| 摘要: |
| 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。 |
| 关键词: 风景园林 城市热环境 地表温度 地表覆盖
物 绿地降温效应 |
| DOI： |
|
| 基金项目: |
|
| The Relationship between Surface Temperatureand Urban Spatial Distribution Structure and ItsPrediction Model |
| BAO Ruiqing |
| Abstract: |
| As for the evaluation of the thermal environment at the
urban scale, to implement the specific spatial areas that affect green
planning and provide methods that can guide the layout of green
space, Xi'an is taken as an example to quantify the relationship
between the spatial distribution of vegetation and construction
land and the surface temperature, and determine the specific areas
of green heat decreasing. Through convolution calculation, the
temperature change is 0 as the boundary to refine the cold and
hot regions, and extract the layout adjustment location of urban
micro-renewal space. Besides, the regression algorithm based
on machine learning is used to predict the landscape surface
temperature including green land, construction land, and water as
the indicator of thermal environment, thus providing a reference
for the thoughtful planning. Through the evaluation of the research
results and comparison with existing methods, the urban spatial
distribution structure can be quantified by using the changes in
surface temperature and land cover, which can provide specific
spatial areas as reference for green planning. |
| Key words: landscape architecture urban thermal environment surface temperature land cover green space cooling effect |
