skiba
Google Earth Engine point extractions for forestry research
What It Does
Skiba streamlines the process of extracting remotely sensed data from Google Earth Engine for forestry applications. It provides a simple interface for querying satellite imagery (Sentinel-2, Landsat, etc.) at specific coordinates, with built-in coordinate buffering to protect sensitive forest plot locations.
Originally developed by Tara Skiba, this fork extends the package for integration with FIA plot-level research workflows.
Key Features
GEE Point Extraction
Retrieve pixel/band values from any Google Earth Engine Image or ImageCollection for provided coordinates with date range filtering.
Location Privacy
Obscure confidential forest plot coordinates by generating buffered points within a specified radius to protect sensitive data.
Interactive Maps
Generate maps with built-in basemaps and GeoJSON overlays for visualizing extraction points and satellite coverage.
Flexible Export
Export results averaged by plot ID or as individual points, with Pandas DataFrame integration for downstream analysis.
Quick Start
pip install skibaimport ee
from skiba import point_extraction, buffer_coordinates
# Authenticate with Google Earth Engine
ee.Authenticate()
ee.Initialize(project='your-gee-project')
# Extract satellite data for forest plots
pe = point_extraction()
results = pe.get_coordinate_data(
df=forest_plots_df,
source="COPERNICUS/S2_SR",
start_date="2024-01-01",
end_date="2024-12-31"
)
# Buffer sensitive coordinates for privacy
bc = buffer_coordinates()
buffered = bc.buffer(df=forest_plots_df, radius_ft=100)Use Cases
- Extracting spectral band values from satellite imagery for forest inventory plots
- Linking ground-truth FIA plot data with vegetation indices (NDVI, EVI)
- Protecting confidential plot coordinates while enabling satellite data retrieval
- Batch processing large sets of forest monitoring coordinates against GEE datasets
Get Started
Check out the documentation and interactive demo to start extracting satellite data.