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- LiDAR Remote Sensing of Vegetation Biomass

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1006/anbo.1995.1015openalex-snapshot

Size-dependent Allometry of Tree Height, Diameter and Trunk-taper

inferredcites →https://doi.org/10.1007/978-1-4613-8363-5_3openalex-snapshot

Use of GIS for Estimating Potential and Actual Forest Biomass for Continental South and Southeast Asia

inferredcites →https://doi.org/10.1007/bf00546760openalex-snapshot

Use of forest inventories and geographic information systems to estimate biomass density of tropical forests: Application to tropical Africa

inferredcites →https://doi.org/10.1007/s00442-005-0100-xopenalex-snapshot

Tree allometry and improved estimation of carbon stocks and balance in tropical forests

inferredcites →https://doi.org/10.1007/s00442-011-2165-zopenalex-snapshot

A universal airborne LiDAR approach for tropical forest carbon mapping

inferredcites →https://doi.org/10.1007/s10021-008-9221-5openalex-snapshot

Environmental and Biotic Controls over Aboveground Biomass Throughout a Tropical Rain Forest

inferredcites →https://doi.org/10.1007/s10584-004-3155-5openalex-snapshot

Relating Radar Remote Sensing of Biomass to Modelling of Forest Carbon Budgets

inferredcites →https://doi.org/10.1007/s13595-011-0023-0openalex-snapshot

Synergistic use of very high-frequency radar and discrete-return lidar for estimating biomass in temperate hardwood and mixed forests

inferredcites →https://doi.org/10.1016/0034-4257(84)90031-2openalex-snapshot

Determining forest canopy characteristics using airborne laser data

inferredcites →https://doi.org/10.1016/0034-4257(88)90028-4openalex-snapshot

Estimating forest biomass and volume using airborne laser data

inferredcites →https://doi.org/10.1016/j.agrformet.2011.05.013openalex-snapshot

3D-laser scanning: A non-destructive method for studying above- ground biomass and growth of juvenile trees

inferredcites →https://doi.org/10.1016/j.agrformet.2012.05.019openalex-snapshot

Allometric equation choice impacts lidar-based forest biomass estimates: A case study from the Sierra National Forest, CA

inferredcites →https://doi.org/10.1016/j.biombioe.2007.06.022openalex-snapshot

Estimating biomass of individual pine trees using airborne lidar

inferredcites →https://doi.org/10.1016/j.foreco.2004.12.001openalex-snapshot

Estimating stand structure using discrete-return lidar: an example from low density, fire prone ponderosa pine forests

inferredcites →https://doi.org/10.1016/j.foreco.2006.12.018openalex-snapshot

Satellite-based estimation of biomass carbon stocks for northeast China's forests between 1982 and 1999

inferredcites →https://doi.org/10.1016/j.isprsjprs.2005.07.001openalex-snapshot

Estimating forest biomass using small footprint LiDAR data: An individual tree-based approach that incorporates training data

inferredcites →https://doi.org/10.1016/j.isprsjprs.2008.09.007openalex-snapshot

Full-waveform topographic lidar: State-of-the-art

inferredcites →https://doi.org/10.1016/j.isprsjprs.2009.04.002openalex-snapshot

3D segmentation of single trees exploiting full waveform LIDAR data

inferredcites →https://doi.org/10.1016/j.isprsjprs.2009.09.004openalex-snapshot

Assessment of terrain elevation derived from satellite laser altimetry over mountainous forest areas using airborne lidar data

inferredcites →https://doi.org/10.1016/j.isprsjprs.2010.09.001openalex-snapshot

Status and future of laser scanning, synthetic aperture radar and hyperspectral remote sensing data for forest biomass assessment

inferredcites →https://doi.org/10.1016/j.isprsjprs.2012.02.009openalex-snapshot

Using multi-frequency radar and discrete-return LiDAR measurements to estimate above-ground biomass and biomass components in a coastal temperate forest

