Mapping fire-induced vegetation depletion in the Peloncillo Mountains Arizona and New Mexico

J. Rogan; S. R. YooL

doi:10.1080/01431160152558279

Mapping fire-induced vegetation depletion in the Peloncillo Mountains Arizona and New Mexico

J. Rogan, S. R. YooL

Geography, Development and Enviroment, School of

Research output: Contribution to journal › Article › peer-review

111 Scopus citations

Abstract

Forest depletions caused by fire can be detected by remote sensors if the change event causes a change in surface reflective or thermal properties. Pre and post-fire TM imagery of a semi-arid region was used to map the burn scar of a management-ignited fire into three classes of fire severity. The multitemporal imagery was enhanced using several brightness, greenness, and wetness indices. The wetness indices were most accurate at delineating fire severity because fire severity appears related to changes in plant and soil moisture content. Overall kappa for Kauth Thomas Δ wetness, the TM 7/4 index, and the second standardised Principal Component were 0.62, 0.59, and 0.61 respectively. The highest overall kappa of 0.66 was achieved using combined Kauth Thomas Δ brightness, Δ greenness and Δ wetness indices.

Original language	English (US)
Pages (from-to)	3101-3121
Number of pages	21
Journal	International Journal of Remote Sensing
Volume	22
Issue number	16
DOIs	https://doi.org/10.1080/01431160152558279
State	Published - Nov 10 2001

ASJC Scopus subject areas

Earth and Planetary Sciences(all)

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10.1080/01431160152558279

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title = "Mapping fire-induced vegetation depletion in the Peloncillo Mountains Arizona and New Mexico",

abstract = "Forest depletions caused by fire can be detected by remote sensors if the change event causes a change in surface reflective or thermal properties. Pre and post-fire TM imagery of a semi-arid region was used to map the burn scar of a management-ignited fire into three classes of fire severity. The multitemporal imagery was enhanced using several brightness, greenness, and wetness indices. The wetness indices were most accurate at delineating fire severity because fire severity appears related to changes in plant and soil moisture content. Overall kappa for Kauth Thomas Δ wetness, the TM 7/4 index, and the second standardised Principal Component were 0.62, 0.59, and 0.61 respectively. The highest overall kappa of 0.66 was achieved using combined Kauth Thomas Δ brightness, Δ greenness and Δ wetness indices.",

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AB - Forest depletions caused by fire can be detected by remote sensors if the change event causes a change in surface reflective or thermal properties. Pre and post-fire TM imagery of a semi-arid region was used to map the burn scar of a management-ignited fire into three classes of fire severity. The multitemporal imagery was enhanced using several brightness, greenness, and wetness indices. The wetness indices were most accurate at delineating fire severity because fire severity appears related to changes in plant and soil moisture content. Overall kappa for Kauth Thomas Δ wetness, the TM 7/4 index, and the second standardised Principal Component were 0.62, 0.59, and 0.61 respectively. The highest overall kappa of 0.66 was achieved using combined Kauth Thomas Δ brightness, Δ greenness and Δ wetness indices.

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Mapping fire-induced vegetation depletion in the Peloncillo Mountains Arizona and New Mexico

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