FUSION OF SENTINEL-2 AND PLANETSCOPE IMAGERY FOR VEGETATION DETECTION AND MONITORING Article Swipe
Mateo Gašparović
,
Damir Medak
,
Ivan Pilaš
,
Luka Jurjević
,
Ivan Balenović
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.5194/isprs-archives-xlii-1-155-2018
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.5194/isprs-archives-xlii-1-155-2018
Different spatial resolutions satellite imagery with global almost daily revisit time provide valuable information about the earth surface in a short time. Based on the remote sensing methods satellite imagery can have different applications like environmental development, urban monitoring, etc. For accurate vegetation detection and monitoring, especially in urban areas, spectral characteristics, as well as the spatial resolution of satellite imagery is important. In this research, 10-m and 20-m Sentinel-2 and 3.7-m PlanetScope satellite imagery were used. Although in nowadays research Sentinel-2 satellite imagery is often used for land-cover classification or vegetation detection and monitoring, we decided to test a fusion of Sentinel-2 imagery with PlanetScope because of its higher spatial resolution. The main goal of this research is a new method for Sentinel-2 and PlanetScope imagery fusion. The fusion method validation was provided based on the land-cover classification accuracy. Three land-cover classifications were made based on the Sentinel-2, PlanetScope and fused imagery. As expected, results show better accuracy for PS and fused imagery than the Sentinel-2 imagery. PlanetScope and fused imagery have almost the same accuracy. For the vegetation monitoring testing, the Normalized Difference Vegetation Index (NDVI) from Sentinel-2 and fused imagery was calculated and mutually compared. In this research, all methods and tests, image fusion and satellite imagery classification were made in the free and open source programs. The method developed and presented in this paper can easily be applied to other sciences, such as urbanism, forestry, agronomy, ecology and geology.
Related Topics
Concepts
Remote sensing
Satellite imagery
Vegetation (pathology)
Satellite
Environmental science
Normalized Difference Vegetation Index
Land cover
Image fusion
Image resolution
Geology
Land use
Computer science
Climate change
Artificial intelligence
Ecology
Engineering
Biology
Pathology
Image (mathematics)
Medicine
Aerospace engineering
Oceanography
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.5194/isprs-archives-xlii-1-155-2018
- https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1/155/2018/isprs-archives-XLII-1-155-2018.pdf
- OA Status
- diamond
- Cited By
- 49
- References
- 19
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2893700198
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2893700198Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.5194/isprs-archives-xlii-1-155-2018Digital Object Identifier
- Title
-
FUSION OF SENTINEL-2 AND PLANETSCOPE IMAGERY FOR VEGETATION DETECTION AND MONITORINGWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-09-26Full publication date if available
- Authors
-
Mateo Gašparović, Damir Medak, Ivan Pilaš, Luka Jurjević, Ivan BalenovićList of authors in order
- Landing page
-
https://doi.org/10.5194/isprs-archives-xlii-1-155-2018Publisher landing page
- PDF URL
-
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1/155/2018/isprs-archives-XLII-1-155-2018.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1/155/2018/isprs-archives-XLII-1-155-2018.pdfDirect OA link when available
- Concepts
-
Remote sensing, Satellite imagery, Vegetation (pathology), Satellite, Environmental science, Normalized Difference Vegetation Index, Land cover, Image fusion, Image resolution, Geology, Land use, Computer science, Climate change, Artificial intelligence, Ecology, Engineering, Biology, Pathology, Image (mathematics), Medicine, Aerospace engineering, OceanographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
49Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 13, 2024: 3, 2023: 5, 2022: 5, 2021: 5Per-year citation counts (last 5 years)
- References (count)
-
19Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2893700198 |
|---|---|
| doi | https://doi.org/10.5194/isprs-archives-xlii-1-155-2018 |
| ids.doi | https://doi.org/10.5194/isprs-archives-xlii-1-155-2018 |
| ids.mag | 2893700198 |