inferredcites →https://doi.org/10.1016/j.jag.2012.01.010openalex-snapshot

Above ground biomass estimation across forest types at different degradation levels in Central Kalimantan using LiDAR data

inferredcites →https://doi.org/10.1016/j.jenvman.2006.09.021openalex-snapshot

Net primary productivity of China's terrestrial ecosystems from a process model driven by remote sensing

inferredcites →https://doi.org/10.1016/j.rse.2004.07.016openalex-snapshot

Quantifying forest above ground carbon content using LiDAR remote sensing

inferredcites →https://doi.org/10.1016/j.rse.2005.01.010openalex-snapshot

Geographic variability in lidar predictions of forest stand structure in the Pacific Northwest

inferredcites →https://doi.org/10.1016/j.rse.2005.03.005openalex-snapshot

Mapping forest structure for wildlife habitat analysis using waveform lidar: Validation of montane ecosystems

inferredcites →https://doi.org/10.1016/j.rse.2005.10.019openalex-snapshot

Empirical relationships between AIRSAR backscatter and LiDAR-derived forest biomass, Queensland, Australia

inferredcites →https://doi.org/10.1016/j.rse.2006.01.021openalex-snapshot

Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR/InSAR, ETM+, Quickbird) synergy

inferredcites →https://doi.org/10.1016/j.rse.2006.07.001openalex-snapshot

The use of waveform lidar to measure northern temperate mixed conifer and deciduous forest structure in New Hampshire

inferredcites →https://doi.org/10.1016/j.rse.2006.07.017openalex-snapshot

Exploring LiDAR–RaDAR synergy—predicting aboveground biomass in a southwestern ponderosa pine forest using LiDAR, SAR and InSAR

inferredcites →https://doi.org/10.1016/j.rse.2006.09.032openalex-snapshot

Remotely sensed measurements of forest structure and fuel loads in the Pinelands of New Jersey

inferredcites →https://doi.org/10.1016/j.rse.2006.11.014openalex-snapshot

Forest canopy height and carbon estimation at Monks Wood National Nature Reserve, UK, using dual-wavelength SAR interferometry

inferredcites →https://doi.org/10.1016/j.rse.2007.02.006openalex-snapshot

Investigating RaDAR–LiDAR synergy in a North Carolina pine forest

inferredcites →https://doi.org/10.1016/j.rse.2007.08.021openalex-snapshot

Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information

inferredcites →https://doi.org/10.1016/j.rse.2007.09.009openalex-snapshot

Integrating waveform lidar with hyperspectral imagery for inventory of a northern temperate forest

inferredcites →https://doi.org/10.1016/j.rse.2008.03.004openalex-snapshot

Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser

inferredcites →https://doi.org/10.1016/j.rse.2008.06.003openalex-snapshot

Regional aboveground forest biomass using airborne and spaceborne LiDAR in Québec

inferredcites →https://doi.org/10.1016/j.rse.2008.09.009openalex-snapshot

Lidar remote sensing of forest biomass: A scale-invariant estimation approach using airborne lasers

inferredcites →https://doi.org/10.1016/j.rse.2009.07.010openalex-snapshot

Distinguishing between live and dead standing tree biomass on the North Rim of Grand Canyon National Park, USA using small-footprint lidar data

inferredcites →https://doi.org/10.1016/j.rse.2010.03.019openalex-snapshot

Measuring forest structure and biomass in New England forest stands using Echidna ground-based lidar

inferredcites →https://doi.org/10.1016/j.rse.2010.08.027openalex-snapshot

Mapping biomass and stress in the Sierra Nevada using lidar and hyperspectral data fusion

inferredcites →https://doi.org/10.1016/j.rse.2010.08.029openalex-snapshot

Estimation of tropical rain forest aboveground biomass with small-footprint lidar and hyperspectral sensors

