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Validation of the Effective Resolution of SMAP Enhanced Resolution Backscatter Products

Authors :
David G. Long
Julie Z. Miller
Source :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 3390-3404 (2023)
Publication Year :
2023
Publisher :
IEEE, 2023.

Abstract

NASA's Soil Moisture Active Passive (SMAP) mission originally included both passive and active L-band measurement capabilities. It was the first satellite instrument to provide global L-band radar observations of normalized radar cross section ($\sigma ^{0}$) at multiple resolutions. The SMAP radar collected high-resolution ($\sim$1–3 km) synthetic aperture radar (SAR) measurements over most of the earth's land mass. It simultaneously collected low-resolution 6 × 30 km “slice” and full-footprint 29 × 35 km measurements. The SMAP radar operated for 83 days, from day of the year 103 to 186 in 2015, before the transmitter failed. The SMAP radar was designed to make vegetation roughness measurements in support of the SMAP primary mission to measure soil moisture, but the radar data are useful for a variety of applications, particularly in the polar regions. Unfortunately, limitations in the data download volume precluded the downlink of high-resolution data over Antarctica, sea ice in the polar regions, and various islands. Nonetheless, low-resolution slice and footprint data were collected and downlinked over these areas. To better exploit these low-resolution data, this article employs image reconstruction techniques to create twice-daily enhanced resolution SMAP radar images from the slice and footprint measurements. To validate the resolution enhancement, the enhanced resolution data are compared to SAR results over Greenland and South America. The new dataset is provided to the science community to support cryosphere and climate studies.

Details

Language :
English
ISSN :
21511535
Volume :
16
Database :
Directory of Open Access Journals
Journal :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.ff3206a2116c45e199bfe6d6dbd3409f
Document Type :
article
Full Text :
https://doi.org/10.1109/JSTARS.2023.3260726