ISO/TS 19163-1:2016
(Main)Geographic information — Content components and encoding rules for imagery and gridded data — Part 1: Content model
Geographic information — Content components and encoding rules for imagery and gridded data — Part 1: Content model
ISO/TS 19163-1:2016 classifies imagery and regularly spaced gridded thematic data into types based on attribute property, sensor type and spatial property, and defines an encoding-neutral content model for the required components for each type of data. It also specifies logical data structures and the rules for encoding the content components in the structures. The binding between the content and a specific encoding format will be defined in the subsequent parts of ISO 19163. ISO/TS 19163-1:2016 does not address LiDAR, SONAR data and ungeoreferenced gridded data. The logical data structures and the rules for encoding the content components will be addressed in the subsequent parts of ISO 19163.
Information géographique — Composantes de contenu et règles de codage pour l'imagerie et les données maillées — Partie 1: Modèle de contenu
Geografske informacije - Komponente vsebin in pravila kodiranja za podobe in mrežne podatke - 1. del: Vzorec vsebine
Ta tehnična specifikacija razvršča podobe in enakomerno razporejene tematske podatke v vrste na podlagi lastnosti atributov, vrste senzorja in prostorske lastnosti, ter določa kodirno nevtralen vzorec vsebine za zahtevane komponente posamezne vrste podatkov. Določa tudi strukture logičnih podatkov in pravila za kodiranje komponent vsebine v strukturah.
Povezava med vsebino in določenim formatom kodiranja bo določena v nadaljnjih delih standarda ISO 19163.
Ta tehnična specifikacija ne obravnava podatkov LiDAR, SONAR in negeoreferenčnih mrežnih podatkov.
Strukture logičnih podatkov in pravila za kodiranje komponent vsebine bodo obravnavana v nadaljnjih delih standarda ISO 19163.
General Information
Standards Content (Sample)
SLOVENSKI STANDARD
01-junij-2017
Geografske informacije - Komponente vsebin in pravila kodiranja za podobe in
mrežne podatke - 1. del: Vzorec vsebine
Geographic information -- Content components and encoding rules for imagery and
gridded data -- Part 1: Content model
Information géographique -- Composantes de contenu et règles de codage pour
l'imagerie et les données maillées -- Partie 1: Modèle de contenu
Ta slovenski standard je istoveten z: ISO/TS 19163-1:2016
ICS:
07.040 Astronomija. Geodezija. Astronomy. Geodesy.
Geografija Geography
35.240.70 Uporabniške rešitve IT v IT applications in science
znanosti
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.
TECHNICAL ISO/TS
SPECIFICATION 19163-1
First edition
2016-01-15
Geographic information — Content
components and encoding rules for
imagery and gridded data —
Part 1:
Content model
Information géographique — Composantes de contenu et règles de
codage pour l’imagerie et les données maillées —
Partie 1: Modèle de contenu
Reference number
©
ISO 2016
© ISO 2016, Published in Switzerland
All rights reserved. Unless otherwise specified, no part of this publication may be reproduced or utilized otherwise in any form
or by any means, electronic or mechanical, including photocopying, or posting on the internet or an intranet, without prior
written permission. Permission can be requested from either ISO at the address below or ISO’s member body in the country of
the requester.
ISO copyright office
Ch. de Blandonnet 8 • CP 401
CH-1214 Vernier, Geneva, Switzerland
Tel. +41 22 749 01 11
Fax +41 22 749 09 47
copyright@iso.org
www.iso.org
ii © ISO 2016 – All rights reserved
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Conformance . 1
3 Normative references . 1
4 Terms and definitions . 2
5 Symbols and abbreviated terms . 4
5.1 Abbreviated terms . 4
5.2 UML notations . 4
6 Related International Standards . 5
7 Categories of imagery and gridded data . 6
7.1 General . 6
7.2 Imagery . 7
7.3 Gridded data . 8
8 Content component models . 8
8.1 General . 8
8.2 Imagery and gridded data . 8
8.2.1 General. 8
8.2.2 IE_ImageryAndGriddedData . 9
8.2.3 IE_Georectified . 9
8.2.4 IE_Georeferenceable .10
8.3 Thematic gridded data .10
8.3.1 IE_ThematicGriddedData .10
8.3.2 IE_CategoricalGriddedData .10
8.3.3 IE_NumericalGriddedData .10
8.4 Imagery .11
8.4.1 IE_Imagery.11
8.4.2 IE_FusedImage .13
8.4.3 IE_SimulatedImage .13
8.4.4 IE_OpticalImage .13
8.4.5 IE_MicrowaveData .13
8.4.6 IE_SARData.14
8.4.7 IE_RadiometerData .15
9 General approach for encoding (informative) .16
Annex A (normative) Abstract test suite .18
Annex B (normative) Data dictionary of content component models .21
Bibliography .38
Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out
through ISO technical committees. Each member body interested in a subject for which a technical
committee has been established has the right to be represented on that committee. International
organizations, governmental and non-governmental, in liaison with ISO, also take part in the work.
ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of
electrotechnical standardization.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular the different approval criteria needed for the
different types of ISO documents should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www.iso.org/directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of
any patent rights identified during the development of the document will be in the Introduction and/or
on the ISO list of patent declarations received (see www.iso.org/patents).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation on the meaning of ISO specific terms and expressions related to conformity
assessment, as well as information about ISO’s adherence to the WTO principles in the Technical
Barriers to Trade (TBT) see the following URL: Foreword - Supplementary information
The committee responsible for this document is ISO/TC 211, Geographic information/Geomatics.
ISO 19163 consists of the following parts, under the general title Geographic information — Content
components and encoding rules for imagery and gridded data:
— Part 1: Content model [Technical Specification]
Other parts are planned, but are not yet specified.
iv © ISO 2016 – All rights reserved
Introduction
Geographic imagery and gridded thematic data are widely used in the geospatial community and
related fields.
A preliminary work item on imagery and gridded data components, carried out by ISO/TC 211 in 1999
to 2000, provides a summary of the conceptual classification of gridded data based on spatial and
attribute properties and identifies five basic components of imagery and gridded data (ISO/TC 211 N
1017). ISO/TS 19101-2, ISO 19123 and ISO/TS 19129 specify domains and ranges of imagery, grids and
coverages, and their associated relationships. ISO/TS 19129 breaks down the metadata into discovery,
structural, acquisition and quality metadata. However, there are no detailed descriptions on each
category and no clear associations with metadata defined in ISO 19115:2003, ISO 19115-2, ISO/TS 19130
and ISO/TS 19130-2.
Imagery is acquired by remote sensors directly or derived from source imagery. Value-added image
processing can be used to derive physical properties of a remote object from images (ISO/TS 19101-2).
Besides the derived images, imagery can also be integrated with other data sources to produce new
gridded coverage data for a specific theme, called thematic data, which is widely used in various
applications. However, the characteristics of thematic data are not covered by the existing International
Standards and Technical Specifications noted above.
ISO/TS 19130 identifies the type of remote sensors by the measurand of the sensor, e.g. optical
radiation, microwave energy and SONAR (acoustic) energy. Images acquired by optical sensors have
different appearances and characteristics compared with those by a microwave sensor, e.g. SAR data.
The framework defined in ISO/TS 19129 describes imagery, gridded and coverage data at multiple levels,
including an abstract level, a content model level and an encoding level. The first two levels combine
a number of well-defined content structures in accordance with ISO 19123 and define the contents of
continuous quadrilateral gridded coverages with grids of both constant and variable cell sizes. However,
the content model level does not specify the necessary metadata for common understanding when
integrating datasets encoded in different formats. At the encoding level, ISO/TS 19129 does not provide
the explicit encoding rules for mapping content model to machine-independent encoding structure, which
is crucial for the mapping and translation of images in different formats without losing information.
Based on the frameworks defined in ISO/TS 19101-2 and ISO 19123, this Technical Specification specifies
the categories of imagery and gridded data and establishes a corresponding hierarchical content model.
Categories of imagery and gridded data are defined based on thematic and spatial attributes and sensor
types. The content model is then defined to describe the required content components of each category,
including the spatial and attribute structures and the critical metadata entries as well. These metadata
entries are specified as the minimum required metadata information for the purpose of common
understanding. Traditionally, remote sensing data products generally have a header part and a data
part. This Technical Specification describes the minimum content requirements for the header part.
