基于GIS的地形要素插值验证及三维建模研究
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摘要
针对不同空间插值计算方法对于三维可视化建模精度差异问题,为进一步提高三维可视化效果,以重庆市某工程场区的高程数据作为样本点,基于普通克里格法、张力样条函数法、反距离加权法,根据地统计学理论与工程实际相结合,分别对高程数据进行空间插值.同时,预留部分样本点要素作为验证点进行插值精度对比,分析其插值结果及差异原因进而完成三维可视化建模与分析工作.结果表明:在本工程实例中,张力样条函数法在地表高程上插值精度最高、误差最小,其次是普通克里格法、反距离加权法.依据上述分析结果得出的最优插值方法,应用GIS(Geographic Information System)技术,在地形数据不充分的条件下完成了场区三维模型的构建,三维模型较好地反映了地表起伏和资源分布状态.
In consideration of accuracy differences of 3 Dvisualization modeling led by different spatial interpolation methods,this paper aims to further improve the three-dimensional visualization effect,taking the elevation points of a specific field in Chongqing as a sample,this paper performs spatial interpolation of elevation data respectively,based on the interpolation methods of Ordinary Kriging,Tension Spline Function,and Inverse Distance Weighting,and the combination of the geostatistics theory and engineering practice.Parts of the sample points were reserved as the verification points to compare the interpolation precision,analyze the interpolation results,and understand the causes of the differences,which were essential for the 3 Dvisualization modeling and further analysis.The results show that the Tension Spline Function method exposes the highest interpolation accuracy and the smallest error on the surface elevation,followed by Ordinary Kriging and Inverse Distance Weighting meth-ods.Using this method and GIS technology,a 3 Dmodel was constructed which properly reflects ground surface relief and distribution pattern,even though the elevation data were insufficient.
In consideration of accuracy differences of 3 Dvisualization modeling led by different spatial interpolation methods,this paper aims to further improve the three-dimensional visualization effect,taking the elevation points of a specific field in Chongqing as a sample,this paper performs spatial interpolation of elevation data respectively,based on the interpolation methods of Ordinary Kriging,Tension Spline Function,and Inverse Distance Weighting,and the combination of the geostatistics theory and engineering practice.Parts of the sample points were reserved as the verification points to compare the interpolation precision,analyze the interpolation results,and understand the causes of the differences,which were essential for the 3 Dvisualization modeling and further analysis.The results show that the Tension Spline Function method exposes the highest interpolation accuracy and the smallest error on the surface elevation,followed by Ordinary Kriging and Inverse Distance Weighting meth-ods.Using this method and GIS technology,a 3 Dmodel was constructed which properly reflects ground surface relief and distribution pattern,even though the elevation data were insufficient.
引文
[1]李新,程国栋,卢玲.空间内插方法比较[J].地球科学进展,2000(3):260-265.
[2]王璞玉,李忠勤,吴利华,等.GPR,GPS与GIS支持下的冰川厚度及冰储量分析:以天山博格达峰黑沟8号冰川为例[J].地球科学(中国地质大学学报),2012,37(S1):179-187.
[3]唐新建,任伟中,王川婴,等.多尺度数字高程模型[J].岩土力学,2006(12):2294-2298.
[4]谢谟文,柴小庆,贾宁,等.滑坡实时监测网络地理信息系统研发及应用[J].岩石力学与工程学报,2011,30(10):2090-2102.
[5]赵玉杰,师荣光,白志鹏,等.山东淄博玉米产区土壤砷含量空间变异研究[J].环境科学,2006(8):1676-1681.
[6]段祝庚,肖化顺,袁伟湘.基于离散点云数据的森林冠层高度模型插值方法[J].林业科学,2016,52(9):86-94.
[7] GEACH M R,STOKES M,TELFER M W,et al.The application of geospatial interpolation methods in the reconstruction of quaternary landform records[J].Geomorphology,2014,216(216):234-246.
