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A VARI-based relative greenness from MODIS data for computing the Fire Potential Index

P. Schneider, D.A. Roberts, P.C. Kyriakidis
2008 Remote Sensing of Environment  
To compare MODIS-based NDVI-FPI and VARI-FPI, RG was calculated from a 6-year time series of MODIS composites and validated against in-situ observations of LFM as a surrogate for vegetation greenness.  ...  RG from both indices was then compared in terms of its performance for computing the FPI using historical wildfire data.  ...  Furthermore, the authors also acknowledge the contribution of four anonymous reviewers, whose comments substantially improved the quality of the manuscript.  ... 
doi:10.1016/j.rse.2007.07.010 fatcat:g4lh5wyolbeidjz4dcoyq7rbnq

The DLR FireBIRD Small Satellite Mission: Evaluation of Infrared Data for Wildfire Assessment

Michael Nolde, Simon Plank, Rudolf Richter, Doris Klein, Torsten Riedlinger
2021 Remote Sensing  
Wildfires significantly influence ecosystem patterns and processes on a global scale. In many cases, they pose a threat to human lives and property.  ...  This study uses and compares two different methods to derive the FRP from FireBIRD data. The data are analyzed regarding six major fire incidents in different regions of the world.  ...  In August 2016, wildfires were raging in northern Portugal as well as on Madeira. An emergency has been declared for the region of Porto.  ... 
doi:10.3390/rs13081459 fatcat:gdqerytgvvbphb6ia4pr46lbxq

A Framework for Multi-Dimensional Assessment of Wildfire Disturbance Severity from Remotely Sensed Ecosystem Functioning Attributes

Bruno Marcos, João Gonçalves, Domingo Alcaraz-Segura, Mário Cunha, João P. Honrado
2021 Remote Sensing  
Together with effect sizes, this ranking was used to select a parsimonious set of indicators for analyzing the main effects of wildfire disturbances on ecosystem functioning, for both the whole study area  ...  Here, we propose a satellite-based framework to evaluate the impacts, at short to medium term (i.e., from the year of fire to the second year after), of wildfires on four dimensions of ecosystem functioning  ...  The funders 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/rs13040780 fatcat:kd3nxhytkjbxln64wk2noaglme

Earth Science Applications of Sensor Data [chapter]

Anuj Karpatne, James Faghmous, Jaya Kawale, Luke Styles, Mace Blank, Varun Mithal, Xi Chen, Ankush Khandelwal, Shyam Boriah, Karsten Steinhaeuser, Michael Steinbach, Vipin Kumar (+1 others)
2012 Managing and Mining Sensor Data  
Advances in earth observation technologies have led to the acquisition of vast volumes of accurate, timely and reliable environmental data which encompass a multitude of information about the land, ocean  ...  Hence, a thorough understanding of earth science sensor datasets has a direct impact on a range of societally relevant issues.  ...  Acknowledgments This work was supported in part by the National Science Foundation under Grants IIS-1029711 and IIS-0905581, an NSF Graduate Research Fellowship, an NSF Nordic Research Opportunity, and  ... 
doi:10.1007/978-1-4614-6309-2_15 fatcat:wtutvripnffmdlqjcj744qlbji

Use of Remote Sensing in Wildfire Management [chapter]

Brigitte Leblon, Laura Bourgeau-Chavez, Jess San-Miguel-Ayanz
2012 Sustainable Development - Authoritative and Leading Edge Content for Environmental Management  
Chen, Use of Remote Sensing in Wildfire Management 75  ...  Acknowledgement The pre-fire conditions study is a compendium of the works from the following students: Lisa Gallant, Shannon White, Mark Doyle, Melissa Abbott, Guy Strickland, Keith Abbott, Steven Oldford  ...  Although most of the studies on burnt area mapping were based on the use of optical imagery, there are a series of examples in which data from active sensors such as the Synthetic Aperture Radar (SAR)  ... 
doi:10.5772/45829 fatcat:dhems6dw75f4biafdy4j3zs5su

