Texas A&M College of Agriculture and Life Sciences
Lidar Applications for the Study of Ecosystems with Remote Sensing Laboratory
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Publications

  1. Rana, P., Popescu, A. Tolvanen, B. Gautam, S. Srinivasan, and T. Tokola. 2023. Estimation of tropical forest aboveground biomass in Nepal using multiple remotely sensed data and deep learning, International Journal of Remote Sensing, 44:17, 5147-5171, https://doi.org/10.1080/01431161.2023.2240508
  2. Yadav, P.K.; Thomasson, J.A.; Hardin, R.; Searcy, S.W.; Braga-Neto, U.; Popescu, S.C.; Rodriguez, R., III; Martin, D.E.; Enciso, J.; Meza, K.; et al. 2023. Plastic Contaminant Detection in Aerial Imagery of Cotton Fields Using Deep Learning. Agriculture2023, 13, 1365. https://doi.org/10.3390/agriculture13071365
  3. E. Akturk, S.C. Popescu, and L. Malambo. 2023. ICESat-2 for Canopy Cover Estimation at Large-Scale on a Cloud-Based Platform. Sensors 2023, 23, 3394. https://doi.org/10.3390/s23073394
  4. Narine, L.L., S.C. Popescu, and L. Malambo. 2023. A Methodological Framework for Mapping Canopy Cover Using ICESat-2 in the Southern US. Remote Sensing 15, 1548. https://doi.org/10.3390/rs15061548
  5. Malambo, L., S.C. Popescu, J. Rakestraw, NW Ku, and T.A. Owoola, 2023. Regional Stem Volume Mapping: A Feasibility Assessment of Scaling Tree-Level Estimates. Forests 14, 506 https://doi.org/10.3390/f14030506
  6. Malambo, L., S. Popescu, and M. Liu. 2023. Landsat-Scale Regional Forest Canopy Height Mapping Using ICESat-2 Along-Track Heights: Case Study of Eastern Texas. Remote Sensing 15(1), 1. https://doi.org/10.3390/rs15010001
  7. Yadav, P.K., J.A. Thomasson, R. Hardin, S.W. Searcy, U. Braga-Neto, S.C. Popescu, D.E. Martin, R. Rodriguez, K. Meza, J. Enciso, J. Solorzano Diaz, T. Wang. 2023. Detecting volunteer cotton plants in a corn field with deep learning on UAV remote-sensing imagery. Computers and Electronics in Agriculture 204, 107551. https://doi.org/10.1016/j.compag.2022.107551
  8. Narine, L., L. Malambo, and S.C. Popescu. 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
  9. Guerra-Henández, L.L. Narine, A. Pascual, E. Gonzalez-Ferreiro, B. Botequim, L. Malambo, A. Neuenschwander, S.C. Popescu, and S. Godinho. 2022. Aboveground biomass mapping by integrating ICESat-2, SENTINEL-1, SENTINEL-2, ALOS2/PALSAR2, and topographic information in Mediterranean Forest. GIScience & Remote Sensing 59, 1509-1533. https://doi.org/10.1080/15481603.2022.2115599
  10. M. Liu and S.C. Popescu. 2022. Estimation of biomass burning emissions by integrating ICESat-2, Landsat 8, and Sentinel-1 data. Remote Sensing of Environment 280(2022). https://doi.org/10.1016/j.rse.2022.113172
  11. P. Varvia, L. Korhonen, A. Bruguiere, J. Toivonen, P. Packalen, M. Maltamo, S. Saarela, S.C. Popescu. 2022. How to Consider the Effects of Time of Day, Beam Strength, and Snow Cover in ICESat-2 based estimation of boreal forest biomass? Remote Sensing of Environment 280, 113174. https://doi.org/10.1016/j.rse.2022.113174
  12. Olariu, H., L. Malambo, S.C. Popescu, C. Virgil, and B.P. Wilcox, 2022. Woody Plant Encroachment: Evaluating Methodologies for Semiarid Woody Species Classification from Drone Images. Remote Sensing 14(7), 1665. https://doi.org/10.3390/rs14071665 
