Ronald E. McRoberts

12.0k total citations · 2 hit papers
225 papers, 8.5k citations indexed

About

Ronald E. McRoberts is a scholar working on Environmental Engineering, Nature and Landscape Conservation and Ecology. According to data from OpenAlex, Ronald E. McRoberts has authored 225 papers receiving a total of 8.5k indexed citations (citations by other indexed papers that have themselves been cited), including 175 papers in Environmental Engineering, 138 papers in Nature and Landscape Conservation and 115 papers in Ecology. Recurrent topics in Ronald E. McRoberts's work include Remote Sensing and LiDAR Applications (171 papers), Forest ecology and management (134 papers) and Remote Sensing in Agriculture (100 papers). Ronald E. McRoberts is often cited by papers focused on Remote Sensing and LiDAR Applications (171 papers), Forest ecology and management (134 papers) and Remote Sensing in Agriculture (100 papers). Ronald E. McRoberts collaborates with scholars based in United States, Norway and Italy. Ronald E. McRoberts's co-authors include Erkki Tomppo, Erik Næsset, Gherardo Chirici, Terje Gobakken, M. G. Lawrence, Mark D. Nelson, James A. Westfall, L. David Mech, Daniel G. Wendt and Susanne Winter and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and Science Advances.

In The Last Decade

Ronald E. McRoberts

217 papers receiving 8.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

National Forest Inventories

2009 525 citations Erkki Tomppo, Ronald E. McRoberts et al. profile →
Changes in global terrestrial live biomass over the 21st century

2021 200 citations Grant M. Domke, Ronald E. McRoberts et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ronald E. McRoberts United States	55	5.5k	4.6k	4.1k	3.5k	1.4k	225	8.5k
John Armston United States	42	5.5k 1.0×	3.1k 0.7×	4.0k 1.0×	2.8k 0.8×	821 0.6×	132	7.5k
Andrew T. Hudak United States	55	6.0k 1.1×	4.1k 0.9×	5.8k 1.4×	6.1k 1.8×	1.8k 1.2×	230	11.0k
M. A. Lefsky United States	34	7.2k 1.3×	4.7k 1.0×	5.2k 1.3×	3.7k 1.1×	1.6k 1.1×	70	10.2k
Terje Gobakken Norway	56	8.8k 1.6×	6.4k 1.4×	4.5k 1.1×	2.3k 0.7×	3.4k 2.4×	243	10.5k
Darius Culvenor Australia	32	3.7k 0.7×	2.4k 0.5×	3.3k 0.8×	2.1k 0.6×	1.0k 0.7×	54	5.8k
Glenn Newnham Australia	32	3.4k 0.6×	2.3k 0.5×	2.5k 0.6×	1.8k 0.5×	1.1k 0.7×	63	5.1k
Mathias Disney United Kingdom	49	5.7k 1.0×	3.8k 0.8×	4.0k 1.0×	3.0k 0.9×	1.4k 1.0×	160	8.1k
Barbara Koch Germany	34	3.8k 0.7×	2.3k 0.5×	3.0k 0.7×	1.3k 0.4×	1.2k 0.8×	124	5.5k
Ross Nelson United States	36	4.6k 0.8×	3.3k 0.7×	2.6k 0.6×	1.3k 0.4×	1.6k 1.1×	62	5.4k
Sorin Popescu United States	38	5.2k 0.9×	3.1k 0.7×	3.1k 0.8×	1.5k 0.4×	1.6k 1.1×	104	6.3k

Countries citing papers authored by Ronald E. McRoberts

Since Specialization

Citations

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

Fields of papers citing papers by Ronald E. McRoberts

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ronald E. McRoberts. 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 Ronald E. McRoberts. The network helps show where Ronald E. McRoberts may publish in the future.

Co-authorship network of co-authors of Ronald E. McRoberts

This figure shows the co-authorship network connecting the top 25 collaborators of Ronald E. McRoberts. A scholar is included among the top collaborators of Ronald E. McRoberts 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 Ronald E. McRoberts. Ronald E. McRoberts 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

Francini, Saverio, Mart‐Jan Schelhaas, Elia Vangi, et al.. (2024). Forest species mapping and area proportion estimation combining Sentinel-2 harmonic predictors and national forest inventory data. International Journal of Applied Earth Observation and Geoinformation. 131. 103935–103935. 12 indexed citations

Ståhl, Göran, Terje Gobakken, Svetlana Saarela, et al.. (2024). Why ecosystem characteristics predicted from remotely sensed data are unbiased and biased at the same time – and how this affects applications. Forest Ecosystems. 11. 100164–100164. 10 indexed citations

Hou, Zhengyang, Göran Ståhl, Ronald E. McRoberts, et al.. (2024). Nexus of certain model-based estimators in remote sensing forest inventory. Forest Ecosystems. 11. 100245–100245. 1 indexed citations

