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Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

Abstract：

:A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

journal_name

Environ Monit Assess

journal_title

Environmental monitoring and assessment

authors

Wang J,Deng Z

doi

10.1007/s10661-017-6010-7

subject

Has Abstract

pub_date

2017-06-01 00:00:00

pages

286

issue

6

eissn

0167-6369

issn

1573-2959

pii

10.1007/s10661-017-6010-7

journal_volume

189

pub_type

杂志文章

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