DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation Applications Article Swipe
Ibrahim Fayad
,
Max Zimmer
,
Martin Schwartz
,
Fabian Gieseke
,
Philippe Ciais
,
Gabriel Belouze
,
Sarah Brood
,
Aurélien De Truchis
,
Alexandre d’Aspremont
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2502.17066
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2502.17066
Significant efforts have been directed towards adapting self-supervised multimodal learning for Earth observation applications. However, most current methods produce coarse patch-sized embeddings, limiting their effectiveness and integration with other modalities like LiDAR. To close this gap, we present DUNIA, an approach to learn pixel-sized embeddings through cross-modal alignment between images and full-waveform LiDAR data. As the model is trained in a contrastive manner, the embeddings can be directly leveraged in the context of a variety of environmental monitoring tasks in a zero-shot setting. In our experiments, we demonstrate the effectiveness of the embeddings for seven such tasks: canopy height mapping, fractional canopy cover, land cover mapping, tree species identification, plant area index, crop type classification, and per-pixel waveform-based vertical structure mapping. The results show that the embeddings, along with zero-shot classifiers, often outperform specialized supervised models, even in low-data regimes. In the fine-tuning setting, we show strong performances near or better than the state-of-the-art on five out of six tasks.
Related Topics
Concepts
No concepts available.
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2502.17066
- https://arxiv.org/pdf/2502.17066
- OA Status
- green
- OpenAlex ID
- https://openalex.org/W4414847475
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4414847475Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2502.17066Digital Object Identifier
- Title
-
DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation ApplicationsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-02-24Full publication date if available
- Authors
-
Ibrahim Fayad, Max Zimmer, Martin Schwartz, Fabian Gieseke, Philippe Ciais, Gabriel Belouze, Sarah Brood, Aurélien De Truchis, Alexandre d’AspremontList of authors in order
- Landing page
-
https://arxiv.org/abs/2502.17066Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2502.17066Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2502.17066Direct OA link when available
- Cited by
-
0Total citation count in OpenAlex
Full payload
| id | https://openalex.org/W4414847475 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.2502.17066 |
| ids.doi | https://doi.org/10.48550/arxiv.2502.17066 |
| ids.openalex | https://openalex.org/W4414847475 |
| fwci | |
| type | preprint |
| title | DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation Applications |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10757 |
| topics[0].field.id | https://openalex.org/fields/33 |
| topics[0].field.display_name | Social Sciences |
| topics[0].score | 0.9466999769210815 |
| topics[0].domain.id | https://openalex.org/domains/2 |
| topics[0].domain.display_name | Social Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/3305 |
| topics[0].subfield.display_name | Geography, Planning and Development |
| topics[0].display_name | Geographic Information Systems Studies |
| topics[1].id | https://openalex.org/T12698 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9452000260353088 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2215 |
| topics[1].subfield.display_name | Building and Construction |
| topics[1].display_name | 3D Modeling in Geospatial Applications |
| topics[2].id | https://openalex.org/T13067 |
| topics[2].field.id | https://openalex.org/fields/19 |
| topics[2].field.display_name | Earth and Planetary Sciences |
| topics[2].score | 0.9332000017166138 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1906 |
| topics[2].subfield.display_name | Geochemistry and Petrology |
| topics[2].display_name | Geological Modeling and Analysis |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:2502.17066 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/2502.17066 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | text |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/2502.17066 |
| locations[1].id | doi:10.48550/arxiv.2502.17066 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400194 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | arXiv (Cornell University) |
| locations[1].source.host_organization | https://openalex.org/I205783295 |
| locations[1].source.host_organization_name | Cornell University |
