# Jack-bo1220/Awesome-Remote-Sensing-Foundation-Models

Repository: https://github.com/Jack-bo1220/Awesome-Remote-Sensing-Foundation-Models
Canonical: https://ross.abutalabs.com/products/awesome-remote-sensing-foundation-models
Homepage: https://jack-bo1220.github.io/project/RSFM.html
License Family: other
Last push: 2026-05-07T14:14:37+00:00

## Health v2 (maintenance only)
Score: 63/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 81, release rhythm 35, longevity 71
- inputs: {"age_days": 1006, "days_push": 118, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1928, forks 175 (observed 2026-08-28T04:05:55.774594+00:00)

## What it is
A curated awesome-list cataloging papers, code, pre-trained weights, datasets, and benchmarks for Remote Sensing Foundation Models (RSFMs). It organizes entries by model type (vision, vision-language, generative, agents) and includes a searchable web index built from the README.

## Use cases
- find pretrained foundation models for satellite imagery
- discover remote sensing datasets and benchmarks
- survey the state of the art in earth observation AI
- locate code and weights for remote sensing vision-language models
- research geospatial self-supervised learning papers
- compare remote sensing foundation model benchmarks

## When to choose
- you need a comprehensive, actively updated index of RSFM research and resources
- you are starting research or a project involving satellite/aerial imagery models
- you want links to papers, code, and weights in one place

## When to avoid
- you need runnable software rather than a reference catalog
- your domain is unrelated to remote sensing or geospatial imagery
- you need a single maintained model rather than a survey of many

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, machine-learning, computer-vision
- domain: artificial-intelligence, deep-learning, awesome-lists, image-processing
- platform: -
- tags: awesome-list, remote-sensing, foundation-models, satellite-imagery, earth-observation, research-index, pretrained-weights, datasets, benchmarks, web-server

## Member repositories
- Jack-bo1220/Awesome-Remote-Sensing-Foundation-Models (main) score 63

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:55.774594+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:09:06.334911+00:00, confidence not recorded.
  - readme: https://github.com/Jack-bo1220/Awesome-Remote-Sensing-Foundation-Models (fetched 2026-08-28T04:05:55.774594+00:00, sha 17e546c90c7d)
  - homepage: https://jack-bo1220.github.io/project/RSFM.html (fetched 2026-08-29T10:48:51.502978+00:00, sha 713929a9d7df)
- Data as of 2026-08-30T08:39:29.467469+00:00.