A5020419497- Remote Sensing and LiDAR Applications
- Forest ecology and management
- Remote Sensing in Agriculture
- Forest Ecology and Biodiversity Studies
- Conservation, Biodiversity, and Resource Management
- Atmospheric and Environmental Gas Dynamics
- Ecology and Vegetation Dynamics Studies
- Geography and Environmental Studies
- Land Use and Ecosystem Services
- 3D Surveying and Cultural Heritage
- Plant Water Relations and Carbon Dynamics
- Plant and animal studies
- Environmental and biological studies
- Agricultural and Food Sciences
- Fire effects on ecosystems
- Species Distribution and Climate Change
- Tree Root and Stability Studies
- Economic and Environmental Valuation
- Oil Palm Production and Sustainability
- Soil erosion and sediment transport
- Agroforestry and silvopastoral systems
- Forest Biomass Utilization and Management
- Geochemistry and Geologic Mapping
- Forest Management and Policy
- Fish biology, ecology, and behavior
Universidade Federal dos Vales do Jequitinhonha e Mucuri
2016-2025
Universidade de São Paulo
2015-2024
Eucalyptus Research Center
2017
Governo do Estado de São Paulo
2017
Secretaria Regional do Ambiente e Recursos Naturais
2017
Forest Science and Research Institute
2016
Universidade Federal de Viçosa
2015
Secretaria de Agricultura e Abastecimento
2015
Swedish University of Agricultural Sciences
2015
Vale (Brazil)
2009
Airborne Laser Scanning (ALS) has been considered as a primary source to model the structure and function of forest canopy through indicators leaf area index (LAI) vertical profiles density (LAD). However, little is known about effects laser pulse grain size (horizontal binning resolution) point cloud on estimation LAD their associated LAIs. Our objective was determine optimal values for reliable stable estimates from ALS data obtained over dense tropical forest. Profiles were compared using...
Forest landscape restoration is a global priority to mitigate negative effects of climate change, conserve biodiversity, and ensure future sustainability forests, with international pledges concentrated in tropical forest regions. To hold efforts accountable monitor their outcomes, traditional strategies for monitoring tree cover increase by field surveys are falling short, because they labor-intensive costly. Meanwhile remote sensing approaches have not been able distinguish different types...
Abstract Secondary forests in the Amazon are important carbon sinks, biodiversity reservoirs, and connections between forest fragments. However, their regrowth is highly threatened by fire. Using airborne laser scanning (ALS), surveyed 2016 2018, we analyzed canopy metrics burned (fires occurred 2001 2018) unburned secondary across different successional stages ability to recover after We assessed maximum mean height, openness at 5 10 m, roughness, leaf area index (LAI) height volume (LAHV)...
Assessing the persistent impacts of fragmentation on aboveground structure tropical forests is essential to understanding consequences land use change for carbon storage and other ecosystem functions. We investigated influence edge distance fragment size canopy structure, woody biomass (AGB), AGB turnover in Biological Dynamics Forest Fragments Project (BDFFP) central Amazon, Brazil, after 22+ yr isolation, by combining variables collected with portable profiling lidar airborne laser...
Abstract Tall trees are key drivers of ecosystem processes in tropical forest, but the controls on distribution very tallest remain poorly understood. The recent discovery grove giant over 80 meters tall Amazon forest requires a reevaluation current thinking. We used high‐resolution airborne laser surveys to measure canopy height across 282,750 ha old‐growth and second‐growth forests randomly sampling entire Brazilian Amazon. investigated how resources disturbances shape maximum through...
Abstract Canopy gaps are openings in the forest canopy resulting from branch fall and tree mortality events. The geographical distribution of large may reflect underlying variation growth processes. However, a lack data at appropriate scale has limited our ability to study this relationship until now. We detected using unique LiDAR dataset consisting 650 transects randomly distributed across 2500 km 2 Brazilian Amazon. characterized size power law we explore exponent, α . evaluated how...
The Amazon Forest, the largest contiguous tropical forest in world, stores a significant fraction of carbon on land. Changes climate and land use affect total stocks, making it critical to continuously update revise best estimates for region, particularly considering changes dynamics. Forest inventory data cover only tiny coverage is not sufficient ensure reliable interpolation validation. This paper presents new above-ground biomass map Brazilian associated uncertainty both with resolution...
