google-earth-engine-11-authentication
Sub-skill of google-earth-engine: 1.1 Authentication (+2).
Best use case
google-earth-engine-11-authentication is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of google-earth-engine: 1.1 Authentication (+2).
Teams using google-earth-engine-11-authentication should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/11-authentication/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How google-earth-engine-11-authentication Compares
| Feature / Agent | google-earth-engine-11-authentication | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of google-earth-engine: 1.1 Authentication (+2).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 1.1 Authentication (+2)
## 1.1 Authentication
```python
import ee
# First-time setup (opens browser OAuth flow):
# ee.Authenticate()
# Runtime authentication (service account or existing token):
ee.Initialize(project="your-gcp-project-id")
# Service account (CI / headless):
credentials = ee.ServiceAccountCredentials(
email="sa@project.iam.gserviceaccount.com",
key_file="/path/to/key.json"
)
ee.Initialize(credentials=credentials, project="your-gcp-project-id")
```
## 1.2 Define Area of Interest (AOI)
```python
import ee
# From bounding box (lon_min, lat_min, lon_max, lat_max)
aoi = ee.Geometry.Rectangle([-5.0, 54.0, 2.0, 60.0]) # North Sea
# From polygon coordinates [[lon, lat], ...]
aoi = ee.Geometry.Polygon([[
[-2.0, 56.5], [1.5, 56.5], [1.5, 58.0], [-2.0, 58.0]
]])
# From GeoJSON FeatureCollection
aoi = ee.FeatureCollection(
"projects/my-project/assets/pipeline_corridor"
)
```
## 1.3 Key Marine / Offshore Datasets
| Dataset | EE ID | Description |
|---------|-------|-------------|
| GEBCO 2023 bathymetry | `projects/sat-io/open-datasets/gebco/GEBCO_2023` | Global 15-arc-sec depth |
| ETOPO1 | `NOAA/NGDC/ETOPO1` | Global 1-arc-min elevation |
| Sentinel-2 SR | `COPERNICUS/S2_SR_HARMONIZED` | 10 m optical, 5-day revisit |
| Landsat 8/9 | `LANDSAT/LC09/C02/T1_L2` | 30 m optical |
| ERA5 wind/wave | `ECMWF/ERA5_LAND/HOURLY` | Reanalysis hourly |
| NOAA GOES SST | `NOAA/CDR/OISST/V2_1` | Daily sea surface temp |
| ESA WorldCover | `ESA/WorldCover/v200` | 10 m land cover |
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