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Model applications and DNN training data sets

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SVD Models

This repository is part of SVD (Scaling Vegetation Dynamics). It contains SVD projects (i.e. all data required to run SVD), and data for training the Deep Neural Networks that are at the core of SVD.

See https://github.com/SVDmodel/SVD for the model code and executable of SVD.

Overview

NPKA

SVD project and training data for the study area (Kalkalpen Nationalpark) used for the paper:

"A scalable model of vegetation transitions using deep neural networks", by Werner Rammer and Rupert Seidl.

GYE

SVD project folder for the Greater Yellowstone Ecosystem. This data set was used for the paper: "Widespread regeneration failure in forests of Greater Yellowstone under scenarios of future climate and fire", by Werner Rammer et al.