  13. B. Sapkota, S. Popescu, N. Rajan, R.G. Leon, C. Reberg-Horton, S. Mirsky, M.V. Bagavathiannan. 2022. Use of synthetic images for training a deep learning model for weed detection and biomass estimation in cotton. Scientific Reports 12, 19580. https://doi.org/10.1038/s41598-022-23399-z
  14. Simoneaux, B., C. Neely, A.M.H. Ibrahim, N. Rajan, and S. Popescu, 2022. Comparing Mechanical Harvest with Alternative Ground-Based Methods for Estimating Forage Yields in Cool-season Annual Grasses. Agrosystems, Geosciences & Environment 2022;5:e20250. https://doi.org/10.1002/agg2.20250 
  15. Yadav, P.K., J.A. Thomasson, S.W. Searcy, R. Hardin, U. Braga-Neto, S.C. Popescu, D.E. Martin, R. Rodriguez, K. Meza, J. Enciso, J. Solorzano Diaz, T. Wang. 2022. Assessing the performance of YOLOv5 algorithm for detecting volunteer cotton plants in corn fields at three different growth stages. Artificial Intelligence in Agriculture 6, 292-303. https://doi.org/10.1016/j.aiia.2022.11.005
  16. Malambo, L. and S.C. Popescu. 2021. Assessing the agreement of ICESat-2 terrain and canopy height with airborne lidar over US ecozones. Remote Sensing of the Environment 266: 112711 https://doi.org/10.1016/j.rse.2021.112711
  17. Liu, Meng, S.C. Popescu and L. Malambo. 2021. Effects of spatial resolution on burned forest classification with ICESat-2 photon counting Data.
    Frontiers in Remote Sensing 2:666251. https://doi.org/10.3389/frsen.2021.666251
  18. Ku, N.-W.; Popescu, S.; Eriksson, M., 2021. Regionalization of an Existing Global Forest Canopy Height Model for Forests of the Southern United States. Remote Sensing2021 (13) https://doi.org/10.3390/rs13091722
  19. Adak, A., Murray, S.C., Andersen, S.L., Popescu, S., Malambo, L., C. Romay, N. de Leon. 2021. Unoccupied Aerial Systems (UAS) Discovered Overlooked Loci Capturing the Variation of Entire Growing Period in Maize. The Plant Genome. https://doi.org/10.1002/tpg2.20102
  20. Malambo, , Popescu, S., 2020. PhotonLabeler: An Inter-Disciplinary Platform for Visual Interpretation and Labeling of ICESat-2 Geolocated Photon Data. Remote Sensing.  12 (19), 3168. https://doi.org/10.3390/rs12193168
  21. Kim, J., S.C. Popescu, R.R. Lopez, X.B. Wu, and N.J. Silvy.  2020.  Vegetation mapping of No Name Key, Florida using lidar and multispectral remote sensing.  International Journal of Remote Sensing. 41 (24): 9469-9506. https://doi.org/10.1080/01431161.2020.1800125 
  22. Narine, L.L., S.C. Popescu, and L. Malambo. 2020. Using ICESat-2 to Estimate and Map Forest Aboveground Biomass: A First Example. Remote Sensing12 (11), 1824. https://doi.org/10.3390/rs12111824
  23. Liu, S. Popescu, and L. Malambo. 2020. Feasibility of Burned Area Mapping Based on ICESat-2 Photon Counting Data. Remote Sensing 12(1), 24 https://doi.org/10.3390/rs12010024
  24. Klockow, P.A., B. Putman, J.G. Vogel, G.W. Moore, C.B. Edgard, and S.C. Popescu, 2020. Allometry and structural volume change of standing dead southern pine trees using non-destructive terrestrial LiDAR. Remote Sensing of the Environment241(2020) 111729. https://doi.org/10.1016/j.rse.2020.111729
  25. Andersen, S.L., Murray, S.C., Malambo, L., Chang, A., Popescu, S.,Cope, D., Jung, J., & Thomasson, J.A. (2020). Unoccupied aerial system enabled functional modeling of maize height reveals dynamic expression of loci. Plant Direct. 4. https://doi.org/10.1002/pld3.223 
