Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Paper: Python-Based GeoImagery Dataset Development for Deep Learning-Driven Forest Wildfire Detection #916

Merged
merged 34 commits into from
Sep 25, 2024
Merged
Show file tree
Hide file tree
Changes from 22 commits
Commits
Show all changes
34 commits
Select commit Hold shift + click to select a range
aec1c21
id and author data
valemar10 May 23, 2024
dc6a708
add abstract and title
valemar10 May 23, 2024
fa52f64
add introduction
valemar10 May 23, 2024
36f8173
add introduction
valemar10 May 23, 2024
3fb7daf
finish introduction
valemar10 May 23, 2024
4823f43
Upload paper
valemar10 May 31, 2024
77e568e
Upload paper
valemar10 May 31, 2024
758bdbe
Upload paper
valemar10 May 31, 2024
bffb3b4
Fix .tex ref
valemar10 May 31, 2024
d641575
Final edits
valemar10 May 31, 2024
3dc88d1
Final edits
valemar10 May 31, 2024
5d58260
Update papers/Valeria_Martin/main.tex
valemar10 May 31, 2024
da18fc1
add orcid and missing dois
valemar10 Jun 4, 2024
d94e41b
Update papers/Valeria_Martin/myst.yml
valemar10 Jul 11, 2024
f1462e9
Update papers/Valeria_Martin/myst.yml
valemar10 Jul 11, 2024
acdadbe
reviewed paper
valemar10 Jul 15, 2024
332eabe
Merge branch 'Valeria_Martin' of https://github.com/valemar10/scipy_p…
valemar10 Jul 15, 2024
ec7bfef
reviewed paper
valemar10 Jul 15, 2024
626992b
reviewed paper
valemar10 Jul 15, 2024
41de7d4
reviewed paper
valemar10 Jul 15, 2024
8ae451f
reviewed paper
valemar10 Jul 15, 2024
523f3df
reviewed paper
valemar10 Jul 15, 2024
da091af
Update papers/Valeria_Martin/main.tex
valemar10 Jul 23, 2024
94cbe01
Update papers/Valeria_Martin/main.tex
valemar10 Jul 23, 2024
237cb3c
implement reviews
valemar10 Jul 23, 2024
c2cf4f3
implement reviews
valemar10 Jul 23, 2024
42adf59
implement reviews
valemar10 Jul 23, 2024
66111c3
implement reviews
valemar10 Jul 23, 2024
bdc493e
implement reviews
valemar10 Jul 23, 2024
2d11f45
implement reviews
valemar10 Jul 23, 2024
c547e5c
implement reviews
valemar10 Jul 23, 2024
d5d6352
implement reviews
valemar10 Jul 23, 2024
23f8029
implement reviews
valemar10 Jul 23, 2024
64e6b4d
improved vgg text
valemar10 Aug 1, 2024
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Binary file added papers/Valeria_Martin/6channel.png
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file added papers/Valeria_Martin/augment.png
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file added papers/Valeria_Martin/banner.png
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file added papers/Valeria_Martin/crop.png
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file added papers/Valeria_Martin/label1.png
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
628 changes: 628 additions & 0 deletions papers/Valeria_Martin/main.tex

Large diffs are not rendered by default.

