Lists (6)
Stars
A curated list of papers that focus on how to represent Earth data in embedding space — spatial, temporal, or semantic — and how those embeddings behave or are applied.
This repository contains the official implementation of the paper "LandSegmenter: Towards a Flexible Foundation Model for Land Use and Land Cover Mapping".
An AI powered geospatial application that allows you to explore and visualize Earth science data using natural language.
A cluster computing framework for processing large-scale geospatial data
Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnot…
The Clay Foundation Model - An open source AI model and interface for Earth
Implementation of 'DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation' [CVPR 2022]
[NeurIPS 2021] LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation
Reproduce the training of DPT-based segmentation head in the Dino-v3 paper.
Semantic segmentation of satellite imagery to classify land cover types using deep learning models.
[ICCV'25 oral] Official Code for "LoftUp: Learning a Coordinate-Based Feature Upsampler for Vision Foundation Models"
A Python package to super-resolve Sentinel-2 satellite imagery up to 2.5 meters.
DuckDB is an analytical in-process SQL database management system
Tool to convert geopandas vector data into rasterized xarray data.
🐍 Geometric Computer Vision Library for Spatial AI
a pure-rust 2D rasterizer for geospatial applications
Delineate Anything: Resolution-Agnostic Field Boundary Delineation on Satellite Imagery. Foundation Model for Field Boundary Delineation.
Interactive land cover classification of TESSERA embeddings
[NeurIPS2021] A plant image dataset with high label ambiguity and a long-tailed distribution