Spatio-temporal pattern of urban vegetation in the central business district of the Wa municipality of Ghana

Abstract

Increasing physical infrastructure development influences the spatial distribution of vegetation and temperature in many cities around the globe. However, in emerging cities such as Wa Municipality in Ghana and elsewhere, research attention has focused on urban expansion or urban sprawl and the impacts thereof on the peri‑urban vegetation. Considering the importance of vegetation in regulating temperature, reducing windstorm, carbon sequestration and creating beauty, this paper concentrates on the threat posed by urban retrofitting activities on vegetation in open spaces in the Wa Central Business District (CBD). The study area was gridded into 1 ha plots using the Fishnet tool in ArcMap. One hundred and fifty-seven full plots and 75 plots of various sizes less than 1 ha were obtained from the fishnet gridding. One hundred and thirteen full plots were sampled for the counting of the trees. Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) maps were prepared from 2014, 2017 and 2020 Landsat 8 satellite images. Point NDVI and LST values were extracted for 600 random points and used to analyze the spatial distribution using Global and Local Moran I tests. Two-sample t-test and Pearson correlation statistical tests were performed to assess the significance of any differences in the NDVI, LST and the tree density for 2014, 2017 and 2020. The results revealed that the average tree densities for 2017 and 2020 in the Wa CBD were 4 and 3 trees ha−1, respectively which were classified as very low. The spatial distribution of the NDVI values showed low, high and insignificant clusters. The NDVI values were within the range of 0.019–0.219. The clusters of high values were found around state institutional structures, where large open spaces existed while clusters of low values were found around the market, transport stations and densely populated areas where open spaces were very few. The land surface temperature trend revealed increasing minimum and maximum values. The minimum LST values were 32 °C, 33 °C and 36 °C in 2014, 2017 and 2020, respectively and the maximum LST values were 36 °C, 37 °C and 40 °C for 2014, 2017 and 2020, respectively. It is concluded that tree density and NDVI values in the CBD are low, signifying isolated trees and patches of vegetation in the area. Also, it was revealed that as greenness reduces LST increases. The Wa Municipal Assembly and the Regional Forestry Commission should intensify public education on tree planting and maintenance in the city.