Alicia Peduzzi

519 total citations
30 papers, 396 citations indexed

About

Alicia Peduzzi is a scholar working on Nature and Landscape Conservation, Environmental Engineering and Ecology. According to data from OpenAlex, Alicia Peduzzi has authored 30 papers receiving a total of 396 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Nature and Landscape Conservation, 15 papers in Environmental Engineering and 11 papers in Ecology. Recurrent topics in Alicia Peduzzi's work include Forest ecology and management (21 papers), Remote Sensing and LiDAR Applications (14 papers) and Remote Sensing in Agriculture (11 papers). Alicia Peduzzi is often cited by papers focused on Forest ecology and management (21 papers), Remote Sensing and LiDAR Applications (14 papers) and Remote Sensing in Agriculture (11 papers). Alicia Peduzzi collaborates with scholars based in United States, Mexico and Türkiye. Alicia Peduzzi's co-authors include Randolph H. Wynne, Valerie A. Thomas, Thomas R. Fox, Ross Nelson, José Luis Hernández‐Stefanoni, Juan Manuel Dupuy, Kristofer Johnson, Richard A. Birdsey, Fernando Tun‐Dzul and Bruce D. Cook and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and International Journal of Remote Sensing.

In The Last Decade

Alicia Peduzzi

30 papers receiving 386 citations

Peers

Alicia Peduzzi

NLC

ECOLO

GPC

Francisco Rodríguez Spain

Diego Giuliarelli Italy

M Rasamoelina Madagascar

Michael Heym Germany

Ernest William Mauya Tanzania

Stéphane Momo Takoudjou Cameroon

Petra Adler Germany

Lan Qie United Kingdom

Keiko Ioki Japan

P.K. Tickle Australia

Francisco Rodríguez Spain

Alicia Peduzzi

241 ×1.0

278 ×1.2

NLC

129 ×0.6

ECOLO

238 ×1.9

GPC

56 ×1.0

Citations per year, relative to Alicia Peduzzi Alicia Peduzzi (= 1×) peers Francisco Rodríguez

Countries citing papers authored by Alicia Peduzzi

Since Specialization

Citations

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

Fields of papers citing papers by Alicia Peduzzi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alicia Peduzzi

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

Peduzzi, Alicia, et al.. (2025). Advancing biomass estimation in hydroponic lettuce using RGB-depth imaging and morphometric descriptors with machine learning. Computers and Electronics in Agriculture. 234. 110299–110299. 1 indexed citations

Merry, Krista, et al.. (2024). Estimating Forest Inventory Information for the Talladega National Forest Using Airborne Laser Scanning Systems. Remote Sensing. 16(16). 2933–2933. 3 indexed citations

Peduzzi, Alicia, et al.. (2024). Reliable plant segmentation under variable greenhouse illumination conditions. Computers and Electronics in Agriculture. 229. 109711–109711. 2 indexed citations

Peduzzi, Alicia, et al.. (2024). Surface Heat Monitoring with High-Resolution UAV Thermal Imaging: Assessing Accuracy and Applications in Urban Environments. Remote Sensing. 16(5). 930–930. 12 indexed citations

Lee, Taeyoon, et al.. (2024). Mapping percent canopy cover using individual tree- and area-based procedures that are based on airborne LiDAR data: Case study from an oak-hickory-pine forest in the USA. Ecological Indicators. 167. 112710–112710. 6 indexed citations

Abrams, Jesse, et al.. (2024). Informal Land Tenure and Livelihood Resilience in the Chaco Salteño, Argentina. Society & Natural Resources. 37(12). 1673–1690. 2 indexed citations

Montes, Cristián R., et al.. (2023). A Comparison of Modeling Methods for Predicting Forest Attributes Using Lidar Metrics. Remote Sensing. 15(5). 1284–1284. 16 indexed citations

Peduzzi, Alicia, et al.. (2023). Assessment of understory vegetation in a plantation forest of the southeastern United States using terrestrial laser scanning. Ecological Informatics. 77. 102254–102254. 5 indexed citations

Peduzzi, Alicia, et al.. (2023). Biomass Estimation of Urban Forests Using LiDAR and High-Resolution Aerial Imagery in Athens–Clarke County, GA. Forests. 14(5). 1064–1064. 5 indexed citations

10.

Valdez‐Lazalde, José René, et al.. (2020). Medición del índice de área foliar y su dinámica estacional en plantaciones de Eucalyptus urophylla S. T. Blake. SHILAP Revista de lepidopterología. 12(63). 1 indexed citations

11.

Dupuy, Juan Manuel, et al.. (2019). Combining high resolution satellite imagery and lidar data to model woody species diversity of tropical dry forests. Ecological Indicators. 101. 975–984. 22 indexed citations

12.

Valdez‐Lazalde, José René, et al.. (2019). Transectos de datos LiDAR: una estrategia de muestreo para estimar biomasa aérea en áreas forestales. Madera y Bosques. 25(3). 3 indexed citations

13.

Valdez‐Lazalde, José René, et al.. (2017). Above-ground net primary productivity in commercial Eucalyptus urophylla S. T. Blake plantations in Huimanguillo, Tabasco, Mexico.. 51(3). 343–358. 1 indexed citations

14.

Valdez‐Lazalde, José René, et al.. (2017). PRODUCTIVIDAD PRIMARIA NETA AÉREA EN PLANTACIONES COMERCIALES DE Eucalyptus urophylla S. T. Blake EN HUIMANGUILLO, TABASCO, MÉXICO. Redalyc (Universidad Autónoma del Estado de México). 51(3). 343–358. 1 indexed citations

15.

Santos-Posadas, Héctor M. De los, et al.. (2017). ESTIMACIÓN DEL VOLUMEN COMERCIAL EN PLANTACIONES DE Eucalyptus urophylla CON MODELOS DE VOLUMEN TOTAL Y DE RAZÓN. Redalyc (Universidad Autónoma del Estado de México). 51(5). 561–580. 9 indexed citations

16.

Hernández‐Stefanoni, José Luis, Kristofer Johnson, Bruce D. Cook, et al.. (2015). Estimating species richness and biomass of tropical dry forests using LIDAR during leaf‐on and leaf‐off canopy conditions. Applied Vegetation Science. 18(4). 724–732. 17 indexed citations

17.

Hernández‐Stefanoni, José Luis, Juan Manuel Dupuy, Kristofer Johnson, et al.. (2014). Improving Species Diversity and Biomass Estimates of Tropical Dry Forests Using Airborne LiDAR. Remote Sensing. 6(6). 4741–4763. 64 indexed citations

18.

Raymond, Crystal L., Sean P. Healey, Alicia Peduzzi, & Paul L. Patterson. (2014). Representative regional models of post-disturbance forest carbon accumulation: Integrating inventory data and a growth and yield model. Forest Ecology and Management. 336. 21–34. 22 indexed citations

19.

Peduzzi, Alicia, et al.. (2012). Combined Use of Airborne Lidar and DBInSAR Data to Estimate LAI in Temperate Mixed Forests. Remote Sensing. 4(6). 1758–1780. 17 indexed citations

20.

Peduzzi, Alicia. (2007). Leaf Area Assessments of Overstory and Understory Vegetation in Pine Plantations Located in South Georgia and North Florida, US. NCSU Libraries Repository (North Carolina State University Libraries). 4 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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