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Meteorology-Conditioned High-Resolution Vegetation Forecasting: A Hierarchical Multi-Modal Fusion Network

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Introduction

Meteorology-Conditioned High-Resolution Vegetation Forecasting: A Hierarchical Multi-Modal Fusion Network

How to run

We recommend setting up the environment by installing pixi.

# Build the environment
pixi install

# Activate the env
pixi shell

# Run code
python main.py -c conf/*.toml

Datasets

Due to confidentiality reasons, the original data cannot be provided.

However, we have included a toy dataset. It can be downloaded directly from Hugging Face:

cd HMMFN

# Make sure git-lfs is installed (https://git-lfs.com)
git lfs install

git clone https://huggingface.co/datasets/sun2ot/HMMFN datasets
# If you are a Chinese user, we recommend using a mirror site:
# git clone https://hf-mirror.com/datasets/sun2ot/HMMFN datasets

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Meteorology-Conditioned High-Resolution Vegetation Forecasting: A Hierarchical Multi-Modal Fusion Network

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