@manual{QGIS,
    title = {QGIS Geographic Information System},
    author = {{QGIS Development Team}},
    organization = {Open Source Geospatial Foundation},
    year = {2025},
    url = {https://qgis.org},
  }

@article{zhu2017deep,
  title={Deep learning in remote sensing: A comprehensive review and list of resources},
  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},
  volume={5},
  number={4},
  pages={8--36},
  year={2017},
  doi={10.1109/mgrs.2017.2762307},
  publisher={IEEE}
}

@article{yuan2020deep,
  title={Deep learning in environmental remote sensing: Achievements and challenges},
  author={Qiangqiang Yuan and Huanfeng Shen and Tongwen Li and Zhiwei Li and Shuwen Li and Yun Jiang and Hongzhang Xu and Weiwei Tan and Qianqian Yang and Jiwen Wang and Jianhao Gao and Liangpei Zhang},
  journal={Remote Sensing of Environment},
  volume={241},
  pages={111716},
  year={2020},
  doi={10.1016/j.rse.2020.111716},
  publisher={Elsevier}
}
@article{yasir2023coupling,
  title={Coupling of deep learning and remote sensing: a comprehensive systematic literature review},
  author={Yasir, Muhammad and Jianhua, Wan and Shanwei, Liu and Sheng, Hui and Mingming, Xu and Hossain, Md},
  journal={International Journal of Remote Sensing},
  volume={44},
  number={1},
  pages={157--193},
  year={2023},
  doi={10.1080/01431161.2022.2161856},
  publisher={Taylor \& Francis}
}


@misc{goodfellow2016deep,
  title={Deep learning},
  author={Goodfellow, Ian},
  year={2016},
  publisher={MIT press}
}

@article{shwartz2024compress,
  title={To compress or not to compress—self-supervised learning and information theory: A review},
  author={Shwartz Ziv, Ravid and LeCun, Yann},
  journal={Entropy},
  volume={26},
  number={3},
  pages={252},
  year={2024},
  doi={10.3390/e26030252},
  publisher={MDPI}
}

@CONFERENCE{HullermeierRifqi2009,
  author  = {Hullermeier, E. and Rifqi, M.},
  title   = {A Fuzzy Variant of the Rand Index for Comparing Clustering Structures},
  booktitle = {in Proc. IFSA/EUSFLAT Conf.}, 
  year    = {2009},
  pages   = {1294-1298}
}

@inproceedings{caron2021emerging,
  title={Emerging Properties in Self-Supervised Vision Transformers},
  author={Caron, Mathilde and Touvron, Hugo and Misra, Ishan and J\'egou, Herv\'e  and Mairal, Julien and Bojanowski, Piotr and Joulin, Armand},
  booktitle={Proceedings of the International Conference on Computer Vision (ICCV)},
  year={2021},
  doi={10.1109/iccv48922.2021.00951},
  pages={9650--9660},
}

@incollection{boettinger2008landsat,
  title={Landsat spectral data for digital soil mapping},
  author={Boettinger, JL and Ramsey, RD and Bodily, JM and Cole, NJ and Kienast-Brown, S and Nield, SJ and Saunders, AM and Stum, AK},
  booktitle={Digital soil mapping with limited data},
  pages={193--202},
  doi={10.1007/978-1-4020-8592-5_16},
  year={2008},
  publisher={Springer}
}

@article{maynard2017hyper,
  title={Hyper-temporal remote sensing for digital soil mapping: Characterizing soil-vegetation response to climatic variability},
  author={Maynard, Jonathan J and Levi, Matthew R},
  journal={Geoderma},
  volume={285},
  pages={94--109},
  year={2017},
  doi={10.1016/j.geoderma.2016.09.024},
  publisher={Elsevier}
}

@article{lecun2015deep,
  title={Deep learning},
  author={LeCun, Yann and Bengio, Yoshua and Hinton, Geoffrey},
  journal={nature},
  volume={521},
  number={7553},
  pages={436--444},
  year={2015},
  publisher={Nature Publishing Group UK London}
}

