Spatial modeling of land-use change in a rapidly urbanizing landscape in central Iran: integration of remote sensing, CA-Markov, and landscape metrics.

摘要: In the present paper, land use/land cover (LULC) change was predicted in Greater Isfahan area (GIA), central Iran. The GIA has been growing rapidly recent years, and attempts to simulate its spatial expansion would be essential make appropriate decisions LULC management plans achieve sustainable development. Several modeling tools were employed outline scenarios for future dynamics of LULCs region. Specifically, we explored past changes study from 1996 2018 2030 2050. For this purpose, performed object-oriented decision tree techniques on Landsat Sentinel-2 satellite images. CA-Markov hybrid model utilized analyze trends predict changes. quantitatively measured using landscape metrics. According results, majority related increasing residential areas decreasing irrigated lands. results indicated that lands grow 27,886.87 ha 67,093.62 ha over1996-2050 while decrease 99,799.4 ha 50,082.16 ha during same period time. confusion matrix map built a total 525 ground truth points yielded Kappa coefficient overall accuracy 78% 82%, respectively. Moreover, constructed base map, as reference, judge with 88%. provide useful insights management. research also proved promising capability remote sensing algorithms, metrics planning area.