inferredcites →https://doi.org/10.1016/j.rse.2011.10.009openalex-snapshot

Airborne scanning LiDAR in a double sampling forest carbon inventory

inferredcites →https://doi.org/10.1016/j.rse.2012.01.015openalex-snapshot

Forest structure modeling with combined airborne hyperspectral and LiDAR data

inferredcites →https://doi.org/10.1016/j.rse.2012.01.021openalex-snapshot

Integration of airborne lidar and vegetation types derived from aerial photography for mapping aboveground live biomass

inferredcites →https://doi.org/10.1016/j.rse.2012.07.006openalex-snapshot

Forest biomass estimation from airborne LiDAR data using machine learning approaches

inferredcites →https://doi.org/10.1016/s0034-4257(00)00210-8openalex-snapshot

Laser altimeter canopy height profiles: methods and validation for closed-canopy, broadleaf forests

inferredcites →https://doi.org/10.1016/s0034-4257(01)00281-4openalex-snapshot

Estimation of tropical forest structural characteristics using large-footprint lidar

inferredcites →https://doi.org/10.1016/s0034-4257(03)00039-7openalex-snapshot

Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions

inferredcites →https://doi.org/10.1016/s0034-4257(03)00098-1openalex-snapshot

Modeling airborne laser scanning data for the spatial generation of critical forest parameters in fire behavior modeling

inferredcites →https://doi.org/10.1016/s0034-4257(96)00148-4openalex-snapshot

The use of imaging radars for ecological applications—A review

inferredcites →https://doi.org/10.1016/s0034-4257(96)00213-1openalex-snapshot

Separating the ground and airborne laser sampling phases to estimate tropical forest basal area, volume, and biomass

inferredcites →https://doi.org/10.1016/s0034-4257(98)00071-6openalex-snapshot

Surface Lidar Remote Sensing of Basal Area and Biomass in Deciduous Forests of Eastern Maryland, USA

inferredcites →https://doi.org/10.1016/s0034-4257(98)00091-1openalex-snapshot

Use of Large-Footprint Scanning Airborne Lidar To Estimate Forest Stand Characteristics in the Western Cascades of Oregon

inferredcites →https://doi.org/10.1016/s0034-4257(99)00052-8openalex-snapshot

Lidar Remote Sensing of the Canopy Structure and Biophysical Properties of Douglas-Fir Western Hemlock Forests

inferredcites →https://doi.org/10.1016/s0264-3707(02)00042-xopenalex-snapshot

ICESat's laser measurements of polar ice, atmosphere, ocean, and land

inferredcites →https://doi.org/10.1016/s0378-1127(97)00019-4openalex-snapshot

Biomass equations for sixty-five North American tree species

inferredcites →https://doi.org/10.1016/s0924-2716(99)00002-7openalex-snapshot

The Laser Vegetation Imaging Sensor: a medium-altitude, digitisation-only, airborne laser altimeter for mapping vegetation and topography

inferredcites →https://doi.org/10.1016/s1352-2310(00)00459-3openalex-snapshot

Biomass burning losses of carbon estimated from ecosystem modeling and satellite data analysis for the Brazilian Amazon region

inferredcites →https://doi.org/10.1021/es0259887openalex-snapshot

Accurate Estimation of Forest Carbon Stocks by 3-D Remote Sensing of Individual Trees

inferredcites →https://doi.org/10.1023/a:1005336724350openalex-snapshot

GREENHOUSE GASES FROM DEFORESTATION IN BRAZILIAN AMAZONIA: NET COMMITTED EMISSIONS

inferredcites →https://doi.org/10.1029/2005gl023971openalex-snapshot

Estimates of forest canopy height and aboveground biomass using ICESat

inferredcites →https://doi.org/10.1029/2008jd011674openalex-snapshot

Vegetation profiles in tropical forests from multibaseline interferometric synthetic aperture radar, field, and lidar measurements