@article{krizhevsky2017imagenet,
  title={ImageNet classification with deep convolutional neural networks},
  author={Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
  journal={Communications of the ACM},
  doi={10.1145/3065386},
  volume={60},
  number={6},
  pages={84--90},
  year={2017},
  publisher={ACM New York, NY, USA}
}

@inproceedings{he2022masked,
  title={Masked autoencoders are scalable vision learners},
  author={He, Kaiming and Chen, Xinlei and Xie, Saining and Li, Yanghao and Doll{\'a}r, Piotr and Girshick, Ross},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  doi={10.1109/cvpr52688.2022.01553},
  pages={16000--16009},
  year={2022}
}

@article{bao2021beit,
  title={Beit: Bert pre-training of image transformers},
  author={Bao, Hangbo and Dong, Li and Piao, Songhao and Wei, Furu},
  journal={arXiv preprint arXiv:2106.08254},
  year={2021}
}

@inproceedings{ericsson2021well,
  title={How well do self-supervised models transfer?},
  author={Ericsson, Linus and Gouk, Henry and Hospedales, Timothy M},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  doi={10.1109/cvpr46437.2021.00537},
  pages={5414--5423},
  year={2021}
}

@article{dosovitskiy2020image,
  title={An image is worth 16x16 words: Transformers for image recognition at scale},
  author={Dosovitskiy, Alexey and Beyer, Lucas and Kolesnikov, Alexander and Weissenborn, Dirk and Zhai, Xiaohua and Unterthiner, Thomas and Dehghani, Mostafa and Minderer, Matthias and Heigold, Georg and Gelly, Sylvain and others},
  journal={arXiv preprint arXiv:2010.11929},
  url={https://arxiv.org/pdf/2010.11929/100},
  year={2020}
}

@article{mcinnes2018umap,
  title={Umap: Uniform manifold approximation and projection for dimension reduction},
  author={McInnes, Leland and Healy, John and Melville, James},
  journal={arXiv preprint arXiv:1802.03426},
  year={2018}
}

@misc{kingma2017adam,
      title={Adam: A Method for Stochastic Optimization}, 
      author={Diederik P. Kingma and Jimmy Ba},
      year={2017},
      eprint={1412.6980},
      archivePrefix={arXiv},
      primaryClass={id='cs.LG' full_name='Machine Learning' is_active=True alt_name=None in_archive='cs' is_general=False description='Papers on all aspects of machine learning research (supervised, unsupervised, reinforcement learning, bandit problems, and so on) including also robustness, explanation, fairness, and methodology. cs.LG is also an appropriate primary category for applications of machine learning methods.'}
}

@inproceedings{torchgeo,
    address = {Seattle, Washington},
    author = {Stewart, Adam J. and Robinson, Caleb and Corley, Isaac A. and Ortiz, Anthony and Lavista Ferres, Juan M. and Banerjee, Arindam},
    booktitle = {Proceedings of the 30th International Conference on Advances in Geographic Information Systems},
    doi = {10.1145/3557915.3560953},
    month = nov,
    pages = {1--12},
    publisher = {Association for Computing Machinery},
    series = {SIGSPATIAL '22},
    title = {{TorchGeo}: Deep Learning With Geospatial Data},
    url = {https://dl.acm.org/doi/10.1145/3557915.3560953},
    year = {2022}
}

@article{paszke2017automatic,
  title={Automatic differentiation in PyTorch},
  author={Paszke, Adam and Gross, Sam and Chintala, Soumith and Chanan, Gregory and Yang, Edward and DeVito, Zachary and Lin, Zeming and Desmaison, Alban and Antiga, Luca and Lerer, Adam},
  year={2017},
  journal={NIPS 2017 Autodiff Workshop},
}

