The spectral signature of coniferous forests: the role of stand structure and leaf area index

Abstract

ABSTRACT Recently there has been an increasing interest in variables such as the leaf area index (LAI) that can be used to describe forest ecosystem processes and that can be obtained through optical remote sensing. The generic nature of remote sensing techniques and the wide range of spatial and temporal resolutions of the data sets make it possible to apply remote sensing in studying various processes and structure of a multitude of terrestrial ecosystems. The prerequisite for the development of any remote sensing application should nevertheless be an understanding of the physical principles behind the spectral signal measured by satellite- or air-borne instruments. The boreal forests of the northern hemisphere, dominated by coniferous tree species, form the largest unbroken forest zone in the world. From the perspective of remote sensing, a widely acknowledged, but poorly explained phenomenon is the generally observed lower spectral reflectances of coniferous forests when compared to broadleaved forests. The only alternative to explaining this phenomenon is studying the radiative transfer process in coniferous canopies. In this dissertation, the relationships of spectral and structural properties of boreal coniferous forests were investigated through empirical and simulation studies, and this new information was applied in LAI retrieval from optical satellite images over conifer-dominated areas in Finland. The first part assessed the effect of macro- and microscale grouping on the spectral signature of coniferous stands. Results indicated that crown size and shape are important factors influencing stand reflectance and that a main explanation for the low reflectances of conifer stands especially in the near infrared wavelengths is the high level of within-shoot scattering. The second part focused on estimating LAI from optical satellite images both using spectral vegetation indices and by inverting a physically based forest reflectance model. Both methods indicated their feasibility for LAI estimation. A general observation was that inclusion of the previously little-used middle infra-red wavelength in both retrieval methods slightly improves the remotely sensed LAI estimates for conifers.