M. Chica-Rivas
Impact in
- Media Technology top 1%
- Remote-Sensing Image Classification
- Environmental Engineering top 2%
- Soil Geostatistics and Mapping
- Urban Heat Island Mitigation
Papers in
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- Remote-Sensing Image Classification 4
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- Geochemistry and Geologic Mapping 3
- Co-authors
- Víctor Rodríguez‐Galiano (5 shared papers)Mario Chica‐Olmo (3 shared papers)M. Sánchez-Castillo (2 shared papers)Eulogio Pardo‐Igúzquiza (3 shared papers)Jorge Chica‐Olmo (1 shared paper)J.P. Rigol-Sánchez (1 shared paper)
- Journals
- International Journal of Applied Earth Observation and Geoinformation (1 paper)International Journal of Digital Earth (1 paper)Ore Geology Reviews (1 paper)Sustainability (1 paper)Boletín de la Sociedad Geológica Mexicana (1 paper)
- Partner nations
- SpainUnited Kingdom
In The Last Decade
M. Chica-Rivas
7 papers receiving 1.6k citations
M. Chica-Rivas's Hit Papers
Peers
Comparison fields: 5 of 149
- Media Technology 304
- Environmental Engineering 425
- Artificial Intelligence 610
- Global and Planetary Change 230
- Mechanical Engineering 358
Countries citing papers authored by M. Chica-Rivas
This map shows the geographic impact of M. Chica-Rivas'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. Chica-Rivas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Chica-Rivas more than expected).
Fields of papers citing papers by M. Chica-Rivas
This network shows the impact of papers produced by M. Chica-Rivas. 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. Chica-Rivas. The network helps show where M. Chica-Rivas may publish in the future.
Co-authors
The 6 scholars most cited alongside M. Chica-Rivas, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Machine learning predictive models for mineral prospectivity: An evaluation of neural networks, random forest, regression trees and support vector machines Hit paper breakdown → | 2015 | 1165 |
| 2 | 2014 | 180 | |
| 3 | 2012 | 135 | |
| 4 | 2011 | 88 | |
| 5 | 2019 | 33 | |
| 6 | 2011 | 2 | |
| 7 | 2010 | 1 |
About M. Chica-Rivas
M. Chica-Rivas is a scholar working on Media Technology, Artificial Intelligence, Environmental Engineering, Ecology and Global and Planetary Change, having authored 7 papers that have together received 1.6k indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (4 papers), Geochemistry and Geologic Mapping (3 papers), Remote Sensing in Agriculture (2 papers), Soil Geostatistics and Mapping (2 papers), Land Use and Ecosystem Services (2 papers), Mineral Processing and Grinding (1 paper), Housing Market and Economics (1 paper) and Geological and Geophysical Studies Worldwide (1 paper). The work is most often cited by research in Media Technology (304 citations), Environmental Engineering (425 citations), Artificial Intelligence (610 citations), Global and Planetary Change (230 citations) and Mechanical Engineering (358 citations). M. Chica-Rivas has collaborated with scholars based in Spain and United Kingdom. Frequent co-authors include Víctor Rodríguez‐Galiano, Mario Chica‐Olmo, M. Sánchez-Castillo, Eulogio Pardo‐Igúzquiza, Jorge Chica‐Olmo and J.P. Rigol-Sánchez. Their work appears in journals such as International Journal of Applied Earth Observation and Geoinformation, International Journal of Digital Earth, Ore Geology Reviews, Sustainability and Boletín de la Sociedad Geológica Mexicana.
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.