375 changes: 375 additions & 0 deletions papers/Valeria_Martin/mybib.bib
Original file line number Diff line number Diff line change
@@ -0,0 +1,375 @@
@article{gorelick2017google,
title={Google Earth Engine: Planetary-scale geospatial analysis for everyone},
author={Gorelick, Noel and Hancher, Matt and Dixon, Mike and Ilyushchenko, Simon and Thau, David and Moore, Rebecca},
journal={Remote Sensing of Environment},
year={2017},
publisher={Elsevier},
doi={10.1016/j.rse.2017.06.031},
url={https://doi.org/10.1016/j.rse.2017.06.031}
}
@article{DRUSCH201225,
title = {Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services},
author = {M. Drusch and U. {Del Bello} and S. Carlier and O. Colin and V. Fernandez and F. Gascon and B. Hoersch and C. Isola and P. Laberinti and P. Martimort and A. Meygret and F. Spoto and O. Sy and F. Marchese and P. Bargellini},
journal = {Remote Sensing of Environment},
volume = {120},
pages = {25-36},
year = {2012},
note = {The Sentinel Missions - New Opportunities for Science},
issn = {0034-4257},
doi = {https://doi.org/10.1016/j.rse.2011.11.026},
url = {https://www.sciencedirect.com/science/article/pii/S0034425712000636}
}
@Article{rs14071552,
AUTHOR = {Jiang, Huiwei and Peng, Min and Zhong, Yuanjun and Xie, Haofeng and Hao, Zemin and Lin, Jingming and Ma, Xiaoli and Hu, Xiangyun},
TITLE = {A Survey on Deep Learning-Based Change Detection from High-Resolution Remote Sensing Images},
JOURNAL = {Remote Sensing},
VOLUME = {14},
YEAR = {2022},
NUMBER = {7},
ARTICLE-NUMBER = {1552},
URL = {https://www.mdpi.com/2072-4292/14/7/1552},
ISSN = {2072-4292},
DOI = {10.3390/rs14071552}
}
@Article{eleo,
AUTHOR = {Parelius, Eleonora Jonasova},
TITLE = {A Review of Deep-Learning Methods for Change Detection in Multispectral Remote Sensing Images},
JOURNAL = {Remote Sensing},
VOLUME = {15},
YEAR = {2023},
NUMBER = {8},
ARTICLE-NUMBER = {2092},
URL = {https://www.mdpi.com/2072-4292/15/8/2092},
ISSN = {2072-4292},
DOI = {10.3390/rs15082092}
}

@misc{rasterio,
title = {Rasterio: Access to geospatial raster data},
author = {{Gillies, Sean}},
year = {2013},
version = {1.3.9},
howpublished = {\url{https://rasterio.readthedocs.io/}}
}
@misc{tifffile,
title = {Tifffile: Read and write TIFF files},
author = {Gohlke, Christoph and Contributors},
year = {2021},
version = {2021.7.2},
howpublished = {\url{https://pypi.org/project/tifffile/}
doi = {https://doi.org/10.5281/zenodo.6795861}}
}
@inproceedings{lecun,
author = {Lecun, Yann and Bengio, Y.},
year = {1995},
month = {01},
pages = {},
title = {Convolutional Networks for Images, Speech, and Time-Series},
journal = {The Handbook of Brain Theory and Neural Networks}
}
@article{kingma2014adam,
title={Adam: A method for stochastic optimization},
author={Kingma, Diederik P and Ba, Jimmy},
journal={arXiv preprint arXiv:1412.6980},
year={2014}
}
@inproceedings{tan2019,
title={EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks},
author={Tan, Mingxing and Le, Quoc V},
booktitle={Proceedings of the 36th International Conference on Machine Learning (ICML)},
pages={6105--6114},
year={2019}
}
@article{numpy,
author = {Harris, Charles R. and Millman, K. Jarrod and van der Walt, Stéfan J. and Gommers, Ralf and Virtanen, Pauli and Cournapeau, David and Wieser, Eric and Taylor, Julian and Berg, Sebastian and Smith, Nathaniel J. and Kern, Robert and Picus, Matti and Hoyer, Stephan and van Kerkwijk, Marten H. and Brett, Matthew and Haldane, Allan and del Río, Jaime Fernández and Wiebe, Mark and Peterson, Pearu and Gérard-Marchant, Pierre and Sheppard, Kevin and Reddy, Tyler and Weckesser, Warren and Abbasi, Hameer and Gohlke, Christoph and Oliphant, Travis E.},
publisher = {Springer Science and Business Media {LLC}},
doi = {https://doi.org/10.1038/s41586-020-2649-2},
date = {2020-09},
year = {2020},
journal = {Nature},
number = {7825},
pages = {357--362},
title = {Array programming with {NumPy}},
volume = {585},
}
@misc{shapely,
title = {Shapely: Manipulation and Analysis of Geometric Objects},
author = {Sean Gillies and Brendan Ward and René Buffat and Jonathan J. Helmus and Stefan van der Walt and David Shean and Hugo Ledoux and Andrew Ysasi and Mike Taves and Howard Butler and Tim Head and Adriano Ferrari and Jeremiah England and Benjamin Root and Erik Zandvliet and Oliver Tonnhofer and Olivier de Ribaupierre and Patrick Sier and Filipe},
year = {2023},
month = {January},
version = {v2.0.0},
publisher = {Zenodo},
doi = {10.5281/zenodo.7428463},
url = {https://zenodo.org/record/7428463}
}