The Amazon forest contains globally important carbon stocks, but in recent years, atmospheric measurements suggest that it has been releasing more than absorbed because of deforestation and degradation. Accurately attributing the sources loss to degradation natural disturbances remains a challenge difficulty classifying simultaneously estimating changes. We used unique, randomized, repeated, very high-resolution airborne laser scanning survey provide direct, detailed, partitioning...
Tree stem form in native tropical forests is very irregular, posing a challenge to establishing taper equations that can accurately predict the diameter at any height along and subsequently merchantable volume. Artificial intelligence approaches be useful techniques minimizing estimation errors within complex variations of vegetation. We evaluated performance Random Forest® regression tree Neural Network procedures modelling taper. Diameters volume outside bark were compared traditional...
Abstract Drone‐based remote sensing is a promising new technology that combines the benefits of ground‐based and satellite‐derived forest monitoring by collecting fine‐scale data over relatively large areas in cost‐effective manner. Here, we explore potential GatorEye drone‐lidar system to monitor tropical succession canopy structural attributes including height, spatial heterogeneity, gap fraction, leaf area density (LAD) vertical distribution, Shannon index (an LAD), (LAI), understory LAI....
Monitoring reduced impact logging (RIL) activities in sustainably managed forest areas the Amazon is a costly and complex, yet crucial endeavor. One viable monitoring option use of airborne laser scanning (LiDAR), which enables estimating structure parameters over large timeframe with high accuracy. In this study, we propose assess applicability five indicators for RIL based on Light Detection Ranging (LiDAR) data acquisition under concession. Five Annual Production Units (APUs) were...
Rede neural artificial consiste em um conjunto de unidades que contêm funções matemáticas, unidas por pesos. As redes são capazes aprender, mediante modificação dos pesos sinápticos, e generalizar o aprendizado para outros arquivos desconhecidos. O projeto neurais é composto três etapas: pré-processamento, processamento e, fim, pós-processamento dados. Um problemas clássicos podem ser abordados a aproximação funções. Nesse grupo, pode-se incluir estimação do volume árvores. Foram utilizados...
This study aimed to develop ALS-based models for estimating stem, crown and aboveground biomass in three types of Mediterranean forest, based on low density ALS data. Two different modelling approaches were used: (i) linear with variable selection methods (Stepwise Selection [SS], Clustering/Exhaustive search [CE] Genetic Algorithm [GA]), (ii) previously Published Models (PM) applicable diverse forest. Results indicated more accurate estimations components pure Pinus pinea L. (rRMSE =...
The accurate prediction of forest above-ground biomass is nowadays key to implementing climate change mitigation policies, such as reducing emissions from deforestation and degradation. In this context, the coefficient determination (R2) widely used a means evaluating proportion variance in dependent variable explained by model. However, validity R2 for comparing observed versus predicted values has been challenged presence bias, instance remote sensing predictions biomass. We tested...
Light Detection and Ranging (LiDAR) remote sensing has been established as one of the most promising tools for large-scale forest monitoring mapping. Continuous advances in computational techniques, such machine learning algorithms, have increasingly improving our capability to model attributes accurately at high spatial temporal resolution. While there previous studies exploring use LiDAR algorithms inventory modeling, yet, no demonstrated combined impact sample size different modeling...
Abstract The future of tropical forests hinges on the balance between disturbance rates, which are expected to increase with climate change, and tree growth. Whereas growth is a slow process, events occur sporadically tend be short‐lived. This difference challenges forest monitoring achieve sufficient resolution capture growth, while covering necessary scale characterize rates. Airborne LiDAR time series can address this challenge by measuring landscape changes in canopy height at 1 m...
Abstract Tropical forests are increasingly threatened by deforestation and degradation, impacting carbon storage, climate regulations biodiversity. Restoring these ecosystems is crucial for environmental sustainability, yet monitoring efforts poses significant challenges. Secondary in a constant state of flux, with growth depending on multiple factors. Remote sensing technologies offer cost‐effective, scalable transferable solutions, advancing forest restoration towards more accurate,...