Spatial modeling of land-use change in a rapidly urbanizing landscape in central Iran: integration of remote sensing, CA
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Spatial modeling of land-use change in a rapidly urbanizing landscape in central Iran: integration of remote sensing, CA-Markov, and landscape metrics Zeynab Karimzadeh Motlagh & Ali Lotfi & Saeid Pourmanafi & Saeedreza Ahmadizadeh & Alireza Soffianian
Received: 1 March 2020 / Accepted: 28 September 2020 # Springer Nature Switzerland AG 2020
Abstract In the present paper, land use/land cover (LULC) change was predicted in the Greater Isfahan area (GIA), central Iran. The GIA has been growing rapidly in recent years, and attempts to simulate its spatial expansion would be essential to make appropriate decisions in LULC management plans and achieve sustainable development. Several modeling tools were employed to outline sustainable scenarios for future dynamics of LULCs in the region. Specifically, we explored past LULC changes in the study area from 1996 to 2018 and predicted its future changes for 2030 and 2050. For this purpose, we performed objectoriented and decision tree techniques on Landsat and Sentinel-2 satellite images. The CA-Markov hybrid model was utilized to analyze past trends and predict future LULC changes. LULC changes were quantitatively measured using landscape metrics. According to the results, the majority of changes were related to increasing residential areas and decreasing irrigated
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10661-020-08647-x) contains supplementary material, which is available to authorized users. Z. K. Motlagh : A. Lotfi (*) : S. Pourmanafi : A. Soffianian Department of Natural Resources, Isfahan University of Technology, Isfahan, Iran e-mail: [email protected] S. Ahmadizadeh Department of Natural Resources and Environment, University of Birjand, Birjand, Iran
lands. The results indicated that residential lands would grow from 27,886.87 ha to 67,093.62 ha over1996– 2050 while irrigated lands decrease from 99,799.4 ha to 50,082.16 ha during the same period of time. The confusion matrix of the 2018 LULC map was built using a total of 525 ground truth points and yielded a Kappa coefficient and overall accuracy of 78% and 82%, respectively. Moreover, the confusion matrix constructed base on the Sentinel-2 map, as a reference, to judge the predicted 2018 LULC map with a Kappa coefficient of 88%. The results of this study provide useful insights for sustainable land management. The results of this research also proved the promising capability of remote sensing algorithms, CA-Markov model and landscape metrics future LULC planning in the study area. Keywords Land-use change . Satellite image processing . Sentinel-2 . CA-Markov model . Landscape metrics . Greater Isfahan area (GIA)
Introduction The rapid growth of the world’s urban population in the recent centuries has led to the expansion of urban areas (Asgarian et al. 2018); as a result, a drastic land use/land cover (LULC) change has occurred around them. Control and management of the suburban LULC change due to its destructive effects on natural environments and conse
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