Agronomic, weather, and remote sensing data for the simultaneous assessment of nitrogen and water status in winter wheat using hyperspectral and thermal sensors

This dataset includes agronomic, climatic, thermal and spectral information from field experiments conducted in Aranjuez (Central Spain) with winter wheat (Triticum aestivum L.) in 2018 and 2019. The total number of experiments was two, and each experiment comprises 32 plots with various combination...

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Detalles Bibliográficos
Autores: Quemada, Miguel, Pancorbo, J. L., Alonso-Ayuso, María, Raya-Sereno, M. D., Gabriel, José Luis, Camino, Carlos, Zarco-Tejada, Pablo J.
Tipo de recurso: conjunto de datos
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/401224
Acceso en línea:http://hdl.handle.net/10261/401224
Access Level:acceso abierto
Palabra clave:Agronomy
Remote Sensing
Precision Agriculture
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oai_identifier_str oai:digital.csic.es:10261/401224
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Agronomic, weather, and remote sensing data for the simultaneous assessment of nitrogen and water status in winter wheat using hyperspectral and thermal sensors
title Agronomic, weather, and remote sensing data for the simultaneous assessment of nitrogen and water status in winter wheat using hyperspectral and thermal sensors
spellingShingle Agronomic, weather, and remote sensing data for the simultaneous assessment of nitrogen and water status in winter wheat using hyperspectral and thermal sensors
Quemada, Miguel
Agronomy
Remote Sensing
Precision Agriculture
title_short Agronomic, weather, and remote sensing data for the simultaneous assessment of nitrogen and water status in winter wheat using hyperspectral and thermal sensors
title_full Agronomic, weather, and remote sensing data for the simultaneous assessment of nitrogen and water status in winter wheat using hyperspectral and thermal sensors
title_fullStr Agronomic, weather, and remote sensing data for the simultaneous assessment of nitrogen and water status in winter wheat using hyperspectral and thermal sensors
title_full_unstemmed Agronomic, weather, and remote sensing data for the simultaneous assessment of nitrogen and water status in winter wheat using hyperspectral and thermal sensors
title_sort Agronomic, weather, and remote sensing data for the simultaneous assessment of nitrogen and water status in winter wheat using hyperspectral and thermal sensors
dc.creator.none.fl_str_mv Quemada, Miguel
Pancorbo, J. L.
Alonso-Ayuso, María
Raya-Sereno, M. D.
Gabriel, José Luis
Camino, Carlos
Zarco-Tejada, Pablo J.
author Quemada, Miguel
author_facet Quemada, Miguel
Pancorbo, J. L.
Alonso-Ayuso, María
Raya-Sereno, M. D.
Gabriel, José Luis
Camino, Carlos
Zarco-Tejada, Pablo J.
author_role author
author2 Pancorbo, J. L.
Alonso-Ayuso, María
Raya-Sereno, M. D.
Gabriel, José Luis
Camino, Carlos
Zarco-Tejada, Pablo J.
