空间插值算法在沥青路面气候分区中的应用研究——以温度参数为例
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摘要
温度是沥青路面气候分区的重要指标之一,其插值结果的精度对沥青路面气候分区影响极大。论文分别基于3种一般插值法及3种基于数字高程模型(DEM)的趋势面模拟+残差内插法对辽宁省14 a累年最热、冷月平均温度进行插值研究,对插值结果的空间分布、精度及其对沥青路面气候分区影响进行了详细的分析比较。研究结果表明:3种基于DEM的趋势面模拟+残值内插法均能反映温度随海拔高度等地形特征的变化趋势,而一般插值法则不能,且前者的精度约高于后者1倍,其中基于DEM的趋势面模拟+残值内插法中反距离插值法的精度最高,一般插值法中薄板样条法的精度最低;插值算法的精度越高,通过插值得到的温度数据与实际温度分布数据越接近,分区结果越准确。
Temperature is one of the important indicators of the asphalt pavement climatic zoning,its accuracy of the interpolation results has great influence on the asphalt pavement climate zoning.Based on three general interpolation methods and three trend surface simulation and residual interpolation methods based on digital elevation model(DEM) respectively,interpolated annual average temperature in the hottest and coldest month of 14 years in Liaoning province.The results of the interpolation space distribution,precision and its impact on the climate zoning of asphalt pavement were analyzed and compared in detail.The results showed that:three trend surface simulation and residual interpolation methods based on DEM could reflect temperature change trend with elevation and topographic features,but three general interpolation methods couldn't be,and the accuracy of the former was about higher than the latter 1 times.At the same time,the accuracy of trend surface simulation and residual interpolation methods based on DEM in inverse distance weight was highest,the accuracy of general interpolation method in spline was lowest.Last but not the least,the higher the accuracy of the interpolation,the more close to the temperature data obtained by interpolation and the actual temperature data,the more accurate the zoning results.
Temperature is one of the important indicators of the asphalt pavement climatic zoning,its accuracy of the interpolation results has great influence on the asphalt pavement climate zoning.Based on three general interpolation methods and three trend surface simulation and residual interpolation methods based on digital elevation model(DEM) respectively,interpolated annual average temperature in the hottest and coldest month of 14 years in Liaoning province.The results of the interpolation space distribution,precision and its impact on the climate zoning of asphalt pavement were analyzed and compared in detail.The results showed that:three trend surface simulation and residual interpolation methods based on DEM could reflect temperature change trend with elevation and topographic features,but three general interpolation methods couldn't be,and the accuracy of the former was about higher than the latter 1 times.At the same time,the accuracy of trend surface simulation and residual interpolation methods based on DEM in inverse distance weight was highest,the accuracy of general interpolation method in spline was lowest.Last but not the least,the higher the accuracy of the interpolation,the more close to the temperature data obtained by interpolation and the actual temperature data,the more accurate the zoning results.
引文
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[2]孙立军.沥青路面结构行为学[M].上海:同济大学出版社,2013.
[3]GB JTJ-86,公路自然区划标准[S].
[4]JTG F40-2004,公路沥青路面施工技术规范[S].
[5]JTG D50-2006,公路沥青路面设计规范[S].
[6]沈金安.道路沥青及沥青混合料的气候分区及关键性技术指标[J].中国公路学报,1997,10(1):1-9.
[7]M.W.Witc Zak.Environmental factors in long term Performance[C].
[8]Harvey J,Chong A,Roesler J.Climate region for mechanisticempirical pavement design in California and expected effects on performance[R].Berkeley:University of California at Berkeley,2000.
[9]徐超,吴大千,张治国.山东省多年气象要素空间插值方法比较研究[J].山东大学学报:理学报,2008,43(3):1-5.
[10]苗英豪,王秉纲.中国沥青路面气候影响分区方案[J].交通运输工程学报,2007,7(6):64-69.
[11]梁武星,李小刚,高超.陕西省公路沥青路面路用性能的气候分区[J].公路交通科技,2012,29(6):16-21.
[12]高国栋.西藏地区沥青路面气候分区与改性沥青适用性研究[D].西安:长安大学,2012.
[13]辽宁省地质矿产局.辽宁省区域地质志[M].北京:地质出版社,1989.
[14]Mishra U,Lal R,Slater B,et al.Predicting soil organic carbon stock using profile depth distribution functions and ordinary krig ing[J].Soil Science Society of America Journal,2009,73(2):614-621.
[15]Sangalli L M,Ramsay J O,Ramsay T O.Spatial spline regression models[J].Journal of the Royal Statistical Society:Series B(Statistical Methodology),2013,75(4):681-703.
[16]Chen F W,Liu C W.Estimation of the spatial rainfall distribution using inverse distance weighting(IDW)in the middle of Taiwan[J].Paddy and Water Environment,2012,10(3):209-222.
[17]翁笃鸣,罗哲贤.山区地形气候[M].北京:气象出版社,1990.
[18]林忠辉,莫兴国,李宏轩,等.中国陆地区域气象要素的空间插值[J].地理学报,2002,57(1):547-561.