Biodiversity Mapping in a Tropical West African Forest with Airborne Hyperspectral Data

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The conservation and restoration of forest ecosystems require detailed knowledge of the native plant compositions. Here, we map global forest tree composition and assess the impacts of historical forest cover loss and climate change on trees. The global oc ...

The worsening of drought events with rising air temperature alters tree water relations causing severe hydraulic impairments and widespread forest mortality. Mixing tree species with contrasting hydraulic traits could reduce forest vulnerability to extreme ...

As air temperature and vapor pressure deficit (VPD) increase continuously, forests are losing more water through evapotranspiration, with large consequences for local and global hydrological cycles. In regions with high vegetation cover, soil warming can b ...

Patterns in nature arise from processes interacting across a continuum of spatial scales, where new relationships emerge at each level of investigation. These patterns are nested features encompassing fine-scale local patterns, such as topography and geolo ...

The rates of tropical deforestation remain high, resulting in carbon emissions, biodiversity loss, and impacts on local communities. To design effective policies to tackle this, it is necessary to know what the drivers behind deforestation are. Since drive ...

In sub-Mediterranean ecosystems, shade-tolerant broadleaf evergreens, especially the invasive Trachycarpus fortunei, are spreading uncontrollably in the forest understorey, impeding the regeneration of the native deciduous woody vegetation. Most invasive s ...

Enhancing tree diversity may be important to fostering resilience to drought-related climate extremes. So far, little attention has been given to whether tree diversity can increase the survival of trees and reduce its variability in young forest plantatio ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

Forest soils harbor hyper-diverse microbial communities which fundamentally regulate carbon and nutrient cycling across the globe. Directly testing hypotheses on how microbiome diversity is linked to forest carbon storage has been difficult, due to a lack ...

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Context. Gaia DR3 has offered the scientific community a remarkable dataset of approximately one million spectra acquired with the radial velocity spectrometer (RVS) in the calcium II triplet region, which is well suited to identify very metal-poor (VMP) s ...

We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be exp ...

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

A measurement of the Higgs boson (H) production via vector boson fusion (VBF) and its decay into a bottom quark-antiquark pair (b (b) over bar) is presented using proton-proton collision data recorded by the CMS experiment at root s = 13TeV and correspondi ...

Dataset corresponding to the following manuscript: Slagter, A., Setyadji, J.A., Vogt, E.L. et al. Nanoindentation Hardness and Modulus of Al2O3–SiO2–CaO and MnO–SiO2–FeO Inclusions in Iron. Metall Mater Trans A (2024). https://doi.org/10.1007/s11661-024-0 ...

Biodiversity Mapping in a Tropical West African Forest with Airborne Hyperspectral Data

Chattez avec Graph Search

Regional uniqueness of tree species composition and response to forest loss and climate change

From roots to canopy: Unraveling the influence of species diversity on tree water relations under warmer and drier climates

Soil warming alters tree water use and canopy stomatal conductance in a mixed subtropical forest

At what spatial scale does natural selection operate? Using multiscale frameworks to calibrate the effects of environmental factors across landscape continuums

Mapping drivers of tropical forest loss with satellite image time series and machine learning

Invasive palms have more efficient and prolonged CO2 assimilation compared to native sub-Mediterranean vegetation

Tree diversity reduces variability in sapling survival under drought

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Random matrix methods for high-dimensional machine learning models

Spectral Estimators for High-Dimensional Matrix Inference

Fungal community composition predicts forest carbon storage at a continental scale

Data and scripts for the RaFSIP scheme

Gaia's brightest very metal-poor (VMP) stars Metallicity catalogue of a thousand VMP stars from Gaia's radial velocity spectrometer spectra

A Pareto Dominance Principle for Data-Driven Optimization

Aggregating Spatial and Photometric Context for Photometric Stereo

Data-driven statistical optimization of a groundwater monitoring network

Measurement of the Higgs boson production via vector boson fusion and its decay into bottom quarks in proton-proton collisions at √s=13 TeV

Nanoindentation hardness and modulus of Al2O3-SiO2-CaO and MnO-SiO2-FeO inclusions in iron