Above ground biomass estimation in an African tropical forest with lidar and hyperspectral data

Monitoring Forests: Parameters Estimation and Vegetation Classification with Multisource Remote Sensing Data

2 Acknowledgments 3 Table of contents 4 Chapter 1 Introduction 6 1.1 Thesis objectives, motivations and innovation 7 1.2 Materials and methods 15 1.2.1 The Sierra Nevada, U.S.A (study site 1) 16 1.2.2 The Alps, Bozen, Italy (study site 2) 16 1.2.3 Gola Rainforest National Park, Sierra Leone (study site 3) 17 1.3 Thesis outline 18 1.4 References 19 Chapter 2 – Remote sensing of forested landscap...

Estimation of tropical rain forest aboveground biomass with small-footprint lidar and hyperspectral sensors

Above-ground biomass estimation in closed canopy Neotropical forests using lidar remote sensing: factors affecting the generality of relationships

Aim Previous studies have developed strong, site-specific relationships between canopy metrics from lidar (light detecting and ranging) remote sensing data and forest structural characteristics such as above-ground biomass (AGBM), but the generality of these relationships is unknown. In this study, we examine the generality of relationships between lidar metrics and forest structural characteri...

Optimal Wavelength Selection on Hyperspectral Data with Fused Lasso for Biomass Estimation of Tropical Rain Forest

Above-ground biomass prediction of tropical rain forest using remote sensing data is of paramount importance to continuous largearea forest monitoring. Hyperspectral data can provide rich spectral information for the biomass prediction; however, the prediction accuracy is affected by a small-sample-size problem, which widely exists as overfitting in using high dimensional data where the number ...

Integration Ofwaveform Lidar and Hyperspectral Data to Estimate Structural Attributes of Tropical Forests

Estimation of forest structural attributes is important in biodiversity and global carbon cycle studies. These estimates can be used to predict important forest characteristics such as aboveground biomass (AGBM), which helps determine the amount of carbon in terrestrial vegetation pools. Traditional field sampling-based estimation methods are not only time consuming, expensive, and limited to l...