GeoAI: Artificial Intelligence for Geospatial Data

Code and datasets for paper "K2: A Foundation Language Model for Geoscience Knowledge Understanding and Utilization" in WSDM-2024

A collection of papers related to Geo-spatial Information Science in NeurIPS 2024.

A collection of Jupyter notebook examples for using GeoAI

A project template for spatial data science projects marrying best practices from the respective disciplines of Geography and Artificial Intelligence.

A collection of papers related to Geo-spatial Information Science in CVPR 2025.

AISdb Python package for smart AIS data storage and itegration.

Template for performing GeoAI retail analysis using ArcGIS and Machine Learning.

This repo contains reports obtained from GeoAI development performed by The Directorate of Thematic Survey and Mapping of ATR/BPN

Evaluation of the quality of LLM geo knowledge

The image viewer is a simple-to-use Microsoft PowerBI visual for stepping through images.

A lightweight frontend app using transformers.js showcasing the use of semantic similarity for geospatial applications such as geosocial media. Building on Overturempas Places, dynamically loading data from a singe 9Gb flatgeobuf file.

Codes and data for a published work "A method to evaluate task-specific importance of spatio-temporal units based on explainable artificial intelligence" (https://doi.org/10.1080/13658816.2020.1805116)

A geospatial package

Finetuning Large Foundation Model for finding Locus Bredding Pattern

The 3rd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data (GeoSearch)

Protect what matters most - your family's only home, Earth. This decentralized nervous system lets idle devices work like forest networks, helping Earth sense, verify, and heal environmental challenges naturally. Join us in awakening Earth's intelligence. 🌍

This repository focuses on GeoAI-based ground-level NO₂ estimation, developing machine learning models to predict surface NO₂ concentrations using only public remote sensing data as predictor variables.

In this repository, I will share exercises and resources that have enriched my learning journey towards my dream job. I'll include coding scripts and exercises I've worked on and learned from, both in geospatial data science and other related fields.