RRepoGEO

REPOGEO REPORT · LITE

acgeospatial/awesome-earthobservation-code

Default branch master · commit ff6f976f · scanned 5/24/2026, 11:17:35 AM

GitHub: 1,345 stars · 247 forks

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface acgeospatial/awesome-earthobservation-code, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Clarify repo's identity as a curated list in the README's opening

    Why:

    CURRENT
    A curated list of awesome tools, tutorials, code, helpful projects, links, stuff about Earth Observation and Geospatial stuff! Please note that this is <b>not</b> offically an awesome list.
    COPY-PASTE FIX
    A curated list of awesome tools, tutorials, code, helpful projects, links, and resources focused on Earth Observation and Geospatial topics. This repository serves as a comprehensive index for developers, researchers, and data scientists seeking programmatic resources in the EO domain.
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://github.com/acgeospatial/awesome-earthobservation-code
  • mediumtopics#3
    Add topics that emphasize its nature as a curated list/resource

    Why:

    CURRENT
    awesome, awesome-list, earth-observation, geospatial-data, google-earth-engine, remote-sensing, satellite-data, satellite-imagery
    COPY-PASTE FIX
    awesome, awesome-list, earth-observation, geospatial-data, google-earth-engine, remote-sensing, satellite-data, satellite-imagery, curated-list, resource-directory, learning-resources, geospatial-code

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface acgeospatial/awesome-earthobservation-code
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Earth Engine
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Earth Engine · recommended 1×
  2. qgis/QGIS · recommended 1×
  3. ESRI ArcGIS Pro · recommended 1×
  4. ArcGIS Online · recommended 1×
  5. Sentinel Hub · recommended 1×
  • CATEGORY QUERY
    Where can I find comprehensive resources and tools for earth observation and geospatial analysis?
    you: not recommended
    AI recommended (in order):
    1. Google Earth Engine
    2. QGIS (qgis/QGIS)
    3. ESRI ArcGIS Pro
    4. ArcGIS Online
    5. Sentinel Hub
    6. GDAL/OGR (OSGeo/gdal)
    7. OpenStreetMap
    8. Overpass API (drolbr/Overpass-API)
    9. Nominatim (osm-search/Nominatim)
    10. Jupyter Notebooks (jupyter/notebook)
    11. GeoPandas (geopandas/geopandas)
    12. Rasterio (rasterio/rasterio)
    13. scikit-learn (scikit-learn/scikit-learn)
    14. TensorFlow (tensorflow/tensorflow)
    15. PyTorch (pytorch/pytorch)

    AI recommended 15 alternatives but never named acgeospatial/awesome-earthobservation-code. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best open-source libraries for remote sensing and satellite imagery processing?
    you: not recommended
    AI recommended (in order):
    1. GDAL/OGR
    2. Rasterio
    3. xarray
    4. OpenCV
    5. Orfeo ToolBox (OTB)
    6. scikit-image
    7. eo-learn

    AI recommended 7 alternatives but never named acgeospatial/awesome-earthobservation-code. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of acgeospatial/awesome-earthobservation-code?
    pass
    AI did not name acgeospatial/awesome-earthobservation-code — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts acgeospatial/awesome-earthobservation-code in production, what risks or prerequisites should they evaluate first?
    pass
    AI named acgeospatial/awesome-earthobservation-code explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo acgeospatial/awesome-earthobservation-code solve, and who is the primary audience?
    pass
    AI did not name acgeospatial/awesome-earthobservation-code — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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  • Brand-free category queries5 vs 2 in Lite
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