Support Vector Regression Machine Learning Tool to Predict GNSS Clock Corrections in Real-Time PPP Technique

[EN] Real-time Precise Point Positioning (PPP) can provide the Global Navigation Satellites Systems (GNSS) users with the ability to determine their position accurately using only one GNSS receiver. The PPP solution does not rely on a base receiver or local GNSS network. However, for establishing a real-time PPP solution, the GNSS users are required to receive the Real-Time Service (RTS) message over the Network Transported of RTCM via Internet Protocol (NTRIP). The RTS message includes orbital, code biases, and clock corrections. GNSS users receive those corrections produced by the analysis center with some latency, which degraded the quality of coordinates obtained through realtime PPP. In this research, we investigate the Support Vector Machine (SVR) machine learning tool to overcome the latency for clock corrections in the IGS03 product. Three days of continuous GNSS observations at BREST permanent station in France were selected as a case study. BNC software was used to generate clock corrections files. Taking as reference the clock correction values without latency. The SVR solution shows a reduction in the standard deviation and range with about 30% and 20%, respectively, in comparison to the latency solution for all satellites except those satellites in GLONASS M block.Qafisheh, MWA.; Martín Furones, ÁE.; Torres-Sospedra, J. (2020). Support Vector Regression Machine Learning Tool to Predict GNSS Clock Corrections in Real-Time PPP Technique. CEUR Workshop Proceedings. 1-8. http://hdl.handle.net/10251/178545S1

Python software tools for GNSS interferometric reflectometry (GNSS-IR)

