陈永刚, 王艳霞, 杨兴娇, 等. 云南山地城镇气温空间分异的影响因素分析[J]. 西南林业大学学报(自然科学), 2022, 42(2): 130–138 . DOI: 10.11929/j.swfu.202102036
引用本文: 陈永刚, 王艳霞, 杨兴娇, 等. 云南山地城镇气温空间分异的影响因素分析[J]. 西南林业大学学报(自然科学), 2022, 42(2): 130–138 . DOI: 10.11929/j.swfu.202102036
Chen Yonggang, Wang Yanxia, Yang Xingjiao, Huang Yan, Cai Zhiyong, Zhou Ruliang. Analysis of Influencing Factors on Spatial Variation of Air Temperature in Mountain Towns in Yunnan Province[J]. Journal of Southwest Forestry University, 2022, 42(2): 130-138. DOI: 10.11929/j.swfu.202102036
Citation: Chen Yonggang, Wang Yanxia, Yang Xingjiao, Huang Yan, Cai Zhiyong, Zhou Ruliang. Analysis of Influencing Factors on Spatial Variation of Air Temperature in Mountain Towns in Yunnan Province[J]. Journal of Southwest Forestry University, 2022, 42(2): 130-138. DOI: 10.11929/j.swfu.202102036

云南山地城镇气温空间分异的影响因素分析

Analysis of Influencing Factors on Spatial Variation of Air Temperature in Mountain Towns in Yunnan Province

  • 摘要: 以云南省不同流域内典型山地城镇为分析区域,通过消除和减弱海拔、纬度因素对多年平均气温场的影响后,在同一海拔、纬度面的典型山地城镇气温场中,基于自然地理和社会经济数据,以普通最小二乘法(OLS)建立影响因素与气温分布的全局空间回归模型,以地理加权法(GWR)建立局部空间回归模型。结果表明:对山地城镇气温具有显著性影响的因素分别为城镇GDP、地形隆起高度、流域开口角度、植被指数、第三产业比值,OLS模型调整后R2可达0.789,GWR建立的局部空间回归模型更具可靠性;以预留小城镇为检验样本,对气温模型进行精度检验,消除海拔纬度方案平均绝对误差为1.09 ℃,均方根误差为1.35 ℃,消除海拔纬度的方案较单一消除海拔纬度、保留海拔纬度的方案对气温值具有更好的精度误差。研究结果反映了山地城镇自然地理格局以及人类社会活动对气温场的分布具有重要的影响。

     

    Abstract: This study takes typical mountainous towns in different basins in Yunnan Province as the analysis area. By removing and weakening the effects of altitude and latitude on the multi-year mean temperature field, in the temperature field of typical mountain towns at the same altitude and latitude, based on physical geographic and socioeconomic data, the global spatial regression model of influencing factors and temperature distribution was established by the ordinary least square(OLS), and the local spatial regression model was established by geographical weighted regression(GWR). Result shows that the main factors that had significant influence on the air temperature in mountain towns were GDP, topographic uplift height, basin opening angle, the third industry ratio and vegetation index. The R2 of the ordinary least square adjusted with the air temperature is 0.789, the local spatial regression model established by geographical weighted regression is more reliable. Taking reserved mountain towns as test samples, the independence test of the temperature model was carried out. The plan of eliminating altitude and latitude MAE is 1.09 ℃, and the RMSE is 1.35 ℃, the plan of eliminating altitude and latitude has better accuracy error to temperature than the plan of eliminating altitude and latitude only and preserving altitude and latitude only.The study reflects that the natural geographical pattern of mountain towns and human social activities play an important role in the distribution and spatial simulation of temperature field.

     

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