Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping

Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California

(2020) Laura Duncanson et al.   REMOTE SENSING OF ENVIRONMENT

High-resolution mapping of forest canopy height using machine learning by coupling ICESat-2 LiDAR with Sentinel-1, Sentinel-2 and Landsat-8 data

(2020) Wang Li et al.   International Journal of Applied Earth Observation and Geoinformation

Monitoring Forest Loss in ALOS/PALSAR Time-Series with Superpixels

(2019) Charlie Marshak et al.   Remote Sensing

Estimating aboveground biomass and forest canopy cover with simulated ICESat-2 data

(2019) Lana L. Narine et al.   REMOTE SENSING OF ENVIRONMENT

Object-based random forest modelling of aboveground forest biomass outperforms a pixel-based approach in a heterogeneous and mountain tropical environment

(2019) Eduarda M.O. Silveira et al.   International Journal of Applied Earth Observation and Geoinformation

The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space

(2019) Shaun Quegan et al.   REMOTE SENSING OF ENVIRONMENT

Synergy of ICESat-2 and Landsat for Mapping Forest Aboveground Biomass with Deep Learning

(2019) Lana L. Narine et al.   Remote Sensing

Canopy and Terrain Height Retrievals with ICESat-2: A First Look

(2019) Amy L. Neuenschwander et al.   Remote Sensing

Forest biomass estimation over three distinct forest types using TanDEM-X InSAR data and simulated GEDI lidar data

(2019) Wenlu Qi et al.   REMOTE SENSING OF ENVIRONMENT

Quantification of sawgrass marsh aboveground biomass in the coastal Everglades using object-based ensemble analysis and Landsat data

(2018) Caiyun Zhang et al.   REMOTE SENSING OF ENVIRONMENT

An above-ground biomass map of African savannahs and woodlands at 25 m resolution derived from ALOS PALSAR

(2018) Alexandre Bouvet et al.   REMOTE SENSING OF ENVIRONMENT

Research Pathways of Forest Above-Ground Biomass Estimation Based on SAR Backscatter and Interferometric SAR Observations

(2018) Maurizio Santoro et al.   Remote Sensing

Generalized Hierarchical Model-Based Estimation for Aboveground Biomass Assessment Using GEDI and Landsat Data

(2018) Svetlana Saarela et al.   Remote Sensing

Improved forest height estimation by fusion of simulated GEDI Lidar data and TanDEM-X InSAR data

(2018) Wenlu Qi et al.   REMOTE SENSING OF ENVIRONMENT

The ATL08 land and vegetation product for the ICESat-2 Mission

(2018) Amy Neuenschwander et al.   REMOTE SENSING OF ENVIRONMENT

Measurement of fine-spatial-resolution 3D vegetation structure with airborne waveform lidar: Calibration and validation with voxelised terrestrial lidar

(2017) Steven Hancock et al.   REMOTE SENSING OF ENVIRONMENT

Coverage of high biomass forests by the ESA BIOMASS mission under defense restrictions

(2017) João M.B. Carreiras et al.   REMOTE SENSING OF ENVIRONMENT

Evaluating Site-Specific and Generic Spatial Models of Aboveground Forest Biomass Based on Landsat Time-Series and LiDAR Strip Samples in the Eastern USA

(2017) Ram Deo et al.   Remote Sensing

Radiometric Correction of Airborne Radar Images Over Forested Terrain With Topography

(2016) Marc Simard et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Landsat 8 and ICESat-2: Performance and potential synergies for quantifying dryland ecosystem vegetation cover and biomass

(2016) Nancy F. Glenn et al.   REMOTE SENSING OF ENVIRONMENT

Forest aboveground biomass mapping and estimation across multiple spatial scales using model-based inference

(2016) Qi Chen et al.   REMOTE SENSING OF ENVIRONMENT

Estimating Forest Aboveground Biomass by Combining Optical and SAR Data: A Case Study in Genhe, Inner Mongolia, China

(2016) Zhenfeng Shao et al.   SENSORS

Sensitivity of L-Band SAR Backscatter to Aboveground Biomass of Global Forests

(2016) Yifan Yu et al.   Remote Sensing

Data Fusion and Remote Sensing: An ever-growing relationship

(2016) Michael Schmitt et al.   IEEE Geoscience and Remote Sensing Magazine

The uncertainty of biomass estimates from modeled ICESat-2 returns across a boreal forest gradient

(2015) P.M. Montesano et al.   REMOTE SENSING OF ENVIRONMENT

yaImpute: AnRPackage forkNN Imputation

(2015) Nicholas L. Crookston et al.   Journal of Statistical Software

A Python-Based Open Source System for Geographic Object-Based Image Analysis (GEOBIA) Utilizing Raster Attribute Tables

(2014) Daniel Clewley et al.   Remote Sensing

Forest Variable Estimation Using Radargrammetric Processing of TerraSAR-X Images in Boreal Forests

(2014) Henrik Persson et al.   Remote Sensing

The Remote Sensing and GIS Software Library (RSGISLib)

(2013) Peter Bunting et al.   COMPUTERS & GEOSCIENCES

Assessing Performance of L- and P-Band Polarimetric Interferometric SAR Data in Estimating Boreal Forest Above-Ground Biomass

(2012) Maxim Neumann et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

A meta-analysis of terrestrial aboveground biomass estimation using lidar remote sensing

(2012) S.G. Zolkos et al.   REMOTE SENSING OF ENVIRONMENT

Estimation of forest above-ground biomass using multi-parameter remote sensing data over a cold and arid area

(2011) Xin Tian et al.   International Journal of Applied Earth Observation and Geoinformation

Forest biomass mapping from lidar and radar synergies

(2011) Guoqing Sun et al.   REMOTE SENSING OF ENVIRONMENT

A threshold insensitive method for locating the forest canopy top with waveform lidar

(2011) Steven Hancock et al.   REMOTE SENSING OF ENVIRONMENT

Impact of spatial variability of tropical forest structure on radar estimation of aboveground biomass

(2011) Sassan Saatchi et al.   REMOTE SENSING OF ENVIRONMENT

A global forest canopy height map from the Moderate Resolution Imaging Spectroradiometer and the Geoscience Laser Altimeter System

(2010) Michael A. Lefsky   GEOPHYSICAL RESEARCH LETTERS

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

LiDAR Utility for Natural Resource Managers

(2009) Andrew Thomas Hudak et al.   Remote Sensing