For ease of implementation, this Technical Specification defines encoding rules to map the content
models to XML-based encodings, following the general encoding rules defined in ISO 19118 and the
encoding rules for UML-to-GML application schema defined in ISO 19136:2007, Annex E. Since GMLCOV
schema (OGC 09-146r2) is optimized for handling coverages, the coverage component of the schema can
be based on GMLCOV.
An increasingly large volume of image and gridded data, both natural and synthetic, is being produced
because more remote sensors are becoming available. These data are encoded in diverse formats,
such as GeoTIFF, BIIF, HDF-EOS, JPEG 2000, NetCDF and others as described in ISO/TR 19121. These
encoding formats follow different data models, preventing them from being interoperable. In order to
encode the contents defined in this Technical Specification into these data formats, ISO 19163 has been
split into multiple parts with this Technical Specification defining the content components and general
encoding rules and the subsequent parts defining the binding between the contents and individual
physical data formats.
TECHNICAL SPECIFICATION ISO/TS 19163-1:2016(E)
Geographic information — Content components and
encoding rules for imagery and gridded data —
Part 1:
Content model
1 Scope
This Technical Specification classifies imagery and regularly spaced gridded thematic data into types
based on attribute property, sensor type and spatial property, and defines an encoding-neutral content
model for the required components for each type of data. It also specifies logical data structures and
the rules for encoding the content components in the structures.
The binding between the content and a specific encoding format will be defined in the subsequent parts
of ISO 19163.
This Technical Specification does not address LiDAR, SONAR data and ungeoreferenced gridded data.
The logical data structures and the rules for encoding the content components will be addressed in the
subsequent parts of ISO 19163.
2 Conformance
This Technical Specification standardizes the categories of imagery and regularly spaced gridded
thematic data as well as their core content models. There is one conformance class for each data category.
Any set of imagery and regularly spaced gridded thematic data claiming conformance to this Technical
Specification shall satisfy the corresponding requirements defined in the abstract test suite in Annex A.
3 Normative references
The following documents, in whole or in part, are normatively referenced in this document and are
indispensable for its application. For dated references, only the edition cited applies. For undated
references, the latest edition of the referenced document (including any amendments) applies.
ISO 19103:2015, Geographic information — Conceptual schema language
ISO 19111, Geographic information — Spatial referencing by coordinates
ISO 19115-1, Geographic information — Metadata — Part 1: Fundamentals
1)
ISO 19115-2 , Geographic information — Metadata — Part 2: Extensions for imagery and gridded data
ISO 19123:2005, Geographic information — Schema for coverage geometry and functions
ISO/TS 19101-2:2008, Geographic information — Reference model — Part 2: Imagery
ISO/TS 19130:2010, Geographic information - Imagery sensor models for geopositioning
ISO/TS 19159-1, Geographic information — Calibration and validation of remote sensing imagery sensors
and data — Part 1: Optical sensors
1) At the publication time of this Technical Specification, only ISO 19115-2:2009, which references to
ISO 19115:2003, is available. The new version of ISO 19115-2, which is under revision at the publication time of this
Technical Specification, will refer to ISO 19115-1:2014.
4 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
4.1
attribute
named property of an entity
Note 1 to entry: Describes a geometrical, topological, thematic, or other characteristic of an entity.
[SOURCE: ISO/IEC 2382:2015, 2121440, modified — Note 1 to entry has been added.]
4.2
binding
specification of a mapping relating the information defined in a content model (4.3) (data and metadata)
to the data format that carries that information
4.3
content model
information view of an application schema
Note 1 to entry: In this Technical Specification, a content model describes the required content components and
their interrelationship of imagery (4.12) and gridded thematic data (4.14).
[SOURCE: ISO/TS 19129:2009, 4.1.2, modified — Note 1 to entry has been added.]
4.4
conversion rule
rule for converting instances in the input data structure to instances in the output data structure
[SOURCE: ISO 19118:2011, 4.7]
4.5
encoding rule
identifiable collection of conversion rules (4.4) that define the encoding for a particular data structure
EXAMPLE XML, ISO 10303-21, ISO/IEC 8211.
Note 1 to entry: An encoding rule specifies the types of data to be converted as well as the syntax, structure and
codes used in the resulting data structure.
[SOURCE: ISO 19118:2011, 4.14]
4.6
fused image
image produced by fusing images from multiple sources
4.7
geopositioning
determining the geographic position of an object
[SOURCE: ISO/TS 19130:2010, 4.36, modified]
4.8
georectified
corrected for positional displacement with respect to the surface of the Earth
[SOURCE: ISO 19115-2:2009, 4.12]
2 © ISO 2016 – All rights reserved
4.9
georeferenceable
associated with a geopositioning (4.7) information that can be used to convert grid (4.10) coordinate
values to values of coordinates referenced to an external coordinate reference system related to the
Earth by a datum
4.10
grid
network composed of two or more sets of curves in which the members of each set intersect the
members of the other sets in an algorithmic way
[SOURCE: ISO 19123:2005, 4.1.23, modified]
4.11
gridded data
data whose attribute (4.1) values are associated with positions on a grid (4.10) coordinate system
Note 1 to entry: Gridded data are a subtype of coverage data, which represent attribute values of geographic
features in terms of a spatial grid.
[SOURCE: ISO 19115-2:2009, 4.17, modified — Note 1 to entry has been added.]
4.12
imagery
representation of phenomena as images produced by electronic and/or optical techniques
Note 1 to entry: The term imagery is often used colloquially with various meanings in different contexts. It is
often used to describe any set of gridded, point set or other form of coverage data that can be portrayed.
[SOURCE: ISO/TS 19101-2:2008, 4.14, modified — Note 1 to entry has been added.]
4.13
looks
groups of signal samples in a SAR processor that splits the full synthetic aperture into several sub-
apertures, each representing an independent look of the identical scene
Note 1 to entry: The resulting image formed by incoherent summing of these looks is characterized by reduced
speckle and degraded spatial resolution.
4.14
thematic data
gridded data (4.11) whose attribute (4.1) values describe characteristics of a grid (4.10) coverage feature
in a grid format
Note 1 to entry: Most gridded thematic data are derived from imagery (4.12) data using geophysical/atmospheric
inversion algorithms. Gridded thematic data may also be obtained from other sources such as digitization of
topographic map sheets.
4.15
ungeoreferenced grid
gridded data (4.11) that does not include any information that can be used to determine a cell’s
geographic coordinate values
EXAMPLE A digital photo without georectification information included.
5 Symbols and abbreviated terms
5.1 Abbreviated terms
BIIF Basic Image Interchange Format
CRS Coordinate Reference System
DEM Digital Elevation Model
EOS Earth Observing System
HDF Hierarchical Data Format
JPEG200 Joint Photographic Experts Group 2000
netCDF network Common Data Form
SAR Synthetic aperture radar
TIFF Tagged Image File Format
UML Unified Modeling Language
5.2 UML notations
This Technical Specification presents conceptual models of imagery and gridded data, specified in the
2)
Unified Modeling Language (UML). ISO 19103 describes the way in which UML is used in the ISO 19100
family of standards. It differs from standard UML only in the existence and interpretation of some
special stereotypes, in particular, “CodeList”. ISO 19103 specifies the basic data types used in the UML
model. The UML diagrams defined in this Technical Specification represent conceptual models only and
are not intended for automatic encoding within XML Schema.
Annex B contains a data dictionary for the UML models defined in this Technical Specification.
Table 1 lists the prefixes of UML classes used in the referenced ISO standards in this Technical
Specification. IE is the prefix of the UML classes defined in this Technical Specification. In Table 1, the
first column describes the prefix used in the packages of the second column and the third column is the
ISO standard where the package is defined.
2) This International Standard is under preparation.
4 © ISO 2016 – All rights reserved
Table 1 — UML package identifiers
Identifier Package International
Standard
EX Extent information ISO 19115-1
LE Lineage extended ISO 19115-2
LI Lineage ISO 19115-1
MD Metadata ISO 19115-1
MI Metadata for imagery ISO 19115-2
SD Sensor data ISO/TS 19130
CV Coverage ISO 19123
CA Calibration and validation of sensor ISO/TS 19159-1
GM Geometry root ISO 19107
IE Content components and encoding rules for imagery and ISO 19163
gridded data
6 Related International Standards
Figure 1 illustrates the relationship between this Technical Specification and other International
Standards related to imagery and gridded data. This Technical Specification fits the reference model
defined in ISO/TS 19101-2 and follows the abstract content framework defined in ISO 19123. CV_Coverage
is chosen as the super-class to establish the content component model of imagery and gridded data.
