The current climate changes imply the rise of the mean temperature of the cities during hot periods. To help the public policy to be more efficient about Urban Heat Island (UHI) reduction we aim to define a UHI risk indicator. To be useful at a local scale, the resolution of this index must be at the scale of the buildings – i.e. about 5 m.

The UHI risk indicator can be mapped with the use of standard methods like direct or indirect measurements, meso or micro scale simulations, or via climate zones classifications. All these methods are not applicable over a whole territory or cannot produce map with a fine resolution as expected.

We choose here to use an intermediate approach by developing a physically based simplified micro scale model to produce a UHI index (ranging between 0 and 1). This model is based on data of the territory (vector data and imagery analysis) and physical laws governing heat exchanges between sun, city and atmosphere; in ideal climatic conditions (anticyclonic, without winds and clouds).

The objective is to develop an algorithm integrated into a Geographic Information System (GIS) software like QGis with a reasonable computational time to be executed on a personal computer.

当前的气候变化意味着炎热时期城市平均气温的上升。为了帮助公共政策更有效地减少城市热岛(UHI)，我们旨在定义 UHI 风险指标。为了在局部尺度上有用，该指数的分辨率必须在建筑物的尺度上——即大约 5 m。

UHI 风险指标可以使用标准方法进行映射，例如直接或间接测量、中观或微尺度模拟，或通过气候区分类。所有这些方法都不适用于整个领土或无法按预期生成具有精细分辨率的地图。

我们在这里选择通过开发​​基于物理的简化微观模型来使用中间方法来生成UHI 指数（介于 0 和 1 之间）。该模型基于领土数据（矢量数据和图像分析）和控制太阳、城市和大气之间热交换的物理规律；在理想的气候条件下（反气旋，没有风和云）。

目标是开发一种算法，集成到地理信息系统(GIS) 软件（如QGis）中，并在个人计算机上执行合理的计算时间。