Journal of Geographical Sciences ›› 2019, Vol. 29 ›› Issue (11): 1841-1858.doi: 10.1007/s11442-019-1992-0

• Research Articles • Previous Articles     Next Articles

The spatial local accuracy of land cover datasets over the Qiangtang Plateau, High Asia

LIU Qionghuan1,2, ZHANG Yili1,2,3,*(), LIU Linshan1, LI Lanhui1,2, QI Wei1   

  1. 1.Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2.University of Chinese Academy of Sciences, Beijing 100049, China
    3.CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China
  • Received:2018-05-27 Accepted:2019-02-12 Online:2019-11-25 Published:2019-12-05
  • Contact: Yili ZHANG E-mail:zhangyl@igsnrr.ac.cn
  • About author:Liu Qionghuan, PhD Candidate, E-mail: liuqionghuan@yeah.net
  • Supported by:
    The Strategic Priority Research Program of the Chinese Academy of Sciences(Nos. XDA20040200);The Strategic Priority Research Program of the Chinese Academy of Sciences(XDB03030500);Key Foundation Project of Basic Work of the Ministry of Science and Technology of China(No. 2012FY111400);National Key Technologies R & D Program(No. 2012BC06B00)

Abstract:

We analyzed the spatial local accuracy of land cover (LC) datasets for the Qiangtang Plateau, High Asia, incorporating 923 field sampling points and seven LC compilations including the International Geosphere Biosphere Programme Data and Information System (IGBPDIS), Global Land cover mapping at 30 m resolution (GlobeLand30), MODIS Land Cover Type product (MCD12Q1), Climate Change Initiative Land Cover (CCI-LC), Global Land Cover 2000 (GLC2000), University of Maryland (UMD), and GlobCover 2009 (GlobCover). We initially compared resultant similarities and differences in both area and spatial patterns and analyzed inherent relationships with data sources. We then applied a geographically weighted regression (GWR) approach to predict local accuracy variation. The results of this study reveal that distinct differences, even inverse time series trends, in LC data between CCI-LC and MCD12Q1 were present between 2001 and 2015, with the exception of category areal discordance between the seven datasets. We also show a series of evident discrepancies amongst the LC datasets sampled here in terms of spatial patterns, that is, high spatial congruence is mainly seen in the homogeneous southeastern region of the study area while a low degree of spatial congruence is widely distributed across heterogeneous northwestern and northeastern regions. The overall combined spatial accuracy of the seven LC datasets considered here is less than 70%, and the GlobeLand30 and CCI-LC datasets exhibit higher local accuracy than their counterparts, yielding maximum overall accuracy (OA) values of 77.39% and 61.43%, respectively. Finally, 5.63% of this area is characterized by both high assessment and accuracy (HH) values, mainly located in central and eastern regions of the Qiangtang Plateau, while most low accuracy regions are found in northern, northeastern, and western regions.

Key words: land cover datasets, spatial accuracy assessment, remote sensing, Qiangtang Plateau, High Asia