Publications

*graduate student advisee, +undergraduate student advisee or #Post-Doctoral/Research Associate advisee directly supervised on research related to publication

  1. *Gautam, A., Narine, L.L., Anderson, C.J., and Cristan, R. 2025. Synergistic use of ICESat-2 lidar data and Sentinel-2 imagery for assessing hurricane-driven forest changes. Environmental Monitoring and Assessment, 197, 1310, https://doi.org/10.1007/s10661-025-14749-1
  2. Badal D., Cristan R., Narine L.L., Kumar S., Rijal A., Parajuli M. 2025. Effectiveness of Unmanned Aerial Vehicle-Based LiDAR for Assessing the Impact of Catastrophic Windstorm Events on Timberland. Drones, 2025; 9(11):756, https://doi.org/10.3390/drones9110756
  3. Vatandaslar C, Boston K, Ucar Z, Narine LL, Madden M, and Akay AE. 2025. Precision Forestry Revisited. Remote Sensing, 17(20):3465. https://doi.org/10.3390/rs17203465
  4. *Singh, S., Narine, L.L., and Eckhardt, L. 2025. UAV-multispectral imaging and machine learning for Brown Spot Needle Blight severity assessment in southeastern US pine forests. Environmental Research Communications,7(9), https://doi.org/10.1088/2515-7620/ae06fb
  5. *Tiwari, K., Narine, L.L., Maggard, A., Daniel, M., Gallagher, T., Fan, Z., Singh, B., and Sandamali, J. 2025. Regional-scale forest aboveground biomass mapping using temporally consistent ICESat-2, Landsat, and field inventory data. PLoS One, 20(9), https://doi.org/10.1371/journal.pone.0330831
  6. Narine, L.L., and +Johnson, B. 2025. A spatially comprehensive canopy cover dataset derived from NASA’s ice, cloud and land elevation satellite-2 (ICESat-2) for the state of Alabama, USA. Data in Brief, 62, https://doi.org/10.1016/j.dib.2025.111902
  7. *Thapa, N., Narine, L.L., and Wilson, A.E. 2025. Forest Aboveground Biomass Estimation Using Airborne LiDAR: A Systematic Review and Meta-Analysis. Journal of Forestry, https://doi.org/10.1007/s44392-025-00029-w
  8. *Singh, S., Narine, L.L., Willoughby, J., and Eckhardt, L.G. 2025. Remote sensing-based detection of brown spot needle blight: a comprehensive review, and future directions. PeerJ, 13:e19407, https://doi.org/10.7717/peerj.19407
  9. *Sandamali, J., and Narine, L.L. 2025. A data-driven, cloud-based approach for forest aboveground biomass mapping using GEDI and other Earth observation data: An ecoregion-specific Investigation across the state of Alabama, USA. Geocarto International, 40(1), https://doi.org/10.1080/10106049.2025.2465446
  10. Willoughby, J.R., Lamka, G.F., Dunning, K.H., Narine, L., Belsare, A., and Sundaram, M. 2025. Using AI enhanced agent-based models to support management of wild populations. Landscape Ecology, 40(129), https://doi.org/10.1007/s10980-025-02149-2
  11. Mwema, T., Zohdy, S., Sundaram, M., Lepczyk, C.A., Narine, L., and Willoughby, J. 2024. A quantitative and systematic analysis of Anopheles stephensi bionomics and control approaches. Acta Tropica, 260, https://doi.org/10.1016/j.actatropica.2024.107431
  12. *Thapa, N., Narine, L.L., Fan, Z., Yang, S., and Tiwari, K. 2023. Detection of invasive plants using NAIP imagery and airborne LiDAR in coastal Alabama and Mississippi, USA. Annals of Forest Research, 66(1), https://doi.org/10.15287/afr.2023.2548
  13. Harder A.M., Sundaram M., Narine L., and Willoughby J.R. 2023. Remotely sensed environmental measurements detect decoupled processes driving population dynamics at contrasting scales. Ecology and Evolution, https://doi.org/10.1002/ece3.10358
  14. Rijal, A., Cristan, R., Gallagher, T., Narine, L.L., and Parajuli, M. 2023. Evaluating the feasibility and potential of unmanned aerial vehicles to monitor implementation of forestry best management practices in the coastal plain of the southeastern United States. Forest Ecology and Management, 545(1), https://doi.org/10.3390/rs15061548
  15. Narine, L.L., Popescu, S., Malambo, L. 2023. A Methodological Framework for Mapping Canopy Cover Using ICESat-2 in the Southern USA. Remote Sensing, 15(6), https://doi.org/10.3390/rs15061548
  16. Adjei, E., Li, W., Narine, L., and Zhang, Y. 2023. What Drives Land Use Change in the Southern U.S.? A Case Study of Alabama. Forests, 14(2), https://doi.org/10.3390/f14020171
