Marc Linderman

4.3k total citations · 2 hit papers
43 papers, 3.1k citations indexed

About

Marc Linderman is a scholar working on Ecology, Global and Planetary Change and Ecological Modeling. According to data from OpenAlex, Marc Linderman has authored 43 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Ecology, 25 papers in Global and Planetary Change and 14 papers in Ecological Modeling. Recurrent topics in Marc Linderman's work include Remote Sensing in Agriculture (18 papers), Land Use and Ecosystem Services (17 papers) and Species Distribution and Climate Change (14 papers). Marc Linderman is often cited by papers focused on Remote Sensing in Agriculture (18 papers), Land Use and Ecosystem Services (17 papers) and Species Distribution and Climate Change (14 papers). Marc Linderman collaborates with scholars based in United States, China and Belgium. Marc Linderman's co-authors include Jianguo Liu, Li An, Zhiyun Ouyang, Hemin Zhang, Pedram Rowhani, David B. Lobell, Navin Ramankutty, Jian Yang, Jiaguo Qi and Éric F. Lambin and has published in prestigious journals such as Science, Journal of Geophysical Research Atmospheres and Remote Sensing of Environment.

In The Last Decade

Marc Linderman

43 papers receiving 2.9k citations

Hit Papers

Ecological Degradation in Protected Areas: The Case of Wo... 2001 2026 2009 2017 2001 2011 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marc Linderman United States 27 1.3k 1.1k 553 457 382 43 3.1k
Jane Southworth United States 37 3.0k 2.2× 1.7k 1.6× 449 0.8× 405 0.9× 609 1.6× 115 4.9k
Praveen Noojipady United States 23 2.3k 1.7× 1.9k 1.7× 885 1.6× 248 0.5× 250 0.7× 30 3.7k
Erfu Dai China 32 2.3k 1.7× 818 0.8× 324 0.6× 145 0.3× 321 0.8× 126 3.2k
D. J. Barrett Australia 30 2.4k 1.8× 1.0k 0.9× 679 1.2× 148 0.3× 591 1.5× 87 4.1k
Lyndon Estes United States 24 1.7k 1.3× 1.0k 0.9× 543 1.0× 337 0.7× 329 0.9× 55 3.1k
P. K. Joshi India 42 2.9k 2.2× 1.9k 1.8× 1.4k 2.5× 404 0.9× 493 1.3× 161 5.6k
Antonio Trabucco Italy 31 1.7k 1.3× 1.0k 1.0× 416 0.8× 545 1.2× 878 2.3× 69 4.4k
Maria J. Santos Switzerland 35 1.2k 0.9× 1.7k 1.6× 275 0.5× 554 1.2× 648 1.7× 121 3.4k
Javier Gallego Italy 18 1.7k 1.3× 1.3k 1.2× 474 0.9× 233 0.5× 492 1.3× 27 2.8k
D.C. Howard United Kingdom 25 987 0.7× 791 0.7× 297 0.5× 200 0.4× 459 1.2× 97 2.4k

Countries citing papers authored by Marc Linderman

Since Specialization
Citations

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

Fields of papers citing papers by Marc Linderman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marc Linderman

This figure shows the co-authorship network connecting the top 25 collaborators of Marc Linderman. A scholar is included among the top collaborators of Marc Linderman 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 Marc Linderman. Marc Linderman 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
1.
Linderman, Marc, et al.. (2022). Object based classification of a riparian environment using ultra-high resolution imagery, hierarchical landcover structures, and image texture. Scientific Reports. 12(1). 11291–11291. 10 indexed citations
2.
Guo, Long, Xiaoru Sun, Peng Fu, et al.. (2021). Mapping soil organic carbon stock by hyperspectral and time-series multispectral remote sensing images in low-relief agricultural areas. Geoderma. 398. 115118–115118. 122 indexed citations
4.
Hong, Yongsheng, Songchao Chen, Yiyun Chen, et al.. (2020). Comparing laboratory and airborne hyperspectral data for the estimation and mapping of topsoil organic carbon: Feature selection coupled with random forest. Soil and Tillage Research. 199. 104589–104589. 97 indexed citations
5.
6.
7.
Guo, Long, Haitao Zhang, Tiezhu Shi, et al.. (2018). Prediction of soil organic carbon stock by laboratory spectral data and airborne hyperspectral images. Geoderma. 337. 32–41. 83 indexed citations
8.
Khandelwal, Meena, Matthew E. Hill, Paul R. Greenough, et al.. (2016). Why Have Improved Cook-Stove Initiatives in India Failed?. World Development. 92. 13–27. 130 indexed citations
9.
Liang, Dong, Mary Kathryn Cowles, & Marc Linderman. (2016). Bayesian MODIS NDVI back-prediction by intersensor calibration with AVHRR. Remote Sensing of Environment. 186. 393–404. 10 indexed citations
10.
Guo, Long, Chang Zhao, Haitao Zhang, et al.. (2016). Comparisons of spatial and non-spatial models for predicting soil carbon content based on visible and near-infrared spectral technology. Geoderma. 285. 280–292. 51 indexed citations
11.
Liang, Dong, et al.. (2011). An Optimal Spatial Sampling for Demographic and Health Surveys. SSRN Electronic Journal. 2 indexed citations
12.
Hull, Vanessa, Weihua Xu, Wei Liu, et al.. (2011). Evaluating the efficacy of zoning designations for protected area management. Biological Conservation. 144(12). 3028–3037. 104 indexed citations
13.
Rowhani, Pedram, Marc Linderman, & Éric F. Lambin. (2011). Global interannual variability in terrestrial ecosystems: sources and spatial distribution using MODIS-derived vegetation indices, social and biophysical factors. International Journal of Remote Sensing. 32(19). 5393–5411. 14 indexed citations
14.
Parker, Dawn C., Barbara Entwisle, Ronald R. Rindfuss, et al.. (2008). Case studies, cross-site comparisons, and the challenge of generalization: comparing agent-based models of land-use change in frontier regions. Journal of Land Use Science. 3(1). 41–72. 50 indexed citations
15.
Bearer, Scott, Marc Linderman, Jinyan Huang, et al.. (2007). Effects of fuelwood collection and timber harvesting on giant panda habitat use. Biological Conservation. 141(2). 385–393. 93 indexed citations
16.
Viña, Andrés, Scott Bearer, Xiaohong Chen, et al.. (2007). TEMPORAL CHANGES IN GIANT PANDA HABITAT CONNECTIVITY ACROSS BOUNDARIES OF WOLONG NATURE RESERVE, CHINA. Ecological Applications. 17(4). 1019–1030. 75 indexed citations
17.
Linderman, Marc, Li An, Scott Bearer, et al.. (2006). Interactive Effects Of Natural And Human Disturbances On Vegetation Dynamics Across Landscapes. Ecological Applications. 16(2). 452–463. 31 indexed citations
18.
Linderman, Marc, Pedram Rowhani, David Benz, Suzanne Serneels, & Éric F. Lambin. (2005). Land‐cover change and vegetation dynamics across Africa. Journal of Geophysical Research Atmospheres. 110(D12). 39 indexed citations
19.
An, Li, Frank Lupi, Jianguo Liu, Marc Linderman, & Jinyan Huang. (2002). Modeling the choice to switch from fuelwood to electricity. Ecological Economics. 42(3). 445–457. 92 indexed citations
20.
Liu, Jianguo, Marc Linderman, Zhiyun Ouyang, et al.. (2001). Ecological Degradation in Protected Areas: The Case of Wolong Nature Reserve for Giant Pandas. Science. 292(5514). 98–101. 555 indexed citations breakdown →

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026