Brian T. Lamb

698 total citations
32 papers, 480 citations indexed

About

Brian T. Lamb is a scholar working on Ecology, Environmental Engineering and Global and Planetary Change. According to data from OpenAlex, Brian T. Lamb has authored 32 papers receiving a total of 480 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Ecology, 23 papers in Environmental Engineering and 13 papers in Global and Planetary Change. Recurrent topics in Brian T. Lamb's work include Remote Sensing in Agriculture (20 papers), Remote Sensing and LiDAR Applications (11 papers) and Soil Geostatistics and Mapping (9 papers). Brian T. Lamb is often cited by papers focused on Remote Sensing in Agriculture (20 papers), Remote Sensing and LiDAR Applications (11 papers) and Soil Geostatistics and Mapping (9 papers). Brian T. Lamb collaborates with scholars based in United States and Spain. Brian T. Lamb's co-authors include W. Dean Hively, Craig S. T. Daughtry, Miguel Quemada, Jacob Shermeyer, Gregory W. McCarty, Maria Tzortziou, Philip E. Dennison, Zhuoting Wu, Jyoti S. Jennewein and Ryan M. Stauffer and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Remote Sensing of Environment and Sensors.

In The Last Decade

Brian T. Lamb

27 papers receiving 465 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian T. Lamb United States 13 310 240 186 124 50 32 480
Enrico C. Paringit Philippines 11 291 0.9× 171 0.7× 184 1.0× 59 0.5× 44 0.9× 44 492
Zhaoqin Li Canada 13 288 0.9× 155 0.6× 241 1.3× 149 1.2× 29 0.6× 26 522
John Iiames United States 10 272 0.9× 138 0.6× 208 1.1× 102 0.8× 17 0.3× 18 449
Amina Rangoonwala United States 15 275 0.9× 109 0.5× 159 0.9× 81 0.7× 27 0.5× 35 467
Jianxi Huang China 9 158 0.5× 191 0.8× 258 1.4× 110 0.9× 23 0.5× 32 514
Yousef Aldakheel Saudi Arabia 6 266 0.9× 325 1.4× 90 0.5× 52 0.4× 48 1.0× 11 503
Cankut Örmeci Türkiye 11 149 0.5× 167 0.7× 239 1.3× 154 1.2× 20 0.4× 21 431
L. C. Lepine United States 13 246 0.8× 137 0.6× 342 1.8× 148 1.2× 33 0.7× 18 546
Lei Lu China 12 115 0.4× 210 0.9× 141 0.8× 166 1.3× 42 0.8× 22 427
Li Pan China 10 251 0.8× 127 0.5× 297 1.6× 107 0.9× 25 0.5× 18 459

Countries citing papers authored by Brian T. Lamb

Since Specialization
Citations

This map shows the geographic impact of Brian T. Lamb'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 Brian T. Lamb with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian T. Lamb more than expected).

Fields of papers citing papers by Brian T. Lamb

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian T. Lamb. 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 Brian T. Lamb. The network helps show where Brian T. Lamb may publish in the future.

