The drying up of Hamoun International Wetland (HIW) and the loss of vegetation in this area have led to an increase in ambient temperature. This research examines the changes in the surface of HIW and its role in air temperature (Tair) using data on land surface temperature (LST), vegetation, wind speed, and relative humidity. The Cubist regression model (CRM) is used to simulate the effects of land surface factors (LSFs) on Tair. Four microsites with different plant cover percentages were selected for this purpose. After data collection, 75% of the data were used for modeling and 25% of the data were used for model testing. The results showed that CRM has adequate performance for estimating Tair. The assessment of the relationship between land surface temperature (LST) and Tair at 2 meter height showed that there was a high correlation coefficient between 0.86 and 0.91 in the different microsites. The results of using CRM for estimating Tair showed that this model can estimate air temperature from independent parameters of LST, wind speed, vegetation percentage, and relative humidity with a correlation coefficient of 0.98. In this model, the LST, relative humidity, and vegetation percentage were entered with values of 100%, 93%, and 83% respectively. Wind speed was not included in the model because the measurements were constant and less than 4 m/s throughout the period (no changes).

中文翻译：

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基于地表因素的立体派气温建模（哈蒙国际湿地案例）

哈蒙国际湿地（HIW）的干涸和该地区植被的丧失导致环境温度升高。本研究利用地表温度 (LST)、植被、风速和相对湿度的数据，研究了 HIW 表面的变化及其对气温 (Tair) 的影响。使用立体回归模型（CRM）来模拟地表因子（LSF）对Tair的影响。为此选择了四个具有不同植物覆盖率的微站点。数据收集后，75%的数据用于建模，25%的数据用于模型测试。结果表明，CRM 在估计 Tair 方面具有足够的性能。对2米高度地表温度（LST）与Tair关系的评估表明，不同微站点之间存在0.86至0.91之间的较高相关系数。使用CRM估算Tair的结果表明，该模型可以根据LST、风速、植被百分比和相对湿度的独立参数估算气温，相关系数为0.98。在此模型中，输入的 LST、相对湿度和植被百分比值分别为 100%、93% 和 83%。风速未包含在模型中，因为整个期间测量值保持恒定且小于 4 m/s（无变化）。