This Technical Specification refers to metadata related to imagery and gridded data defined in
ISO 19115-1 and ISO 19115-2, the sensor information related to acquisition of imagery defined in
ISO/TS 19130 and the calibration and validation of sensors defined in ISO/TS 19159-1.
This Technical Specification defines an UML schema for the content model which can be bound with any
widely used data formats of imagery and gridded data, such as GeoTIFF, BIIF, JPEG 2000, NetCDF and HDF.
ISO 19115-1:2014 Metadata - Fundamentals ISO 19115-2:2009 Metadata - Imagery
ISO 19123:2005 Coverages ISO 19159-1 Calibration and Validation
metadata
metadata
calibration
abstract content on coverage
ISO 19163 Content components and encoding rules
sensor information
standardization requirements
binding binding
ISO 19101-2:2008 Imagery Reference ISO/TS 19130:2010 Sensor Data
binding binding binding
GeoTIFF NetCDF
HDF-EOS JPEG 2000 BIIF
Figure 1 — Relationship with related International Standards
7 Categories of imagery and gridded data
7.1 General
Clause 7 categorizes imagery according to digital sensor types and gridded data according to the
attribute and geometry properties. The required content components of each data category are
specified in UML content models of Clause 8.
The intention of this Technical Specification is not to define a comprehensive classification system
of imagery and gridded data, but to specify the contents of some categories of them. A hierarchical
category framework of imagery and gridded data is defined in Figure 2. The root of the framework is
Coverage defined in ISO 19123. Imagery and gridded data are a subclass of coverage. The two subclasses
of imagery and gridded data, which are imagery data and thematic gridded data, are defined in this
Technical Specification.
6 © ISO 2016 – All rights reserved
Coverage Data
Imagery and Gridded Data
Thematic Gridded Data Imagery Data
Numerical Categorical Optical Imagery Synthetic Imagery
Microw av e Data
Thematic Data Thematic Data Data Data
Active Passive Fused Imagery Simulated
Microw av e Data Microw av e Data Data Imagery Data
SAR Data Radiometer Data
Figure 2 — Categories of imagery and gridded data
7.2 Imagery
Imagery is a kind of coverage whose attribute values are numerical representations of the physical
parameters (e.g. radiance) measured by imagery sensors. According to ISO/TS 19101-2, a sensor can
be classified as an electromagnetic energy sensor or a mechanical wave energy sensor based on the
type of energy sensed by the sensor. The former class is further categorized into an optical sensor, a
microwave sensor or a light detection and ranging sensor (LiDAR) according to the measurand of the
sensor (ISO/TS 19130). SONAR is a typical example of mechanical wave energy sensor. These sensors
produce optical, microwave, LiDAR and SONAR imagery data, respectively.
The data acquired by LiDAR and SONAR, which exhibit distinct characteristics that differ from optical
images and microwave data, are not covered by this Technical Specification due to the limit of the scope.
These types of data may be addressed in a future extension or subsequent part of ISO 19163.
Optical images are acquired from visible and infrared sensors by detecting the radiation reflected or
emitted from target objects (ISO/TS 19101-2). Different materials reflect, absorb or emit radiation at
different wavelengths, and accordingly each object type has a spectral signature. Analysing spectral
signatures within remotely sensed images identifies differentiation between these objects. Thus,
images may be classified depending on the number of spectral bands, for example panchromatic,
multispectral and hyperspectral.
Microwave data are classified into active and passive microwave data corresponding to active and
passive microwave sensors. Synthetic aperture radar (SAR) is a typical active microwave sensor that
uses a series of radar pulses transmitted and received over time from a moving platform to create an
image, as specified by ISO/TS 19130.
Passive microwave sensors measure the energy and/or the phase of microwaves emitted from objects.
Passive microwave data can be used to derive various geophysical quantities, such as rainfall, sea
surface temperature, vertical water vapour, ocean surface wind speed, sea ice parameters, snow
water equivalent and soil surface moisture (ISO/TS 19101-2). There is more than one type of passive
microwave data, but this Technical Specification only specifies the contents of microwave imaging
radiometer data.
In addition to images acquired directly by a certain sensor, image fusion and image simulation
techniques can generate new images from original images, fused image and simulated image. The image
fusion techniques allow the integration of images from different sources. The fused image can have
complementary multisource characteristics. For example, a higher-spatial-resolution panchromatic
image is fused with lower-spatial-resolution multispectral data to provide multispectral information
with higher spatial resolution; optical images and SAR data can be merged in order to simultaneously
exploit the spectral and textural information.
7.3 Gridded data
Gridded data are a subtype of coverage (ISO 19115-2). In order to avoid the content overlap, this
Technical Specification limits gridded data to regularly spaced gridded thematic data whose attribute
values are values of a geographic feature (e.g. altitude, leaf area index) and whose geometric state is
regularly spaced quadrilateral grid.
Most thematic data are derived from imagery by information retrieval processing with domain-specific
or application-specific algorithms. Some thematic data, such as Digital Elevation Model (DEM) and
scanned or rasterized data, are not necessarily derived from imagery data. DEM and rasterized data
are often integrated with imagery data in various applications, for example a 3D virtual terrain. There
are several different geometric states for thematic data, gridded-based, point-based, surface-based
and segmented based one (ISO/TS 19101-2). This Technical Specification only defines the content of
regular-gridded thematic data.
Thematic data have categorical attributes or numerical attributes of a geographic feature or
phenomenon. Typical examples of numerical data are DEM and land surface temperature, and those of
categorical data are land cover and land use data. Categorical attributes shall not be interpolated.
8 Content component models
8.1 General
This Technical Specification defines the required content components of imagery and gridded data
based on the hierarchical category framework (Figure 2). 8.2 to 8.4 describe these categories using
UML model diagrams and the corresponding data dictionary is given in Annex B.
8.2 Imagery and gridded data
8.2.1 General
The structure and association of imagery and gridded data are illustrated in Figure 3. The topmost
class of this Technical Specification, IE_ImageryAndGriddedData, is a subclass of CV_Coverage defined
in ISO 19123. The information of coordinate reference system is specified in ISO 19111. IE_Georectified
and IE_Georeferenceable are aggregated to describe the associate geolocation information of
georectified and georeferenceable data, respectively.
The data dictionary of this UML diagram is given in B.1.
8 © ISO 2016 – All rights reserved
From ISO 19123:2005
«type»
Coverage Core::CV_Coverage
0.*
CoordinateReferenceSystem
From ISO 19111:2007 shown for informative purposes only
+CRS
IO_IdentiiedObjectBase
IE_ImageryAndGriddedData
RS_ReferenceSystem
«type»
Coordinate Reference Systems::SC_CRS
georeferenceableSpatialInfo
georecti’iedSpatialInfo
{sizeof(georecti’iedSpatialInfo)+
sizeof(georeferenceableSpatialInfo)=1}
0.1
0.1
IE_Georectiied IE_Georeferenceable
+ geolocationSource: IE_GeolocationSourceCode [1.*] + geolocationInfo: SD_SensorModel
+ correctionModel: IE_GeometricCorrectionModelCode
+ checkPoints: IE_LocationGCP [1.*]
From ISO 19115-1:2014
MD_GridSpatialRepresentation
MD_GridSpatialRepresentation
Spatial representation information::MD_Georectiied Spatial representation information::MD_Georeferenceable
«CodeList» «CodeList» «union»
IE_GeolocationSourceCode IE_GeometricCorrectionModelCode IE_LocationGCP
+ GCP + CorrespondenceModel + GCPRepository: SD_GCPRepository
+ SystemParameters + PhysicalSensorModel + imageIdenti’iableGCP: SD_ImageIdenti’iableGCP
+ SystemParameters+DEM + TrueReplacementModel + locationGCP: SD_GCPLocation
+ SystemParameters+GCP
+ SystemParameters+GCP+DEM
+ GCP+DEM
Figure 3 — IE_ImageryAndGriddedData
8.2.2 IE_ImageryAndGriddedData
IE_ImageryAndGriddedData inherits the attributes of CV_Coverage and defines an attribute
interpolationType to identify the interpolation method that shall be used to derive a feature attribute
value at any direct position.
