Evaluating the effectiveness of forest type stratification for aboveground biomass inference

No abstract is available for this paper.

• Publication year

  2025

• Venue

  International Journal of Applied Earth Observation and Geoinformation

• Publication date

  2025-09-01

• Fields of study

  Computer Science, Environmental Science

• Identifiers
  DOI 10.1016/j.jag.2025.104829
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Large live biomass carbon losses from droughts in the northern temperate ecosystems during 2016-2022

  2025cited by this paper
• Why ecosystem characteristics predicted from remotely sensed data are unbiased and biased at the same time – And how this affects applications

  2024cited by this paper
• A Separable Bootstrap Variance Estimation Algorithm for Hierarchical Model‐Based Inference of Forest Aboveground Biomass Using Data From NASA's GEDI and Landsat Missions

  2024cited by this paper
• Tree species classification in a typical natural secondary forest using UAV-borne LiDAR and hyperspectral data

  2023cited by this paper
• An approach to estimating forest biomass while quantifying estimate uncertainty and correcting bias in machine learning maps

  2023cited by this paper
• On the temporal mismatch between in-situ and satellite-derived spring phenology of European beech forests

  2023cited by this paper
• How many bootstrap replications are necessary for estimating remote sensing-assisted, model-based standard errors?

  2023cited by this paper
• Combining Sample Plot Stratification and Machine Learning Algorithms to Improve Forest Aboveground Carbon Density Estimation in Northeast China Using Airborne LiDAR Data

  2022cited by this paper
• Statistically rigorous, model-based inferences from maps

  2022cited by this paper
• A century of national forest inventories – informing past, present and future decisions

  2021cited by this paper
• Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory

  2020cited by this paper
• A Tutorial on Model-Assisted Estimation with Application to Forest Inventory

  2020cited by this paper
• Stratification-Based Forest Aboveground Biomass Estimation in a Subtropical Region Using Airborne Lidar Data

  2020cited by this paper
• Pervasive shifts in forest dynamics in a changing world

  2020cited by this paper
• Estimating the productive potential of five natural forest types in northeastern China

  2019cited by this paper
• Overselling overall map accuracy misinforms about research reliability

  2019cited by this paper
• Efficiency of post-stratification for a large-scale forest inventory—case Finnish NFI

  2019cited by this paper
• Double sampling for post-stratification in forest inventory

  2019cited by this paper
• Combining UAV and Sentinel-2 auxiliary data for forest growing stock volume estimation through hierarchical model-based inference

  2018cited by this paper
• Comparative Analysis of Modeling Algorithms for Forest Aboveground Biomass Estimation in a Subtropical Region

  2018cited by this paper
• Effects of temporally external auxiliary data on model-based inference

  2017cited by this paper
• Assessing 3D point clouds from aerial photographs for species-specific forest inventories

  2017cited by this paper
• Multivariate inference for forest inventories using auxiliary airborne laser scanning data

  2017cited by this paper
• Use of models in large-area forest surveys: comparing model-assisted, model-based and hybrid estimation

  2016cited by this paper
• Biomass resilience of Neotropical secondary forests

  2016cited by this paper
• Carbon sequestration potential of second-growth forest regeneration in the Latin American tropics

  2016cited by this paper
• Propagating uncertainty through individual tree volume model predictions to large-area volume estimates

  2016cited by this paper
• Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity

  2016cited by this paper
• Carbon storage, net primary production, and net ecosystem production in four major temperate forest types in northeastern China

  2016cited by this paper
• Statistical rigor in LiDAR-assisted estimation of aboveground forest biomass

  2016cited by this paper
• Review of studies on tree species classification from remotely sensed data

  2016cited by this paper
• Large-scale estimation of change in aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data

  2016cited by this paper
• Stratified aboveground forest biomass estimation by remote sensing data

  2015cited by this paper
• Generalizing predictive models of forest inventory attributes using an area-based approach with airborne LiDAR data

  2015cited by this paper
• Developing additive systems of biomass equations for nine hardwood species in Northeast China

  2015cited by this paper
• Effects of uncertainty in model predictions of individual tree volume on large area volume estimates

  2014cited by this paper
• A compatible system of biomass equations for three conifer species in Northeast, China

  2014cited by this paper
• Quantifying Uncertainty in Random Forests via Confidence Intervals and Hypothesis Tests

  2014cited by this paper
• Good practices for estimating area and assessing accuracy of land change

  2014cited by this paper
• Estimating spatial variation in Alberta forest biomass from a combination of forest inventory and remote sensing data

  2013cited by this paper
• Inference for lidar-assisted estimation of forest growing stock volume

  2013cited by this paper
• Image Texture Feature Extraction Using GLCM Approach

  2013cited by this paper
• The Performance of Random Forests in an Operational Setting for Large Area Sclerophyll Forest Classification

  2013cited by this paper
• Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation

  2013cited by this paper
• Assessing the accuracy of regional LiDAR-based biomass estimation using a simulation approach

  2012cited by this paper
• Post-stratified estimation of forest area and growing stock volume using lidar-based stratifications

  2012cited by this paper
• Geolocation Performance With Biased Range Measurements

  2012cited by this paper
• Model-based inference for biomass estimation in a LiDAR sample survey in Hedmark County, Norway

  2011cited by this paper
• Post-stratified estimation: with-in strata and total sample size recommendations

  2011cited by this paper
• Prediction of species specific forest inventory attributes using a nonparametric semi-individual tree crown approach based on fused airborne laser scanning and multispectral data

  2010cited by this paper
• Probability- and model-based approaches to inference for proportion forest using satellite imagery as ancillary data

  2010cited by this paper
• Regional aboveground forest biomass using airborne and spaceborne LiDAR in Québec.

  2008cited by this paper
• Controlled stratification for quantile estimation

  2008cited by this paper
• Forest inventory and stratified estimation: a cautionary note

  2008cited by this paper
• Remote sensing support for national forest inventories

  2007cited by this paper
• A model-based approach to estimating forest area

  2006cited by this paper
• The potential and challenge of remote sensing‐based biomass estimation

  2006cited by this paper
• Accuracy Assessment of FIA's Nationwide Biomass Mapping Products: Results From the North Central FIA Region

  2005cited by this paper
• Evaluating Classified MODIS Satellite Imagery as a Stratification Tool

  2004cited by this paper
• Inference for Superpopulation Parameters Using Sample Surveys

  2002cited by this paper
• Remote Sensing Precision Requirements For FIA Estimation

  2001cited by this paper
• Design-based and model-based inference in survey sampling: appreciating the difference

  1998cited by this paper
• Classification and Boundary Vagueness in Mapping Presettlement Forest Types

  1998cited by this paper
• Interpreting vegetation indices

  1991cited by this paper

• Mapping aboveground tree biomass and uncertainty using an upscaling approach: A case study of the larch forests in northeastern China using UAV laser scanning data

  2026cites this paper
• Bridging forestry practice and remote sensing: scaling up forest composition with integrated UAV LiDAR and hyperspectral data

  2026cites this paper
• Automatic tree-level based forest inventories retrieval via ultra-high resolution UAV images and deep learning

  2026cites this paper
• Evaluating Disturbance Regime Stratification for Aboveground Biomass Estimation in a Heterogeneous Forest Landscape: Insights from the Atewa Landscape, Ghana

  2026cites this paper
• Efficiency of Data Clustering for Stratification and Sampling in the Two-Phase ALS-Enhanced Forest Stock Inventory

  2025cites this paper