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Agencia Estatal de Investigación (España)
Ministerio de Ciencia e Innovación (España)
European Commission
Alonso-Ayuso, María [0000-0003-2249-4737]
Raya-Sereno, M. D. [0000-0002-4401-790X]
Gabriel, José Luis [0000-0002-5508-4120]
Camino, Carlos [0000-0001-5188-4406]
Zarco-Tejada, Pablo J. [0000-0003-1433-6165]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Agronomy
Remote Sensing
Precision Agriculture
topic Agronomy
Remote Sensing
Precision Agriculture
description This dataset includes agronomic, climatic, thermal and spectral information from field experiments conducted in Aranjuez (Central Spain) with winter wheat (Triticum aestivum L.) in 2018 and 2019. The total number of experiments was two, and each experiment comprises 32 plots with various combinations of water (2 levels) and nitrogen (4 levesl) applications. The agronomic data are summarized in an Excel file and contains the biomass, nitrogen concentration and content in the biomass, the shoot biomass, the shoot biomass nitrogen concentration and content, the spikes biomass, the spikes biomass nitrogen concentration and content, and the nitrogen nutrition index (NNI) at various dates. This crop file also contains the crop yield, protein content and N exported in the wheat grain (N output) at harvest in July. The thermal and spectral file includes the average canopy temperature and the average spectral reflectance from each plot at various dates. The weather data file includes the main climate variables registered in a meteorological station located on the farm.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/dataset
http://purl.org/coar/resource_type/c_ddb1
Publisher's version
info:eu-repo/semantics/publishedVersion
format dataset
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/401224
url http://hdl.handle.net/10261/401224
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-124041OB-C21
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-124041OB-C22
Pancorbo, J. L.; Camino, Carlos;Alonso-Ayuso, María; Raya-Sereno, María D.; González-Fernández, Ignacio; Gabriel, José Luis ; Zarco-Tejada, Pablo J.; Quemada, Miguel. 2021. Simultaneous assessment of nitrogen and water status in winter wheat using hyperspectral and thermal sensors. http://dx.doi.org/10.1016/j.eja.2021.126287. http://hdl.handle.net/10261/268114
https://doi.org/10.17632/b7xg8d8m9k.1
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/csv
application/vnd.ms-excel
dc.publisher.none.fl_str_mv Mendeley Data
publisher.none.fl_str_mv Mendeley Data
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
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spelling Agronomic, weather, and remote sensing data for the simultaneous assessment of nitrogen and water status in winter wheat using hyperspectral and thermal sensorsQuemada, MiguelPancorbo, J. L.Alonso-Ayuso, MaríaRaya-Sereno, M. D.Gabriel, José LuisCamino, CarlosZarco-Tejada, Pablo J.AgronomyRemote SensingPrecision AgricultureThis dataset includes agronomic, climatic, thermal and spectral information from field experiments conducted in Aranjuez (Central Spain) with winter wheat (Triticum aestivum L.) in 2018 and 2019. The total number of experiments was two, and each experiment comprises 32 plots with various combinations of water (2 levels) and nitrogen (4 levesl) applications. The agronomic data are summarized in an Excel file and contains the biomass, nitrogen concentration and content in the biomass, the shoot biomass, the shoot biomass nitrogen concentration and content, the spikes biomass, the spikes biomass nitrogen concentration and content, and the nitrogen nutrition index (NNI) at various dates. This crop file also contains the crop yield, protein content and N exported in the wheat grain (N output) at harvest in July. The thermal and spectral file includes the average canopy temperature and the average spectral reflectance from each plot at various dates. The weather data file includes the main climate variables registered in a meteorological station located on the farm.[+ Value of the data:] Data relating agronomic and sensor information from wheat under different nitrogen and water conditions will be useful for understanding crop performance and optimizing irrigation and nitrogen fertilization. The data on nitrogen nutrition index (NNI) are particularly valuable because there is a need to relate solid nutritional indicators with remote sensing data.