Can ISO-Defined Urban Sustainability Indicators Be Derived from Remote Sensing: An Expert Weighting Approach

Arthur Lehner, Christoph Erlacher, Matthias Schlögl, Jacob Wegerer, Thomas Blaschke and Klaus Steinnocher
Additional contact information
Arthur Lehner: Center for Energy, Austrian Institute of Technology, Vienna 1210, Austria
Christoph Erlacher: Department of Geoinformatics, University of Salzburg, Salzburg 5020, Austria
Matthias Schlögl: Transportation Infrastructure Technologies, Austrian Institute of Technology, Vienna 1210, Austria
Jacob Wegerer: Center for Energy, Austrian Institute of Technology, Vienna 1210, Austria
Thomas Blaschke: Department of Geoinformatics, University of Salzburg, Salzburg 5020, Austria
Klaus Steinnocher: Center for Energy, Austrian Institute of Technology, Vienna 1210, Austria

Sustainability, 2018, vol. 10, issue 4, 1-31

Abstract: In the context of the United Nations’ “Agenda 2030 for Sustainable Development” and the presented Sustainable Development Goals (SDGs), the process of developing and agreeing on indicators to monitor the SDGs implementation becomes fundamental. In this paper, we identify indicators for the sustainable development of cities that have the greatest potential for their underlying data to be measured by means of remote sensing. We first identified existing indicators, which are derived from the International Standard ISO 37120, “Indicators for city services and quality of life”, as being partly or fully measured by the use of remote sensing, and then presented these indicators to remote sensing experts in an assessment procedure. We then investigated Multi-Criteria Decision-Making (MCDM) weighting methods to identify the most relevant quality of life indicators that can be captured by means of remote sensing techniques. We assess the remote sensing experts’ knowledge in the context of Decision Support Systems (DSS), and by means of both a questionnaire-based approach and a pairwise comparison approach. The approaches are compared with each other regarding their complexity, their potentials and limitations, and the respectively identified remote sensing based indicators. We identified three indicators related to surface characteristics as having the highest remote sensing potential. When contrasted to the results of the pairwise comparison, the questionnaire-based approach revealed high usability and confirmability. In the end, this approach enables cities’ administrations to decide which indicators they want to cover by means of remote sensing, depending on the capacities of their departments.

Keywords: urban remote sensing; urban sustainable development; Multi-Criteria Decision-Making; uncertainty weighting; quality of life (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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