Techniques and Methods 11–C7
The U.S. Geological Survey (USGS) Land Remote Sensing Program is developing an operational capability to produce Climate Data Records (CDRs) and Essential Climate Variables (ECVs) from the Landsat Archive to support a wide variety of science and resource management activities from regional to global scale. The USGS Earth Resources Observation and Science (EROS) Center is charged with prototyping systems and software to generate these high-level data products. Various USGS Geographic Science Centers are charged with particular ECV algorithm development and (or) selection as well as the evaluation and application demonstration of various USGS CDRs and ECVs. Because it is a foundation for many other ECVs, the first CDR in development is the Landsat Surface Reflectance Product (LSRP). The LSRP incorporates data quality information in a bit-packed structure that is not readily accessible without postprocessing services performed by the user. This document describes two general methods of LSRP quality-data extraction for use in image processing systems. Helpful hints for the installation and use of software originally developed for manipulation of Hierarchical Data Format (HDF) produced through the National Aeronautics and Space Administration (NASA) Earth Observing System are first provided for users who wish to extract quality data into separate HDF files. Next, steps follow to incorporate these extracted data into an image processing system. Finally, an alternative example is illustrated in which the data are extracted within a particular image processing system.
First posted January 18, 2013
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Jones, J.W., Starbuck, M.J., and Jenkerson, C.B., 2013, Landsat surface reflectance quality assurance extraction (version 1.7): U.S. Geological Survey Techniques and Methods, book 11, chap. C7, 9 p., available only at https://pubs.usgs.gov/tm/11/c07.
Data Access and Acquisition
Software Access and Acquisition
Software Installation and Setup
Running the Command Named “unpack_sds_bits”
Adding QA Data to ENVI
Adding QA Data to ERDAS Imagine