Allows: multiple feature classes topology. Spatial and nonspatial objects created by ArcGIS. Standalone relational database, SpatiaLite is the spatial extension of SQLite. Text format where the first six lines represent the raster header, followed by the raster cell values arranged in rows and columns. A TIFF file containing additional spatial metadata. Single file format allowing for quick reading and writing of vector data. XML schema created for exchange of GPS data. XML-based format for spatial visualization, developed for use with Google Earth. No support for: files > 2GB mixed types names > 10 chars cols > 255.Įxtends the JSON exchange format by including a subset of the simple feature representation mostly used for storing coordinates in longitude and latitude it is extended by the TopoJSON format Popular format consisting of at least three files. TABLE 8.1: TABLE 8.2: Selected spatial file formats. Table 8.1 presents some basic information about selected and often used spatial file formats. GDAL provides access to more than 200 vector and raster data formats. Many open and proprietary GIS programs, including GRASS GIS, ArcGIS and QGIS, use GDAL behind their GUIs for doing the legwork of ingesting and spitting out geographic data in appropriate formats. GDAL provides a unified and high-performance interface for reading and writing of many raster and vector data formats. GDAL (which should be pronounced “goo-dal”, with the double “o” making a reference to object-orientation), the Geospatial Data Abstraction Library, has resolved many issues associated with incompatibility between geographic file formats since its release in 2000. Today the variety of file formats may seem bewildering but there has been much consolidation and standardization since the beginnings of GIS software in the 1960s when the first widely distributed program ( SYMAP) for spatial analysis was created at Harvard University ( Coppock and Rhind 1991). Geographic datasets are usually stored as files or in spatial databases.įile formats can either store vector or raster data, while spatial databases such as PostGIS can store both (see also Section 10.7). The final Section 8.9 demonstrates methods for saving visual outputs (maps), in preparation for Chapter 9 on visualization. If you want to put your data ‘into production’ in web services (or if you want be sure that your data adheres to established standards), geographic metadata is important, as described in Section 8.7.Īnother possibility to obtain spatial data is to use web services, outlined in Section 8.8. In terms of where to find data, Section 8.5 describes geoportals and how to import data from them.ĭedicated packages to ease geographic data import, from sources including OpenStreetMap, are described in Section 8.6. Reading and writing from and to these file formats is covered in Sections 8.3 and 8.4, respectively. There are many geographic file formats, each with their own advantages and disadvantages, as described in Section 8.2. However, data import and export are fundamental to the success or otherwise of projects: small I/O mistakes made at the beginning of projects (e.g., using an out-of-date dataset) can lead to large problems later down the line. Geographic data I/O is often done in haste at the beginning and end of projects and otherwise ignored. Taken together, these processes of input/output can be referred to as data I/O. Geographic data input is essential for geocomputation: real-world applications are impossible without data.ĭata output is also vital, enabling others to use valuable new or improved datasets resulting from your work. This chapter is about reading and writing geographic data.
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