Surveying & Geoinformatics

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Surveying & Geoinformatics

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Start date: 2014Subject: search.filters.subject.Remote Sensing

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    A Remote-Sensing Based Assessment of Seasonal Variation in Vegetation Quality and Productivity in Nimbia Forest
    (Civil and Environmental Research, 2015) Ifeanyi C. Onuigbo, Joseph O. Odumosu, Ekundayo. A. Adesina, Nanpon. Zitta, Oluibukun G. Ajayi, Abdullahi A. Kuta
    Agriculture plays a vital role in the growth and sustainability of developing countries, such as those in sub-Saharan Africa. Therefore, there is a need to monitor and assess the changes taking place in vegetation quality and productivity. The conventional ground survey method has proved to be highly tedious, laborious, and grossly limited, especially when large and densely forested regions are concerned. This paper presents a remote sensing-based approach as a real-time technology to determine the effect and extent of water loss caused by seasons on vegetation quality in Nimbia forest, Kaduna State. ENVI 4.7, ArcGIS 10.0, and Global Mapper Software were used, and a discrepancy of about 45% in the quality of vegetation has been observed between seasons in the region under study.
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    Assessing the risk of soil loss using geographical information system (GIS) and the revised universal soil loss equation (RUSLE)
    (2024-09-30) Ekundayo Adesina, Oluibukun Ajayi, Joseph Odumosu, Abel Illah
    Soil erosion poses a significant environmental challenge in many developing nations, and critically evaluating the threat of soil erosion is paramount for sustainable land management practices. This study aims to identify the contributing factors to erosion and estimate the amount of soil loss in the Bosso Local Government Area of Niger State, Nigeria, using the Revised Universal Soil Loss Equation (RUSLE) model. Factors like rainfall erosivity (𝑅), soil erodibility (𝐾), topography (𝐿𝑆), cover and management (𝐶), and support practices (𝑃), were integrated into a Geographic Information System (GIS) environment to generate variable layers. The estimated values of 𝑅,𝐾, 𝐿𝑆, 𝐶, 𝑎𝑛𝑑 𝑃 ranged between 438.866 and 444.319 MJmmha-1 h-1 yr-1, 0.06 to 0.015 megajoules per hectare hour megajoules-1 hectare-1 millimeter-1, 0 and 572, 0 to 0.2, and 0 to 1, respectively. GIS raster calculations derived from these factors revealed a mean estimated soil loss rate of 0-6672.83t/h/yr-1 (tons per hectare per year). Notably, rainfall emerged as the most influential factor driving soil erosion within the study area. The study highlights the necessity for immediate intervention to mitigate soil erosion in the study area. Furthermore, to formulate effective conservation and management strategies, this study advocates for further research prioritizing severity analysis areas and estimating sediment loss across the region.