The relationship between effective plant area index and Landsat spectral response across elevation, solar insolation, and spatial scales in a northern Idaho forest

Abstract

Leaf area index (LAI) is an important forest characteristic related to photosynthesis and carbon sequestration, and gains in efficiency for LAI measurements are possible using remotely sensed imagery. However, the potential effects of complex topography on this measurement system are not well understood. Our objective was to understand how complex terrain and measurement aggregation influence the relationship between LAI and remotely sensed vegetation indices across a mountainous conifer forest. We identified NDVIc, a middle-infrared (MIR) correction to NDVI (Normalized Difference Vegetation Index), as the vegetation index providing the best prediction of effective plant area index (PAIe), u..