地表温度与城市空间分布结构的关系及其预测模型

就城市尺度级别下的热环境进行评价,为了能够落实影响绿地规划的具体空间区域,并提供可以指导绿地布局的方法,以西安为例,量化植被、建设用地空间分布与地表温度的关系,确定绿地降温的具体区域;通过卷积计算,以温度变化为0作为界限,细化冷区和热区,提取城市微更新下绿地布局待调整的位置;基于机器学习的回归算法,由绿地、建设用地和水体分布预测作为热环境指示因子的地表温度,从而为规划的合理性提供参考。通过对研究结果的评价,以及与已有方法的比较,利用地表温度和地表覆盖变化,量化城市空间分布结构,为绿地规划提供可以落实的具体空间区域。

The Relationship between Surface Temperatureand Urban Spatial Distribution Structure and ItsPrediction Model

As for the evaluation of the thermal environment at theurban scale, to implement the specific spatial areas that affect greenplanning and provide methods that can guide the layout of greenspace, Xi''an is taken as an example to quantify the relationshipbetween the spatial distribution of vegetation and constructionland and the surface temperature, and determine the specific areasof green heat decreasing. Through convolution calculation, thetemperature change is 0 as the boundary to refine the cold andhot regions, and extract the layout adjustment location of urbanmicro-renewal space. Besides, the regression algorithm basedon machine learning is used to predict the landscape surfacetemperature including green land, construction land, and water asthe indicator of thermal environment, thus providing a referencefor the thoughtful planning. Through the evaluation of the researchresults and comparison with existing methods, the urban spatialdistribution structure can be quantified by using the changes insurface temperature and land cover, which can provide specificspatial areas as reference for green planning.