Hou, Zhengyang, Göran Ståhl, Ronald E. McRoberts, et al.. (2023). Conjugating remotely sensed data assimilation and model-assisted estimation for efficient multivariate forest inventory. Remote Sensing of Environment. 299. 113854–113854. 6 indexed citations

Knott, Jonathan A., Greg C. Liknes, Sungchan Oh, et al.. (2023). Effects of outliers on remote sensing‐assisted forest biomass estimation: A case study from the United States national forest inventory. Methods in Ecology and Evolution. 14(7). 1587–1602. 17 indexed citations

Tomppo, Erkki, Yrjö Rauste, Ronald E. McRoberts, et al.. (2023). Sentinel-1 Time Series for Predicting Growing Stock Volume of Boreal Forest: Multitemporal Analysis and Feature Selection. Remote Sensing. 15(14). 3489–3489. 6 indexed citations

Francini, Saverio, Ronald E. McRoberts, Luca Congedo, et al.. (2023). Estimating Afforestation Area Using Landsat Time Series and Photointerpreted Datasets. Remote Sensing. 15(4). 923–923. 16 indexed citations

Francini, Saverio, Giovanni D’Amico, Ronald E. McRoberts, et al.. (2023). Reusing Remote Sensing-Based Validation Data: Comparing Direct and Indirect Approaches for Afforestation Monitoring. Remote Sensing. 15(6). 1638–1638. 10 indexed citations

Antropov, Oleg, et al.. (2023). Deep Learning Model Transfer in Forest Mapping Using Multi-Source Satellite SAR and Optical Images. Remote Sensing. 15(21). 5152–5152. 6 indexed citations

10.

D’Amico, Giovanni, Ronald E. McRoberts, Francesca Giannetti, et al.. (2022). Effects of lidar coverage and field plot data numerosity on forest growing stock volume estimation. European Journal of Remote Sensing. 55(1). 199–212. 4 indexed citations

11.

Francini, Saverio, Ronald E. McRoberts, Francesca Giannetti, et al.. (2021). The Three Indices Three Dimensions (3I3D) algorithm: a new method for forest disturbance mapping and area estimation based on optical remotely sensed imagery. International Journal of Remote Sensing. 42(12). 4693–4711. 25 indexed citations

12.

Vangi, Elia, Giovanni D’Amico, Saverio Francini, et al.. (2021). The Effect of Forest Mask Quality in the Wall-to-Wall Estimation of Growing Stock Volume. Remote Sensing. 13(5). 1038–1038. 19 indexed citations

13.

Giannetti, Francesca, R. Pegna, Saverio Francini, et al.. (2020). A New Method for Automated Clearcut Disturbance Detection in Mediterranean Coppice Forests Using Landsat Time Series. Remote Sensing. 12(22). 3720–3720. 26 indexed citations

14.

Francini, Saverio, Ronald E. McRoberts, Francesca Giannetti, et al.. (2020). Near-real time forest change detection using PlanetScope imagery. European Journal of Remote Sensing. 53(1). 233–244. 76 indexed citations

15.

Lister, Andrew J., Hans Henrik Andersen, Tracey S. Frescino, et al.. (2020). Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory. Forests. 11(12). 1364–1364. 66 indexed citations

16.

Næsset, Erik, Terje Gobakken, & Ronald E. McRoberts. (2019). A Model-Dependent Method for Monitoring Subtle Changes in Vegetation Height in the Boreal–Alpine Ecotone Using Bi-Temporal, Three Dimensional Point Data from Airborne Laser Scanning. Remote Sensing. 11(15). 1804–1804. 7 indexed citations

17.

McRoberts, Ronald E., Stephen V. Stehman, Greg C. Liknes, et al.. (2018). The effects of imperfect reference data on remote sensing-assisted estimators of land cover class proportions. ISPRS Journal of Photogrammetry and Remote Sensing. 142. 292–300. 63 indexed citations

18.

McRoberts, Ronald E., Erkki Tomppo, Klemens Schadauer, et al.. (2009). Harmonizing National Forest Inventories. Journal of Forestry. 107(4). 179–187. 60 indexed citations

19.

Finley, Andrew O., Ronald E. McRoberts, & Alan R. Ek. (2006). Applying an Efficient k-Nearest Neighbor Search to Forest Attribute Imputation. Forest Science. 52(2). 130–135. 15 indexed citations

20.

Stevens, C., Margaret A. Palmer, Anna Tang, & Ronald E. McRoberts. (1990). Use of Aminopeptidase Substrate Specificities to Identify Species of Cylindrocladium in Wisconsin Nurseries. Mycologia. 82(4). 436–443. 1 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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