Although cartography is the foundation for GIS technology, modern technology allows GIS practitioners to create and publish web mapping services, develop powerful user-intuitive applications, create interactive dashboards, and tell effective stories with data alongside narration and media. GIS tools enable the user to do more than creating maps. However, not all complex scientific data can be read easily or understood by libraries such as the Geospatial Data Abstraction Library (GDAL), which tells software what information to parse from data files and how to display them properly. These help ensure the data are formatted in a way for tools to read and write. NASA scientific data work well in GIS tools if they are created using standards such as the Hierarchical Data Format - Earth Observing System (HDF-EOS) and conventions such as Climate Forecast (CF). Often, this relies on Coordinate Systems (the values used to define a position within a spatial reference to represent location when capturing the data) as well as Projections (how the values are located and displayed on a map). GIS tools rely on information stored in data files to determine the correct method of visualization. In addition to correctly ingesting and reading these files, primary software platforms have developed new tools to aid in common workflows along with the management, analysis, and distribution of multidimensional data.įor tutorials and guidelines on using multidimensional NASA data in a GIS, visit the GIS Data Pathfinder. In recent years, GIS software has increased support for scientific data formats in their platforms. For more information about mosaic datasets, see the Esri article What are mosaic datasets? In some GIS software platforms, a single mosaic dataset can then be used to query, process, analyze, and serve data. The underlying raster data do not have to be connecting or overlapping, but can be isolated or intermittent datasets. A multidimensional mosaic dataset stores information about the dimensions and variables as fields in the mosaic dataset footprint table. A mosaic dataset is a data model that acts as a shell to input a collection of multiple raster files that include different file formats and is viewed as a single image. In tools such as QGIS and ArcGIS, support for raster data is provided using a mosaic dataset. Some of the more common cloud-ready formats include Cloud Optimized GeoTIFF (COG), Meta Raster Format (MRF), and Cloud Raster Format (CRF). These most common specialized formats include, Network Common Data Form (NetCDG), Hierarchical Data Format (HDF), and General Regularly-distributed Information in Binary (GRIB). Multidimensional data formats share common structures for storing multiple variables, with each variable being a multidimensional array in a raster format. These data associated metadata are stored in scientific data formats used by the Earth science community. Multidimensional data represent data that are acquired at different dimensions such as depths, heights, and times (z). GIS data contain spatial coordinates to represent where features are located. This is typically done using X (longitude) and Y (latitude) coordinates. They can be remotely sensed from instruments aboard airplanes and satellites, created from imagery, or acquired in the field. GIS data contain spatial coordinates to represent where features are located. Geospatial data are collected in a variety of ways. Overview of Multidimensional Data in GIS Collect The need is growing for NASA Earth science data to be in GIS-ready formats for easy integration and analysis in the primary tools employed by user communities. GIS is used in nearly all fields that need to understand the spatial patterns and relationships between different datasets, such as land-use planning, emergency response, and resource management. Remote sensing data and imagery from Earth observations can be visualized within a GIS to provide more context about any area under study.
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