  26. Malambo, S. Popescu, N.W. Ku, W. Rooney, T. Zhou, S. Moore, 2019. A Deep Learning Semantic Segmentation-Based Approach for Field-Level Sorghum Panicle Counting. Remote Sensing 11(24), 2939. https://doi.org/10.3390/rs11242939
  27. Narine, L. Popescu, S.C. and L. Malambo, 2019. Synergy of ICESat-2 and Landsat for Mapping Forest Aboveground Biomass with Deep Learning. Remote Sensing 11(12), 1503 https://doi.org/10.3390/rs11121503
  28. Zhou, T. and C. Popescu, 2019. waveformlidar: An R Package for Waveform LiDAR Processing and Analysis. Remote Sensing 11(21), 2552 https://doi.org/10.3390/rs11212552
  29. Tolleson, D. E.C. Rhodes, L. Malambo, J.P. Angerer, R.R. Redden, M.L. Treadwell, S.C. Popescu, 2019. Old School and High Tech: A Comparison of Methods to Quantify Ashe Juniper Biomass as Fuel or Forage. Rangelands 41(4) 159-168. https://doi.org/10.1016/j.rala.2019.06.001
  30. Ku, N.W. and C. Popescu, 2019. A Comparison of Multiple Methods for Mapping Local-Scale Mesquite Tree Aboveground Biomass with Remotely Sensed Data. Biomass and Bioenergy 122:270-279. https://doi.org/10.1016/j.biombioe.2019.01.045 
  31. Narine, L.L., C. Popescu, A. Neuenschwander, T. Zhou, S. Srinivasan, and K. Harbeck. 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
  32. Malambo, L., C. Popescu, D.W. Horne, A.N. Pugh, W.L. Rooney, 2019. Automated detection and measurement of individual sorghum panicles using density-based clustering of terrestrial lidar data. ISPRS Journal of Photogrammetry and Remote Sensing 149:1-13. https://doi.org/10.1016/j.isprsjprs.2018.12.015
  33. L. Anderson, S.C. Murray, L. Malambo, C. Ratcliff, S. Popescu, D. Cope, A. Chang, J. Jung, and J.A. Thomasson. 2019. Prediction of Maize Grain Yield before Maturity Using Improved Temporal Height Estimates of Unmanned Aerial Systems. The Plant Phenome Journal 2(1): 1-15.  https://doi.org/10.2135/tppj2019.02.0004
  34. Popescu, S.C., T. Zhou, R. Nelson, A. Neuenschwander, R. Sheridan, L. Narine, and K.M. Walsh, 2018. Photon counting LiDAR: an adaptive ground and canopy height retrieval algorithm for ICESat-2 data. Remote Sensing of the Environment 208: 154-170. https://doi.org/10.1016/j.rse.2018.02.019 
  35. Zhou, T., C. Popescu, L. Malambo, K. Zhao, K. Krause, 2018. From Lidar waveforms to hyper point clouds: a novel data product to characterize vegetation structure. Remote Sensing 10 (1949). http://dx.doi.org/10.3390/rs10121949
  36. Han, X., J.A. Thomasson, G.C. Bagnall, N.A. Pugh, D.W. Horne, W.L. Rooney, J. Jung, A. Chang, L. Malambo, C. Popescu, I.T. Gates, and D.A. Cope, 2018. Measurement and Calibration of Plant-Height from Fixed-Wing UAV Images. Sensors 18, (4092). http://dx.doi.org/10.3390/s18124092
  37. Putman, E.B. and S.C. Popescu, 2018. Automated Estimation of Standing Dead Tree Volume Using Vowelized Terrestrial Lidar Data. IEEE Transactions on Geoscience and Remote Sensing 56(11): 6484-6503. doi: 10.1109/TGRS.2018.2839088
  38. Putman, E.B., S.C. Popescu, M. Eriksson, T. Zhou, P. Klockow, J. Vogel, G. Moore, 2018. Detecting and Quantifying Standing Dead Tree Structural Loss with Reconstructed Tree Models Using Voxelized Terrestrial Lidar Data. Remote Sensing of the Environment 209: 52-65. https://doi.org/10.1016/j.rse.2018.02.028
