# positions[].organizations[].parent[].label
College of Agriculture and Life Sciences

# overview
Dr. Sorin Popescu's academic interests focus on the application of remote sensing, in particular, and spatial sciences, in general, in natural resources assessment, monitoring, and management. His research interests include remote sensing applications in natural resources and forest sciences, assessment of forest fuels, forest volume and biomass, land use and land cover change, forest carbon sources and sinks, and global environmental change. He has developed various algorithms and software tools for multisensor data fusion and for processing LIDAR data for estimating forest biophysical parameters, such as stand density, tree height, crown diameter, volume, and biomass.

# keywords[]
30 Agricultural, Veterinary And Food Sciences

# keywords[]
30 Agricultural, Veterinary And Food Sciences

# keywords[]
30 Agricultural, Veterinary And Food Sciences

# keywords[]
30 Agricultural, Veterinary And Food Sciences

# keywords[]
Terrestrial Light Detection And Ranging (lidar)

# keywords[]
3709 Physical Geography And Environmental Geoscience

# keywords[]
12 Responsible Consumption And Production

# educationAndTraining[].organization.label
Virginia Tech - (Blacksburg, Virginia, United States)

# publications[].label
PhotonLabeler: An Inter-Disciplinary Platform for Visual Interpretation and Labeling of ICESat-2 Geolocated Photon Data

# publications[].label
Special Issue - Lidar Remote Sensing for Characterizing Forest Vegetation FOREWORD

# publications[].label
Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research.

# publications[].label
The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2): Science requirements, concept, and implementation

# publications[].label
Assessing the agreement of ICESat-2 terrain and canopy height with airborne lidar over US ecozones

# publications[].label
Fusion of small-footprint lidar and multispectral data to estimate plot-level volume and biomass in deciduous and pine forests in Virginia, USA

# publications[].label
Connecting the Dots: How Ecohydrological Connectivity Can Support Remote Sensing and Modeling to Inform Management of Woody Plant Encroachment

# publications[].label
Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass

# publications[].label
The use of remote sensing to develop a site history for restoration planning in an arid landscape

# publications[].label
SMALL FARM PONDS: OVERLOOKED FEATURES WITH IMPORTANT IMPACTS ON WATERSHED SEDIMENT TRANSPORT

# publications[].label
The Use of Terrestrial Laser Scanning (TLS) in Dune Ecosystems: The Lessons Learned

# publications[].publisher
Coastal Education and Research Foundation

# publications[].label
Volunteer Cotton Plant Detection In Corn Field With Deep Learning

# publications[].publisher
SPIE, the international society for optics and photonics

# publications[].label
A structured framework for identifying risks sources related to human resources in a 4.0 working environment perspective

# publications[].label
Lidar-based mapping of leaf area index and its use for validating GLOBCARBON satellite LAI product in a temperate forest of the southern USA

# publications[].label
Detecting volunteer cotton plants in a corn field with deep learning on UAV remote-sensing imagery

# publications[].label
Using lidar in determining forest canopy parameters

# publications[].label
A simplified method of predicting percent volume in log portions

# publications[].label
Computer-based synthetic data to assess the tree delineation algorithm from airborne LiDAR survey

# publications[].label
Using lidar-Derived fuel maps with farsite for fire behavoir modeling

# publications[].label
A scalar measure tracing tree species composition in space or time

# publications[].label
Fusion of lidar and multispectral data to quantify salt marsh carbon stocks

# publications[].label
An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning

# publications[].label
Using ICESat-2 to Estimate and Map Forest Aboveground Biomass: A First Example

# publications[].label
From LiDAR Waveforms to Hyper Point Clouds: A Novel Data Product to Characterize Vegetation Structure

# publications[].label
Estimating aboveground biomass and forest canopy cover with simulated ICESat-2 data

# publications[].label
Unoccupied aerial systems discovered overlooked loci capturing the variation of entire growing period in maize.