[+ Detailed description:] The file ‘Crop_agronomic_data_wheat.xlsx’ contains the specific date in which each sample was taken, the N and water level, the dry biomass (kg dm/ha), the N concentration (%) and N content (kg N/ha) of the aerial biomass, the shoot biomass (kg dm/ha) with its N concentration (%) and N content (kg N/ha), the spike biomass (kg dm/ha) with its N concentration (%) and N content (kg N/ha), the NNI adjusted and the NNI calculated following Justes equation. In addition, the dataset contains the wheat grain yield (kg dm/ ha), grain N concentration (%) and grain content or N output (kg N ha/1) at harvest in the two years were recorded. The file ‘Crop_Reflectance_temp_from_Plane.xlsx’ contains the average canopy temperature (ºC) and the average spectral reflectance from each plot at various dates. The values were obtained from the airborne images acquired with thermal and hyperspectral cameras mounted on a plane that flight at 300 m over the experiment in March, April and May. The original images are available under reasonable request to the authors. The ‘Weather_Data_Aranjuez_01_01_2018_31_12_2020’ file includes the main climate variables registered in a meteorological station located on the farm.More detail about these data can be found in the article entitled ' Simultaneous assessment of nitrogen and water status in winter wheat using hyperspectral and thermal sensors’ published in European Journal of Agronomy (vol. 127, p. 126287) by Pancorbo et al. in 2021.[Steps to reproduce] Biomass, N concentration and N content in the different plant components were determined from two samples (0.5 x 0.5 m) collected in each plot at three different growth stages (mid stem elongation, final stem elongation and flowering) both years. At harvest, the central fringe from each plot was harvested with an experimental combine to record grain yield. The N concentration of wheat components (spikes and the rest of the biomass) and grain was determined by the combustion method in a subsample from each plot. The NNI was determined as the ratio between the actual crop N concentration and the critical N concentration for a given biomass (i.e. the N concentration that enables maximum growth). Spectral and thermal data were extracted from images acquired from hyperspectral and thermal sensors onboard an aircraft flying 300 m above ground at 70 knots ground speed with heading on the solar plane. The hyperspectral imager covering the VNIR region (Hyperspec VNIR model, Headwall Photonics, Fitchburg, MA, USA) captured the reflected light between 400 and 850 nm with a spectral resolution of 6.5 nm full-width at half maximum (FWHM) and 50º field of view (FOV) that yielded a spatial resolution of 0.2 m. Reflectance in the SWIR region was obtained with a hyperspectral sensor (NIR-100 model, Headwall Photonics, Fitchburg, MA, USA) from 950 to 1750 nm at 6.05 nm FWHM, with an FOV of 38.6º and 0.6 m spatial resolution. The surface temperature was recorded with a thermal sensor (SC655 model, FLIR Systems, Wilsonville, OR, USA) at a spatial resolution of 0.25 m, 16-bit radiometric resolution, focal length of 13.1 mm, and 45 × 33.7º FOV in each flight. The sensor has ±2 °C of accuracy, and a thermal sensitivity <0.05 °C at 30°C. A single nadir-oriented image was collected from each plot with the thermal sensor, and from the borders to obtain dry and wet bare soil temperature. The surface temperature of each plot was calculated as the average of the pixels in the center of the acquired image. Throughout the sampling, air temperature, radiance and relative humidity were monitored.Ministerio de Ciencia, Tecnología e Innovación PID2021-124041OB-C21/22Peer reviewedMendeley DataAgencia Estatal de Investigación (España)Ministerio de Ciencia e Innovación (España)European CommissionAlonso-Ayuso, María [0000-0003-2249-4737]Raya-Sereno, M. D. [0000-0002-4401-790X]Gabriel, José Luis [0000-0002-5508-4120]Camino, Carlos [0000-0001-5188-4406]Zarco-Tejada, Pablo J. [0000-0003-1433-6165]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252025info:eu-repo/semantics/datasethttp://purl.org/coar/resource_type/c_ddb1Publisher's versioninfo:eu-repo/semantics/publishedVersiontext/csvapplication/vnd.ms-excelhttp://hdl.handle.net/10261/401224reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-124041OB-C21info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-124041OB-C22Pancorbo, J. L.; Camino, Carlos;Alonso-Ayuso, María; Raya-Sereno, María D.; González-Fernández, Ignacio; Gabriel, José Luis ; Zarco-Tejada, Pablo J.; Quemada, Miguel. 2021. Simultaneous assessment of nitrogen and water status in winter wheat using hyperspectral and thermal sensors. http://dx.doi.org/10.1016/j.eja.2021.126287. http://hdl.handle.net/10261/268114https://doi.org/10.17632/b7xg8d8m9k.1Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4012242026-05-22T06:33:51Z
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