A high-resolution fuel type mapping procedure based on satellite imagery and neural networks: Updating fuel maps for wildfire simulators

Author:

López-De-Castro MarcosORCID,Prieto-Herráez Diego,Asensio-Sevilla María Isabel,Pagnini Gianni

Funder

U.S. Department of Education

European Regional Development Fund

Horizon 2020 European Innovation Council Fast Track to Innovation

Ministerio de Economía y Competitividad

España Ministerio de Ciencia e Innovación

Junta de Castilla y León

European Commission

Eusko Jaurlaritza

Junta de Castilla y Leon Consejeria de Educacion

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geography, Planning and Development

Reference67 articles.

1. Aids to Determining Fuel Models for Estimating Fire Behavior;Anderson,1982

2. Forest fires and climate change: causes, consequences and management options;Aponte;Int. J. Wildland Fire,2016

3. Global sensitivity analysis of fuel-type-dependent input variables of a simplified physical fire spread model;Asensio;Math. Comput. Simulat.,2020

4. Phyfire: an online gis-integrated wildfire spread simulation tool based on a semiphysical model;Asensio,2020

5. Pixel-based and object-oriented approaches in segregating cocoa from forest in the Juabeso-Bia landscape of Ghana;Ashiagbor;Remote Sens. Appl.: Soc. Environ.,2020

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