Výsledky vyhledávání - "composite burn index (CBI)"

Akademický článek

A Study of the Effectiveness of the Composite Burn Index (CBI) in Assessing the Severity of Forest Soil Fires in Latakia Governorate

Autor: Mona Barakat, Manhal Alzoubi, Ola Merhej, Ruba Issa

Publikováno v: Syrian Journal for Science and Innovation, Vol 1, Iss 2 (2023)

The intensity of fires is a determining factor in assessing the condition of the region after the fire, as the fires that occurred on 10-9/10/2020 were extremely painful after they turned the green cover in our coastal mountains into ashes. The damag

Externí odkaz: https://doaj.org/article/c2a0e56e98c244899f61825bf74ffee6

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Akademický článek

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Akademický článek

Region-Specific Remote-Sensing Models for Predicting Burn Severity, Basal Area Change, and Canopy Cover Change following Fire in the Southwestern United States

Autor: Alicia L. Reiner, Craig Baker, Maximillian Wahlberg, Benjamin M. Rau, Joseph D. Birch

Publikováno v: Fire, Vol 5, Iss 5, p 137 (2022)

Estimates of burn severity and forest change following wildfire are used to determine changes in forest cover, fuels, carbon stocks, soils, wildlife habitat, and to evaluate fuel and fire management strategies and effectiveness. However, current remo

Externí odkaz: https://doaj.org/article/1ee6922d801740bfb555f989ff7e7220

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Akademický článek

Burned Area Detection and Burn Severity Assessment of a Heathland Fire in Belgium Using Airborne Imaging Spectroscopy (APEX)

Autor: Lennert Schepers, Birgen Haest, Sander Veraverbeke, Toon Spanhove, Jeroen Vanden Borre, Rudi Goossens

Publikováno v: Remote Sensing, Vol 6, Iss 3, Pp 1803-1826 (2014)

Uncontrolled, large fires are a major threat to the biodiversity of protected heath landscapes. The severity of the fire is an important factor influencing vegetation recovery. We used airborne imaging spectroscopy data from the Airborne Prism Experi

Externí odkaz: https://doaj.org/article/c9a1a87698c5435fa96e3dd437599a05

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Akademický článek

Vegetation and Soil Fire Damage Analysis Based on Species Distribution Modeling Trained with Multispectral Satellite Data

Autor: Carmen Quintano, Alfonso Fernández-Manso, Leonor Calvo, Dar A. Roberts

Publikováno v: Remote Sensing, Vol 11, Iss 15, p 1832 (2019)

Forest managers demand reliable tools to evaluate post-fire vegetation and soil damage. In this study, we quantify wildfire damage to vegetation and soil based on the analysis of burn severity, using multitemporal and multispectral satellite data and

Externí odkaz: https://doaj.org/article/dcf53b719c2641a88ee0a41d4880416e

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Akademický článek

Mean Composite Fire Severity Metrics Computed with Google Earth Engine Offer Improved Accuracy and Expanded Mapping Potential

Autor: Sean A. Parks, Lisa M. Holsinger, Morgan A. Voss, Rachel A. Loehman, Nathaniel P. Robinson

Publikováno v: Remote Sensing, Vol 10, Iss 6, p 879 (2018)

Landsat-based fire severity datasets are an invaluable resource for monitoring and research purposes. These gridded fire severity datasets are generally produced with pre- and post-fire imagery to estimate the degree of fire-induced ecological change

Externí odkaz: https://doaj.org/article/9e032a6b20fd42f98821c021ca537b66

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Integration of Ground Truth Data via Cloud Computing for Enhanced Burn Severity Mapping – An Example from Honduras. GI_Forum|GI_Forum 2021, Volume 1

Until now, most severity products are generated from a reclassification of dNBR index ranges. In this study, we focused on an automated global burn severity mapping approach. Using the catalogue of satellite imagery and the high-performance computing

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______386::291928df213557a46b511a83bf829215
http://epub.oeaw.ac.at/?arp=8947-3inhalt/A03_2152_RP_Ariza.pdf

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Akademický článek

Exploring the Relationship between Burn Severity Field Data and Very High Resolution GeoEye Images: The Case of the 2011 Evros Wildfire in Greece

Autor: Eleni Dragozi, Ioannis Z. Gitas, Sofia Bajocco, Dimitris G. Stavrakoudis

Publikováno v: Remote Sensing, Vol 8, Iss 7, p 566 (2016)

Monitoring post-fire vegetation response using remotely-sensed images is a top priority for post-fire management. This study investigated the potential of very-high-resolution (VHR) GeoEye images on detecting the field-measured burn severity of a for

Externí odkaz: https://doaj.org/article/fd3aadabb80a46b6a0a132fac2df6336

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Vegetation and soil fire damage analysis based on species distribution modeling trained with multispectral satellite data

Autor: Alfonso Fernández-Manso, Carmen Quintano, Dar A. Roberts, Leonor Calvo

Publikováno v: Remote Sensing
Volume 11
Issue 15
Pages: 1832
BULERIA. Repositorio Institucional de la Universidad de León
instname
UVaDOC. Repositorio Documental de la Universidad de Valladolid
Remote Sensing, Vol 11, Iss 15, p 1832 (2019)

Producción Científica
Forest managers demand reliable tools to evaluate post-fire vegetation and soil damage. In this study, we quantify wildfire damage to vegetation and soil based on the analysis of burn severity, using multitemporal and mul

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a8f90a808b8b6acab59da0cd822998e
https://doi.org/10.3390/rs11151832

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