Social and Behavioral Sciences Commons^™

Detecting And Visualizing Observation Hot-Spots In Massive Volunteer-Contributed Geographic Data Across Spatial Scales Using Gpu-Accelerated Kernel Density Estimation, Guiming Zhang

Geography and the Environment: Faculty Scholarship

Volunteer-contributed geographic data (VGI) is an important source of geospatial big data that support research and applications. A major concern on VGI data quality is that the underlying observation processes are inherently biased. Detecting observation hot-spots thus helps better understand the bias. Enabled by the parallel kernel density estimation (KDE) computational tool that can run on multiple GPUs (graphics processing units), this study conducted point pattern analyses on tens of millions of iNaturalist observations to detect and visualize volunteers’ observation hot-spots across spatial scales. It was achieved by setting varying KDE bandwidths in accordance with the spatial scales at which …