@software{geopandas,
author = {Kelsey Jordahl and
Joris Van den Bossche and
Martin Fleischmann and
Jacob Wasserman and
James McBride and
Jeffrey Gerard and
Jeff Tratner and
Matthew Perry and
Adrian Garcia Badaracco and
Carson Farmer and
Geir Arne Hjelle and
Alan D. Snow and
Micah Cochran and
Sean Gillies and
Lucas Culbertson and
Matt Bartos and
Nick Eubank and
maxalbert and
Aleksey Bilogur and
Sergio Rey and
Christopher Ren and
Dani Arribas-Bel and
Leah Wasser and
Levi John Wolf and
Martin Journois and
Joshua Wilson and
Adam Greenhall and
Chris Holdgraf and
Filipe and
François Leblanc},
title = {geopandas/geopandas: v0.8.1},
month = jul,
year = 2020,
publisher = {Zenodo},
version = {v0.8.1},
doi = {10.5281/zenodo.3946761},
url = {https://doi.org/10.5281/zenodo.3946761}
}
@article{sklearn1,
author = {Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V. and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P. and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
year = {2011},
journal = {Journal of Machine Learning Research},
pages = {2825--2830},
title = {Scikit-learn: Machine Learning in {P}ython},
volume = {12},
}

@inproceedings{sklearn2,
author = {Buitinck, Lars and Louppe, Gilles and Blondel, Mathieu and Pedregosa, Fabian and Mueller, Andreas and Grisel, Olivier and Niculae, Vlad and Prettenhofer, Peter and Gramfort, Alexandre and Grobler, Jaques and Layton, Robert and VanderPlas, Jake and Joly, Arnaud and Holt, Brian and Varoquaux, Gaël},
booktitle = {ECML PKDD Workshop: Languages for Data Mining and Machine Learning},
year = {2013},
pages = {108--122},
title = {{API} design for machine learning software: experiences from the scikit-learn project},
}
@misc{pandas1,
author = {{The Pandas Development Team}},
title = {pandas-dev/pandas: Pandas},
month = feb,
year = {2020},
publisher = {Zenodo},
version = {latest},
Doi = {https://doi.org/10.5281/zenodo.3509134},
}
@book{goodfellow2016deep,
title={Deep Learning},
author={Goodfellow, Ian and Bengio, Yoshua and Courville, Aaron},
publisher={MIT Press},
year={2016},
address={Cambridge, MA, USA},
isbn={0262035618}
}
@InProceedings{Simonyan15,
author = "Karen Simonyan and Andrew Zisserman",
title = "Very Deep Convolutional Networks for Large-Scale Image Recognition",
booktitle = "International Conference on Learning Representations",
year = "2015",
}
@article{DBLP:RonnebergerFB15,
author = {Olaf Ronneberger and
Philipp Fischer and
Thomas Brox},
title = {U-Net: Convolutional Networks for Biomedical Image Segmentation},
journal = {CoRR},
volume = {abs/1505.04597},
year = {2015},
url = {http://arxiv.org/abs/1505.04597},
eprinttype = {arXiv},
eprint = {1505.04597},
timestamp = {Mon, 13 Aug 2018 16:46:52 +0200},
biburl = {https://dblp.org/rec/journals/corr/RonnebergerFB15.bib},
bibsource = {dblp computer science bibliography, https://dblp.org},
doi = {10.1007/978-3-319-24574-4_28}
}

