Spatial Integration Of Raster Data Based On Global Grid

With the rapid development of remote sensing detection technology,the amount of remote sensing raster data also explodes.Due to the different application fields,production departments and data acquisition methods of these remote sensing raster data,they choose different spatial references.It is an important content of current research that how to enable people of different professions and different research fields to obtain the required data conveniently and quickly from the remote sensing raster data with various types of spatial reference.For raster data,different raster data with different purposes are used for data production with different spatial references.However,this brings some difficulties for users to retrieve data.In actual use,users need to convert the retrieval area to the spatial reference where the target data is located,and the raster data need to be converted to the same spatial reference when using the data of different spatial reference in the same area.The tedious transformation of spatial reference brings many difficulties and inconveniences to users,and it is difficult to meet the demand of remote sensing big data sharing.In this paper,the spatial integration of raster data with different spatial references and the corresponding technical optimization are studied by using the global grid as a unified spatial reference framework.The main contents and achievements are as follows:1.A spatial association model of raster data based on global grid is studied.In this model,the spatial correlation between grid elements and image elements is realized by using the global grid technology and the idea of map projection numerical transformation.2.Based on the spatial correlation model,the method of raster data subdivision based on global grid is studied,and a large grid index table is designed to store the integrated information.Finally,the method of spatial integration of all kinds of raster data with different spatial references is realized,and data sets are selected to carry out the integration experiment.3.Based on multilevel grid partitioning and R-tree index,an index method for spatial integration of raster data is proposed to improve the retrieval and access performance of integrated data.Experimental results show that multilevel mixed spatial index has obvious advantages in retrieval compared with single grid index and Postgre SQL index.This paper contains 28 figures,9 tables,84 references.