Adapting moving-window metrics to vector datasets for the characterization and comparison of simulated urban scenarios

Abstract

Descriptive scenarios about the possible evolution of landuse in our cities are essential instruments in urban planning.Although the simulation of these scenarios has enormouspotential, further characterization is needed in order to beable to evaluate and compare them so as to provide moreeffective support for public policy. One of the most com-monly used tools for assessing these scenarios is spatialmoving-window metrics, a useful mechanism for extract-ing accurate information from simulated land-use mapson urban diversity and urban growth patterns. This articleseeks to explore this question further and has two mainaims. First, to develop and implement vSHEI and vLEI, twomultiscale composition and configuration vector moving-window metrics for calculating urban diversity and urbangrowth patterns. Second, to test these metrics using thespatially explicit simulation of three prospective scenariosin the Henares Corridor (Spain), comparing the results andanalyzing how well the scenario narratives match their spa-tial configuration, as measured using vSHEI and vLEI. Viathe implementation of vSHEI and vLEI, we obtained urbandiversity and urban expansion values at a local level, offer-ing more precise and more realistic, mappable information on the composition and configuration of urban land usethan that provided by raster metrics or by vector Patch-Matrix model metrics. We also used these metrics to testwhether the simulated scenarios matched their descriptionin the narrative storylines. Our results demonstrate the po-tential of vector moving-window metrics for characterizingthe urban patterns that might develop under different sce-narios at the parcel level.