Temporal and Spatial Upscaling with PlanetScope Data: Predicting Relative Canopy Dieback in the Piñon-Juniper Woodlands of Utah Article Swipe
Elliot Shayle
,
Dirk Zeuss
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/rs17193323
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/rs17193323
Drought-induced forest mortality threatens biodiversity globally, particularly in arid, and semi-arid woodlands. The continual development of remote sensing approaches enables enhanced monitoring of forest health. Herein, we investigate the ability of a limited ground-truthed canopy dieback dataset and satellite image derived Normalised Difference Vegetation Index (NDVI) to make inferences about forest health as temporal and spatial extent from its collection increases. We used ground-truthed observations of relative canopy mortality from the Pinus edulis-Juniperus osteosperma woodlands of southeastern Utah, United States of America, collected after the 2017–2018 drought, and PlanetScope satellite imagery. Through assessing different modelling approaches, we found that NDVI is significantly associated with sitewide mean canopy dieback, with beta regression being the most optimal modelling framework due to the bounded nature of the variable relative canopy dieback. Model performance was further improved by incorporating the proportion of J. osteosperma as an interaction term, matching the reports of species-specific differential dieback. A time-series analysis revealed that NDVI retained its predictive power for our whole testing period; four years after the initial ground-truthing, thus enabling retrospective inference of defoliation and regreening. A spatial random forest model trained on our ground-truthed observations accurately predicted dieback across the broader landscape. These findings demonstrate that modest field campaigns combined with high-resolution satellite data can generate reliable, scalable insights into forest health, offering a cost-effective method for monitoring drought-impacted ecosystems under climate change.
Related Topics
Concepts
No concepts available.
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/rs17193323
- https://www.mdpi.com/2072-4292/17/19/3323/pdf?version=1759065872
- OA Status
- gold
- References
- 49
- OpenAlex ID
- https://openalex.org/W4414611292
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4414611292Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/rs17193323Digital Object Identifier
- Title
-
Temporal and Spatial Upscaling with PlanetScope Data: Predicting Relative Canopy Dieback in the Piñon-Juniper Woodlands of UtahWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-09-28Full publication date if available
- Authors
-
Elliot Shayle, Dirk ZeussList of authors in order
- Landing page
-
https://doi.org/10.3390/rs17193323Publisher landing page
- PDF URL
-
https://www.mdpi.com/2072-4292/17/19/3323/pdf?version=1759065872Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2072-4292/17/19/3323/pdf?version=1759065872Direct OA link when available
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
49Number of works referenced by this work
Full payload
| id | https://openalex.org/W4414611292 |
|---|---|
| doi | https://doi.org/10.3390/rs17193323 |
| ids.doi | https://doi.org/10.3390/rs17193323 |
| ids.openalex | https://openalex.org/W4414611292 |
| fwci | 0.0 |
| type | article |
| title | Temporal and Spatial Upscaling with PlanetScope Data: Predicting Relative Canopy Dieback in the Piñon-Juniper Woodlands of Utah |
| biblio.issue | 19 |
| biblio.volume | 17 |
| biblio.last_page | 3323 |
| biblio.first_page | 3323 |
| topics[0].id | https://openalex.org/T10266 |
| topics[0].field.id | https://openalex.org/fields/23 |
| topics[0].field.display_name | Environmental Science |
| topics[0].score | 0.9950000047683716 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2306 |
| topics[0].subfield.display_name | Global and Planetary Change |
| topics[0].display_name | Plant Water Relations and Carbon Dynamics |
| topics[1].id | https://openalex.org/T10555 |
| topics[1].field.id | https://openalex.org/fields/23 |
| topics[1].field.display_name | Environmental Science |
| topics[1].score | 0.9930999875068665 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2306 |
| topics[1].subfield.display_name | Global and Planetary Change |
| topics[1].display_name | Fire effects on ecosystems |
| topics[2].id | https://openalex.org/T10017 |
| topics[2].field.id | https://openalex.org/fields/19 |
| topics[2].field.display_name | Earth and Planetary Sciences |
| topics[2].score | 0.9929999709129333 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1902 |
| topics[2].subfield.display_name | Atmospheric Science |
| topics[2].display_name | Geology and Paleoclimatology Research |
| is_xpac | False |
| apc_list.value | 2500 |