| locations[1].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://doi.org/10.48550/arxiv.2502.17066 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5088075756 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-7504-5623 |
| authorships[0].author.display_name | Ibrahim Fayad |
| authorships[0].countries | FR |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210124937 |
| authorships[0].affiliations[0].raw_affiliation_string | LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (Bât. 12, avenue de la Terrasse, F-91198 GIF-SUR-YVETTE CEDEX - France) |
| authorships[0].affiliations[1].institution_ids | https://openalex.org/I4210121852 |
| authorships[0].affiliations[1].raw_affiliation_string | Kayrros (France) |
| authorships[0].institutions[0].id | https://openalex.org/I4210121852 |
| authorships[0].institutions[0].ror | https://ror.org/02x6t2s89 |
| authorships[0].institutions[0].type | company |
| authorships[0].institutions[0].lineage | https://openalex.org/I4210121852 |
| authorships[0].institutions[0].country_code | FR |
| authorships[0].institutions[0].display_name | Kopoos Consulting (France) |
| authorships[0].institutions[1].id | https://openalex.org/I4210124937 |
| authorships[0].institutions[1].ror | https://ror.org/03dsd0g48 |
| authorships[0].institutions[1].type | facility |
| authorships[0].institutions[1].lineage | https://openalex.org/I1294671590, https://openalex.org/I1294671590, https://openalex.org/I195731000, https://openalex.org/I2738703131, https://openalex.org/I277688954, https://openalex.org/I4210124937, https://openalex.org/I4210148025 |
| authorships[0].institutions[1].country_code | FR |
| authorships[0].institutions[1].display_name | Laboratoire des Sciences du Climat et de l'Environnement |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Ibrahim Fayad |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Kayrros (France), LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (Bât. 12, avenue de la Terrasse, F-91198 GIF-SUR-YVETTE CEDEX - France) |
| authorships[1].author.id | https://openalex.org/A5057301701 |
| authorships[1].author.orcid | https://orcid.org/0009-0007-8683-1030 |
| authorships[1].author.display_name | Max Zimmer |
| authorships[1].countries | DE |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I195893171 |
| authorships[1].affiliations[0].raw_affiliation_string | ZIB - Zuse Institute Berlin (Konrad-Zuse-Zentrum für Informationstechnik Berlin (ZIB Takustraße 7 D-14195 Berlin-Dahlem - Germany) |
| authorships[1].institutions[0].id | https://openalex.org/I195893171 |
| authorships[1].institutions[0].ror | https://ror.org/02eva5865 |
| authorships[1].institutions[0].type | facility |
| authorships[1].institutions[0].lineage | https://openalex.org/I195893171 |
| authorships[1].institutions[0].country_code | DE |
| authorships[1].institutions[0].display_name | Zuse Institute Berlin |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Zimmer, Max |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | ZIB - Zuse Institute Berlin (Konrad-Zuse-Zentrum für Informationstechnik Berlin (ZIB Takustraße 7 D-14195 Berlin-Dahlem - Germany) |
| authorships[2].author.id | https://openalex.org/A5086030901 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-4038-9068 |
| authorships[2].author.display_name | Martin Schwartz |
| authorships[2].countries | FR |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210124937 |
| authorships[2].affiliations[0].raw_affiliation_string | LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (Bât. 12, avenue de la Terrasse, F-91198 GIF-SUR-YVETTE CEDEX - France) |
| authorships[2].institutions[0].id | https://openalex.org/I4210124937 |
| authorships[2].institutions[0].ror | https://ror.org/03dsd0g48 |
| authorships[2].institutions[0].type | facility |
| authorships[2].institutions[0].lineage | https://openalex.org/I1294671590, https://openalex.org/I1294671590, https://openalex.org/I195731000, https://openalex.org/I2738703131, https://openalex.org/I277688954, https://openalex.org/I4210124937, https://openalex.org/I4210148025 |
| authorships[2].institutions[0].country_code | FR |
| authorships[2].institutions[0].display_name | Laboratoire des Sciences du Climat et de l'Environnement |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Schwartz, Martin |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (Bât. 12, avenue de la Terrasse, F-91198 GIF-SUR-YVETTE CEDEX - France) |
| authorships[3].author.id | https://openalex.org/A5023532714 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-7093-5803 |
