Paper
17 August 1998 Monitoring postfire succession in the Santa Monica mountains using hyperspectral imagery
Hong-lie Qiu, John A. Gamon, Dar A. Roberts, Marcos Luna
Author Affiliations +
Proceedings Volume 3502, Hyperspectral Remote Sensing and Application; (1998) https://doi.org/10.1117/12.317812
Event: Asia-Pacific Symposium on Remote Sensing of the Atmosphere, Environment, and Space, 1998, Beijing, China
Abstract
The varying fire frequency in the Santa Monica Mountains provides unique opportunities for examining the impacts of disturbance and succession on community composition and ecosystem function at the landscape scale. Fire resets the 'successional clock' of this evergreen-dominated ecosystem and favors early successional annuals that tend to have higher photosynthetic rates and leaf transpiration rates than mature, long-lived woody perennials. Hyperspectral sensors like the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) offer promising opportunities for remotely detecting these dynamic physiological properties in changing landscapes. Specifically, we expect altered photochemical reflectance index (PRI) and water band index (WBI) values for stands in early succession following fire. PRI and WBI from Santa Monica Mountains AVIRIS imagery indeed show complex patterns varying with season and successional state, possibly revealing varying photosynthetic activity in these dynamic, fire-prone landscapes. Further work is attempting to also consider the impact of changing canopy structure and vegetation type on physiological properties detectable with hyperspectral imagery.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hong-lie Qiu, John A. Gamon, Dar A. Roberts, and Marcos Luna "Monitoring postfire succession in the Santa Monica mountains using hyperspectral imagery", Proc. SPIE 3502, Hyperspectral Remote Sensing and Application, (17 August 1998); https://doi.org/10.1117/12.317812
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Cited by 2 scholarly publications.
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KEYWORDS
Vegetation

Whole body imaging

Reflectivity

Hyperspectral imaging

Ecosystems

Sensors

Atmospheric corrections

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