| ids.openalex | https://openalex.org/W2893700198 |
| fwci | 3.06685082 |
| type | article |
| title | FUSION OF SENTINEL-2 AND PLANETSCOPE IMAGERY FOR VEGETATION DETECTION AND MONITORING |
| biblio.issue | |
| biblio.volume | XLII-1 |
| biblio.last_page | 160 |
| biblio.first_page | 155 |
| topics[0].id | https://openalex.org/T13890 |
| topics[0].field.id | https://openalex.org/fields/19 |
| topics[0].field.display_name | Earth and Planetary Sciences |
| topics[0].score | 0.9986000061035156 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1902 |
| topics[0].subfield.display_name | Atmospheric Science |
| topics[0].display_name | Remote Sensing and Land Use |
| topics[1].id | https://openalex.org/T10111 |
| topics[1].field.id | https://openalex.org/fields/23 |
| topics[1].field.display_name | Environmental Science |
| topics[1].score | 0.9979000091552734 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2303 |
| topics[1].subfield.display_name | Ecology |
| topics[1].display_name | Remote Sensing in Agriculture |
| topics[2].id | https://openalex.org/T10689 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9975000023841858 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2214 |
| topics[2].subfield.display_name | Media Technology |
| topics[2].display_name | Remote-Sensing Image Classification |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C62649853 |
| concepts[0].level | 1 |
| concepts[0].score | 0.8160620927810669 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q199687 |
| concepts[0].display_name | Remote sensing |
| concepts[1].id | https://openalex.org/C2778102629 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7052873373031616 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q725252 |
| concepts[1].display_name | Satellite imagery |
| concepts[2].id | https://openalex.org/C2776133958 |
| concepts[2].level | 2 |
| concepts[2].score | 0.6605952382087708 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q7918366 |
| concepts[2].display_name | Vegetation (pathology) |
| concepts[3].id | https://openalex.org/C19269812 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5652082562446594 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q26540 |
| concepts[3].display_name | Satellite |
| concepts[4].id | https://openalex.org/C39432304 |
| concepts[4].level | 0 |
| concepts[4].score | 0.5335512757301331 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q188847 |
| concepts[4].display_name | Environmental science |
| concepts[5].id | https://openalex.org/C1549246 |
| concepts[5].level | 3 |
| concepts[5].score | 0.5243784785270691 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q718775 |
| concepts[5].display_name | Normalized Difference Vegetation Index |
| concepts[6].id | https://openalex.org/C2780648208 |
| concepts[6].level | 3 |
| concepts[6].score | 0.5081415176391602 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q3001793 |
| concepts[6].display_name | Land cover |
| concepts[7].id | https://openalex.org/C69744172 |
| concepts[7].level | 3 |
| concepts[7].score | 0.4891989231109619 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q860822 |
| concepts[7].display_name | Image fusion |
| concepts[8].id | https://openalex.org/C205372480 |
| concepts[8].level | 2 |
| concepts[8].score | 0.4131048619747162 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q210521 |
| concepts[8].display_name | Image resolution |
| concepts[9].id | https://openalex.org/C127313418 |
| concepts[9].level | 0 |
| concepts[9].score | 0.27126622200012207 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q1069 |
| concepts[9].display_name | Geology |
| concepts[10].id | https://openalex.org/C4792198 |
| concepts[10].level | 2 |
| concepts[10].score | 0.2060094177722931 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q1165944 |
| concepts[10].display_name | Land use |
| concepts[11].id | https://openalex.org/C41008148 |
| concepts[11].level | 0 |
| concepts[11].score | 0.19220373034477234 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[11].display_name | Computer science |
| concepts[12].id | https://openalex.org/C132651083 |
| concepts[12].level | 2 |
| concepts[12].score | 0.12089326977729797 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q7942 |
| concepts[12].display_name | Climate change |
| concepts[13].id | https://openalex.org/C154945302 |
