Airborne Lidar Sampling Strategies to Enhance Forest Aboveground Biomass Estimation from Landsat Imagery

Optimizing the Remote Detection of Tropical Rainforest Structure with Airborne Lidar: Leaf Area Profile Sensitivity to Pulse Density and Spatial Sampling

(2019) Danilo Roberti Alves de Almeida et al.   Remote Sensing

Estimating canopy structure and biomass in bamboo forests using airborne LiDAR data

(2019) Lin Cao et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

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

(2018) Wenjuan Shen et al.   AGRICULTURAL AND FOREST METEOROLOGY

Large-area mapping of Canadian boreal forest cover, height, biomass and other structural attributes using Landsat composites and lidar plots

(2018) Giona Matasci et al.   REMOTE SENSING OF ENVIRONMENT

Model-Assisted Estimation of Tropical Forest Biomass Change: A Comparison of Approaches

(2018) Nikolai Knapp et al.   Remote Sensing

Machine learning approaches for forest classification and change analysis using multi-temporal Landsat TM images over Huntington Wildlife Forest

(2018) Manqi Li et al.   GIScience & Remote Sensing

Tree crown complementarity links positive functional diversity and aboveground biomass along large-scale ecological gradients in tropical forests

(2018) Arshad Ali et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Allometric models to estimate above-ground biomass and carbon stocks in Rhizophora apiculata tropical managed mangrove forests (Southern Viet Nam)

(2018) Truong Van Vinh et al.   FOREST ECOLOGY AND MANAGEMENT

Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application

(2017) Stefanos Georganos et al.   GIScience & Remote Sensing

Assessing the suitability of data from Sentinel-1A and 2A for crop classification

(2017) Rei Sonobe et al.   GIScience & Remote Sensing

Evaluation of Goddard’s LiDAR, hyperspectral, and thermal data products for mapping urban land-cover types

(2017) Caiyun Zhang et al.   GIScience & Remote Sensing

A comparison of geographic datasets and field measurements to model soil carbon using random forests and stepwise regressions (British Columbia, Canada)

(2017) Heather J. Richardson et al.   GIScience & Remote Sensing

Examining effective use of data sources and modeling algorithms for improving biomass estimation in a moist tropical forest of the Brazilian Amazon

(2017) Yunyun Feng et al.   International Journal of Digital Earth

Interest of Integrating Spaceborne LiDAR Data to Improve the Estimation of Biomass in High Biomass Forested Areas

(2017) Mohammad Hajj et al.   Remote Sensing

Sampling effort and uncertainty in leaf litterfall mass and nutrient flux in northern hardwood forests

(2017) Yang Yang et al.   Ecosphere

Multisensor and Multispectral LiDAR Characterization and Classification of a Forest Environment

(2016) Christopher Hopkinson et al.   CANADIAN JOURNAL OF REMOTE SENSING

Integration of Landsat time series and field plots for forest productivity estimates in decision support models

(2016) Céline Boisvenue et al.   FOREST ECOLOGY AND MANAGEMENT

Effects of LiDAR point density, sampling size and height threshold on estimation accuracy of crop biophysical parameters

(2016) Shezhou Luo et al.   OPTICS EXPRESS

Large-scale estimation of aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data

(2016) Liviu Theodor Ene et al.   REMOTE SENSING OF ENVIRONMENT

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

(2016) Gaia Vaglio Laurin et al.   Remote Sensing

Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest Aboveground Biomass Estimation

(2016) Panpan Zhao et al.   Remote Sensing

Multisensor and Multispectral LiDAR Characterization and Classification of a Forest Environment

(2016) Christopher Hopkinson et al.   CANADIAN JOURNAL OF REMOTE SENSING

Mapping forests with Lidar provides flexible, accurate data with many uses

(2015) Maggi Kelly et al.   CALIFORNIA AGRICULTURE

Evaluation of ALOS/PALSAR L-Band Data for the Estimation of Eucalyptus Plantations Aboveground Biomass in Brazil

(2015) Nicolas Baghdadi et al.   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Geostatistical modeling using LiDAR-derived prior knowledge with SPOT-6 data to estimate temperate forest canopy cover and above-ground biomass via stratified random sampling

(2015) Wang Li et al.   International Journal of Applied Earth Observation and Geoinformation

Model-assisted estimation of growing stock volume using different combinations of LiDAR and Landsat data as auxiliary information

(2015) Svetlana Saarela et al.   REMOTE SENSING OF ENVIRONMENT

Airborne laser scanner-assisted estimation of aboveground biomass change in a temperate oak–pine forest

(2014) Nicholas S. Skowronski et al.   REMOTE SENSING OF ENVIRONMENT

Estimating above-ground biomass by fusion of LiDAR and multispectral data in subtropical woody plant communities in topographically complex terrain in North-eastern Australia

(2014) Sisira Ediriweera et al.   JOURNAL OF FORESTRY RESEARCH

Forest Biomass Mapping of Northeastern China Using GLAS and MODIS Data

(2013) Yuzhen Zhang et al.   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Integrating airborne LiDAR and space-borne radar via multivariate kriging to estimate above-ground biomass

(2013) Olivier W. Tsui et al.   REMOTE SENSING OF ENVIRONMENT

Subalpine zone delineation using LiDAR and Landsat imagery

(2012) Hans Ole Ørka et al.   REMOTE SENSING OF ENVIRONMENT

Forest biomass estimation from airborne LiDAR data using machine learning approaches

(2012) Colin J. Gleason et al.   REMOTE SENSING OF ENVIRONMENT

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

(2012) Qi Chen et al.   REMOTE SENSING OF ENVIRONMENT

Model-assisted estimation of biomass in a LiDAR sample survey in Hedmark County, NorwayThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time.

(2011) Timothy G. Gregoire et al.   CANADIAN JOURNAL OF FOREST RESEARCH

Update of forest inventory data with lidar and high spatial resolution satellite imagery

(2011) Thomas Hilker et al.   CANADIAN JOURNAL OF REMOTE SENSING

A GEOBIA framework to estimate forest parameters from lidar transects, Quickbird imagery and machine learning: A case study in Quebec, Canada

(2011) Gang Chen et al.   International Journal of Applied Earth Observation and Geoinformation

An airborne lidar sampling strategy to model forest canopy height from Quickbird imagery and GEOBIA

(2011) Gang Chen et al.   REMOTE SENSING OF ENVIRONMENT

Improved Biomass Estimation Using the Texture Parameters of Two High-Resolution Optical Sensors

(2010) Janet E. Nichol et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Fusion of LiDAR and imagery for estimating forest canopy fuels

(2010) Todd L. Erdody et al.   REMOTE SENSING OF ENVIRONMENT

Using satellite radar backscatter to predict above-ground woody biomass: A consistent relationship across four different African landscapes

(2009) E. T. A. Mitchard et al.   GEOPHYSICAL RESEARCH LETTERS

Regional aboveground forest biomass using airborne and spaceborne LiDAR in Québec

(2008) J BOUDREAU et al.   REMOTE SENSING OF ENVIRONMENT