| authorships[3].author.display_name | Fabian Gieseke |
| authorships[3].countries | DE |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I22465464 |
| authorships[3].affiliations[0].raw_affiliation_string | WWU - Westfälische Wilhelms-Universität Münster = University of Münster (Universität Münster Schlossplatz 2 48149 Münster - Germany) |
| authorships[3].institutions[0].id | https://openalex.org/I22465464 |
| authorships[3].institutions[0].ror | https://ror.org/00pd74e08 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I22465464 |
| authorships[3].institutions[0].country_code | DE |
| authorships[3].institutions[0].display_name | University of Münster |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Gieseke, Fabian |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | WWU - Westfälische Wilhelms-Universität Münster = University of Münster (Universität Münster Schlossplatz 2 48149 Münster - Germany) |
| authorships[4].author.id | https://openalex.org/A5070378593 |
| authorships[4].author.orcid | https://orcid.org/0000-0001-8560-4943 |
| authorships[4].author.display_name | Philippe Ciais |
| authorships[4].countries | FR |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210124937 |
| authorships[4].affiliations[0].raw_affiliation_string | LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (Bât. 12, avenue de la Terrasse, F-91198 GIF-SUR-YVETTE CEDEX - France) |
| authorships[4].institutions[0].id | https://openalex.org/I4210124937 |
| authorships[4].institutions[0].ror | https://ror.org/03dsd0g48 |
| authorships[4].institutions[0].type | facility |
| authorships[4].institutions[0].lineage | https://openalex.org/I1294671590, https://openalex.org/I1294671590, https://openalex.org/I195731000, https://openalex.org/I2738703131, https://openalex.org/I277688954, https://openalex.org/I4210124937, https://openalex.org/I4210148025 |
| authorships[4].institutions[0].country_code | FR |
| authorships[4].institutions[0].display_name | Laboratoire des Sciences du Climat et de l'Environnement |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Philippe Ciais |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (Bât. 12, avenue de la Terrasse, F-91198 GIF-SUR-YVETTE CEDEX - France) |
| authorships[5].author.id | https://openalex.org/A5119398491 |
| authorships[5].author.orcid | |
| authorships[5].author.display_name | Gabriel Belouze |
| authorships[5].countries | FR |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I4210124937 |
| authorships[5].affiliations[0].raw_affiliation_string | LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (Bât. 12, avenue de la Terrasse, F-91198 GIF-SUR-YVETTE CEDEX - France) |
| authorships[5].institutions[0].id | https://openalex.org/I4210124937 |
| authorships[5].institutions[0].ror | https://ror.org/03dsd0g48 |
| authorships[5].institutions[0].type | facility |
| authorships[5].institutions[0].lineage | https://openalex.org/I1294671590, https://openalex.org/I1294671590, https://openalex.org/I195731000, https://openalex.org/I2738703131, https://openalex.org/I277688954, https://openalex.org/I4210124937, https://openalex.org/I4210148025 |
| authorships[5].institutions[0].country_code | FR |
| authorships[5].institutions[0].display_name | Laboratoire des Sciences du Climat et de l'Environnement |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Gabriel Belouze |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (Bât. 12, avenue de la Terrasse, F-91198 GIF-SUR-YVETTE CEDEX - France) |
| authorships[6].author.id | https://openalex.org/A5119398492 |
| authorships[6].author.orcid | |
| authorships[6].author.display_name | Sarah Brood |
| authorships[6].affiliations[0].raw_affiliation_string | SIERRA - Statistical Machine Learning and Parsimony (48 Rue Barrault, 75013 Paris - France) |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Sarah Brood |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | SIERRA - Statistical Machine Learning and Parsimony (48 Rue Barrault, 75013 Paris - France) |
| authorships[7].author.id | https://openalex.org/A5061243037 |
| authorships[7].author.orcid | https://orcid.org/0000-0003-3515-4176 |
| authorships[7].author.display_name | Aurélien De Truchis |
| authorships[7].countries | FR |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I4210121852 |
| authorships[7].affiliations[0].raw_affiliation_string | Kayrros (France) |
| authorships[7].institutions[0].id | https://openalex.org/I4210121852 |
| authorships[7].institutions[0].ror | https://ror.org/02x6t2s89 |
| authorships[7].institutions[0].type | company |
| authorships[7].institutions[0].lineage | https://openalex.org/I4210121852 |
