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VeRCYe Documentation

This documentation aims to provides a comprehensive guide to running the Versatile Crop Yield Estimate (VeRCYe) pipeline. The original VeRCYe algorithm is published here.

Currently the documentation is a work in progress, so please visit again soon.

Features

  • Tools to greatly reduce manual effort required for executing the VERYCE crop yield estimate pipeline.
  • All workflow steps are wrapped in a well-documented CLI interface to permit step by step execution.
  • The core CLI steps are also wrapped in a Snakemake-based data processing pipeline to batch execute yield estimates in an easy to run and reproducible manner.

Overview

The VeRCYe pipeline is split into two main components:

  • LAI Generation: Download remotely sensed imagery and predict Leaf Area Index (LAI) values per pixel.
  • Yield Simulation and Prediction: Simulate numerous likely configurations using APSIM and identify the best-matching simulations with the LAI data. This step also includes evaluation and reporting tools.

Setup

0. Clone this repository

git clone https://github.com/JPLMLIA/vercye_ops.git

1. Check Python Version and GDAL

This repository has been tested and run with python 3.10.16 and with gdal==3.1.0. Ensure you have installed the corresponding versions (python --version and gdalinfo --version). If you are running your code on a shared cluster, you might have to run module load gdal/3.1.0, before being able to use GDAL.

2. Install the requirements

Navigate to this package's root directory and run:

conda install --yes --file requirements.txt
# or
pip install -r requirements.txt

Note: As of June 2024, if using conda, you may also need to install Snakemake and a specific dependency manually via pip:

bash pip install snakemake pulp==2.7.0

3. Install the VeRCYe package

From the root directory, run:

pip install -e .

4. Install APSIMX

There are two options for running APSIM:

  • Using Docker: Simply set a parameter during configuration of your yield study. The Docker container will build automatically. (Ensure docker is installed.)
  • Building the binary manually: See instructions in vercye_ops/apsim/README.md.

Note: If running on UMD systems, APSIM is pre-installed at:

/gpfs/data1/cmongp2/wronk/Builds/ApsimX/bin/Release/net6.0/Models

5. Install jq

To manipulate JSON files via the command line:

module load jq

Running your first yield study

You will first have to generate LAI data from remotely sensed imagery. Refer to the LAI Creation Guide for details.

Once you have generated the LAI data, you can run your yield study, by following the Running a Yieldstudy Guide.

Technical Details

The technical implementation details are outlined in he Architecture Section. Fore more details check out the code in vercye_ops.

Development

Development tipps and best practices are documented under Development Tipps