Articles citing this paper
Global fire size distribution: from power law to log-normal
Stijn Hantson A B E F , Salvador Pueyo C D F and Emilio Chuvieco A
+ Author Affiliations
- Author Affiliations
A Environmental Remote Sensing Research Group, Department of Geography and Geology, University of Alcala, c/o Colegios 2, 28801 Alcalá de Henares, Spain.
B Institute of Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology, Kreuzeckbahnstraße 19, 82467 Garmisch-Partenkirchen, Germany.
C Department d’Ecologia, Universitat de Barcelona, Avinguda Diagonal 645, 08028 Barcelona, Catalonia, Spain.
D Research and Degrowth, c/o Hospital 77-4, 08003 Barcelona, Catalonia, Spain.
E Corresponding author. Email: hantson.stijn@gmail.com
F These authors contributed equally to this work.
International Journal of Wildland Fire 25(4) 403-412 https://doi.org/10.1071/WF15108
Submitted: 3 June 2015 Accepted: 29 October 2015 Published: 2 February 2016
31 articles found in Crossref database.
Overwintering fires rising in eastern Siberia
Xu Wenxuan,
Scholten Rebecca C,
Hessilt Thomas D,
Liu Yongxue, Veraverbeke Sander
Environmental Research Letters. 2022 17(4). p.045005
Temporal and spatial patterns of fire activity in three biomes of Brazil
Abreu Marcel Carvalho,
Lyra Gustavo Bastos,
de Oliveira-Júnior José Francisco,
Souza Amaury,
Pobočíková Ivana,
de Souza Fraga Micael, Abreu Rodolfo Cesar Real
Science of The Total Environment. 2022 844 p.157138
Forest Fire Occurrence Prediction in China Based on Machine Learning Methods
Pang Yongqi,
Li Yudong,
Feng Zhongke,
Feng Zemin,
Zhao Ziyu,
Chen Shilin, Zhang Hanyue
Remote Sensing. 2022 14(21). p.5546
Application of remote sensing and machine learning algorithms for forest fire mapping in a Mediterranean area
Mohajane Meriame,
Costache Romulus,
Karimi Firoozeh,
Bao Pham Quoc,
Essahlaoui Ali,
Nguyen Hoang,
Laneve Giovanni, Oudija Fatiha
Ecological Indicators. 2021 129 p.107869
Predictive Modeling of Forest Fires in Yunnan Province: An Integration of ARIMA and Stepwise Regression Analysis
Shi Yan,
Feng Changping, Yang Shipeng
Applied Sciences. 2023 14(1). p.256
Wildfire Susceptibility Mapping Using Deep Learning Algorithms in Two Satellite Imagery Dataset
Bahadori Nazanin,
Razavi-Termeh Seyed Vahid,
Sadeghi-Niaraki Abolghasem,
Al-Kindi Khalifa M.,
Abuhmed Tamer,
Nazeri Behrokh, Choi Soo-Mi
Forests. 2023 14(7). p.1325
Analysis of the Threat of Forest Fires to Ancient Cities by GIS and Remote Sensing Methods
TÜKEL Ezgi, KALKAN Kaan
Turkish Journal of Geosciences. 2022 3(2). p.58
Power Law Size Distributions in Geoscience Revisited
Corral Álvaro, González Álvaro
Earth and Space Science. 2019 6(5). p.673
Lognormals, power laws and double power laws in the distribution of frequencies of harmonic codewords from classical music
Serra-Peralta Marc,
Serrà Joan, Corral Álvaro
Scientific Reports. 2022 12(1).
Truncated lognormal distributions and scaling in the size of naturally defined population clusters
Corral Álvaro,
Udina Frederic, Arcaute Elsa
Physical Review E. 2020 101(4).
Consistent spatial scaling of high‐severity wildfire can inform expected future patterns of burn severity
Buonanduci Michele S.,
Donato Daniel C.,
Halofsky Joshua S.,
Kennedy Maureen C., Harvey Brian J.
