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Land cover mapping is essential to monitoring the environment and understanding the effects of human activities on it. The automatic approaches to land cover mapping (i.e., image segmentation) mostly used traditional machine learning that…

Image and Video Processing · Electrical Eng. & Systems 2021-03-24 Sanja Šćepanović , Oleg Antropov , Pekka Laurila , Yrjö Rauste , Vladimir Ignatenko , Jaan Praks

Urban planning applications (energy audits, investment, etc.) require an understanding of built infrastructure and its environment, i.e., both low-level, physical features (amount of vegetation, building area and geometry etc.), as well as…

Computer Vision and Pattern Recognition · Computer Science 2017-09-15 Adrian Albert , Jasleen Kaur , Marta Gonzalez

Satellite remote sensing presents a cost-effective solution for synoptic flood monitoring, and satellite-derived flood maps provide a computationally efficient alternative to numerical flood inundation models traditionally used. While…

Geophysics · Physics 2022-09-05 Antara Dasgupta , Lasse Hybbeneth , Björn Waske

Vegetation is the natural linkage connecting soil, atmosphere and water. It can represent the change of land cover to a certain extent and serve as an indicator for global change research. Methods for measuring coverage can be divided into…

Image and Video Processing · Electrical Eng. & Systems 2019-09-11 Chunxue Wu , Bobo Ju , Naixue Xiong , Guisong Yang , Yan Wu , Hongming Yang , Jiaying Huang , Zhiyong Xu

Quantifying the impacts of anthropogenic global warming requires accurate Earth system model (ESM) simulations. Statistical bias correction and downscaling can be applied to reduce errors and increase the resolution of ESMs. However,…

Geophysics · Physics 2024-06-24 Philipp Hess , Niklas Boers

Climate change may be classified as the most important environmental problem that the Earth is currently facing, and affects all living species on Earth. Given that air-quality monitoring stations are typically ground-based their abilities…

Machine Learning · Computer Science 2023-05-08 Andrew Rowley , Oktay Karakuş

While annotated images for change detection using satellite imagery are scarce and costly to obtain, there is a wealth of unlabeled images being generated every day. In order to leverage these data to learn an image representation more…

Computer Vision and Pattern Recognition · Computer Science 2021-04-13 Marrit Leenstra , Diego Marcos , Francesca Bovolo , Devis Tuia

Air pollution is a major driver of climate change. Anthropogenic emissions from the burning of fossil fuels for transportation and power generation emit large amounts of problematic air pollutants, including Greenhouse Gases (GHGs). Despite…

Machine Learning · Computer Science 2021-09-01 Linus Scheibenreif , Michael Mommert , Damian Borth

Accurate assessment of atmospheric nitrogen dioxide (NO$_2$) and sulfur dioxide (SO$_2$) is essential for understanding climate-air quality interactions, supporting environmental policy, and protecting public health. Traditional monitoring…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Prasanjit Dey , Soumyabrata Dev , Bianca Schoen-Phelan

Modeling environmental ecosystems is critical for the sustainability of our planet, but is extremely challenging due to the complex underlying processes driven by interactions amongst a large number of physical variables. As many variables…

Machine Learning · Computer Science 2025-10-13 Shiyuan Luo , Juntong Ni , Shengyu Chen , Runlong Yu , Yiqun Xie , Licheng Liu , Zhenong Jin , Huaxiu Yao , Xiaowei Jia

Satellite remote sensing is playing an increasing role in the rapid mapping of damage after natural disasters. In particular, synthetic aperture radar (SAR) can image the Earth's surface and map damage in all weather conditions, day and…

Accurate change detection from satellite imagery is essential for monitoring rapid mass-movement hazards such as snow avalanches, which increasingly threaten human life, infrastructure, and ecosystems due to their rising frequency and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Mattia Gatti , Alberto Mariani , Ignazio Gallo , Fabiano Monti

Forecasting the state of vegetation in response to climate and weather events is a major challenge. Its implementation will prove crucial in predicting crop yield, forest damage, or more generally the impact on ecosystems services relevant…

As global warming increases the complexity of weather patterns; the precision of weather forecasting becomes increasingly important. Our study proposes a novel preprocessing method and convolutional autoencoder model developed to improve…

Machine Learning · Computer Science 2024-11-11 Yo-Hwan Choi , Seon-Yu Kang , Minjong Cheon

The worldwide variation in vegetation height is fundamental to the global carbon cycle and central to the functioning of ecosystems and their biodiversity. Geospatially explicit and, ideally, highly resolved information is required to…

Computer Vision and Pattern Recognition · Computer Science 2022-04-19 Nico Lang , Walter Jetz , Konrad Schindler , Jan Dirk Wegner

The Amazon rainforests have been suffering widespread damage, both via natural and artificial means. Every minute, it is estimated that the world loses forest cover the size of 48 football fields. Deforestation in the Amazon rainforest has…

Computer Vision and Pattern Recognition · Computer Science 2018-09-05 Somnath Rakshit , Soumyadeep Debnath , Dhiman Mondal

In this paper we discuss and address the challenges of predicting extreme atmospheric events like intense rainfall, hail, and strong winds. These events can cause significant damage and have become more frequent due to climate change.…

Atmospheric and Oceanic Physics · Physics 2023-10-06 Mikhail Mozikov , Ilya Makarov , Alexandr Bulkin , Daria Taniushkina , Roland Grinis , Yury Maximov

Air pollution represents a pivotal environmental challenge globally, playing a major role in climate change via greenhouse gas emissions and negatively affecting the health of billions. However predicting the spatial and temporal patterns…

Machine Learning · Computer Science 2024-02-13 Madhav Khirwar , Ankur Narang

Detecting surface changes from satellite imagery is critical for rapid disaster response and environmental monitoring, yet remains challenging due to the complex interplay between atmospheric noise, seasonal variations, and sensor…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Bertrand Rouet-Leduc , Claudia Hulbert

With changing climatic conditions, we are already seeing an increase in extreme weather events and their secondary consequences, including landslides. Landslides threaten infrastructure, including roads, railways, buildings, and human life.…

Computer Vision and Pattern Recognition · Computer Science 2023-10-11 Alexandra Jarna Ganerød , Gabriele Franch , Erin Lindsay , Martina Calovi