# publications[].label
Bayesian and Classical Machine Learning Methods: A Comparison for Tree Species Classification with LiDAR Waveform Signatures

# publications[].label
Classification of Tree Species in Overstorey Canopy of Subtropical Forest Using QuickBird Images.

# publications[].label
Satellite lidar vs. small footprint airborne lidar: Comparing the accuracy of aboveground biomass estimates and forest structure metrics at footprint level

# publications[].label
Use of synthetic images for training a deep learning model for weed detection and biomass estimation in cotton.

# publications[].label
Bayesian decomposition of full waveform LiDAR data with uncertainty analysis

# publications[].label
Old School and High Tech: A Comparison of Methods to Quantify Ashe Juniper Biomass as Fuel or Forage

# publications[].label
Annals of Forest Research: 80 years from first publishing

# publications[].publisher
Marin Dracea National Research-Development Institute in Forestry

# publications[].label
Forest Measurements with Airborne and Ground-Based Laser Scanning

# publications[].label
Regional Stem Volume Mapping: A Feasibility Assessment of Scaling Tree-Level Estimates

# publications[].label
Estimation of Biomass Components by Airborne Laser Scanning

# publications[].label
Woody Plant Encroachment: Evaluating Methodologies for Semiarid Woody Species Classification from Drone Images

# publications[].label
Bringing All Lidar Data Together: Investigations of Spatially Coincident Terrestrial, Airborne, and Satellite Lidar Data for Deriving Vegetation Structure Metrics

# publications[].label
A survey on the need for airborne lidar training

# publications[].publisher
American Society for Photogrammetry and Remote Sensing

# publications[].label
A study on the need for LiDAR training in academia and industry

# publications[].label
Estimating plot-level tree heights with lidar: local filtering with a canopy-height based variable window size

# publications[].label
ICESat-2 for Canopy Cover Estimation at Large-Scale on a Cloud-Based Platform.

# publications[].label
Assessment of Available Rangeland Woody Plant Biomass with a Terrestrial Lidar System

# publications[].publisher
American Society for Photogrammetry and Remote Sensing

# publications[].label
Mapping forest aboveground biomass with a simulated ICESat-2 vegetation canopy product and Landsat data

# publications[].label
Feasibility of Burned Area Mapping Based on ICESAT-2 Photon Counting Data

# publications[].label
Vegetation mapping of No Name Key, Florida using lidar and multispectral remote sensing

# publications[].label
Modeling Forest Aboveground Biomass and Volume Using Airborne LiDAR Metrics and Forest Inventory and Analysis Data in the Pacific Northwest

# publications[].label
Multitemporal field-based plant height estimation using 3D point clouds generated from small unmanned aerial systems high-resolution imagery

# publications[].label
Detecting and quantifying standing dead tree structural loss with reconstructed tree models using voxelized terrestrial lidar data

# publications[].label
Annals of Forest Research: ten years of international publication

# publications[].publisher
Marin Dracea National Research-Development Institute in Forestry

# publications[].label
Sensitivity analysis of fire behavior modeling with LIDAR-derived surface fuel maps

# publications[].label
Gold - A novel deconvolution algorithm with optimization for waveform LiDAR processing

# publications[].label
waveformlidar: An R Package for Waveform LiDAR Processing and Analysis

# publications[].label
Deriving forest canopy fuel parameters for loblolly pine forests in eastern Texas

# publications[].label
Automated Estimation of Standing Dead Tree Volume Using Voxelized Terrestrial Lidar Data

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass?

# publications[].label
Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection

# publications[].label
Multi-temporal terrestrial laser scanning for modeling tree biomass change

# publications[].label
A Methodological Framework for Mapping Canopy Cover Using ICESat-2 in the Southern USA

# publications[].label
Lidar remote sensing of forest biomass: A scale-invariant estimation approach using airborne lasers

