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Created: January 31, 2003.
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OGC Working Group Issues Draft Specification for Sensor Model Language (SensorML).

The Open GIS Consortium Natural Resources and Environment (NRE) Working Group has released a draft specification for Sensor Model Language (SensorML) for In-Situ and Remote Sensors, together with fifteen XML Schemas. SensorML "provides an XML schema for defining the geometric, dynamic, and observational characteristics of a sensor. Sensors are devices for the measurement of physical quantities. There are a great variety of sensor types from simple visual thermometers to complex electron microscopes and earth observing satellites... The standardization of a Sensor Model Language (SensorML) and the availability of SensorML documents for all Earth observing sensors will allow for significant opportunities for software systems to support the processing, analysis, and visual fusion of multiple sensors. SensorML does not provide a detailed description of the hardware design of a sensor but rather it is a general schema for describing a functional model of the sensor. The schema is designed such that it can be used to support the processing and geolocation of data from virtually any sensor, whether mobile or dynamic, in-situ or remotely sensed, or active or passive. This allows one to develop general, yet robust, software that can process and geolocate data from a wide variety of sensors ranging from simple to complex sensor systems. SensorML supports both rigorous sensor models and mathematical sensor models. A rigorous sensor model is defined here as one that describes the geometry and dynamics of the instrument and provides specialized with the ability to utilize this information along with position and orientation of the platform in order to derive geolocation of the sensor data. sensor models are typically derived using a rigorous model, perhaps augmented by human interaction. These mathematical models typically hide the characteristics of the sensor, and allow for geolocation of sensor data through the use of polynomial functions."

Bibliographic information: Sensor Model Language (SensorML) for In-situ and Remote Sensors. Edited by Mike Botts (University of Alabama in Huntsville). Open GIS Discussion Paper [not an adopted standard]. Open GIS Consortium Inc. Issued by the OGC Natural Resources and Environment (NRE) Working Group. Publication Date: 2002-12-20. Reference number: OGC 02-026r4. Version 0.7. 118 pages. With associated XML Schemas.


Sensors are "capable of observing and measuring particular properties [for example, properties such as temperature, count, rock type, chemical concentration, or radiation emissivity]. Either by design or as a result of operational conditions, these sensors have particular response characteristics that can be used to determine the values of the measurements, as well as assess the quality of these measurements. In addition to the response characteristics, the sensor system has properties of location and orientation that allow one to associate the measured values with a particular geospatial location at a particular time. The role of the SensorML is to provide characteristics required for processing, georegistering, and assessing the quality of measurements from sensor systems.

SensorML Overview

SensorML is an XML schema for defining the geometric, dynamic, and observational characteristics of a sensor. The purpose of SensorML is: (1) to provide general sensor information in support of data discovery; (2) to support the processing and analysis of the sensor measurements; (3) to support the geolocation of the measured data; (4) to provide performance characteristics (e.g., accuracy, threshold, etc.); (5) to archive fundamental properties and assumptions regarding sensor. SensorML provides functional model for sensor, not detail description of hardware. It supports rigorous models, which can describe sensor parameters independent of platform and target, as well as mathematical models which can directly map between sensor and target space. SensorML can apply to virtually any sensor, whether in-situ or remote sensors, and whether it is mounted on a stationary or dynamic platform. Geolocation of observed data will be supported through "plug-n-play" models for sensor grids, frame cameras, scanners, and replacement sensor (RPC - Rapid Positioning Coordinates/Rational Polynomial Coefficients).

Through ongoing efforts of the UAH/VAST team and others, it has been shown that the SensorML concept provides significant advantages for processing, visualization, and data mining of dynamic sensor data within a distributed desktop environment. In addition, the on-board use and direct distribution of a SensorML by the sensor itself, can provide additional major benefits with regard to the remote in-the-field processing of real-time sensor data, for autonomous operation of sensor systems (e.g. guidance, on-board processing, and target recognition), and for cross-communication within a SensorWeb among aircraft, UAVs, satellites, and ground-based sensors.

