25 October 2016 Regional assessment of trends in vegetation change dynamics using principal component analysis
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Abstract
Vegetation forms the basis for the existence of animal and human. Due to changes in climate and human perturbation, most of the natural vegetation of the world has undergone some form of transformation both in composition and structure. Increased anthropogenic activities over the last decades had pose serious threat on the natural vegetation in Nigeria, many vegetated areas are either transformed to other land use such as deforestation for agricultural purpose or completely lost due to indiscriminate removal of trees for charcoal, fuelwood and timber production. This study therefore aims at examining the rate of change in vegetation cover, the degree of change and the application of Principal Component Analysis (PCA) in the dry sub-humid region of Nigeria using Normalized Difference Vegetation Index (NDVI) data spanning from 1983-2011. The method used for the analysis is the T-mode orientation approach also known as standardized PCA, while trends are examined using ordinary least square, median trend (Theil-Sen) and monotonic trend. The result of the trend analysis shows both positive and negative trend in vegetation change dynamics over the 29 years period examined. Five components were used for the Principal Component Analysis. The results of the first component explains about 98 % of the total variance of the vegetation (NDVI) while components 2-5 have lower variance percentage (< 1%). Two ancillary land use land cover data of 2000 and 2009 from European Space Agency (ESA) were used to further explain changes observed in the Normalized Difference Vegetation Index. The result of the land use data shows changes in land use pattern which can be attributed to anthropogenic activities such as cutting of trees for charcoal production, fuelwood and agricultural practices. The result of this study shows the ability of remote sensing data for monitoring vegetation change in the dry-sub humid region of Nigeria.
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B. A. Osunmadewa, B. A. Osunmadewa, E. Csaplovics, E. Csaplovics, Majdaldin R. A., Majdaldin R. A., C. O. Adeofun, C. O. Adeofun, D. Aralova, D. Aralova, } "Regional assessment of trends in vegetation change dynamics using principal component analysis", Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 99981Y (25 October 2016); doi: 10.1117/12.2242011; https://doi.org/10.1117/12.2242011
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