# publications[].label
Synergy of ICESat-2 and Landsat for Mapping Forest Aboveground Biomass with Deep Learning

# publications[].label
Effects of Spatial Resolution on Burned Forest Classification With ICESat-2 Photon Counting Data

# publications[].label
Bayesian learning with Gaussian processes for supervised classification of hyperspectral data

# publications[].publisher
American Society for Photogrammetry and Remote Sensing

# publications[].label
Mapping surface fuel models using lidar and multispectral data fusion for fire behavior

# publications[].label
A comparison of multiple methods for mapping local-scale mesquite tree aboveground biomass with remotely sensed data

# publications[].label
Automated detection and measurement of individual sorghum panicles using density-based clustering of terrestrial lidar data

# publications[].label
An IPCC-Compliant Technique for Forest Carbon Stock Assessment Using Airborne LiDAR-Derived Tree Metrics and Competition Index

# publications[].label
Characterizing canopy cover with ICESat-2: A case study of southern forests in Texas and Alabama, USA

# publications[].label
A Deep Learning Semantic Segmentation-Based Approach for Field-Level Sorghum Panicle Counting

# publications[].label
Airborne lidar remote sensing applications, in non-forested short stature environments: a review

# publications[].publisher
Marin Dracea National Research-Development Institute in Forestry

# publications[].label
Seeing the trees in the forest: Using lidar and multispectral data fusion with local filtering and variable window size for estimating tree height

# publications[].publisher
American Society for Photogrammetry and Remote Sensing

# publications[].tags
12 Responsible Consumption and Production

# publications[].label
Allometry and structural volume change of standing dead southern pine trees using non-destructive terrestrial LiDAR

# publications[].label
Estimating biomass of individual pine trees using airborne lidar

# publications[].label
Aboveground biomass mapping by integrating ICESat-2, SENTINEL-1, SENTINEL-2, ALOS2/PALSAR2, and topographic information in Mediterranean forests

# publications[].label
Modeling Forest Aboveground Biomass and Volume Using Airborne LiDAR Metrics and Forest Inventory and Analysis Data in the Pacific Northwest

# publications[].label
The role of elevation, relative sea-level history and vegetation transition in determining carbon distribution in Spartina alterniflora dominated salt marshes

# publications[].label
Characterizing forest canopy structure with lidar composite metrics and machine learning

# publications[].label
Terrestrial Laser Scanning as an Effective Tool to Retrieve Tree Level Height, Crown Width, and Stem Diameter

# publications[].label
Measurement and Calibration of Plant-Height from Fixed-Wing UAV Images.

# publications[].label
Assessing forest fuel models using LIDAR remote sensing

# publications[].label
A voxel-based lidar method for estimating crown base height for deciduous and pine trees

# publications[].label
Unoccupied aerial system enabled functional modeling of maize height reveals dynamic expression of loci.

# publications[].label
Characterization of canopy fuels using ICESat/GLAS data

# publications[].label
Photon counting LiDAR: An adaptive ground and canopy height retrieval algorithm for ICESat-2 data

# publications[].label
Modeling the impact of sea level rise on endangered deer habitat.

# publications[].label
Regionalization of an Existing Global Forest Canopy Height Model for Forests of the Southern United States

# publications[].label
A novel reflectance-based model for evaluating chlorophyll concentrations of fresh and water-stressed leaves

# researcherOn[].label
ICESAT 2 SCIENCE DEFINITION TEAM: IMPROVING ESTIMATES OF FOREST BIOPHYSICAL PARAMETERS WITH AN INTEGRATED MULTI-SCALE APPROACHNOVERALL GOAL OF THIS PROPOSAL IS TO FURTHER ADVANCE THE KNOWLEDGE OF THE VEGETATION SCIENCE PRODUCTS RELATED TO THE ICESAT 2 MI

# researcherOn[].awardedBy.label
National Aeronautics and Space Administration - (Washington D.C., District of Columbia, United States)

# researcherOn[].label
Map/Geo-reference Critical Pecan and Other Carya Accessions at ARS Orchards in Somerville and Brownwood, Texas

# researcherOn[].awardedBy.label
Agricultural Research Service - (Washington D.C., District of Columbia, United States)

# researcherOn[].label
Dissertation Research: Biomass estimation and uncertainty analysis: Integrating Bayesian modeling and small-footprint waveform LiDAR data