8.2.3 IE_Georectified
IE_Georectified specifies the source of geolocations and the model used for geometric correction. The
attribute checkPoints specifies the format and source of ground control points used as check points in a
georectified image. The ground control points can be given in coordinates (defined in SD_LocationGCP),
or marked in images or described in texts (defined in SD_ImageIdentifiableGCP), or accessed from a
GCP repository based on access restrictions (defined in SD_GCPRepository). SD_LocationGCP inherits
the attributes of MI_GCP from ISO 19115-2 and adds a grid coordinate of GCP.
More spatial attributes about the check points and other attributes are inherited from MD_Georectified
defined in ISO 19115-1.
8.2.4 IE_Georeferenceable
Geolocation information of georeferenceable data shall be acquired from SD_SensorModel, which
defines the geometric correction models. More spatial attributes about georeferenceable data are
inherited from MD_Georeferenceable defined in ISO 19115-1.
8.3 Thematic gridded data
8.3.1 IE_ThematicGriddedData
IE_ThematicGriddedData (Figure 4) contains the common characteristics of thematic gridded data. The
attribute dataInfo provides the basic information about the data (defined in MD_CoverageDescription
of ISO 19115-1). The attributes, annotation and geographicFeature, define vector-based annotations and
features overlapped on the gridded data in order to improve the understanding.
The processing and the source for producing the thematic gridded data are described with the attribute
retrievalProcessingInfo and the attribute sourceInfo, respectively.
There are two subtypes of thematic gridded data, categorical and numerical, which are specified with
IE_CategoricalGriddedData class and IE_NumericalGriddedData class.
The data dictionary for the UML diagram in 8.3 (Figure 4) is given in B.2.
8.3.2 IE_CategoricalGriddedData
IE_CategoricalGriddedData specifies the number of categories of a categorical data layer
(numberOfCategories), the description on the classification to produce the categorical data
(classificationDescription), and the number of bits for recording each value (bitsPerValue). IE_
CategoricalValueAndColour describes the lookup table of the relationship between each value and its
semantics and colour palette of each category. The content of “description” may be a reference to a
classification legend item as defined in ISO 19144-1.
8.3.3 IE_NumericalGriddedData
IE_NumericalGriddedData specifies the meaning of the numerical gridded data with the attribute
valueDescription and inherits the information about the maximum and minimum value, units,
bitsPerValue and so on from MD_SampleDimension.
10 © ISO 2016 – All rights reserved
CV_Coverage
IE_ImageryandGriddedData::IE_ImageryAndGriddedData
+ interpolationType: CV_InterpolationMethod [0.1]
IE_ThematicGriddedData
+ dataInfo: MD_CoverageDescription
+ annotation: GM_Object [0.*]
+ geographicFeature: GM_Object [0.*]
+ retrievalProcessingInfo: LE_Processing [0.*]
+ sourceInfo: CharacterString [0.*]
{sizeof(datainfo.attributeGroup.attribute.MD_SampleDimension)>1}
IE_CategoricalGriddedData IE_NumericalGriddedData
+ classi‡icationDescription: CharacterString [0.1] + valueDescription: CharacterString
+ numberOfCategories: Integer
+ bitsPerValue: Integer [0.1]
lookupTable
n
{n=numberofCategories}
«DataType»
IE_CategoricalValueAndColour
IE_ColourPalette
+ categoryName: CharacterString
+ red: Integer
+ colourPalette: IE_ColourPalette [0.1]
+ green: Integer
+ description: CharacterString [0.1]
+ blue: Integer
+ value: Integer
Figure 4 — IE_ThematicGriddedData
8.4 Imagery
8.4.1 IE_Imagery
The class IE_Imagery (Figure 5) inherits the attributes from IE_ImageryAndGriddedData. In addition,
IE_Imagery defines the following required information: acquisition time, image parameters, number of
bands, platform, sensor, processing action, calibration and validation of sensor.
The attribute imageDescription gives the basic parameters on acquiring image data. The attribute
processingAction records the processing steps being taken on the dataset. LE_ProcessingActionCode
lists the possible actions for image processing.
The attribute radiometricCorrectionType describes the type of image radiometric correction taken,
which is either absolute correction or relative correction. The attribute sensorCalibrationValidation
with its type CA_CalibrationValidation specifies the information required for sensor calibration and
validation. CA_CalibrationValidation is defined in ISO/TS 19159-1.
CV_Coverage
«CodeList»
IE_RadiometricCalibrationTypeCode
IE_ImageryandGriddedData::IE_ImageryAndGriddedData
+ AbsoluteRadiometricCalibration
+ interpolationType: CV_InterpolationMethod [0.1]
+ RelativeRadiometricCalibration
«CodeList»
IE_ProcessingActionCode
+ ImageEnhancement
+ ImageFusion
+ ImageSmoothing
IE_Imagery
+ acquisitionTime: TM_Period
+ imageDescription: MD_ImageDescription [0.1]
mosaicInfo
{isMosaic=TRUE}
+ isMosaic: Boolean
+ numberofBands: Integer
1.*
+ processingAction: IE_ProcessingActionCode [0.1]
+ radiometricCalibrationType: IE_RadiometricCalibrationTypeCode [0.1]
IE_MosaicElement
+ sensorCalibrationValidation: CA_CalibrationValidation [0.1]
+ platformInfo: MI_Platform [0.1]
+ elementID: Integer
+ sensorInfo: MI_Instrument [0.1]
+ acquisitionTime: TM_Period
+ geometry: EX_Extent
IE_OpticalImage:: IE_MicrowaveData:: IE_SyntheticImage
IE_OpticalImage IE_MicrowaveData
+ intendedUse: MD_Usage [0.1]
band information
IE_SimulatedImage IE_FusedImage
+ simulateMethod: CharacterString + numberOfSourceImages: Integer
+ provenance: LI_Lineage [0.1] + processingSteps: LE_ProcessStep [0.*]
n
{n=numberofBands}
From ISO 19115-2:2009 shown for informative purposes only
MD_Band
Content information - Imagery::MI_Band
Figure 5 — IE_Imagery
The attribute sensorInfo, defined in MI_Instrument of ISO 19115-2, contains basic information about the
sensor. The attributes platformInfo, defined in MI_Platform of ISO 19115-2, specifies the information of
a platform on which the sensor is mounted.
If an image is a mosaic of multiple images, i.e. IsMosaic = TRUE, the acquisition time, extent and
identification of each image shall be recorded as a mosaic element, IE_MosaicElement. The geometry
attribute for the extent can contain multiple polygons, as described in ISO 19115-1.
IE_Imagery associates with n (n = numberofBands) MI_Band classes, each of which describes the
information of a band. The detailed information of MI_Band is defined in ISO 19115-2.
According to the categories of imagery and gridded data (Figure 2), IE_Imagery has three subclasses,
IE_OpticalImage (8.4.4), IE_MicrowaveData (8.4.5) and IE_SyntheticImage. IE_SyntheticImage
defines the intended usage of the imagery and it has two subclasses, IE_FusedImage (8.4.2) and IE_
SimulatedImage (8.4.3).
The data dictionary for the UML diagrams in 8.4 (Figure 5 to 9) is given in B.3.
12 © ISO 2016 – All rights reserved
8.4.2 IE_FusedImage
The class IE_FusedImage describes the number of source images and the processing steps used to
produce a fused image.
8.4.3 IE_SimulatedImage
The class IE_SimulatedImage describes the method for simulating an image and its provenance.
Simulated images are used to evaluate the characteristics of a sensor system and validate the retrieval
algorithms prior to the system being put into the operational environment.
8.4.4 IE_OpticalImage
The class IE_OpticalImage (Figure 6) contains the information specific to images acquired by optical
sensors. The attribute opticalImageType identifies the type of an optical image, such as a hyperspectral,
infrared, multispectral, panchromatic or other image. The attribute opticalSensorType specifies the
type of an optical sensor.
IE_ImageryAndGriddedData
«CodeList»
IE_OpticalImageTypeCode IE_Imagery::IE_Imagery
+ HyperspectralImage
+ InfraredImage
+ MultispectralImage
+ PanchromaticImage
+ Other
«CodeList»
IE_OpticalImage
IE_OpticalSensorTypeCode
+ opticalImageType: IE_OpticalImageTypeCode [0.1]
+ Frame
+ opticalSensorType: IE_OpticalSensorTypeCode [0.1]
+ Pushbroom
+ Whiskbroom
+ Other
Figure 6 — IE_OpticalImage
8.4.5 IE_MicrowaveData
As shown in Figure 7, IE_MicrowaveData has two subclasses, which are IE_ActiveMWData and IE_
PassiveMWData. There is more than one type of active and passive microwave data, but this Technical
Specification only specifies the contents of data from SAR (IE_SARData) and microwave radiometers
(IE_RadiometerData).
