PROGRESS IN GEOGRAPHY ›› 2007, Vol. 26 ›› Issue (2): 97-105.doi: 10.11820/dlkxjz.2007.02.011

• Original Articles • Previous Articles     Next Articles

Classification of Land Use Degr ee in Yunnan Province Based on SOFM Networks

YE Minting1,2, WANG Yanglin1,2, PENG Jian1,2, WU Jiansheng1,2   

  1. 1. College of Environmental Sciences, Peking University, Beijing 100871 China|
    2. The Key Laboratory for Environmental and Urban Sciences, Shenzhen Graduate School, Peking University, Shenzhen, China 518055
  • Received:2006-08-01 Revised:2007-01-01 Online:2007-03-25 Published:2007-03-25


Study on land use degree is one of the superiority fields of land arrangement and sustainable land use research. Classification of land use degree provides guidelines for utilization and conservation of regional land use as it can indicate regional differentiation regularity and existent problems. A considerable amount of research has been done on land use degree during the last decade. In this paper, Yunnan Province is taken as a case and unsupervised artificial neural network, namely Self- Organizing Feature Mapping (SOFM), is used in land use degree classification. The results indicate that classification of land use degree based on SOFM networks is a promising approach to land use studies. In this paper, Multiple Cropping Index is employed to the land use degree model so as to indicate the quality differences within a specific land use type. More improvements of the model should be brought through by further consideration. As for the data employed as input for training, not only the status quo of land use degree but also the influence factors are included. After the iterative learning phase in the SOFM analysis, six output units representing different classes of land use degree come forth, i.e., High land use degree - high population pressure - high economy pressure region, High land use degree - medium population pressure - medium economy pressure region, Low land use degree - medium population pressure - medium economy pressure region, Low land use degree - low population pressure- low economy pressure region, Medium land use degree- medium population pressurelow economy pressure region, and medium land use degree- low population pressure- low economy pressure region. Accordingly, some advice on utilization and conservation of land use is proposed based on the studying result. From the results obtained so far, it seems that SOFM is superiors over others in many aspects and has been trained to perform complex functions in various fields of application, including land use degree classification. But more improvements should be conducted before further applications.

Key words: classification, land use degree, SOFMmodel, Yunnan Province