Decision tree-based machine learning models for above-ground biomass estimation using multi-source remote sensing data and object-based image analysis

Modelling lidar-derived estimates of forest attributes over space and time: A review of approaches and future trends

(2021) Nicholas C. Coops et al.   REMOTE SENSING OF ENVIRONMENT

A Systematic Review of Landsat Data for Change Detection Applications: 50 Years of Monitoring the Earth

(2021) MohammadAli Hemati et al.   Remote Sensing

Estimation of Forest Biomass in Beijing (China) Using Multisource Remote Sensing and Forest Inventory Data

(2020) Yan Zhu et al.   Forests

Estimating Mangrove Above-Ground Biomass Using Extreme Gradient Boosting Decision Trees Algorithm with Fused Sentinel-2 and ALOS-2 PALSAR-2 Data in Can Gio Biosphere Reserve, Vietnam

(2020) Tien Dat Pham et al.   Remote Sensing

Image Segmentation and Object-Based Image Analysis for Environmental Monitoring: Recent Areas of Interest, Researchers’ Views on the Future Priorities

(2020) Brian Alan Johnson et al.   Remote Sensing

Google Earth Engine for geo-big data applications: A meta-analysis and systematic review

(2020) Haifa Tamiminia et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

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

Forest aboveground biomass estimation using Landsat 8 and Sentinel-1A data with machine learning algorithms

(2020) Yingchang Li et al.   Scientific Reports

A Review of Terrestrial Carbon Assessment Methods Using Geo-Spatial Technologies with Emphasis on Arid Lands

(2020) Salem Issa et al.   Remote Sensing

A carbon monitoring system for mapping regional, annual aboveground biomass across the northwestern USA

(2020) Andrew T Hudak et al.   Environmental Research Letters

Object-Oriented LULC Classification in Google Earth Engine Combining SNIC, GLCM, and Machine Learning Algorithms

(2020) Andrea Tassi et al.   Remote Sensing

Forest aboveground biomass estimation using machine learning regression algorithm in Yok Don National Park, Vietnam

(2019) An Thi Ngoc Dang et al.   Ecological Informatics

Estimate of winter-wheat above-ground biomass based on UAV ultrahigh-ground-resolution image textures and vegetation indices

(2019) Jibo Yue et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Automatic building extraction from high-resolution aerial images and LiDAR data using gated residual refinement network

(2019) Jianfeng Huang et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Ground Data are Essential for Biomass Remote Sensing Missions

(2019) Jérôme Chave et al.   SURVEYS IN GEOPHYSICS

High-resolution mapping of aboveground biomass for forest carbon monitoring system in the Tri-State region of Maryland, Pennsylvania and Delaware, USA

(2019) Wenli Huang et al.   Environmental Research Letters

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

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

(2019) Siqi Li et al.   Remote Sensing

Estimating aboveground biomass in subtropical forests of China by integrating multisource remote sensing and ground data

(2019) Rong Zhang et al.   REMOTE SENSING OF ENVIRONMENT

Influence of Variable Selection and Forest Type on Forest Aboveground Biomass Estimation Using Machine Learning Algorithms

(2019) Li et al.   Forests

Improving Forest Aboveground Biomass Estimation Using Landsat 8 Imagery by Incorporating Forest Crown Density as a Dummy Variable

(2019) Chao Li et al.   CANADIAN JOURNAL OF FOREST RESEARCH

OUP accepted manuscript

(2018)   FORESTRY

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

Integrating Airborne LiDAR and Optical Data to Estimate Forest Aboveground Biomass in Arid and Semi-Arid Regions of China

(2018) Luodan Cao et al.   Remote Sensing

Object-Based Mapping of Aboveground Biomass in Tropical Forests Using LiDAR and Very-High-Spatial-Resolution Satellite Data

(2018) Yasumasa Hirata et al.   Remote Sensing

SAR-Based Estimation of Above-Ground Biomass and Its Changes in Tropical Forests of Kalimantan Using L- and C-Band

(2018) Anna Berninger et al.   Remote Sensing

Implementation of the LandTrendr Algorithm on Google Earth Engine

(2018) Robert Kennedy et al.   Remote Sensing

Estimation of Forest Above-Ground Biomass by Geographically Weighted Regression and Machine Learning with Sentinel Imagery

(2018) Lin Chen et al.   Forests

The First Wetland Inventory Map of Newfoundland at a Spatial Resolution of 10 m Using Sentinel-1 and Sentinel-2 Data on the Google Earth Engine Cloud Computing Platform