IE_Imagery
IE_MicrowaveData
IE_ActiveMWData IE_PassiveMWData
IE_SARData::IE_SARData IE_RadiometerData::IE_RadiometerData
Figure 7 — IE_MicrowaveData
8.4.6 IE_SARData
The class IE_SARData (Figure 8) contains characteristics of SAR d
...
TECHNICAL ISO/TS
SPECIFICATION 19163-1
First edition
2016-01-15
Geographic information — Content
components and encoding rules for
imagery and gridded data —
Part 1:
Content model
Information géographique — Composantes de contenu et règles de
codage pour l’imagerie et les données maillées —
Partie 1: Modèle de contenu
Reference number
©
ISO 2016
© ISO 2016, Published in Switzerland
All rights reserved. Unless otherwise specified, no part of this publication may be reproduced or utilized otherwise in any form
or by any means, electronic or mechanical, including photocopying, or posting on the internet or an intranet, without prior
written permission. Permission can be requested from either ISO at the address below or ISO’s member body in the country of
the requester.
ISO copyright office
Ch. de Blandonnet 8 • CP 401
CH-1214 Vernier, Geneva, Switzerland
Tel. +41 22 749 01 11
Fax +41 22 749 09 47
copyright@iso.org
www.iso.org
ii © ISO 2016 – All rights reserved
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Conformance . 1
3 Normative references . 1
4 Terms and definitions . 2
5 Symbols and abbreviated terms . 4
5.1 Abbreviated terms . 4
5.2 UML notations . 4
6 Related International Standards . 5
7 Categories of imagery and gridded data . 6
7.1 General . 6
7.2 Imagery . 7
7.3 Gridded data . 8
8 Content component models . 8
8.1 General . 8
8.2 Imagery and gridded data . 8
8.2.1 General. 8
8.2.2 IE_ImageryAndGriddedData . 9
8.2.3 IE_Georectified . 9
8.2.4 IE_Georeferenceable .10
8.3 Thematic gridded data .10
8.3.1 IE_ThematicGriddedData .10
8.3.2 IE_CategoricalGriddedData .10
8.3.3 IE_NumericalGriddedData .10
8.4 Imagery .11
8.4.1 IE_Imagery.11
8.4.2 IE_FusedImage .13
8.4.3 IE_SimulatedImage .13
8.4.4 IE_OpticalImage .13
8.4.5 IE_MicrowaveData .13
8.4.6 IE_SARData.14
8.4.7 IE_RadiometerData .15
9 General approach for encoding (informative) .16
Annex A (normative) Abstract test suite .18
Annex B (normative) Data dictionary of content component models .21
Bibliography .38
Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out
through ISO technical committees. Each member body interested in a subject for which a technical
committee has been established has the right to be represented on that committee. International
organizations, governmental and non-governmental, in liaison with ISO, also take part in the work.
ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of
electrotechnical standardization.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular the different approval criteria needed for the
different types of ISO documents should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www.iso.org/directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of
any patent rights identified during the development of the document will be in the Introduction and/or
on the ISO list of patent declarations received (see www.iso.org/patents).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation on the meaning of ISO specific terms and expressions related to conformity
assessment, as well as information about ISO’s adherence to the WTO principles in the Technical
Barriers to Trade (TBT) see the following URL: Foreword - Supplementary information
The committee responsible for this document is ISO/TC 211, Geographic information/Geomatics.
ISO 19163 consists of the following parts, under the general title Geographic information — Content
components and encoding rules for imagery and gridded data:
— Part 1: Content model [Technical Specification]
Other parts are planned, but are not yet specified.
iv © ISO 2016 – All rights reserved
Introduction
Geographic imagery and gridded thematic data are widely used in the geospatial community and
related fields.
A preliminary work item on imagery and gridded data components, carried out by ISO/TC 211 in 1999
to 2000, provides a summary of the conceptual classification of gridded data based on spatial and
attribute properties and identifies five basic components of imagery and gridded data (ISO/TC 211 N
1017). ISO/TS 19101-2, ISO 19123 and ISO/TS 19129 specify domains and ranges of imagery, grids and
coverages, and their associated relationships. ISO/TS 19129 breaks down the metadata into discovery,
structural, acquisition and quality metadata. However, there are no detailed descriptions on each
category and no clear associations with metadata defined in ISO 19115:2003, ISO 19115-2, ISO/TS 19130
and ISO/TS 19130-2.
Imagery is acquired by remote sensors directly or derived from source imagery. Value-added image
processing can be used to derive physical properties of a remote object from images (ISO/TS 19101-2).
Besides the derived images, imagery can also be integrated with other data sources to produce new
gridded coverage data for a specific theme, called thematic data, which is widely used in various
applications. However, the characteristics of thematic data are not covered by the existing International
Standards and Technical Specifications noted above.
ISO/TS 19130 identifies the type of remote sensors by the measurand of the sensor, e.g. optical
radiation, microwave energy and SONAR (acoustic) energy. Images acquired by optical sensors have
different appearances and characteristics compared with those by a microwave sensor, e.g. SAR data.
The framework defined in ISO/TS 19129 describes imagery, gridded and coverage data at multiple levels,
including an abstract level, a content model level and an encoding level. The first two levels combine
a number of well-defined content structures in accordance with ISO 19123 and define the contents of
continuous quadrilateral gridded coverages with grids of both constant and variable cell sizes. However,
the content model level does not specify the necessary metadata for common understanding when
integrating datasets encoded in different formats. At the encoding level, ISO/TS 19129 does not provide
the explicit encoding rules for mapping content model to machine-independent encoding structure, which
is crucial for the mapping and translation of images in different formats without losing information.
Based on the frameworks defined in ISO/TS 19101-2 and ISO 19123, this Technical Specification specifies
the categories of imagery and gridded data and establishes a corresponding hierarchical content model.
Categories of imagery and gridded data are defined based on thematic and spatial attributes and sensor
types. The content model is then defined to describe the required content components of each category,
including the spatial and attribute structures and the critical metadata entries as well. These metadata
entries are specified as the minimum required metadata information for the purpose of common
understanding. Traditionally, remote sensing data products generally have a header part and a data
part. This Technical Specification describes the minimum content requirements for the header part.
For ease of implementation, this Technical Specification defines encoding rules to map the content
models to XML-based encodings, following the general encoding rules defined in ISO 19118 and the
encoding rules for UML-to-GML application schema defined in ISO 19136:2007, Annex E. Since GMLCOV
schema (OGC 09-146r2) is optimized for handling coverages, the coverage component of the schema can
be based on GMLCOV.
An increasingly large volume of image and gridded data, both natural and synthetic, is being produced
because more remote sensors are becoming available. These data are encoded in diverse formats,
such as GeoTIFF, BIIF, HDF-EOS, JPEG 2000, NetCDF and others as described in ISO/TR 19121. These
encoding formats follow different data models, preventing them from being interoperable. In order to
encode the contents defined in this Technical Specification into these data formats, ISO 19163 has been
split into multiple parts with this Technical Specification defining the content components and general
encoding rules and the subsequent parts defining the binding between the contents and individual
physical data formats.
TECHNICAL SPECIFICATION ISO/TS 19163-1:2016(E)
Geographic information — Content components and
encoding rules for imagery and gridded data —
Part 1:
Content model
1 Scope
This Technical Specification classifies imagery and regularly spaced gridded thematic data into types
based on attribute property, sensor type and spatial property, and defines an encoding-neutral content
model for the required components for each type of data. It also specifies logical data structures and
the rules for encoding the content components in the structures.
The binding between the content and a specific encoding format will be defined in the subsequent parts
of ISO 19163.
This Technical Specification does not address LiDAR, SONAR data and ungeoreferenced gridded data.
The logical data structures and the rules for encoding the content components will be addressed in the
subsequent parts of ISO 19163.
2 Conformance
This Technical Specification standardizes the categories of imagery and regularly spaced gridded
thematic data as well as their core content models. There is one conformance class for each data category.
Any set of imagery and regularly spaced gridded thematic data claiming conformance to this Technical
Specification shall satisfy the corresponding requirements defined in the abstract test suite in Annex A.
3 Normative references
The following documents, in whole or in part, are normatively referenced in this document and are
indispensable for its application. For dated references, only the edition cited applies. For undated
references, the latest edition of the referenced document (including any amendments) applies.
