Spatial and temporal dynamics of urban green spaces: an assessment using remote sensing time-series data in Blantyre City, Malawi

Abstract

Urban expansion and its ecological footprint are increasing at an alarming rate globally. This is putting pressure on the management of Urban Green Space (UGS) which are vital for biodiversity and ecological conservation. UGS contribute to sustainable development of these urban ecosystems. Recently, UGS have been considered to be substantially important for quality of life. In this study, UGS in the city of Blantyre, which has experienced rapid urbanization from 1990 to 2020, were delineated using remotely sensed Landsat-5 TM and Landsat-8 OLI time-series imagery. Maximum Likelihood Supervised Learning Algorithm was utilized to characterize landcover/landuse (LULC) categories, and further extrapolate to dynamic patterns of Urban Green Spaces (UGS). Kappa statistical coefficient and overall accuracy assessment were used to validate the LULC classification. Post-classification technique was used to compare and empirically categorize LULC and UGS changes between 1990 and 2020. Vector analysis change detection was performed to assess the dynamic patterns in UGS over time. The results indicate
rapid decrease in UGS footprint by 19.26km 2 representing a 42% decrease between 1990 and 2020. These changes in the study area are attributed to increased urbanization, population growth, socio-economic development, changes in microclimatic patterns and lack of policy and enforcement by the city authorities. The finding that the UGS in Blantyre city has substantially decreased over the past three decades is significant to the city’s policymakers, residents and researchers to better understand the shifting dynamics in LULC, and the particularities of UGS
depletion in such a critical city for Malawi’s socio-economic growth.