Landform classification using soil data and remote sensing in northern Ordos Plateau of China

Landform classification using soil data and remote sensing in northern Ordos Plateau of China
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鄂尔多斯高原北部土壤数据与遥感地貌分类

DOI:
10.1007/s11442-012-0956-8
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发表时间:
2012-06
影响因子:
4.9
通讯作者:
Shi Junxiao
Shi Junxiao
中科院分区:
地球科学2区
文献类型:
--
作者:
Wang Xixi;Duan Limin;Zhang Shengwei;Shi Junxiao

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地形分类通常只使用地形高度。然而,实践表明,同一海拔高度的地点可能有明显不同的地貌,这取决于这些地点下面土壤的特性。本研究的目的是:1)开发一种基于海拔和土壤特性的地貌分类方法; 2)使用该方法确定位于中国鄂尔多斯高原北方的流域内的地貌。利用在200个采样点中的134个采样点收集的数据,本研究确定了2010年获得的D10(土壤颗粒直径按重量计细10%)和长期平均土壤水分,可以从遥感图像中以合理的精度估计,可以用来代表研究流域的土壤特性。此外,采样数据显示,该流域包括9个地貌类型,即移动的沙丘(MD),移动的半移动的沙丘(SMD),滚动固定半固定沙丘(RFD),平坦桑迪(FD),草桑迪(GS),基岩(BR),平坦桑迪基岩(FSB),山谷农业用地(VA),沼泽和盐湖(SW)。使用在134个采样点收集的数据推导出一组逻辑回归方程,并使用其余66个采样点的数据进行验证。验证结果表明,该方程具有中等的分类精度(Kappa系数> 43%)。结果表明,研究区的优势地貌类型为FD(36.3%)、BR(27.0%)和MD(23.5%),而其他6种地貌类型(即SMD、RFD、GS、FSB、VA和SW)组合占13.2%。此外,在这项研究中确定的地貌进行了比较,由地质为基础的分类图所提出的类。比较结果表明,基于地质的分类不能确定多个地貌在一类是取决于土壤特性。
Landform classification is commonly done using topographic altitude only. However, practice indicates that locations at a same altitude may have distinctly different landforms, depending on characteristics of soils underneath those locations. The objectives of this study were to: 1) develop a landform classification approach that is based on both altitude and soil characteristic; and 2) use this approach to determine landforms within a watershed located in northern Ordos Plateau of China. Using data collected at 134 out of 200 sampling sites, this study determined that D10(the diameter of soil particles 10% finer by weight) and long-term average soil moisture acquired in 2010, which can be estimated at reasonable accuracy from remote sensing imagery, can be used to represent soil characteristics of the study watershed. Also, the sampling data revealed that this watershed consists of nine classes of landforms, namely mobile dune (MD), mobile semi-mobile dune (SMD), rolling fixed semi-fixed dune (RFD), flat sandy land (FD), grassy sandy land (GS), bedrock (BR), flat sandy bedrock (FSB), valley agricultural land (VA), and swamp and salt lake (SW). A set of logistic regression equations were derived using data collected at the 134 sampling sites and verified using data at the remaining 66 sites. The verification indicated that these equations have moderate classification accuracy (Kappa coefficients> 43%). The results revealed that the dominant classes in the study watershed are FD (36.3%), BR (27.0%), and MD (23.5%), while the other six types of landforms (i.e., SMD, RFD, GS, FSB, VA, and SW) in combination account for 13.2%. Further, the landforms determined in this study were compared with the classes presented by a geologically-based classification map. The comparison indicated that the geologically-based classification could not identify multiple landforms within a class that are dependent upon soil characteristics.
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