ISO 19103:2015, Geographic information — Conceptual schema language
ISO 19111, Geographic information — Spatial referencing by coordinates
ISO 19115-1, Geographic information — Metadata — Part 1: Fundamentals
1)
ISO 19115-2 , Geographic information — Metadata — Part 2: Extensions for imagery and gridded data
ISO 19123:2005, Geographic information — Schema for coverage geometry and functions
ISO/TS 19101-2:2008, Geographic information — Reference model — Part 2: Imagery
ISO/TS 19130:2010, Geographic information - Imagery sensor models for geopositioning
ISO/TS 19159-1, Geographic information — Calibration and validation of remote sensing imagery sensors
and data — Part 1: Optical sensors
1) At the publication time of this Technical Specification, only ISO 19115-2:2009, which references to
ISO 19115:2003, is available. The new version of ISO 19115-2, which is under revision at the publication time of this
Technical Specification, will refer to ISO 19115-1:2014.
4 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
4.1
attribute
named property of an entity
Note 1 to entry: Describes a geometrical, topological, thematic, or other characteristic of an entity.
[SOURCE: ISO/IEC 2382:2015, 2121440, modified — Note 1 to entry has been added.]
4.2
binding
specification of a mapping relating the information defined in a content model (4.3) (data and metadata)
to the data format that carries that information
4.3
content model
information view of an application schema
Note 1 to entry: In this Technical Specification, a content model describes the required content components and
their interrelationship of imagery (4.12) and gridded thematic data (4.14).
[SOURCE: ISO/TS 19129:2009, 4.1.2, modified — Note 1 to entry has been added.]
4.4
conversion rule
rule for converting instances in the input data structure to instances in the output data structure
[SOURCE: ISO 19118:2011, 4.7]
4.5
encoding rule
identifiable collection of conversion rules (4.4) that define the encoding for a particular data structure
EXAMPLE XML, ISO 10303-21, ISO/IEC 8211.
Note 1 to entry: An encoding rule specifies the types of data to be converted as well as the syntax, structure and
codes used in the resulting data structure.
[SOURCE: ISO 19118:2011, 4.14]
4.6
fused image
image produced by fusing images from multiple sources
4.7
geopositioning
determining the geographic position of an object
[SOURCE: ISO/TS 19130:2010, 4.36, modified]
4.8
georectified
corrected for positional displacement with respect to the surface of the Earth
[SOURCE: ISO 19115-2:2009, 4.12]
2 © ISO 2016 – All rights reserved
4.9
georeferenceable
associated with a geopositioning (4.7) information that can be used to convert grid (4.10) coordinate
values to values of coordinates referenced to an external coordinate reference system related to the
Earth by a datum
4.10
grid
network composed of two or more sets of curves in which the members of each set intersect the
members of the other sets in an algorithmic way
[SOURCE: ISO 19123:2005, 4.1.23, modified]
4.11
gridded data
data whose attribute (4.1) values are associated with positions on a grid (4.10) coordinate system
Note 1 to entry: Gridded data are a subtype of coverage data, which represent attribute values of geographic
features in terms of a spatial grid.
[SOURCE: ISO 19115-2:2009, 4.17, modified — Note 1 to entry has been added.]
4.12
imagery
representation of phenomena as images produced by electronic and/or optical techniques
Note 1 to entry: The term imagery is often used colloquially with various meanings in different contexts. It is
often used to describe any set of gridded, point set or other form of coverage data that can be portrayed.
[SOURCE: ISO/TS 19101-2:2008, 4.14, modified — Note 1 to entry has been added.]
4.13
looks
groups of signal samples in a SAR processor that splits the full synthetic aperture into several sub-
apertures, each representing an independent look of the identical scene
Note 1 to entry: The resulting image formed by incoherent summing of these looks is characterized by reduced
speckle and degraded spatial resolution.
4.14
thematic data
gridded data (4.11) whose attribute (4.1) values describe characteristics of a grid (4.10) coverage feature
in a grid format
Note 1 to entry: Most gridded thematic data are derived from imagery (4.12) data using geophysical/atmospheric
inversion algorithms. Gridded thematic data may also be obtained from other sources such as digitization of
topographic map sheets.
4.15
ungeoreferenced grid
gridded data (4.11) that does not include any information that can be used to determine a cell’s
geographic coordinate values
EXAMPLE A digital photo without georectification information included.
5 Symbols and abbreviated terms
5.1 Abbreviated terms
BIIF Basic Image Interchange Format
CRS Coordinate Reference System
DEM Digital Elevation Model
EOS Earth Observing System
HDF Hierarchical Data Format
JPEG200 Joint Photographic Experts Group 2000
netCDF network Common Data Form
SAR Synthetic aperture radar
TIFF Tagged Image File Format
UML Unified Modeling Language
5.2 UML notations
This Technical Specification presents conceptual models of imagery and gridded data, specified in the
2)
Unified Modeling Language (UML). ISO 19103 describes the way in which UML is used in the ISO 19100
family of standards. It differs from standard UML only in the existence and interpretation of some
special stereotypes, in particular, “CodeList”. ISO 19103 specifies the basic data types used in the UML
model. The UML diagrams defined in this Technical Specification represent conceptual models only and
are not intended for automatic encoding within XML Schema.
Annex B contains a data dictionary for the UML models defined in this Technical Specification.
Table 1 lists the prefixes of UML classes used in the referenced ISO standards in this Technical
Specification. IE is the prefix of the UML classes defined in this Technical Specification. In Table 1, the
first column describes the prefix used in the packages of the second column and the third column is the
ISO standard where the package is defined.
2) This International Standard is under preparation.
4 © ISO 2016 – All rights reserved
Table 1 — UML package identifiers
Identifier Package International
Standard
EX Extent information ISO 19115-1
LE Lineage extended ISO 19115-2
LI Lineage ISO 19115-1
MD Metadata ISO 19115-1
MI Metadata for imagery ISO 19115-2
SD Sensor data ISO/TS 19130
CV Coverage ISO 19123
CA Calibration and validation of sensor ISO/TS 19159-1
GM Geometry root ISO 19107
IE Content components and encoding rules for imagery and ISO 19163
gridded data
6 Related International Standards
Figure 1 illustrates the relationship between this Technical Specification and other International
Standards related to imagery and gridded data. This Technical Specification fits the reference model
defined in ISO/TS 19101-2 and follows the abstract content framework defined in ISO 19123. CV_Coverage
is chosen as the super-class to establish the content component model of imagery and gridded data.
This Technical Specification refers to metadata related to imagery and gridded data defined in
ISO 19115-1 and ISO 19115-2, the sensor information related to acquisition of imagery defined in
ISO/TS 19130 and the calibration and validation of sensors defined in ISO/TS 19159-1.
This Technical Specification defines an UML schema for the content model which can be bound with any
widely used data formats of imagery and gridded data, such as GeoTIFF, BIIF, JPEG 2000, NetCDF and HDF.
ISO 19115-1:2014 Metadata - Fundamentals ISO 19115-2:2009 Metadata - Imagery
ISO 19123:2005 Coverages ISO 19159-1 Calibration and Validation
metadata
metadata
calibration
abstract content on coverage
ISO 19163 Content components and encoding rules
sensor information
standardization requirements
binding binding
ISO 19101-2:2008 Imagery Reference ISO/TS 19130:2010 Sensor Data
binding binding binding
GeoTIFF NetCDF
HDF-EOS JPEG 2000 BIIF
Figure 1 — Relationship with related International Standards
7 Categories of imagery and gridded data
7.1 General
Clause 7 categorizes imagery according to digital sensor types and gridded data according to the
attribute and geometry properties. The required content components of each data category are
specified in UML content models of Clause 8.
The intention of this Technical Specification is not to define a comprehensive classification system
of imagery and gridded data, but to specify the contents of some categories of them. A hierarchical
category framework of imagery and gridded data is defined in Figure 2. The root of the framework is
Coverage defined in ISO 19123. Imagery and gridded data are a subclass of coverage. The two subclasses
of imagery and gridded data, which are imagery data and thematic gridded data, are defined in this
Technical Specification.
