urban-greenspace-assessment

Extract geospatial data to evaluate urban green spaces and produce reports.

Updated Jun 2, 2026

Search Tags:#remote sensing #equity analysis #urban governance #green space #NDVI

Ready to run

npx skills add https://github.com/bettercallfan/deerflow --skill urban-greenspace-assessment

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: urban-greenspace-assessment
Source: https://github.com/bettercallfan/deerflow/tree/main/skills/custom/remote_sensing_image/urban-greenspace-assessment
Command: npx skills add https://github.com/bettercallfan/deerflow --skill urban-greenspace-assessment

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires rasterio, scipy, shapely, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill addresses the challenge of evaluating urban green-space coverage, connectivity, service accessibility, and ecological function completeness.

Core Features & Use Cases

Green-Space Coverage: Calculates the percentage of green spaces within a specified area.
Connectivity and Accessibility: Identifies the accessibility and connectivity of green spaces within a community.
Landscape Metrics: Measures landscape metrics like area, patch density, and connectivity.
Equity Analysis: Optionally analyzes the equity of green-space distribution.

Quick Start

Assess the green-space coverage and accessibility in the 'city-area.geojson' using the urban-greenspace-assessment skill.

Frequently Asked Questions about urban-greenspace-assessment

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

FAQPage Schema

How do I calculate urban green-space coverage and NDVI from high-resolution imagery?▼

You can calculate urban green-space coverage and NDVI by processing high-resolution imagery with rasterio, which extracts geospatial data to evaluate vegetation density and map green areas within a specified region.

Can I analyze the equity of green-space distribution using population data?▼

Yes, you can analyze green-space equity by integrating optional population data, allowing you to assess accessibility and connectivity of green spaces across different community demographics.

What's the best way to measure landscape metrics like patch density for urban green spaces?▼

The best way to measure landscape metrics like patch density and connectivity is by using scipy and shapely to compute geospatial landscape features, producing detailed reports on green-space ecological functions.

Does this urban green-space assessment work with GeoJSON files for community accessibility reporting?▼

Yes, this urban green-space assessment processes GeoJSON files to identify green-space accessibility and connectivity within a community, generating comprehensive reports on service availability and landscape coverage.

Do I need rasterio and shapely to map urban green spaces and compute landscape metrics?▼

Yes, you need rasterio to handle high-resolution imagery for NDVI calculation and shapely to process geometric boundaries, as these dependencies are essential for green-space mapping and landscape metric computation.