| apc_list.currency | CHF |
| apc_list.value_usd | 2707 |
| apc_paid.value | 2500 |
| apc_paid.currency | CHF |
| apc_paid.value_usd | 2707 |
| language | en |
| locations[0].id | doi:10.3390/rs17193323 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S43295729 |
| locations[0].source.issn | 2072-4292 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2072-4292 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Remote Sensing |
| locations[0].source.host_organization | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.mdpi.com/2072-4292/17/19/3323/pdf?version=1759065872 |
| 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 | Remote Sensing |
| locations[0].landing_page_url | https://doi.org/10.3390/rs17193323 |
| locations[1].id | pmh:oai:doaj.org/article:2b1407681e834177848758de7c0fb622 |
| locations[1].is_oa | False |
| 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].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Remote Sensing, Vol 17, Iss 19, p 3323 (2025) |
| locations[1].landing_page_url | https://doaj.org/article/2b1407681e834177848758de7c0fb622 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5044632433 |
| authorships[0].author.orcid | https://orcid.org/0009-0008-2994-0887 |
| authorships[0].author.display_name | Elliot Shayle |
| authorships[0].countries | DE |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I161103922 |
| authorships[0].affiliations[0].raw_affiliation_string | Umweltinformatik, Fachbereich Geographie, Philipps Universität Marburg, Deutschhausstraße 12, 35032 Marburg, Germany |
| authorships[0].institutions[0].id | https://openalex.org/I161103922 |
| authorships[0].institutions[0].ror | https://ror.org/01rdrb571 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I161103922 |
| authorships[0].institutions[0].country_code | DE |
| authorships[0].institutions[0].display_name | Philipps University of Marburg |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Elliot S. Shayle |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Umweltinformatik, Fachbereich Geographie, Philipps Universität Marburg, Deutschhausstraße 12, 35032 Marburg, Germany |
| authorships[1].author.id | https://openalex.org/A5046750467 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-6457-2866 |
| authorships[1].author.display_name | Dirk Zeuss |
| authorships[1].countries | DE |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I161103922 |
| authorships[1].affiliations[0].raw_affiliation_string | Umweltinformatik, Fachbereich Geographie, Philipps Universität Marburg, Deutschhausstraße 12, 35032 Marburg, Germany |
| authorships[1].institutions[0].id | https://openalex.org/I161103922 |
| authorships[1].institutions[0].ror | https://ror.org/01rdrb571 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I161103922 |
| authorships[1].institutions[0].country_code | DE |
| authorships[1].institutions[0].display_name | Philipps University of Marburg |
| authorships[1].author_position | last |
| authorships[1].raw_author_name | Dirk Zeuss |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Umweltinformatik, Fachbereich Geographie, Philipps Universität Marburg, Deutschhausstraße 12, 35032 Marburg, Germany |
| has_content.pdf | True |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.mdpi.com/2072-4292/17/19/3323/pdf?version=1759065872 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Temporal and Spatial Upscaling with PlanetScope Data: Predicting Relative Canopy Dieback in the Piñon-Juniper Woodlands of Utah |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10266 |
| primary_topic.field.id | https://openalex.org/fields/23 |
| primary_topic.field.display_name | Environmental Science |
| primary_topic.score | 0.9950000047683716 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2306 |
| primary_topic.subfield.display_name | Global and Planetary Change |
| primary_topic.display_name | Plant Water Relations and Carbon Dynamics |
| cited_by_count | 0 |
| locations_count | 2 |
| best_oa_location.id | doi:10.3390/rs17193323 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S43295729 |
| best_oa_location.source.issn | 2072-4292 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2072-4292 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Remote Sensing |
| best_oa_location.source.host_organization | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.mdpi.com/2072-4292/17/19/3323/pdf?version=1759065872 |
| 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 | Remote Sensing |
| best_oa_location.landing_page_url | https://doi.org/10.3390/rs17193323 |
| primary_location.id | doi:10.3390/rs17193323 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S43295729 |
| primary_location.source.issn | 2072-4292 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2072-4292 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Remote Sensing |
