Modeling of global change phenomena with GIS using the global change data base. II: Prototype synthesis of the AVHRR-based vegetation index from terrestrial data

Abstract

Part I of this article reviewed an approach to modeling in scientific geographic information systems (GIS) by digitally synthesizing environmental parameters or phenomena as functions of other data. This interactive approach to global environmental modeling complements the approach of dynamic process models while enabling the scientist to rigorously assess the character of data used as boundary conditions in other models on widely available personal computers and workstations. Part II presents a case history using existing GISs to recreate the AVHRR-based vegetation index using data derived from in situ study on the Earth's surface. The example explores the relationship between the global vegetation index and ecosystems, soils, and precipitation, and defects in our present ability to describe these features. The degree of success of the model shows that GIS and the global change data base can be effective modeling tools, especially when functions are added to enhance the modeling capabilities of GIS. One function, INDEX, developed for this case history, is a simple utility that models a single data set as a function of another data set. A second function THEMCOIN, takes two input categorical data sets, such as vegetation and soils maps, and computes the mean and standard deviation of a third input data set of numerical values, such as elevation, precipitation, or vegetation index computed from AVHRR data. THEMCOIN outputs a table of these empirical relationships. It also optionally models the numerical data set based on correlations with the categorical data sets. Both of these functions facilitate environmental modeling in GIS. The models begin to approximate vegetation index as a function of ecosystem, precipitation, and soils. Statistical output from the models extends our understanding of relationships between environmental parameters.