inferredcites →https://doi.org/10.1029/2008jg000893openalex-snapshot

Regional forest growth rates measured by combining ICESat GLAS and Landsat data

inferredcites →https://doi.org/10.1029/2009jg000933openalex-snapshot

Estimation of tropical forest height and biomass dynamics using lidar remote sensing at La Selva, Costa Rica

inferredcites →https://doi.org/10.1029/2009jg000935openalex-snapshot

Importance of biomass in the global carbon cycle

inferredcites →https://doi.org/10.1029/2009jg000936openalex-snapshot

Assessing general relationships between aboveground biomass and vegetation structure parameters for improved carbon estimate from lidar remote sensing

inferredcites →https://doi.org/10.1029/2009jg000937openalex-snapshot

Linking models and data on vegetation structure

inferredcites →https://doi.org/10.1046/j.1365-2486.1998.00114.xopenalex-snapshot

State and change in carbon pools in the forests of tropical Africa

inferredcites →https://doi.org/10.1046/j.1365-2486.2001.00426.xopenalex-snapshot

The spatial distribution of forest biomass in the Brazilian Amazon: a comparison of estimates

inferredcites →https://doi.org/10.1046/j.1466-822x.2002.00303.xopenalex-snapshot

Lidar remote sensing of above‐ground biomass in three biomes

inferredcites →https://doi.org/10.1046/j.1466-822x.2003.00010.xopenalex-snapshot

Above‐ground biomass estimation in closed canopy Neotropical forests using lidar remote sensing: factors affecting the generality of relationships

inferredcites →https://doi.org/10.1071/wf07138openalex-snapshot

Ground-based LIDAR: a novel approach to quantify fine-scale fuelbed characteristics

inferredcites →https://doi.org/10.1073/pnas.1019576108openalex-snapshot

Benchmark map of forest carbon stocks in tropical regions across three continents

inferredcites →https://doi.org/10.1073/pnas.261555198openalex-snapshot

A large carbon sink in the woody biomass of Northern forests

inferredcites →https://doi.org/10.1080/01431160050029486openalex-snapshot

Technical note: Canopy height models and airborne lasers to estimate forest biomass: Two problems

inferredcites →https://doi.org/10.1080/01431160701736505openalex-snapshot

Mapping the height and above‐ground biomass of a mixed forest using lidar and stereo Ikonos images

inferredcites →https://doi.org/10.1080/01431160802158310openalex-snapshot

Improvement of the Edge‐based Morphological (EM) method for lidar data filtering

inferredcites →https://doi.org/10.1080/02827580410019490openalex-snapshot

Estimation of above ground forest biomass from airborne discrete return laser scanner data using canopy-based quantile estimators

inferredcites →https://doi.org/10.1080/02827580410019508openalex-snapshot

Measuring biomass and carbon in delaware using an airborne profiling LIDAR

inferredcites →https://doi.org/10.1080/02827580500373186openalex-snapshot

Weibull and percentile models for lidar-based estimation of basal area distribution

inferredcites →https://doi.org/10.1080/02827581.2011.624116openalex-snapshot

A fine-scale model for area-based predictions of tree-size-related attributes derived from LiDAR canopy heights

inferredcites →https://doi.org/10.1080/07038992.1986.10855092openalex-snapshot

Gross-Merchantable Timber Volume Estimation Using an Airborne Lidar System

inferredcites →https://doi.org/10.1080/10106049309354429openalex-snapshot

Geographical distributions of carbon in biomass and soils of tropical Asian forests

inferredcites →https://doi.org/10.1088/1748-9326/2/4/045023openalex-snapshot

Monitoring and estimating tropical forest carbon stocks: making REDD a reality

inferredcites →https://doi.org/10.1088/1748-9326/4/3/034009openalex-snapshot

Tropical forest carbon assessment: integrating satellite and airborne mapping approaches

inferredcites →https://doi.org/10.1093/forestscience/49.3.419openalex-snapshot

Estimation of Tree Height and Stem Volume on Plots Using Airborne Laser Scanning

inferredcites →https://doi.org/10.1093/forestscience/52.6.636openalex-snapshot

Forest Volume and Biomass Estimation Using Small-Footprint Lidar-Distributional Parameters on a Per-Segment Basis

