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1-dimensional convolutional neural networks (CNN) for the classification of soil texture based on hyperspectral data
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README.md

DOI arXiv License: MIT

CNN Soil Texture Classification

1-dimensional convolutional neural networks (CNN) for the classification of soil texture based on hyperspectral data.

Description

We present 1-dimensional (1D) convolutional neural networks (CNN) for the classification of soil texture based on hyperspectral data. The following CNN models are included:

These 1D CNNs are optimized for the soil texture classification based on the hyperspectral data of the Land Use/Cover Area Frame Survey (LUCAS) topsoil dataset. It is available here. For more information have a look in our publication (see below).

Introducing paper: arXiv:1901.04846

Licence: MIT

Authors:

Citation of the code and the paper: see below and in the bibtex file

Requirements

Setup

git clone https://github.com/felixriese/CNN-SoilTextureClassification.git

cd CNN-SoilTextureClassification/

wget https://raw.githubusercontent.com/titu1994/keras-coordconv/c045e3f1ff7dabd4060f515e4b900263eddf1723/coord.py .

Usage

You can import the Keras models like that:

import cnn_models as cnn

model = cnn.getKerasModel("LucasCNN")
model.compile(...)

Example code is given in the lucas_classification.py. You can use it like that:

from lucas_classification import lucas_classification

score = lucas_classification(
    data=[X_train, X_val, y_train, y_val],
    model_name="LucasCNN",
    batch_size=32,
    epochs=200,
    random_state=42)

print(score)

Citation

The bibtex file including both references is available here.

Paper

F. M. Riese and S. Keller, "Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data", 2019, arXiv:1901.04846, Accepted at ISPRS Geospatial Week 2019 in Enschede (NL).

@article{riese2019soil,
    author = {Riese, Felix~M. and Keller, Sina},
    title = {Soil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data},
    year = {2019},
    note = {Accepted at ISPRS Geospatial Week 2019 in Enschede (NL)},
    archivePrefix = {arXiv},
    eprint = {1901.04846},
    primaryClass = {cs.CV},
    url = {https://arxiv.org/abs/1901.04846}
}

Code

F. M. Riese, "CNN Soil Texture Classification", doi.org/10.5281/zenodo.2540718, 2019.

DOI

@misc{riese2019cnn,
    author       = {Riese, Felix~M.},
    title        = {{CNN Soil Texture Classification}},
    year         = {2019},
    publisher    = {Zenodo},
    DOI          = {10.5281/zenodo.2540718},
    howpublished = {\href{https://doi.org/10.5281/zenodo.2540718}{doi.org/10.5281/zenodo.2540718}}
}
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