WhiteRef: A New Tower-Based Hyperspectral System for Continuous Reflectance Measurements Article Swipe
YOU?
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· 2015
· Open Access
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· DOI: https://doi.org/10.3390/s150101088
Proximal sensing is fundamental to monitor the spatial and seasonal dynamics of ecosystems and can be considered as a crucial validation tool to upscale in situ observations to the satellite level. Linking hyperspectral remote sensing with carbon fluxes and biophysical parameters is critical to allow the exploitation of spatial and temporal extensive information for validating model simulations at different scales. In this study, we present the WhiteRef, a new hyperspectral system designed as a direct result of the needs identified during the EUROSPEC ES0903 Cost Action, and developed by Fondazione Edmund Mach and the Institute of Biometeorology, CNR, Italy. The system is based on the ASD FieldSpec Pro spectroradiometer and was designed to acquire continuous radiometric measurements at the Eddy Covariance (EC) towers and to fill a gap in the scientific community: in fact, no system for continuous spectral measurements in the Short Wave Infrared was tested before at the EC sites. The paper illustrates the functioning of the WhiteRef and describes its main advantages and disadvantages. The WhiteRef system, being based on a robust and high quality commercially available instrument, has a clear potential for unattended continuous measurements aiming at the validation of satellites’ vegetation products.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s150101088
- https://www.mdpi.com/1424-8220/15/1/1088/pdf?version=1420721095
- OA Status
- gold
- Cited By
- 28
- References
- 40
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2009151878
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2009151878Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s150101088Digital Object Identifier
- Title
-
WhiteRef: A New Tower-Based Hyperspectral System for Continuous Reflectance MeasurementsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-01-08Full publication date if available
- Authors
-
Karolina Sakowska, Damiano Gianelle, Alessandro Zaldei, Alasdair MacArthur, Federico Carotenuto, F. Miglietta, Roberto Zampedri, M. Cavagna, Loris VescovoList of authors in order
- Landing page
-
https://doi.org/10.3390/s150101088Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/15/1/1088/pdf?version=1420721095Direct 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/1424-8220/15/1/1088/pdf?version=1420721095Direct OA link when available
- Concepts
-
Remote sensing, Hyperspectral imaging, Eddy covariance, Spectroradiometer, Environmental science, Satellite, Moderate-resolution imaging spectroradiometer, Earth observation, Meteorology, Computer science, Reflectivity, Engineering, Geography, Ecosystem, Aerospace engineering, Optics, Ecology, Biology, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
28Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 8, 2023: 1, 2022: 1, 2020: 2Per-year citation counts (last 5 years)
- References (count)
-
40Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.before | 147 |
| abstract_inverted_index.carbon | 36 |
| abstract_inverted_index.direct | 74 |
| abstract_inverted_index.during | 80 |
| abstract_inverted_index.fluxes | 37 |
| abstract_inverted_index.level. | 30 |
| abstract_inverted_index.remote | 33 |
| abstract_inverted_index.result | 75 |
| abstract_inverted_index.robust | 174 |
| abstract_inverted_index.sites. | 151 |
| abstract_inverted_index.study, | 62 |
| abstract_inverted_index.system | 70, 100, 135 |
| abstract_inverted_index.tested | 146 |
| abstract_inverted_index.towers | 122 |
| abstract_inverted_index.Action, | 85 |
| abstract_inverted_index.Linking | 31 |
| abstract_inverted_index.acquire | 113 |
| abstract_inverted_index.crucial | 19 |
| abstract_inverted_index.monitor | 5 |
| abstract_inverted_index.present | 64 |
| abstract_inverted_index.quality | 177 |
| abstract_inverted_index.scales. | 59 |
| abstract_inverted_index.sensing | 1, 34 |
| abstract_inverted_index.spatial | 7, 48 |
| abstract_inverted_index.system, | 169 |
| abstract_inverted_index.upscale | 23 |
| abstract_inverted_index.EUROSPEC | 82 |
| abstract_inverted_index.Infrared | 144 |
| abstract_inverted_index.Proximal | 0 |
| abstract_inverted_index.WhiteRef | 159, 168 |
| abstract_inverted_index.critical | 42 |
| abstract_inverted_index.designed | 71, 111 |
| abstract_inverted_index.dynamics | 10 |
| abstract_inverted_index.seasonal | 9 |
| abstract_inverted_index.spectral | 138 |
| abstract_inverted_index.temporal | 50 |
| abstract_inverted_index.FieldSpec | 106 |
| abstract_inverted_index.Institute | 94 |
| abstract_inverted_index.WhiteRef, | 66 |
| abstract_inverted_index.available | 179 |
| abstract_inverted_index.describes | 161 |
| abstract_inverted_index.developed | 87 |
| abstract_inverted_index.different | 58 |
| abstract_inverted_index.extensive | 51 |
| abstract_inverted_index.potential | 184 |
| abstract_inverted_index.products. | 196 |
| abstract_inverted_index.satellite | 29 |
| abstract_inverted_index.Covariance | 120 |
| abstract_inverted_index.Fondazione | 89 |
| abstract_inverted_index.advantages | 164 |
| abstract_inverted_index.community: | 131 |
| abstract_inverted_index.considered | 16 |
| abstract_inverted_index.continuous | 114, 137, 187 |
| abstract_inverted_index.ecosystems | 12 |
| abstract_inverted_index.identified | 79 |
| abstract_inverted_index.parameters | 40 |
| abstract_inverted_index.scientific | 130 |
| abstract_inverted_index.unattended | 186 |
| abstract_inverted_index.validating | 54 |
| abstract_inverted_index.validation | 20, 192 |
| abstract_inverted_index.vegetation | 195 |
| abstract_inverted_index.biophysical | 39 |
| abstract_inverted_index.functioning | 156 |
| abstract_inverted_index.fundamental | 3 |
| abstract_inverted_index.illustrates | 154 |
| abstract_inverted_index.information | 52 |
| abstract_inverted_index.instrument, | 180 |
| abstract_inverted_index.radiometric | 115 |
| abstract_inverted_index.simulations | 56 |
| abstract_inverted_index.commercially | 178 |
| abstract_inverted_index.exploitation | 46 |
| abstract_inverted_index.measurements | 116, 139, 188 |
| abstract_inverted_index.observations | 26 |
| abstract_inverted_index.hyperspectral | 32, 69 |
| abstract_inverted_index.satellites’ | 194 |
| abstract_inverted_index.disadvantages. | 166 |
| abstract_inverted_index.Biometeorology, | 96 |
| abstract_inverted_index.spectroradiometer | 108 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5026443988 |
| countries_distinct_count | 4 |
| institutions_distinct_count | 9 |
| corresponding_institution_ids | https://openalex.org/I103225651 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/15 |
| sustainable_development_goals[0].score | 0.6299999952316284 |
| sustainable_development_goals[0].display_name | Life in Land |
| citation_normalized_percentile.value | 0.93924895 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |