Preprints
Filtering by Subject: Computer Sciences
Natural forests of the world - a 2020 baseline for deforestation and degradation monitoring
Published: 2025-04-29
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Environmental Sciences, Geographic Information Sciences, Remote Sensing
Informed decisions to reduce deforestation, protect biodiversity, and curb carbon emissions require not just knowing where forests are, but understanding their composition. Identifying natural forests, which serve as critical biodiversity hotspots and major carbon sinks, is particularly valuable. We developed a novel global natural forest map for 2020 at 10 m resolution. This map can support [...]
Mapping Responsible AI Workflows for Geospatial Data Science: Developing the I-GUIDE Data Ethics Toolkit
Published: 2025-04-23
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Environmental Sciences, Geographic Information Sciences, Geography, Library and Information Science, Sustainability
AI workflows in geospatial data science promise substantial societal benefits yet pose persistent challenges of ethical risk, transparency, and reproducibility. Current guidance, ranging from high‑level principles to isolated documentation templates, remains difficult to translate into day‑to‑day research practice, especially for teams operating under tight deadlines. This paper reports the [...]
Leveraging Automated Machine Learning (AutoML) for Urban Climate Emulation
Published: 2025-04-23
Subjects: Computer Sciences, Earth Sciences, Environmental Engineering, Environmental Sciences
Urban climate models are critical for understanding and addressing the impacts of urban climate change. Yet, process-based urban climate models face limitations of high-entry barriers and substantial computing resource consumption, prompting the development of data-driven methods. However, the recently developed urban climate emulators, being location-dependent, are less scalable and may overlook [...]
Three times accelerated glacier area loss in Svalbard revealed by deep learning
Published: 2025-03-22
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Glaciology, Physical Sciences and Mathematics
The rapid warming in polar regions highlights the need to monitor climate change impacts such as glacier retreat and related global sea level rise. Glacier area is an essential climate variable but its tracking is complicated by the labour-intensive manual digitisation of satellite imagery. Here we introduce ICEmapper, a deep learning model that maps glacier outlines from Sentinel-1 time series [...]
From Magma Chambers to Magma Oceans: A Unified Model for the Thermo-chemical-mechanical Evolution of Magma Bodies
Published: 2025-02-06
Subjects: Applied Mathematics, Computer Sciences, Earth Sciences, Physical Sciences and Mathematics, Planetary Sciences
Magma bodies play a critical role in Earth's geological evolution, influencing volcanic activity, crustal differentiation, and planetary-scale processes. Understanding their thermo-chemical and mechanical evolution requires models that integrate fluid dynamics, phase changes, and chemical transport. This study presents a new numerical model that couples these processes using a multi-phase, [...]
Global drivers of forest loss at 1 km resolution
Published: 2024-12-20
Subjects: Computer Sciences, Environmental Sciences, Geographic Information Sciences, Remote Sensing
Forests are in decline worldwide due to human activities such as agricultural expansion, urbanization, and mineral extraction. Forest loss due to generally temporary causes, such as wildfire and forest management, is important to distinguish from permanent land use conversion due to the differing ecological and climate impacts of these disturbances and for the purposes of developing effective [...]
A Conversational Intelligent Assistant for Enhanced Operational Support in Floodplain Management with Multimodal Data
Published: 2024-12-19
Subjects: Artificial Intelligence and Robotics, Civil and Environmental Engineering, Computer Sciences, Databases and Information Systems, Earth Sciences, Environmental Engineering, Environmental Sciences, Environmental Studies, Hydraulic Engineering, Hydrology, Water Resource Management
Floodplain management is crucial for mitigating flood risks and enhancing community resilience, yet floodplain managers often face significant challenges, including the complexity of data analysis, regulatory compliance, and effective communication with diverse stakeholders. This study introduces Floodplain Manager AI, an innovative artificial intelligence (AI) based virtual assistant designed to [...]
Tracking Drought Impacts from Texts: Towards AI-Assisted Drought Impact Detection
Published: 2024-12-06
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Environmental Indicators and Impact Assessment, Environmental Sciences, Hydrology
Drought is recognized for its extensive and varied impacts. Based on the drought-related textual datasets from the National Drought Mitigation Center, our research applies advanced artificial intelligence techniques, including deep learning and natural language processing, to enhance the monitoring of multifaceted drought impacts in the United States. This study also delves into predicting [...]
