- -

Multi-constellation GNSS interferometric reflectometry with mass-market sensors as a solution for soil moisture monitoring

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Multi-constellation GNSS interferometric reflectometry with mass-market sensors as a solution for soil moisture monitoring

Mostrar el registro sencillo del ítem

Ficheros en el ítem

Thumbnail
Nombre: Martín;Ibañez;Baxaul ...
Tamaño: 9.632Mb
Formato: PDF
Descripción: Versión editorial
Abrir
dc.contributor.author Martín Furones, Ángel Esteban es_ES
dc.contributor.author Ibañez Asensio, Sara es_ES
dc.contributor.author Baixauli, Carlos es_ES
dc.contributor.author Blanc Clavero, Sara es_ES
dc.contributor.author Anquela Julián, Ana Belén es_ES
dc.date.accessioned 2021-05-28T03:33:30Z
dc.date.available 2021-05-28T03:33:30Z
dc.date.issued 2020-07-15 es_ES
dc.identifier.issn 1027-5606 es_ES
dc.identifier.uri http://hdl.handle.net/10251/166904
dc.description.abstract [EN] Per capita arable land is decreasing due to the rapidly increasing population, and fresh water is becoming scarce and more expensive. Therefore, farmers should continue to use technology and innovative solutions to improve efficiency, save input costs, and optimise environmental resources (such as water). In the case study presented in this paper, the Global Navigation Satellite System interferometric reflectometry (GNSS-IR) technique was used to monitor soil moisture during 66¿d, from 3 December 2018 to 6 February 2019, in the installations of the Cajamar Centre of Experiences, Paiporta, Valencia, Spain. Two main objectives were pursued. The first was the extension of the technique to a multi-constellation solution using GPS, GLONASS, and GALILEO satellites, and the second was to test whether mass-market sensors could be used for this technique. Both objectives were achieved. At the same time that the GNSS observations were made, soil samples taken at 5¿cm depth were used for soil moisture determination to establish a reference data set. Based on a comparison with that reference data set, all GNSS solutions, including the three constellations and the two sensors (geodetic and mass market), were highly correlated, with a correlation coefficient between 0.7 and 0.85. es_ES
dc.language Inglés es_ES
dc.publisher EUROPEAN GEOSCIENCES UNION es_ES
dc.relation.ispartof Hydrology and Earth System Sciences es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject GNSS-IR reflectometry es_ES
dc.subject Signal to noise ratio (SNR) es_ES
dc.subject Remote sensing es_ES
dc.subject Soil moisture es_ES
dc.subject.classification PRODUCCION VEGETAL es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.subject.classification INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA es_ES
dc.title Multi-constellation GNSS interferometric reflectometry with mass-market sensors as a solution for soil moisture monitoring es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.5194/hess-24-3573-2020 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Cartográfica Geodesia y Fotogrametría - Departament d'Enginyeria Cartogràfica, Geodèsia i Fotogrametria es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Producción Vegetal - Departament de Producció Vegetal es_ES
dc.description.bibliographicCitation Martín Furones, ÁE.; Ibañez Asensio, S.; Baixauli, C.; Blanc Clavero, S.; Anquela Julián, AB. (2020). Multi-constellation GNSS interferometric reflectometry with mass-market sensors as a solution for soil moisture monitoring. Hydrology and Earth System Sciences. 24(7):3573-3582. https://doi.org/10.5194/hess-24-3573-2020 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.5194/hess-24-3573-2020 es_ES
