Articles citing this paper
Pixel and object-based classification approaches for mapping forest fuel types in Tenerife Island from ASTER data
Alfonso Alonso-Benito A C , Lara A. Arroyo B , Manuel Arbelo A , Pedro Hernández-Leal A and Alejandro González-Calvo A
+ Author Affiliations
- Author Affiliations
A Grupo de Observación de la Tierra y la Atmósfera (GOTA), Departamento de Física FEES, Universidad de La Laguna, E-38206 La Laguna (S/C Tenerife), Spain.
B Centre for Human and Social Sciences, Spanish Council for Scientific Research, Albasanz 26-28, E-28037 Madrid, Spain.
C Corresponding author. Email: aaloben@ull.es
International Journal of Wildland Fire 22(3) 306-317 https://doi.org/10.1071/WF11068
Submitted: 13 May 2011 Accepted: 16 July 2012 Published: 3 October 2012
15 articles found in Crossref database.
Satellite image based methods for fuels maps updating
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII (2016)
Mapping Chestnut Stands Using Bi-Temporal VHR Data
Marchetti Francesca,
Waske Björn,
Arbelo Manuel,
Moreno-Ruíz Jose, Alonso-Benito Alfonso
Remote Sensing. 2019 11(21). p.2560
Generation of high-resolution fuel model maps from discrete airborne laser scanner and Landsat-8 OLI: A low-cost and highly updated methodology for large areas
Marino Eva,
Ranz Pedro,
Tomé José Luis,
Noriega Miguel Ángel,
Esteban Jessica, Madrigal Javier
Remote Sensing of Environment. 2016 187 p.267
Geographic Information Systems - Data Science Approach (2023)
Generation and Mapping of Fuel Types for Fire Risk Assessment
Aragoneses Elena, Chuvieco Emilio
Fire. 2021 4(3). p.59
A Multimodal Data Fusion and Deep Learning Framework for Large-Scale Wildfire Surface Fuel Mapping
Alipour Mohamad,
La Puma Inga,
Picotte Joshua,
Shamsaei Kasra,
Rowell Eric,
Watts Adam,
Kosovic Branko,
Ebrahimian Hamed, Taciroglu Ertugrul
Fire. 2023 6(2). p.36
Remote Sensing, natural hazards and the contribution of ESA Sentinels missions
Poursanidis Dimitris, Chrysoulakis Nektarios
Remote Sensing Applications: Society and Environment. 2017 6 p.25
Forest fuel type classification: Review of remote sensing techniques, constraints and future trends
Abdollahi Abolfazl, Yebra Marta
Journal of Environmental Management. 2023 342 p.118315
Classification and mapping of European fuels using a hierarchical, multipurpose fuel classification system
Aragoneses Elena,
García Mariano,
Salis Michele,
Ribeiro Luís M., Chuvieco Emilio
Earth System Science Data. 2023 15(3). p.1287
Fusion of WorldView-2 and LiDAR Data to Map Fuel Types in the Canary Islands
Alonso-Benito Alfonso,
Arroyo Lara,
Arbelo Manuel, Hernández-Leal Pedro
Remote Sensing. 2016 8(8). p.669
A Comparative Analysis of EO-1 Hyperion, Quickbird and Landsat TM Imagery for Fuel Type Mapping of a Typical Mediterranean Landscape
Mallinis Giorgos,
Galidaki Georgia, Gitas Ioannis
Remote Sensing. 2014 6(2). p.1684
Structure-level fuel load assessment in the wildland–urban interface: a fusion of airborne laser scanning and spectral remote-sensing methodologies
Skowronski Nicholas S.,
Haag Scott,
Trimble Jim,
Clark Kenneth L.,
Gallagher Michael R., Lathrop Richard G.
International Journal of Wildland Fire. 2016 25(5). p.547
A national fuel type mapping method improvement using sentinel-2 satellite data
Stefanidou Alexandra,
Gitas Ioannis Z., Katagis Thomas
Geocarto International. 2022 37(4). p.1022
Fuel type mapping using object-based image analysis of DMC and Landsat-8 OLI imagery
Stefanidou A.,
Dragozi E.,
Stavrakoudis D., Gitas I. Z.
Geocarto International. 2018 33(10). p.1064
Forest fire fuel through the lens of remote sensing: Review of approaches, challenges and future directions in the remote sensing of biotic determinants of fire behaviour
Gale Matthew G.,
Cary Geoffrey J.,
Van Dijk Albert I.J.M., Yebra Marta
Remote Sensing of Environment. 2021 255 p.112282