@misc{grinsztajn2022treebased,
      title={Why do tree-based models still outperform deep learning on tabular data?}, 
      author={Léo Grinsztajn and Edouard Oyallon and Gaël Varoquaux},
      year={2022},
      eprint={2207.08815},
      archivePrefix={arXiv},
      primaryClass={id='cs.LG' full_name='Machine Learning' is_active=True alt_name=None in_archive='cs' is_general=False description='Papers on all aspects of machine learning research (supervised, unsupervised, reinforcement learning, bandit problems, and so on) including also robustness, explanation, fairness, and methodology. cs.LG is also an appropriate primary category for applications of machine learning methods.'}
}


@software{HLS_Foundation_2023,
    author          = {Jakubik, Johannes and Chu, Linsong and Fraccaro, Paolo and Bangalore, Ranjini and Lambhate, Devyani and Das, Kamal and Oliveira Borges, Dario and Kimura, Daiki and Simumba, Naomi and Szwarcman, Daniela and Muszynski, Michal and Weldemariam, Kommy and Zadrozny, Bianca and Ganti, Raghu and Costa, Carlos and Watson, Campbell and Mukkavilli, Karthik and Roy, Sujit and Phillips, Christopher and Ankur, Kumar and Ramasubramanian, Muthukumaran and Gurung, Iksha and Leong, Wei Ji and Avery, Ryan and Ramachandran, Rahul and Maskey, Manil and Olofossen, Pontus and Fancher, Elizabeth and Lee, Tsengdar and Murphy, Kevin and Duffy, Dan and Little, Mike and Alemohammad, Hamed and Cecil, Michael and Li, Steve and Khallaghi, Sam and Godwin, Denys and Ahmadi, Maryam and Kordi, Fatemeh and Saux, Bertrand and Pastick, Neal and Doucette, Peter and Fleckenstein, Rylie and Luanga, Dalton and Corvin, Alex and Granger, Erwan},
    doi             = {10.57967/hf/0952},
    month           = aug,
    title           = {{HLS Foundation}},
    repository-code = {https://github.com/nasa-impact/hls-foundation-os},
    year            = {2023}
}

@article{cong2022satmae,
  title={Sat{MAE}: Pre-training transformers for temporal and multi-spectral satellite imagery},
  author={Cong, Yezhen and Khanna, Samar and Meng, Chenlin and Liu, Patrick and Rozi, Erik and He, Yutong and Burke, Marshall and Lobell, David and Ermon, Stefano},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  doi={10.52202/068431-0015},
  pages={197--211},
  year={2022}
}

@inproceedings{braham2022self,
  title={Self supervised learning for few shot hyperspectral image classification},
  author={Braham, Nassim Ait Ali and Mou, Lichao and Chanussot, Jocelyn and Mairal, Julien and Zhu, Xiao Xiang},
  booktitle={IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium},
  pages={267--270},
  year={2022},
  organization={IEEE}
}

@article{oquab2023dinov2,
  title={Dinov2: Learning robust visual features without supervision},
  author={Oquab, Maxime and Darcet, Timoth{\'e}e and Moutakanni, Th{\'e}o and Vo, Huy and Szafraniec, Marc and Khalidov, Vasil and Fernandez, Pierre and Haziza, Daniel and Massa, Francisco and El-Nouby, Alaaeldin and others},
  journal={arXiv preprint arXiv:2304.07193},
  year={2023}
}

@misc{he2018mask,
      title={Mask R-CNN}, 
      author={Kaiming He and Georgia Gkioxari and Piotr Dollár and Ross Girshick},
      year={2018},
      eprint={1703.06870},
      archivePrefix={arXiv},
      primaryClass={id='cs.CV' full_name='Computer Vision and Pattern Recognition' is_active=True alt_name=None in_archive='cs' is_general=False description='Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.'}
}

@misc{ronneberger2015unet,
      title={U-Net: Convolutional Networks for Biomedical Image Segmentation}, 
      author={Olaf Ronneberger and Philipp Fischer and Thomas Brox},
      year={2015},
      eprint={1505.04597},
      archivePrefix={arXiv},
      primaryClass={id='cs.CV' full_name='Computer Vision and Pattern Recognition' is_active=True alt_name=None in_archive='cs' is_general=False description='Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.'}
}

