Publications related to Tropical forest

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

Devis Tuia, Nina Marion Aurélia Van Tiel, Loïc Pellissier

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 ...

Nature Portfolio2024

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

Charlotte Grossiord, Christoph Bachofen

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 ...

Elsevier2024

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

Devis Tuia, Gaston Jean Lenczner, Jan Dirk Wegner, Jan Pisl, Marc Conrad Russwurm, Lloyd Haydn Hughes

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 ...

Iop Publishing Ltd2024

Unraveling ice multiplication in winter orographic clouds via in-situ observations, remote sensing and modeling

Athanasios Nenes, Alexis Berne, Satoshi Takahama, Georgia Sotiropoulou, Paraskevi Georgakaki, Romanos Foskinis, Kunfeng Gao, Anne-Claire Marie Billault--Roux

Recent years have shown that secondary ice production (SIP) is ubiquitous, affecting all clouds from polar to tropical regions. SIP is not described well in models and may explain biases in warm mixed-phase cloud ice content and structure. Through modeling ...

Nature Portfolio2024

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Devis Tuia, Gaston Jean Lenczner, Thiên-Anh Claris Nguyen, Marc Conrad Russwurm

Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

Elsevier Science Inc2024

Unraveling secondary ice production in winter orographic clouds through a synergy of in-situ observations, remote sensing and modeling

Athanasios Nenes, Alexis Berne, Satoshi Takahama, Georgia Sotiropoulou, Paraskevi Georgakaki, Romanos Foskinis, Kunfeng Gao, Anne-Claire Marie Billault--Roux

Recent years have shown that secondary ice production (SIP) is ubiquitous, affecting all clouds from polar to tropical regions. SIP is not described well in models and for this may vastly underpredict ice crystal number concentrations in warm mixed-phase c ...

2023

Semi-Supervised Deep Learning Representations in Earth Observation Based Forest Management

Devis Tuia, Marc Conrad Russwurm, Lloyd Haydn Hughes, Oleg Antropov, Sudipan Saha

In this study, we examine the potential of several self-supervised deep learning models in predicting forest attributes and detecting forest changes using ESA Sentinel-1 and Sentinel-2 images. The performance of the proposed deep learning models is compare ...

The Institute of Electrical and Electronics Engineers, Inc2023

Sunshine and a pinch of tropical soils: A natural, low-cost photo-Fenton variation for safer water, assisted by H2O2 or percabonate

César Pulgarin, Michaël Bensimon, Stefanos Giannakis, Thomas Guillaume, Jérémie Decker

Clean water is essential for human survival, but access to safe drinking water remains a challenge in resource -limited regions. Herein, we explored a low-cost but effective solution for water potabilization using natural iron sources from soils along with ...

ELSEVIER2023

Mapping forest in the Swiss Alps treeline ecotone with explainable deep learning

Devis Tuia, Benjamin Alexander Kellenberger, Thiên-Anh Claris Nguyen

Forest maps are essential to understand forest dynamics. Due to the increasing availability of remote sensing data and machine learning models like convolutional neural networks, forest maps can these days be created on large scales with high accuracy. Com ...

Elsevier2022

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Tropical forest

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

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

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

Unraveling ice multiplication in winter orographic clouds via in-situ observations, remote sensing and modeling

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Unraveling secondary ice production in winter orographic clouds through a synergy of in-situ observations, remote sensing and modeling

Semi-Supervised Deep Learning Representations in Earth Observation Based Forest Management

Sunshine and a pinch of tropical soils: A natural, low-cost photo-Fenton variation for safer water, assisted by H2O2 or percabonate

Mapping forest in the Swiss Alps treeline ecotone with explainable deep learning

Population structure and signals of local adaptation in Eugenia uniflora (Myrtaceae), a widely distributed species in the Atlantic Forest

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Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Population structure and signals of local adaptation in Eugenia uniflora (Myrtaceae), a widely distributed species in the Atlantic Forest

Mapping forest in the Swiss Alps treeline ecotone with explainable deep learning

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

Sunshine and a pinch of tropical soils: A natural, low-cost photo-Fenton variation for safer water, assisted by H2O2 or percabonate

Semi-Supervised Deep Learning Representations in Earth Observation Based Forest Management