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green-space-monitoring

Analyze multi-temporal GeoTIFF imagery to detect urban green space changes using NDVI/EVI indices.

Updated Jun 2, 2026
Search Tags:#change detection#remote sensing#NDVI#green space monitoring#EVI#governance report
One-click install
npx skills add https://github.com/bettercallfan/deerflow --skill green-space-monitoring
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: green-space-monitoring
Source: https://github.com/bettercallfan/deerflow/tree/main/skills/custom/remote_sensing_image/green-space-monitoring
Command: npx skills add https://github.com/bettercallfan/deerflow --skill green-space-monitoring

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires rasterio, numpy, scipy.ndimage, json, and includes scripts (resource) components.

What problem does it solve?

This Skill allows for the monitoring of urban green space coverage changes over time, providing insights into the gain and loss of green spaces using multi-temporal remote sensing imagery.

Core Features & Use Cases

  • Change Detection: Detects green space loss and gain areas based on NDVI/EVI vegetation indices.
  • Reporting: Generates governance reports for decision-making.
  • Use Case: For urban planning and environmental monitoring, the Skill can track the expansion and contraction of green spaces within a city, aiding in urban management and sustainability assessments.

Quick Start

Invoke the skill by mentioning "绿地变化监测" with inputs of the required image files and other relevant parameters.

Frequently Asked Questions about green-space-monitoring

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I monitor urban green space coverage changes using remote sensing imagery?▼

To monitor urban green space coverage changes, you analyze multi-temporal remote sensing GeoTIFF images to calculate NDVI and EVI vegetation indices, identifying spatial gain and loss areas over time.

How do I detect green space loss and gain areas from NDVI or EVI indices?▼

Detecting green space loss and gain requires calculating NDVI or EVI indices from multi-temporal GeoTIFF inputs and performing change detection analysis to highlight areas of vegetation expansion or contraction.

Can I generate a governance report for urban green space monitoring with this approach?▼

Yes, urban green space monitoring includes generating governance reports. After detecting vegetation index changes from multi-temporal imagery, the process outputs structured reports for urban planning decision-making.

Do I need GeoTIFF images to calculate vegetation indices for change detection?▼

Yes, GeoTIFF images are required as the primary input format. You need to supply multi-temporal GeoTIFF files and associated parameters to calculate NDVI/EVI indices and execute the change detection workflow.

What is the best way to track urban green space expansion and contraction for sustainability assessments?▼

The best way to track urban green space expansion and contraction is by applying NDVI and EVI vegetation index analysis to multi-temporal remote sensing imagery, which quantifies coverage changes for sustainability assessments.

Are there limitations when using NDVI and EVI for green space change detection in urban environments?▼

Green space change detection using NDVI and EVI depends on the quality and temporal alignment of input GeoTIFF imagery, meaning cloud cover or sensor calibration issues in remote sensing data can impact accuracy.

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