| concepts[13].level | 1 |
| concepts[13].score | 0.11371514201164246 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[13].display_name | Artificial intelligence |
| concepts[14].id | https://openalex.org/C18903297 |
| concepts[14].level | 1 |
| concepts[14].score | 0.07217255234718323 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q7150 |
| concepts[14].display_name | Ecology |
| concepts[15].id | https://openalex.org/C127413603 |
| concepts[15].level | 0 |
| concepts[15].score | 0.06039890646934509 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[15].display_name | Engineering |
| concepts[16].id | https://openalex.org/C86803240 |
| concepts[16].level | 0 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[16].display_name | Biology |
| concepts[17].id | https://openalex.org/C142724271 |
| concepts[17].level | 1 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q7208 |
| concepts[17].display_name | Pathology |
| concepts[18].id | https://openalex.org/C115961682 |
| concepts[18].level | 2 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q860623 |
| concepts[18].display_name | Image (mathematics) |
| concepts[19].id | https://openalex.org/C71924100 |
| concepts[19].level | 0 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[19].display_name | Medicine |
| concepts[20].id | https://openalex.org/C146978453 |
| concepts[20].level | 1 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q3798668 |
| concepts[20].display_name | Aerospace engineering |
| concepts[21].id | https://openalex.org/C111368507 |
| concepts[21].level | 1 |
| concepts[21].score | 0.0 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q43518 |
| concepts[21].display_name | Oceanography |
| keywords[0].id | https://openalex.org/keywords/remote-sensing |
| keywords[0].score | 0.8160620927810669 |
| keywords[0].display_name | Remote sensing |
| keywords[1].id | https://openalex.org/keywords/satellite-imagery |
| keywords[1].score | 0.7052873373031616 |
| keywords[1].display_name | Satellite imagery |
| keywords[2].id | https://openalex.org/keywords/vegetation |
| keywords[2].score | 0.6605952382087708 |
| keywords[2].display_name | Vegetation (pathology) |
| keywords[3].id | https://openalex.org/keywords/satellite |
| keywords[3].score | 0.5652082562446594 |
| keywords[3].display_name | Satellite |
| keywords[4].id | https://openalex.org/keywords/environmental-science |
| keywords[4].score | 0.5335512757301331 |
| keywords[4].display_name | Environmental science |
| keywords[5].id | https://openalex.org/keywords/normalized-difference-vegetation-index |
| keywords[5].score | 0.5243784785270691 |
| keywords[5].display_name | Normalized Difference Vegetation Index |
| keywords[6].id | https://openalex.org/keywords/land-cover |
| keywords[6].score | 0.5081415176391602 |
| keywords[6].display_name | Land cover |
| keywords[7].id | https://openalex.org/keywords/image-fusion |
| keywords[7].score | 0.4891989231109619 |
| keywords[7].display_name | Image fusion |
| keywords[8].id | https://openalex.org/keywords/image-resolution |
| keywords[8].score | 0.4131048619747162 |
| keywords[8].display_name | Image resolution |
| keywords[9].id | https://openalex.org/keywords/geology |
| keywords[9].score | 0.27126622200012207 |
| keywords[9].display_name | Geology |
| keywords[10].id | https://openalex.org/keywords/land-use |
| keywords[10].score | 0.2060094177722931 |
| keywords[10].display_name | Land use |
| keywords[11].id | https://openalex.org/keywords/computer-science |
| keywords[11].score | 0.19220373034477234 |
| keywords[11].display_name | Computer science |
| keywords[12].id | https://openalex.org/keywords/climate-change |
| keywords[12].score | 0.12089326977729797 |
| keywords[12].display_name | Climate change |
| keywords[13].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[13].score | 0.11371514201164246 |
| keywords[13].display_name | Artificial intelligence |
| keywords[14].id | https://openalex.org/keywords/ecology |
| keywords[14].score | 0.07217255234718323 |
| keywords[14].display_name | Ecology |
| keywords[15].id | https://openalex.org/keywords/engineering |
| keywords[15].score | 0.06039890646934509 |
| keywords[15].display_name | Engineering |
| language | en |
| locations[0].id | doi:10.5194/isprs-archives-xlii-1-155-2018 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2737215817 |
