We propose to determine the information content of multi-temporal land imaging in discrete Landsat-like spectral bands at 30 m with a 360 km swath width and compare this to the information content of hyper-spectral land imaging at 60 m with a swath width of 145 km. We will analyze 30 m visible and near infrared cloud-free data collected every two weeks for the entire continuous lower 48-sates in 2011 and 2012.
The extremely successful Landsat series of satellites have collected invaluable imagery of the Earth’s surface since Landsat-1 was launched in 1972. Since 1982 with Landsat-4’s thematic mapper instrument, 30 m multispectral imagery have been collected in discrete visible, near-infrared, and short wave infrared bands complemented by thermal imagery at coarser resolutions. Landsat-8, launched in 2013, and Landsat-7, launched in 1999 and since 2003 suffering from a lack of scan line corrections, are the sources of current US land imaging data. JPL and their associates have proposed the replacing the Landsat 30 m discrete multispectral visible, near-infrared, and short wave infrared imaging with hyper-spectral imagers, patterned after HyspIRI, a JPL instrument.
The argument hyper-spectral imager enthusiasts make for replacing a discrete band Landsat-type instrument is there is more information in hyper-spectral data, because you have so many more spectral bands. JPL’s hyper-spectral HyspIRI instrument, scheduled for launch in 2016, has a 60 m spatial resolution, 212 spectral bands, and a 145 km swath width. This argument never considers information theory and the fact that there is a very high correlation between adjacent spectral intervals in the visible, near infrared, and short-wave infrared regions. This has been investigated with hyper-spectral data by Tucker and Maxwell (1976) and Tucker (1978) who found extremely high correlations between adjacent 5 nm spectral intervals in the visible and near-infrared spectral regions. These results have been further extended by Tucker and Sellers (1986).
The “hyper-spectral conundrum” results from the trade off between the number of spectral bands, spatial resolution, radiometric accuracy, and swath width or revisit frequency. It is difficult ir not impossible for a hyper-spectral instrument with hundreds of bands to have a 30 m spatial resolution and a short revisit frequency.
Tucker, C.J. and E.L. Maxwell, 1976. Sensor Design for Monitoring Vegetation Canopies. Photogrammetric Engineering and Remote Sensing 42(11):1399-1410.
Tucker, C. J. 1978. A Comparison of Satellite Sensor Bands for Vegetation Monitoring. Photogrammetric Engineering and Remote Sensing 44(11):1169-1180.
Tucker. C.J. and P.J. Sellers, 1986. Satellite remote sensing of primary production. International Journal of Remote Sensing 7:1395-1416.More »
Our results will benefit the Landsat/Future Land Imaging Program as it decides to continue witn imagers or change to a hyper-spectral instrument.
This work benefits land imaging.
This project benefits the USGS, USDA, and all other federal agencies that use Landsat data to monitor land areas that are their responsibility.More »
|Organizations Performing Work||Role||Type||Location|
|Goddard Space Flight Center (GSFC)||Lead Organization||NASA Center||Greenbelt, Maryland|
|USDA Agricultural Research Service (USDA-ARS)||US Government||West Lafayette, Indiana|