Academic Articles & Research Papers

Machine Learning Methods in the Environmental Sciences

Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and th...

Increased Atmospheric Aridity and Reduced Precipitation Drive the 2023 Extreme Wildfire Season in Canada

Abstract Canada experienced an unprecedented wildfire season in 2023. Here, we analyzed the exceptional scale, dominant driving factors, and potential impacts on permafrost of these wildfires using Moderate Resolution Imaging Spectroradiome...

COVID-19 Outbreak Prediction with Machine Learning

Abstract Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simpl...

Machine learning for ecosystem services

Recent developments in machine learning have expanded data-driven modelling (DDM) capabilities, allowing artificial intelligence to infer the behaviour of a system by computing and exploiting correlations between observed variables within i...

Precision water quality indices forecasting through an optimized hybrid SMW-LSSVM-R model enhanced by SATLDE and uncertainty analysis

Precise forecasting of water quality indices (WQI) is essential for safeguarding ecosystems, human health, and sustainable water resource management. This study presents an innovative approach for evaluating river Water Quality Indices usin...

Integrating BIM, Machine Learning, and PMBOK for Green Project Management in Saudi Arabia: A Framework for Energy Efficiency and Environmental Impact Reduction

This study introduces a comprehensive framework combining building information modeling (BIM), project management body of knowledge (PMBOK), and machine learning (ML) to optimize energy efficiency and reduce environmental impacts in Riyadh’...

Spatially contextualized analysis of energy use for commuting in India

India’s land transport GHG emissions are small in international comparison, but growing exponentially. Understanding of geographically-specific determinants of GHG emissions is crucial to devise low-carbon sustainable development strategies...

MATCHA, a novel regional hydroclimate-chemical reanalysis: System description and evaluation

We present MATCHA (Model for Atmospheric Transport and Chemistry in Asia), a 17-year (2003–2019) regional hydroclimate-chemical reanalysis for Asia (58–140° E, 4– 40° N) at 12 km resolution. MATCHA couples the Weather Research and Forecasti...

Machine Learning for Climate Precipitation Prediction Modeling over South America

Many natural disasters in South America are linked to meteorological phenomena. Therefore, forecasting and monitoring climatic events are fundamental issues for society and various sectors of the economy. In the last decades, machine learni...

Synergistic multi-altimeter for estimating water level in the coastal zone of Beibu Gulf using SEL, ALES + and BFAST algorithms

Accurately monitoring and predicting the large-scale dynamic changes of water levels in coastal zones is essential for its protection, restoration and sustainable development. However, there has been a challenge for achieving this goal usin...

Determinants of Tourism Demand Using Machine Learning Techniques

The purpose of the current study was to determine factors affecting tourism demand using machine learning techniques. The results of different linear regression and random forest models on both the train and test sets were compared using RM...

Using generalized random forests to characterize vulnerability to adverse health outcomes following wildfire smoke exposure in California

Background: As the health burden attributable to wildfire activity increases under climate change, it is crucial to determine which subgroups face heightened vulnerability to wildfire smoke. Marginalized communities may experience dispropor...

Global patterns of gully occurrence and their sensitivity to environmental changes

Gully formation is a significant driver of soil erosion and land degradation worldwide and often leads to important downstream impacts. Nonetheless, our understanding of the global patterns and the factors controlling this process remains l...

The role of artificial intelligence in achieving the Sustainable Development Goals

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals. Using a consensus-based expert elicitation proces...

Aligning artificial intelligence with climate change mitigation

Assessing climate and land use impacts on surface water yield using remote sensing and machine learning

Abstract Climate and land use changes are critical factors affecting watershed water yields, with significant implications for water resources at both local and regional levels. This study examined the combined effects of temporal and spati...

Artificial Intelligence for Enhancing Resilience

In an increasingly complex and unpredictable world, resilience-the ability to withstand and recover from adverse conditions is essential across various sectors. This research paper investigates the transformative potential of artificial int...

Happiness Index Determination by Analyzing Satellite Images for Urbanization

Waterbody identification from satellite images in an automated manner is one of the difficult tasks in the domain of Remote Sensing (RS). In recent years, several image processing approaches have been developed to process RGB or multispectr...

A Generative Super‐Resolution Model for Enhancing Tropical Cyclone Wind Field Intensity and Resolution

Abstract Extreme winds associated with tropical cyclones (TCs) can cause significant loss of life and economic damage globally, highlighting the need for accurate, high‐resolution modeling and forecasting for wind. However, due to their coa...

Spatio-temporal assessment of Toumeyella parvicornis spread in mediterranean coastal pine forests through sentinel-2 data

Mediterranean coastal pine forests offer vital ecological and cultural benefits but face threats from climate change, urbanization, and pests. Among invasive agents, Toumeyella parvicornis is a severe threat to Pinus pinea along Italy's coa...