Co-authorship network of co-authors of Brian T. Lamb

This figure shows the co-authorship network connecting the top 25 collaborators of Brian T. Lamb. A scholar is included among the top collaborators of Brian T. Lamb 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 Brian T. Lamb. Brian T. Lamb 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.
Lamb, Brian T., et al.. (2025). Multiyear crop residue cover mapping using narrow-band vs. broad-band shortwave infrared satellite imagery. Soil and Tillage Research. 251. 106524–106524. 1 indexed citations
2.
Hively, W. Dean, Feng Gao, Gregory W. McCarty, et al.. (2025). Satellite assessment of winter cover crop and conservation tillage outcomes to support adaptive management in working landscapes. Journal of Environmental Quality. 54(6). 1548–1571.
3.
Jennewein, Jyoti S., W. Dean Hively, Brian T. Lamb, et al.. (2025). Multispectral red‐edge indices accurately estimate nitrogen content in winter cereal cover crops. Agronomy Journal. 117(1). 3 indexed citations
4.
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Jennewein, Jyoti S., W. Dean Hively, Brian T. Lamb, et al.. (2024). Spaceborne imaging spectroscopy enables carbon trait estimation in cover crop and cash crop residues. Precision Agriculture. 25(5). 2165–2197. 3 indexed citations
7.
Jennewein, Jyoti S., et al.. (2024). Intercomparison of Same-Day Remote Sensing Data for Measuring Winter Cover Crop Biophysical Traits. Sensors. 24(7). 2339–2339. 6 indexed citations
8.
Lamb, Brian T., W. Dean Hively, Philip E. Dennison, & Jyoti S. Jennewein. (2024). Spaceborne Spectral Characterization Of Non-Photosynthetic Vegetation Cover. 1256–1259. 1 indexed citations
9.
Kraatz, Simon, Brian T. Lamb, W. Dean Hively, et al.. (2023). Comparing NISAR (Using Sentinel-1), USDA/NASS CDL, and Ground Truth Crop/Non-Crop Areas in an Urban Agricultural Region. Sensors. 23(20). 8595–8595. 6 indexed citations
10.
Dennison, Philip E., Brian T. Lamb, Michael J. Campbell, et al.. (2023). Modeling global indices for estimating non-photosynthetic vegetation cover. Remote Sensing of Environment. 295. 113715–113715. 20 indexed citations
11.
Lamb, Brian T., Philip E. Dennison, W. Dean Hively, et al.. (2022). Optimizing Landsat Next Shortwave Infrared Bands for Crop Residue Characterization. Remote Sensing. 14(23). 6128–6128. 11 indexed citations
12.
Jordan, Carolyn E., Ryan M. Stauffer, Brian T. Lamb, et al.. (2021). New in situ aerosol hyperspectral optical measurements over 300–700 nm – Part 2: Extinction, total absorption, water- and methanol-soluble absorption observed during the KORUS-OC cruise. Atmospheric measurement techniques. 14(1). 715–736. 3 indexed citations
13.
Jordan, Carolyn E., Ryan M. Stauffer, Brian T. Lamb, et al.. (2021). New in situ aerosol hyperspectral optical measurements over 300–700 nm – Part 1: Spectral Aerosol Extinction (SpEx) instrument field validation during the KORUS-OC cruise. Atmospheric measurement techniques. 14(1). 695–713. 3 indexed citations
14.
Hively, W. Dean, Brian T. Lamb, Craig S. T. Daughtry, et al.. (2021). Evaluation of SWIR Crop Residue Bands for the Landsat Next Mission. Remote Sensing. 13(18). 3718–3718. 34 indexed citations
15.
Lamb, Brian T., Maria Tzortziou, & K. C. McDonald. (2021). A Fused Radar–Optical Approach for Mapping Wetlands and Deepwaters of the Mid–Atlantic and Gulf Coast Regions of the United States. Remote Sensing. 13(13). 2495–2495. 9 indexed citations
16.
Lamb, Brian T.. (2020). Tidal Wetland Inundation and Vegetation Phenology from Space: A Synthesis of Approaches for Characterizing Ecological Status and Inundation Dynamics in Tidal Wetlands with Remote Sensing Observations. CUNY Academic Works (City University of New York). 1 indexed citations
17.
Thompson, Anne M., Ryan M. Stauffer, Debra E. Kollonige, et al.. (2019). Comparison of Near‐Surface NO2 Pollution With Pandora Total Column NO2 During the Korea‐United States Ocean Color (KORUS OC) Campaign. Journal of Geophysical Research Atmospheres. 124(23). 13560–13575. 21 indexed citations
18.
Wagenbrenner, Natalie, et al.. (2012). Scalar Transport and Dispersion in Complex Terrain within a High Resolution Mass-Consistent Wind Modeling Framework. AGU Fall Meeting Abstracts. 2012.
19.
Velasco, Erik, S. N. Pressley, G. Allwine, et al.. (2007). Eddy Covariance Flux Measurements of Pollutant Gases in the Mexico City Urban Area: a Useful Technique to Evaluate Emissions inventories. AGUFM. 2007.
20.
Pressley, S. N., J. L. Jiménez, Eiko Nemitz, et al.. (2007). Eddy Covariance Flux Measurements of Urban Aerosols During the MILAGRO Mexico City Field Campaign. AGU Fall Meeting Abstracts. 2007.

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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