@article{devlin2018bert,
  title={Bert: Pre-training of deep bidirectional transformers for language understanding},
  author={Devlin, Jacob},
  journal={arXiv preprint arXiv:1810.04805},
  year={2018}
}

@article{achiam2023gpt,
  title={Gpt-4 technical report},
  author={Achiam, Josh and Adler, Steven and Agarwal, Sandhini and Ahmad, Lama and Akkaya, Ilge and Aleman, Florencia Leoni and Almeida, Diogo and Altenschmidt, Janko and Altman, Sam and Anadkat, Shyamal and others},
  journal={arXiv preprint arXiv:2303.08774},
  year={2023}
}

@article{jakubik2023prithvi,
    author          = {Jakubik, Johannes and Roy, Sujit and Phillips, C. E. and Fraccaro, Paolo and Godwin, Denys and Zadrozny, Bianca and Szwarcman, Daniela and Gomes, Carlos and Nyirjesy, Gabby and Edwards, Blair and Kimura, Daiki and Simumba, Naomi and Chu, Linsong and Mukkavilli, S. Karthik and Lambhate, Devyani and Das, Kamal and Bangalore, Ranjini and Oliveira, Dario and Muszynski, Michal and Ankur, Kumar and Ramasubramanian, Muthukumaran and Gurung, Iksha and Khallaghi, Sam and Li, Hanxi (Steve) and Cecil, Michael and Ahmadi, Maryam and Kordi, Fatemeh and Alemohammad, Hamed and Maskey, Manil and Ganti, Raghu and Weldemariam, Kommy and Ramachandran, Rahul},
    month           = oct,
    title           = {{Foundation Models for Generalist Geospatial Artificial Intelligence}},
    journal         = {Preprint Available on {a}r{X}iv:2310.18660},
    year            = {2023},
    url             = {https://arxiv.org/pdf/2310.18660},
}

@article{xiong2024neural,
  title={Neural Plasticity-Inspired Multimodal Foundation Model Earth Observation},
  author={Xiong, Zhitong and Wang, Yi and Zhang, Fahong and Stewart, Adam J and Hanna, Jo{\"e}lle and Borth, Damian and Papoutsis, Ioannis and Saux, Bertrand Le and Camps-Valls, Gustau and Zhu, Xiao Xiang},
  journal={arXiv preprint arXiv:2403.15356},
  year={2024},
  url={https://arxiv.org/pdf/2403.15356},
}

@article{vaswani2017attention,
  title={Attention is all you need},
  author={Vaswani, A},
  journal={Advances in Neural Information Processing Systems},
  year={2017}
}

@misc{rw2019timm,
  author = {Ross Wightman},
  title = {PyTorch Image Models},
  year = {2019},
  publisher = {GitHub},
  journal = {GitHub repository},
  doi = {10.5281/zenodo.4414861},
  howpublished = {\url{https://github.com/rwightman/pytorch-image-models}}
}

@misc{wolf2019huggingface,
      title={{H}ugging{F}ace's {T}ransformers: State-of-the-art Natural Language Processing}, 
      author={Thomas Wolf and Lysandre Debut and Victor Sanh and Julien Chaumond and Clement Delangue and Anthony Moi and Pierric Cistac and Tim Rault and Rémi Louf and Morgan Funtowicz and Joe Davison and Sam Shleifer and Patrick von Platen and Clara Ma and Yacine Jernite and Julien Plu and Canwen Xu and Teven Le Scao and Sylvain Gugger and Mariama Drame and Quentin Lhoest and Alexander M. Rush},
      year={2020},
      eprint={1910.03771},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/1910.03771}, 
}

@inproceedings{torchgeo2022,
    address = {Seattle, Washington},
    author = {Stewart, Adam J. and Robinson, Caleb and Corley, Isaac A. and Ortiz, Anthony and Lavista Ferres, Juan M. and Banerjee, Arindam},
    booktitle = {Proceedings of the 30th International Conference on Advances in Geographic Information Systems},
    doi = {10.1145/3557915.3560953},
    month = nov,
    pages = {1--12},
    publisher = {Association for Computing Machinery},
    series = {SIGSPATIAL '22},
    title = {{TorchGeo}: Deep Learning With Geospatial Data},
    url = {https://dl.acm.org/doi/10.1145/3557915.3560953},
    year = {2022}
}

