Version 1
: Received: 13 March 2020 / Approved: 15 March 2020 / Online: 15 March 2020 (12:50:52 CET)
How to cite:
Perez, J.; Ornon, A.; Usui, H. R Script for Classifying Patterns of Urban Growth. Preprints2020, 2020030243. https://doi.org/10.20944/preprints202003.0243.v1
Perez, J.; Ornon, A.; Usui, H. R Script for Classifying Patterns of Urban Growth. Preprints 2020, 2020030243. https://doi.org/10.20944/preprints202003.0243.v1
Perez, J.; Ornon, A.; Usui, H. R Script for Classifying Patterns of Urban Growth. Preprints2020, 2020030243. https://doi.org/10.20944/preprints202003.0243.v1
APA Style
Perez, J., Ornon, A., & Usui, H. (2020). R Script for Classifying Patterns of Urban Growth. Preprints. https://doi.org/10.20944/preprints202003.0243.v1
Chicago/Turabian Style
Perez, J., Alexandre Ornon and Hiroyuki Usui. 2020 "R Script for Classifying Patterns of Urban Growth" Preprints. https://doi.org/10.20944/preprints202003.0243.v1
Abstract
This paper presents a script that classify spatial patterns of residential urban growth using a morpho-structural approach. The script performs a combination of variography analysis and morphological closings over buildings possessing a residential function in 2002 and 2017 within a region located in southern France named Centre-Var. The different bounding regions then allow classifying new residential buildings into different categories according to their degrees of clustering/scattering and to their locations regarding existing urban areas. Preliminary results show that this protocol is able to provide useful insights regarding the degree of contribution of each new residential building to different patterns of urban growth (clustered infill, scattered infill, clustered edge-expansion, scattered edge-expansion, clustered leapfrog and scattered leapfrog). Open-access to the script and to the test region data is provided.
Social Sciences, Geography, Planning and Development
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