  39. Strimbu, B.M., M. Paun, C. Montes, and C. Popescu, 2018. A Scalar Measure Tracing Tree Species Composition in Space or Time. Physica A 51: 285-292. https://doi.org/10.1016/j.physa.2018.07.036
  40. Pugh, N., D.W. Horne, S. Murray, G. Carvalho, L. Malambo, J. Jung, A. Chang, M. Maeda, C. Popescu, T. Chu, M. Starek, M. J. Brewer, G. Richardson, and W.L. Rooney, 2018. Temporal Estimates of Crop Growth in Sorghum and Maize Breeding Enabled by Unmanned Aerial Systems. The Plant Phenome Journal 1:170006  doi:10.2135/tppj2017.08.0006
  41. Zhou, T., C. Popescu, A.M. Lawing, M. Eriksson, B.M. Strimbu, and P.C. Burkner, 2018. Bayesian and Classical Machine Learning Methods: A Comparison for Tree Species Classification with LiDAR Waveform Signatures. Remote Sensing2018, 10(1), 39; doi:10.3390/rs10010039
  42. Malambo, S.C. Popescu, S.C. Murray, E. Putman, N.A. Pugh, D.W. Horne, G. Richardson, R. Sheridan, 3 B. Rooney, R. Avant, M. Vidrine, B. McCutchen, D. Baltensperger, M. Bishop, 2018. Multitemporal Field-based Plant Height Estimation using 3D Point Clouds Generated from Small Unmanned Aerial Systems High-resolution Imagery, International Journal of Applied Earth Observation and Geoinformation 64: 31-42. https://doi.org/10.1016/j.jag.2017.08.014
  43. Zhou, T. and C. Popescu, 2017. Bayesian decomposition of full waveform LiDAR data with uncertainty analysis. Remote Sensing of Environment 200(2017): 43-62. http://dx.doi.org/10.1016/j.rse.2017.08.012
  44. Markus, T., T. Neumann, A. Martino, W. Abdalati, K. Brunt, B. Csatho, S. Farrell, H. Fricker, A. Gardner, D. Harding, M. Jasinski, R. Kwok, L. Magruder, D. Lubin, S. Luthcke, J. Morison, R. Nelson, A. Neuenschwander, S. Palm, Popescu, C.K. Shum, B.E. Schutz, B. Smith, Y. Yang, J. Zwally, 2017. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2): Science requirements, concept, and implementation. Remote Sensing of Environment 190(2017): 260-273. http://dx.doi.org/10.1016/j.rse.2016.12.029
  45. Zhou, T., S.C. Popescu, K. Krause, R.D. Sheridan, and E. Putman, 2017. Gold – A novel deconvolution algorithm with optimization for waveform LiDAR processing. ISPRS Journal of Photogrammetry and Remote Sensing 129(2017): 131-150. http://dx.doi.org/10.1016/j.isprsjprs.2017.04.021
  46. Kulawardhana, R.W., C. Popescu, R.A. Feagin, 2017. Airborne lidar remote sensing applications in non-forested short stature environments: a review. Annals of Forest Research 60(1). 10.15287/afr.2016.719.
  47. L.C. Rubas-Leal, R.A. Washington-Allen, S.C. Popescu, and J.R. Conner, 2017. Estimation of Above-ground Biomass in Mt. Apo Natural Park in the Southern Philippines Using Terrestrial LiDAR System. Banwa B. 12:res005.
  48. Shi Y, J.A. Thomasson, S.C. Murray, N.A. Pugh, W.L. Rooney, S. Shafian, N. Rajan, G. Rouze, C.L.S. Morgan, H.L. Neely, A. Rana, M.V. Bagavathiannan, J. Henrickson, E. Bowden, J. Valasek, J. Olsenholler, M.P. Bishop, Sheridan, E.B. Putman, S. C. Popescu, T. Burks, D. Cope, A. Ibrahim, B.F. McCutchen, D.D. Baltensperger, R.V. Avant, Jr, M. Vidrine, C. Yang, 2016. Unmanned aerial vehicles for high-throughput phenotyping and agronomic research. PLoS ONE 11(7): e0159781. DOI:10.1371/journal.pone.0159781.
