Geoskill: Coastline Change Monitor
Multi-temporal shoreline change rate analysis. Generates transects, computes Endpoint Rate (EPR) and Linear Regression Rate (LRR), and identifies erosion hotspots. Use when monitor…
ruiduobao
@ruiduobao
Install
$ openclaw skills install @ruiduobao/geoskill-coastline-change-monitorCoastline Change Monitor
Multi-temporal shoreline change analysis with transect-based rate computation.
Trigger
Use when the user wants to:
- Monitor coastline erosion/accretion over time
- Compute shoreline change rates (EPR/LRR)
- Identify erosion hotspots
- Compare shoreline positions across years
CLI Usage
# Vector shorelines
python scripts/coastline_change_monitor.py \
--shoreline-files shore_2015.geojson shore_018.geojson shore_2021.geojson \
--years 2015 2018 2021
# Raster water masks
python scripts/coastline_change_monitor.py \
--shoreline-files water_2015.tif water_2018.tif water_2021.tif \
--years 2015 2018 2021 \
--transect-spacing 50 --transect-length 300
Parameters
| Parameter | Default | Description |
|---|---|---|
--shoreline-files | required | Shoreline files (one per year) |
--years | auto | Years for each file |
--transect-spacing | 100 | Spacing between transects |
--transect-length | 500 | Length of each transect |
--erosion-threshold | -1.0 | EPR threshold for hotspots (m/yr) |
--output-dir | ./coastline-output | Output directory |
Output
| File | Description |
|---|---|
shorelines.geojson | All shorelines with year attribute |
transects.geojson | Generated transect lines |
change_rates.csv | EPR/LRR per transect |
erosion_hotspots.geojson | Significant erosion segments |
report.html | HTML summary report |
output-manifest.json | Machine-readable manifest |
Exit Codes
| Code | Meaning |
|---|---|
| 0 | Success |
| 2 | Argument error |
| 3 | Dependency missing |
| 6 | Data validation failure |
| 7 | Processing failure |
数据下载
本 skill 可自动从 Microsoft Planetary Computer 下载数据 (无需 API key):
python coastline_change_monitor.py --bbox 116,39,117,40 --date-range 2024-06-01,2024-06-30 --output-dir <tmp>
--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 <path.geojson>: 替代 --bbox 的 GeoJSON 多边形--cache-dir <path>: 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)。
Top skills in this category
Openclaw Command Center
@jontsaiMission control dashboard for OpenClaw - real-time session monitoring, LLM usage tracking, cost intelligence, and system vitals. View all your AI agents in o...
Interview Simulator
@wscatsSimulates mock interviews for any role and experience level with tailored technical, behavioral, and case questions plus detailed feedback and scoring.
moltbook-interact
@lunarcmdInteract with Moltbook social network for AI agents. Post, reply, browse, and analyze engagement. Use when the user wants to engage with Moltbook, check their feed, reply to posts, or track their activity on the agent social network.
Web Development
@ivangdavilaBuild, debug, and deploy websites using HTML, CSS, JavaScript, and modern frameworks following production best practices.
Baidu Wenku AI picture book of video
@ide-rea百度文库AI绘本是一个基于人工智能制作绘本视频的工具,支持生成静态绘本和动态绘本(URL输出)。能帮助文本内容创作者们在缺乏绘画技能的情况下,快速生成精美绘本视频,提高内容生产效率。无论是在儿童教育、亲子互动、品牌营销,还是在社交媒体内容创作等领域都能应用。