N. Pinto

2.2k total citations · 1 hit paper
31 papers, 1.4k citations indexed

About

N. Pinto is a scholar working on Environmental Engineering, Aerospace Engineering and Ecology. According to data from OpenAlex, N. Pinto has authored 31 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Environmental Engineering, 12 papers in Aerospace Engineering and 11 papers in Ecology. Recurrent topics in N. Pinto's work include Remote Sensing and LiDAR Applications (14 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (12 papers) and Cryospheric studies and observations (8 papers). N. Pinto is often cited by papers focused on Remote Sensing and LiDAR Applications (14 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (12 papers) and Cryospheric studies and observations (8 papers). N. Pinto collaborates with scholars based in United States, Germany and Brazil. N. Pinto's co-authors include Marc Simard, Joshua B. Fisher, Alessandro Baccini, Timothy H. Keitt, Ralph Dubayah, M. A. Hofton, Marco Lavalle, Scott Hensley, Carlos Roberto Sanquetta and Franciel Eduardo Rex and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and Oikos.

In The Last Decade

N. Pinto

30 papers receiving 1.4k citations

Hit Papers

Mapping forest canopy height globally with spaceborne lidar 2011 2026 2016 2021 2011 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
N. Pinto United States 10 756 643 600 436 267 31 1.4k
Clare S. Rowland United Kingdom 18 776 1.0× 515 0.8× 616 1.0× 285 0.7× 174 0.7× 45 1.4k
Ramón Alberto Díaz Varela Spain 22 897 1.2× 1.1k 1.6× 537 0.9× 303 0.7× 280 1.0× 42 2.0k
Kim Lowell United States 21 586 0.8× 530 0.8× 484 0.8× 297 0.7× 138 0.5× 97 1.4k
Heather Reese Sweden 20 1.1k 1.5× 983 1.5× 650 1.1× 485 1.1× 233 0.9× 42 1.9k
C. S. R. Neigh United States 19 929 1.2× 497 0.8× 782 1.3× 266 0.6× 334 1.3× 51 1.5k
Kathleen M. Bergen United States 18 668 0.9× 822 1.3× 591 1.0× 368 0.8× 238 0.9× 44 1.5k
João M. B. Carreiras United Kingdom 25 1.0k 1.4× 785 1.2× 881 1.5× 497 1.1× 156 0.6× 46 1.9k
Geoffrey Brian Groom Denmark 18 740 1.0× 351 0.5× 554 0.9× 248 0.6× 144 0.5× 38 1.3k
Steven R. Schill United States 22 795 1.1× 478 0.7× 694 1.2× 259 0.6× 223 0.8× 51 1.7k
Darren Pouliot Canada 28 1.1k 1.5× 708 1.1× 765 1.3× 304 0.7× 665 2.5× 49 2.2k

Countries citing papers authored by N. Pinto

Since Specialization
Citations

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

Fields of papers citing papers by N. Pinto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of N. Pinto

This figure shows the co-authorship network connecting the top 25 collaborators of N. Pinto. A scholar is included among the top collaborators of N. Pinto 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 N. Pinto. N. Pinto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
2.
Pinto, N., et al.. (2023). Burn Severity Mapping with L-band UAVSAR Observations Over Los Angeles’ Largest Wildfire. 3375–3378. 1 indexed citations
3.
Chen, Richard H., N. Pinto, Xueyang Duan, Alireza Tabatabaeenejad, & Mahta Moghaddam. (2020). Mapping Tree Canopy Cover and Canopy Height with L-Band SAR Using LiDAR Data and Random Forests. 4136–4139. 4 indexed citations
4.
Hensley, Scott, Bruce Chapman, Brian Hawkins, et al.. (2020). Boreal Forest Radar Tomography at P, L and S-Bands at Berms and Delta Junction. 96–99. 1 indexed citations
5.
Miller, Charles E., P. C. Griffith, S. J. Goetz, et al.. (2019). An overview of ABoVE airborne campaign data acquisitions and science opportunities. Environmental Research Letters. 14(8). 80201–80201. 62 indexed citations
6.
Moura, Marks Melo, et al.. (2019). REGRESSÕES ROBUSTA E LINEAR PARA ESTIMATIVA DE BIOMASSA VIA IMAGEM SENTINEL EM UMA FLORESTA TROPICAL. SHILAP Revista de lepidopterología. 4(2). 81–81. 6 indexed citations
7.
Lou, Yunling, Scott Hensley, Bruce Chapman, et al.. (2019). Recent Airborne Sar Demonstrations for Monitoring and Assessment of Volcanic Lava Flow and Severe Flooding. 9388–9390. 2 indexed citations
8.
Hawkins, Brian, N. Pinto, Marco Lavalle, & S. Hensley. (2018). AfriSAR: Polarimetric Height Profiles by TomoSAR, Lope and Rabi Forests, Gabon, 2016. Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics.
9.
Lou, Yunling, Scott Hensley, Brian Hawkins, et al.. (2017). Uavsar program: Recent upgrades to support vegetation structure studies and land ICE topography mapping. 5893–5895. 1 indexed citations
10.
Lavalle, Marco, S. Hensley, Yunling Lou, et al.. (2016). Canopy Height and Vertical Structure from Multibaseline Polarimetric InSAR: First Results of the 2016 NASA/ESA AfriSAR Campaign. AGU Fall Meeting Abstracts. 2016. 1 indexed citations
11.
Hensley, Scott, Yunling Lou, Thierry Michel, et al.. (2016). UAVSAR PolInSAR and tomographic experiments in Germany. elib (German Aerospace Center). 7517–7520. 1 indexed citations
12.
Cook, Bruce D., et al.. (2014). CMS: LiDAR-derived Estimates of Aboveground Biomass at Four Forested Sites, USA. Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics. 3 indexed citations
13.
Bohn, T. J., E. Podest, R. Schroeder, et al.. (2013). The effects of surface moisture heterogeneity on wetland carbon fluxes in the West Siberian Lowland. 3 indexed citations
14.
Bohn, T. J., E. Podest, R. Schroeder, et al.. (2013). Modeling the large-scale effects of surface moisture heterogeneity on wetland carbon fluxes in the West Siberian Lowland. Biogeosciences. 10(10). 6559–6576. 28 indexed citations
15.
Duncanson, Laura, Ralph Dubayah, G. C. Hurtt, et al.. (2012). How important is individual tree information for biomass modeling and mapping. AGUFM. 2012. 3 indexed citations
16.
Pinto, N., et al.. (2012). Terrain radiometric calibration of airborne UAVSAR for forested area. Geo-spatial Information Science. 15(4). 229–240. 6 indexed citations
17.
Dubayah, Ralph, Amanda Armstrong, Bruce D. Cook, et al.. (2011). County-Scale Carbon Estimation in NASA's Carbon Monitoring System. AGU Fall Meeting Abstracts. 2011. 2 indexed citations
18.
Simard, M., et al.. (2009). UAVSAR's first campaign over temperate and boreal forests. AGU Fall Meeting Abstracts. 2009. 1 indexed citations
19.
Simard, Marc, et al.. (2008). Characterizing Vegetation 3D structure Globally using Spaceborne Lidar and Radar.. AGU Fall Meeting Abstracts. 2008. 2 indexed citations
20.
Pinto, N. & Timothy H. Keitt. (2008). Beyond the least-cost path: evaluating corridor redundancy using a graph-theoretic approach. Landscape Ecology. 24(2). 253–266. 202 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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