草地学报 ›› 2016, Vol. 24 ›› Issue (4): 793-801.DOI: 10.11733/j.issn.1007-0435.2016.04.012

• 研究论文 • 上一篇    下一篇

内蒙古地区草地表层土壤容重空间格局分析

乔宇鑫1,3, 朱华忠2,5, 钟华平2, 伍兆文1,3, 孟雷1, 周李磊2,4   

  1. 1. 中国农业大学生物科学院, 北京 100083;
    2. 中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室, 北京 100101;
    3. 中国科学院地理科学与资源研究所陆地表层格局与模拟院重点实验室, 北京 100101;
    4. 重庆师范大学三峡库区地表过程与环境遥感重庆市重点实验室, 重庆 400047;
    5. 江苏省地理信息资源开发与利用协同创新中心, 江苏 南京 210023
  • 收稿日期:2015-07-20 修回日期:2016-07-13 出版日期:2016-08-15 发布日期:2016-11-29
  • 通讯作者: 钟华平,E-mail:zhonghp@igsnrr.ac.cn
  • 作者简介:乔宇鑫(1993-),男,内蒙古包头人,学士,E-mail:1076998051@qq.com
  • 基金资助:

    科技部国家科技基础性工作专项(2012FY111900-2,2011FY110400-3);国家科技基础条件平台-地球系统科学数据共享平台(2005DKA32300);北京市大学生科学研究与创业行动计划项目(2015bj021)资助

Spatial Pattern Analysis on the Soil Bulk Density of Grassland in Inner Mongolia Autonomous Region, China

QIAO Yu-xin1,3, ZHU Hua-zhong2,5, ZHONG Hua-ping2, WU Zhao-wen1,3, Meng Lei1, ZHOU Li-lei2,4   

  1. 1. China Agricultural University, Beijing 100083, China;
    2. State key Laboratory of Resources and Environment Information System, Institute of Geographical Sciences and Natural Resources Researches, CAS, Beijing 100101, China;
    3. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    4. Chongqing Normal University, Chongqing Key Laboratory of Earth Surface Processes and Environmental Remote Sensing in Three Gorges Reservoir Area, Chongqing 400047, China;
    5. Jiangsu Center for Collaborative innovation in Geographic Information Resource Development and Application, Nanjing, Jiangsu Province 210023, China
  • Received:2015-07-20 Revised:2016-07-13 Online:2016-08-15 Published:2016-11-29

摘要:

本文以内蒙古地区草地表层土壤容重调查测定数据为基础,结合遥感和气候多重数据,进行草地土壤容重与海拔、年均气温、年均降雨、≥10℃积温、湿润度和NDVI等6个生态要素之间的回归分析。根据回归拟合方程,借助ArcGIS平台进行单因素插值,并通过插值预测结果与实测数据的拟合程度进行各因素对土壤容重影响的权重分析,加权叠加并综合插值出内蒙古草地土壤容重1 km×1 km栅格的空间分布图。结果表明:内蒙古地区草地土壤容重平均值为1.45 g·cm-3,其中温性荒漠类草地的土壤容重最大,为1.58 g·cm-3,温性草甸草原类土壤容重最小,为1.27 g·cm-3;空间格局上,草地表层土壤容重自东向西方向呈现由低到高逐渐递增的趋势。综合插值得到的内蒙古草地表层土壤容重空间格局图,通过预测值与实测值之间的复相关性检验,其复相关系数R2=0.6739,均方根误差(RMSE)为0.1424 g·cm-3,总体偏差为9.77%,平均预测精度达90.23%。综合空间插值结果较好地反映了内蒙古地区土壤容重空间分布情况,与土壤类型和草地类型的分布基本吻合。

关键词: 土壤容重, 回归分析, 空间插值, 空间格局, 草地, 内蒙古

Abstract:

Based on the measured data of the surface soil bulk density of 198 grassland plots in the region of Inner Mongolia and combined with remote sensing data and multiple meteorological data,this study completed the correlation analysis and regression of the soil bulk density with six ecological elements:altitude, annual average temperature, annual rainfall, ≥10℃accumulated temperature, wettability and NDVI. According to the regression fitting equation and using ArcGIS platform for single factor interpolation, the weight analyses of the 6 factors' influence on the soil bulk were conducted using the interpolation fitting degree of the predicted results and the measured data, and then finished the weighted superposition and integrated interpolation in Inner Mongolia grassland soil bulk density of 1 km×1 km grid space distribution. The results showed that the average soil bulk density of Inner Mongolia grasslands was 1.45 g·cm-3. Soil bulk density of temperate desert grassland was the largest,1.58 g·cm-3. The soil bulk density of warm meadow steppe was the minimum, 1.27 g·cm-3. The surface soil bulk density from east to west showed the tendency of gradual increase on the spatial pattern. Through complex phase test between predicted values and the measured values, the multiple correlation coefficient (R2) of the surface soil bulk density spatial pattern of Inner Mongolia grassland was 0.6739.The root mean square error (RMSE) was 0.1424 g·cm-3. The overall deviation was 9.77%. The average accuracy was 90.23%. The result of the comprehensive spatial interpolation well reflected the spatial distribution of soil bulk density in the region of Inner Mongolia and it basically agreed with the distribution of soil type and grass type.

Key words: Soil bulk density, Regression analysis, Spatial interpolation, Spatial pattern, Grassland, Inner Mongolia

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