(2018) Masoud Mahdianpari et al.   Remote Sensing

Stacked Sparse Autoencoder Modeling Using the Synergy of Airborne LiDAR and Satellite Optical and SAR Data to Map Forest Above-Ground Biomass

(2017) Zhenfeng Shao et al.   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

High-resolution precipitation mapping in a mountainous watershed: ground truth for evaluating uncertainty in a national precipitation dataset

(2017) Christopher Daly et al.   INTERNATIONAL JOURNAL OF CLIMATOLOGY

Accurate crop-type classification using multi-temporal optical and multi-polarization SAR data in an object-based image analysis framework

(2017) Bahram Salehi et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Google Earth Engine: Planetary-scale geospatial analysis for everyone

(2017) Noel Gorelick et al.   REMOTE SENSING OF ENVIRONMENT

The extent of forest in dryland biomes

(2017) Jean-François Bastin et al.   SCIENCE

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

(2017) Mohammad Hajj et al.   Remote Sensing

Understanding ‘saturation’ of radar signals over forests

(2017) Neha Joshi et al.   Scientific Reports

Allometric equations for integrating remote sensing imagery into forest monitoring programmes

(2016) Tommaso Jucker et al.   GLOBAL CHANGE BIOLOGY

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

(2016) Zhenfeng Shao et al.   SENSORS

Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data

(2016) Tianyu Hu et al.   Remote Sensing

Mapping Tree Canopy Cover and Aboveground Biomass in Sudano-Sahelian Woodlands Using Landsat 8 and Random Forest

(2015) Martin Karlson et al.   Remote Sensing

Estimates of Aboveground Biomass from Texture Analysis of Landsat Imagery

(2014) Katharine Kelsey et al.   Remote Sensing

How did we get here? An early history of forestry lidar1

(2013) Ross Nelson   CANADIAN JOURNAL OF REMOTE SENSING

Status and prospects for LiDAR remote sensing of forested ecosystems

(2013) M.A. Wulder et al.   CANADIAN JOURNAL OF REMOTE SENSING

A Combined Object- and Pixel-Based Image Analysis Framework for Urban Land Cover Classification of VHR Imagery

(2013) Bahram Salehi et al.   PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING

Using Landsat-derived disturbance and recovery history and lidar to map forest biomass dynamics

(2013) Dirk Pflugmacher et al.   REMOTE SENSING OF ENVIRONMENT

High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm

(2012) Onisimo Mutanga et al.   International Journal of Applied Earth Observation and Geoinformation

Estimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions

(2012) M.E.J. Cutler et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

LiDAR-Landsat data fusion for large-area assessment of urban land cover: Balancing spatial resolution, data volume and mapping accuracy

(2012) Kunwar K. Singh et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Using Landsat-derived disturbance history (1972–2010) to predict current forest structure

(2012) Dirk Pflugmacher 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

Object-Based Classification of Urban Areas Using VHR Imagery and Height Points Ancillary Data

(2012) Bahram Salehi et al.   Remote Sensing

Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data

(2012) Sandra Eckert   Remote Sensing

A simple technique for estimating above-ground biomass in short-rotation willow plantations

(2011) R.D. Hangs et al.   BIOMASS & BIOENERGY

Introduction to the GEOBIA 2010 special issue: From pixels to geographic objects in remote sensing image analysis

(2011) Elisabeth A. Addink et al.   International Journal of Applied Earth Observation and Geoinformation

Estimating above-ground biomass in young forests with airborne laser scanning

(2011) Erik Næsset   INTERNATIONAL JOURNAL OF REMOTE SENSING

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

(2011) Sorin C. Popescu et al.   REMOTE SENSING OF ENVIRONMENT

Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data

(2010) Mariano García et al.   REMOTE SENSING OF ENVIRONMENT

Improved estimates of forest vegetation structure and biomass with a LiDAR-optimized sampling design

(2009) Todd J. Hawbaker et al.   JOURNAL OF GEOPHYSICAL RESEARCH

Reducing Emissions from Deforestation and Degradation in Cameroon — Assessing costs and benefits

(2008) Valentin Bellassen et al.   ECOLOGICAL ECONOMICS

Protecting climate with forests

(2008) Robert B Jackson et al.   Environmental Research Letters

Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States

(2008) Christopher Daly et al.   INTERNATIONAL JOURNAL OF CLIMATOLOGY

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

(2008) B. St‐Onge et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

A broad-band leaf chlorophyll vegetation index at the canopy scale

(2008) M. Vincini et al.   PRECISION AGRICULTURE

Regional aboveground forest biomass using airborne and spaceborne LiDAR in Québec

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