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gulabpatel / AIAg

Smart Agriculture, Remote Sensing, GIS, geemap, leafmap, Computer Vision, LLMs

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10 Free GIS Data Source

A nice collection of free #GIS data sources "10 ๐…๐ซ๐ž๐ž ๐†๐ˆ๐’ ๐ƒ๐š๐ญ๐š ๐’๐จ๐ฎ๐ซ๐œ๐ž๐ฌ: ๐๐ž๐ฌ๐ญ ๐†๐ฅ๐จ๐›๐š๐ฅ ๐‘๐š๐ฌ๐ญ๐ž๐ซ ๐š๐ง๐ ๐•๐ž๐œ๐ญ๐จ๐ซ ๐ƒ๐š๐ญ๐š๐ฌ๐ž๐ญ๐ฌ":

  1. ๐๐š๐ญ๐ฎ๐ซ๐š๐ฅ ๐„๐š๐ซ๐ญ๐ก ๐ƒ๐š๐ญ๐š: https://lnkd.in/diZSdcKt
  2. ๐”๐’๐†๐’ ๐„๐š๐ซ๐ญ๐ก ๐„๐ฑ๐ฉ๐ฅ๐จ๐ซ๐ž๐ซ: https://lnkd.in/daNe97jE
  3. ๐Ž๐ฉ๐ž๐ง๐’๐ญ๐ซ๐ž๐ž๐ญ๐Œ๐š๐ฉ: https://lnkd.in/dRECBK7q
  4. ๐„๐ฌ๐ซ๐ข ๐Ž๐ฉ๐ž๐ง ๐ƒ๐š๐ญ๐š ๐‡๐ฎ๐›: https://hub.arcgis.com/
  5. ๐๐€๐’๐€โ€™๐ฌ ๐’๐จ๐œ๐ข๐จ๐ž๐œ๐จ๐ง๐จ๐ฆ๐ข๐œ ๐ƒ๐š๐ญ๐š ๐š๐ง๐ ๐€๐ฉ๐ฉ๐ฅ๐ข๐œ๐š๐ญ๐ข๐จ๐ง๐ฌ ๐‚๐ž๐ง๐ญ๐ž๐ซ (๐’๐„๐ƒ๐€๐‚): https://lnkd.in/d3YfbMiP
  6. ๐Ž๐ฉ๐ž๐ง ๐“๐จ๐ฉ๐จ๐ ๐ซ๐š๐ฉ๐ก๐ฒ: https://opentopography.org
  7. ๐”๐๐„๐ ๐„๐ง๐ฏ๐ข๐ซ๐จ๐ง๐ฆ๐ž๐ง๐ญ๐š๐ฅ ๐ƒ๐š๐ญ๐š ๐„๐ฑ๐ฉ๐ฅ๐จ๐ซ๐ž๐ซ: https://lnkd.in/dXN9gMgD
  8. ๐๐€๐’๐€ ๐„๐š๐ซ๐ญ๐ก ๐Ž๐›๐ฌ๐ž๐ซ๐ฏ๐š๐ญ๐ข๐จ๐ง๐ฌ (๐๐„๐Ž): https://neo.gsfc.nasa.gov
  9. ๐’๐ž๐ง๐ญ๐ข๐ง๐ž๐ฅ ๐’๐š๐ญ๐ž๐ฅ๐ฅ๐ข๐ญ๐ž ๐ƒ๐š๐ญ๐š: https://lnkd.in/dJmAy47y
  10. ๐“๐ž๐ซ๐ซ๐š ๐๐จ๐ฉ๐ฎ๐ฅ๐ฎ๐ฌ: https://terra.ipums.org ๐‘๐ž๐š๐ ๐ญ๐ก๐ž ๐Ÿ๐ฎ๐ฅ๐ฅ ๐š๐ซ๐ญ๐ข๐œ๐ฅ๐ž ๐ก๐ž๐ซ๐ž: https://lnkd.in/dFbCFwcK DataSource

๐“๐จ๐จ๐ฅ๐ฌ ๐ญ๐จ ๐ฆ๐š๐ข๐ง๐ฅ๐ฒ ๐ฏ๐ข๐ฌ๐ฎ๐š๐ฅ๐ข๐ณ๐ž ๐ง๐ž๐ญ๐ฐ๐จ๐ซ๐ค๐ฌ:

๐๐ž๐ญ๐ฐ๐จ๐ซ๐ค ๐ฅ๐ข๐›๐ซ๐š๐ซ๐ข๐ž๐ฌ ๐ข๐ง ๐๐ฒ๐ญ๐ก๐จ๐ง:

9 use cases of Deep Learning with Imagery and tips on how to get started.

  1. Extracting building footprints Instance Segmentation Models: MaskRCNN

  2. Identifying new construction Change Detection Models: STA-Net ChangeDetector

  3. Classifying homes as damaged or not after a forest fire Object Classification Models: FeatureClassifier with ResNet, Inception, VGG backbones

  4. Detecting swimming pools Object Detection Models: SingleShotDetector(SSD), RetinaNet, YOLO, FasterRCNN, MMDetection

  5. Road extraction Road Extraction Models: MultiTaskRoadExtractor

  6. Crop Classification Imagery Time Series Classification Models: PSETAE

  7. Land cover classification Pixel Classification Models: UNetClassifier, PSPNetClassifier, DeepLab, MMSegmentation

  8. Mapping residential parcels Edge Detection Models: BDCNEdgeDetector, HEDEdgeDetector, ConnectNet

  9. Increasing (upscaling) image resolution Image Enhancement Models: SuperResolution

How to start?

  1. Prepear your input imagery data, and generate true-ortho with ArcGIS Reality for best accuracy.
  2. ArcGIS API for Python + arcgis.learn module - Functions for calling the Deep Learning Tools https://lnkd.in/dCfsifZh
  3. Explore and test pre-trained models - ArcGIS Living Atlas https://lnkd.in/dQsE5FXp
  4. Use ArcGIS tools to improve or train your own models (see guide in each DLPK)
  5. Build own Apps & Solutions

Application of AI in Agriculture

  1. Crop and soil monitoring
  2. Insect and plant disease detection
  3. Livestock health monitoring
  4. Intelligent spraying
  5. Automatic weeding
  6. Aerial survey and imaging
  7. Produce grading and sorting
  8. The future of AI in Agriculture: Farmers as AI engineers?

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Smart Agriculture, Remote Sensing, GIS, geemap, leafmap, Computer Vision, LLMs

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