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satellite-imagery

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Analyze satellite imagery at planetary scale.

Education & Research#change detection#satellite imagery#ndvi#geotiff export#google earth engine#land use land cover#geemap
Authorxjtulyc
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill helps you compute vegetation and land-surface change insights from satellite imagery without manually downloading and processing huge geospatial datasets.

Core Features & Use Cases

  • NDVI and vegetation indices: Generate NDVI/EVI/other indices from Sentinel-2 or Landsat-style band sets.
  • LULC classification: Perform supervised land use/land cover classification using Random Forest with training labels.
  • Change detection: Compare two time windows (bitemporal) to quantify and classify change intensity.
  • GeoTIFF export: Export classified/change products to GeoTIFF for GIS workflows and reporting.
  • Use Case Example: Create a 2023 NDVI time series for an area of interest, then classify land cover and detect where vegetation changed between 2018 and 2023.

Quick Start

Use the satellite-imagery skill to compute a monthly NDVI time series for a selected region in 2023 using Google Earth Engine and geemap, then save the resulting plot.

Dependency Matrix

Required Modules

None required

Components

assets

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: satellite-imagery
Download link: https://github.com/xjtulyc/awesome-rosetta-skills/archive/main.zip#satellite-imagery

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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