dc.description.upvformatpinicio 3573 es_ES
dc.description.upvformatpfin 3582 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 24 es_ES
dc.description.issue 7 es_ES
dc.relation.pasarela S\416075 es_ES
dc.description.references Chan, S. K., Bindlish, R., O'Neill, P. E., Njoku, E., Jackson, T., Colliander, A., Chen, F., Burgin, M., Dunbar, S., Piepmeier, J., Yueh, S., Entekhabi, D., Cosh, M. H., Caldwell, T., Walker, J., Wu, X., Berg, A., Rowlandson, T., Pacheco, A., McNairn, H., Thibeault, M., Martiìnez-Fernaìndez, J., Gonzaìlez-Zamora, A., Seyfried, M., Bosch, D., Starks, P., Goodrich, D., Prueger, J., Palecki, M., Small, E. E., Zreda, M., Calvet, J.-C., Crow, W., and Kerr, Y.: Assessment of the SMAP passive soil moisture product, IEEE T. Geosci. Remote, 54, 4994–5007, 2016. es_ES
dc.description.references Chen, Q., Won, D., Akos, D. M., and Small, E. E.: Vegetation using GPS interferometric reflectometry: experimental results with a horizontal polarized antenna, IEEE J. Sel. Top. Appl., 9, 4771–4780, 2016. es_ES
dc.description.references Chew, C. C., Small, E. E., Larson, K. M., and Zavorotny, V. U.: Effects of near-surface soil moisture on GPS SNR data: development and retrieval algorithm for soil moisture, IEEE T. Geosci. Remote, 52, 537–543, 2014. es_ES
dc.description.references Chew, C. C., Small, E. E., Larson, K. M., and Zavorotny, U.Z.: Vegetation sensing using GPS-interferometric reflectometry: theoretical effects of canopy parameters on signal-to-noise ratio data, IEEE T. Geosci. Remote, 53, 2755–2764, 2015. es_ES
dc.description.references Chew, C. C., Small, E. E., and Larson, K. M.: An algorithm for soil moisture estimation using GPS-interferometric reflectometry for bare and vegetated soil, GPS Solut., 20, 525–537, 2016. es_ES
dc.description.references Hofmann-Wellenhof, B., Lichtenegger, H., and Wasle, E.: GNSS Global Navigation Satellite Systems, GPS, GLONASS, GALILEO and more, Springer, Vienna, Austria, New York, USA, 2008. es_ES
dc.description.references Katzberg, S. J., Torres, O., Grant, M. S., and Masters, D.: Utilizing calibrated GPS reflected signals to estimate soil reflectivity and dielectric constant: results from SMEX02, Remote Sens. Environ., 100, 17–28, 2005. es_ES
dc.description.references Kerr, Y., Waldteufel, P., Wigneron, J., Martinuzzi, J., Font, J., and Berger, M.: Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) mission, IEEE T. Geosci. Remote, 39, 1729–1735, 2001. es_ES
dc.description.references Larson, K. M. and Nievinski, F. G.: GPS snow sensing: results from the EarthScope plate boundary observatory, GPS Solut., 17, 41–52, 2013. es_ES
dc.description.references Larson, K. M., Small, E. E., Gutmann, E. D., Bilich, A. L., Axelrad, A., and Braun, J. J.: Using GPS multipath to measure soil moisture fluctuations: initial results, GPS Solut., 12, 173–177, 2008a. es_ES
dc.description.references Larson, K. M., Small, E. E., Gutmann, E. D., Bilich, A. L., Braun, J. J., and Zavorotny, V. U.: Use of GPS receivers as a soil moisture network for water cycle studies, Geophys. Res. Lett., 35, L24405, https://doi.org/10.1029/2008GL036013, 2008b. es_ES
dc.description.references Larson, K. M., Braun, J. J., Small, E. E., and Zavorotny, V. U.: GPS multipath and its relation to near-surface soil moisture content, IEEE J. Sel. Top. Appl., 3, 91–99, 2010. es_ES
dc.description.references Leick, A., Rapoport, L., and Tatarnikov, D.: GPS satellite surveying, 4th edn., John Wiley & Sons, Hoboken, New Jersey, USA, 840 pp., 2015. es_ES
dc.description.references Li, G. and Geng, J.: Characteristics of raw multi-GNSS measurement error from Google Android smart devices, GPS Solut., 23, 1–5, https://doi.org/10.1007/s10291-019-0885-4, 2019. es_ES