  49. Chinsu, L. *, G. Thomson, and C. Popescu, 2016. An IPCC-Compliant Technique for Forest Carbon Stock Assessment using Airborne LiDAR-derived Tree Metrics and Competition Index. Remote Sensing, 8, 528. DOI:10.3390/rs8060528
  50. Berg, M.D., C. Popescu, B.P. Wilcox, J.P. Angerer, E.C. Rhodes, J. McAlister, and W.E. Fox, 2016. Small Farm Ponds: Overlooked Features with Important Impacts on Watershed Sediment Transport. Journal of the American Water Resources Association (JAWRA) 52(1): 67-76. DOI: 10.1111/1752-1688.12369.
  51. Abdullah, M., R.A. Feagin, S. Whisenant, L. Al-Musawi, and S. Popescu, The use of remote sensing to develop site history for restoration planning in an arid landscape. Restoration Ecology 24(1): 91-99. doi: 10.1111/rec.12289
  52. Chinsu, L. C. Popescu, G. Thomson, K. Tsogt, and C. Chang, 2015. Classification of Tree Species in Overstorey Canopy of Subtropical Forest Using QuickBird Images. PLOS ONE 10(5): e0125554 1-23. doi:10.1371/journal.pone.0125554
  53. Kulawardhana, R.W., R.A. Feagin, C. Popescu, T.W. Boutton, K.M. Yeager and T.S. Bianchi, 2015. The role of elevation and relative sea level history in determining carbon distribution in Spartina alterniflora dominated salt marshes. Estuarine, Coastal and Shelf Science 154: 48-57; http://dx.doi.org/10.1016/j.ecss.2014.12.032
  54. Srinivasan, S., S.C. Popescu, M. Eriksson, D. Sheridan, and NW Ku, 2015. Terrestrial Laser Scanning as an Effective Tool to Retrieve Tree Level Height, Crown Width, and Stem Diameter. Remote Sensing 7: 1877-1896; doi: 10.3390/rs70201877
  55. Chinsu, L., C. Popescu, P.T. Chang, 2015. A Novel Reflectance-based Model for Evaluating Chlorophyll Concentration of Fresh and Water-Stressed Leaves. Biogeosciences 12, 49–66; doi:10.5194/bg-12-49-2015
  56. D. Sheridan, S.C. Popescu, D. Gatziolis, C.L.S. Morgan, and N.W. Ku, 2015. Modeling Forest Aboveground Biomass and Volume Using Airborne Lidar Metrics and Forest Inventory and Analysis Data in the Pacific Northwest. Remote Sensing 7(1): 229-255; http://dx.doi.org/10.3390/rs70100229
  57. W. Kulawardhana, S.C. Popescu, R.A. Feagin, 2014. Fusion of lidar and multispectral data to quantify salt marsh carbon stocks. Remote Sensing of Environment 154: 345-357. http://dx.doi.org/10.1016/j.rse.2013.10.036
  58. Srinivasan, S., C. Popescu, M. Eriksson, R. Sheridan, and N.W. Ku., 2014. Multi-Temporal Terrestrial Laser Scanning for Modeling Tree Biomass Change. Forest Ecology and Management 319: 304-317. http://dx.doi.org/10.1016/j.foreco.2014.01.038
  59. A. Feagin, A.M. Williams, S.C. Popescu, J. Stukey, R.A. Washington-Allen, 2014. The use of terrestrial lidar scanning (TLS) in dune ecosystems: the lessons learned. Journal of Coastal Research 30(1) 111–119. DOI: 10.2112/JCOASTRES-D-11-00223.
  60. Galvincio, J. D., H. A. Silva, and C, Popescu, 2014. Analysis of influence of evapotranspiration on rainfall in an atlantic forest using remote sensing data. Revista Brasileira de Geografia Física V. 07 N. 01 (2014) 017-033 (in English).
