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GPU-accelerated Optimization of Fuel Treatments for Mitigating Wildfire Hazard
2013
Procedia Computer Science
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Fuel treatment is considered a suitable way to mitigate the hazard related to potential wildfires on a landscape. ...
Then, we propose a computational approach that leads to a spatially-optimized treatment layout exploiting Tabu Search and General-Purpose computing on Graphics Processing Units (GPGPU). ...
The latter exploits the fast GPU shared memory and was implemented according to the optimized examples included in the CUDA SDK. ...
doi:10.1016/j.procs.2013.05.262
fatcat:a6btpd5fm5cytnvjnaf75eeasy
Deep Learning Based Wildfire Event Object Detection from 4K Aerial Images Acquired by UAS
2020
AI
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We introduce a coarse-to-fine framework to auto-detect wildfires that are sparse, small, and irregularly-shaped. ...
Unmanned Aerial Systems, hereafter referred to as UAS, are of great use in hazard events such as wildfire due to their ability to provide high-resolution video imagery over areas deemed too dangerous for ...
The funder had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. ...
doi:10.3390/ai1020010
fatcat:q6wlf3p5hffltesjg2i5e6yj2e
Uni-Temporal Multispectral Imagery for Burned Area Mapping with Deep Learning
2021
Remote Sensing
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., U-Net, HRNet, Fast-SCNN, and DeepLabv3+, and machine learning (ML) algorithms were applied to Sentinel-2 imagery and Landsat-8 imagery in three wildfire sites in two different local climate zones. ...
Using only a post-fire image, the DL methods not only provide automatic, accurate, and bias-free large-scale mapping option with cross-sensor applicability, but also have potential to be used for onboard ...
Accurate and timely mapping of burned areas is, therefore, needed for the assessment of economic losses caused by the wildfires, managing post-fire hazards such as landslides or mudflows, and planning ...
doi:10.3390/rs13081509
doaj:fa579a4d3ad346a2b492b2448310403c
fatcat:jhls5zm62bchzkhtb4srrjr2xy
A review of machine learning applications in wildfire science and management
[article]
2020
arXiv
pre-print
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We also discuss the advantages and limitations of various ML approaches and identify opportunities for future advances in wildfire science and management within a data science context. ...
Here, we present a scoping review of ML in wildfire science and management. ...
The authors would also like to thank Intact Insurance and the Western Partnership for Wildland Fire Science for their support. ...
arXiv:2003.00646v1
fatcat:5ufhtbwlsvd2rdk3ogbmqpnxuu
Attention to Fires: Multi-Channel Deep Learning Models for Wildfire Severity Prediction
2021
Applied Sciences
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Wildfires are one of the natural hazards that the European Union is actively monitoring through the Copernicus EMS Earth observation program which continuously releases public information related to such ...
Furthermore, a novel multi-channel attention-based analysis is presented to uncover the prediction behaviour and provide model interpretability. ...
The authors are grateful to Moreno La Quatra for his help in exploiting the HPC resources.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app112211060
fatcat:gw2kmvo36va7xb7nbb7rthsfn4
On the Use of Interferometric Synthetic Aperture Radar Data for Monitoring and Forecasting Natural Hazards
2021
Mathematical Geosciences
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are irreplaceable tools for modeling and simulating natural hazards scenarios from a mathematical perspective. ...
We describe the techniques exploited to extract ground displacement information from satellite radar sensor images and the applicability of such data to the study of natural hazards such as landslides, ...
More advanced multi-temporal or multi-interferogram InSAR techniques allow one to estimate time series of surface deformation maps by analyzing a stack of SAR images of the same geographical region collected ...
doi:10.1007/s11004-021-09948-8
fatcat:izgtwzv7yzgbdfkrgl2bmv26ui
Deep Learning and Earth Observation to Support the Sustainable Development Goals
[article]
2021
arXiv
pre-print
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New developments and a plethora of applications are already changing the way humanity will face the living planet challenges. ...
This paper reviews current deep learning approaches for Earth observation data, along with their application towards monitoring and achieving the SDGs most impacted by the rapid development of deep learning ...
There is a clear need for innovation for fast, accurate, and costeffective cadastral mapping needed for LASs [168] . ...
arXiv:2112.11367v1
fatcat:7eve5dr45vcublfqyzzrccuvxa
An Alertness-Adjustable Cloud/Fog IoT Solution for Timely Environmental Monitoring Based on Wildfire Risk Forecasting
2020
Energies
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Finally, a user-driven web interface is highlighted to accompany the system; it is capable of augmenting the data curation and visualization, and offering real-time wildfire risk forecasting based on Chandler's ...
