J. Sanz

1.5k total citations
51 papers, 1.2k citations indexed

About

J. Sanz is a scholar working on Environmental Engineering, Ecology and Global and Planetary Change. According to data from OpenAlex, J. Sanz has authored 51 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Environmental Engineering, 11 papers in Ecology and 9 papers in Global and Planetary Change. Recurrent topics in J. Sanz's work include Remote Sensing in Agriculture (9 papers), Solar Radiation and Photovoltaics (8 papers) and Energy Load and Power Forecasting (7 papers). J. Sanz is often cited by papers focused on Remote Sensing in Agriculture (9 papers), Solar Radiation and Photovoltaics (8 papers) and Energy Load and Power Forecasting (7 papers). J. Sanz collaborates with scholars based in Spain, United States and France. J. Sanz's co-authors include José Luis Casanova Roque, Diego Gómez, Pablo Salvador, C. Casanova‐Mateo, Sancho Salcedo‐Sanz, L. Cornejo-Bueno, S. Jiménez‐Fernández, Pedro Antonio Gutiérrez, César Hervás‐Martínez and David Guijo-Rubio and has published in prestigious journals such as Environmental Pollution, Atmospheric Environment and Energy.

In The Last Decade

J. Sanz

48 papers receiving 1.1k citations

Peers

Countries citing papers authored by J. Sanz

Since Specialization

Citations

This map shows the geographic impact of J. Sanz'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 J. Sanz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Sanz more than expected).

Fields of papers citing papers by J. Sanz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. Sanz. 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 J. Sanz. The network helps show where J. Sanz may publish in the future.

Co-authorship network of co-authors of J. Sanz

This figure shows the co-authorship network connecting the top 25 collaborators of J. Sanz. A scholar is included among the top collaborators of J. Sanz 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 J. Sanz. J. Sanz 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

#	Work	Indexed citations
1	Hybridizing Machine Learning Algorithms With Numerical Models for Accurate Wind Power Forecasting 2025 ·Expert Systems ·(unknown), (unknown), Jorge Pérez‐Aracil, J. Sanz, C. Casanova‐Mateo, Sancho Salcedo‐Sanz	3
2	Spain on fire: A novel wildfire risk assessment model based on image satellite processing and atmospheric information 2023 ·Knowledge-Based Systems ·(unknown), Javier Huertas‐Tato, Jorge Pérez‐Aracil, C. Casanova‐Mateo, J. Sanz, David Camacho	13
3	Machine Learning Classification-Regression Schemes for Desert Locust Presence Prediction in Western Africa 2023 ·SSRN Electronic Journal ·L. Cornejo-Bueno, Jorge Pérez‐Aracil, C. Casanova‐Mateo, J. Sanz, Sancho Salcedo‐Sanz	1
4	Machine Learning Classification–Regression Schemes for Desert Locust Presence Prediction in Western Africa 2023 ·Applied Sciences ·L. Cornejo-Bueno, Jorge Pérez‐Aracil, C. Casanova‐Mateo, J. Sanz, Sancho Salcedo‐Sanz	6
5	Randomization-based machine learning in renewable energy prediction problems: Critical literature review, new results and perspectives 2022 ·Applied Soft Computing ·Javier Del Ser, David Casillas-Pérez, L. Cornejo-Bueno, (unknown), J. Sanz, C. Casanova‐Mateo, Sancho Salcedo‐Sanz	40
6	A new approach to monitor water quality in the Menor sea (Spain) using satellite data and machine learning methods 2021 ·Environmental Pollution ·Diego Gómez, Pablo Salvador, J. Sanz, José Luis Casanova Roque	65
7	Regional estimation of garlic yield using crop, satellite and climate data in Mexico 2021 ·Computers and Electronics in Agriculture ·Diego Gómez, Pablo Salvador, J. Sanz, (unknown)	12
8	Modelling wheat yield with antecedent information, satellite and climate data using machine learning methods in Mexico 2021 ·Agricultural and Forest Meteorology ·Diego Gómez, Pablo Salvador, J. Sanz, José Luis Casanova Roque	74
9	Analysis and Prediction of Dammed Water Level in a Hydropower Reservoir Using Machine Learning and Persistence-Based Techniques 2020 ·Water ·(unknown), David Casillas-Pérez, C. Casanova‐Mateo, (unknown), (unknown), J. Sanz, Pedro Antonio Gutiérrez, Sancho Salcedo‐Sanz	34
10	Evolutionary artificial neural networks for accurate solar radiation prediction 2020 ·Energy ·David Guijo-Rubio, Antonio M. Durán-Rosal, Pedro Antonio Gutiérrez, (unknown), C. Casanova‐Mateo, J. Sanz, Sancho Salcedo‐Sanz, César Hervás‐Martínez	70
11	Desert locust detection using Earth observation satellite data in Mauritania 2019 ·Journal of Arid Environments ·Diego Gómez, Pablo Salvador, J. Sanz, C. Casanova, (unknown), José Luis Casanova Roque	40
12	Efficient prediction of total column ozone based on support vector regression algorithms, numerical models and Suomi-satellite data 2017 ·Atmósfera ·L. Carro‐Calvo, C. Casanova‐Mateo, (unknown), J. Sanz, (unknown), (unknown), (unknown), Sancho Salcedo‐Sanz	5
13	A novel Grouping Genetic Algorithm–Extreme Learning Machine approach for global solar radiation prediction from numerical weather models inputs 2016 ·Solar Energy ·(unknown), S. Jiménez‐Fernández, L. Cornejo-Bueno, C. Casanova‐Mateo, J. Sanz, (unknown), Sancho Salcedo‐Sanz	91
14	Feature selection in solar radiation prediction using bootstrapped SVRs 2016 ·(unknown), Vanessa Gómez-Verdejo, Manel Martínez‐Ramón, C. Casanova‐Mateo, J. Sanz, S. Jiménez‐Fernández, Sancho Salcedo‐Sanz	11
15	Can Eltonian processes explain species distributions at large scale? A case study with Great Bustard (Otis tarda) 2014 ·Diversity and Distributions ·José Manuel Álvarez‐Martínez, Susana Suárez‐Seoane, Carlos Palacı́n, J. Sanz, Juan Carlos Alonso	16
16	An approach to the analysis of the critical control points of the Costa Brava water reclamation facilities 2013 ·Water Practice & Technology ·Lluís Sala, J. Sanz, (unknown)	0
17	Detection and Monitoring of Forest Fires in China Through the Envisat-AATSR Sensor 2006 ·Á. Calle, J. Sanz, (unknown), José Luis Casanova Roque, J. G. Goldammer, Zengyuan Li, (unknown)	4
18	Forest Fires Identification Using AATSR and MODIS Data 2006 ·(unknown), (unknown), Xin Tian, José Luis Casanova Roque, Á. Calle, (unknown), J. Sanz	0
19	Fire Detection and Monitoring, in Real Time, Using MSG Images 2004 ·ESASP ·Á. Calle, A. Romo, J. Sanz, José Luis Casanova Roque	1
20	Case report: Oncogenous osteomalacia: A new case secondary to a malignant tumor 1986 ·Bone ·H. Rico, (unknown), J. Sanz, F. Gómez-Castresana, (unknown), Eva Hernández, Isabel Krsnik	8

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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