{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:30:01Z","timestamp":1772253001221,"version":"3.50.1"},"reference-count":20,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2019,3,25]],"date-time":"2019-03-25T00:00:00Z","timestamp":1553472000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study was undertaken to derive and analyze the advanced microwave scanning radiometer-Earth observing satellite (EOS) (AMSR-E) sea surface temperature (SST) footprint associated with the remote sensing systems (RSS) level-2 (L2) product. The footprint, in this case, is characterized by the weight attributed to each     4 \u00d7 4     km square contributing to the SST value of a given (AMSR-E) pixel. High-resolution L2 SST fields obtained from the moderate-resolution imaging spectroradiometer (MODIS), carried on the same spacecraft as AMSR-E, are used as the sub-resolution \u201cground truth\u201d from which the AMSR-E footprint is determined. Mathematically, the approach is equivalent to a linear inversion problem, and its solution is pursued by means of a constrained least square approximation based on the bootstrap sampling procedure. The method yielded an elliptic-like Gaussian kernel with an aspect ratio \u22481.58, very close to the AMSR-E     6.93  GHz     channel aspect ratio, \u22481.74. (The     6.93  GHz     channel is the primary spectral frequency used to determine SST.) The semi-major axis of the estimated footprint is found to be aligned with the instantaneous field-of-view of the sensor as expected from the geometric characteristics of AMSR-E. Footprints were also analyzed year-by-year and as a function of latitude and found to be stable\u2014no dependence on latitude or on time. Precise knowledge of the footprint is central for any satellite-derived product characterization and, in particular, for efforts to deconvolve the heavily oversampled AMSR-E SST fields and for studies devoted to product validation and comparison. A preliminary analysis suggests that use of the derived footprint will reduce the variance between AMSR-E and MODIS fields compared to the results obtained ignoring the shape and size of the footprint as has been the practice in such comparisons to date.<\/jats:p>","DOI":"10.3390\/rs11060715","type":"journal-article","created":{"date-parts":[[2019,3,27]],"date-time":"2019-03-27T05:03:12Z","timestamp":1553662992000},"page":"715","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Determining the AMSR-E SST Footprint from Co-Located MODIS SSTs"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8614-7633","authenticated-orcid":false,"given":"Brahim","family":"Boussidi","sequence":"first","affiliation":[{"name":"Graduate School of Oceanography, University of Rhode Island, 215 South Ferry Road, Narragansett, RI 02882, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7296-3282","authenticated-orcid":false,"given":"Peter","family":"Cornillon","sequence":"additional","affiliation":[{"name":"Graduate School of Oceanography, University of Rhode Island, 215 South Ferry Road, Narragansett, RI 02882, USA"}]},{"given":"Gavino","family":"Puggioni","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Statistics, University of Rhode Island, 9 Greenhouse Road, Suite 2, Kingston, RI 02881, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2250-3106","authenticated-orcid":false,"given":"Chelle","family":"Gentemann","sequence":"additional","affiliation":[{"name":"Earth and Space Research, Seattle, WA 98121, USA"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,25]]},"reference":[{"key":"ref_1","unstructured":"GCOS (2006). 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