Urban sprawl is a ubiquitous with a complex network of driving forces and human and natural impacts on various scales of the coupled human-environment urban system. In Germany, a land consumption of 30 ha per day is envisaged. In that regard, the effect of growing metropolitan areas on the climate of local neighborhoods becomes more and more a topic in regional planning. Accordingly, the objectives of the study are a) to contribute to the climate change related land cover simulation efforts in Germany in a spatially explicit manner with a resolution of 30 m, b) to investigate future land consumption rates and population growth rates having a view on goal 11 of UN’s SDG, and c) analyze the spatial impact of planning policies in regard to land use planning and official climate change prevention strategies using Rhine-Ruhr Metropolitan Area (RRMA) in Western Germany as a study area. The study makes use of land use and land cover classification of multispectral satellite data and the derivation of land surface temperature based on Landsat satellite in order to calibrate and validate the urban growth model SUSM (scenario-based urban growth simulation model). Two scenarios for future land consumption 2030 are implemented and the future impacts of urban growth with the projection of land consumption rate (LCR), population growth rate (PGR), and LCRPGR index on municipality level, as well as the impact on regions vulnerable to climate change evaluated. The comparison of simulated urban growth to observed urban growth from 2005 to 2017 shows that the PA of SUSM for historic scenario is 68.06% with an overall accuracy of 97.15%, a Matthews correlation coefficient of 0.66, a figure of merit of 0.51 and area under curve of 0.84. The total quantity of new urban areas of our SUSM simulation 2030 were approximately 283 km². While the difference in the simulated total quantity is nearly zero, the simulated allocation of new urban areas across the districts can differ by up to 25 km² in the two scenarios. The number of municipalities with efficient urban land development rates increases in the SUSM scenario where no regional land development plan has been incorporated. This holds true for the number of municipalities with inefficient land use where even an increase from no plan to plan can be observed. LCRPGR is negative in most municipalities reflecting opposing trends of population and land consumption development. Most of new urban areas are distributed in open spaces important for the regional climate change prevention strategy. 32.98 % of new urban areas in our region of interest can be found in these zones in the planning scenario and 25.76 % in the scenario without planning information in SUSM model. It can be concluded that regional planning in RRMA region has no positive effect on the interregional development of future land consumption in terms of quantity, allocation, and impact on climate change prevention.

城市蔓延无处不在，具有复杂的驱动力网络以及人类和自然对耦合的人类-环境城市系统的各种规模的影响。在德国，预计每天消耗 30 公顷的土地。在这方面，不断增长的大都市区对当地社区气候的影响越来越成为区域规划中的一个话题。因此，该研究的目标是 a) 以 30 m 的分辨率以空间明确的方式为德国与气候变化相关的土地覆盖模拟工作做出贡献，b) 调查未来的土地消耗率和人口增长率，有一个观点关于联合国可持续发展目标的目标 11，c) 以德国西部的莱茵-鲁尔都市区 (RRMA) 作为研究区域，分析有关土地利用规划和官方气候变化预防战略的规划政策的空间影响。该研究利用多光谱卫星数据的土地利用和土地覆盖分类以及基于Landsat卫星的地表温度推导，对城市增长模型SUSM（基于情景的城市增长模拟模型）进行校准和验证。实施了 2030 年未来土地消耗的两种情景，并通过城市层面的土地消耗率 (LCR)、人口增长率 (PGR) 和 LCRPGR 指数预测城市增长的未来影响，以及对脆弱地区的影响气候变化评估。模拟城市增长与 2005 年至 2017 年观察到的城市增长的比较表明，SUSM 对历史情景的 PA 为 68.06%，总体准确度为 97.15%，马修斯相关系数为 0.66，品质因数为 0.51，面积为0.84 的曲线。我们的 SUSM 模拟 2030 的新城区总量约为 283 公里² . 虽然模拟总量的差异几乎为零，但不同地区的新城区的模拟分配差异可能高达 25 公里²在这两种情况下。在没有纳入区域土地开发计划的 SUSM 情景中，具有有效城市土地开发率的城市数量增加。这适用于土地利用效率低下的城市数量，甚至可以观察到从无规划到规划的增加。大多数城市的 LCRPGR 为负，反映了人口和土地消费发展的相反趋势。大多数新城区分布在对区域气候变化预防战略很重要的开放空间中。在我们感兴趣的区域中，32.98% 的新城区可以在规划场景中的这些区域中找到，在 SUSM 模型中没有规划信息的场景中可以找到 25.76%。