| locations[0].source.issn | 1682-1750, 1682-1777, 2194-9034 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1682-1750 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences |
| locations[0].source.host_organization | https://openalex.org/P4310313756 |
| locations[0].source.host_organization_name | Copernicus Publications |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310313756 |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1/155/2018/isprs-archives-XLII-1-155-2018.pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| locations[0].landing_page_url | https://doi.org/10.5194/isprs-archives-xlii-1-155-2018 |
| locations[1].id | pmh:oai:doaj.org/article:b957945b5e87402f9867737c27207762 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].source.host_organization_lineage | |
| locations[1].license | cc-by-sa |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | https://openalex.org/licenses/cc-by-sa |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-1, Pp 155-160 (2018) |
| locations[1].landing_page_url | https://doaj.org/article/b957945b5e87402f9867737c27207762 |
| locations[2].id | pmh:oai:publications.copernicus.org:isprs-archives71881 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S4306400433 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | Biogeosciences (European Geosciences Union) |
| locations[2].source.host_organization | https://openalex.org/I2799957102 |
| locations[2].source.host_organization_name | European Geosciences Union |
| locations[2].source.host_organization_lineage | https://openalex.org/I2799957102 |
| locations[2].license | cc-by |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | Text |
| locations[2].license_id | https://openalex.org/licenses/cc-by |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | eISSN: 2194-9034 |
| locations[2].landing_page_url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1/155/2018/ |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5039337836 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-2345-7882 |
| authorships[0].author.display_name | Mateo Gašparović |
| authorships[0].countries | HR |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I181343428 |
| authorships[0].affiliations[0].raw_affiliation_string | Chair of Photogrammetry and Remote Sensing, Faculty of Geodesy, University of Zagreb, Kačićeva 26, Zagreb, Croatia |
| authorships[0].institutions[0].id | https://openalex.org/I181343428 |
| authorships[0].institutions[0].ror | https://ror.org/00mv6sv71 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I181343428 |
| authorships[0].institutions[0].country_code | HR |
| authorships[0].institutions[0].display_name | University of Zagreb |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | M. Gašparović |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Chair of Photogrammetry and Remote Sensing, Faculty of Geodesy, University of Zagreb, Kačićeva 26, Zagreb, Croatia |
| authorships[1].author.id | https://openalex.org/A5020669312 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-3660-0051 |
| authorships[1].author.display_name | Damir Medak |
| authorships[1].countries | HR |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I181343428 |
| authorships[1].affiliations[0].raw_affiliation_string | Chair of Geoinformatics, Faculty of Geodesy, University of Zagreb, Kačićeva 26, Zagreb, Croatia |
| authorships[1].institutions[0].id | https://openalex.org/I181343428 |
| authorships[1].institutions[0].ror | https://ror.org/00mv6sv71 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I181343428 |
| authorships[1].institutions[0].country_code | HR |
| authorships[1].institutions[0].display_name | University of Zagreb |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | D. Medak |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Chair of Geoinformatics, Faculty of Geodesy, University of Zagreb, Kačićeva 26, Zagreb, Croatia |
| authorships[2].author.id | https://openalex.org/A5070729118 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-5364-2523 |
| authorships[2].author.display_name | Ivan Pilaš |
| authorships[2].countries | HR |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210158666 |
| authorships[2].affiliations[0].raw_affiliation_string | Division for Forest Ecology, Croatian Forest Research Institute, Cvjetno naselje 41, Jastrebarsko, Croatia |