@article{marmanis2016deep,
title={Deep learning Earth observation classification using ImageNet pretrained networks},
author={Marmanis, Dimitrios and Datcu, Mihai and Esch, Thomas and Stilla, Uwe},
journal={IEEE Geoscience and Remote Sensing Letters},
volume={13},
number={1},
pages={105--109},
year={2016},
publisher={IEEE},
doi={10.1109/LGRS.2015.2499239}
}

@article{Alzubaidi2021ReviewOD,
title={Review of deep learning: concepts, CNN architectures, challenges, applications, future directions},
author={Laith Alzubaidi and Jinglan Zhang and Amjad J. Humaidi and Ayad Al-dujaili and Ye Duan and Omran Al-Shamma and Jos{\'e} I. Santamar{\'i}a and Mohammed Abdulraheem Fadhel and Muthana Al-Amidie and Laith Farhan},
journal={Journal of Big Data},
year={2021},
volume={8},
url={https://api.semanticscholar.org/CorpusID:232434552},
doi = {10.1186/s40537-021-00444-8}
}


@article{Adegun2023,
author = {Adegun, A.A. and Viriri, S. and Tapamo, JR.},
title = {Review of deep learning methods for remote sensing satellite images classification: experimental survey and comparative analysis},
journal = {Journal of Big Data},
volume = {10},
pages = {93},
year = {2023},
doi = {10.1186/s40537-023-00772-x},
url = {https://doi.org/10.1186/s40537-023-00772-x}
}

@article{al-dabbagh2023uni,
title={Uni-temporal Sentinel-2 imagery for wildfire detection using deep learning semantic segmentation models},
author={Al-Dabbagh, Ali Mahdi and Ilyas, Muhammad},
journal={Geomatics, Natural Hazards and Risk},
volume={14},
number={1},
year={2023},
doi={10.1080/19475705.2023.2196370},
publisher={Taylor & Francis}
}

@article{hu2015transferring,
title={Transferring deep convolutional neural networks for the scene classification of high-resolution remote sensing imagery},
author={Hu, Fan and Xia, Gui-Song and Hu, Jingwen and Zhang, Liangpei},
journal={Remote Sensing},
volume={7},
number={11},
pages={14680--14707},
year={2015},
publisher={MDPI},
doi = {10.3390/rs71114680}
}


@ARTICLE{8113128,
author={Zhu, Xiao Xiang and Tuia, Devis and Mou, Lichao and Xia, Gui-Song and Zhang, Liangpei and Xu, Feng and Fraundorfer, Friedrich},
journal={IEEE Geoscience and Remote Sensing Magazine},
title={Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources},
year={2017},
volume={5},
number={4},
pages={8-36},
keywords={Machine learning;Remote sensing;Feature extraction;Hyperspectral imaging;Computer vision;Tutorials;Remote sensing;Climate change},
doi={10.1109/MGRS.2017.2762307}}

@misc{california_department_of_forestry_and_fire_protection_2024,
title = {Fire and Resource Assessment Program, Historical Fire Perimeter Data},
author = {{California Department of Forestry and Fire Protection}},
year = 2024,
howpublished = {Accessed May 10, 2024},
url = {https://www.fire.ca.gov/what-we-do/fire-resource-assessment-program}
}

