Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 651-656, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-651-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 651-656, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-651-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

THE APPLICATION RESEARCH OF NATIONAL GEOGRAPHY CENSUS DATA IN THE DEPARTMENTAL INVESTIGATION AND MANAGEMENT-TAKING LAND MANAGEMENT AS AN EXAMPLE

N. Jiang N. Jiang
  • Shandong Provincial Institute of Land Surveying and Mapping, 250102, Jinan, Shandong, China

Keywords: National Geography Census Data, Land Management, Land Cover Classification Data, Spatial Transfer Matrix, Geographic National Conditions Monitoring, Yellow River Delta

Abstract. According to the "Natural priority, Status quo priority" principle of acquisition, the national geography census data has the characteristics of objectivity, impartiality and accuracy. It provides a new perspective for the management and decision-making support of other industries as a "third party" and plays an important role in the professional management and investigation of various departments including land, transportation, forestry and water conservancy. Taking land resources supervision as an example, the Yellow River Delta efficient eco-economic zone as the research area, based on the national geographic census data and the land survey data, this paper established the correspondence of the two types of data through the reclassification of the land cover classification data, calculated the spatial coincidence rate of the same land class and the circulation relations among different land classes through the spatial overlay analysis and the calculation of space transfer matrix, quantified the differences between the data and objectively analysed the causes of the differences; On this basis, combined with land supervision hot spots, supplemented by multi-source remote sensing images and socio-economic data, analysed the application of geographic census data in the land regulation from multi-point.