Canadian Forest Service Publications

A wetness index using terrain-corrected surface temperature and normalized difference vegetation index derived from standard MODIS products: an evaluation of its use in a humid forest-dominated region of eastern Canada. 2007. Hassan, Q.K.; Bourque, C.P-A.; Meng, F.-R.; Cox, R.M. Sensors 7: 2028-2048.

Year: 2007

Issued by: Atlantic Forestry Centre

Catalog ID: 27497

Language: English

Availability: Order paper copy (free), PDF (download)

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In this paper, we develop a method to estimate land-surface water content in a mostly forest-dominated (humid) and topographically varied region of eastern Canada. The approach is centered on a temperature-vegetation wetness index (TVWI) that uses standard 8-day MODIS-based image composites of land surface temperature (Ts) and surface reflectance as primary input. In an attempt to improve estimates of TVWI in high elevation areas, terrain-induced variations in Ts are removed by applying grid, digital elevation model-based calculations of vertical atmospheric pressure to calculations of surface potential temperature. Here, surface potential temperature corrects Ts to the temperature value to what it would be at mean sea level (i.e., ~101.3 kPa) in a neutral atmosphere. The vegetation component of the TVWI uses 8-day composites of surface reflectance in the calculation of normalized difference vegetation index (NDVI) values. TVWI and corresponding wet and dry edges are based on an interpretation of scatterplots generated by plotting surface potential temperature as a function of NDVI. A comparison of spatially averaged field measurements of volumetric soil water content (VSWC) and TVWI for the 2003-2005 period revealed that variation with time to both was similar in magnitudes. Growing season, point mean measurements of VSWC and TVWI were 31.0% and 28.8% for 2003, 28.6% and 29.4% for 2004, and 40.0% and 38.4% for 2005, respectively. An evaluation of the long-term spatial distribution of land-surface wetness generated with the new surface potential temperature-NDVI function and a process-based model of soil water content showed a strong relationship (i.e., r2 = 95.7%).