The purpose of this [Discussion Paper] release is to allow public comment and discussion regarding the proposed SensorML specification before being considered for approval as an OpenGIS Technical Specification. We also recognize that there are several individuals and activities within other communities that can provide valuable input to the design of SensorML and particularly the design of specific Sensor Models (for geolocation of observations) and Sensor Reponse characteristics... Under the auspices of the Global Mapping Task Team (GMTT) within the international Committee for Earth Observing Satellites (CEOS), Mike Botts began development of an XML-based Sensor Model Language for describing the geometric, dynamic, and radiometric properties of dynamic sensors. Development and testing of SensorML has progressed primarily under the auspices of the OpenGIS Consortium, through funding from the NASA AIST program, EPA, NIMA, and JITC. The SensorML is also under consideration by the ISO TC211 Project 19130. [from the announcement]

OGC Web Services 1.2 Testbed Initiative

Live sensors were featured in a recent demonstration by participants in the OGC Web Services 1.2 Testbed Initiative. "The demonstration focused on three emergency response situations in a mock Department of Homeland Security Emergency Operations Center, showing how recent advances in OGC's interoperability architecture enable integration of geospatial information and geoprocessing software via the World Wide Web. Attendees saw the use of live sensors, the tasking of an unmanned aerial vehicle (UAV) and the integration of data, services, and other elements hosted on servers worldwide... Some of the work in OWS 1.2 focused on enhancing existing OpenGIS Specifications such as Geography Markup Language and Web Feature Service while others defined new interfaces that may someday become specifications, including such technologies as image handling, Web-based sensor planning and collection, service registries, symbol/style management, and composite services (linking or chaining one service to another). The UAV scenario illustrated mobile targeting -- using an aerial sensor to capture images over an area -- and allowed analysts to examine them to determine if a specific vehicle entered the area of interest. Behind the scenes a series of services executing together, a composite service, made this possible. Draft interfaces for a variety of services, including a Sensor Planning Service, Web Notification Service, Sensor Collection Service, Sensor Model Language (SensorML), Image Archive Service, Web Coverage Service, and Coverage Portrayal Service each played a part in the procedure. These services, all linked together, demonstrated a method to gather imagery in a rapid fashion, potentially within minutes, and provide it for analysis..."

SensorML Description

The information provided by SensorML includes

  • Observation characteristics: Physical properties measured (e.g., radiometry, temperature, concentration, etc.), Quality characteristics (e.g., accuracy, precision), and Response characteristics (e.g., spectral curve, temporal response, etc.)
  • Geometry Characteristics: Size, shape, spatial weight function (e.g., point spread function) of individual samples; Geometric and temporal characteristics of sensor and sample collections (e.g., scans or arrays) that are required for metric exploitation
  • Description and Documentation: Overall information about the sensor; History and reference information supporting the SensorML document.

A SensorML document can be considered a 'living' description of a sensor. The SensorML document can begin as a template document, which is initially created using the sensor model design and is then appended or altered during the manufacturing, calibration, deployment, maintenance, and ultimately the removal of the sensor from service. Much of the specification of a sensor is shared by all sensor instances of the same model-number from the same manufacturer. This will typically include a description of measured properties, sample geometry, and the geometry and dynamics of any internal sampling arrays (such as scan patterns or frame camera properties). This initial template may include in addition some calibration parameters.

The standardization of a Sensor Model Language (SensorML) and the availability of SensorML documents for all Earth observing sensors will allow for significant opportunities for software systems to support the processing, analysis, and visual fusion of multiple sensors. Traditionally software that supported multiple sensors has been forced to deal with proprietary software designed for each individual sensor... In contrast, the availability of standard SensorML files allows for the development of general navigation software capable of geolocating and transforming any sensor data for which a SensorML file exists. Referred to as an Observation Dynamics Model (ODM), this concept is built around the availability of separate description files for providing sensor-system specific information regarding platform position and rotation, instrument geometry and dynamics, target planet shape and position, and perhaps other time-tagged information, such as data dropouts, instrument modes of operation, or spacecraft clock adjustments.

One intent of a standard SensorML is to allow the development of software libraries that can parse these files and calculate required look angles and timing for each sensor pixel. Other efforts are establishing standards for storage and transmission of sensor platform location and rotation in order to insure that such formats are also maintained, available, and readable by similar APIs... [excerpted from the v0.7 draft discussion paper]

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