@article{van2008visualizing,
  title={Visualizing data using t-SNE.},
  author={Van der Maaten, Laurens and Hinton, Geoffrey},
  journal={Journal of machine learning research},
  volume={9},
  number={11},
  year={2008}
}

@article{scikit-learn,
  title={Scikit-learn: Machine Learning in {P}ython},
  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.},
  journal={Journal of Machine Learning Research},
  volume={12},
  pages={2825--2830},
  year={2011}
}

@article{mcinnes2017hdbscan,
  title={hdbscan: Hierarchical density based clustering.},
  author={McInnes, Leland and Healy, John and Astels, Steve and others},
  journal={J. Open Source Softw.},
  volume={2},
  number={11},
  pages={205},
  year={2017}
}

@article{chen2022deep,
  title={Deep learning for instance retrieval: A survey},
  author={Chen, Wei and Liu, Yu and Wang, Weiping and Bakker, Erwin M and Georgiou, Theodoros and Fieguth, Paul and Liu, Li and Lew, Michael S},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  volume={45},
  number={6},
  pages={7270--7292},
  year={2022},
  publisher={IEEE}
}

@article{aszkowski2023deepness,
title = {Deepness: Deep neural remote sensing plugin for QGIS},
journal = {SoftwareX},
volume = {23},
pages = {101495},
year = {2023},
issn = {2352-7110},
doi = {10.1016/j.softx.2023.101495},
url = {https://www.sciencedirect.com/science/article/pii/S2352711023001917},
author = {Przemysław Aszkowski and Bartosz Ptak and Marek Kraft and Dominik Pieczyński and Paweł Drapikowski},
keywords = {QGIS, Deep learning, Remote sensing, Segmentation, Object detection},
}

@article{wu2020integer,
  title={Integer quantization for deep learning inference: Principles and empirical evaluation},
  author={Wu, Hao and Judd, Patrick and Zhang, Xiaojie and Isaev, Mikhail and Micikevicius, Paulius},
  journal={arXiv preprint arXiv:2004.09602},
  year={2020}
}

@software{zhao2023geosam,
  author       = {Zhao, Zhuoyi and Fan, Chengyan and Liu, Lin},
  title        = {{Geo SAM: A QGIS plugin using Segment Anything Model (SAM) to accelerate geospatial image segmentation}},
  month        = jul,
  year         = 2023,
  publisher    = {Zenodo},
  version      = {1.1.0},
  doi          = {10.5281/zenodo.8191039},
  url          = {https://doi.org/10.5281/zenodo.8191039}
}

@article{liu2024deepseek,
  title={Deepseek-v3 technical report},
  author={Liu, Aixin and Feng, Bei and Xue, Bing and Wang, Bingxuan and Wu, Bochao and Lu, Chengda and Zhao, Chenggang and Deng, Chengqi and Zhang, Chenyu and Ruan, Chong and others},
  journal={arXiv preprint arXiv:2412.19437},
  year={2024}
}

@misc{marsocci2024pangaea,
      title={PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models}, 
      author={Valerio Marsocci and Yuru Jia and Georges Le Bellier and David Kerekes and Liang Zeng and Sebastian Hafner and Sebastian Gerard and Eric Brune and Ritu Yadav and Ali Shibli and Heng Fang and Yifang Ban and Maarten Vergauwen and Nicolas Audebert and Andrea Nascetti},
      year={2024},
      eprint={2412.04204},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.04204}, 
}

@inproceedings{fang2023eva,
  title={Eva: Exploring the limits of masked visual representation learning at scale},
  author={Fang, Yuxin and Wang, Wen and Xie, Binhui and Sun, Quan and Wu, Ledell and Wang, Xinggang and Huang, Tiejun and Wang, Xinlong and Cao, Yue},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  doi={10.1109/cvpr52729.2023.01855},
  pages={19358--19369},
  year={2023}
}

