ctreeskit 0.1.2

CTrees toolkit for geospatial analysis and forest carbon monitoring. Core features include xarray-based analysis tools.

CTrees Tools - Beta Version

CTreesKit is a public package used split into two sections, "arraylake_tools" which allows a simplified way of converting from geotiffs -> zarr format and saving the data into arraylake (by Earthmover). "xr_analyzer" is a small wrapper for xarray functions used for zonal stats that use the arraylake datasource as the input. These can also be used with Earthmover's opensource icechunk format as well! Tutorials to come in May 2025 with additional functionality. Slide Deck for CNG Conference about this pip package

Open Source Components (ctreeskit-core)

Current:

pip install git+https://github.com/ctrees-products/ctreeskit.git

(( Future -> To Be Implemented June 2025))

pip install ctreeskit

Quick Links

• Installation Guide
• Xr Analyzer ReadMe
• Arraylake Tools ReadMe

Table of Contents

1. Installation
   • PyPI Installation
   • GitHub Installation
   • Development Setup
   • Testing
   • Contributing
2. Features
3. API Reference
   • XR Spatial Processor Overview
   • XR Zonal Stats Overview
   • Arraylake Tools Overview

Installation

You can install ctreeskit either from PyPI or directly from GitHub:

From PyPI

pip install ctreeskit

From GitHub

pip install git+https://github.com/ctrees-products/ctreeskit.git

Development Installation

For development, you can install with all dependencies:

# Clone the repository
git clone https://github.com/ctrees-products/ctreeskit.git
cd ctreeskit

# Create and activate virtual environment
python -m venv venv
source venv/bin/activate  # On macOS/Linux

# Install in editable mode with all dependencies
pip install -e ".[all]"

Dependencies

• xarray
• rioxarray (for spatial operations)
• numpy
• shapely
• pyproj
• s3fs (for Amazon S3 storage access)
• python > 3.11

Testing

To run the tests for the ctreeskit package, navigate to the project directory and execute:

pytest -m tests

Contributing

Contributions are welcome! Please submit a pull request or open an issue for any enhancements or bug fixes.

Features

• Spatial processing with xarray DataArrays
• Area calculations and geometry data
• Arraylake Ingestion tools

A Python module for efficient geospatial operations on raster data using xarray, with support for integrating vector geometries and calculating areas.

API Reference

XrSpatialProcessor

Xr Spatial Processor ReadMe

This module provides tools to:

• Process geospatial vector data (from files or objects) into standardized geometry containers
• Clip rasters to geometries or bounding boxes
• Align and resample rasters to match reference grids
• Calculate accurate cell areas for geographic rasters
• Create weighted masks based on geometry-pixel intersections

XrZonalStats

Xr Zonal Stats ReadMe

This module provides tools to:

• Calculate area statistics for different classes in categorical rasters
• Calculate area statistics for a combination of two categorical rasters combined
• Support both time-series and static (non-temporal) raster data
• Offer flexible area calculation options (pixel counts, constant values, or spatially-variable areas)
• Generate tabular summaries as pandas DataFrames

ArraylakeTools

Arraylake Tools ReadMe

This module provides tools to:

• Calculate area statistics for different classes in categorical rasters
• Support both time-series and static (non-temporal) raster data
• Offer flexible area calculation options (pixel counts, constant values, or spatially-variable areas)
• Generate tabular summaries as pandas DataFrames