Integration and Execution of Community Land Model Urban (CLMU) in a Containerized Environment
Published: 2024-11-27
Subjects: Civil Engineering, Computer Sciences, Earth Sciences, Environmental Engineering, Environmental Sciences
The Community Land Model Urban (CLMU) is a process-based numerical urban climate model that simulates the interactions between the atmosphere and urban surfaces, serving as a powerful tool for the convergence of urban and climate science research. Despite its advanced capabilities, CLMU presents significant challenges for users unfamiliar with numerical modeling due to the complexities of model [...]
Application of machine learning methods to forecast petrophysical properties in basalts of the Serra Geral Group: Implications for carbon storage
Published: 2024-10-22
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Environmental Sciences, Geophysics and Seismology, Oil, Gas, and Energy, Physical Sciences and Mathematics
This study applies machine learning techniques for forecasting petrophysical properties (density, porosity, and permeability) in the basalts of the Serra Geral Group, located in the Paraná Basin, Brazil. These properties are crucial for the successful implementation of carbon capture and storage (CCS), an important technology to combat climate change. Employing machine learning models—XGBoost, [...]
DARTS: Multi-year database of AI-detected retrogressive thaw slumps in the circum-arctic permafrost region
Published: 2024-10-20
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geomorphology, Physical Sciences and Mathematics
Retrogressive Thaw Slumps (RTS) and Active Layer Detachment Slides (ALD) are widespread thermal mass-wasting hillslope failures triggered by thawing permafrost. Despite increasing rates of these failures, knowledge about their pan-arctic spatial and temporal distribution remains limited. We present the Database of AI-detected Arctic RTS and ALD footprints (DARTS), the largest hillslope [...]
Advancing vegetation monitoring with virtual laser scanning of dynamic scenes (VLS-4D): Opportunities, implementations and future perspectives
Published: 2024-10-07
Subjects: Computer Sciences, Earth Sciences, Environmental Sciences, Geographic Information Sciences, Geography, Numerical Analysis and Scientific Computing, Physical and Environmental Geography, Remote Sensing
Virtual Laser Scanning (VLS) is an established and valuable research tool in forestry and ecology, widely used to simulate labelled LiDAR point cloud data for sensitivity analysis, model training and method testing. In VLS, vegetation has traditionally been modelled as static, neglecting the influence of vegetation dynamics on LiDAR point cloud representations and limiting applications to [...]
Climate Suitability Modelling of Miracle Tree Moringa oleifera Distribution in Pakistan using MaxEnt
Published: 2024-09-24
Subjects: Computer Sciences
Climate change has badly affected many countries in the world and Pakistan is being listed among the top ten of those countries. Pakistan is facing many adverse consequences due to climate change, which includes food security issues, water scarcity, temperature rise and high air pollution index. Moringa oleifera, known to be the miracle tree, has multiple advantages and can be used to combat [...]
Comparative Analysis of SVM and CNN for Hyperspectral Image Classification
Published: 2024-08-13
Subjects: Computer Engineering, Computer Sciences, Other Computer Sciences, Physical Sciences and Mathematics
This paper presents a comparative analysis of tra- ditional machine learning methods and Convolutional Neural Networks (CNNs) for hyperspectral image classification. Utilizing the Indian Pines dataset, we explore the efficacy of Principal Component Analysis (PCA) combined with a Support Vector Machine (SVM) classifier against a deep learning approach involving CNNs. Our methodology includes [...]
TROPICAL STORM SURGE: FORMATION, IMPACT, AND RECENT ADVANCES IN ITS PREDICTION TOWARDS DEVELOPING MITIGATION STRATEGIES
Published: 2024-07-19
Subjects: Computer Sciences, Earth Sciences, Environmental Sciences, Oceanography and Atmospheric Sciences and Meteorology, Other Physical Sciences and Mathematics, Physics, Planetary Sciences
Tropical storm surge poses significant risks to coastal areas, necessitating precise prediction for effective emergency preparedness and mitigation. Recent advances in numerical models such as SLOSH, ADCIRC, and FVCOM have revolutionized storm surge forecasting by accurately simulating complex hydrodynamic processes, bolstered by ADCIRC's use of high-resolution grids and parallel computing for [...]