[EN] Global Navigation Satellite System (GNSS) interferometric reflectometry, also known as the GNSS-IR, uses data from geodetic-quality GNSS antennas to extract information about the environment surrounding the antenna. Soil moisture moni-toring is one of the most important applications of the GNSS-IR technique. This manuscript presents the main ideas and implementation decisions needed to write the Python code for software tools that transform RINEX format observation and navigation files into an appropriate format for GNSS-IR (which includes the SNR observations and the azimuth and elevation of the satellites) and to determine the reflection height and the adjusted phase and amplitude values of the interferometric wave for each individual satellite track. The main goal of the manuscript is to share the software with the scientific com-munity to introduce new users to the GNSS-IR technique.The authors want to thank the staff of the Cajamar Center of Experiences, and especially Carlos Baixauli, for their support and collaboration in the Paiporta experiment. The authors also want to thank Alfred Leick and Steve Hilla for their valuable comments and suggestions.Martín Furones, ÁE.; Luján García Muñoz, R.; Anquela Julián, AB. (2020). Python software tools for GNSS interferometric reflectometry (GNSS-IR). GPS Solutions. 24(4):1-7. https://doi.org/10.1007/s10291-020-01010-0S17244Chen Q, Won D, Akos DM, Small EE (2016) Vegetation using GPS interferometric reflectometry: experimental results with a horizontal polarized antenna. IEEE J Select Top Appl Earth Obs Rem Sens 9(10):4771–4780. https://doi.org/10.1109/JSTARS.2016.2565687Chew CC, Small EE, Larson KM, Zavorotny VU (2014) Effects of near-surface soil moisture on GPS SNR data: development and retrieval algorithm for soil moisture. IEEE T Geosci Rem Sens 52(1):537–543. https://doi.org/10.1109/TGRS.2013.2242332Chew CC, Small EE, Larson KM, Zavorotny UZ (2015) Vegetation sensing using GPS-interferometric reflectometry: theoretical effects of canopy parameters on signal-to-noise ratio data. IEEE T Geosci Rem Sens 53(5):2755–2764. https://doi.org/10.1109/TGRS.2014.2364513Chew CC, Small EE, Larson KM (2016) An algorithm for soil moisture estimation using GPS-interferometric reflectometry for bare and vegetated soil. GPS Solut 20(3):525–537. https://doi.org/10.1007/s10291-015-0462-4Gurtner W, Estey L (2015) RINEX: the receiver independent exchange format version 3.03. ftp://igs.org/pub/data/format/rinex303.pdfLarson KM, Small EE, Gutmann ED, Bilich AL, Axelrad A, Braun JJ (2008a) Using GPS multipath to measure soil moisture fluctuations: initial results. GPS Solut 12(3):173–177. https://doi.org/10.1007/s10291-007-0076-6Larson KM, Small EE, Gutmann ED, Bilich AL, Braun JJ, Zavorotny VU (2008b) Use of GPS receivers as a soil moisture network for water cycle studies. Geophys Res Lett 35:L24405. https://doi.org/10.1029/2008GL036013Larson KM, Gutmann E, Zavorotny VU, Braun J, Williams M, Nievinski FG (2009) Can we measure snow depth with GPS receivers? Geophys Res Lett 36:L17502. https://doi.org/10.1029/2009GL039430Larson KM, Braun JJ, Small EE, Zavorotny VU (2010) GPS multipath and its relation to near-surface soil moisture content. IEEE J Selec Top Appl Earth Obs Rem Sens 3(1):91–99. https://doi.org/10.1109/JSTARS.2009.2033612Larson KM, Nievinski FG (2013) GPS snow sensing: results from the EarthScope plate boundary observatory. GPS Solut 17(1):41–52. https://doi.org/10.1007/s10291-012-0259-7Leick A, Rapoport L, Tatarnikov D (2015) GPS satellite surveying, 4th edn. Wiley, Hoboken, p 840Martín A, Ibañez S, Baixauli C, Blanc S, Anquela AB (2020) Multi-constellation interferometric reflectometry with mass-market sensors as a solution for soil moisture monitoring. Hydrol Earth Syst Sci. https://doi.org/10.5194/hess-24-3573-2020Nievinski GG, Larson KM (2014) An open source GPS multipath simulator in Matlab/Octave. GPS Solut 18:473–481. https://doi.org/10.1007/s10291-014-0370-zNischan T (2016) GFZRNX—RINEX GNSS data conversion and manipulation toolbox (Version 1.05). GFZ Data Serv. https://doi.org/10.5880/GFZ.1.1.2016.002Roesler C, Larson KM (2018) Software tools for GNSS interferometric reflectometry (GNSS-IR). GPS Solut. https://doi.org/10.1007/s10291-018-0744-8Roussel N, Ramilien G, Frappart F, Darrozes J, Gay A, Biancale R, Striebig N, Hanquiez V, Bertin X, Allain A (2015) Sea level monitoring and sea estimate using a single geodetic receiver. Remote Sens Environ 171:261–277. https://doi.org/10.1016/j.rse.2015.10.011Roussel N, Frappart F, Ramillien G, Darroes J, Baup F, Lestarquit L, Ha MC (2016) Detection of soil moisture variations using GPS and GLONASS SNR data for elevation angles ranging from 2º to 70º. IEEE J Selec Top Appl Earth Obs Rem Sens 9(10):4781–4794. https://doi.org/10.1109/JSTARS.2016.2537847Sanz J, Juan JM, Hernández-Pajares M (2013) GNSS data processing. Volume I: fundamentals and algorithms. European Space Agency Communications, 223 ppSmall EE, Larson KM, Chew CC, Dong J, Ochsner TE (2016) Validation of GPS-IR soil moisture retrievals: comparison of different algorithms to remove vegetation effects. IEEE J Selec Top Appl Earth Obs Rem Sens 9(10):4759–4770. https://doi.org/10.1109/JSTARS.2015.2504527Vey S, Güntner A, Wickert J, Blume T, Ramatschi M (2016) 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/s10291-015-0474-0Wan W, Larson KM, Small EE, Chew CC, Braun JJ (2015) Using geodetic GPS receivers to measure vegetation water content. GPS Solut 19:237–248. https://doi.org/10.1007/s10291-014-0383-7Zhang S, Roussel N, Boniface K, Ha MC, Frappart F, Darrozes J, Baup F, Calvet JC (2017) 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-21-4767-201

Analysis of Twitter messages using big data tools to evaluate and locate the activity in the city of Valencia (Spain)

[EN] This paper presents the big data architecture and work flow used to download georeferenced tweets, store them in a NoSQL database, analyse them using the Apache Spark framework, and visualize the results. The study covers a complete year (from December 10, 2016 to December 10, 2017) in the city of Valencia (Eastern Spain), which is considered to be the third most important in Spain, having a population of nearly 800,000 inhabitants and a size of 135 km(2). The concepts of a specific event map and a specific event map with positive or negative sentiment are developed to highlight the location of an event. This approach is undertaken by subtracting the heat map of a specific day from the mean daily heat map, which is obtained by taking into account the 365 days of the studied period. This paper demonstrates how the proposed analysis from tweets can be used to depict city events and discover their spatiotemporal characteristics. Finally, the combination of all daily specific events maps in a single map, leads to the conclusion that the city of Valencia city has appropriate urban infrastructures to support these events.The authors would like to thank the comments and suggestions of the anonymous reviewers and the editor, which have helped to improve the original version.Martín Furones, ÁE.; Anquela Julián, AB.; Cos-Gayón López, FJ. (2019). Analysis of Twitter messages using big data tools to evaluate and locate the activity in the city of Valencia (Spain). Cities. (86):37-50. https://doi.org/https://doi.org/10.1016/j.cities.2018.12.014S37508