6 © ISO 2016 – All rights reserved
Coverage Data
Imagery and Gridded Data
Thematic Gridded Data Imagery Data
Numerical Categorical Optical Imagery Synthetic Imagery
Microw av e Data
Thematic Data Thematic Data Data Data
Active Passive Fused Imagery Simulated
Microw av e Data Microw av e Data Data Imagery Data
SAR Data Radiometer Data
Figure 2 — Categories of imagery and gridded data
7.2 Imagery
Imagery is a kind of coverage whose attribute values are numerical representations of the physical
parameters (e.g. radiance) measured by imagery sensors. According to ISO/TS 19101-2, a sensor can
be classified as an electromagnetic energy sensor or a mechanical wave energy sensor based on the
type of energy sensed by the sensor. The former class is further categorized into an optical sensor, a
microwave sensor or a light detection and ranging sensor (LiDAR) according to the measurand of the
sensor (ISO/TS 19130). SONAR is a typical example of mechanical wave energy sensor. These sensors
produce optical, microwave, LiDAR and SONAR imagery data, respectively.
The data acquired by LiDAR and SONAR, which exhibit distinct characteristics that differ from optical
images and microwave data, are not covered by this Technical Specification due to the limit of the scope.
These types of data may be addressed in a future extension or subsequent part of ISO 19163.
Optical images are acquired from visible and infrared sensors by detecting the radiation reflected or
emitted from target objects (ISO/TS 19101-2). Different materials reflect, absorb or emit radiation at
different wavelengths, and accordingly each object type has a spectral signature. Analysing spectral
signatures within remotely sensed images identifies differentiation between these objects. Thus,
images may be classified depending on the number of spectral bands, for example panchromatic,
multispectral and hyperspectral.
Microwave data are classified into active and passive microwave data corresponding to active and
passive microwave sensors. Synthetic aperture radar (SAR) is a typical active microwave sensor that
uses a series of radar pulses transmitted and received over time from a moving platform to create an
image, as specified by ISO/TS 19130.
Passive microwave sensors measure the energy and/or the phase of microwaves emitted from objects.
Passive microwave data can be used to derive various geophysical quantities, such as rainfall, sea
surface temperature, vertical water vapour, ocean surface wind speed, sea ice parameters, snow
water equivalent and soil surface moisture (ISO/TS 19101-2). There is more than one type of passive
microwave data, but this Technical Specification only specifies the contents of microwave imaging
radiometer data.
In addition to images acquired directly by a certain sensor, image fusion and image simulation
techniques can generate new images from original images, fused image and simulated image. The image
fusion techniques allow the integration of images from different sources. The fused image can have
complementary multisource characteristics. For example, a higher-spatial-resolution panchromatic
image is fused with lower-spatial-resolution multispectral data to provide multispectral information
with higher spatial resolution; optical images and SAR data can be merged in order to simultaneously
exploit the spectral and textural information.
7.3 Gridded data
Gridded data are a subtype of coverage (ISO 19115-2). In order to avoid the content overlap, this
Technical Specification limits gridded data to regularly spaced gridded thematic data whose attribute
values are values of a geographic feature (e.g. altitude, leaf area index) and whose geometric state is
regularly spaced quadrilateral grid.
Most thematic data are derived from imagery by information retrieval processing with domain-specific
or application-specific algorithms. Some thematic data, such as Digital Elevation Model (DEM) and
scanned or rasterized data, are not necessarily derived from imagery data. DEM and rasterized data
are often integrated with imagery data in various applications, for example a 3D virtual terrain. There
are several different geometric states for thematic data, gridded-based, point-based, surface-based
and segmented based one (ISO/TS 19101-2). This Technical Specification only defines the content of
regular-gridded thematic data.
Thematic data have categorical attributes or numerical attributes of a geographic feature or
phenomenon. Typical examples of numerical data are DEM and land surface temperature, and those of
categorical data are land cover and land use data. Categorical attributes shall not be interpolated.
8 Content component models
8.1 General
This Technical Specification defines the required content components of imagery and gridded data
based on the hierarchical category framework (Figure 2). 8.2 to 8.4 describe these categories using
UML model diagrams and the corresponding data dictionary is given in Annex B.
8.2 Imagery and gridded data
8.2.1 General
The structure and association of imagery and gridded data are illustrated in Figure 3. The topmost
class of this Technical Specification, IE_ImageryAndGriddedData, is a subclass of CV_Coverage defined
in ISO 19123. The information of coordinate reference system is specified in ISO 19111. IE_Georectified
and IE_Georeferenceable are aggregated to describe the associate geolocation information of
georectified and georeferenceable data, respectively.
The data dictionary of this UML diagram is given in B.1.
8 © ISO 2016 – All rights reserved
From ISO 19123:2005
«type»
Coverage Core::CV_Coverage
0.*
CoordinateReferenceSystem
From ISO 19111:2007 shown for informative purposes only
+CRS
IO_IdentiiedObjectBase
IE_ImageryAndGriddedData
RS_ReferenceSystem
«type»
Coordinate Reference Systems::SC_CRS
georeferenceableSpatialInfo
georecti’iedSpatialInfo
{sizeof(georecti’iedSpatialInfo)+
sizeof(georeferenceableSpatialInfo)=1}
0.1
0.1
IE_Georectiied IE_Georeferenceable
+ geolocationSource: IE_GeolocationSourceCode [1.*] + geolocationInfo: SD_SensorModel
+ correctionModel: IE_GeometricCorrectionModelCode
+ checkPoints: IE_LocationGCP [1.*]
From ISO 19115-1:2014
MD_GridSpatialRepresentation
MD_GridSpatialRepresentation
Spatial representation information::MD_Georectiied Spatial representation information::MD_Georeferenceable
«CodeList» «CodeList» «union»
IE_GeolocationSourceCode IE_GeometricCorrectionModelCode IE_LocationGCP
+ GCP + CorrespondenceModel + GCPRepository: SD_GCPRepository
+ SystemParameters + PhysicalSensorModel + imageIdenti’iableGCP: SD_ImageIdenti’iableGCP
+ SystemParameters+DEM + TrueReplacementModel + locationGCP: SD_GCPLocation
+ SystemParameters+GCP
+ SystemParameters+GCP+DEM
+ GCP+DEM
Figure 3 — IE_ImageryAndGriddedData
8.2.2 IE_ImageryAndGriddedData
IE_ImageryAndGriddedData inherits the attributes of CV_Coverage and defines an attribute
interpolationType to identify the interpolation method that shall be used to derive a feature attribute
value at any direct position.
8.2.3 IE_Georectified
IE_Georectified specifies the source of geolocations and the model used for geometric correction. The
attribute checkPoints specifies the format and source of ground control points used as check points in a
georectified image. The ground control points can be given in coordinates (defined in SD_LocationGCP),
or marked in images or described in texts (defined in SD_ImageIdentifiableGCP), or accessed from a
GCP repository based on access restrictions (defined in SD_GCPRepository). SD_LocationGCP inherits
the attributes of MI_GCP from ISO 19115-2 and adds a grid coordinate of GCP.
More spatial attributes about the check points and other attributes are inherited from MD_Georectified
defined in ISO 19115-1.
8.2.4 IE_Georeferenceable
Geolocation information of georeferenceable data shall be acquired from SD_SensorModel, which
defines the geometric correction models. More spatial attributes about georeferenceable data are
inherited from MD_Georeferenceable defined in ISO 19115-1.
8.3 Thematic gridded data
8.3.1 IE_ThematicGriddedData
IE_ThematicGriddedData (Figure 4) contains the common characteristics of thematic gridded data. The
attribute dataInfo provides the basic information about the data (defined in MD_CoverageDescription
of ISO 19115-1). The attributes, annotation and geographicFeature, define vector-based annotations and
features overlapped on the gridded data in order to improve the understanding.
The processing and the source for producing the thematic gridded data are described with the attribute
retrievalProcessingInfo and the attribute sourceInfo, respectively.
There are two subtypes of thematic gridded data, categorical and numerical, which are specified with
IE_CategoricalGriddedData class and IE_NumericalGriddedData class.
The data dictionary for the UML diagram in 8.3 (Figure 4) is given in B.2.
8.3.2 IE_CategoricalGriddedData
IE_CategoricalGriddedData specifies the number of categories of a categorical data layer
(numberOfCategories), the description on the classification to produce the categorical data
(classificationDescription), and the number of bits for recording each value (bitsPerValue). IE_
CategoricalValueAndColour describes the lookup table of the relationship between each value and its
semantics and colour palette of each category. The content of “description” may be a reference to a
classification legend item as defined in ISO 19144-1.
