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Related papers: Mapping waterways worldwide with deep learning

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Surprisingly a number of Earth's waterways remain unmapped, with a significant number in low and middle income countries. Here we build a computer vision model (WaterNet) to learn the location of waterways in the United States, based on…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Matthew Pierson , Zia Mehrabi

Hydraulic geometry parameters describing river hydrogeomorphic is important for flood forecasting. Although well-established, power-law hydraulic geometry curves have been widely used to understand riverine systems and mapping flooding…

Spatially consistent and up-to-date maps of human settlements are crucial for addressing policies related to urbanization and sustainability, especially in the era of an increasingly urbanized world.The availability of open and free…

Image and Video Processing · Electrical Eng. & Systems 2020-10-30 Christina Corbane , Vasileios Syrris , Filip Sabo , Panagiotis Politis , Michele Melchiorri , Martino Pesaresi , Pierre Soille , Thomas Kemper

Floods are among the most frequent and catastrophic natural disasters and affect millions of people worldwide. It is important to create accurate flood maps to plan (offline) and conduct (real-time) flood mitigation and flood rescue…

Computer Vision and Pattern Recognition · Computer Science 2020-07-15 P. Chaudhary , S. D'Aronco , J. P. Leitao , K. Schindler , J. D. Wegner

Where are the Earth's streams flowing right now? Inland surface waters expand with floods and contract with droughts, so there is no one map of our streams. Current satellite approaches are limited to monthly observations that map only the…

Computer Vision and Pattern Recognition · Computer Science 2020-11-17 Dolores Garcia , Gonzalo Mateo-Garcia , Hannes Bernhardt , Ron Hagensieker , Ignacio G. Lopez Francos , Jonathan Stock , Guy Schumann , Kevin Dobbs , Freddie Kalaitzis

Floods cause extensive global damage annually, making effective monitoring essential. While satellite observations have proven invaluable for flood detection and tracking, comprehensive global flood datasets spanning extended time periods…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Amit Misra , Kevin White , Simone Fobi Nsutezo , William Straka , Juan Lavista

The availability of curated large-scale training data is a crucial factor for the development of well-generalizing deep learning methods for the extraction of geoinformation from multi-sensor remote sensing imagery. While quite some…

Computer Vision and Pattern Recognition · Computer Science 2019-06-20 Michael Schmitt , Lloyd Haydn Hughes , Chunping Qiu , Xiao Xiang Zhu

Determining the location of an image anywhere on Earth is a complex visual task, which makes it particularly relevant for evaluating computer vision algorithms. Yet, the absence of standard, large-scale, open-access datasets with reliably…

Global surface water detection in very-high-resolution (VHR) satellite imagery can directly serve major applications such as refined flood mapping and water resource assessment. Although achievements have been made in detecting surface…

Computer Vision and Pattern Recognition · Computer Science 2023-03-17 Yansheng Li , Bo Dang , Wanchun Li , Yongjun Zhang

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

Flooding remains a major global challenge, worsened by climate change and urbanization, demanding advanced solutions for effective disaster management. While traditional 2D flood mapping techniques provide limited insights, 3D flood…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Wenfeng Jia , Bin Liang , Yuxi Liu , Muhammad Arif Khan , Lihong Zheng

Surface water dynamics play a critical role in Earth's climate system, influencing ecosystems, agriculture, disaster resilience, and sustainable development. Yet monitoring rivers and surface water at fine spatial and temporal scales…

The proliferation of floating anthropogenic debris in rivers has emerged as a pressing environmental concern, exerting a detrimental influence on biodiversity, water quality, and human activities such as navigation and recreation. The…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Gauthier Grimmer , Romain Wenger , Clément Flint , Germain Forestier , Gilles Rixhon , Valentin Chardon

Computational complexity has been the bottleneck of applying physically-based simulations on large urban areas with high spatial resolution for efficient and systematic flooding analyses and risk assessments. To address this issue of long…

Computer Vision and Pattern Recognition · Computer Science 2020-05-14 Zifeng Guo , Joao P. Leitao , Nuno E. Simoes , Vahid Moosavi

Climate change has caused disruption in certain weather patterns, leading to extreme weather events like flooding and drought in different parts of the world. In this paper, we propose machine learning methods for analyzing changes in water…

Signal Processing · Electrical Eng. & Systems 2023-01-19 Francesco Mauro , Benjamin Rich , Veronica Wairimu Muriga , Alessandro Sebastianelli , Silvia Liberata Ullo

Remote sensing of the Earth's surface water is critical in a wide range of environmental studies, from evaluating the societal impacts of seasonal droughts and floods to the large-scale implications of climate change. Consequently, a large…

Computer Vision and Pattern Recognition · Computer Science 2022-12-29 Joachim Moortgat , Ziwei Li , Michael Durand , Ian Howat , Bidhyananda Yadav , Chunli Dai

Waterline usually plays as an important visual cue for maritime applications. However, the visual complexity of inland waterline presents a significant challenge for the development of highly efficient computer vision algorithms tailored…

Computer Vision and Pattern Recognition · Computer Science 2019-11-26 Jing Huang , Hengfeng Miao , Lin Li , Yuanqiao Wen , Changshi Xiao

Landslides pose severe threats to infrastructure, economies, and human lives, necessitating accurate detection and predictive mapping across diverse geographic regions. With advancements in deep learning and remote sensing, automated…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Rahul A. Burange , Harsh K. Shinde , Omkar Mutyalwar

In the globalized economic world, it has become important to understand the purpose behind infrastructural and construction initiatives occurring within developing regions of the earth. This is critical when the financing for such projects…

Computer Vision and Pattern Recognition · Computer Science 2020-09-02 Kyle McCullough , Andrew Feng , Meida Chen , Ryan McAlinden

Spatial patterns of water table depth (WTD) play a crucial role in shaping ecological resilience, hydrological connectivity, and human-centric systems. Generally, a large-scale (e.g., continental or global) continuous map of static WTD can…

Machine Learning · Computer Science 2025-03-14 Joseph Janssen , Ardalan Tootchi , Ali A. Ameli
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