Assessing Vegetation Change and its Effects on City Climate for Sustainable Urbanism Using Geographic System and Remote System Techniques: A Case Study of Adi Town, Benue, Nigeria

Abstract

Vegetation is one the most important and renewable resources of the earth's ecosystem. However, vegetation has been in a high state of decline both globally and locally. With the increase in Urbanization across the globe, the city micro-climate is constantly changing, affecting the living environment, necessitating the need for sustainable urbanism This study focused on the rate of vegetation change and its impacts on the environment in Adi town. The research objectives seek to determine the status and rate of vegetation change in Adi and assess the impact of climate on the change in vegetation in Adi. Landsat imageries obtained from United State Geological Survey, USGS, were used for vegetation analysis while rainfall and temperature data obtained from Akperan Orshi College of Agriculture Meteorological Station were used to compare the change in vegetation and climate parameters. The research methods applied Normalized Differential Vegetation Index, (NDVI) from Landsat imageries using supervised classification. Sample tables were created for each imagery; then maximum likelihood classification was employed for the reclassification of the different land uses. A bivariate linear regression of the values obtained from Normalized Differential Vegetation Index and rainfall data was employed for analysis. The NDVI result showed that high vegetation decreased in Adi from 38.69% to 1.01% from 1986 to 2019 while the built-up area increased from 6.78% to 44.60% from 1986 to 2003 and declined to 9.94% in 2019. Agriculture land increased from 48.333% to 69.809 while bare surfaces increased in land area from 1.36% to 7.98% from 1986 to 2019. The relationship between climate and vegetation was significantly weak. The result of the regression showed that the rainfall and NDVI was negative and linear and did not reveal bivariate outliers. The correlation between NDVI and rainfall was statistically significant at α=0.05. The regression equation is given by Y= - 498X+908802. Thus, for every unit decrease in rainfall, NDVI decreases by -498. Further findings using descriptive statistics from the questionnaire responses showed that human activities have contributed massively for the degradation of the vegetation in the study area. Responses from questionnaire showed that agricultural practices, burn bricks practices, deforestation, urbanization and fuel wood collection were the major causes of vegetation degradation in the study area ranging from erosion, variation in the town micro-climate, biodiversity loss and reduction in agricultural yield.