| authorships[2].institutions[0].id | https://openalex.org/I4210158666 |
| authorships[2].institutions[0].ror | https://ror.org/049k26g38 |
| authorships[2].institutions[0].type | facility |
| authorships[2].institutions[0].lineage | https://openalex.org/I4210158666 |
| authorships[2].institutions[0].country_code | HR |
| authorships[2].institutions[0].display_name | Croatian Forest Research Institute |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | I. Pilaš |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Division for Forest Ecology, Croatian Forest Research Institute, Cvjetno naselje 41, Jastrebarsko, Croatia |
| authorships[3].author.id | https://openalex.org/A5089277274 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-6411-6692 |
| authorships[3].author.display_name | Luka Jurjević |
| authorships[3].countries | HR |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I4210158666 |
| authorships[3].affiliations[0].raw_affiliation_string | Division for Forest Management and Forestry Economics, Croatian Forest Research Institute, Cvjetno naselje 41, Jastrebarsko, Croatia |
| authorships[3].institutions[0].id | https://openalex.org/I4210158666 |
| authorships[3].institutions[0].ror | https://ror.org/049k26g38 |
| authorships[3].institutions[0].type | facility |
| authorships[3].institutions[0].lineage | https://openalex.org/I4210158666 |
| authorships[3].institutions[0].country_code | HR |
| authorships[3].institutions[0].display_name | Croatian Forest Research Institute |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | L. Jurjević |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Division for Forest Management and Forestry Economics, Croatian Forest Research Institute, Cvjetno naselje 41, Jastrebarsko, Croatia |
| authorships[4].author.id | https://openalex.org/A5061875476 |
| authorships[4].author.orcid | https://orcid.org/0000-0001-7422-753X |
| authorships[4].author.display_name | Ivan Balenović |
| authorships[4].countries | HR |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210158666 |
| authorships[4].affiliations[0].raw_affiliation_string | Division for Forest Management and Forestry Economics, Croatian Forest Research Institute, Cvjetno naselje 41, Jastrebarsko, Croatia |
| authorships[4].institutions[0].id | https://openalex.org/I4210158666 |
| authorships[4].institutions[0].ror | https://ror.org/049k26g38 |
| authorships[4].institutions[0].type | facility |
| authorships[4].institutions[0].lineage | https://openalex.org/I4210158666 |
| authorships[4].institutions[0].country_code | HR |
| authorships[4].institutions[0].display_name | Croatian Forest Research Institute |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | I. Balenović |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Division for Forest Management and Forestry Economics, Croatian Forest Research Institute, Cvjetno naselje 41, Jastrebarsko, Croatia |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1/155/2018/isprs-archives-XLII-1-155-2018.pdf |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | FUSION OF SENTINEL-2 AND PLANETSCOPE IMAGERY FOR VEGETATION DETECTION AND MONITORING |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T13890 |
| primary_topic.field.id | https://openalex.org/fields/19 |
| primary_topic.field.display_name | Earth and Planetary Sciences |
| primary_topic.score | 0.9986000061035156 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1902 |
| primary_topic.subfield.display_name | Atmospheric Science |
| primary_topic.display_name | Remote Sensing and Land Use |
| related_works | https://openalex.org/W3207046288, https://openalex.org/W3023446922, https://openalex.org/W4324030030, https://openalex.org/W4385533602, https://openalex.org/W3189212133, https://openalex.org/W2021379394, https://openalex.org/W2554736181, https://openalex.org/W2615806692, https://openalex.org/W2080965330, https://openalex.org/W2547534968 |
| cited_by_count | 49 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 13 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 3 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 5 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 5 |
| counts_by_year[4].year | 2021 |
| counts_by_year[4].cited_by_count | 5 |
| counts_by_year[5].year | 2020 |
| counts_by_year[5].cited_by_count | 11 |
| counts_by_year[6].year | 2019 |