A Review on Early Forest Fire Detection Systems Using Optical Remote Sensing

Panagiotis Barmpoutis, Periklis Papaioannou, Kosmas Dimitropoulos, Nikos Grammalidis
2020 Sensors  
Finally, the strengths and weaknesses of fire detection systems based on optical remote sensing are discussed aiming to contribute to future research projects for the development of early warning fire  ...  This paper presents an overview of the optical remote sensing technologies used in early fire warning systems and provides an extensive survey on both flame and smoke detection algorithms employed by each  ...  Unmanned Aerial Vehicles Terrestrial imaging systems can detect both flame and smoke, but in many cases, it is almost impossible to view, in a timely manner, the flames of a wildfire from a ground-based  ... 
doi:10.3390/s20226442 pmid:33187292 fatcat:4sw3yywfx5gl5cv3ml6jfkdvja

Uni-Temporal Multispectral Imagery for Burned Area Mapping with Deep Learning

Xikun Hu, Yifang Ban, Andrea Nascetti
2021 Remote Sensing  
Our study aims to expound on the capability of deep learning (DL) models for automatically mapping burned areas from uni-temporal multispectral imagery.  ...  Accurate burned area information is needed to assess the impacts of wildfires on people, communities, and natural ecosystems.  ...  We acknowledge the use of data from Sentinel-2 operated by the Copernicus Programme and Landsat-8 data by NASA.  ... 
doi:10.3390/rs13081509 doaj:fa579a4d3ad346a2b492b2448310403c fatcat:jhls5zm62bchzkhtb4srrjr2xy

A Systematic Review of Applications of Machine Learning Techniques for Wildfire Management Decision Support

Karol Bot, José G. Borges
2022 Inventions  
The emphasis is on providing a summary of these applications with a classification according to the case study type, machine learning method, case study location, and performance metrics.  ...  The review considers documents published in the last four years, using a sample of 135 documents (review articles and research articles).  ...  A mask region-based convolutional neural network approach was used to automate dead tree detection from aerial spaces in [56] .  ... 
doi:10.3390/inventions7010015 fatcat:cce4w6uuv5gwlk4ladocmw6cvu

Knowledge Extracted from Copernicus Satellite Data

Dumitru Octavian, Schwarz Gottfried, Eltoft Torbjørn, Kræmer Thomas, Wagner Penelope, Hughes Nick, Arthus David, Fleming Andrew, Koubarakis Manolis, Datcu Mihai
2019 Zenodo  
In this publication, we focus on the Polar case which requires the selection of validation areas, the generation of a training dataset, the development and testing of deep learning algorithms, and the  ...  By applying an already established active learning approach based on a Support Vector Machine with relevance feedback [2], we can limit ourselves to a limited number of typical satellite images to extract  ...  In this study, the glaciers lakes were extracted by different indices.  ... 
doi:10.5281/zenodo.3941573 fatcat:zzifwgljifck5bpjnboetsftfu

A review of machine learning applications in wildfire science and management [article]

Piyush Jain, Sean C P Coogan, Sriram Ganapathi Subramanian, Mark Crowley, Steve Taylor, Mike D Flannigan
2020 arXiv   pre-print
Our objective is to improve awareness of ML among wildfire scientists and managers, as well as illustrate the challenging range of problems in wildfire science available to data scientists.  ...  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.  ...  Acknowledgments The motivation for this paper arose from the "Not the New Normal" BC AI Wildfire Symposium held in Vancouver, BC, on 12 October 2018.  ... 
arXiv:2003.00646v1 fatcat:5ufhtbwlsvd2rdk3ogbmqpnxuu

Role of Machine Learning Algorithms in Forest Fire Management: A Literature Review

