M. Vall‐llossera

5.0k total citations
188 papers, 3.5k citations indexed

About

M. Vall‐llossera is a scholar working on Environmental Engineering, Atmospheric Science and Aerospace Engineering. According to data from OpenAlex, M. Vall‐llossera has authored 188 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 155 papers in Environmental Engineering, 111 papers in Atmospheric Science and 66 papers in Aerospace Engineering. Recurrent topics in M. Vall‐llossera's work include Soil Moisture and Remote Sensing (153 papers), Precipitation Measurement and Analysis (59 papers) and Synthetic Aperture Radar (SAR) Applications and Techniques (45 papers). M. Vall‐llossera is often cited by papers focused on Soil Moisture and Remote Sensing (153 papers), Precipitation Measurement and Analysis (59 papers) and Synthetic Aperture Radar (SAR) Applications and Techniques (45 papers). M. Vall‐llossera collaborates with scholars based in Spain, Netherlands and Germany. M. Vall‐llossera's co-authors include Adriano Camps, I. Corbella, María Piles, N. Duffo, F. Torres, José Martínez‐Fernández, Nilda Sánchez, Xavier Bosch-Lluis, I. Ramos‐Perez and Nereida Rodriguez-Alvarez and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Remote Sensing of Environment and Water Resources Research.

In The Last Decade

M. Vall‐llossera

179 papers receiving 3.4k citations

Peers

M. Vall‐llossera

OCEAN

GPC

David M. Le Vine United States

Manuel Martín‐Neira Netherlands

Andreas Colliander United States

Nazzareno Pierdicca Italy

Valery U. Zavorotny United States

Philippe Waldteufel France

Clara Chew United States

François Cabot France

M. Hallikainen Finland

S.N. Madsen United States

David M. Le Vine United States

M. Vall‐llossera

3.4k ×1.2

2.7k ×1.2

1.2k ×1.1

1.1k ×1.8

OCEAN

438 ×1.4

GPC

Citations per year, relative to M. Vall‐llossera M. Vall‐llossera (= 1×) peers David M. Le Vine

Countries citing papers authored by M. Vall‐llossera

Since Specialization

Citations

This map shows the geographic impact of M. Vall‐llossera's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by M. Vall‐llossera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Vall‐llossera more than expected).

Fields of papers citing papers by M. Vall‐llossera

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Vall‐llossera. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by M. Vall‐llossera. The network helps show where M. Vall‐llossera may publish in the future.

Co-authorship network of co-authors of M. Vall‐llossera

This figure shows the co-authorship network connecting the top 25 collaborators of M. Vall‐llossera. A scholar is included among the top collaborators of M. Vall‐llossera based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with M. Vall‐llossera. M. Vall‐llossera is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Vall‐llossera, M., Carlos López-Martínez, Adriano Camps, et al.. (2024). 60-m Resolution Soil Moisture Estimation Based on a Multisensor Feedforward Neural Network Model. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 15543–15566. 3 indexed citations

Pablos, Míriam, Antonio Turiel, Adriano Camps, et al.. (2024). Spatial Spectra Assessment of SMOS Soil Moisture at Different Spatial Scales. DIGITAL.CSIC (Spanish National Research Council (CSIC)). 5147–5150. 1 indexed citations

Chaparro, David, Thomas Jagdhuber, María Piles, et al.. (2023). Estimation of Gravimetric Vegetation Moisture in the Western United States Using a Multi-Sensor Approach. QRU Quaderns de Recerca en Urbanisme. 6. 1505–1508.

Vall‐llossera, M., Carlos López-Martínez, Adriano Camps, et al.. (2023). A Random Forest Approach for Soil Moisture Estimation at 60 Meters Spatial Resolution. QRU Quaderns de Recerca en Urbanisme. 98. 2898–2901. 2 indexed citations

Chaparro, David, et al.. (2022). Global Unsupervised Assessment of Multifrequency Vegetation Optical Depth Sensitivity to Vegetation Cover. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16. 538–552. 10 indexed citations

Vall‐llossera, M., et al.. (2020). Validation of SMOS L3 AND L4 Soil Moisture Products In The Remedhus (SPAIN) AND CEMADEN (BRAZIL) Networks. Revista Brasileira de Geografia Física. 13(2). 691–712. 6 indexed citations

Pablos, Míriam, M. Vall‐llossera, María Piles, et al.. (2019). Influence of Quality Filtering Approaches in BEC SMOS L3 Soil Moisture Products. DIGITAL.CSIC (Spanish National Research Council (CSIC)). 6941–6944. 2 indexed citations

Sánchez, Nilda, María Piles, M. Vall‐llossera, et al.. (2013). Soil Moisture Maps At Very High Spatial Resolution Through Optical, Thermal And L-Band Observations. 722. 325. 1 indexed citations

Ramos‐Perez, I., Giuseppe Forte, Xavier Bosch-Lluis, et al.. (2011). First results of the PAU-SA synthetic aperture radiometer. 3633–3636. 1 indexed citations

10.

Bosch-Lluis, Xavier, Albert Aguasca, Adriano Camps, et al.. (2010). Study of maize plants effects in the retrieval of soil moisture using the interference pattern GNSS-R technique. QRU Quaderns de Recerca en Urbanisme. 3813–3816. 8 indexed citations

11.

Ramos‐Perez, I., Xavier Bosch-Lluis, Adriano Camps, et al.. (2010). On-ground tests and measurements of the Passive Advanced Unit Synthetic Aperture (PAU-SA). 3114–3117. 3 indexed citations

12.

Camps, Adriano, M. Vall‐llossera, María Piles, et al.. (2008). Improving the Spatial Resolution of Synthetic Aperture Radiometer Imagery using Auxiliary Information: Application to the Smos Mission. III – 411. 1 indexed citations

13.

Sabia, Roberto, Adriano Camps, M. Vall‐llossera, Marco Talone, & Jordi Font. (2007). Towards an ocean salinity error budget estimation within the SMOS mission. br 224. 38–41. 4 indexed citations

14.

Monerris, A., et al.. (2006). Soil Moisture Retrieval Using L-band Radiometry: Dependence on Soil Type and Moisture Profiles. 171–175. 11 indexed citations

15.

Torres, F., I. Corbella, Adriano Camps, et al.. (2006). Denormalization of Visibilities for In-Orbit Calibration of Interferometric Radiometers. IEEE Transactions on Geoscience and Remote Sensing. 44(10). 2679–2686. 28 indexed citations

16.

Camps, Adriano, et al.. (2003). Sea surface emissivity at L-band: derived dependence with incidence and azimuth angles. ESASP. 525. 105–116. 3 indexed citations

17.

Vall‐llossera, M., et al.. (2003). Sea surface emissivity modeling at L-band: an inter-comparison study. ESASP. 525. 143–153. 4 indexed citations

18.

Gabarró, Carolina, Jordi Font, Adriano Camps, & M. Vall‐llossera. (2003). Retrieved sea surface salinity and wind speed from L-band measurements for WISE and EuroSTARRS campaigns. DIGITAL.CSIC (Spanish National Research Council (CSIC)). 525. 163–171. 3 indexed citations

19.

Geffrin, Jean‐Michel, et al.. (2003). Reduction of the model noise in non-linear reconstruction via an efficient calculation of the incident field: application to a 434 MHz scanner. UPCommons institutional repository (Universitat Politècnica de Catalunya). 2. 996–999. 2 indexed citations

20.

Rubio‐Marcos, Fernando, et al.. (2003). End-to-end Simulator of 2-D Interferometric Radiometry. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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