i. Abstract

The “Multi-Spectral Imagery” extension defines how to encode and store reflected electromagnetic radiation from the infrared wavelengths into a CDB.  The portion of the spectrum targeted is between the visible spectrum (current imagery and texture in CDB), and longer wavelength infrared that is primarily emissive and can be simulated based on the material temperature. 

ii.          Keywords

The following are keywords to be used by search engines and document catalogues.

ogcdoc, OGC document, CDB, simulation, synthetic environment, data store, infrared, NIR, near-infrared, SWIR, short-wave infrared, imagery

iii.          Preface

Attention is drawn to the possibility that some of the elements of this document may be the subject of patent rights. The Open Geospatial Consortium shall not be held responsible for identifying any or all such patent rights.

Recipients of this document are requested to submit, with their comments, notification of any relevant patent claims or other intellectual property rights of which they may be aware that might be infringed by any implementation of the standard set forth in this document, and to provide supporting documentation.

iv.          Submitting organizations

The following organizations submitted this Document to the Open Geospatial Consortium (OGC):

The OGC CDB Standards Working Group:

http://www.opengeospatial.org/projects/groups/cdbswg

v.          Submitters

All questions regarding this submission should be directed to the editor or the submitters:

1.    Scope

The scope of this optional extension is to add non-visible reflected light energy that falls between red visible light and mid-wave infrared light energy that is primarily emissive.  This extension is limited to only adding this new data type and does not change any existing requirements or structure of the CDB.  This standard also attempts to harmonize with the existing component selectors of CDB in visual spectrum.

2.    Conformance

This standard defines requirements for a Multi-Spectral extension of CDB.

Conformance with this standard shall be checked using all the relevant tests specified in Annex A (normative) of this document. The framework, concepts, and methodology for testing, and the criteria to be achieved to claim conformance are specified in the OGC Compliance Testing Policies and Procedures and the OGC Compliance Testing web site[1].

3.    References

The following normative documents contain provisions that, through reference in this text, constitute provisions of this document. For dated references, subsequent amendments to, or revisions of, any of these publications do not apply. For undated references, the latest edition of the normative document referred to applies.

OGC: OGC 15-115r3 Volume 1 CDB Core Standard: Model and Physical Data Store Structure version 1.0, 2016. https://portal.opengeospatial.org/files/?artifact_id=72712

OGC: OGC 07-011, Abstract Specification Topic 6: The Coverage Type and its Subtypes, version 7.0 (identical to ISO 19123:2005), 2007.

OGC: OGC 09-146r6, OGC Coverage Implementation Schema (CIS), 2015.

4.    Terms and Definitions

This document uses the terms defined in Sub-clause 5.3 of [OGC 06-121r8], which is based on the ISO/IEC Directives, Part 2, Rules for the structure and drafting of International Standards. In particular, the word “shall” (not “must”) is the verb form used to indicate a requirement to be strictly followed to conform to this standard.

For the purposes of this document, the following additional terms and definitions apply.

4.1           

Coordinate Reference Systems

Coordinate system that is related to the real world by a datum

[ISO 19111:2007]

4.2           

Direct Position

Position described by a single set of coordinates within a coordinate reference system. [ISO 19123:2005]

4.3           

Spectrum

The entire range of frequencies of electromagnetic radiation, and their respective wavelengths

4.4           

Infrared (IR)

Electromagnetic radiation with wavelengths longer than those of visible light, approximately between 700 nm to 1.0 mm.  The sub-divisions within the infrared spectrum are not fixed and vary between industries.  The subdivisions used here are based on typical remote sensing usage, but are not fixed by a standard.

4.5           

Near-Infrared (NIR)

The portion of the Infrared spectrum immediately longer than red visible light.  In remote sensing applications, this is typically defined by the wavelengths detected by silicon sensors, and is usually defined as light in the 0.750 µm to 1.0 or 1.1 µm (400THz to 272 THz or 300THz) range.  This light energy is reflected by most objects.

4.6           

Short-Wavelength Infrared (SWIR)

The portion of the Infrared spectrum longer than Near Infrared.  In remote sensing applications, this is typically defined as light in the 1.0 µm to 3.0 µm (100 – 300 THz) range.  In these wavelengths, silicon is transparent and detectors are typically manufactured with gallium arsenide (GaA).  These wavelengths are reflected by most objects, although a very hot object might emit energy in this range.