  61. Zhao, K., D. Valle, C. Popescu, X. Zhang, B. Mallik, 2013. Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection. Remote Sensing of Environment132: 102-119.  dx.doi.org/10.1016/j.rse.2012.12.026
  62. García, M,C. Popescu, D. Riaño, A. Neuenschwander, E. Chuvieco, M. Agca, and K. Zhao. 2012. Characterization of canopy fuels using ICESat/GLAS data. Remote Sensing of Environment 123: 81-89.
  63. Ku, N.W., C. Popescu, R. J. Ansley, and H. L. Perotto-Baldivieso, 2012. Assessment of Available Rangeland Woody Plant Biomass with a Terrestrial Lidar System. Photogrammetric Engineering & Remote Sensing 78(4): 349-361.
  64. Kaartinen, H., J. Hyyppä, X. Yu, M. Vastaranta, H. Hyyppä, A. Kukko, M. Holopainen, C. Heipke, M. Hirschmugl, F. Morsdorf, E. Næsset, J. Pitkänen, Popescu, S. Solberg, B. M. Wolf and J.C. Wu, 2012. An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning. Remote Sensing (4): 950-974.
  65. Popescu, S.C., Zhao, A. Neuenschwander, and C. Lin, 2011. Satellite lidar vs. small footprint airborne lidar: comparing the accuracy of aboveground biomass estimates and forest structure metrics at footprint level. Remote Sensing of Environment 115(11): 2786-2797. (the top 25 hottest article)
  66. Zhao, K.G., Popescu, S.C., Meng, and M. Agca, 2011. Characterizing forest canopy structure with composite lidar metrics and machine learning. Remote Sensing of Environment 115(8): 1978-1996. (the top 25 hottest article)
  67. Agca, M., Popescu, S.C., and C.W. Harper, 2011. Deriving Forest Canopy Fuel Parameters for Loblolly Pine Trees in Eastern Texas. Canadian Journal of Forest Research 41(8): 1618-1625.
  68. Wang, L., A.G. Birt, C.W. Lafon, D.M. Cairns, R.N. Coulson, M.D. Tchakerian, W. Xi, C. Popescu and J.M. Guldin, 2011. Computer-based synthetic data to assess the tree delineation algorithm from airborne LiDAR survey. GeoInformatica DOI 10.1007/s10707-011-0148-1.
  69. Popescu, S.C. and R.F. Nelson, 2011. Lidar Remote Sensing for Characterizing Forest Vegetation. Photogrammetric Engineering & Remote Sensing 77(3): 217-218.
  70. Zhao, K. and C. Popescu, 2009. Lidar-based mapping of leaf area index and its use for validating GLOBCARBON satellite LAI product in a temperate forest of the southern USA. Remote Sensing of Environment 113 (8): 1628–1645.
  71. Zhao, K., C. Popescu, & R.F. Nelson, 2009. Lidar remote sensing of forest biomass: A scale-invariant estimation approach using airborne lasers. Remote Sensing of Environment 113(1): 182-196.
  72. Mutlu, M., C. Popescu, and K. Zhao, 2008. Sensitivity analysis of fire behavior modeling with lidar-derived surface fuel maps. Forest Ecology and Management 256: 289-294.
  73. Zhao, K., C. Popescu, & X. Zhang, 2008. Bayesian Learning with Gaussian Processes for Supervised Classification of Hyperspectral Data, Photogrammetric Engineering & Remote Sensing 74(10): 1223-1234.
  74. Popescu, S.C. and Zhao, 2008. A voxel-based lidar method for assessing crown base height. Remote Sensing of Environment 112(3): 767-781.
  75. Mutlu, M., C. Popescu, C. Stripling, and T. Spencer, 2008. Assessing surface fuel models using LiDAR and multispectral data fusion. Remote Sensing of Environment 112(1): 274-285. (the top 25 hottest article)
  76. Zhao,, S. C. Popescu, & R. F. Nelson, 2008. Quantifying the Uncertainty for the Line-intercept Sampling Estimators of Canopy Cover, Journal of Forest Planning (Japanese Society of Forest Planning) 13: 195-205.
  77. Zhao K. and Popescu, S.C. Hierarchical watershed segmentation of canopy height model for multi-scale forest inventory. International Archives of Photogrammetry and Remote Sensing (IAPRS) Volume XXXVI, Part 3 / W52, 2007: 436-441.