, wildfires. ...
To further highlight its performance, the developed prototype was put to the test under a real case scenario involving one of Greece's most notable environmental hazards, the wildfires. ...
doi:10.3390/en13143693
fatcat:zuf6vuiaubbs7ex3ifsi2c64vm
Free software: A review, in the context of disaster management
2015
International Journal of Applied Earth Observation and Geoinformation
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However, to make efficient use of available data and information -before, during and after a disaster -reliable software is required. ...
Free geoinformatics can help to optimize the limited financial, technological and manpower resources that many organisations face, providing a sustainable input to analytical activities. ...
Hence, multi-core CPU and GPU processing applications are an opportunity for FOSS4geoinfo. ...
doi:10.1016/j.jag.2015.05.012
fatcat:m4rglhfau5forazmlshjm3iiem
A Brief Review of Recent Developments in the Integration of Deep Learning with GIS
2022
Geomatics and Environmental Engineering
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This study tries to provide a brief overview of the use of DL methods in GIS. ...
The two technologies may be connected to form a dynamic system that is incredibly well adapted to the evaluation of environmental conditions through the interrelationships of texture, size, pattern, and ...
Flood hazard mapping was produced using a deep convolution neural network model and a GIS. ...
doi:10.7494/geom.2022.16.2.21
fatcat:i235nk3i3rbg3j7dcekaddrcca
How Will Climate Change Affect the United States in Decades to Come?
2017
EOS
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A new U.S. government report shows that climate is changing and that human activities will lead to many more changes. ...
Here human-caused wildfires are more likely to occur and represent a main hazard for people, houses and infrastructures. ...
Our work focuses in efficient 2D simulation of THM models in multi-GPU clusters, particularly the mechanical part using explicit finite differences approximation. ...
doi:10.1029/2017eo086015
fatcat:35mql2szkna45gayq6x4qjjnhu
The Acceptance of Using Information Technology for Disaster Risk Management: A Systematic Review
2020
Engineering Journal
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This study conducted a systematic review with the academic researches during 2011-2018. ...
For coping with disaster, several sectors try to develop the frameworks, systems, technologies and so on. ...
The authors also would like to thank Ms. Sirin Sampaothip for language editing. ...
doi:10.4186/ej.2020.24.4.111
fatcat:jq4tquj7avanddzld4kiahwpgi
A Framework for Cloud-Based Spatially-Explicit Uncertainty and Sensitivity Analysis in Spatial Multi-Criteria Models
2021
ISPRS International Journal of Geo-Information
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Implementing the proposed framework will contribute to a more robust assessment of spatial multi-criteria decision-making applications, facilitating a broader access to SEUSA by the research community ...
This paper presents the design of a framework to perform SEUSA as a Service in a cloud-based environment scalable to very large raster datasets and applicable to various domains, such as landscape assessment ...
[18] presented GPU-based parallelization approaches to accelerate the generation of the suitability surfaces, which constitute an input for the uncertainty and sensitivity analysis for each pixel location ...
doi:10.3390/ijgi10040244
fatcat:t4gur366k5bvjavsp7erph2gsq
Distributed Fusion of Heterogeneous Remote Sensing and Social Media Data: A Review and New Developments
2021
Proceedings of the IEEE
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In order to meet these challenges, distributed computing is increasingly viewed as a feasible solution to parallelize the analysis of massive data coming from different sources (e.g., remote sensing and ...
many situations in which using only remote sensing data cannot fully meet the requirements of applications in which a (near) real-time response is needed. ...
In related fashion, the study in [84] proposed a per-field classification approach to automatically map fine-grained urban land use. ...
doi:10.1109/jproc.2021.3079176
fatcat:gk2xqgsipjfr7kfanauymtk724
Spatiotemporal event detection: a review
2020
International Journal of Digital Earth
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Spatiotemporal event detection serves as a gateway to enable a better understanding by detecting events that represent the abnormal status of relevant phenomena. ...
The novelty of this review is to revisit the definition and requirements of event detection and to layout the overall workflow (from sensing and event extraction methods to the operations and decision-supporting ...
This community paper is one of a set of efforts to setup the foundation for future spatiotemporal studies/sciences. Yang, Yu and Bambacus initialized the concept for this paper. ...
doi:10.1080/17538947.2020.1738569
fatcat:urbuc2zii5bajjmmkzu6idyrg4
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