基于地理国情普查与土地利用现状数据融合分析研究——以黄河三角洲地区数据为例

Data Fusion Analysis Based on Geographical Conditions Survey and Present of Land Use——Setting Data of the Yellow River Delta Area as an Example

摘要:

收集黄河三角洲地区土地利用现状数据和地理国情普查数据，将土地利用现状数据中的“DLTB”层采用场模型和地理国情普查数据中的地表覆盖分类数据“LCA”层，进行区域无缝覆盖，将这两类数据完整对应。对于无法一一对应的类别，采用“主要对应”进行对比。对于不同土地利用类别对应到国情普查中相同的类别时，类别面积不重复、不漏算。以全覆盖做全局对比，结合土地利用的其他数据、地理国情要素数据进行细类比对、专题比对。以指标体系中分类含义为基础，兼顾实际，建立两类数据对照关系。以土地利用大类为基础，对普查数据二、三级类重新归类，形成与土地利用现状数据有对照意义的“大类”。统计各类地物面积时，采用相同的方法进行统计，总结该地区两类数据存在的异同，并分析差异的原因，为两类数据的相互利用提供借鉴。

Abstract:

After collectiong land use data and surveying data of geographical conditions in the Yellow River Delta region, seamless coverage of the region has been carried out between the "DLTB" layer in the current land use data by using field model and "LCA" layer in the land cover classification data in the geographic conditions survey. The two kinds of data are corresponded completly. For the categories that cannot be corresponded onetoone, "main correspondence" should be used. When different land use categories correspond to the same category in the national conditions survey, the area of the category is not duplicated or omitted. Comparing the whole coverage with other data of land use and geographic and national conditions data, a detailed comparison and thematic comparison have been made. Based on the classification implication in the index system and taking into account the actual situation, a comparative relationship between the two types of data has been established. On the basis of land use categories, the second and third categories of survey data are reclassified to form a "big category" which has a comparative significance with the current land use data. When calculating the area of various types of land objects, the same method is used to make statistics. The similarities and differences between the two types of data in this area have been summarized, and the reasons for the differences have been analyzed, so as to provide a reference for the mutual utilization of the two types of data.