inferredcites →https://doi.org/10.1093/jof/86.10.31openalex-snapshot

Using Airborne Lasers to Estimate Forest Canopy and Stand Characteristics

inferredcites →https://doi.org/10.1109/36.134089openalex-snapshot

Relating forest biomass to SAR data

inferredcites →https://doi.org/10.1109/36.718859openalex-snapshot

Polarimetric SAR interferometry

inferredcites →https://doi.org/10.1109/igarss.1994.399307openalex-snapshot

Optimization of an airborne laser altimeter for remote sensing of vegetation and tree canopies

inferredcites →https://doi.org/10.1109/igarss.2003.1294300openalex-snapshot

Height-biomass allometry in temperate forests performance accuracy of height-biomass allometry

inferredcites →https://doi.org/10.1109/jproc.2009.2034765openalex-snapshot

The ICESat-2 Laser Altimetry Mission

inferredcites →https://doi.org/10.1109/lgrs.2012.2210536openalex-snapshot

Synergistic Use of Satellite Laser Altimetry and Shuttle Radar Topography Mission DEM for Estimating Ground Elevation Over Mountainous Vegetated Areas

inferredcites →https://doi.org/10.1109/tgrs.2008.922032openalex-snapshot

Forest Height Inversion Using High-Resolution P-Band Pol-InSAR Data

inferredcites →https://doi.org/10.1109/tgrs.2009.2031101openalex-snapshot

Estimation of Forest Structure, Ground, and Canopy Layer Characteristics From Multibaseline Polarimetric Interferometric SAR Data

inferredcites →https://doi.org/10.1109/tgrs.2009.2031635openalex-snapshot

Model-Based Estimation of Forest Canopy Height in Red and Austrian Pine Stands Using Shuttle Radar Topography Mission and Ancillary Data: A Proof-of-Concept Study

inferredcites →https://doi.org/10.1111/j.0269-8463.2004.00830.xopenalex-snapshot

Is West, Brown and Enquist's model of allometric scaling mathematically correct and biologically relevant?

inferredcites →https://doi.org/10.1111/j.1365-2435.2005.01022.xopenalex-snapshot

Yes, West, Brown and Enquist"s model of allometric scaling is both mathematically correct and biologically relevant

inferredcites →https://doi.org/10.1111/j.1365-2486.2005.00955.xopenalex-snapshot

Aboveground Forest Biomass and the Global Carbon Balance

inferredcites →https://doi.org/10.1111/j.1365-2486.2006.01120.xopenalex-snapshot

The regional variation of aboveground live biomass in old‐growth Amazonian forests

inferredcites →https://doi.org/10.1111/j.1654-1103.2012.01471.xopenalex-snapshot

Tropical forest biomass estimation and the fallacy of misplaced concreteness

inferredcites →https://doi.org/10.1111/j.1744-7429.2007.00383.xopenalex-snapshot

Allometric Models for Predicting Aboveground Biomass in Two Widespread Woody Plants in Hawaii

inferredcites →https://doi.org/10.1126/science.247.4948.1322openalex-snapshot

Amazon Deforestation and Climate Change

inferredcites →https://doi.org/10.1139/x00-142openalex-snapshot

An evaluation of alternate remote sensing products for forest inventory, monitoring, and mapping of Douglas-fir forests in western Oregon

inferredcites →https://doi.org/10.1139/x05-112openalex-snapshot

Canadian national tree aboveground biomass equations

inferredcites →https://doi.org/10.1139/x05-230openalex-snapshot

Mapping stand-level forest biophysical variables for a mixedwood boreal forest using lidar: an examination of scanning density

