Publications

2023

Large-scale detection of marine debris in coastal areas with Sentinel-2

M. C. Russwurm; S. J. Venkatesa; D. Tuia 

iScience. 2023. Vol. 26, num. 12, p. 108402. DOI : 10.1016/j.isci.2023.108402.

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Stay close, but not too close: aerial image analysis reveals patterns of social distancing in seal colonies

J. P. A. Hoekendijk; A. Grundlehner; S. Brasseur; B. Kellenberger; D. Tuia et al. 

Royal Society Open Science. 2023. Vol. 10, num. 8. DOI : 10.1098/rsos.230269.

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Short-term runoff forecasting in an alpine catchment with a long short-term memory neural network

C. Frank; M. Rußwurm; J. Fluixa-Sanmartin; D. Tuia 

Frontiers in Water. 2023-04-19. Vol. 5. DOI : 10.3389/frwa.2023.1126310.

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Social media and deep learning reveal specific cultural preferences for biodiversity

I. Havinga; D. Marcos; P. Bogaart; D. Massimino; L. Hein et al. 

People and Nature. 2023-02-19. Vol. 5, num. 3, p. 981-998. DOI : 10.1002/pan3.10466.

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End-to-end learned early classification of time series for in-season crop type mapping

M. Rußwurm; N. Courty; R. Emonet; S. Lefèvre; D. Tuia et al. 

ISPRS Journal of Photogrammetry and Remote Sensing. 2023-01-25. Vol. 196, p. 445-456. DOI : 10.1016/j.isprsjprs.2022.12.016.

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Predicting the liveability of Dutch cities with aerial images and semantic intermediate concepts

A. Levering; D. Marcos; J. van Vliet; D. Tuia 

Remote Sensing of Environment. 2023-01-25. Vol. 287, p. 113454. DOI : 10.1016/j.rse.2023.113454.

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2022

Geoinformation Harvesting From Social Media Data: A community remote sensing approach

X. X. Zhu; Y. Wang; M. Kochupillai; M. Werner; M. Haeberle et al. 

Ieee Geoscience And Remote Sensing Magazine. 2022-12-01. Vol. 10, num. 4, p. 150-180. DOI : 10.1109/MGRS.2022.3219584.

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Attribute Prediction as Multiple Instance Learning

D. Marcos Gonzalez; A. Potze; W. Xu; D. Tuia; Z. Akata 

Transactions on Machine Learning Research. 2022-09-06. Vol. 08.

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Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

J. Sauder; M. Genzel; P. Jung 

IEEE Journal on Selected Areas in Information Theory. 2022-11-11. Vol. 3, num. 3, p. 481-492. DOI : 10.1109/JSAIT.2022.3221644.

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Fine-grained population mapping from coarse census counts and open geodata

N. Metzger; J. E. Vargas-Muñoz; R. C. Daudt; B. Kellenberger; T. T-T. Whelan et al. 

Scientific Reports. 2022-12-01. Vol. 12, num. 1. DOI : 10.1038/s41598-022-24495-w.

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Mapping forest in the Swiss Alps treeline ecotone with explainable deep learning

T-A. Nguyen; B. Kellenberger; D. Tuia 

Remote Sensing of Environment. 2022-09-02. Vol. 281, p. 113217. DOI : 10.1016/j.rse.2022.113217.

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Perspectives in machine learning for wildlife conservation

D. Tuia; B. Kellenberger; S. Beery; B. R. Costelloe; S. Zuffi et al. 

Nature Communications. 2022-02-09. Vol. 13, num. 1, p. 792. DOI : 10.1038/s41467-022-27980-y.

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Deep Learning and Earth Observation to Support the Sustainable Development Goals: Current Approaches, Open Challenges, and Future Opportunities

C. Persello; J. D. Wegner; R. Haensch; D. Tuia; P. Ghamisi et al. 

IEEE Geoscience And Remote Sensing Magazine. 2022-01-13. Vol. 10, num. 2, p. 172 – 200. DOI : 10.1109/MGRS.2021.3136100.

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Civil war hinders crop production and threatens food security in Syria

X-Y. Li; X. Li; Z. Fan; L. Mi; T. Kandakji et al. 

Nature Food. 2022-01-10. Vol. 3, num. 1, p. 38-+. DOI : 10.1038/s43016-021-00432-4.

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Semantic Segmentation of Remote Sensing Images With Sparse Annotations

Y. Hua; D. Marcos; L. Mou; X. X. Zhu; D. Tuia 

Ieee Geoscience And Remote Sensing Letters. 2022-01-01. Vol. 19, p. 1-5, 8006305. DOI : 10.1109/LGRS.2021.3051053.

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A Semisupervised CRF Model for CNN-Based Semantic Segmentation With Sparse Ground Truth

L. Maggiolo; D. Marcos; G. Moser; S. B. Serpico; D. Tuia 

IEEE Transactions On Geoscience And Remote Sensing. 2022-01-19. Vol. 60, num. 5606315. DOI : 10.1109/TGRS.2021.3095832.

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2021

Wasserstein Adversarial Regularization for learning with label noise

K. Fatras; B. B. Damodaran; S. Lobry; R. Flamary; D. Tuia et al. 

IEEE Transactions on Pattern Analysis and Machine Intelligence. 2021.  p. 1-1. DOI : 10.1109/TPAMI.2021.3094662.

