Technological driving forces of LUCC: Conceptualization, quantification, and the example of urban power distribution networks

Abstract

Consideration of technology is important for understanding the driving forces of human induced land-use and land-cover changes (LUCC). However, technological driving forces (TechDF) are seldom considered in quantitative analyses of LUCC because technology is difficult to quantify. In this paper we suggest addressing this difficulty by deducing quantification rationales from conceptualizations. We use the example of a comparative study of urban medium-voltage networks (MV networks) and urban land-use distribution to illustrate our approach. First, we outline how the effect of TechDF on LUCC can be conceptualized based on ‘contextualism’, a position concerning the role of technology in social and environmental change, and contrast this with the more common assumption of technological determinism. We outline further how MV networks can be conceptualized based on network genealogy, deduce a quantification rationale based on contextualism and network genealogy, and quantify MV networks. As a result of our case study we find that based on contextualism and network genealogy, the Tech DF of MV networks can be conceptualized as relational graphs of supplier–consumer interactions. Thus, the supplier–consumer-land-use interactions are specific for each context, for example for each city. A number of graph-theoretic measures of network topology provide a corresponding quantification rationale. Second, we use the results of a statistical analysis to discuss whether the quantification and quantification rationale for MV networks correspond to the conceptualization of MV networks based on contextualism and network genealogy. We answer this question broadly in the affirmative. Third, we discuss the issues that remain ambiguous for a conclusive answer. We also discuss the results of the statistical analysis in the light of comparative studies of urban land-use distribution. In conclusion, we regard combining conceptualization, quantification rationale, and quantification as promising in overcoming difficulties with the quantification of Tech DF in general.