| authorships[7].institutions[0].country_code | FR |
| authorships[7].institutions[0].display_name | Kopoos Consulting (France) |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | De Truchis, Aurelien |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | Kayrros (France) |
| authorships[8].author.id | https://openalex.org/A5063516752 |
| authorships[8].author.orcid | https://orcid.org/0000-0003-3851-216X |
| authorships[8].author.display_name | Alexandre d’Aspremont |
| authorships[8].countries | FR |
| authorships[8].affiliations[0].institution_ids | https://openalex.org/I29607241 |
| authorships[8].affiliations[0].raw_affiliation_string | LIENS - Laboratoire d'informatique de l'école normale supérieure (45 Rue d'Ulm 75230 PARIS CEDEX 05 - France) |
| authorships[8].affiliations[1].institution_ids | https://openalex.org/I1294671590 |
| authorships[8].affiliations[1].raw_affiliation_string | CNRS - Centre National de la Recherche Scientifique (France) |
| authorships[8].affiliations[2].raw_affiliation_string | SIERRA - Statistical Machine Learning and Parsimony (48 Rue Barrault, 75013 Paris - France) |
| authorships[8].institutions[0].id | https://openalex.org/I1294671590 |
| authorships[8].institutions[0].ror | https://ror.org/02feahw73 |
| authorships[8].institutions[0].type | government |
| authorships[8].institutions[0].lineage | https://openalex.org/I1294671590 |
| authorships[8].institutions[0].country_code | FR |
| authorships[8].institutions[0].display_name | Centre National de la Recherche Scientifique |
| authorships[8].institutions[1].id | https://openalex.org/I29607241 |
| authorships[8].institutions[1].ror | https://ror.org/05a0dhs15 |
| authorships[8].institutions[1].type | other |
| authorships[8].institutions[1].lineage | https://openalex.org/I2746051580, https://openalex.org/I29607241 |
| authorships[8].institutions[1].country_code | FR |
| authorships[8].institutions[1].display_name | École Normale Supérieure - PSL |
| authorships[8].author_position | last |
| authorships[8].raw_author_name | d'Aspremont, Alexandre |
| authorships[8].is_corresponding | False |
| authorships[8].raw_affiliation_strings | CNRS - Centre National de la Recherche Scientifique (France), LIENS - Laboratoire d'informatique de l'école normale supérieure (45 Rue d'Ulm 75230 PARIS CEDEX 05 - France), SIERRA - Statistical Machine Learning and Parsimony (48 Rue Barrault, 75013 Paris - France) |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/2502.17066 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation Applications |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T10757 |
| primary_topic.field.id | https://openalex.org/fields/33 |
| primary_topic.field.display_name | Social Sciences |
| primary_topic.score | 0.9466999769210815 |
| primary_topic.domain.id | https://openalex.org/domains/2 |
| primary_topic.domain.display_name | Social Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/3305 |
| primary_topic.subfield.display_name | Geography, Planning and Development |
| primary_topic.display_name | Geographic Information Systems Studies |
| cited_by_count | 0 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:2502.17066 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/2502.17066 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | text |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/2502.17066 |
| primary_location.id | pmh:oai:arXiv.org:2502.17066 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/2502.17066 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | text |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2502.17066 |
| publication_date | 2025-02-24 |
| publication_year | 2025 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 60, 73, 80 |
| abstract_inverted_index.As | 54 |
| abstract_inverted_index.In | 83, 140 |
| abstract_inverted_index.To | 32 |
| abstract_inverted_index.an | 39 |
| abstract_inverted_index.be | 66 |
| abstract_inverted_index.in | 59, 69, 79, 137 |
| abstract_inverted_index.is | 57 |
| abstract_inverted_index.of | 72, 75, 90, 157 |
| abstract_inverted_index.on | 154 |
| abstract_inverted_index.or | 149 |
| abstract_inverted_index.to | 41 |
| abstract_inverted_index.we | 36, 86, 144 |
| abstract_inverted_index.The | 121 |
| abstract_inverted_index.and | 25, 50, 115 |
| abstract_inverted_index.can | 65 |
| abstract_inverted_index.for | 10, 93 |
| abstract_inverted_index.our | 84 |
| abstract_inverted_index.out | 156 |
| abstract_inverted_index.six | 158 |
| abstract_inverted_index.the | 55, 63, 70, 88, 91, 125, 141, 152 |
| abstract_inverted_index.area | 110 |
| abstract_inverted_index.been | 3 |
