J
Jamal Jokar Arsanjani
Researcher at Aalborg University – Copenhagen
Publications - 93
Citations - 3221
Jamal Jokar Arsanjani is an academic researcher from Aalborg University – Copenhagen. The author has contributed to research in topics: Volunteered geographic information & Population. The author has an hindex of 26, co-authored 85 publications receiving 2391 citations. Previous affiliations of Jamal Jokar Arsanjani include University of Vienna & Heidelberg University.
Papers
More filters
Journal ArticleDOI
Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion
TL;DR: A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regressors of Tehran, Iran to create a probability surface of spatiotemporal states of built-up land use for the years 2006, 2016, and 2026.
Journal ArticleDOI
Fine-resolution population mapping using OpenStreetMap points-of-interest
TL;DR: An alternative approach for building level areal interpolation that uses VGI as ancillary data is presented, suggesting that VGI can be used to accurately estimate population distribution, but that further research is needed to understand how POIs can reveal population distribution patterns.
Journal ArticleDOI
Spatiotemporal simulation of urban growth patterns using agent-based modeling: The case of Tehran
TL;DR: This simulation provides strong evidence that during the next decade planning authorities will have to cope with continuous as well as heterogeneously distributed urban growth.
Journal ArticleDOI
Tracking dynamic land-use change using spatially explicit Markov Chain based on cellular automata: the case of Tehran
TL;DR: The main objective of this research is to monitor urban sprawl in the metropolis of Tehran and to assess the CA–Markov model in the simulation of land-use change, which predicts forthcoming changes over time, based on the past use of land in the research area.
Book ChapterDOI
Quality Assessment of the Contributed Land Use Information from OpenStreetMap Versus Authoritative Datasets
TL;DR: The empirical findings suggest OSM as an alternative complementary source for extracting LU information whereas exceeding 50 % of the selected cities are mapped by mappers, and strength the potential of collaboratively collected LU features for providing temporal LU maps as well as updating/enriching existing inventories.