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

• Published in: Journal of geographical sciences 2012-08, Vol.22 (4), p.681-698
• Main Authors: Luo, Yanyun, Liu, Tingxi, Wang, Xixi, Duan, Limin, Zhang, Shengwei, Shi, Junxiao
• Format: Article
• Language: English
• Subjects: Agricultural land; Altitude; Asia; Bedrock; Bgi / Prodig; China; Classification; Dunes; Earth and Environmental Science; Freshwater; Geographical Information Systems/Cartography; Geography; Landforms; logistic; Nature Conservation; Physical Geography; Remote sensing; Remote Sensing/Photogrammetry; Salt lakes; Soil moisture; Watersheds; 中国土壤; 丹霞地貌; 半固定沙丘; 半流动沙丘; 地形分类; 遥感图像; 鄂尔多斯高原
• ISSN: 1009-637X; 1861-9568
• DOI: 10.1007/s11442-012-0956-8

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 K 〉 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.