Gully Development Mapping for Effective Remediation and Control Using Geospatial Technology | Chapter 8 | Challenging Issues on Environment and Earth Science Vol. 4

 Gully erosion has reached alarming proportions in south-eastern Nigeria, prompting the use of geospatial information technology to map a gully erosion site in Oron, Akwa Ibom State, for effective remediation and control. The use of dual frequency Leica GPS 1200 provided ground controls in the vicinity of the gully head. The formation and growth of gullies causes large amounts of sediment to be released into receiving streams, polluting sources of water supply for the rapidly growing urban population. The obtained data were downloaded and processed using Leica Geo Office 8.3 before being exported to Arc GIS 10.1 and Auto CAD Civil 3D 2013 for terrain analysis-DEM. In addition, the Leica Total Station TS 06 was used for topographic mapping. The defined runoff contributing area aided in calculating the maximum discharge (using the Rational method). The computed runoff of 33.919m3/s accounts for the rapid rate of gully headscarp retreat of 1.2 m/day prior to intervention by the state government during the month of July. The findings were put to use in the design of gully control structures.

Author (s) Details

Dr. Charles Udosen
Department of Geography, University of Uyo, Uyo, Nigeria.

Mr. Okon Efiong Ubom
Shell Petroleum Development Company Ltd, Uyo, Nigeria.

Mr. Abasi-Ifreke S. Etok
Akwa Ibom State, College of Arts and Sciences, Nung Ukim, Ikono, Nigeria.

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Assessment and Evaluating the Effects of Generalisation Approaches and DEM Resolution on the Extraction of Terrain Indices in Kwazulu Natal, South Africa | Chapter 5 | International Research in Environment, Geography and Earth Science Vol. 6

 In deriving primary topographic attributes that serve as input variables for a variety of hydrological and geomorphological studies, digital elevation model (DEM) data is basic. However, consensus on the influence of the source and resolution of DEM on the application of these topographic attributes to landscape characterization is still varied. At the same time, elevation data from many major sources and resolutions are available for South Africa: the Shuttle Radar Topographic Mission (SRTM), the EarthEnv and Stellenbosch University DEM (SUDEM). In a local context, limited research was conducted comparing the extraction of terrain attributes increasingly accessible to high-resolution Digital Terrain Data (DTM) such as LiDAR (Light Detection and Ranging). However, LiDAR 's usefulness in topographic analysis poses its difficulties in terms of operational resolution, processing requirements and limited spatial coverage. Elevation, slope, topographic wetness index and surface roughness attributes of terrain derived from DEMs from different sources, at different spatial resolutions and using three generalisation algorithms, namely: mean cell aggregation, nearest neighbour and topo-to-raster corrected hydrological. We demonstrate that topographic variable extraction is heavily dependent on the approach of DEM source and generalisation. Although higher resolution DEMs can reflect the "real" surface more accurately, for all extracted variables, they do not necessarily give the best results. Our findings illustrate the caveats of selecting non-fit-for - purpose DEMs for topographic analysis and provide an easy but efficient solution for reconciling the selection of DEMs before terrain analysis and topographic feature characterization based on neighbourhood size resolution. Finding the best mix of when surface data can be upgraded, what DEMS to use, and what spatial scale works to ensure that The most optimal surface integrity is also still context-specific. This research , however , shows a robust structure for the interpretation of optimal sensor choice and spatial scale for the southern-coastal region of KZN to understand the geomorphological processes in the landscape.

Author (s) Details

Jonathan T. Atkinson
Stellenbosch Department of Soil Science, Matieland, Stellenbosch, South Africa.

Dr. Willem P. De Clercq
Stellenbosch Water Research Institute, Matieland, Stellenbosch, South Africa.

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