Research | Interagency Lidar Monitoring & Research Applications

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Data citation and recent lidar research publications updated quarterly

Links to Publications

Data Citation and Acknowledgment
There are no restrictions on the use of IntELiMon products. Please cite the IntELiMon datasets using the information below.

U.S. Geological Survey, 2026, IntELiMon (Interagency Ecosystem Lidar Monitoring): U.S. Geological Survey database, https://doi.org/10.5066/P13T3UG3

FGDC metadata can be found through the USGS Science Data Catalog (SDC) at: USGS Science Data Catalog

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JOURNAL ARTICLES
MANUSCRIPT

Title	Authors	Year	Citation
Detecting historic tar kilns and tar production sites using high-resolution, aerial LiDAR-derived digital elevation models: Introducing the Tar Kiln Feature Detection workflow (TKFD) using open-access R and FIJI software.	Snitker, G., Moser, J.D., Southerlin, B., Stewart, C.	2022	Full Citation Snitker, G., Moser, J.D., Southerlin, B., Stewart, C., 2022, Detecting historic tar kilns and tar production sites using high-resolution, aerial LiDAR-derived digital elevation models: Introducing the Tar Kiln Feature Detection workflow (TKFD) using open-access R and FIJI software, at https://www.sciencedirect.com/science/article/abs/pii/S2352409X22000037?via%3Dihub.
Semantic segmentation of archaeological features on public lands – Case study of historical cotton terraces within the Piedmont National Wildlife Refuge, GA, USA.	Gravel-Miguel, C., Snitker, G., Hirniak, J., Peck, K., Fetterhoff, A.	2024	Full Citation Gravel-Miguel, C., Snitker, G., Hirniak, J., Peck, K., Fetterhoff, A., 2024, Semantic segmentation of archaeological features on public lands – Case study of historical cotton terraces within the Piedmont National Wildlife Refuge, GA, USA, Manuscript in revision at Advances in Archaeological Practice.
Traditional field metrics and terrestrial LiDAR predict plant richness in southern pine forests.	C.T. Anderson, S.L. Dietz, S.M. Pokswinski, A.M. Jenkins, M.J. Kaeser, J.K. Hiers, B.D. Pelc	2021	Full Citation C.T. Anderson, S.L. Dietz, S.M. Pokswinski, A.M. Jenkins, M.J. Kaeser, J.K. Hiers, B.D. Pelc, 2021, Traditional field metrics and terrestrial LiDAR predict plant richness in southern pine forests, Forest Ecology and Management, at https://doi.org/10.1016/j.foreco.2021.119118.
Estimation of Plot-Level Burn Severity Using Terrestrial Laser Scanning.	Michael R. Gallagher, Aaron E. Maxwell, Luis Andrés Guillén, Alexis Everland, E. Louise Loudermilk, Nicholas S. Skowronski	2021	Full Citation Michael R. Gallagher, Aaron E. Maxwell, Luis Andrés Guillén, Alexis Everland, E. Louise Loudermilk, Nicholas S. Skowronski, 2021, Estimation of Plot-Level Burn Severity Using Terrestrial Laser Scanning, MDPI, at https://doi.org/10.3390/rs13204168.
Terrestrial laser scan metrics predict surface vegetation biomass and consumption in a frequently burned southeastern U.S. ecosystem.	E. Louise Loudermilk, Scott Pokswinski, Christie M. Hawley, Aaron Maxwell, Michael Gallagher, Nicholas Skowronski, Andrew T. Hudak, Chad Hoffman, J. Kevin Hiers	2023	Full Citation E. Louise Loudermilk, Scott Pokswinski, Christie M. Hawley, Aaron Maxwell, Michael Gallagher, Nicholas Skowronski, Andrew T. Hudak, Chad Hoffman, J. Kevin Hiers, 2023, Terrestrial laser scan metrics predict surface vegetation biomass and consumption in a frequently burned southeastern U.S. ecosystem, bioRxiv, at https://www.biorxiv.org/content/10.1101/2023.01.15.524107v1.

Title	Authors	Year	Citation
Detecting historic tar kilns and tar production sites using high-resolution, aerial LiDAR-derived digital elevation models: Introducing the Tar Kiln Feature Detection workflow (TKFD) using open-access R and FIJI software.	Snitker, G., Moser, J.D., Southerlin, B., Stewart, C.	2022	Full Citation Snitker, G., Moser, J.D., Southerlin, B., Stewart, C., 2022, Detecting historic tar kilns and tar production sites using high-resolution, aerial LiDAR-derived digital elevation models: Introducing the Tar Kiln Feature Detection workflow (TKFD) using open-access R and FIJI software, at https://www.sciencedirect.com/science/article/abs/pii/S2352409X22000037?via%3Dihub.
Traditional field metrics and terrestrial LiDAR predict plant richness in southern pine forests.	C.T. Anderson, S.L. Dietz, S.M. Pokswinski, A.M. Jenkins, M.J. Kaeser, J.K. Hiers, B.D. Pelc	2021	Full Citation C.T. Anderson, S.L. Dietz, S.M. Pokswinski, A.M. Jenkins, M.J. Kaeser, J.K. Hiers, B.D. Pelc, 2021, Traditional field metrics and terrestrial LiDAR predict plant richness in southern pine forests, Forest Ecology and Management, at https://doi.org/10.1016/j.foreco.2021.119118.
Estimation of Plot-Level Burn Severity Using Terrestrial Laser Scanning.	Michael R. Gallagher, Aaron E. Maxwell, Luis Andrés Guillén, Alexis Everland, E. Louise Loudermilk, Nicholas S. Skowronski	2021	Full Citation Michael R. Gallagher, Aaron E. Maxwell, Luis Andrés Guillén, Alexis Everland, E. Louise Loudermilk, Nicholas S. Skowronski, 2021, Estimation of Plot-Level Burn Severity Using Terrestrial Laser Scanning, MDPI, at https://doi.org/10.3390/rs13204168.
Terrestrial laser scan metrics predict surface vegetation biomass and consumption in a frequently burned southeastern U.S. ecosystem.	E. Louise Loudermilk, Scott Pokswinski, Christie M. Hawley, Aaron Maxwell, Michael Gallagher, Nicholas Skowronski, Andrew T. Hudak, Chad Hoffman, J. Kevin Hiers	2023	Full Citation E. Louise Loudermilk, Scott Pokswinski, Christie M. Hawley, Aaron Maxwell, Michael Gallagher, Nicholas Skowronski, Andrew T. Hudak, Chad Hoffman, J. Kevin Hiers, 2023, Terrestrial laser scan metrics predict surface vegetation biomass and consumption in a frequently burned southeastern U.S. ecosystem, bioRxiv, at https://www.biorxiv.org/content/10.1101/2023.01.15.524107v1.

Title	Authors	Year	Citation
Semantic segmentation of archaeological features on public lands – Case study of historical cotton terraces within the Piedmont National Wildlife Refuge, GA, USA.	Gravel-Miguel, C., Snitker, G., Hirniak, J., Peck, K., Fetterhoff, A.	2024	Full Citation Gravel-Miguel, C., Snitker, G., Hirniak, J., Peck, K., Fetterhoff, A., 2024, Semantic segmentation of archaeological features on public lands – Case study of historical cotton terraces within the Piedmont National Wildlife Refuge, GA, USA, Manuscript in revision at Advances in Archaeological Practice.