inferredcites →https://doi.org/10.1139/x09-002openalex-snapshot

Estimating Quebec provincial forest resources using ICESat/GLAS

inferredcites →https://doi.org/10.1155/2012/436537openalex-snapshot

Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates

inferredcites →https://doi.org/10.14358/pers.69.3.267openalex-snapshot

A Portable Airborne Laser System for Forest Inventory

inferredcites →https://doi.org/10.14358/pers.72.8.923openalex-snapshot

Isolating Individual Trees in a Savanna Woodland Using Small Footprint Lidar Data

inferredcites →https://doi.org/10.14358/pers.73.12.1355openalex-snapshot

Estimating Basal Area and Stem Volume for Individual Trees from Lidar Data

inferredcites →https://doi.org/10.14358/pers.73.2.175openalex-snapshot

Filtering Airborne Laser Scanning Data with Morphological Methods

inferredcites →https://doi.org/10.14358/pers.78.4.349openalex-snapshot

Assessment of Available Rangeland Woody Plant Biomass with a Terrestrial Lidar System

inferredcites →https://doi.org/10.1890/02-5120openalex-snapshot

APPLICATION OF 1-M AND 4-M RESOLUTION SATELLITE DATA TO ECOLOGICAL STUDIES OF TROPICAL RAIN FORESTS

inferredcites →https://doi.org/10.1890/1051-0761(1999)009[0968:spoapa]2.0.co;2openalex-snapshot

SPATIAL PATTERNS OF ABOVEGROUND PRODUCTION AND MORTALITY OF WOODY BIOMASS FOR EASTERN U.S. FORESTS

inferredcites →https://doi.org/10.1890/1051-0761(2001)011[1174:baneft]2.0.co;2openalex-snapshot

BIOMASS AND NPP ESTIMATION FOR THE MID-ATLANTIC REGION (USA) USING PLOT-LEVEL FOREST INVENTORY DATA

inferredcites →https://doi.org/10.1890/1051-0761(2006)016[2356:rapvow]2.0.co;2openalex-snapshot

REGIONAL AND PHYLOGENETIC VARIATION OF WOOD DENSITY ACROSS 2456 NEOTROPICAL TREE SPECIES

inferredcites →https://doi.org/10.2307/1312677openalex-snapshot

Imaging Radar for Ecosystem Studies

inferredcites →https://doi.org/10.2307/1313568openalex-snapshot

Terrestrial Biomass and the Effects of Deforestation on the Global Carbon Cycle

inferredcites →https://doi.org/10.2737/ne-gtr-319openalex-snapshot

Comprehensive database of diameter-based biomass regressions for North American tree species

inferredcites →https://doi.org/10.2747/1548-1603.48.2.141openalex-snapshot

A Review of Remote Sensing of Forest Biomass and Biofuel: Options for Small-Area Applications

inferredcites →https://doi.org/10.3390/rs3091957openalex-snapshot

ICESat/GLAS Data as a Measurement Tool for Peatland Topography and Peat Swamp Forest Biomass in Kalimantan, Indonesia

inferredcites →https://doi.org/10.3390/s7081559openalex-snapshot

Airborne Laser Scanning of Forest Stem Volume in a Mountainous Environment

inferredcites →https://doi.org/10.5194/bg-9-179-2012openalex-snapshot

Mapping tropical forest biomass with radar and spaceborne LiDAR in Lopé National Park, Gabon: overcoming problems of high biomass and persistent cloud

inferredcites →https://doi.org/10.5589/m03-025openalex-snapshot

Lidar remote sensing of biophysical properties of tolerant northern hardwood forests

inferredcites →https://doi.org/10.5589/m10-037openalex-snapshot

Integration of GLAS and Landsat TM data for aboveground biomass estimation

inferredcites →https://doi.org/10.5589/m12-007openalex-snapshot

Fusing small-footprint waveform LiDAR and hyperspectral data for canopy-level species classification and herbaceous biomass modeling in savanna ecosystems