Ecology Letters. 2023 26(10). p.1687
Influência dos Elementos Meteorológicos Sobre o Comportamento do Fogo
Torres Fillipe Tamiozzo Pereira,
Silva Júnior Milton Ribas da, Lima Gumercindo Souza
Revista Brasileira de Meteorologia. 2019 34(1). p.33
Fuel fragmentation and fire size distributions in managed and unmanaged boreal forests in the province of Saskatchewan, Canada
Lehsten Veiko,
de Groot William, Sallaba Florian
Forest Ecology and Management. 2016 376 p.148
Nonparametric multivariate analysis of variance for affecting factors on the extent of forest fire damage in Jilin Province, China
Li Jing,
Shan Yanlong,
Yin Sainan,
Wang Mingxia,
Sun Long, Wang Daning
Journal of Forestry Research. 2019 30(6). p.2185
Advances in Intelligent, Interactive Systems and Applications (2019)
Forest fire susceptibility prediction using machine learning models with resampling algorithms, Northern part of Eastern Ghat Mountain range (India)
Bera Biswajit,
Shit Pravat Kumar,
Sengupta Nairita,
Saha Soumik, Bhattacharjee Sumana
Geocarto International. 2022 37(26). p.11756
Using long temporal reference units to assess the spatial accuracy of global satellite-derived burned area products
Franquesa Magí,
Lizundia-Loiola Joshua,
Stehman Stephen V., Chuvieco Emilio
Remote Sensing of Environment. 2022 269 p.112823
Reconstructing 34 Years of Fire History in the Wet, Subtropical Vegetation of Hong Kong Using Landsat
Chan Aland H. Y.,
Guizar-Coutiño Alejandro,
Kalamandeen Michelle, Coomes David A.
Remote Sensing. 2023 15(6). p.1489
Fire spread and the issue of community-level selection in the evolution of flammability
Schertzer Emmanuel, Staver A. Carla
Journal of The Royal Society Interface. 2018 15(147). p.20180444
Joint modeling and prediction of massive spatio-temporal wildfire count and burnt area data with the INLA-SPDE approach
Zhang Zhongwei,
Krainski Elias,
Zhong Peng,
Rue Harvard, Huser Raphaël
Extremes. 2023 26(2). p.339
Alternative stable equilibria and critical thresholds created by fire regimes and plant responses in a fire‐prone community
Miller Adam D.,
Thompson Jonathan R.,
Tepley Alan J., Anderson‐Teixeira Kristina J.
Ecography. 2019 42(1). p.55
Land cover, more than monthly fire weather, drives fire-size distribution in Southern Québec forests: Implications for fire risk management
Marchal Jean,
Cumming Steve G.,
McIntire Eliot J. B., Carcaillet Christopher
PLOS ONE. 2017 12(6). p.e0179294
One extreme fire weather event determines the extent and frequency of wildland fires
Wang Xianli,
Swystun Tom,
Oliver Jacqueline, Flannigan Mike D
Environmental Research Letters. 2021 16(11). p.114031
Universal Fractal Scaling Laws for Surface Water Bodies and Their Zones of Influence
Nagajothi K.,
Rajashekara H. M., Sagar B. S. Daya
IEEE Geoscience and Remote Sensing Letters. 2021 18(5). p.781
A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data
Lizundia-Loiola Joshua,
Otón Gonzalo,
Ramo Rubén, Chuvieco Emilio
Remote Sensing of Environment. 2020 236 p.111493
The accumulative law and its probability model: an extension of the Pareto distribution and the log-normal distribution
Feng Minyu,
Deng Liang-Jian,
Chen Feng,
Perc Matjaž, Kurths Jürgen
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 2020 476(2237).
Global environmental controls on wildfire burnt area, size, and intensity
Haas Olivia,
Prentice Iain Colin, Harrison Sandy P
Environmental Research Letters. 2022 17(6). p.065004
Projected changes in fire size from daily spread potential in Canada over the 21st century
Wang Xianli,
Studens Kala,
Parisien Marc-André,
Taylor Steve W,
Candau Jean-Noël,
Boulanger Yan, Flannigan Mike D
Environmental Research Letters. 2020 15(10). p.104048
Quantifying fire trends in boreal forests with Landsat time series and self-organized criticality
Kato Akira,
Thau David,
Hudak Andrew T.,
Meigs Garrett W., Moskal L. Monika
Remote Sensing of Environment. 2020 237 p.111525
Transitioning western U.S. dry forests to limited committed warming with bet‐hedging and natural disturbances
Baker William L.
Ecosphere. 2018 9(6).
INFERNO: a fire and emissions scheme for the UK Met Office's Unified Model
Mangeon Stéphane,
Voulgarakis Apostolos,
Gilham Richard,
Harper Anna,
Sitch Stephen, Folberth Gerd
Geoscientific Model Development. 2016 9(8). p.2685