| primary_location.source.host_organization | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.mdpi.com/2072-4292/17/19/3323/pdf?version=1759065872 |
| 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 | Remote Sensing |
| primary_location.landing_page_url | https://doi.org/10.3390/rs17193323 |
| publication_date | 2025-09-28 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W1981213426, https://openalex.org/W4214901135, https://openalex.org/W3213505683, https://openalex.org/W2785348225, https://openalex.org/W3125213608, https://openalex.org/W4386489002, https://openalex.org/W2990796782, https://openalex.org/W3090783707, https://openalex.org/W1967839820, https://openalex.org/W4405560098, https://openalex.org/W1575234955, https://openalex.org/W2153989276, https://openalex.org/W2106013526, https://openalex.org/W2518211819, https://openalex.org/W1531807346, https://openalex.org/W2099428109, https://openalex.org/W2615200802, https://openalex.org/W2914709307, https://openalex.org/W2980482440, https://openalex.org/W4399462481, https://openalex.org/W4220730626, https://openalex.org/W1720178141, https://openalex.org/W4312126429, https://openalex.org/W4224309885, https://openalex.org/W2775497650, https://openalex.org/W4206079995, https://openalex.org/W1971653980, https://openalex.org/W2010175410, https://openalex.org/W1987670201, https://openalex.org/W3023775819, https://openalex.org/W2990427812, https://openalex.org/W1549716303, https://openalex.org/W2804233742, https://openalex.org/W2157395790, https://openalex.org/W2168745915, https://openalex.org/W4213448449, https://openalex.org/W2793997912, https://openalex.org/W2052611179, https://openalex.org/W4378070128, https://openalex.org/W4389735362, https://openalex.org/W2951986078, https://openalex.org/W4235713844, https://openalex.org/W1986156814, https://openalex.org/W2911010442, https://openalex.org/W2561491215, https://openalex.org/W2066045922, https://openalex.org/W2859181474, https://openalex.org/W3031909544, https://openalex.org/W3102027041 |
| referenced_works_count | 49 |
| abstract_inverted_index.A | 151, 180 |
| abstract_inverted_index.a | 31, 218 |
| abstract_inverted_index.J. | 138 |
| abstract_inverted_index.We | 61 |
| abstract_inverted_index.an | 141 |
| abstract_inverted_index.as | 52, 140 |
| abstract_inverted_index.by | 133 |
| abstract_inverted_index.in | 7 |
| abstract_inverted_index.is | 100 |
| abstract_inverted_index.of | 15, 22, 30, 65, 75, 80, 122, 137, 147, 176 |
| abstract_inverted_index.on | 186 |
| abstract_inverted_index.to | 46, 118 |
| abstract_inverted_index.we | 26, 96 |
| abstract_inverted_index.The | 12 |
| abstract_inverted_index.and | 9, 37, 54, 87, 178 |
| abstract_inverted_index.can | 209 |
| abstract_inverted_index.due | 117 |
| abstract_inverted_index.for | 161, 221 |
| abstract_inverted_index.its | 58, 158 |
| abstract_inverted_index.our | 162, 187 |
| abstract_inverted_index.the | 28, 70, 84, 112, 119, 123, 135, 145, 169, 194 |
| abstract_inverted_index.was | 130 |
| abstract_inverted_index.NDVI | 99, 156 |
| abstract_inverted_index.beta | 109 |
| abstract_inverted_index.data | 208 |
| abstract_inverted_index.four | 166 |
| abstract_inverted_index.from | 57, 69 |
| abstract_inverted_index.into | 214 |
| abstract_inverted_index.make | 47 |
| abstract_inverted_index.mean | 105 |
| abstract_inverted_index.most | 113 |
| abstract_inverted_index.that | 98, 155, 200 |
| abstract_inverted_index.thus | 172 |
| abstract_inverted_index.used | 62 |
| abstract_inverted_index.with | 103, 108, 205 |
| abstract_inverted_index.Index | 44 |
| abstract_inverted_index.Model | 128 |
| abstract_inverted_index.Pinus | 71 |
| abstract_inverted_index.These | 197 |
| abstract_inverted_index.Utah, | 77 |
| abstract_inverted_index.about | 49 |
| abstract_inverted_index.after | 83, 168 |
| abstract_inverted_index.arid, | 8 |
| abstract_inverted_index.being | 111 |
| abstract_inverted_index.field | 202 |
| abstract_inverted_index.found | 97 |
| abstract_inverted_index.image | 39 |
| abstract_inverted_index.model | 184 |
| abstract_inverted_index.power | 160 |
| abstract_inverted_index.term, | 143 |
| abstract_inverted_index.under | 225 |
| abstract_inverted_index.whole | 163 |
| abstract_inverted_index.years | 167 |
| abstract_inverted_index.(NDVI) | 45 |
| abstract_inverted_index.States | 79 |
| abstract_inverted_index.United | 78 |
| abstract_inverted_index.across | 193 |
| abstract_inverted_index.canopy | 34, 67, 106, 126 |
| abstract_inverted_index.extent | 56 |
| abstract_inverted_index.forest | 1, 23, 50, 183, 215 |
| abstract_inverted_index.health | 51 |
| abstract_inverted_index.method | 220 |
| abstract_inverted_index.modest | 201 |
| abstract_inverted_index.nature | 121 |
| abstract_inverted_index.random | 182 |
| abstract_inverted_index.remote | 16 |