inferredcites →https://doi.org/10.5772/17479openalex-snapshot

Lidar Remote Sensing for Biomass Assessment

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4664227openalex-extracted

Incorporating Individual Tree Features into an Area-Based Approach for Estimating Forest Stock Volume

inferred← citeshttps://doi.org/10.1002/esp.4929openalex-snapshot

Emergent characteristics of rockfall inventories captured at a regional scale

inferred← citeshttps://doi.org/10.1016/j.agrformet.2018.04.005openalex-snapshot

Annual forest aboveground biomass changes mapped using ICESat/GLAS measurements, historical inventory data, and time-series optical and radar imagery for Guangdong province, China

inferred← citeshttps://doi.org/10.1016/j.asr.2021.03.035openalex-snapshot

Synergistic evaluation of Sentinel 1 and 2 for biomass estimation in a tropical forest of India

inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2014.01.001openalex-snapshot

Above ground biomass estimation in an African tropical forest with lidar and hyperspectral data

inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2015.05.007openalex-snapshot

Modeling aboveground tree woody biomass using national-scale allometric methods and airborne lidar

inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2017.03.013openalex-snapshot

Monitoring mangrove biomass change in Vietnam using SPOT images and an object-based approach combined with machine learning algorithms

inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2018.11.001openalex-snapshot

Estimating forest structural attributes using UAV-LiDAR data in Ginkgo plantations

inferred← citeshttps://doi.org/10.1016/j.rsase.2018.10.013openalex-snapshot

Comparison of different reflectance indices for vegetation analysis using Landsat-TM data

inferred← citeshttps://doi.org/10.1016/j.rse.2014.10.004openalex-snapshot

Generalizing predictive models of forest inventory attributes using an area-based approach with airborne LiDAR data

inferred← citeshttps://doi.org/10.1016/j.rse.2015.01.009openalex-snapshot

Uncertainty of remotely sensed aboveground biomass over an African tropical forest: Propagating errors from trees to plots to pixels

inferred← citeshttps://doi.org/10.1016/j.rse.2015.12.039openalex-snapshot

On the interest of penetration depth, canopy area and volume metrics to improve Lidar-based models of forest parameters

inferred← citeshttps://doi.org/10.1016/j.rse.2017.11.018openalex-snapshot

Linking lidar and forest modeling to assess biomass estimation across scales and disturbance states

inferred← citeshttps://doi.org/10.1016/j.rse.2018.04.005openalex-snapshot

A data-driven framework to identify and compare forest structure classes using LiDAR

inferred← citeshttps://doi.org/10.1016/j.tfp.2023.100436openalex-snapshot

Weight estimation models for commercial Pinus radiata wood in small felling stands based on UAV-LiDAR data

inferred← citeshttps://doi.org/10.1016/j.ufug.2023.128098openalex-snapshot

Utilizing LiDAR to quantify aboveground tree biomass within an urban university

inferred← citeshttps://doi.org/10.1080/01431161.2017.1338839openalex-snapshot

Comparison of UAS photogrammetric products for tree detection and characterization of coniferous stands

inferred← citeshttps://doi.org/10.1080/17538947.2014.990526openalex-snapshot

A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems

inferred← citeshttps://doi.org/10.1109/atsip.2016.7523138openalex-snapshot

Variational multiscale approach to LAI profile inversion based on LiDAR full waveform measurements

inferred← citeshttps://doi.org/10.1109/jstars.2015.2496358openalex-snapshot

Combined Use of Airborne LiDAR and Satellite GF-1 Data to Estimate Leaf Area Index, Height, and Aboveground Biomass of Maize During Peak Growing Season

inferred← citeshttps://doi.org/10.1109/lgrs.2015.2443553openalex-snapshot

Retrieval and Accuracy Assessment of Tree and Stand Parameters for Chinese Fir Plantation Using Terrestrial Laser Scanning

inferred← citeshttps://doi.org/10.1117/1.jrs.9.097696openalex-snapshot

Review of the use of remote sensing for biomass estimation to support renewable energy generation