Computational time reduction for sequential batch solutions in GNSS precise point positioning technique

[EN] Precise point positioning (PPP) is a well established Global Navigation Satellite System (GNSS) technique that only requires information from the receiver (or rover) to obtain high-precision position coordinates. This is a very interesting and promising technique because eliminates the need for a reference station near the rover receiver or a network of reference stations, thus reducing the cost of a GNSS survey. From a computational perspective, there are two ways to solve the system of observation equations produced by static PPP either in a single step (so-called batch adjustment) or with a sequential adjustment/filter. The results of each should be the same if they are both well implemented. However, if a sequential solution (that is, not only the final coordinates, but also those observed in previous GNSS epochs), is needed, as for convergence studies, finding a batch solution becomes a very time consuming task owing to the need for matrix inversion that accumulates with each consecutive epoch. This is not a problem for the filter solution, which uses information computed in the previous epoch for the solution of the current epoch. Thus filter implementations need extra considerations of user dynamics and parameter state variations between observation epochs with appropriate stochastic update parameter variances from epoch to epoch. These filtering considerations are not needed in batch adjustment, which makes it attractive. The main objective of this research is to significantly reduce the computation time required to obtain sequential results using batch adjustment. The new method we implemented in the adjustment process led to a mean reduction in computational time by 45%.This research was supported by the Spanish Science and Innovation Directorate project number AYA2010-18706 and the Generalitat Valenciana Geronimo Forteza research program with project number FPA/2014/056.Martín Furones, ÁE.; Anquela Julián, AB.; Dimas-Pagés, A.; Cos-Gayón López, FJ. (2017). Computational time reduction for sequential batch solutions in GNSS precise point positioning technique. Computers & Geosciences. 105:34-42. doi:10.1016/j.cageo.2017.03.023S344210

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

[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.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-24-3573-2020S35733582247Chan, 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.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.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.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.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.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.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.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.Larson, K. M. and Nievinski, F. G.: GPS snow sensing: results from the EarthScope plate boundary observatory, GPS Solut., 17, 41–52, 2013.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.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.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.Leick, A., Rapoport, L., and Tatarnikov, D.: GPS satellite surveying, 4th edn., John Wiley & Sons, Hoboken, New Jersey, USA, 840 pp., 2015.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.Lomb, N. R.: Least-squares frequency – Analysis of unequally spaced data, Astrophys. Space Sci., 39, 447–462, 1976.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.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.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.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.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.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.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.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.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.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.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

Estudio del geoide en el parque nacional de Doñana

En el marco de los proyectos de la DGICyT “Procesos hidrogeológicos y geomorfológicos en los humedales del área de Doñana” y “Análisis de la dinámica del sistema acuífero de Doñana y sus relaciones con la evolución reciente del modelado dunar y con los usos del terreno y del acuífero” (Madre I y Madre II, respectivamente), se ha establecido una red GPS enlazada con la red REGENTE y dotada de cota ortométrica en todos sus puntos mediante nivelación geométrica y medidas de gravedad. Uno de los objetivos de estas redes es el de analizar y ajustar los modelos de geoide existente IBERGEO95 y EGG97, así como de calcular un nuevo modelo que se adapte a la zona y que permita facilitar el establecimiento de un modelo hidrogeológico para este área. Un modelo de geoide de precisión permitirá convertir las cotas de los posicionamientos GPS de elipsoidales a ortométricas. Esto es fundamental para los trabajos de modelado hidrológico superficial y subterráneo que se están llevando a cabo en el entorno del Parque Nacional de Doñana. Contar con un modelo de geoide bien escalado localmente también ha sido un punto clave para el adecuado ajuste de un MDT de la marisma obtenido mediante Láser Escáner Aerotransportado por encargo de la Confederación Hidrográfica del Guadalquivir. Por otra parte, las singularidades del campo gravitatorio podrán corroborar la existencia de algunas estructuras geológicas tipo falla regional. En esta comunicación se resumen los trabajos realizados hasta la fecha y se presenta el estado actual del modelo de geoide.Peer ReviewedPostprint (published version

Kinematic GNSS-PPP results from various software packages and raw data configurations

