The 10th ACM SIGSPATIAL International Workshop on Analytics for Big Spatial Data (BigSpatial 2022)

Abstract

Analysis and management of big data are important areas of research for data researchers and scientists. Both the industry and governmental agencies have invested tremendous resources and effort in the area of big data analysis and management in the past decade. Within the realm of big data, spatial and spatio-temporal data are still one of the fastest-growing types of data. With advances in remote sensors, sensor networks, and the proliferation of location sensing devices in daily life activities and common business practices, the generation of disparate, dynamic, and geographically distributed spatiotemporal data has continued to explode in recent years. In addition, significant progress in ground, air, and space-borne sensor technologies has led to unprecedented access to earth science data for scientists from different disciplines. For example, NASA recently collected its 10 millionth Landsat image [4] and the volume of satellite imagery being collected has reached the petabyte scale. Analysis of this large-scale data poses new challenges to researchers.