  17. *Tiwari, K., and Narine, L.L 2022. A Comparison of Machine Learning and Geostatistical Approaches for Mapping Forest Canopy Height over the Southeastern US Using ICESat-2. Remote Sensing, 14(22), https://doi.org/10.3390/rs14225651
  18. Fan, Z., Yang, S., Kush, J.M., and Narine, L. 2022. Natural Regeneration Dynamics of Longleaf Pine Under Frequent, Low-Intensity Prescribed Fires in Southern Alabama, USA. Forest Science, fxac032, https://doi.org/10.1093/forsci/fxac032
  19. Guerra-Hernández, J., Narine, L.L., Pascual, A., Gonzalez-Ferreiro, E., Botequim, B., Malambo, L., Neuenschwander, A., Popescu, S.C., and Godinho, S. 2022. Aboveground biomass mapping by integrating ICESat-2, SENTINEL-1, SENTINEL-2, ALOS2/PALSAR2, and topographic information in Mediterranean forests. GIScience & Remote Sensing, 59(1), 1509-1533, https://doi.org/10.1080/15481603.2022.2115599
  20. #Shepard, N.T., Narine, L., Peng, Y., and Maggard, A. 2022. Climate Smart Forestry in the Southern United States. Forests, 13(9), https://doi.org/10.3390/f13091460
  21. Narine, L., Malambo, L., and Popescu, S. 2022. Characterizing canopy cover with ICESat-2: A case study of southern forests in Texas and Alabama, USA. Remote Sensing of Environment, 281, https://doi.org/10.1016/j.rse.2022.113242
  22. *Brown, S., Narine, L.L., and Gilbert, J. 2022. Using airborne lidar, multispectral imagery, and field inventory data to estimate basal area, volume, and aboveground biomass in heterogeneous mixed species forests: a case study in Southern Alabama. Remote Sensing, 14(11), https://doi.org/10.3390/rs14112708
  23. +Stack, V. and Narine, L.L. 2022. Sustainability at Auburn University: Assessing Rooftop Solar Energy Potential for Electricity Generation with Remote Sensing and GIS in a Southern US Campus. Sustainability, 14(2), https://doi.org/10.3390/su14020626
  24. Narine, L.L., Popescu, S., and Malambo, L. 2020. Using ICESat-2 to estimate and map forest aboveground biomass: A first example. Remote Sensing, 12(11), https://doi.org/10.3390/rs12111824
  25. Narine, L.L., Popescu, S., and Malambo, L. 2019. Synergy of ICESat-2 and Landsat for mapping forest aboveground biomass with deep learning. Remote Sensing, 11, 1-19, https://doi.org/10.3390/rs11121503
  26. Narine, L.L., Popescu, S., Zhou, T., Srinivasan, S., and Harbeck, K. 2019. Mapping forest aboveground biomass with a simulated ICESat-2 vegetation canopy product and Landsat data. Annals of Forest Research, 62(1), 1-17, https://doi.org/10.15287/afr.2018.1163
  27. Narine, L.L., Popescu, S., Neuenschwander, A., Zhou, T., Srinivasan, S., and Harbeck, K. 2019. Estimating aboveground biomass and forest canopy cover with simulated ICESat-2 data. Remote Sensing of Environment, 224: 1-11, https://doi.org/10.1016/j.rse.2019.01.037
  28. Popescu, S.C., Zhou, T., Nelson, R, Neuenschwander, A., Sheridan, R., Narine, L., and Walsh, K.M. 2018. Photon counting LiDAR: an adaptive ground and canopy height retrieval algorithm for ICESat-2 data. Remote Sensing of Environment, 208: 154-170, https://doi.org/10.1016/j.rse.2018.02.019
  29. Cai, Z., Narine, L.L., D’Amato, A., and Aguilar, F.X. 2016. Attitudinal and revenue effects on non-industrial private forest owners’ willingness-to-harvest timber and woody biomass. Forest Policy and Economics, 63:52-61, https://doi.org/10.1016/j.forpol.2015.11.007
  30. Aguilar, F.X., Daniel, M., and Narine, L.L. 2013. Opportunities and challenges to the supply of woody biomass for energy from Missouri nonindustrial privately owned forests. Journal of Forestry, 111(4):249-260, https://doi.org/10.5849/jof.13-009

Products

  1. Narine, L.L., and +Johnson, B. 2025. An ICESat-2-derived Canopy Cover Map for Alabama, USA. https://doi.org/10.17605/OSF.IO/VM68P
  2. *Tiwari, K. and Narine, L.L. 2025 . Regional-scale forest aboveground biomass mapping with ICESat-2 over the southeastern United States. https://doi.org/10.17605/OSF.IO/WHCSA
  3. *Sandamali, J., and Narine, L.L. 2025. An EO-based forest aboveground biomass map for Alabama. https://doi.org/10.17605/OSF.IO/T8WDQ
  4. *Tiwari, K., and Narine, L.L. 2025. An ICESat-2-derived forest canopy height map for the southeastern US for the year 2020. https://doi.org/10.17605/OSF.IO/JU9RX