| counts_by_year[6].cited_by_count | 7 |
| locations_count | 3 |
| best_oa_location.id | doi:10.5194/isprs-archives-xlii-1-155-2018 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2737215817 |
| best_oa_location.source.issn | 1682-1750, 1682-1777, 2194-9034 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1682-1750 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences |
| best_oa_location.source.host_organization | https://openalex.org/P4310313756 |
| best_oa_location.source.host_organization_name | Copernicus Publications |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310313756 |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1/155/2018/isprs-archives-XLII-1-155-2018.pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| best_oa_location.landing_page_url | https://doi.org/10.5194/isprs-archives-xlii-1-155-2018 |
| primary_location.id | doi:10.5194/isprs-archives-xlii-1-155-2018 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2737215817 |
| primary_location.source.issn | 1682-1750, 1682-1777, 2194-9034 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1682-1750 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences |
| primary_location.source.host_organization | https://openalex.org/P4310313756 |
| primary_location.source.host_organization_name | Copernicus Publications |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310313756 |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1/155/2018/isprs-archives-XLII-1-155-2018.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| primary_location.landing_page_url | https://doi.org/10.5194/isprs-archives-xlii-1-155-2018 |
| publication_date | 2018-09-26 |
| publication_year | 2018 |
| referenced_works | https://openalex.org/W1964789567, https://openalex.org/W2603849672, https://openalex.org/W6676969904, https://openalex.org/W2009619252, https://openalex.org/W2897021373, https://openalex.org/W2796354922, https://openalex.org/W2766138163, https://openalex.org/W2078489713, https://openalex.org/W1889848888, https://openalex.org/W2793603191, https://openalex.org/W2805837072, https://openalex.org/W2795126628, https://openalex.org/W2773009449, https://openalex.org/W2132424470, https://openalex.org/W2808070124, https://openalex.org/W2620823684, https://openalex.org/W2911964244, https://openalex.org/W2112693869, https://openalex.org/W2772311832 |
| referenced_works_count | 19 |
| abstract_inverted_index.a | 20, 100, 120 |
| abstract_inverted_index.As | 154 |
| abstract_inverted_index.In | 64, 199 |
| abstract_inverted_index.PS | 161 |
| abstract_inverted_index.as | 53, 55, 237 |
| abstract_inverted_index.be | 231 |
| abstract_inverted_index.in | 19, 48, 79, 214, 226 |
| abstract_inverted_index.is | 62, 85, 119 |
| abstract_inverted_index.of | 59, 102, 108, 116 |
| abstract_inverted_index.on | 24, 136, 147 |
| abstract_inverted_index.or | 91 |
| abstract_inverted_index.to | 98, 233 |
| abstract_inverted_index.we | 96 |
| abstract_inverted_index.For | 41, 178 |
| abstract_inverted_index.The | 113, 129, 221 |
| abstract_inverted_index.all | 202 |
| abstract_inverted_index.and | 45, 68, 71, 94, 125, 151, 162, 170, 191, 196, 204, 208, 217, 224, 242 |
| abstract_inverted_index.can | 31, 229 |
| abstract_inverted_index.for | 88, 123, 160 |
| abstract_inverted_index.its | 109 |
| abstract_inverted_index.new | 121 |
| abstract_inverted_index.the | 16, 25, 56, 137, 148, 166, 175, 179, 183, 215 |
| abstract_inverted_index.was | 133, 194 |
| abstract_inverted_index.10-m | 67 |
| abstract_inverted_index.20-m | 69 |
| abstract_inverted_index.etc. | 40 |
| abstract_inverted_index.free | 216 |
| abstract_inverted_index.from | 189 |
| abstract_inverted_index.goal | 115 |
| abstract_inverted_index.have | 32, 173 |
| abstract_inverted_index.like | 35 |
| abstract_inverted_index.made | 145, 213 |
| abstract_inverted_index.main | 114 |
| abstract_inverted_index.open | 218 |
| abstract_inverted_index.same | 176 |
| abstract_inverted_index.show | 157 |
| abstract_inverted_index.such | 236 |
| abstract_inverted_index.test | 99 |
| abstract_inverted_index.than | 165 |
| abstract_inverted_index.this | 65, 117, 200, 227 |
| abstract_inverted_index.time | 11 |
| abstract_inverted_index.used | 87 |
| abstract_inverted_index.well | 54 |
| abstract_inverted_index.were | 76, 144, 212 |
| abstract_inverted_index.with | 6, 105 |
| abstract_inverted_index.3.7-m | 72 |
