Acta Geographica Sinica ›› 2019, Vol. 74 ›› Issue (3): 460-474.doi: 10.11821/dlxb201903005

• Land Use and Ecosystem Services • Previous Articles     Next Articles

An ecological function zoning approach coupling SOFM and SVM: A case study in Ordos

Qi MAO1(), Jian PENG1,2(), Yanxu LIU1, Wenhuan WU2, Mingyue ZHAO1, Yanglin WANG1   

  1. 1. Ministry of Education Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
    2. Key Laboratory for Environmental and Urban Sciences, School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen 518055, Guangdong, China
  • Received:2017-08-21 Revised:2018-12-05 Online:2019-03-25 Published:2019-03-19
  • Supported by:
    Commonwealth Project of Ministry of Land and Resources, No.201511001-01


It is of great significance to analyze the main environmental issues, coupled with their spatial heterogeneity, and divide the ecological function zones to achieve ecological security and optimization of territory development in a certain region. In recent years, ecological function zoning, widely concerned by scholars, has played a vital role in regional ecosystem management and sustainable development. There arose a problem that the spatial characteristics of ecological functions were hard to be reflected in the previous studies based on spatial average data over basins or geopolitical regions such as counties, cities and provinces. This paper, using the approaches of coupling self-organizing feature map (SOFM) and support vector machine (SVM), attempts to develop an automatic demarcation and zoning approach, and explores the best possible division of ecological functions in the city of Ordos with the index system of ecological function zoning in mind involving the ecosystem services as well as ecological sensitivity. Ordos, which is located in the transitional zone between temperate grasslands and desserts, has become a key research area of global terrestrial ecosystem. The ecological functional zoning indexes indicate that there appears an obvious spatial heterogeneity of ecosystem functions in Ordos. Accordingly, land grids have been clustered into 7 ecological function types by SOFM with clustering quality index (CQI) in view. Hence, Ordos has been divided into 11 ecological function zones owing to the implementation of SVM to identify the optimal division borders, in which the border demarcation is treated as a classification system in spatial domain. The optimal combination of SVM hyperparameters is determined by grid search method. In this study, machine learning algorithm has been adopted to cope with the situation where the bottom-up physical regionalization might weaken the spatial position attribute of the partition features, and to realize the quantitative conversion from classification to partition. It has turned out that such SOFM-SVM-coupled zoning approach could effectively improve the spatial accuracy of the partition, which can be considered as a new way to realize the automatic ecological zoning.

Key words: SVM, clustering quality index, boundary recognition, ecological function zoning, Ordos