global_attributes:
title:
Pixel Quality Statistics 25m 2.0.0
source:
Remotely observed surface reflectance and modelled cloud/shadow
license:
CC BY Attribution 4.0 International License
summary:
The Pixel Quality (PQ) product is an assessment of whether an image pixel represents an un-obscured unsaturated observation of the Earth's surface and whether the pixel is represented in each spectral band. The PQ product allows users to produce masks which can be used to exclude affected pixels from which don't meet their quality criteria from further analysis. The capacity to automatically exclude such pixels from analysis is essential for emerging multi-temporal analysis techniques that make use of every quality assured pixel within a time series of observations. The PQ-STATS is a countof how many times a pixel contains a clear observation of the surface (land or sea). The count of clean observations provides users with an understanding of how many observations are available for analysis at a particular location for a particular period of time. PQ-STATS is available as a per year summary and as a 'whole of archive' summary (1987 to present).
keywords:
AU/GA,NASA/GSFC/SED/ESD/LANDSAT,ETM+,TM,OLI,EARTH SCIENCE
platform:
LANDSAT-5,LANDSAT-7,LANDSAT-8
instrument:
TM,ETM+,OLI
references:
- Berk, A., Anderson, G.P., Acharya, P.K., Hoke, M.L., Chetwynd, J.H., Bernstein, L.S., Shettle, E.P., Matthew, M.W., and Adler-Golden, S.M. (2003) Modtran 4 Version 3 Revision 1 User s manual. Airforce Research Laboratory, Hanscom, MA, USA. - Chander, G., Markham, B.L., and Helder, D.L. (2009) Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment 113, 893-903. - Edberg, R., and Oliver, S. (2013) Projection-Independent Earth-Solar-Sensor Geometry for Surface Reflectance Correction. Submitted to IGARSS 2013, Melbourne. - Forrest, R.B. (1981) Simulation of orbital image-sensor geometry, Photogrammetric Engineering and Remote Sensing 47, 1187-93. - GA and CSIRO (2010) 1 second SRTM Derived Digital Elevation Models User Guide. Version 1.03. GA, Canberra. - Irish, R. (2000) Landsat 7 Automatic Cloud Cover Assessment, sourced: http://landsathandbook.gsfc.nasa.gov/pdfs/ACCA_SPIE_paper.pdf, last accessed 12/11/2012. - Irons, J.R., Dwyer, J.L., and Barsi, J.A. (2012) The next Landsat satellite: The Landsat Data Continuity Mission. Remote Sensing of Environment (2012), doi:10.1016/j.rse.2011.08.026 - Kalnay, E. Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K.C., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R. Jenne, R., Joseph, D. (1996) The NCEP/NCAR 40-Year Reanalysis Project. Bulletin of the American Meteorological Society 77, 437-71. - Li, F., Jupp, D.L.B., Reddy, S., Lymburner, L., Mueller, N., Tan, P., and Islam, A. (2010) An Evaluation of the Use of Atmospheric and BRDF Correction to Standardize Landsat Data. IEEE J. Selected Topics in Applied Earth Observations and Remote Sensing 3, 257-70.;Li, F. (2010) ARG25 Algorithm Theoretical Basis Document. GA, Canberra. - Li, F., Jupp, D.L.B., Thankappan, M., Lymburner, L., Mueller, N., Lewis, A., and Held, A. (2012) A physics-based atmopheric and BRDF correction for Landsat data over mountainous terrain. Remote Sensing of Environment 124, 756-70. - Lubke, M. (2012) Landsat Geometry Calibration/Validation Update. Presentation at LTWG #21, 25 September 2012, Sioux Falls. USGS, USA. - OGC (2006) OpenGIS Web Map Server Implementation Specification (Ed: Jeff de la Beaujardiere) Ref. OGC 06-042. - OGC (2010) OGC WCS 2.0 Interface Standard - Core. (Ed: Peter Baumann) Ref. OGC 09-110r3. - OGC (2013) CF-netCDF3 Data Model Extension Standard (Eds: Ben Domenico and Stefano Nativi) Ref. OGC 11-165r2. - Roy, D.P., Ju, J., Kline, K., Scaramuzza, P.L., Kovalskyy, V., Hansen, M., Loveland, T.R., Vermote, E., & Zhang, C. (2010). Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United States. Remote Sensing of Environment, 114, 35-49. - Sixsmith, J., Oliver, S., & Lymburner, L. (2013). A hybrid approach to automated Landsat pixel quality. In, Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International (pp. 4146-4149). - Strahler, A.H., and Muller, J.-P. (1999) MODIS BRDF/Albedo Product: Algorithm Theoretical Basis Document Version 5.0. http://modis.gsfc.nasa.gov/data/atbd/atbd_mod09.pdf - TM World Borders vector file: http://thematicmapping.org/downloads/world_borders.php - USGS (2012a) Landsat Thematic Mapper (TM) Level 1 (L1) Data Format Control Book (DFCB). LS-DFCB-20 Version 4.0. USGS, USA. http://landsat.usgs.gov/documents/LS-DFCB-20.pdf - USGS (2012b) Landsat 7 ETM+ Level 1 Product Data Format Control Book (DFCB). LS-DFCB-04 Version 15.0. http://landsat.usgs.gov/documents/LS-DFCB-04.pdf - Vincenty, T. (1975) Direct and Inverse Solutions of Geodesies on the Ellipsoid with Application of Nested Equations. Survey Review 23, 88-93. - Zhu, Z. and Woodcock, C. E. (2012) Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sensing of Environment 118, 83-94. - http://dx.doi.org/10.4225/25/55EF55788BAC1
institution:
Geoscience Australia - Client Services
cdm_data_type:
Grid
publisher_url:
http://www.ga.gov.au
acknowledgment:
Landsat data is provided by the United States Geological Survey (USGS) through direct reception of the data at Geoscience Australias satellite reception facility or download.
publisher_name:
Section Leader, Operations Section, NEMO, Geoscience Australia
publisher_type:
institution
product_version:
Version 2.0, April 2015
publisher_email:
earth.observation@ga.gov.au
keywords_vocabulary:
GCMD
