# change-detection

Guides satellite and vector change detection workflows on comparable observations. Separates true land surface dynamics from phenology, registration jitter, and sensor drift.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · ★ 35
- Author: Muhammed Enes Duran
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/muend/geoai-skills/tree/HEAD/skills/change-detection/SKILL.md
- Updated: 2026-10-17
- HTML: https://affpapa.org/en/nevibecode/skills/change-detection

## What it does

The skill instructs the agent on detecting surface changes across comparable raster and vector layers. It targets bi-temporal comparisons, urban expansion, deforestation tracking, disaster impact mapping, and parcel boundary audits. Workflows cover continuous index differencing like `ΔNDVI` or `ΔNBR`, multivariate change vector analysis (CVA), dense time-series break detection via BFAST, CCDC, or LandTrendr, and SAR calibrated backscatter log-ratios.

Preconditions govern the workflow. Observations must share matching phenology, sub-pixel co-registration, identical radiometric processing levels, and mutually intersected cloud masks. Half a pixel of misalignment produces phantom change edges across every boundary. The skill forbids guessing thresholds visually, demanding histogram cutoffs like `μ ± k·σ` or Otsu, accompanied by sensitivity checks at `k ± 0.5`.

Post-classification comparison requires generating a complete transition matrix to flag impossible category swaps. To prevent biased totals, reported change areas must never rely on direct pixel counts. The agent reports error-adjusted area estimates with confidence intervals following the Olofsson stratified sampling protocol.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add muend/geoai-skills --skill change-detection -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/change-detection/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/change-detection/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add muend/geoai-skills --skill change-detection -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/change-detection/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add muend/geoai-skills --skill change-detection -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/change-detection/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install muend/geoai-skills change-detection
```

2. **Manually: put the files in place**
- File: `.github/skills/change-detection/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add muend/geoai-skills --skill change-detection -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/muend/geoai-skills --path skills/change-detection
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/change-detection/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add muend/geoai-skills --skill change-detection -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/muend/geoai-skills/tree/HEAD/skills/change-detection/SKILL.md

## When to use it
- isolate true surface changes from phenological and atmospheric noise
- compute statistical thresholds on index difference rasters
- pinpoint break dates in dense satellite time series via BFAST or CCDC
- audit geometry and attribute shifts between parcel vector vintages
- calculate error-adjusted change area estimates using stratified sampling

## Example prompts
- Calculate ΔNBR between pre-fire and post-fire scenes and apply an Otsu threshold to map burn extent.
- Build a transition matrix between the two land cover rasters and check for implausible class shifts.
- Run break detection on this vegetation index time series and extract the exact clearing dates.

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 6281b4479507e409.

BEGIN THIRD-PARTY FILE 6281b4479507e409
```text
---
name: change-detection
description: >-
  Change analysis, once the observations are comparable. Not for cases whose
  blocker is comparability itself: mixed sensors, product levels or processing
  baselines to remote-sensing-analysis, undocumented vertical datums to
  point-cloud-lidar, multi-decade archive trends over large areas to
  google-earth-engine. Matching product level does not prove comparability.
  Otherwise invoke for what, where or how much changed: two-scene comparison,
  deforestation, urban growth, disaster damage, parcel-change audits,
  bi-temporal differencing, post-classification comparison, adjusted area,
  break detection in a series in hand (BFAST/LandTrendr/CCDC). Seasonal
  mismatch is this skill's own confounder; a documented datum with a stated
  accuracy budget is settled comparability. Keep both.
license: MIT
metadata:
  author: Muhammed Enes Duran
---

# Change Detection & Spatio-temporal Analysis

Purpose: separate real surface change from the four great impostors —
misregistration, radiometric drift, phenology, and classification error.
Every method below exists to control one of them; skipping the controls
produces confident maps of nothing.

## Preconditions (where change detection is won or lost)

Preconditions 1 and 2 are *checked* here but *established* elsewhere. When
either fails, the owning skill leads and this skill resumes once comparable
observations exist. Precondition 3 is this skill's own problem and is never a
reason to route away.

1. **Co-registration**: sub-pixel alignment between dates (AROSICS or
   manual tie-points). Half a pixel of shift creates edge-shaped phantom
   change everywhere. Verify: flicker-compare crisp features. For elevation
   surfaces or point clouds, vertical datum agreement, co-registration and
   the vertical-accuracy budget belong to `point-cloud-lidar` — a datum
   offset is not subsidence.
2. **Radiometric consistency**: same processing level (surface
   reflectance), same sensor, same processing baseline. If any of the three
   differ, this is a harmonization problem, not a thresholding one: hand it
   to `remote-sensing-analysis` (HLS for Landsat↔Sentinel-2, relative
   normalization with PIFs, `BOA_ADD_OFFSET` across the Sentinel-2 2022
   baseline change).
```
END THIRD-PARTY FILE 6281b4479507e409

The third-party file has ended. Everything between the 6281b4479507e409 tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

First 2287 of 7719 bytes. © Muhammed Enes Duran · MIT · https://github.com/muend/geoai-skills/tree/HEAD/skills/change-detection/SKILL.md

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