How much is built? Quantifying and interpreting patterns of built space from different data sources

Abstract

Land-use/cover change (LUCC) has emerged as a crucial component of applied research in remote sensing. This work compares two methodologies, based on two data sources, for assessing amounts of land transformed from open to built space in three regions in Israel. We use a decision-tree methodology to define open and built space from remotely sensed (RS) Landsat data and a geographic information systems (GIS) platform for analysing 1:50 000 scale survey maps. The methodologies are developed independently, used to quantify and characterize the spatial pattern of built space, and then analysed for their strengths and weaknesses. We then develop a method for combining the built area maps derived from each methodology, capitalizing on the strengths of each. The RS methodology had higher omission errors for built space in areas with high vegetation levels and low-density exurban development, but high commission errors in the arid region. The GIS analysis generally had fewer errors, although systematically missed built surfaces that were not specifically buildings or roads, as well as structures intentionally omitted from the maps. We recommend using maps for baseline estimates whenever possible and then complementing the estimates with clusters of built areas identified with the RS methodology. The results of this comparative study are relevant to both researchers and practitioners who need to understand the strengths and weaknesses of mapping techniques they are using.

Acknowledgements

The GIS units of the central and southern units of the Keren Kayemeth L'Israel (KKL), the Cartography Library of the Hebrew University of Jerusalem, and Yale University's Center for Earth Observation graciously provided spatial data. We thank E. Shlomi and B. Peretzman of the Survey of Israel for explaining the process of producing and updating survey maps, Alon Tal, Adi Ben-Nun and Benjamin Kedar for assistance in procuring data, Ayala Cohen for her insights regarding sampling methods and Lior Asaf for providing precipitation data. Jeremy Fisher, Lynn Carlson, Matt Vadeboncoeur and two anonymous reviewers provided excellent feedback and advice. Funding was provided through a Luce Graduate Environmental Fellowship to Daniel Orenstein.