Data & analysis

Geoskill: Mine Disturbance Monitor

Try it

Monitor surface disturbance at mining sites using multi-temporal optical/SAR/DEM data. Detect bare land, pits, dumps, roads, and vegetation removal. Track disturbance objects across years, identify boundary violations, and generate area statistics.

What it does

Monitor surface disturbance at mining sites using multi-temporal optical/SAR/DEM data. Detect bare land, pits, dumps, roads, and vegetation removal. Track disturbance objects across years, identify boundary violations, and generate area statistics.

The skill document

Mine Disturbance Monitor

Monitor surface disturbance at mining sites using multi-temporal optical/SAR/DEM data. Detect bare land, pits, dumps, roads, and vegetation removal. Track disturbance objects across years, identify disturbances outside mine boundaries (compliance concern), and generate area statistics with evidence.

Trigger

Use when the user wants to:

  • Monitor mine surface disturbance over multiple years
  • Detect bare land / pit / dump / road / vegetation removal expansion
  • Identify disturbances outside mine permit boundaries
  • Track disturbance object status (new / expanding / stable / reclaimed)
  • Generate disturbance area statistics by year and type

CLI Usage

python scripts/mine_disturbance_monitor.py \
  --mine-boundary mine_boundary.geojson \
  --years 2020 2021 2022 2023 \
  --image-dir ./imagery \
  --disturbance-types pit dump road bare \
  --min-area 100 \
  --buffer 500 \
  --output-dir ./disturbance-output

Parameters

ParameterRequiredDefaultDescription
--mine-boundaryYesMine permit boundary (GeoJSON)
--yearsYesList of years to analyze
--image-dirYesDirectory with per-year imagery (YYYY.tif)
--disturbance-typesNopit dump road bareDisturbance types to detect
--compare-demNoOptional DEM for pit/dump classification
--min-areaNo100Minimum disturbance area (m²)
--bufferNo0Buffer distance around boundary (m)
--output-dirNodisturbance-outputOutput directory
--versionNoShow version

Output

FileDescription
disturbance_by_year.geojsonAll disturbance objects with year, type, area, status
disturbance_type.tifRaster map of disturbance types
outside_boundary.geojsonDisturbances outside mine boundary (compliance)
summary.xlsxArea statistics by year and type

Exit Codes

CodeMeaning
0Success
2Argument error
3Dependency missing
6Validation error
7Processing failure

数据下载

本 skill 可自动从 Microsoft Planetary Computer 下载数据 (无需 API key):

python mine_disturbance_monitor.py --bbox 116,39,117,40 --date-range 2024-06-01,2024-06-30 --output-dir 
  • --bbox W,S,E,N: WGS-84 边界框 (西, 南, 东, 北)
  • --date-range START,END: 日期范围 (YYYY-MM-DD,YYYY-MM-DD)
  • --aoi-file : 替代 --bbox 的 GeoJSON 多边形
  • --cache-dir : 缓存目录 (默认 ~/.geoskill_cache)

当用户只给 --bbox + --date-range (没有 --image) 时,skill 自动下载数据。 当用户给 --image 时,走原文件路径 (向后兼容)。

Related skills

Detect forest disturbance from multi-temporal NDVI. Use when the user wants to analyze changes, detect hazards, or generate assessment reports.

1 installs

Monitor construction progress from multi-temporal satellite imagery. Classifies project stages (clearing, earthwork, foundation, structure, finishing, completed) using spectral indices and detects stagnation. Use when tracking infrastructure projects, auditing construction timelines, or generating progress reports from remote sensing data.

1 installs

Monitor forest canopy vitality decline, drought stress, pest damage, or wind throw from multi-temporal spectral indices. Distinguishes short-term fluctuations from persistent decline using historical baselines, persistence state machines, and climate attribution. Use when assessing forest health, detecting anomalies, or planning field sampling.

1 installs

Screen tailings dam bodies, reservoir areas, catchments, and downstream exposure using remote sensing change detection. Produce patrol priorities based on hazard, exposure, and evidence.

1 installs

Analyze land subsidence from InSAR displacement data. Use when the user wants to analyze changes, detect hazards, or generate assessment reports.

1 installs

Detect and quantify urban expansion from multi-temporal built-up rasters. Use when the user wants to analyze changes, compare multi-temporal rasters, compute indices, or generate assessment reports.

1 installs