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The Open Geospatial Consortium and Location Service Standards
Published in Hassan A. Karimi, Advanced Location-Based Technologies and Services, 2016
KML (formerly Keyhole Markup Language) is an XML language focused on geographic visualization, including annotation of maps and images. Geographic visualization includes not only the presentation of graphical data on the globe but also the control of the user’s navigation in the sense of where to go and where to look. In 2006, Google submitted KML to the OGC for consideration as a standard. KML was the first instance of a de facto standard being submitted into the OGC standards process and as such the OGC modified its standards approval process to accommodate standards that have been developed externally from the OGC and then submitted into the OGC process. KML was approved as an OGC standard in 2008.
Working with spatial data
Published in Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton, Texts in Statistical Science, 2017
Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
Keyhole Markup Language (KML) is an XML file format for storing geographic data. KML files can be read by Google Earth and other GIS applications. A Spatial*DataFrame object in R can be written to KML using functions from either the maptools or plotKML packages. These files can then be read by ArcGIS, Google Maps, or Google Earth. Here, we illustrate how to create a KML file for the North Carolina congressional districts data frame that we defined earlier. A screenshot of the resulting output in Google Earth is shown in Figure 14.20.
Working with geospatial data
Published in Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton, Modern Data Science with R, 2021
Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
Keyhole Markup Language (KML) is an XML file format for storing geographic data. KML files can be read by Google Earth and other GIS applications. An sf object in R can be written to KML using the st_write() function. These files can then be read by ArcGIS, Google Maps, or Google Earth. Here, we illustrate how to create a KML file for the North Carolina congressional districts data frame that we defined earlier. A screenshot of the resulting output in Google Earth is shown in Figure 17.16.
Indoor scene texturing based on single mobile phone images and 3D model fusion
Published in International Journal of Digital Earth, 2019
Hanjiang Xiong, Wei Ma, Xianwei Zheng, Jianya Gong, Douadi Abdelalim
In recent years, many indoor 3-D modeling approaches have been investigated. However, the resulting 3-D models are created in various ways and rarely follow a unified standard. Although standards like those of CityGML, OGC’s KML 2.2 (Kolbe 2009), BuildingSmart’s IFC (2014) provide the necessary data structures for the geometric expression, visualization, and properties constitution of a model; nevertheless, they do not support the interconnection relationship between distinct indoor regions. As a geospatial standard for indoor navigation applications, IndoorGML focuses on the topology and semantic information of interior spaces; however, it lacks indoor location description. Even if users are willing, many 3-D modelling approaches fail to satisfy the structural requirements of these standards, and end up not fulfilling the prerequisites, much to the detriment of indoor application optimization. In fact, this incertitude in 3-D models structures not only affects the accuracy of final products, but it also hinders the efficiency of related applications.
A comprehensive optimization strategy for real-time spatial feature sharing and visual analytics in cyberinfrastructure
Published in International Journal of Digital Earth, 2019
For data exchange and interoperability across different platforms, some commonly used vector layer output formats are supported by WFS, including GML (Geography Markup Language; Cox et al. 2002), KML (Keyhole Markup Language), GeoJSON (Butler et al. 2008), CSV (Comma-Separated Values), etc. Among these formats, GML and GeoJSON are the most commonly used. GeoJSON is designed based on the JSON (JavaScript Objective Notation) format. In GeoJSON, each feature is encoded into an object which consists of a list of key-value pairs that correspond to the name and value of feature attributes. GML is defined by the OGC to express geographic features. Inside of the GML document, the features are organized as a list of XML (eXtensible Markup Language) nodes, where the geometry and attribute information are stored in different tags.
CityGML goes mobile: application of large 3D CityGML models on smartphones
Published in International Journal of Digital Earth, 2019
Christoph Blut, Timothy Blut, Jörg Blankenbach
For visualizing CityGML on mobile devices current developments mainly focus on web-based solutions using client/server architectures and tiling systems that load chunks of data according to the current view. Gesquière and Manin (2012) and Gaillard et al. (2015) presented a WebGL™-based architecture that handles the data on a server and exports tiles with data in JSON files. Prieto, Izkara, and Delgado del Hoyo (2012), Giovannini et al. (2014) and Simões, Prandi, and De Amicis (2015) pursue similar concepts by using client/server approaches and a conversion to graphics formats such as X3D™, OBJ or KML for more efficient visualization. The increased focus on HTML5 (WebGL) solutions has introduced entire frameworks for 3D geospatial data visualizations such as Cesium and iTowns. They feature an open source JavaScript and WebGL-based virtual globe and map engine that can display terrain, image data and 3D models. Since Cesium and iTowns do not offer direct support for loading and visualizing CityGML, approaches have been described by Chaturvedi (2014) using KML or Schilling, Bolling, and Nagel (2016) using the GL Transmission Format (glTF) which are natively supported by Cesium. The initial release of glTF by the Khronos Group was in late 2015 with the goal of minimizing transmission and loading times of 3D scenes for WebGL applications. While using formats such as COLLADA, OBJ, X3D or glTF makes the rendering process using existing visualization frameworks particularly simple these pure graphics formats cannot directly store CityGML’s semantic information which eliminates what makes CityGML distinctive. Therefore, a new specification named 3D Tiles based on glTF is being developed that promises the efficiency of glTF and the possibility to store additional information. Specifically the format Batched 3D Model (B3DM) aims at displaying large city models by using batching methods while preserving the per-object properties.