plate-tectonics-data-processing
/plate-tectonics-data-processing
Techniques for processing tectonic plate data, specifically using the PB2002 dataset. Use this skill when filtering points within plates, identifying plate boundaries, or working with global tectonic geometries in GeoPandas.
- Author
- cxcscmu ↗
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- SkillLearnBench ↗
- Licence
- MIT
- Last repository change
- 02.10.2026
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No signals detected. Repository changed on 02.10.2026, without references to retired models or APIs.
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What it does and when to use it
Techniques for processing tectonic plate data, specifically using the PB2002 dataset. Use this skill when filtering points within plates, identifying plate boundaries, or working with global tectonic geometries in GeoPandas.
Original author description
Techniques for processing tectonic plate data, specifically using the PB2002 dataset. Use this skill when filtering points within plates, identifying plate boundaries, or working with global tectonic geometries in GeoPandas.
How it works
- 1. Loading PB2002 Data
- 2. Filtering by Plate Name
- 3. Spatial Joins and Point-in-Polygon
- 4. Identifying Relevant Boundaries
- 5. Geometric Cleanup
SKILL.md preview
---
name: plate-tectonics-data-processing
description: Techniques for processing tectonic plate data, specifically using the PB2002 dataset. Use this skill when filtering points within plates, identifying plate boundaries, or working with global tectonic geometries in GeoPandas.
---
# Plate Tectonics Data Processing
This skill covers the use of the PB2002 (Bird, 2003) dataset for tectonic plate analysis.
## 1. Loading PB2002 Data
The PB2002 dataset typically consists of:
- `PB2002_plates.json`: Polygons representing the extent of each tectonic plate.
- `PB2002_boundaries.json`: LineStrings representing the boundaries between plates.
### Implementation
```python
import geopandas as gpd
plates_gdf = gpd.read_file("PB2002_plates.json")
boundaries_gdf = gpd.read_file("PB2002_boundaries.json")
```
## 2. Filtering by Plate Name
The `Plate` column (or similar) in the plates dataset identifies each plate.
- **Pacific Plate**: Often identified as "PA" or "Pacific".
```python
pacific_plate = plates_gdf[plates_gdf['Plate'] == 'PA']
```
## 3. Spatial Joins and Point-in-Polygon
To find which earthquakes occurred within a specific plate:
```python
# Assuming earthquakes_gdf and plates_gdf are in the same CRS
earthquakes_in_plates = gpd.sjoin(earthquakes_gdf, plates_gdf, how="inner", predicate="within")
# Filter for a specific plate
pacific_quakes = earthquakes_in_plates[earthquakes_in_plates['Plate'] == 'PA']
```
## 4. Identifying Relevant Boundaries
Boundaries are often labeled with the names of the two plates they separate (e.g., "PA-NA" for Pacific-North America).
To get all boundaries associated with the Pacific Plate:
```python
# Search for 'PA' in the boundary name/description column
pacific_boundaries = boundaries_gdf[boundaries_gdf['Name'].str.contains('PA')]
```
## 5. Geometric Cleanup
Tectonic datasets can sometimes have minor self-intersections or gaps.
- Use `gdf.geometry = gdf.geometry.buffer(0)` to fix minor validity issues.
- Use `gdf.union_all()` to create a single geometry representing the entire plate or boundary set.
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