There are 4 repositories under spatiotemporal topic.
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
MobilityDB is a geospatial trajectory data management & analysis platform, built on PostgreSQL and PostGIS.
GeoWave provides geospatial and temporal indexing on top of Accumulo, HBase, BigTable, Cassandra, Kudu, Redis, RocksDB, and DynamoDB.
Data visualization examples and tutorials from scratch. 数据可视化示例代码集与新手学习教程。
tsl: a PyTorch library for processing spatiotemporal data.
Spatiotemporal modeling of spatial transcriptomics
Self-supervised Spatiotemporal Learning via Video Clip Order Prediction
Revealing Occlusions with 4D Neural Fields (CVPR 2022 Oral) - Official Implementation
R package for Bayesian spatial and spatiotemporal GLMMs with possible extremes
Tools to analyze and manipulate climate (spatiotemporal) data. Also used by ClimateTools and ClimatePlots
PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning
Cooperative Attack Algorithm for UAVs is focusing on the cooperative attack problem of UAV swarm system with flight time and attack angle constraints. It includes an efficient attack framework for real-time planning and control of drones.
ST-Hadoop is an open-source MapReduce extension of Hadoop designed specially to analyze your spatio-temporal data efficiently
A Python Package for Adaptive Spatio-Temporal Exploratory Model (AdaSTEM)
Sample JavaScript Aggregation Viewer using Map Service queries with an Aggregation Renderer and rendering images server side
A python library for lossy compression/serialization of trajectory data based on Google's Encoded Polyline Algorithm Format
Sample JavaScript Aggregation Viewer using aggregation (lod) queries and rendering aggregation bins client side
Javascript library for STAC SpatioTemporal Asset Catalog
Trajectory data lossy compression/serialization library based on Google's Encoded Polyline Algorithm Format
A professional list of Papers on AI for Spatial Interpolation in AI conferences and journals.
Investigating how carbon emissions, particulate matter, and climate variables/indices impact mortality from chronic respiratory disease. Working with pollutant, climate, mortality, population, and geographic datasets. Modeling with Random Forest regression.
Analyzed mental health service utilization in Thailand using spatial pattern analysis and cluster analysis.
An R package for species geographical distribution and abundance modelling at high spatiotemporal resolution
Storing GIS data with temporal information (events data) in k-dimensional trees for efficient querying, designed to aid clustering algorithms such as DBSCAN.
Code, logs, and final models for SIGSPATIAL SpatialEpi '22: Spatiotemporal Disease Case Prediction using Contrastive Predictive Coding.
Introductory Code For Doing Simple Avalanche Analysis (Criticality In The Brain) Mainly Through Power Law Analysis In Log-Log Space and Temporal Coarse Graining (K)
Twitter Semantic Data Mining for Harvey Hurricane Credible Event Detection
Multi-step Hourly Temperature Prediction Using Vehicle-IoT and ML
STEHealth is a shiny application for analyzing space-time patterns, cluster detection, and association with risk factors of health outcomes.
Code analysis for "Impact of intensified control strategies on incidence of visceral leishmaniasis in a highly endemic district of Bihar, India: an interrupted time series analysis" Kumar, Siddiqui, Pollington et al.
Data and R code for "Environmental DNA (eDNA) metabarcoding differentiates between micro-habitats within the rocky intertidal" (Shea & Boehm)
Extracts low speed segments from spatiotemporal trajectories using moving median of speed. Fast and robust. Adaptively determines the parameters from the data, instead of setting objective, arbitrary parameters. Each trajectory in a set of trajectories will have unique subjective parameters.