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EORST - Earth Observation and Remote Sensing Toolkit
A Rust library for simplifying raster processing pipelines in Earth observation workflows.
Quick Start
[]
= "1.0"
Highlights
- Parallel read/write - Block-based parallel processing with rayon
- On-the-fly reprojection - Automatic image alignment and coordinate transformation
- Point sampling - Efficient raster value extraction at point locations
- Time series analysis - Multi-temporal data handling
- Band math - Built-in arithmetic operations on raster bands
- ML integration - Optional LightGBM and OpenCV support
Example
From STAC Query (ODC-style workflow)
use ;
use ;
use NaiveDate;
use PathBuf;
// Query satellite imagery from a STAC catalog
let query = new
.start_date
.end_date
.cloudcover
.canonical_bands
.build;
// Download and create a RasterDataset
let feature_collection = query.get?;
let rds = from_stac_query
.block_size
.build;
// Process with `apply` - receives RasterDataBlock with metadata
rds.?;
From Local Files with Layer Selection
use ;
use Array4;
use PathBuf;
// Load specific bands with custom names
let data_source = from_file
.bands // Band indices
.set_names // Assign names
.build;
let rds = from_source
.block_size
.build;
// Process with automatic layer selection by name
rds.?;
Documentation
Full documentation: https://docs.rs/eorst
See also: EORST Documentation Site
Features
| Feature | Description |
|---|---|
use_opencv |
Computer vision operations (erosion, dilation, etc.) |
use_lgbm |
LightGBM machine learning integration |
use_polars |
Polars DataFrame support for zonal statistics |
use_rss |
rss_core integration for remote sensing workflows |
License
LGPL-3.0-or-later