College of Applied Sciences (CAS)-Nepal, Tribhuvan University, Kathmandu, 44613, Nepal.
Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran.
Environ Monit Assess. 2019 Mar 28;191(4):255. doi: 10.1007/s10661-019-7389-0.
Understanding the spatiotemporal dynamics of urbanization and predicting future growth is now essential for sustainable urban planning and policy making. This study explores future urban expansion in the rapidly growing region of eastern lowland Nepal. We used the hybrid cellular automata-Markov (CA-Markov) model, which utilizes historical land use and land cover (LULC) maps and several biophysical change driver variables to predict urban expansion for the years 2026 and 2036. Transitional area matrices were generated based on historical LULC data from 1996 to 2006, from 2006 to 2016, and from 1996 to 2016. The approach was validated by cross comparing the actual and simulated maps for 2016. Evaluation gave satisfactory values of Kno (0.89), Kstandard (0.84), and Klocation (0.89) which verifies the accuracy of the model. Hence, the CA-Markov model was utilized to simulate the LULC map for the years 2026 and 2036. The study area experienced rapid peri/urban expansion and sharp decline in area of cultivated land during 1989-2016. Built-up area increased by 110.90 km over a period of 27 years at the loss of 87.59 km cultivated land. Simulation analysis indicates that urban expansion will continue with urban cover increasing to 230 km (8.95%) and 318.51 km (12.45%) by 2026 and 2036, respectively, with corresponding declines in cultivated land to 1453.83 km (56.86%) and 1374.93 km (53.77%) for the same years. The alarming increase in urban areas coupled with loss of cultivated land will have negative implications for food security and environmental equilibrium in the region.
理解城市化的时空动态并预测未来的增长，对于可持续的城市规划和政策制定至关重要。本研究探讨了尼泊尔东部低地快速增长地区的未来城市扩张。我们使用了混合细胞自动机-马尔可夫（CA-Markov）模型，该模型利用历史土地利用和土地覆盖（LULC）地图以及几个生物物理变化驱动变量，预测了 2026 年和 2036 年的城市扩张。基于 1996 年至 2006 年、2006 年至 2016 年和 1996 年至 2016 年的历史 LULC 数据，生成了过渡区矩阵。该方法通过交叉比较 2016 年的实际和模拟地图进行了验证。评估给出了 Kno（0.89）、Kstandard（0.84）和 Klocation（0.89）的满意值，验证了模型的准确性。因此，CA-Markov 模型被用于模拟 2026 年和 2036 年的 LULC 地图。研究区域在 1989 年至 2016 年期间经历了快速的城郊扩张和耕地面积的急剧下降。在 27 年的时间里，建成区增加了 110.90 平方公里，而耕地面积减少了 87.59 平方公里。模拟分析表明，到 2026 年和 2036 年，城市扩张将继续，城市面积将分别增加到 230 平方公里（8.95%）和 318.51 平方公里（12.45%），而同期耕地面积将减少到 1453.83 平方公里（56.86%）和 1374.93 平方公里（53.77%）。城市面积的惊人增长加上耕地的减少，将对该地区的粮食安全和环境平衡产生负面影响。
