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Developing accurate and reliable models for forest types mapping is critical to support efforts for halting deforestation and for biodiversity conservation (such as European Union Deforestation Regulation (EUDR)). This work introduces…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Yuchang Jiang , Maxim Neumann

As wildfires are expected to become more frequent and severe, improved prediction models are vital to mitigating risk and allocating resources. With remote sensing data, valuable spatiotemporal statistical models can be created and used for…

Machine Learning · Computer Science 2021-11-30 Alissa Chavalithumrong , Hyung-Jin Yoon , Petros Voulgaris

In many scientific fields, such as economics and neuroscience, we are often faced with nonstationary time series, and concerned with both finding causal relations and forecasting the values of variables of interest, both of which are…

Machine Learning · Computer Science 2019-08-01 Biwei Huang , Kun Zhang , Mingming Gong , Clark Glymour

We examine the household-specific effects of the introduction of Time-of-Use (TOU) electricity pricing schemes. Using a causal forest (Athey and Imbens, 2016; Wager and Athey, 2018; Athey et al., 2019), we consider the association between…

General Economics · Economics 2019-10-17 Eoghan O'Neill , Melvyn Weeks

Building fires pose a persistent threat to life, property, and infrastructure, emphasizing the need for advanced risk mitigation strategies. This study presents a data-driven framework analyzing U.S. fire risks by integrating over one…

Machine Learning · Computer Science 2025-04-01 Chenzhi Ma , Hongru Du , Shengzhi Luan , Ensheng Dong , Lauren M. Gardner , Thomas Gernay

We model the spatial dynamics of a forest stand by using a special class of spatio-temporal point processes, the sequential spatial point process, where the spatial dimension is parameterized and the time component is atomic. The sequential…

Wildfires pose a major threat to Portugal, with over 115,000 hectares burned annually on average during 1980-2024, and the country has faced devastating mega-fires such as those in 2017. Accurate forecasts of wildfire occurrence and burned…

Understanding causality is challenging and often complicated by changing causal relationships over time and across environments. Climate patterns, for example, shift over time with recurring seasonal trends, while also depending on…

Machine Learning · Computer Science 2025-01-20 Sarah Mameche , Lénaïg Cornanguer , Urmi Ninad , Jilles Vreeken

Across plant communities worldwide, fire regimes reflect a combination of climatic factors and plant characteristics. To shed new light on the complex relationships between plant characteristics and fire regimes, we developed a new…

Populations and Evolution · Quantitative Biology 2023-04-18 Marta Magnani , Rubén Díaz-Sierra , Luke Sweeney , Antonello Provenzale , Mara Baudena

The increasing frequency of catastrophic natural events, such as wildfires, calls for the development of rapid and automated wildfire detection systems. In this paper, we propose a wildfire identification solution to improve the accuracy of…

Image and Video Processing · Electrical Eng. & Systems 2023-08-08 Angelica Urbanelli , Luca Barco , Edoardo Arnaudo , Claudio Rossi

Climate change has increased the vulnerability of forests to insect-related damage, resulting in widespread forest loss in Central Europe and highlighting the need for effective, continuous monitoring systems. Remote sensing based forest…

Machine Learning · Computer Science 2025-12-10 Maximilian Kirsch , Jakob Wernicke , Pawan Datta , Christine Preisach

Forest canopies embody a dynamic set of ecological factors, acting as a pivotal interface between the Earth and its atmosphere. They are not only the result of an ecosystem's ability to maintain its inherent ecological processes,…

Computational Engineering, Finance, and Science · Computer Science 2024-10-15 Marco L. Della Vedova , Mattias Wahde

In recent years wildfires have caused havoc across the world, especially aggravated in certain regions, due to climate change. Remote sensing has become a powerful tool for monitoring fires, as well as for measuring their effects on…

Applications · Statistics 2021-05-24 Feliu Serra-Burriel , Pedro Delicado , Fernando M. Cucchietti

Wildfires pose a significant global threat to ecosystems worldwide, with California experiencing recurring fires due to various factors, including climate, topographical features, vegetation patterns, and human activities. This study aims…

Modern disease mapping draws upon a wealth of high resolution spatial data products reflecting environmental and/or socioeconomic factors as covariates, or `features', within a geostatistical framework to improve predictions of disease…

Applications · Statistics 2021-03-16 Rohan Arambepola , Peter Gething , Ewan Cameron

This paper presents a statistical analysis of air temperature data from 32 stations in Italy and the UK up to 2000 m above sea level, from 2002 to 2021. The data came from both highland and lowland areas, in order to evaluate both the…

Applications · Statistics 2024-09-27 Chalachew Muluken Liyew , Elvira Di Nardo , Rosa Meo , Stefano Ferraris

Earth's forests play an important role in the fight against climate change, and are in turn negatively affected by it. Effective monitoring of different tree species is essential to understanding and improving the health and biodiversity of…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Venkatesh Ramesh , Arthur Ouaknine , David Rolnick

Europe's contemporary political landscape has been shaped by massive shifts in recent decades caused by geopolitical upheavals such as Brexit and now, COVID-19. The way in which policy makers respond to the current pandemic could have large…

Social and Information Networks · Computer Science 2020-09-29 Josh Bullock , Justin E. Lane , Igor Mikloušić , LeRon Shults

Fine particulate matter, PM$_{2.5}$, has been documented to have adverse health effects and wildland fires are a major contributor to PM$_{2.5}$ air pollution in the US. Forecasters use numerical models to predict PM$_{2.5}$ concentrations…

Applications · Statistics 2019-09-30 Suman Majumder , Yawen Guan , Brian J. Reich , Susan O'Neill , Ana G. Rappold

Prevalence mapping in low resource settings is an increasingly important endeavor to guide policy making and to spatially and temporally characterize the burden of disease. We will focus our discussion on consideration of the complex design…

Methodology · Statistics 2016-08-15 Jon Wakefield , Daniel Simpson , Jessica Godwin
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