[EN] In this study, kinematic precise point positioning (PPP) was tested. The raw data were taken from permanent stations, two airplane trajectories, a car trajectory and a walking trajectory. International GNSS Service (IGS) final products were used in the post-processing phase. The observations were processed using four different on-line software packages: the Canadian Spatial Reference System On-line Global GPS Processing Service (CSRS-PPP), the GPS Analysis and Position Software (GAPS), the Automatic Precise Positioning Service (APPS) and the Magic Global Navigation Satellite System (MagicGNSS). The results and comparisons are described in detail. The main conclusion is that an accuracy better than 10 cm for the planimetric measurements and better than 20 cm for the altimetric measurements can be achieved using the kinematic PPP method in any of the proposed tests. However, at present, the success of the technique is affected by the software used, and differences at the 0.5 m level can be found for the same specific epoch.This research is supported by the Spanish Science and Innovation Directorate project number AYA2010-18706.Martín Furones, ÁE.; Anquela Julián, AB.; Berné Valero, JL.; Sanmartín, M. (2012). Kinematic GNSS-PPP results from various software packages and raw data configurations. Scientific Research and Essays. 7(3):419-431. https://doi.org/10.5897/SRE11.1885S4194317

3rd Congress in Geomatics Engineering

The Congress in Geomatics Engineering aims to bring together scientists, academics and PhD students to exchange and share their results of research and innovation related to any Geomatics discipline. It offers a first-class interdisciplinary platform to present and discuss the innovations, rends, concerns, challenges and solutions adopted in the different fields of Geomatics.This biennial Congress is born within the framework provided by the Interuniversity PhD program in Geomatics Engineering by the Universidad Politécnica de Valencia and the Universidad Politécnica de Madrid.In July 2021 we will celebrate the third edition of the congress at the Universitat Politècnica de Valencia.Martín Furones, ÁE. (2021). 3rd Congress in Geomatics Engineering. Editorial Universitat Politècnica de València. https://doi.org/10.4995/CIGeo2021.2021.13957EDITORIA

Primer congreso en ingeniería geomática. Libro de actas

El I Congreso en Ingeniería Geomática tiene como objetivo reunir a científicos, académicos y estudiantes de doctorado para intercambiar y compartir sus resultados de investigación e innovación relativos a cualquier disciplina Geomática. Ofrece una plataforma interdisciplinar de primer nivel para presentar y discutir las innovaciones, tendencias, preocupaciones, desafíos y soluciones adoptadas en los diferentes campos de la Geomática. Este Congreso, de carácter bienal, nace dentro del marco que proporciona el programa de doctorado interuniversitario en Ingeniería Geomática por la Universidad Politécnica de Valencia y la Universidad Politécnica de Madrid.Martín Furones, ÁE. (2017). Primer congreso en ingeniería geomática. Libro de actas. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/90687EDITORIA

Análisis y ajuste de modelos de geoide. Observación y cálculo de la red gravimétrica de tercer orden en la Provincia de Valencia

En la tesis se presenta la investigación desarrollada sobre el análisis y ajuste de modelos de geoide. La zona elegida para el estudio está comprendida en la Comunidad Valenciana, por lo que se investigarán las posibilidades de análisis y ajuste a las características locales del campo de gravedad de los diferentes modelos de geoide utilizables en la comunidad: modelos globales como el OSU89b, OSU91a, EGM96 o el GPM98, el modelo continental Europeo EGG97 y el modelo regional sobre la Península Ibérica IBERGEO95. Para ello, en primer lugar, se ha realizado una investigación rigurosa sobre las redes de nivelación que atraviesan la Comunidad Valenciana atendiendo a su existencia, estado y precisiones. Así mismo se ha desarrollado una red gravimétrica de tercer orden sobre la Provincia de Valencia, con una nueva metodología de ajuste. A continuación se ha desarrollado un método para la detección de deformaciones locales de geoide utilizando observables GPS/gravedad, se ha procedido al análisis de los modelos mediante puntos GPS/gravedad y GPS/nivelación/gravedad y, posteriormente, se han ajustado los modelos de geoide a puntos GPS/nivelación/gravedad. Finalmente se han transformado los modelos de geoide de alta resolución investigados a geoides con grandes posibilidades prácticas de utilización en la zona de estudio, con valores de error medio de 0.07 m, tanto en valor absoluto como en relativo (considerando distancias máximas de 20-30 Km).Martín Furones, ÁE. (2001). Análisis y ajuste de modelos de geoide. Observación y cálculo de la red gravimétrica de tercer orden en la Provincia de Valencia [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/5696