The theme of Spatial Accuracy 2020 is "Assessing the Quality of Geospatial Big Data" in terms of Methods and Applications. Specifically, each track will focus on the following topics:
Methods:
- Spatial and spatiotemporal data uncertainty
- Spatial statistics (e.g., geostatistics, spatial regression, point patterns, clustering methods, data fusion/assimilation) for uncertainty assessment and modeling
- Big data and learning (deep learning and machine learning) for uncertainty analysis
- The effect of location accuracy on trajectory/movement analyses/modeling
- Visualization of spatial data uncertainty
Applications:
- Spatial data collection/sampling
- Quantification of uncertainty in the applied remote sensing and other sensor technologies (e.g., drones, GPS, low-cost air/noise monitoring sensors)
- The effect of spatial uncertainty in environmental modeling (water, chemical, air, soil, etc.) and climate change (e.g., wildfire, hurricane, landslide, etc.)
- The propagation of uncertainty in the public health (e.g., environmental health, disease mapping, epidemic of infectious disease)
- The role of uncertainty in ecology (e.g., dispersion, migration, and invasion of species)
- Modeling spatial uncertainty in plant and animal epidemiology (e.g., emerging epidemics)
- Spatial econometrics under uncertainty