Land-Cover Removal and Gully Development in Southeast Nigeria: A 30-Year Analysis with Pixel and OBIA Approaches in Juxtaposition
- 1 Imo State University, Nigeria
Abstract
In this study a study of gully erosion in southeast Nigeria is presented. The study of gully development on a regional scale is currently undermined by the inherent costs associated with consistent field monitoring and the lack of historic measurements to perform time series analysis. As a result, there are very few studies which implement long term analyses of gullies in the region as a collective. Consequently, the building of knowledge of the role of environmental changes on the development of gullies is inhibited. Remote sensing methodologies, via the Landsat archive, are used as low economic data source that assisted in the analyses of gullies over the time period 1986 to 2015. The Landsat data is used to establish land cover changes over the time period, via pixel and object-based classification, to identify its role in gully development. The use of classification for this purpose identifies this study as a first of its kind in Nigeria. Aiming to link environmental characteristics and land cover changes with gully development and erosion rates at multiple current locations. In terms of the correlation between vegetation area and gully/openland development, Pixel based classification produced a correlation of r = -0.9 (p<0.05). A similar strength of correlation was exhibited for OBIA with r = -0.9 (p<0.05) with both results indicating a very strong and significant negative correlation between the amount of vegetated area and Gully/open-land development over the study period 1986-2015.
DOI: https://doi.org/10.3844/ajessp.2020.34.47
Copyright: © 2020 Sylvanus Iro. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Land-Cover
- Gully Erosion
- Pixel and OBIA Classification