4.7           

Mid-Wavelength Infrared (MWIR)

The portion of the Infrared spectrum consisting of wavelengths usually defined as 3.0 µm to 8.0 µm (37 – 100 THz). These wavelengths are typically emissive and from very hot objects, such as jet engines.

4.8           

Long-Wavelength Infrared (LWIR)

The portion of the Infrared spectrum consisting of wavelengths usually defined as 8.0 µm to 15.0 µm (20 – 37 THz). These wavelengths are typically emissive and are generated from objects slightly higher than room temperature.

4.9           

Far-Infrared (FIR)

The portion of the Infrared spectrum consisting of wavelengths between 15 µm and 1000 µm (0.3 – 20 THz)

5.    Conventions

This section provides details and examples for any conventions used in the document. Examples of conventions are symbols, abbreviations, use of XML schema, or special notes regarding how to read the document.

5.1    Identifiers

The normative provisions in this standard are denoted by the URI

http://www.opengis.net/spec/cdb-multi-spectral/1.0

All requirements and conformance tests that appear in this document are denoted by partial URIs which are relative to this base. The three letter acronym “Req” is equivalent to the above URI.

6.    Introduction

CDB defines datasets that represent the visual appearance of objects, from the terrain to buildings and trees, in the visible spectrum that humans can detect.  CDB also contains material datasets that can help create representations of other wavelengths that can be detected, such as, passively emitted heat in the Mid- or Long-Wavelength Infrared (MWIR or LWIR) or reflected Radar (radio wavelengths).  Image sensors that can detect wavelengths between the visible spectrum and Mid-Wavelength Infrared are becoming more prevalent, as is data on these wavelengths.  In addition, this portion of the spectrum is primarily reflective, so the material information is insufficient to accurately replicate these wavelengths. This portion of the spectrum contains Near Infrared (NIR) and Short-Wave Infrared (SWIR) energy.

The need for data that comprise these wavelengths comes from the increasing number of sensors and data collections in this portion of the spectrum, as well as the commercial and military uses of this data.  Several current commercial satellites collect NIR imagery, and several government satellites collect multiple bands of both NIR and SWIR imagery.  In addition, available sensors of this data include night-vision that detect light energy primarily in the NIR bands, and newer SWIR sensors that work well in low light and can “see” through haze and smoke in the atmosphere.  One characteristic of these wavelengths is that most vegetation is highly reflective of this energy, and water is highly absorptive, which can aid in better feature recognition during poor visibility conditions by pilots and flight crews.

This extension defines three large wavelength bands within the near and short wavelength infrared wavelengths to store in CDB.  The selection of these bands is influenced by the capabilities of remote sensors and the atmospheric transmission characteristics.  Several commercial and governmental satellites collect data in these ranges, while avoiding wavelengths that water vapor in the atmosphere absorbs.

6.1    Relationship to ISO 19123 and OGC Coverage Implementation Schema (Informative)

Please note: This clause is informative. For this version of CDB, all extensions and related best practices shall remain 100% backwards compatible with existing CDB implementations and CDB Versions 1.0 and 1.1. While there has been considerable effort to align CDB 1.0 and CDB 1.1 with various elements, terms and definitions, and models documented in the OGC standards baseline, more harmonization work is needed. As such, CDB Version 2.0 will incorporate normative requirements from the OGC standards baseline, including specific requirements as specified in CIS.

SWIR data can be represented by a set of regular pixels (grid cells). A SWIR data set is of type grid regular and continuous coverage. This is a coverage that returns different values for the same feature attribute at different direct positions within a single spatial object, temporal object or spatiotemporal object in its domain. [ISO 19123].

Therefore, this CDB SWIR extension is conceptually grounded in the OGC Coverage Implementation Schema (CIS). CIS specifies the OGC coverage model by establishing a concrete, interoperable, conformance-testable coverage structure. CIS is based on the abstract concepts of OGC Abstract Topic 6 (which is identical to ISO 19123). ISO 19123 specifies an abstract model for coverages which is not per se interoperable. In other words, many different and incompatible implementations of the abstract model are possible. CIS, on the other hand, is interoperable in the sense that coverages can be conformance tested, regardless of their data format encoding, down to the level of single grid cell.

