Project -- Drought/Fire

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Remote Sensing of Drought and Fire Potential

Introduction

The logic behind the surface moisture index has been extensively described elsewhere (see Nemani and Running, 1989).  Briefly, it relies on calculating the relationship between NDVI and Ts.  Generally, for a given landscape, as NDVI increases, Ts will decrease.  This is due to vegetation\u2019s ability to regulate Ts by partitioning absorbed radiation to latent heat flux (via evapotranspiration) rather than sensible heat flux.  Absorbed radiation and water availability are the two primary controls on Ts for a given surface.  As water becomes limited at that surface, whether vegetated or not, the absorbed energy will be partitioned to sensible heat flux and the radiant temperature of that surface will increase.  The core of the SMI logic relies on these biophysical principals for monitoring surface moisture status.  If a surface is wet, Ts will be low.  However, as that surface dries, the Ts will increase accordingly.  The relative increase in Ts is more significant in low NDVI areas, corresponding to bare soil or sparse vegetation.  In high NDVI areas the relative change in Ts is not as noticeable due to the aforementioned ability of vegetation to regulate water relations. This is particularly true of forested areas that have access to sub-surface water.  The result is a negative relationship between NDVI and Ts.  As a given area dries, we would expect the relationship between NDVI and Ts, as measured by the slope of a line fit to the Ts/NDVI scatterplot, to become increasingly negative due to an increased Ts for the low NDVI areas.  It is this relationship that is the logical basis for the fire potential and drought indices.

Ongoing Activities

Inclusion of landscape surface meteorological variables derived from gridded DAYMET surfaces will allow a more robust assesment of the remotely sensed relationship between near surface air temperature and a spectral vegetation index for assessing the surface moisture status.  This improved Surface Moisture Index (SMI) will allow conversion to more timely and rigorous analysis of drought condition and fuel moisture.  Historic analysis of SMI variability will provide context for current condition in relation to the long term changes in surface moisture.  Knowing where current condition lies relative to known historic condition will allow us to better assess drought severity and potential for fire growth.

References

Nemani, R., L. Pierce, S. Running, and S. Goward. 1993. "Developing Satellite-derived Estimates of Surface Moisture Status. Journal of Applied
Meteorology. 32(3):548-557.

Nemani, R. and S. Running. 1989. "Estimation of Regional Surface Resistance to Evapotranspiration from NDVI and Thermal-IR AVHRR
Data." Journal of Applied Meteorology. 28(4):276-284.

Riddering, James P., Seielstad, Carl A., Queen, LLoyd P. May,1999. Developing a Computationally Efficient Fire Potential Index from Satellite Derived Estimates of Surface Moisture Status.  Proceedings of the American Society of Photogrammetry and Remote Sensing Annual Conference.  Portland, Oregon.
 

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