Putting information into the service of decision making: the role of remote sensing analysis

Abstract

Outcomes from the analysis of remote sensing imagery are often used in making important decisions. These decisions may have an impact on national security, the establishment of protocols regulating the emission of greenhouse gases, the selection of a corridor for a new highway, global yield of agricultural products, etc. The objective of this paper is to provide a framework in which decisions are made to benefit society from the use of synoptic observations. First, the paper will provide a perspective on decision-making. This is necessary to be able to properly understand where the analysis techniques discussed in the workshop fit into the proposed framework. Next, the paper proposes a taxonomy that defines the link between a particular mathematical analysis technique and the higher level outcome that results from this analysis. This workshop is dedicated to David Landgrebe and an international cadre of image analysts who have pioneered new approaches to the analysis of remote sensing observations - statistical parameter estimation, multispectral and hyperspectral classification, multitemporal analysis, artificial neural network architectures and learning algorithms, among others. It is important to understand that these analysis techniques are necessary in reducing the uncertainties associated with decision-making - that remote sensing analysis is an important step in the decision-making process that has its beginning in the technology used to collect photons and culminates in a host of decision-support tools.