Estimating vegetation dryness to optimize fire risk assessment with spot vegetation satellite data in savanna ecosystems

J. Verbesselt; B. Somers; S. Lhermitte; J. van Aardt; I. Jonckheere; P. Coppin

doi:10.1117/12.627682

18 October 2005 Estimating vegetation dryness to optimize fire risk assessment with spot vegetation satellite data in savanna ecosystems

J. Verbesselt, B. Somers, S. Lhermitte, J. van Aardt, I. Jonckheere, P. Coppin

Author Affiliations +

Proceedings Volume 5976, Remote Sensing for Agriculture, Ecosystems, and Hydrology VII; 59760D (2005) https://doi.org/10.1117/12.627682
Event: SPIE Remote Sensing, 2005, Bruges, Belgium

Abstract

The lack of information on vegetation dryness prior to the use of fire as a management tool often leads to a significant deterioration of the savanna ecosystem. This paper therefore evaluated the capacity of SPOT VEGETATION time-series to monitor the vegetation dryness (i.e., vegetation moisture content per vegetation amount) in order to optimize fire risk assessment in the savanna ecosystem of Kruger National Park in South Africa. The integrated Relative Vegetation Index approach (iRVI) to quantify the amount of herbaceous biomass at the end of the rain season and the Accumulated Relative Normalized Difference vegetation index decrement (ARND) related to vegetation moisture content were selected. The iRVI and ARND related to vegetation amount and moisture content, respectively, were combined in order to monitor vegetation dryness and optimize fire risk assessment in the savanna ecosystems. In situ fire activity data was used to evaluate the significance of the iRVI and ARND to monitor vegetation dryness for fire risk assessment. Results from the binary logistic regression analysis confirmed that the assessment of fire risk was optimized by integration of both the vegetation quantity (iRVI) and vegetation moisture content (ARND) as statistically significant explanatory variables. Consequently, the integrated use of both iRVI and ARND to monitor vegetation dryness provides a more suitable tool for fire management and suppression compared to other traditional satellite-based fire risk assessment methods, only related to vegetation moisture content.

Citation Download Citation

J. Verbesselt, B. Somers, S. Lhermitte, J. van Aardt, I. Jonckheere, and P. Coppin "Estimating vegetation dryness to optimize fire risk assessment with spot vegetation satellite data in savanna ecosystems", Proc. SPIE 5976, Remote Sensing for Agriculture, Ecosystems, and Hydrology VII, 59760D (18 October 2005); https://doi.org/10.1117/12.627682

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KEYWORDS

Vegetation

Ecosystems

Satellites

Binary data

Data modeling

Meteorology

Statistical analysis

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