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deSpeckNet: Generalizing Deep Learning-Based SAR Image Despeckling

A. G. Mullissa; D. Marcos; D. Tuia; M. Herold; J. Reiche 

IEEE Transactions on Geoscience and Remote Sensing. 2021-12-06. Vol. 60, num. 5200315, p. 1-15. DOI : 10.1109/TGRS.2020.3042694.

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Counting using deep learning regression gives value to ecological surveys

J. P. A. Hoekendijk; B. Kellenberger; G. Aarts; S. Brasseur; S. S. H. Poiesz et al. 

Scientific Reports. 2021-12-01. Vol. 11, num. 1, p. 1-12, 23209. DOI : 10.1038/s41598-021-02387-9.

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Social media and deep learning capture the aesthetic quality of the landscape

I. Havinga; D. Marcos; P. W. Bogaart; L. Hein; D. Tuia 

Scientific Reports. 2021-10-08. Vol. 11, p. 1-11, 20000. DOI : 10.1038/s41598-021-99282-0.

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Deploying machine learning to assist digital humanitarians: making image annotation in OpenStreetMap more efficient

J. E. Vargas Muñoz; D. Tuia; A. X. Falcão 

International Journal of Geographical Information Science. 2021. Vol. 35, num. 9, p. 1725-1745. DOI : 10.1080/13658816.2020.1814303.

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Toward a Collective Agenda on AI for Earth Science Data Analysis

D. Tuia; R. Roscher; J. D. Wegner; N. Jacobs; X. Zhu et al. 

IEEE Geoscience and Remote Sensing Magazine. 2021-06-16. Vol. 9, num. 2, p. 88-104. DOI : 10.1109/MGRS.2020.3043504.

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Muti-modal learning in photogrammetry and remote sensing

M. Y. Yang; L. Landrieu; D. Tuia; C. Toth 

Isprs Journal Of Photogrammetry And Remote Sensing. 2021-06-01. Vol. 176, p. 54-54. DOI : 10.1016/j.isprsjprs.2021.03.022.

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On the relation between landscape beauty and land cover: A case study in the U.K. at Sentinel-2 resolution with interpretable AI

A. Levering; D. Marcos; D. Tuia 

ISPRS Journal of Photogrammetry and Remote Sensing. 2021. Vol. 177, p. 194-203. DOI : 10.1016/j.isprsjprs.2021.04.020.

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OpenStreetMap: Challenges and Opportunities in Machine Learning and Remote Sensing

J. E. Vargas-Munoz; S. Srivastava; D. Tuia; A. X. Falcao 

Ieee Geoscience And Remote Sensing Magazine. 2021-03-01. Vol. 9, num. 1, p. 184-199. DOI : 10.1109/MGRS.2020.2994107.

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21 000 birds in 4.5 h: efficient large‐scale seabird detection with machine learning

B. Kellenberger; T. Veen; E. Folmer; D. Tuia 

Remote Sensing in Ecology and Conservation. 2021. Vol. 7, num. 3, p. 445-460. DOI : 10.1002/rse2.200.

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2020

Deep learning for automated detection of Drosophila suzukii : potential for UAV ‐based monitoring

P. P. Roosjen; B. Kellenberger; L. Kooistra; D. R. Green; J. Fahrentrapp 

Pest Management Science. 2020. Vol. 76, num. 9, p. 2994-3002. DOI : 10.1002/ps.5845.

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Defining and spatially modelling cultural ecosystem services using crowdsourced data

I. Havinga; P. W. Bogaart; L. Hein; D. Tuia 

Ecosystem Services. 2020. Vol. 43, p. 101091. DOI : 10.1016/j.ecoser.2020.101091.

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Fine-grained landuse characterization using ground-based pictures: a deep learning solution based on globally available data

S. Srivastava; J. E. Vargas Muñoz; S. Lobry; D. Tuia 

International Journal of Geographical Information Science. 2020. Vol. 34, num. 6, p. 1117-1136. DOI : 10.1080/13658816.2018.1542698.

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AIDE: Accelerating image‐based ecological surveys with interactive machine learning

B. Kellenberger; D. Tuia; D. Morris 

Methods in Ecology and Evolution. 2020-12-03. Vol. 11, num. 12, p. 1716-1727. DOI : 10.1111/2041-210X.13489.

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RSVQA: Visual Question Answering for Remote Sensing Data

S. Lobry; D. Marcos; J. Murray; D. Tuia 

IEEE Transactions on Geoscience and Remote Sensing. 2020-11-26. Vol. 58, num. 12, p. 8555-8566. DOI : 10.1109/TGRS.2020.2988782.

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Concept Discovery for The Interpretation of Landscape Scenicness

P. Arendsen; D. Marcos; D. Tuia 

Machine Learning and Knowledge Extraction. 2020-10-05. Vol. 2, num. 4, p. 397-413. DOI : 10.3390/make2040022.

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A deep learning framework for matching of SAR and optical imagery

L. H. Hughes; D. Marcos; S. Lobry; D. Tuia; M. Schmitt 

ISPRS Journal of Photogrammetry and Remote Sensing. 2020-09-23. Vol. 169, p. 166-179. DOI : 10.1016/j.isprsjprs.2020.09.012.

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