3d Canopy Modelling as a Tool in Remote-sensing Research

This chapter reviews the way in which 3D plant and canopy models have been used in the field of remote sensing. The focus of the chapter is on remote sensing of crops at microwave and optical wavelengths, although other applications are discussed. A brief review of remote sensing of crops is presented, followed by an evaluation of the motivation for using various types of 3D models with remotesensing data. A discussion of current issues and areas requiring future work is provided. REMOTE SENSING OF CROPS Crop monitoring using earth observation (EO) is of major importance for its potential economic value to farm managers, levying or subsidizing bodies, and commodities and futures markets. It is also of value because of the role crops and cropping practices play in wider scientific and societal issues such as the environmental impact of farm-chemical inputs and carbon sequestration (Schlesinger 1999; Robertson et al. 2000). In addition, crops serve as a useful, controlled environment in which to develop generic EO science of wider application. The key capability of remote sensing in this context is to provide regular sets of spatial observations of radiometric properties of earth surface vegetation. EO instruments can be deployed in support of crop monitoring in a variety of ways, including in-field sensors, airborne systems and satellites, obtaining information at a variety of spatial and temporal scales. Deriving estimates of state and rate variables of vegetation canopies has long been a goal of remote-sensing science. Traditionally, this has been attempted on the basis of empirical relationships between remote observations and (measured or modelled) biophysical parameters. For radar applications, relationships are usually derived by calibrating observed quantities (leaf area index (LAI), biomass etc.) with backscatter. For optical measurements, similar quantities are often related to vegetation indices, in an