PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

GeoWave provides geospatial and temporal indexing on top of Accumulo, HBase, BigTable, Cassandra, Kudu, Redis, RocksDB, and DynamoDB.

MobilityDB is a geospatial trajectory data management & analysis platform, built on PostgreSQL and PostGIS.

Data visualization examples and tutorials from scratch. 数据可视化示例代码集与新手学习教程。

Spatiotemporal modeling of spatial transcriptomics

tsl: a PyTorch library for processing spatiotemporal data.

Self-supervised Spatiotemporal Learning via Video Clip Order Prediction

R package for Bayesian spatial and spatiotemporal GLMMs with possible extremes

Hierarchical Climate Regionalization

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

Sample JavaScript Aggregation Viewer using aggregation (lod) queries and rendering aggregation bins client side

Sample JavaScript Aggregation Viewer using Map Service queries with an Aggregation Renderer and rendering images server side

Revealing Occlusions with 4D Neural Fields (CVPR 2022 Oral) - Official Implementation

Physics-informed deep super-resolution of spatiotemporal data

Storing GIS data with temporal information (events data) in k-dimensional trees for efficient querying, designed to aid clustering algorithms such as DBSCAN.

Tools to analyze and manipulate climate (spatiotemporal) data. Also used by ClimateTools and ClimatePlots

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.

An R package for species geographical distribution and abundance modelling at high spatiotemporal resolution