dc.description.references Lomb, N. R.: Least-squares frequency – Analysis of unequally spaced data, Astrophys. Space Sci., 39, 447–462, 1976. es_ES
dc.description.references Masters, D., Axelrad, P., and Katzberg, S.: Initial results of land-reflected GPS bistatic radar measurements in SMEX02, Remote Sens. Environ., 92, 507–520, 2002. es_ES
dc.description.references Mattia, F., Balenzano, A., Satalino, G., Lovergine, F., Peng, J., Wegmuller, U., Cartus, O., Davidson, M. W. J., Ki<span id="page3582"/>m S., Johnson, J., Walker, J., Wu, X., Pauwels, V. R. N., McNairn, H., Caldwell, T., Cosh, M., and Jackson, T.: Sentinel-1 & Sentinel-2 for SOIL Moisture Retrieval at Field Scale, IGARSS 2018–2018, IEEE I. Geosci. Rem. Sens. Symposium, 22–27 July 2018, Valencia, Spain, 6143–6146, https://doi.org/10.1109/IGARSS.2018.8518170, 2018. es_ES
dc.description.references Press, W. H., Teukolsky, S. S., Vetterling, W. T., and Flannery, B. P.: Numerical recipes in Fortran 77, vol. 1, 2nd edn., Cambirdge University Press, New York, USA, 569–573, 1992. es_ES
dc.description.references Roesler, C. and Larson, K. M.: Software tools for GNSS interferometric reflectometry (GNSS-IR), GPS Solut., 22, 80, https://doi.org/10.1007/s10291-018-0744-8, 2018. es_ES
dc.description.references Roussel, N., Frappart, F., Ramillien, G., Darroes, J., Baup, F., Lestarquit, L., and Ha, M. C.: Detection of soil moisture variations using GPS and GLONASS SNR data for elevation angles ranging from 2∘ to 70∘, IEEE J. Sel. Top. Appl., 9, 4781–4794, 2016. es_ES
dc.description.references Small, E. E., Larson, K. M., Chew, C. C., Dong, J., and Ochsner, T. E.: Validation of GPS-IR soil moisture retrievals: comparison of different algorithms to remove vegetation effects, IEEE J. Sel. Top. Appl., 9, 4759–4770, 2016. es_ES
dc.description.references Strang, G. and Borre, K.: Linear algebra, Geodesy and GPS, Wellesley-Cambride Press, 624 pp., available at: https://www.unavco.org/data/gps-gnss/derived-products/pbo-h2o/documentation/documentation.html#soil (last access: 18 December 2019), 1997. es_ES
dc.description.references Vey, S., Güntner, A., Wickert, J., Blume, T., and Ramatschi, M.: Long-term soil moisture dynamics derived from GNSS interferometric reflectometry: a case study for Sutherland, South Africa, GPS Solut., 20, 641–654, https://doi.org/10.1007/s10291-015-0474-0, 2016. es_ES
dc.description.references Wan, W., Larson, K. M., Small, E. E., Chew, C. C., and Braun, J. J.: Using geodetic GPS receivers to measure vegetation water content, GPS Solut., 19, 237–248, 2015. es_ES
dc.description.references Zavorotny, V. U., Masters, D., Gasiewski, A., Bartram, B., Katzberg, S., Aselrad, P., and Zamora, R.: Seasonal polarimetric measurements of soil moisture using tower-based GPS bistatic radar, IGARSS 2003, 2003 IEEE International Geoscience and Remote Sensing Symposium, Proceedings (IEEE Cat. No.03CH37477), Toulouse, France, 2003, vol. 2, 781–783, https://doi.org/10.1109/IGARSS.2003.1293916, 2003. es_ES
dc.description.references Zhang, S., Roussel, N., Boniface, K., Ha, M. C., Frappart, F., Darrozes, J., Baup, F., and Calvet, J.-C.: Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop, Hydrol. Earth Syst. Sci., 21, 4767–4784, https://doi.org/10.5194/hess-21-4767-2017, 2017. es_ES
dc.subject.ods 06.- Garantizar la disponibilidad y la gestión sostenible del agua y el saneamiento para todos es_ES
dc.subject.ods 02.- Poner fin al hambre, conseguir la seguridad alimentaria y una mejor nutrición, y promover la agricultura sostenible es_ES
dc.subject.ods 13.- Tomar medidas urgentes para combatir el cambio climático y sus efectos es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem