TECHNOLOGY TRANSFER AND REMOTE SENSING: MODELS FOR 
SUCCESS AND MODELS FOR FAILURE 
Bill Bruce and Bob Ryerson 
Canada Centre for Remote Sensing 
Energy, Mines and Resources Canada 
Ottawa, CANADA K1A 0Y7 
ABSTRACT: 
Over the past fifteen years the authors have been involved in remote sensing and technology transfer activities in over twenty countries. 
Through direct involvement and/or direct observation, a number of conclusions have been reached on the most appropriate models to lead 
to the beneficial use of remote sensing, whether working in developed or developing countries. These are discussed in this paper. 
The paper also describes a technology transfer model and the key factors associated with this model which lead to successful technology 
transfer. In addition to the routine factors which can contribute to success in technology transfer, the authors have identified a number of other 
important building blocks believed to be essential for successful technology transfer in remote sensing. In this context this paper discusses 
the role of the private or non-government sector, the need for national and international co-operation and co-ordination, the role of academe, 
the role of central R&D organizations, and a number of other factors generally not well discussed in the literature. 
In closing the paper discusses the fragility often associated with successes in remote sensing technology transfer. À slight change in the 
balance of factors may turn a dramatic success into an abject failure - or vice versa. For those who have not yet had success in seeing remote 
sensing applied beneficially in their country or region, the conclusion provides hope. To those who have had success but are tempted to 
change the mix of factors, the paper may provide useful guidance. 
KEY WORDS: Remote Sensing, Technology Transfer, Model 
1. INTRODUCTION 
This paper will provide and then illustrate a technology transfer 
model based on over fifteen years experience in remote sensing 
and technology transfer activities in over twenty countries. Through 
direct involvement and/or direct observation, a number of 
conclusions have been reached on the most appropriate models to 
lead to the beneficial use of remote sensing, whether working in 
developed or developing countries. These are discussed below in 
Section 2, with the key factors associated with this model. The 
remaining sections discuss the role of the private sector, the 
fragility of the technology transfer process, and some suggested 
approaches to improve the chances for success. 
2. MODELLING TECHNOLOGY TRANSFER 
2.1 À Model 
A model is a simplified description of a system to assist in the 
organization, comparison and, in the geographic sense, the 
visualization of information. (Chorley and Haggett, 1967) A system 
is in turn defined as a complex whole, set of connected things or 
parts. The difficulty in building a model is immediately obvious. It 
must be at the same time simple and complex. A technology 
transfer model must take into account the complexities of human 
interactions related to the adoption of technical innovations. This is 
a topic long discussed in both marketing (McCarthy and Shapiro, 
1983) and sociology. (Rogers, 1962) 
2.2 The Challenges of Modelling Remote Sensing 
The nature of remote sensing leads to further complexities in 
attempting to model related technology transfer and adoption. 
Remote sensing is not an exact science. Its relative youth and lack 
of standards leads to confusing and often conflicting claims about 
its capabilities from various proponents. For example, one finds 
advertisements about systems and imagery which all claim that 
their product is the best one for a given application. This problem 
is related in part to the fact that environment, technology and 
experience vary widely over the range of remote sensing 
applications. It is therefore very difficult to find consensus in the 
technical literature on methodology, standards, results or 
application recommendations. Indeed, the technical literature 
contains many papers which seem to claim results that are almost 
diametrically opposed to those presented in other papers. 
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Since most users or potential users do not have a sophisticated 
understanding of the technology and its application, there tends to be 
some uncertainty in the face of the conflicting claims from various 
vendors and proponents in academe, governments or industry. In 
some cases these claims can lead potential users to abandon any idea 
of using the technology, reasoning that the field is not yet mature 
enough to be used effectively. Others may adopt a particular 
technology based on the strength and nature of arguments of a 
particular vendor or proponent. In some cases pressure is brought to 
bear through either aid or diplomatic channels. Others may use the 
technology suggested by a trusted advisor. Still others may decide to 
adopt an approach which they have seen applied successfully in 
similar environments. 
Any model for technology transfer must assume that any or all of these 
decision-making influences are, or can be at play. For that reason it 
would seem reasonable to suggest there must be a built-in feedback 
mechanism which continuously evaluates success and which can stop 
or restructure a project which carries unacceptably high levels of risk. 
However, in the authors’ experience, such action has rarely been taken 
and may not be feasible in practice. The nature of decision making, 
particularly in areas of new technology, suggests that no project, 
however risk-encumbered, will ever be completely stopped once it has 
begun. In reviewing thirty-one papers on technology transfer drawn 
from the CCRS RESORS system, every paper resulted in a positive 
conclusion concerning the efficacy of remote sensing, almost 
independent of the technical results presented. It is therefore essential 
to have built into any technology transfer activity a thorough evaluation 
of the approach as a case study before any larger application is 
attempted. This phased-in approach has also been identified as a key 
element by Itten et al (1990) 
The nature of human interactions is often hard to predict, particularly 
if at the same time one is trying to describe the interactions in simple 
terms. Regardless of the complexity of human interactions, the model 
must be able to account for real-world behaviour. 
2.3 Key Factors Associated With the Model 
A number of the key factors associated with modelling technology 
transfer may not be surprising. They are generally well known and well 
documented in the literature on the diffusion of innovations. (Rogers, 
1962; MCarthy and Shapiro, 1983.) For example, there must first be 
a need which can be cost effectively met with the innovation. There 
must also be a champion and that champion or early innovator must 
be supported by early adopters, adequate training, adequate flow of