Coverages can be encoded in any suitable format (such as GML, JSON, GeoTIFF, TIFF, PNG, JPEG2000, GMLJP2, or Net­CDF) and can be partitioned, e.g., for a time-interleaved representation. Coverages are independent from service definitions and, therefore, can be accessed through a variety of OGC services types, such as the Web Coverage Service (WCS) Standard. The coverage structure can serve a wide range of coverage application domains, thereby contributing to harmonization and interoperability between and across these domains. The SWIR extension uses JPEG2000 as the encoding format. JPEG2000 is used for compatibility with the current CDB standards baseline. Future version may include requirements for other encoding mechanisms that provide better performance, compression, and streaming capabilities.

More specifically, within the CDB SWIR extension, a grid of SWIR values is a type of a regular gridded coverage that has a grid as their domain set describing the direct positions in multi-dimensional coordinate space, depending on the type of grid. In the class grid-regular, simple equidistant grids are established.

7.    CDB Multi-Spectral Extension Requirement Clauses

Clause 7 defines the requirements for encoding and storing multi-spectral imagery and texture in a CDB. These dataset extensions follow the existing CDB requirements for the dataset type they occur within, as defined in the core CDB standard.

7.1    Extension Definition

7.2    Wavelength Ranges

The CDB Multi-Spectral Extension supports three spectral ranges.  The first covers Near Infrared.  The other two ranges cover the two portions of the Short-Wave Infrared band that the atmosphere is transparent to.  Roughly in the middle of the SWIR bands is a large range of wavelengths that the atmosphere (water vapor) absorbs, which is not included in these ranges.

7.3    Terrain Imagery Extension

In a CDB data store, the Visible Spectrum Terrain Imagery (VSTI) is stored in the Tiled Imagery Dataset (CDB 1.0 Volume 1, Section 5.6.2).  The new multi-spectral data files that represents the terrain imagery in the three defined wavelength bands will be stored alongside the existing VSTI using new component selector codes.  This approach also uses the existing time of year alternate representations, due to vegetation being highly reflective.

In addition, this extension defines a subordinate light map representation that is appropriate for the wavelength range.  This would represent any night-time light sources that transmit in these wavelengths, which might be different than the visual terrain light map.

7.3.1    File Type

This extension also conforms to CDB Volume 1, Section 5.6.2.1, where the file types in this dataset are JPEG2000.  These files should also adhere to CDB Volume 1 Requirements 99 & 100. Specifically, these two requirements detail:

·      The rules for metadata about the origin of data defined SHALL be implemented with a JPEG2000 image in the CDB data store; and

·      The rules for metadata about the security of data defined SHALL be implemented with a JPEG2000 image in the CDB data store.

7.3.2    Updated Terrain Imagery Table

The extended Table 5-15 is below, with the new rows and CS1 and CS2 values highlighted.

7.3.3    Default Read Value

Client-devices should default the NIR and SWIR1/SWIR2 values if the data values are not available (files associated with the appropriate wavelength covered by a tile, at a given LOD or coarser, are either missing or cannot be accessed).  The default value can be found in \CDB\Metadata\Defaults.xml and can be provided to the client-devices on demand.  In the case where the default value cannot be found, the CDB standard recommends that client-devices use a default value of half-intensity (0.5).  Note that the default values are expressed as floating-point numbers ranging from 0.0 to 1.0.  This ensures that the default is interpreted in a consistent manner independently of the data representation.

7.4    Model Texture Dataset Extension

This extension extends Table 5-8 of Section 5.3 in adding new CS1 values for all texture types that describe visible light and not physical properties.  This table contains model textures that can be found in one of the following CDB datasets:

·      301_GSModelTexture

·      511_GTModelTexture

·      601_MModelTexture

·      306_GSModelInteriorTexture

·      507_GTModelInteriorTexture

7.4.1    File Types

The file types to represent multi-spectral data should be same type as the visual representation version.

7.4.2    Updated Model Texture Table

The highlighted rows are added by this extension.