Assessment Of Leaf Area Index Research Articles

Aerial Image Texture Information in the Estimation of Northern Deciduous and Mixed Wood Forest Leaf Area Index (LAI)

Leaf area index (LAI) currently may be derived from remotely sensed data with limited accuracy. This research addresses the need for increased accuracy in the estimation of LAI through integration of texture to the relationship between LAI and vegetation indices. The inclusion of texture, which acts as a surrogate for forest structure, to the relationship between LAI and the normalized difference vegetation index (NDVI) increased the accuracy of modeled LAI estimates. First-order, second-order, and a newly developed semivariance moment texture are assessed in the relationship with LAI. The ability to increase the accuracy of LAI estimates was demonstrated over a range of forest species, densities, closures, tolerances, and successional regimes. Initial assessment of LAI from spectral response over the full range of stand types demonstrated the need for stratification by stand type prior to analysis. Stratification of the stands based upon species types yields an improvement in the regression relationships. For example, deciduous hardwood stands, spanning an LAI range from ≈1.5 to 7, have a moderate initial bivariate relationship between LAI and NDVI at an r 2 of 0.42. Inclusion of additional texture statistics to the multivariate relationship between LAI and NDVI further increases the amount of variation accounted for, to an R 2 of 0.61, which represents an increase in ability to estimate hardwood forest LAI from remotely sensed imagery by approximately 20% with the inclusion of texture. Mixed forest stands, which are spectrally diverse, had an insignificant initial r 2 of 0.01 between LAI and NDVI, which improved to a significant R 2 of 0.44 with the inclusion of semivariance moment texture.

Use of in-field measurements of green leaf area and incident radiation to estimate the effects of yellow rust epidemics on the yield of winter wheat

In-field estimates of green leaf area index for treatments with varying amounts of yellow rust ( Puccinia striiformis (Westend.)) were directly proportional to laboratory measured green leaf area index ( R 2=0.75). The field technique depended on shoot counts and a leaf form factor ( F=0.83) which was derived from 20 varieties of winter wheat by relating the product of their leaf lengths and widths to leaf areas measured by a planimeter ( R 2=0.95). In two experiments at ADAS Terrington, UK, on the susceptible winter wheat variety Slejpner, epidemics of yellow rust ranged from nil to severe with 60 (1994) and 52 (1995) different combinations of fungicide dose and timing. Assessments of disease severity (%) integrated as the area under the disease progress curve accounted for yield differences within each season, but the relationship differed markedly between seasons. In-field assessments of green leaf area index integrated over time, or healthy area duration, showed a curvi-linear relationship with grain yield (1994, R 2=0.63; 1995, R 2=0.73), but any healthy area duration value in the brighter year of 1995 related to larger yields than the equivalent value in 1994. Intercepted radiation by green leaf tissue accumulated after flowering (20 June in both years), estimated through the Beer's Law analogy from field-measured green leaf area index and total incident radiation (i.e., healthy area absorption), accounted for more variation in grain yield (1994, R 2=0.80; 1995, R 2=0.92). There was no seasonal difference in the conversion coefficient between grain dry matter and the amount of incident radiation absorbed by green leaf tissue (1.4 g/MJ) but the intercepts of the relationships were sensitive to the date from which integration began. It is suggested that in-field green leaf area index assessments, interpreted through a simple model which provides estimates of differences in intercepted light energy, may prove useful in the analysis of experiments on disease control.