@article{ryali2023hiera,
  title={Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles},
  author={Ryali, Chaitanya and Hu, Yuan-Ting and Bolya, Daniel and Wei, Chen and Fan, Haoqi and Huang, Po-Yao and Aggarwal, Vaibhav and Chowdhury, Arkabandhu and Poursaeed, Omid and Hoffman, Judy and Malik, Jitendra and Li, Yanghao and Feichtenhofer, Christoph},
  journal={ICML},
  year={2023}
}

@article{gui2024survey,
  title={A survey on self-supervised learning: Algorithms, applications, and future trends},
  author={Gui, Jie and Chen, Tuo and Zhang, Jing and Cao, Qiong and Sun, Zhenan and Luo, Hao and Tao, Dacheng},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2024},
  publisher={IEEE}
}

@article{bardes2021vicreg,
  title={Vicreg: Variance-invariance-covariance regularization for self-supervised learning},
  author={Bardes, Adrien and Ponce, Jean and LeCun, Yann},
  journal={arXiv preprint arXiv:2105.04906},
  year={2021}
}

@article{ploton2020spatial,
  title={Spatial validation reveals poor predictive performance of large-scale ecological mapping models},
  author={Ploton, Pierre and Mortier, Fr{\'e}d{\'e}ric and R{\'e}jou-M{\'e}chain, Maxime and Barbier, Nicolas and Picard, Nicolas and Rossi, Vivien and Dormann, Carsten and Cornu, Guillaume and Viennois, Ga{\"e}lle and Bayol, Nicolas and others},
  journal={Nature communications},
  doi={10.1038/s41467-020-18321-y},
  volume={11},
  number={1},
  pages={4540},
  year={2020},
  publisher={Nature Publishing Group UK London}
}

@article{wang2022ssl4eo,
  title={SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation},
  author={Wang, Yi and Braham, Nassim Ait Ali and Xiong, Zhitong and Liu, Chenying and Albrecht, Conrad M and Zhu, Xiao Xiang},
  journal={arXiv preprint arXiv:2211.07044},
  year={2022}
}

@article{sklearn,
  author  = {Fabian Pedregosa and Ga{{\"e}}l Varoquaux and Alexandre Gramfort and Vincent Michel and Bertrand Thirion and Olivier Grisel and Mathieu Blondel and Peter Prettenhofer and Ron Weiss and Vincent Dubourg and Jake Vanderplas and Alexandre Passos and David Cournapeau and Matthieu Brucher and Matthieu Perrot and {{\'E}}douard Duchesnay},
  title   = {Scikit-learn: Machine Learning in Python},
  journal = {Journal of Machine Learning Research},
  year    = {2011},
  volume  = {12},
  number  = {85},
  pages   = {2825--2830},
  url     = {http://jmlr.org/papers/v12/pedregosa11a.html}
}

@article{stewart2024torchgeo,
    author = {Stewart, Adam J. and Robinson, Caleb and Corley, Isaac A. and Ortiz, Anthony and Lavista Ferres, Juan M. and Banerjee, Arindam},
    title = {{TorchGeo}: Deep Learning With Geospatial Data},
    journal = {ACM Transactions on Spatial Algorithms and Systems},
    volume = {11},
    number = {4},
    pages = {1--28},
    url = {https://doi.org/10.1145/3707459},
    doi = {10.1145/3707459},
    month = aug,
    year = {2025}
}

@article{safonova2023ten,
title = {Ten deep learning techniques to address small data problems with remote sensing},
journal = {International Journal of Applied Earth Observation and Geoinformation},
volume = {125},
pages = {103569},
year = {2023},
issn = {1569-8432},
doi = {10.1016/j.jag.2023.103569},
url = {https://www.sciencedirect.com/science/article/pii/S156984322300393X},
author = {Anastasiia Safonova and Gohar Ghazaryan and Stefan Stiller and Magdalena Main-Knorn and Claas Nendel and Masahiro Ryo},
}