| abstract_inverted_index.crop | 112 |
| abstract_inverted_index.even | 136 |
| abstract_inverted_index.five | 155 |
| abstract_inverted_index.gap, | 35 |
| abstract_inverted_index.have | 2 |
| abstract_inverted_index.land | 103 |
| abstract_inverted_index.like | 30 |
| abstract_inverted_index.most | 15 |
| abstract_inverted_index.near | 148 |
| abstract_inverted_index.show | 123, 145 |
| abstract_inverted_index.such | 95 |
| abstract_inverted_index.than | 151 |
| abstract_inverted_index.that | 124 |
| abstract_inverted_index.this | 34 |
| abstract_inverted_index.tree | 106 |
| abstract_inverted_index.type | 113 |
| abstract_inverted_index.with | 27, 128 |
| abstract_inverted_index.Earth | 11 |
| abstract_inverted_index.LiDAR | 52 |
| abstract_inverted_index.along | 127 |
| abstract_inverted_index.close | 33 |
| abstract_inverted_index.cover | 104 |
| abstract_inverted_index.data. | 53 |
| abstract_inverted_index.learn | 42 |
| abstract_inverted_index.model | 56 |
| abstract_inverted_index.often | 131 |
| abstract_inverted_index.other | 28 |
| abstract_inverted_index.plant | 109 |
| abstract_inverted_index.seven | 94 |
| abstract_inverted_index.tasks | 78 |
| abstract_inverted_index.their | 23 |
| abstract_inverted_index.DUNIA, | 38 |
| abstract_inverted_index.LiDAR. | 31 |
| abstract_inverted_index.better | 150 |
| abstract_inverted_index.canopy | 97, 101 |
| abstract_inverted_index.coarse | 19 |
| abstract_inverted_index.cover, | 102 |
| abstract_inverted_index.height | 98 |
| abstract_inverted_index.images | 49 |
| abstract_inverted_index.index, | 111 |
| abstract_inverted_index.strong | 146 |
| abstract_inverted_index.tasks. | 159 |
| abstract_inverted_index.tasks: | 96 |
| abstract_inverted_index.between | 48 |
| abstract_inverted_index.context | 71 |
| abstract_inverted_index.current | 16 |
| abstract_inverted_index.efforts | 1 |
| abstract_inverted_index.manner, | 62 |
| abstract_inverted_index.methods | 17 |
| abstract_inverted_index.models, | 135 |
| abstract_inverted_index.present | 37 |
| abstract_inverted_index.produce | 18 |
| abstract_inverted_index.results | 122 |
| abstract_inverted_index.species | 107 |
| abstract_inverted_index.through | 45 |
| abstract_inverted_index.towards | 5 |
| abstract_inverted_index.trained | 58 |
| abstract_inverted_index.variety | 74 |
| abstract_inverted_index.However, | 14 |
| abstract_inverted_index.adapting | 6 |
| abstract_inverted_index.approach | 40 |
| abstract_inverted_index.directed | 4 |
| abstract_inverted_index.directly | 67 |
| abstract_inverted_index.learning | 9 |
| abstract_inverted_index.limiting | 22 |
| abstract_inverted_index.low-data | 138 |
| abstract_inverted_index.mapping, | 99, 105 |
| abstract_inverted_index.mapping. | 120 |
| abstract_inverted_index.regimes. | 139 |
| abstract_inverted_index.setting, | 143 |
| abstract_inverted_index.setting. | 82 |
| abstract_inverted_index.vertical | 118 |
| abstract_inverted_index.alignment | 47 |
| abstract_inverted_index.leveraged | 68 |
| abstract_inverted_index.per-pixel | 116 |
| abstract_inverted_index.structure | 119 |
| abstract_inverted_index.zero-shot | 81, 129 |
| abstract_inverted_index.embeddings | 44, 64, 92 |
| abstract_inverted_index.fractional | 100 |
| abstract_inverted_index.modalities | 29 |
| abstract_inverted_index.monitoring | 77 |
| abstract_inverted_index.multimodal | 8 |
| abstract_inverted_index.outperform | 132 |
| abstract_inverted_index.supervised | 134 |
| abstract_inverted_index.Significant | 0 |
| abstract_inverted_index.contrastive | 61 |
| abstract_inverted_index.cross-modal | 46 |
| abstract_inverted_index.demonstrate | 87 |
| abstract_inverted_index.embeddings, | 21, 126 |
| abstract_inverted_index.fine-tuning | 142 |
| abstract_inverted_index.integration | 26 |
| abstract_inverted_index.observation | 12 |
| abstract_inverted_index.patch-sized | 20 |
| abstract_inverted_index.pixel-sized | 43 |
| abstract_inverted_index.specialized | 133 |
| abstract_inverted_index.classifiers, | 130 |
| abstract_inverted_index.experiments, | 85 |
| abstract_inverted_index.performances | 147 |
| abstract_inverted_index.applications. | 13 |
| abstract_inverted_index.effectiveness | 24, 89 |
| abstract_inverted_index.environmental | 76 |
| abstract_inverted_index.full-waveform | 51 |
| abstract_inverted_index.waveform-based | 117 |
| abstract_inverted_index.classification, | 114 |
| abstract_inverted_index.identification, | 108 |
| abstract_inverted_index.self-supervised | 7 |
| abstract_inverted_index.state-of-the-art | 153 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 9 |
| citation_normalized_percentile |