Introducing big data to measure the spatial heterogeneity of human activities for optimizing the ecological security pattern: A case study from Guangzhou City, China

Spatial heterogeneity of human activities (SHHA) is part of the heterogeneity of urban ecosystems, which influences the understanding of ecological processes and landscape functions. Few ecological security pattern (ESP) studies have comprehensively measured SHHA and explicitly explained its effect on ESP planning. It affects the efficiency and landscape functions of ESP planning, leading to challenges in maximizing urban development and ecosystem benefits. In this study, Tencent user density (TUD) data considering human activity for all time periods and point of interest (POI) density with fine-scale human activity location information were fused by using wavelet transform as the spatial distribution of human activities. We applied it to correct the resistance surface for ESP planning, then proposed targeted restoration and conservation policies at a fine scale by combining human activities and POIs. The results revealed that the corrected resistance surface could approach the heterogeneous megacity for spatial and functional structures. More importantly, ESP planning based on the corrected resistance surface could enhance efficiency and landscape functions. This research strengthens our understanding of the effect of SHHA on ESP planning. It may provide important insights for policymakers concerning integrated human-natural systems in landscape planning.