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water-quality-monitoring

Analyze multispectral imagery to retrieve water quality parameters and detect pollution hotspots.

Updated Jun 2, 2026
Search Tags:#water quality#remote sensing#pollution monitoring#water analysis#environmental assessment
One-click install
npx skills add https://github.com/bettercallfan/deerflow --skill water-quality-monitoring
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: water-quality-monitoring
Source: https://github.com/bettercallfan/deerflow/tree/main/skills/custom/remote_sensing_image/water-quality-monitoring
Command: npx skills add https://github.com/bettercallfan/deerflow --skill water-quality-monitoring

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill analyzes multispectral imagery to retrieve water quality parameters, identify pollution anomalies, and track temporal trends, assisting in river and lake supervision, drinking water source protection, and blackwater body governance.

Core Features & Use Cases

  • Water Quality Parameter Retrieval: Extracts key water quality parameters like chlorophyll-a, suspended sediment, and turbidity from multispectral imagery.
  • Pollution Anomaly Detection: Identifies pollution hotspots and suspected outfalls.
  • Temporal Trend Analysis: Tracks and reports spatiotemporal changes in water quality.
  • Use Case: For instance, monitor the water quality of a river during the rainy season and identify areas with high pollution levels.

Quick Start

To analyze water quality in the 'river.tif' image, provide the 'river.geojson' boundary file and optional historical reference data.

Frequently Asked Questions about water-quality-monitoring

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

FAQPage Schema
How do I extract water quality parameters from multispectral imagery?▼

Extracting water quality parameters from multispectral imagery involves applying remote sensing analysis to retrieve chlorophyll-a, suspended sediment, and turbidity, identifying pollution hotspots and outfalls across river and lake supervision areas.

What is remote sensing analysis used for in drinking water source protection?▼

Remote sensing analysis supports drinking water source protection by retrieving water quality parameters from multispectral imagery, detecting pollution anomalies, and tracking spatiotemporal trends to ensure water safety.

Can I use rasterio and numpy for water quality monitoring of rivers?▼

Yes, water quality monitoring utilizes rasterio and numpy for geospatial data processing and remote sensing analysis, handling multispectral imagery to extract environmental assessment parameters for river supervision.

How do I track temporal trends in water pollution using multispectral imagery?▼

Track temporal trends in water pollution by processing multispectral imagery against historical reference data, analyzing spatiotemporal changes to report water quality variations and identify emerging pollution hotspots.

Does water quality monitoring with remote sensing require geospatial data processing?▼

Yes, water quality monitoring with remote sensing requires geospatial data processing to handle multispectral imagery, utilizing Python libraries like rasterio and pyproj for spatial boundary analysis.

What's the best way to identify pollution hotspots and suspected outfalls in lakes?▼

Identify pollution hotspots and suspected outfalls in lakes by analyzing multispectral imagery with remote sensing techniques, detecting pollution anomalies within specified geojson boundary files.

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