This study validates the applicability of the extended Markov chain modeling for predicting the dynamics of land use in Lebanon by using (i) the current available population density maps, (ii) Landsat satellite images, (iii) ArcGIS software and (iv) TerrSet software. An extended Markov chain model was developed to predict future land use dynamics by integrating the built-up area into three categories as per the development density based on population density maps for years 2000, 2009 and 2018. Land use classification maps were generated by integrating medium-resolution Landsat images of 30 meters into ArcGIS. The population density maps were combined with the classified land use maps in order to divide the built-up land use areas into three categories: high-, medium- and low-density urban development. The observed transition matrices were computed using TerrSet software. A Markov chain projection of land use for year 2018 was generated based on the actual transition matrix and compared to the observed land use. A Pearson’s chi-square test was conducted to validate the proposed model. Then, a projection of land use for 2036 was conducted based on the actual transition matrix between 2000 and 2018. Finally, insights and recommendations were proposed to address future Lebanese land use dynamics.

这项研究通过使用（i）当前可用的人口密度图，（ii）Landsat卫星图像，（iii）ArcGIS软件和（iv）TerrSet软件，验证了扩展的马尔可夫链模型在预测黎巴嫩土地利用动态中的适用性。通过基于2000年，2009年和2018年的人口密度图，根据发展密度将建成区划分为三类，开发了扩展的马尔可夫链模型来预测未来的土地利用动态。到ArcGIS中30米的高分辨率Landsat图像。人口密度图与分类的土地利用图相结合，以便将建成的土地利用区分为三类：高密度，中密度和低密度的城市发展。使用TerrSet软件计算观察到的跃迁矩阵。根据实际过渡矩阵生成了2018年土地利用的马尔可夫链预测，并将其与观察到的土地利用进行了比较。进行了Pearson的卡方检验以验证所提出的模型。然后，根据2000年至2018年之间的实际过渡矩阵对2036年的土地利用进行了预测。最后，提出了见解和建议，以应对黎巴嫩未来的土地利用动态。