| abstract_inverted_index.Herein, | 25 |
| abstract_inverted_index.Through | 91 |
| abstract_inverted_index.ability | 29 |
| abstract_inverted_index.bounded | 120 |
| abstract_inverted_index.broader | 195 |
| abstract_inverted_index.change. | 227 |
| abstract_inverted_index.climate | 226 |
| abstract_inverted_index.dataset | 36 |
| abstract_inverted_index.derived | 40 |
| abstract_inverted_index.dieback | 35, 192 |
| abstract_inverted_index.enables | 19 |
| abstract_inverted_index.further | 131 |
| abstract_inverted_index.health, | 216 |
| abstract_inverted_index.health. | 24 |
| abstract_inverted_index.initial | 170 |
| abstract_inverted_index.limited | 32 |
| abstract_inverted_index.optimal | 114 |
| abstract_inverted_index.period; | 165 |
| abstract_inverted_index.reports | 146 |
| abstract_inverted_index.sensing | 17 |
| abstract_inverted_index.spatial | 55, 181 |
| abstract_inverted_index.testing | 164 |
| abstract_inverted_index.trained | 185 |
| abstract_inverted_index.America, | 81 |
| abstract_inverted_index.analysis | 153 |
| abstract_inverted_index.combined | 204 |
| abstract_inverted_index.dieback, | 107 |
| abstract_inverted_index.dieback. | 127, 150 |
| abstract_inverted_index.drought, | 86 |
| abstract_inverted_index.enabling | 173 |
| abstract_inverted_index.enhanced | 20 |
| abstract_inverted_index.findings | 198 |
| abstract_inverted_index.generate | 210 |
| abstract_inverted_index.imagery. | 90 |
| abstract_inverted_index.improved | 132 |
| abstract_inverted_index.insights | 213 |
| abstract_inverted_index.matching | 144 |
| abstract_inverted_index.offering | 217 |
| abstract_inverted_index.relative | 66, 125 |
| abstract_inverted_index.retained | 157 |
| abstract_inverted_index.revealed | 154 |
| abstract_inverted_index.scalable | 212 |
| abstract_inverted_index.sitewide | 104 |
| abstract_inverted_index.temporal | 53 |
| abstract_inverted_index.variable | 124 |
| abstract_inverted_index.assessing | 92 |
| abstract_inverted_index.campaigns | 203 |
| abstract_inverted_index.collected | 82 |
| abstract_inverted_index.continual | 13 |
| abstract_inverted_index.different | 93 |
| abstract_inverted_index.framework | 116 |
| abstract_inverted_index.globally, | 5 |
| abstract_inverted_index.inference | 175 |
| abstract_inverted_index.modelling | 94, 115 |
| abstract_inverted_index.mortality | 2, 68 |
| abstract_inverted_index.predicted | 191 |
| abstract_inverted_index.reliable, | 211 |
| abstract_inverted_index.satellite | 38, 89, 207 |
| abstract_inverted_index.semi-arid | 10 |
| abstract_inverted_index.threatens | 3 |
| abstract_inverted_index.woodlands | 74 |
| abstract_inverted_index.Difference | 42 |
| abstract_inverted_index.Normalised | 41 |
| abstract_inverted_index.Vegetation | 43 |
| abstract_inverted_index.accurately | 190 |
| abstract_inverted_index.approaches | 18 |
| abstract_inverted_index.associated | 102 |
| abstract_inverted_index.collection | 59 |
| abstract_inverted_index.ecosystems | 224 |
| abstract_inverted_index.increases. | 60 |
| abstract_inverted_index.inferences | 48 |
| abstract_inverted_index.landscape. | 196 |
| abstract_inverted_index.monitoring | 21, 222 |
| abstract_inverted_index.predictive | 159 |
| abstract_inverted_index.proportion | 136 |
| abstract_inverted_index.regression | 110 |
| abstract_inverted_index.woodlands. | 11 |
| abstract_inverted_index.2017–2018 | 85 |
| abstract_inverted_index.PlanetScope | 88 |
| abstract_inverted_index.approaches, | 95 |
| abstract_inverted_index.defoliation | 177 |
| abstract_inverted_index.demonstrate | 199 |
| abstract_inverted_index.development | 14 |
| abstract_inverted_index.interaction | 142 |
| abstract_inverted_index.investigate | 27 |
| abstract_inverted_index.osteosperma | 73, 139 |
| abstract_inverted_index.performance | 129 |
| abstract_inverted_index.regreening. | 179 |
| abstract_inverted_index.time-series | 152 |
| abstract_inverted_index.biodiversity | 4 |
| abstract_inverted_index.differential | 149 |
| abstract_inverted_index.observations | 64, 189 |
| abstract_inverted_index.particularly | 6 |
| abstract_inverted_index.southeastern | 76 |
| abstract_inverted_index.incorporating | 134 |
| abstract_inverted_index.retrospective | 174 |
| abstract_inverted_index.significantly | 101 |
| abstract_inverted_index.cost-effective | 219 |
| abstract_inverted_index.ground-truthed | 33, 63, 188 |
| abstract_inverted_index.Drought-induced | 0 |
| abstract_inverted_index.high-resolution | 206 |
| abstract_inverted_index.drought-impacted | 223 |
| abstract_inverted_index.edulis-Juniperus | 72 |
| abstract_inverted_index.ground-truthing, | 171 |
| abstract_inverted_index.species-specific | 148 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| citation_normalized_percentile.value | 0.45130777 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |