Position and attitude determination Image acquisition request

© ISO 2001 All rights reserved 25 Validation is the process of assessing, by independent means, the quality of the data products derived from the system outputs [CEOS] Calibration of sensor data is critical for comparison of observations over time and between sensors. Sensor data traceable to standard sources is critical to the use of observations in science-based activities. For example, UV monitoring from space offers the opportunity to achieve global coverage of the UV radiation field. Derived information is only useful to policy makers if the underlying data are rigorously quality assured, i.e. are “of known quality and adequate for their intended use”. Calibration is not always critical. For small target detection in single-channel data, image calibraion is often unnecessary because there is no concern for precise measurements only the contrast between the target and its background. Techniques for calibration are based on metrology that establishes general rules for evaluating and expressing uncertainty in measurement. Metrology is mainly concerned with the uncertainty in the measurement of a well-defined physical quantity - the measurand - that can be characterised by an essentially unique value. It also covers the evaluation and expression of uncertainty associated with the experiment design, measurement methods, and complex systems. Metrology is focused on measurable quantities. A measurable quanity is an attribute of a phenomenon, body or substance that may be distinguished qualitatively and determined quantitatively [VIM]. A measurement is a set of operations having the object of determining a value of a quantity [VIM]. A measurand is a particular quantity subject to measurement [VIM]. A focus of calibration is to determine the accuracy of measurement. Accuracy is a qualitative concept that described the closeness of the agreement between the result of a measurement and a true value of the measurand [VIM]. Quantiatively the uncertainty of measurement characterizes the dispersion of the values that could reasonably be attributed to the measurand. Editor’s note ISO 19113 references ISO 3534-1 for definition of accuracy which differs from VIM definition Uncertainty of measurement comprises, in general, many components. Some of these components may be evaluated from the statistical distribution of the results of series of measurements and can be characterized by experimental standard deviations. The other components, which can also be characterized by standard deviations, are evaluated from assumed probability distributions based on experience or other information. It is understood that the result of the measurement is the best estimate of the value of the measurand, and that all components of uncertainty, including those arising from systematic effects, such as components associated with corrections and reference standards, contribute to the dispersion. For calibration, metrology defines the techniques of traceability. Traceablility is the property of the result of a measurement or the value of a standard whereby it can be related to stated references, usually national or international standards, through an unbroken chain of comparisons all having stated uncertainties [VIM] For image sensing data requiring calibration, the uncertainty of the sensor shall be measured. Determination of uncertainty for an imaging sensor traceability shall be defined.

8.2.6 Position and attitude determination

Concurrent with attribute value data, the imaging sensor and its associated positioning system shall record location and attitude information. This information may be applied immediately to geo-located the data or may be carried with the data, supporting geolocation at a later time. A positioning system is a system of instrumental and computational components for determining position. Examples of positioning systems is provided in © ISO 2001 All rights reserved 26 ISO 19116, Geographic infomation — Positioning services, specifies the data structure and content of an interface that permits communication between position providing devices and position using devices so that the position using devices can obtain and unambiguously interpret position information and determine whether the results meet the requirements of the use. Table 8 - Positioning systems Inertial positioning system Positioning system employing accelerometers, gyroscopes, and computer as integral components to determine coordinates of points or objects relative to an initial known reference point Satellite positioning system Positioning system based upon receipt of signals broadcast from satellites In this context, satellite positioning implies the use of radio signals transmitted from “active” artificial objects orbiting the Earth and received by “passive” instruments on or near the Earth’s surface to determine position, velocity, andor attitude of an object. Examples are GPS and GLONASS. Integrated positioning system Positioning system incorporating two or more positioning technologies Measurements produced by each positioning technology in an integrated system may be any of position, motion, or attitude. There may be redundant measurements. When combined, a unified position, motion, or attitude is determined.

8.2.7 Image acquisition request

Editors note: develop a UML class definition for image acquisition request Issues: data type and quality, observationvisibility requirements, data for planning and tasking

8.3 Geographic imagery information – processed, located, gridded

8.3.1 IG_Image 8.3.1.1 Introduction This clause defines a geographic image as the class IG_Image. IG_Image is an information object. IG_Image is a type of geographic coverage. The preceding clause described sensors for acquiring data that are used to create images. When the sensor data is combined with descriptive representation information an imagery information object is created. Information is a combination of data and representation information ISO 14721. In this Technical Specification, data is a grid of image values, e.g., sensor data, and the representation information is, for example, metadata defined in ISO 19115 and ISO 19115-2. This clause defines how imagery information objects are to be structured.