Relationship between LAI and Landsat TM Spectral Vegetation Indices in the Texas Panhandle
2007
Gowda, P.H. | Chavez, J.L. | Colaizzi, P.D. | Howell, T.A. | Schwartz, R.C. | Marek, T.H.
Mapping and monitoring leaf area index (LAI) is important for spatially distributed modeling of surface energy balance, evapotranspiration and vegetation productivity. Remote sensing can facilitate the rapid collection of LAI information on individual fields over large areas in a time and cost-effective manner. However, there are no LAI models available for the major summer crops in the Texas Panhandle. The main objective of this study was to develop statistical relationship between LAI and Landsat Thematic Mapper (TM) based spectral vegetation indices (SVI) for major crops in the Texas Panhandle. LAI was measured in 48 randomly selected commercial fields in Moore and Ochiltree counties. Data collection was made to coincide with Landsat 5 satellite overpasses on the study area. Numerous derivations of SVIs were examined for estimating LAI using ordinary least square regression models such as linear, quadratic, power and exponential models. The R2 values for the selected models varied from 0.76 to 0.84 with the power function model based on the normalized difference between TM bands 4 and 3 (NDVI) producing the best results. Analysis of the results indicated that the SVI-LAI models based on the simple ratio i.e. the ratio of TM bands 4 and 3, and NDVI are most sensitive to LAI.
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