[8] BEJAR Pizarro M,GUARDIOLA Albert C,GARCA Cárdenas R,et al.Interpolation of GPS and geological data using in SAR deformation maps:Method and application to land subsidence in the alto guadalentín aquifer(SE spain)[J].Remote Sensing,2016,8(11):965.
[9]宋伟涛,王旭春,张鹏,等.平朔东露天煤矿南帮边坡稳定性评价与治理研究[J].青岛理工大学学报,2016,37(1):10-16,130.
[10]鲁振宇,杨太保,郭万钦.降水空间插值方法应用研究:以黄河源区为例[J].兰州大学学报,2006(4):11-14.
[11]杜斌,王长明,贺昕宇,等.锆石Hf和全岩Nd同位素填图研究进展:以三江特提斯造山带为例[J].岩石学报,2016,32(8):2555-2570.
[12]吴聪聪,蓝贵文,耿继军,等.CAD数据向GIS数据转换的方法比较[J].测绘科学,2017,42(2):183-186.
[13]段志鹏,林进清,利锋,等.基于GIS的近海沉积物痕量元素空间分布特征插值方法选择[J].海洋环境科学,2014,33(2):262-268.
[14]彭彬,周艳莲,高苹,等.气温插值中不同空间插值方法的适用性分析:以江苏省为例[J].地球信息科学学报,2011,13(4):539-548.
[15]李杰,翟亮,桑会勇,等.PM_(2.5)浓度插值中不同空间插值方法对比[J].测绘科学,2016,41(4):50-54,101.
[2]王璞玉,李忠勤,吴利华,等.GPR,GPS与GIS支持下的冰川厚度及冰储量分析:以天山博格达峰黑沟8号冰川为例[J].地球科学(中国地质大学学报),2012,37(S1):179-187.
[3]唐新建,任伟中,王川婴,等.多尺度数字高程模型[J].岩土力学,2006(12):2294-2298.
[4]谢谟文,柴小庆,贾宁,等.滑坡实时监测网络地理信息系统研发及应用[J].岩石力学与工程学报,2011,30(10):2090-2102.
[5]赵玉杰,师荣光,白志鹏,等.山东淄博玉米产区土壤砷含量空间变异研究[J].环境科学,2006(8):1676-1681.
[6]段祝庚,肖化顺,袁伟湘.基于离散点云数据的森林冠层高度模型插值方法[J].林业科学,2016,52(9):86-94.
[7] GEACH M R,STOKES M,TELFER M W,et al.The application of geospatial interpolation methods in the reconstruction of quaternary landform records[J].Geomorphology,2014,216(216):234-246.
[8] BEJAR Pizarro M,GUARDIOLA Albert C,GARCA Cárdenas R,et al.Interpolation of GPS and geological data using in SAR deformation maps:Method and application to land subsidence in the alto guadalentín aquifer(SE spain)[J].Remote Sensing,2016,8(11):965.
[9]宋伟涛,王旭春,张鹏,等.平朔东露天煤矿南帮边坡稳定性评价与治理研究[J].青岛理工大学学报,2016,37(1):10-16,130.
[10]鲁振宇,杨太保,郭万钦.降水空间插值方法应用研究:以黄河源区为例[J].兰州大学学报,2006(4):11-14.
[11]杜斌,王长明,贺昕宇,等.锆石Hf和全岩Nd同位素填图研究进展:以三江特提斯造山带为例[J].岩石学报,2016,32(8):2555-2570.
[12]吴聪聪,蓝贵文,耿继军,等.CAD数据向GIS数据转换的方法比较[J].测绘科学,2017,42(2):183-186.
[13]段志鹏,林进清,利锋,等.基于GIS的近海沉积物痕量元素空间分布特征插值方法选择[J].海洋环境科学,2014,33(2):262-268.
[14]彭彬,周艳莲,高苹,等.气温插值中不同空间插值方法的适用性分析:以江苏省为例[J].地球信息科学学报,2011,13(4):539-548.
[15]李杰,翟亮,桑会勇,等.PM_(2.5)浓度插值中不同空间插值方法对比[J].测绘科学,2016,41(4):50-54,101.