The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B4-2022
https://doi.org/10.5194/isprs-archives-XLIII-B4-2022-349-2022
https://doi.org/10.5194/isprs-archives-XLIII-B4-2022-349-2022
01 Jun 2022
 | 01 Jun 2022

INDEXED 3D SCENE LAYERS (I3S) – AN EFFICIENT ENCODING AND STREAMING OGC COMMUNITY STANDARD FOR MASSIVE GEOSPATIAL CONTENT

T. Belayneh

Keywords: I3S, 3D Objects, IntegratedMesh, BVH, Massive Mesh, OGC, Compressed Texture (Basis Universal in KTX TM 2.0)

Abstract. Indexed 3D Scene Layers (I3S), an OGC Community Standard for streaming and storing massive amounts of geospatial content has been rapidly evolving to capture new use cases and techniques to advance geospatial visualization and analysis. I3S enables efficient transmission of various 3D geospatial data types including discrete 3D objects with attributes, integrated surface meshes and point cloud data covering vast geographic areas as well as highly detailed BIM (Building Information Model) content, to web browsers, mobile apps and desktop.

In this paper, we will explore multiple evolutions of I3S, including the latest, OGC I3S Version 1.2, that brings dramatic improvements in performance and scalability. We will demonstrate the advantages, including its support for a paged node access pattern, a more compact geometry layout, advanced material definitions property that supports PBR, as well as its support for supercompression of texture data using the Basis Universal SuperCompressed Texture format in KTX™2.0 containers. We will also demonstrate collaborative & research work done to dramatically improve in Basis compressed texture creation in KTX™2.0 container leveraging both the CPU and GPU – contributions that benefit both the geospatial and 3d graphics communities.

The paper will conclude by highlighting and documenting various use cases and application, where formats such as I3S are pushing the envelope in geospatial technology – by enabling seamless and ubiquitous access to vast amounts of geospatial data which traditionally have required specialized hardware and software platforms.