Resources Science ›› 2017, Vol. 39 ›› Issue (3): 408-417.doi: 10.18402/resci.2017.03.03

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Computation of semantic proximity in land-use data based on feature-matching

Xiaobin JIA1(), Tinghua AI2, Zifeng PENG3   

  1. 1. The Smart City Research Institute of China Electronics Technology Group Corporation,Shenzhen 518026,China
    2. School of Resource and Environmental Sciences,Wuhan University,Wuhan 430079,China
    3. Shenzhen Municipal Planning and Land Real Estate Information Center,Shenzhen 518034,China
  • Received:2016-03-16 Revised:2016-04-30 Online:2017-03-20 Published:2017-03-20


This research aimed to compute the semantic proximity in land-use data. First,this research established a model to express the layer of details of the semantic characteristics in land-use data,started from the basic situation of land-use category and combined with characteristics of ownership. Second,feature-matching was used to gain concrete metric values by computing the matching relationship among ownership,reason of coverage,land cover type,usage,using state,nature of the stem in vegetation,habits of growth in vegetation,usage of vegetation and land use patterns. This research achieves the whole process from semantic modeling to the semantic proximity in land-use data. Third,this experiment takes 38 entities in land-use data as an example to compute semantic proximity among those with the same characteristic in ownership but different characteristic in land use type,and compares the result of the experiment with the judgment of the practical experience to discover that the result of calculations conforms to human cognition and the methods used in calculating the semantic similarity have strong practicability. Finally,the computation results of semantic proximity were transformed into a spatial measurable value to divide the land-use patch into this have the adjacent relationship in spatial position based on the semantic proximity which the area of is smaller than the threshold when the scale is change smaller in the processing of land-use data in order to demonstrate the practical value of the research findings. The results of this research can be directly applied to statistics,processing,planning,management and development of land resources,and in computing semantic proximity in land-use data to calculate semantic adjacent relationships in other related spatial geographic data.

Key words: land-use data, semantic feature, proximity, feature matching