TITLE:
Spatio-Temporal Assessment of Vegetation Resource Dynamics in Nigeria from SPOT Satellite Imageries
AUTHORS:
Sadiq Abdullahi Yelwa, Aliyu Bilya Sanda, Umar Usman
KEYWORDS:
Vegetation, Resources, Desertification, NDVI, SPC
JOURNAL NAME:
American Journal of Climate Change,
Vol.8 No.4,
December
2,
2019
ABSTRACT: Vegetation resources in Nigeria are of vital importance for the sustainable development of the country. However, this essential resource is in danger due to the effect of anthropogenic and climate induced impacts. Currently desert encroachment which cuts across the Sahel is affecting most of the states in the northern part of the country particularly the eleven states considered by the Federal Ministry of Environment in Nigeria as the frontline states. Several studies on the Nigerian environment have shown that there are serious threats to the general environment particularly vegetation. Due to population growth and the need for housing as well as the expansion of the over-utilised farmlands across these states, places considered as reserved areas across the country are being exploited to the detriment of the vegetal resources particularly the forest and rangeland areas. This study utilized Idrisi TerrSet (version 18) raster-based remote sensing and GIS software to analyse seventy two (72) dekadal Normalised Vegetation Index (NDVI) imageries from SPOT satellite covering Nigeria in order to assess the anthropogenic and likely climatic impacts on the vegetal resources using the forward t-mode Principal Component Analysis (PCA) with standardised principal components. Results indicated that Component 1 which explains about 69% of the 72 time-series NDVI imageries shows typical vegetation cover over the study area within the time period under study. While component two indicated a cyclic trend differentiating the ENSO events of 1999 and 2009; component three indicated positive anomaly pattern of vegetation NDVI mostly within Sokoto, Kebbi, Kano, Jigawa and the northern parts of Bauchi, Yobe and Borno states. However, Component four imagery indicated a likely link to the 2009 flood that affected Kainji dam and rivers Niger and Benue. For a better result, the integration of socio-economic and high spatial resolution data into an assessment of this kind in future studies is encouraged.