inferred← citeshttps://doi.org/10.15666/aeer/1701_015031openalex-snapshot

BIOMASS ESTIMATION AND MAPPING OF CAN GIO MANGROVE BIOSPHERE RESERVE IN SOUTH OF VIET NAM USING ALOS-2 PALSAR-2 DATA

inferred← citeshttps://doi.org/10.26525/jtfs2017.29.4.465484openalex-snapshot

Modelling individual tree aboveground biomass using discrete return LiDAR in lowland dipterocarp forest of Malaysia

inferred← citeshttps://doi.org/10.3390/f14122388openalex-snapshot

Research on Estimating and Evaluating Subtropical Forest Carbon Stocks by Combining Multi-Payload High-Resolution Satellite Data

inferred← citeshttps://doi.org/10.3390/fractalfract5010014openalex-snapshot

Application of Fractal Dimension of Terrestrial Laser Point Cloud in Classification of Independent Trees

inferred← citeshttps://doi.org/10.3390/rs10040637openalex-snapshot

Reducing Uncertainty in Mapping of Mangrove Aboveground Biomass Using Airborne Discrete Return Lidar Data

inferred← citeshttps://doi.org/10.3390/rs11010097openalex-snapshot

Estimating Tree Volume Distributions in Subtropical Forests Using Airborne LiDAR Data

inferred← citeshttps://doi.org/10.3390/rs12071101openalex-snapshot

Stratification-Based Forest Aboveground Biomass Estimation in a Subtropical Region Using Airborne Lidar Data

inferred← citeshttps://doi.org/10.3390/rs14010235openalex-snapshot

Identifying Forest Structural Types along an Aridity Gradient in Peninsular Spain: Integrating Low-Density LiDAR, Forest Inventory, and Aridity Index

inferred← citeshttps://doi.org/10.3390/rs15051410openalex-snapshot

Forest Emissions Reduction Assessment Using Optical Satellite Imagery and Space LiDAR Fusion for Carbon Stock Estimation

inferred← citeshttps://doi.org/10.3390/rs16040705openalex-snapshot

UAV-LiDAR Integration with Sentinel-2 Enhances Precision in AGB Estimation for Bamboo Forests

inferred← citeshttps://doi.org/10.3390/rs17071271openalex-snapshot

An Improved Method for Single Tree Trunk Extraction Based on LiDAR Data

inferred← citeshttps://doi.org/10.3390/rs71115114openalex-snapshot

Increasing the Accuracy of Mapping Urban Forest Carbon Density by Combining Spatial Modeling and Spectral Unmixing Analysis

inferred← citeshttps://doi.org/10.3390/rs8010021openalex-snapshot

Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data

inferred← citeshttps://doi.org/10.3390/rs9010011openalex-snapshot

Estimating the Biomass of Maize with Hyperspectral and LiDAR Data

inferred← citeshttps://doi.org/10.3390/rs9010018openalex-snapshot

Potential of ALOS2 and NDVI to Estimate Forest Above-Ground Biomass, and Comparison with Lidar-Derived Estimates

inferred← citeshttps://doi.org/10.46754/jssm.2022.03.008openalex-snapshot

ESTIMATING ABOVEGROUND CARBON OF TEAK-BASED AGROFORESTRY SYSTEMS IN SABAH, MALAYSIA USING AIRBORNE LiDAR

inferred← citeshttps://doi.org/10.51200/bsj.v41i2.4448openalex-snapshot

QUANTIFYING ABOVEGROUND BIOMASS OVER 50-HA TROPICAL FOREST DYNAMIC PLOT IN PASOH, MALAYSIA USING LIDAR AND CENSUS DATA

inferred← citeshttps://doi.org/10.5772/intechopen.90324openalex-snapshot

Forest Biomass - From Trees to Energy

inferred← citeshttps://doi.org/10.7176/jetp/9-8-02openalex-snapshot

Above Ground Biomass Estimation Methods and Challenges: A Review

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