributed hydrological and upper catenary positions and large values lower cate- ecosystem simulation models. nary positions with an overall range typically from 2 to 12 for zero-order upland areas. The purpose here was to continue development of
    Soil Science Society of America Journal - SSSAJ. 01/2000; 64(6).
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    ABSTRACT: Cited By (since 1996): 7, Export Date: 11 January 2013, Source: Scopus, CODEN: CIJPD, doi: 10.1016/j.catena.2008.12.004, Language of Original Document: English, Correspondence Address: Castrignanò, A.; C.R.A.-SCA, Via Celsio Ulpiani n.4, 70125 Bari, Italy; email:, References: Barca, E., Castrignanò, A., Masciale, R., Passarella, G., Sedda, L., Uncertainty assessment of groundwater quality index using sequential indicator simulation (2006) Final Proc. Int. Conf. Spatial Data Methods for Environmental and Ecological Process. Baia delle Zagare (FG), Italy;
    Catena. 01/2009; 77(1):28-38.

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