Arif Muhammad, Alghamdi Khloud K, Sahel Salma A, Alosaimi Samar O, Alsahaft Mashael E, Alharthi Maram A, Arif Maryam
2021 Journal of Robotics and Automation  
) extracted from the data of forest fire events in Dayu county, China during 1980 to 2010.  ...  [138] have conducted a study on a dataset of fire presence only in Tyrol province, Austria, from 1993 to 2011, including the topography data vegetation, climate, and socio-economic parameters.  ... 
doi:10.36959/673/372 fatcat:lo2bzahnazbspax2qzgg7smpne

Historical background and current developments for mapping burned area from satellite Earth observation

Emilio Chuvieco, Florent Mouillot, Guido R. van der Werf, Jesús San Miguel, Mihai Tanasse, Nikos Koutsias, Mariano García, Marta Yebra, Marc Padilla, Ioannis Gitas, Angelika Heil, Todd J. Hawbaker (+1 others)
2019 Remote Sensing of Environment  
With the launch of the first Earth observation satellites, remote sensing quickly became a more practical alternative to detect burned areas, as they provide timely regional and global coverage of fire  ...  Fire has a diverse range of impacts on Earth's physical and social systems.  ...  MODIS data are employed for the detection of hot spots and BA mapping (for fires over 40 ha) on a European scale.  ... 
doi:10.1016/j.rse.2019.02.013 fatcat:eywm3ix63ngvdczdtdci46etwu

Potential and Challenges of Harmonizing 40 Years of AVHRR Data: The TIMELINE Experience

Stefan Dech, Stefanie Holzwarth, Sarah Asam, Thorsten Andresen, Martin Bachmann, Martin Boettcher, Andreas Dietz, Christina Eisfelder, Corinne Frey, Gerhard Gesell, Ursula Gessner, Andreas Hirner (+17 others)
2021 Remote Sensing  
The challenges to generating a well calibrated and harmonized 40-year-long time series based on AVHRR sensor data flown on 14 different platforms are enormous.  ...  However, there is only one medium resolution sensor family in orbit that enables an observation time span of 40 and more years at a daily repeat interval. This is the AVHRR sensor family.  ...  Conflicts of Interest: The authors declare no conflict of interest. Remote Sens. 2021, 13, 3618  ... 
doi:10.3390/rs13183618 fatcat:lynncr3n75gjhia5vzvlotxgeu

Spatial Assessment of Wildfires Susceptibility in Santa Cruz (Bolivia) Using Random Forest

Marcela Bustillo Sánchez, Marj Tonini, Anna Mapelli, Paolo Fiorucci
2021 Geosciences  
The main goal was to develop a model, based on Random Forest, in which probabilistic outputs allowed to elaborate wildfires susceptibility maps.  ...  To fill this gap, we implemented a dataset including the burned area that occurred in the department of Santa Cruz in the period of 2010–2019, and the digital spatial data describing the predisposing factors  ...  Acknowledgments: This study is part of the Master's thesis of Marcela Bustillo Sánchez. Authors acknowledge the "Simon I.  ... 
doi:10.3390/geosciences11050224 doaj:feca479ec35046f8a5167a7582c4e575 fatcat:xl7doge6kvh43p36groqq6vbiy

Estimating the risk of fire outbreaks in the natural environment

Daniela Stojanova, Andrej Kobler, Peter Ogrinc, Bernard Ženko, Sašo Džeroski
2011 Data mining and knowledge discovery  
In this study, we build predictive models to estimate the risk of fire outbreaks in Slovenia, using data from a GIS, Remote Sensing imagery and the weather prediction model ALADIN.  ...  The study is carried out on three datasets, from three regions: one for the Kras region, one for the coastal region and one for continental Slovenia.  ...  Preliminary work on this application, including the data acquisition and pre-processing, was performed within the project "Forecasting GIS model of fire danger in the natural environment" (M1-0032) financed  ... 
doi:10.1007/s10618-011-0213-2 fatcat:7rmp2kd4vvdl5e3kh5b64rvhb4
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