Ms. Betty A. Mulianga Profile

Betty A. Mulianga

at Kenya Sugar Research Foundation

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Publications (1)

Proceedings Article | 16 October 2013 Paper

Estimating potential soil erosion for environmental services in a sugarcane growing area using multisource remote sensing data

B. Mulianga, A. Bégué, M. Simoes, P. Clouvel, P. Todoroff

Proceedings Volume 8887, 88871W (2013) https://doi.org/10.1117/12.2028640

KEYWORDS: Vegetation, Data modeling, Soil science, Earth observing sensors, Remote sensing, MODIS, Environmental sensing, Ecosystems, Landsat, Satellite imaging

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Characterization of landscapes is crucial in modelling potential soil erosion to ascertain environmental services that are provided by the main land use in the ecosystem. Remote sensing techniques have proved successful in characterization of landscapes. In this study area of a rain-fed Kibos-Miwani sugar zone of Kenya, we used Normalized difference vegetation index (NDVI) data extracted from satellite imagery to characterize the spatial and temporal heterogeneity of the vegetation conditions, and to model potential soil erosion. Data used included Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m NDVI acquired in the period 2000 to 2013; 30 m Landsat5 time series images acquired between November 2010 and June 2011; a 30 m digital elevation model (DEM); and ground observations (land cover and soil characteristics). Temporal NDVI was extracted directly from MODIS 250 m images to study the changes in seasonal vegetation conditions with time, and spatial NDVI was extracted by analysing Landsat5 images at the field scale. NDVI extracted from Landsat images for a specific date, represented vegetation conditions for that simulation period. To compute potential soil erosion, we used Landsat 5 NDVI, the slope, aspect, curvature and soil physical properties as input data sets in the spatially explicit Fuzzy-based dynamic soil erosion model (FuDSEM). Land cover data collected revealed that sugarcane was the main land use, occupying 76% of the land cover. Results were consistent with crop management practices, illustrating a spatially heterogeneous land scape with varied vegetation conditions throughout the year. Out of simulations, we noted a homogeneous low erosion risk in areas with natural land cover with a global mean of 0.42. Medium to intense erosion risk in cropped areas was evident, with erosion risk varying from one pixel to the other. Simulation results suggest that crop management practices (planting and harvesting processes) are the drivers of erosion in sugar cane cultivated areas.

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