# researcherOn[].awardedBy.label
National Science Foundation - (Arlington, Virginia, United States)

# researcherOn[].label
ICESat 2 Science Definition Team: Improving Estimates of Forest Biophysical Parameters with an Integrated Multi-Scale Approach

# researcherOn[].awardedBy.label
National Aeronautics and Space Administration - (Washington D.C., District of Columbia, United States)

# researcherOn[].label
Research Opportunities in Space and Earth Science 2011

# researcherOn[].awardedBy.label
National Aeronautics and Space Administration - (Washington D.C., District of Columbia, United States)

# researcherOn[].label
Using LiDAR to Develop a Climate-driven Model of the Disintegration and Decay of Trees Killed During a Severe Drought

# researcherOn[].awardedBy.label
National Aeronautics and Space Administration - (Washington D.C., District of Columbia, United States)

# researcherOn[].label
Aerial and Ground Phenotyping Analytical Tool Development for Plant Breeders Using the Maize G2F project

# researcherOn[].awardedBy.label
United States Department of Agriculture - (Washington D.C., District of Columbia, United States)

# researcherOn[].awardedBy.preferredLabel
USDA-National Institute of Food And Agriculture

# streetAddress
TEXAS A&M AGRILIFE RESEARCH; Ecosystem Science & Management; 2126 TAMU

# organizations[]
College of Agriculture and Life Sciences

# schools[]
College of Agriculture and Life Sciences

# etdChairOf[].label
Mutlu, Muge (2006-12). Mapping surface fuels using LIDAR and multispectral data fusion for fire behavior modeling. Master's Thesis.

# etdChairOf[].label
Zhao, Kaiguang (2008-08). Estimating forest structural characteristics with airborne lidar scanning and a near-real time profiling laser systems. Doctoral Dissertation.

# etdChairOf[].label
Griffin, Alicia Marie Rutledge (2006-12). Using LiDAR and normalized difference vegetation index to remotely determine LAI and percent canopy cover at varying scales. Master's Thesis.

# etdChairOf[].label
Stukey, Jared D. (2009-12). Deriving a Framework for Estimating Individual Tree Measurements with Lidar for Use in the TAMBEETLE Southern Pine Beetle Infestation Growth Model. Master's Thesis.

# etdChairOf[].label
Sheridan, Ryan D. (2011-05). Modeling Plot-Level Biomass and Volume Using Airborne and Terrestrial Lidar Measurements. Master's Thesis.

# etdChairOf[].label
Putman, Eric Bryan (2017-08). Quantifying Standing Dead Tree Volume and Structural Loss with Voxelized Terrestrial Lidar Data. Master's Thesis.

# etdChairOf[].label
Ku, Nian-Wei (2011-05). Assessing Available Woody Plant Biomass on Rangelands with Lidar and Multispectral Remote Sensing. Master's Thesis.

# etdChairOf[].label
Kulawardhana, Ranjani W (2013-12). Quantification of Salt Marsh Carbon Stocks: Integration of Remote Sensing Data and Techniques with Field Measurements. Doctoral Dissertation.

# etdChairOf[].label
Berg, Matthew (2014-05). Integrating Historical Imagery and Sediment Radioisotopes to Shed Light on Long-Term Rangeland Dynamics and Ecosystem Services at the Watershed Scale. Doctoral Dissertation.

# etdChairOf[].label
Mutlu, Muge (2010-12). Estimating Canopy Fuel Parameters with In-Situ and Remote Sensing Data. Doctoral Dissertation.

# etdChairOf[].label
Marcell, Wesley Tyler (2009-12). Systematic Sampling of Scanning Lidar Swaths. Master's Thesis.

# etdChairOf[].label
Srinivasan, Shruthi (2013-12). Multi-temporal Terrestrial Lidar for Estimating Individual Tree Dimensions and Biomass Change. Master's Thesis.

# websites[].label
Lidar Applications for the Study of Ecosystems with Remote Sensing