Rapid urbanization has caused significant changes along the urban-rural gradient, leading to a variety of landscapes that are mainly shaped by human activities. This dynamic interplay also influences the distribution and characteristics of trees outside forests (TOF). Understanding the pattern of these trees will support informed decision-making in urban planning, in conservation strategies, and altogether in sustainable land management practices in the urban context. In this study, we employed a deep learning-based object detection model and high resolution satellite imagery to identify 1.3 million trees with bounding boxes within a 250 km2 research transect spanning the urban-rural gradient of Bengaluru, a megacity in Southern India. Additionally, we developed an allometric equation to estimate diameter at breast height (DBH) from the tree crown diameter (CD) derived from the detected bounding boxes. Our study focused on analyzing variations in tree density and tree size along this gradient. The findings revealed distinct patterns: the urban domain displayed larger tree crown diameters (mean: 8.87 m) and DBH (mean: 43.78 cm) but having relatively low tree density (32 trees per hectare). Furthermore, with increasing distance from the city center, tree density increased, while the mean tree crown diameter and mean tree basal area decreased, showing clear differences of tree density and size between the urban and rural domains in Bengaluru. This study offers an efficient methodology that helps generating instructive insights into the dynamics of TOF along the urban-rural gradient. This may inform urban planning and management strategies for enhancing green infrastructure and biodiversity conservation in rapidly urbanizing cities like Bengaluru.
Read full abstract