  78. Popescu, S.C., 2007. Estimating biomass of individual pine trees using airborne lidar. Biomass & Bioenergy 31(9): 646-655.
  79. Hopkinson, C., C. Popescu, M. Flood, and R. Maher, 2007. A study on the need for LiDAR training. Photogrammetric Engineering & Remote Sensing 73 (5): 537-547.
  80. Popescu, S.C., R.H. Wynne and J.A. Scrivani, 2004. Fusion of small-footprint LiDAR and multispectral data to estimate plot-level volume and biomass in deciduous and pine forests in Virginia, U.S.A. Forest Science 50(4): p. 551 – 565.
  81. Popescu, S.C. and R.H. Wynne, 2004. Seeing the trees in the forest: using LiDAR and multispectral data fusion with local filtering and variable window size for estimating tree height. Photogrammetric Engineering & Remote Sensing 70(5): 589-604.
  82. Popescu, S.C., R.H. Wynne, and R.E. Nelson, 2003. Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass. Canadian Journal of Remote Sensing 29(5): 564-577.
  83. Oderwald, R.G. and C. Popescu, 2003. A simplified method of predicting percent volume in log portions. Southern Journal of Applied Forestry 27(3): 149-152.
  84. Popescu, S.C., R.H. Wynne and R.E. Nelson, 2002. Estimating plot-level tree heights with LiDAR: local filtering with a canopy-height based variable window. Computers and Electronics in Agriculture 37(1-3):71-95.
  85. Popescu, S.C., 1997. An introduction to the potential of GIS and DEMs for spatial analysis at landscape level. In: Forest Scenario Modelling for Ecosystem Management at Landscape Level. G.J. Nabuurs, T. Nuutinen, H. Bartelink and M. Korhonen (Eds): 137-146. 

Book Chapters

  1. Bishop, M.P., M.V. Bagavathiannan, D.A. Cope, D. Huo, S.C. Murray, J.A. Olsenholler, W.L. Rooney, J.A. Thomasson, J. Valasek, B.W. Young, A.M. Filippi, D.B. Hays, L. Malambo, C. Popescu, N. Rajan, V.P. Singh, B. McCutchen, B. Avant, and M. Vidrine, 2018. High Resolution UAS Imagery in Agricultural Research: Concepts, Issues and Research Directions. Chapter 1. High Resolution Remote Sensing. CRC Press.
  2. Popescu, S.C. and M.K. Hauglin, 2014. Estimation of biomass components by airborne laser scanning. In M. Maltamo et al. (eds.), Forestry Applications of Airborne Laser Scanning: Concepts and Case Studies, Series: Managing Forest Ecosystems 27, Springer Science. XII, 412 p. ISBN 978-94-017-8662-1.
  3. Popescu, S.C., 2011. Lidar Remote Sensing (Chapter 3). In Advances in Environmental Remote Sensing, Ed. Qihao Weng, 610p. CRC Press, Taylor and Francis Group. ISBN 9781420091755.

Editor of Proceedings (peer-reviewed and edited)

  1. Popescu S., R. Nelson, Zhao K., and Neuenschwander A. (Eds), 2009. Proceedings of Sivilaser 2009: the 9th International Conference on Lidar Applications for Assessing Forest Ecosystems. October, 2009. College Station, Texas, USA. (ISBN 978-1-61623-997-8).
  • Editor-reviewed articles
  1. Popescu, S.C. and M. Teodosiu. 2018. Annals of Forest Research: Ten Years of International Publication. Annals of Forest Research http://dx.doi.org/10.15287/afr.2018.1022
  2. Popescu, S.C., I.A. Biris, M. Teodosiu, O. Bouriaud, N. Olenici, and D. Mohor. 2014. Annals of Forest Research: 80 years from first publishing. Annals of Forest Research 57(1): 3-4.
  3. Popescu, S.C., P.J. Radtke, and R.H. Wynne, 2003. Forest measurements with airborne and ground-based laser scanning. Geospatial Solutions, Vol. 13, no. 8, pp. 18. (3rd place Fourth Annual Geospatial Solutions Applications Contest).