@InProceedings{geopy,
author = {Lopez Gonzalez-Nieto, P. and Gomez Flechoso, M. and Arribas Mocoroa, M.A. and Mu\~{n}oz Martin, A. and Garcia Lorenzo, M.L. and Cabrera Gomez, G. and Alvarez Gomez, J.A. and Caso Fraile, A. and Orosco Dagan, J.M. and Merinero Palomares, R. and Lahoz-Beltra, R.},
title = {DESIGN AND DEVELOPMENT OF A VIRTUAL LABORATORY IN PYTHON FOR THE TEACHING OF DATA ANALYSIS AND MATHEMATICS IN GEOLOGY: GEOPY},
series = {14th International Technology, Education and Development Conference},
booktitle = {INTED2020 Proceedings},
isbn = {978-84-09-17939-8},
issn = {2340-1079},
doi = {10.21125/inted.2020.0687},
url = {https://doi.org/10.21125/inted.2020.0687},
publisher = {IATED},
location = {Valencia, Spain},
month = {2-4 March, 2020},
year = {2020},
pages = {2236-2242}}
@misc{pyproj2023,
title = {PyProj: A Python interface to PROJ (cartographic projections and coordinate transformations library)},
author = {Snow, Alan D. and Bane Sullivan and Jean-Conrad Varrault and Kristian Evers and Charles Karney and Micah Cochran and Joris Van den Bossche and Kurt Schwehr and Brendan Ward and Jeff Whitaker and Benjamin Root and Alistair Collins and Filipe and Eric Tsai and Leon Derczynski and Jesús Casado and Alex Hagen and Jay Laura and Leonardo Calcagno},
year = 2023,
howpublished = {Zenodo},
doi = {10.5281/zenodo.8365173},
url = {https://zenodo.org/record/8365173}
}

@Article{Hunan,
AUTHOR = {Xiang, Jun and Xing, Yuanjun and Wei, Wei and Yan, Enping and Jiang, Jiawei and Mo, Dengkui},
TITLE = {Dynamic Detection of Forest Change in Hunan Province Based on Sentinel-2 Images and Deep Learning},
JOURNAL = {Remote Sensing},
VOLUME = {15},
YEAR = {2023},
NUMBER = {3},
ARTICLE-NUMBER = {628},
URL = {https://www.mdpi.com/2072-4292/15/3/628},
ISSN = {2072-4292},
DOI = {10.3390/rs15030628}
}
@article{SEYDI2022108999,
title = {Burnt-Net: Wildfire burned area mapping with single post-fire Sentinel-2 data and deep learning morphological neural network},
journal = {Ecological Indicators},
volume = {140},
pages = {108999},
year = {2022},
issn = {1470-160X},
doi = {https://doi.org/10.1016/j.ecolind.2022.108999},
url = {https://www.sciencedirect.com/science/article/pii/S1470160X22004708},
author = {Seyd Teymoor Seydi and Mahdi Hasanlou and Jocelyn Chanussot},
keywords = {Deep learning, Semantic segmentation, Burned area, Sentinel-2, Morphological operator}
}

@misc{tensorflow2015-whitepaper,
title={ {TensorFlow}: Large-Scale Machine Learning on Heterogeneous Systems},
url={https://www.tensorflow.org/},
note={Software available from tensorflow.org},
author={
Mart\'{i}n~Abadi and
Ashish~Agarwal and
Paul~Barham and
Eugene~Brevdo and
Zhifeng~Chen and
Craig~Citro and
Greg~S.~Corrado and
Andy~Davis and
Jeffrey~Dean and
Matthieu~Devin and
Sanjay~Ghemawat and
Ian~Goodfellow and
Andrew~Harp and
Geoffrey~Irving and
Michael~Isard and
Yangqing Jia and
Rafal~Jozefowicz and
Lukasz~Kaiser and
Manjunath~Kudlur and
Josh~Levenberg and
Dandelion~Man\'{e} and
Rajat~Monga and
Sherry~Moore and
Derek~Murray and
Chris~Olah and
Mike~Schuster and
Jonathon~Shlens and
Benoit~Steiner and
Ilya~Sutskever and
Kunal~Talwar and
Paul~Tucker and
Vincent~Vanhoucke and
Vijay~Vasudevan and
Fernanda~Vi\'{e}gas and
Oriol~Vinyals and
Pete~Warden and
Martin~Wattenberg and
Martin~Wicke and
Yuan~Yu and
Xiaoqiang~Zheng},
year={2015},
doi = {10.5281/zenodo.4724125}
}


Loading