Remote Sensing and LiDAR Applications

Non-destructive tree volume estimation using mobile laser scanning: Impact of the tree shape on measurement error.

This study evaluates the accuracy of mobile laser scanning for tree volume estimation, finding that tree shape has a limited impact on measurement error compared to scanning conditions and forest structure.

Simplifying complexity: the reliability of lidar-derived forest structural complexity metrics for conservation management

This study evaluates how resolution choices affect lidar-derived forest structural complexity metrics and their ecological interpretations in conservation management.

An AI-based and coding-free integration for forest Leaf Area Index calculation

This paper introduces a coding-free AI method for improving leaf area index (LAI) calculation from hemispherical images, showing higher consistency and reliability compared to existing tools.

Evaluation of LiDAR-based Canopy Trait Estimation in Midwestern Row Crops

This study evaluates LiDAR's ability to estimate canopy traits in corn and soybean, finding comparable LAI quality in corn but poor performance in soybean due to dense canopies, and accurate stand count in corn with faster data collection.

Tracking 3D forest density dynamics in a mixed temperate forestusing occlusion-aware voxel transmittance and consistent multitemporalUAV-LiDAR

This study uses UAV-LiDAR to track 3D forest density dynamics, revealing seasonal and inter-annual changes in tree structure and biomass.

SatCHM (Satellite Canopy Height Model): Leveraging deep learning for site-specific sub-meter canopy height predictions

SatCHM uses deep learning to predict canopy height from satellite data, achieving sub-meter resolution with limited resources.

Reconstructing coniferous tree crown shape from incomplete point clouds using deep learning

This paper develops a deep learning method to reconstruct coniferous tree crown shapes from incomplete point clouds, improving accuracy in structural metrics.

Small Area Estimation of Forest Volume Using Mixed Effects Random Forests and Multi-Source Remote Sensing Data

This paper compares two methods for estimating forest volume in small areas using remote sensing data, finding that Mixed-Effects Random Forests provide more accurate and stable predictions than Empirical Best Predictor.

A 0.6-meter resolution canopy height model for the contiguous United States

The paper develops NAIP-CHM, a high-resolution canopy height model using NAIP imagery and a U-Net model, achieving high accuracy for ecosystem monitoring.

High-resolution three-dimensional mapping of eelgrass (Zostera marina) habitat and blue carbon using drone-borne LiDAR

This study uses drone-borne LiDAR to quantify eelgrass habitat volume and carbon storage in a Norwegian bay, demonstrating its potential for high-resolution marine habitat monitoring.

Towards Scaling-Up Three-Dimensional Habitat Structural Measurements with Multi-Sensor Remote Sensing

This study evaluates the ability of multi-sensor remote sensing to estimate TLS-derived habitat structure across different ecosystems on La Reunion island, finding that Sentinel-2 provides the best alignment with TLS data, though structural complexity remains challenging to capture.

Modelling forest dynamics using integral projection models (IPMs) and repeat LiDAR

The paper integrates repeat LiDAR data with Integral Projection Models (IPMs) to model forest dynamics, revealing distinct growth responses of eucalypt trees to environmental factors.

Liana cutting accelerates tropical forest recovery at a fraction of the cost of tree planting

This study compares enrichment tree planting and liana cutting for tropical forest restoration, finding liana cutting accelerates canopy height recovery more rapidly and cheaply.

Trait diversity enhances biomass gains via canopy packing in old-growth but not in disturbed Amazon forests.

The study shows that trait diversity enhances biomass gains via canopy packing in old-growth Amazon forests but not in disturbed ones, due to reduced structural complexity after logging.

Tracking savanna vegetation structure in South Africa by extension of GEDI canopy metrics with Landsat, Sentinel-2, and PALSAR

This study extends GEDI canopy metrics to large-scale savanna monitoring using Landsat, Sentinel-2, and PALSAR data to track vegetation structure changes in South Africa.

Fast and Reliable: Evaluating Smartphone LiDAR App for Stem Diameter Measurement and Tree Mapping

This paper evaluates a smartphone LiDAR app for measuring tree stem diameter and mapping, finding it efficient and accurate with minor software limitations.

Carbon bias from grassy tree misclassification: revealing forest structural heterogeneity by integrating GEDI and Sentinel-2

The paper identifies carbon overestimation in bamboo-dominated forests using GEDI and Sentinel-2 data, revealing structural differences and improving carbon accounting.

The Global Canopy Atlas: analysis-ready maps of 3D structure for the world's woody ecosystems

The paper introduces the Global Canopy Atlas, a harmonized dataset of 3D canopy structure from ALS data, and demonstrates its applications in validating satellite maps, analyzing canopy gap patterns, and quantifying forest turnover.

Reliability of canopy photography for forest ecology and biodiversity studies

This study evaluates canopy photography techniques to assess forest structure and understory plant diversity, finding hemispherical photography better captures forest type differences and leaf clumping influences species distribution.

Mapping giant-tree density in the Amazon

The paper analyzes tall-tree density in the Amazon using LiDAR data and environmental metrics, finding that water availability and stable climate drive their distribution.

Canopy height model and NAIP imagery pairs across CONUS

The paper creates a large dataset of canopy height models paired with aerial imagery to improve large-scale CHM production.

Predicting woodland bird species habitat with multi-temporal and multisensor remote sensing data

This paper uses multi-temporal and multisensor remote sensing data to predict bird habitat for four species in the UK, finding that different data types and fusion methods yield varying accuracy for different species.

Tracking tree demography and forest dynamics at scale using remote sensing

The paper tracks tree growth, crown expansion, and mortality over nine years using remote sensing in Western Australia, finding size, competition, and topography influence demographic rates.

Quantifying Forest Biomass and Genetic Contribution using Light Detection and Ranging

This study uses LiDAR to measure tree traits and assess their heritability in larch trees, finding backpack LiDAR provides more accurate DBH estimates than UAV LiDAR.

Tree Surface Area Allometry

This study uses terrestrial laser scanning to measure tree surface areas, finding discrepancies between direct measurements and theoretical predictions, suggesting the need to revise allometric models.

Streamlining the alignment of UAV and TLS forest point clouds: an approach based on ground and tree stems

This paper presents a novel procedure for co-registering terrestrial and UAV point clouds in Mediterranean forests to improve geospatial data processing.

Gaining insight into the allometric scaling of trees by utilizing 3d reconstructed tree models - a SimpleForest study

The paper develops a method to estimate tree volume using 3D reconstructed models and compares it to harvested data, showing significant improvement in accuracy.