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GEOMS – Generic Earth Observation Metadata Standard [1] is a metadata standard used for archiving data from groundbased networks, like the Network for the Detection of Atmospheric Composition Change (NDACC), [2] and for using this kind of data for the validation of NASA [3] and ESA [4] satellite data.
ISO/DIS 19157 Geographic information -- Data quality; ISO/TS 19158:2012 Geographic information—Quality assurance of data supply; ISO/DTS 19159-1 Geographic information -- Calibration and validation of remote sensing imagery sensors and data -- Part 1: Optical sensors; ISO/WD 19160-1 Addressing-- Part 1: Conceptual model
ISO 19157:2013 Geographic information – Data quality ISO/TS 19157-2:2016 Part 2: XML schema implementation; ISO/TS 19158:2012 Geographic information – Quality assurance of data supply; ISO/TS 19159 Geographic information – Calibration and validation of remote sensing imagery sensors and data ISO/TS 19159-1:2014 Part 1: Optical sensors
The quality of remote sensing data consists of its spatial, spectral, radiometric and temporal resolutions. Spatial resolution The size of a pixel that is recorded in a raster image – typically pixels may correspond to square areas ranging in side length from 1 to 1,000 metres (3.3 to 3,280.8 ft).
ISO 28902 Air quality – Environmental meteorology ISO 28902-1:2012 Part 1: Ground-based remote sensing of visual range by lidar; ISO 28902-2:2017 Part 2: Ground-based remote sensing of wind by heterodyne pulsed Doppler lidar; ISO/TR 28980:2007 Ophthalmic optics – Spectacle lenses – Parameters affecting lens power measurement
Quantitative remote sensing is a branch of remote sensing. The quantitative remote sensing system does not directly measure land surface parameters of interest. Instead, the signature remote sensors receive is electromagnetic radiation reflected, scattered, and emitted from both the surface and the atmosphere . [ 1 ]
Remote sensing depends on the interaction of a source of energy with a target, and energy measured from the target. [20] In the "Remote Sensing" diagram, Source 1a is an independent natural source such as the Sun. Source 1b is a source, perhaps manmade, that illuminates the target, such as a searchlight or ground radar transmitter.
Data quality control is the process of controlling the usage of data for an application or a process. This process is performed both before and after a Data Quality Assurance (QA) process, which consists of discovery of data inconsistency and correction. Before: Restricts inputs