8.3.3 IE_NumericalGriddedData
IE_NumericalGriddedData specifies the meaning of the numerical gridded data with the attribute
valueDescription and inherits the information about the maximum and minimum value, units,
bitsPerValue and so on from MD_SampleDimension.
10 © ISO 2016 – All rights reserved
CV_Coverage
IE_ImageryandGriddedData::IE_ImageryAndGriddedData
+ interpolationType: CV_InterpolationMethod [0.1]
IE_ThematicGriddedData
+ dataInfo: MD_CoverageDescription
+ annotation: GM_Object [0.*]
+ geographicFeature: GM_Object [0.*]
+ retrievalProcessingInfo: LE_Processing [0.*]
+ sourceInfo: CharacterString [0.*]
{sizeof(datainfo.attributeGroup.attribute.MD_SampleDimension)>1}
IE_CategoricalGriddedData IE_NumericalGriddedData
+ classi‡icationDescription: CharacterString [0.1] + valueDescription: CharacterString
+ numberOfCategories: Integer
+ bitsPerValue: Integer [0.1]
lookupTable
n
{n=numberofCategories}
«DataType»
IE_CategoricalValueAndColour
IE_ColourPalette
+ categoryName: CharacterString
+ red: Integer
+ colourPalette: IE_ColourPalette [0.1]
+ green: Integer
+ description: CharacterString [0.1]
+ blue: Integer
+ value: Integer
Figure 4 — IE_ThematicGriddedData
8.4 Imagery
8.4.1 IE_Imagery
The class IE_Imagery (Figure 5) inherits the attributes from IE_ImageryAndGriddedData. In addition,
IE_Imagery defines the following required information: acquisition time, image parameters, number of
bands, platform, sensor, processing action, calibration and validation of sensor.
The attribute imageDescription gives the basic parameters on acquiring image data. The attribute
processingAction records the processing steps being taken on the dataset. LE_ProcessingActionCode
lists the possible actions for image processing.
The attribute radiometricCorrectionType describes the type of image radiometric correction taken,
which is either absolute correction or relative correction. The attribute sensorCalibrationValidation
with its type CA_CalibrationValidation specifies the information required for sensor calibration and
validation. CA_CalibrationValidation is defined in ISO/TS 19159-1.
CV_Coverage
«CodeList»
IE_RadiometricCalibrationTypeCode
IE_ImageryandGriddedData::IE_ImageryAndGriddedData
+ AbsoluteRadiometricCalibration
+ interpolationType: CV_InterpolationMethod [0.1]
+ RelativeRadiometricCalibration
«CodeList»
IE_ProcessingActionCode
+ ImageEnhancement
+ ImageFusion
+ ImageSmoothing
IE_Imagery
+ acquisitionTime: TM_Period
+ imageDescription: MD_ImageDescription [0.1]
mosaicInfo
{isMosaic=TRUE}
+ isMosaic: Boolean
+ numberofBands: Integer
1.*
+ processingAction: IE_ProcessingActionCode [0.1]
+ radiometricCalibrationType: IE_RadiometricCalibrationTypeCode [0.1]
IE_MosaicElement
+ sensorCalibrationValidation: CA_CalibrationValidation [0.1]
+ platformInfo: MI_Platform [0.1]
+ elementID: Integer
+ sensorInfo: MI_Instrument [0.1]
+ acquisitionTime: TM_Period
+ geometry: EX_Extent
IE_OpticalImage:: IE_MicrowaveData:: IE_SyntheticImage
IE_OpticalImage IE_MicrowaveData
+ intendedUse: MD_Usage [0.1]
band information
IE_SimulatedImage IE_FusedImage
+ simulateMethod: CharacterString + numberOfSourceImages: Integer
+ provenance: LI_Lineage [0.1] + processingSteps: LE_ProcessStep [0.*]
n
{n=numberofBands}
From ISO 19115-2:2009 shown for informative purposes only
MD_Band
Content information - Imagery::MI_Band
Figure 5 — IE_Imagery
The attribute sensorInfo, defined in MI_Instrument of ISO 19115-2, contains basic information about the
sensor. The attributes platformInfo, defined in MI_Platform of ISO 19115-2, specifies the information of
a platform on which the sensor is mounted.
If an image is a mosaic of multiple images, i.e. IsMosaic = TRUE, the acquisition time, extent and
identification of each image shall be recorded as a mosaic element, IE_MosaicElement. The geometry
attribute for the extent can contain multiple polygons, as described in ISO 19115-1.
IE_Imagery associates with n (n = numberofBands) MI_Band classes, each of which describes the
information of a band. The detailed information of MI_Band is defined in ISO 19115-2.
According to the categories of imagery and gridded data (Figure 2), IE_Imagery has three subclasses,
IE_OpticalImage (8.4.4), IE_MicrowaveData (8.4.5) and IE_SyntheticImage. IE_SyntheticImage
defines the intended usage of the imagery and it has two subclasses, IE_FusedImage (8.4.2) and IE_
SimulatedImage (8.4.3).
The data dictionary for the UML diagrams in 8.4 (Figure 5 to 9) is given in B.3.
12 © ISO 2016 – All rights reserved
8.4.2 IE_FusedImage
The class IE_FusedImage describes the number of source images and the processing steps used to
produce a fused image.
8.4.3 IE_SimulatedImage
The class IE_SimulatedImage describes the method for simulating an image and its provenance.
Simulated images are used to evaluate the characteristics of a sensor system and validate the retrieval
algorithms prior to the system being put into the operational environment.
8.4.4 IE_OpticalImage
The class IE_OpticalImage (Figure 6) contains the information specific to images acquired by optical
sensors. The attribute opticalImageType identifies the type of an optical image, such as a hyperspectral,
infrared, multispectral, panchromatic or other image. The attribute opticalSensorType specifies the
type of an optical sensor.
IE_ImageryAndGriddedData
«CodeList»
IE_OpticalImageTypeCode IE_Imagery::IE_Imagery
+ HyperspectralImage
+ InfraredImage
+ MultispectralImage
+ PanchromaticImage
+ Other
«CodeList»
IE_OpticalImage
IE_OpticalSensorTypeCode
+ opticalImageType: IE_OpticalImageTypeCode [0.1]
+ Frame
+ opticalSensorType: IE_OpticalSensorTypeCode [0.1]
+ Pushbroom
+ Whiskbroom
+ Other
Figure 6 — IE_OpticalImage
8.4.5 IE_MicrowaveData
As shown in Figure 7, IE_MicrowaveData has two subclasses, which are IE_ActiveMWData and IE_
PassiveMWData. There is more than one type of active and passive microwave data, but this Technical
Specification only specifies the contents of data from SAR (IE_SARData) and microwave radiometers
(IE_RadiometerData).
IE_Imagery
IE_MicrowaveData
IE_ActiveMWData IE_PassiveMWData
IE_SARData::IE_SARData IE_RadiometerData::IE_RadiometerData
Figure 7 — IE_MicrowaveData
8.4.6 IE_SARData
The class IE_SARData (Figure 8) contains characteristics of SAR data.
IE_SARData includes the basic information on the system’s wavelength, incidence angle, SAR imaging
mode and sensor. IE_SARSensor represents the SAR sensor and platform information. It includes a
series of IE_OrbitParameters to interpolate the precise orbit information of the sensor during image
acquisition. It also includes a series of IE_SARDopplerCentroidParameters to allow the calculation of
the Doppler centroid for a certain point in time during the image acquisition.
IE_SARDopplerCentroidParameter gives a point in time for which the given values are valid and three
polynomial coefficients from which the Doppler centroid can be calculated:
i
DopperCentroidp=−olynomialc_(oeff tt ) (1)
∑ iref
i=0
where polynomial_coeff is the coefficient given in the IE_SARDopplerCentroidParameter with the
i
exponent = i and t is the reference point given in IE_SARDopplerCentroidParameter.
ref
IE_SARComplexData represents a SAR image containing the complex backscattering information
including real and imaginary values. It includes a sequence of IE_SARComplexLayerTypesCode for the
characterization of the layers in the complex SAR image, the SAR sensor information, as well as the line
and pixel spacing in seconds.
IE_SARAmplitudeData represents a SAR image containing only the amplitude information. It includes
SAR sensor information, an optional calibration value, as well as the number of looks in azimuth and
range direction.
14 © ISO 2016 – All rights reserved
IE_MicrowaveData
«CodeList»
...
Questions, Comments and Discussion
Ask us and Technical Secretary will try to provide an answer. You can facilitate discussion about the standard in here.