| abstract_inverted_index.Based | 23 |
| abstract_inverted_index.Index | 187 |
| abstract_inverted_index.Three | 141 |
| abstract_inverted_index.about | 15 |
| abstract_inverted_index.based | 135, 146 |
| abstract_inverted_index.daily | 9 |
| abstract_inverted_index.earth | 17 |
| abstract_inverted_index.fused | 152, 163, 171, 192 |
| abstract_inverted_index.image | 206 |
| abstract_inverted_index.often | 86 |
| abstract_inverted_index.other | 234 |
| abstract_inverted_index.paper | 228 |
| abstract_inverted_index.short | 21 |
| abstract_inverted_index.time. | 22 |
| abstract_inverted_index.urban | 38, 49 |
| abstract_inverted_index.used. | 77 |
| abstract_inverted_index.(NDVI) | 188 |
| abstract_inverted_index.almost | 8, 174 |
| abstract_inverted_index.areas, | 50 |
| abstract_inverted_index.better | 158 |
| abstract_inverted_index.easily | 230 |
| abstract_inverted_index.fusion | 101, 130, 207 |
| abstract_inverted_index.global | 7 |
| abstract_inverted_index.higher | 110 |
| abstract_inverted_index.method | 122, 131, 222 |
| abstract_inverted_index.remote | 26 |
| abstract_inverted_index.source | 219 |
| abstract_inverted_index.tests, | 205 |
| abstract_inverted_index.applied | 232 |
| abstract_inverted_index.because | 107 |
| abstract_inverted_index.decided | 97 |
| abstract_inverted_index.ecology | 241 |
| abstract_inverted_index.fusion. | 128 |
| abstract_inverted_index.imagery | 5, 30, 61, 75, 84, 104, 127, 164, 172, 193, 210 |
| abstract_inverted_index.methods | 28, 203 |
| abstract_inverted_index.provide | 12 |
| abstract_inverted_index.results | 156 |
| abstract_inverted_index.revisit | 10 |
| abstract_inverted_index.sensing | 27 |
| abstract_inverted_index.spatial | 2, 57, 111 |
| abstract_inverted_index.surface | 18 |
| abstract_inverted_index.Although | 78 |
| abstract_inverted_index.accuracy | 159 |
| abstract_inverted_index.accurate | 42 |
| abstract_inverted_index.geology. | 243 |
| abstract_inverted_index.imagery. | 153, 168 |
| abstract_inverted_index.mutually | 197 |
| abstract_inverted_index.nowadays | 80 |
| abstract_inverted_index.provided | 134 |
| abstract_inverted_index.research | 81, 118 |
| abstract_inverted_index.spectral | 51 |
| abstract_inverted_index.testing, | 182 |
| abstract_inverted_index.valuable | 13 |
| abstract_inverted_index.Abstract. | 0 |
| abstract_inverted_index.Different | 1 |
| abstract_inverted_index.accuracy. | 140, 177 |
| abstract_inverted_index.agronomy, | 240 |
| abstract_inverted_index.compared. | 198 |
| abstract_inverted_index.detection | 44, 93 |
| abstract_inverted_index.developed | 223 |
| abstract_inverted_index.different | 33 |
| abstract_inverted_index.expected, | 155 |
| abstract_inverted_index.forestry, | 239 |
| abstract_inverted_index.presented | 225 |
| abstract_inverted_index.programs. | 220 |
| abstract_inverted_index.research, | 66, 201 |
| abstract_inverted_index.satellite | 4, 29, 60, 74, 83, 209 |
| abstract_inverted_index.sciences, | 235 |
| abstract_inverted_index.urbanism, | 238 |
| abstract_inverted_index.Difference | 185 |
| abstract_inverted_index.Normalized | 184 |
| abstract_inverted_index.Sentinel-2 | 70, 82, 103, 124, 167, 190 |
| abstract_inverted_index.Vegetation | 186 |
| abstract_inverted_index.calculated | 195 |
| abstract_inverted_index.especially | 47 |
| abstract_inverted_index.important. | 63 |
| abstract_inverted_index.land-cover | 89, 138, 142 |
| abstract_inverted_index.monitoring | 181 |
| abstract_inverted_index.resolution | 58 |
| abstract_inverted_index.validation | 132 |
| abstract_inverted_index.vegetation | 43, 92, 180 |
| abstract_inverted_index.PlanetScope | 73, 106, 126, 150, 169 |
| abstract_inverted_index.Sentinel-2, | 149 |
| abstract_inverted_index.information | 14 |
| abstract_inverted_index.monitoring, | 39, 46, 95 |
| abstract_inverted_index.resolution. | 112 |
| abstract_inverted_index.resolutions | 3 |
| abstract_inverted_index.applications | 34 |
| abstract_inverted_index.development, | 37 |
| abstract_inverted_index.environmental | 36 |
| abstract_inverted_index.classification | 90, 139, 211 |
| abstract_inverted_index.classifications | 143 |
| abstract_inverted_index.characteristics, | 52 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.75 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.91691138 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |