Remote Sensing of Lake Water Clarity: Performance and Transferability of Both Historical Algorithms...
Remote Sensing of Lake Water Clarity: Performance and Transferability of Both Historical Algorithms and Machine Learning
About this item
Full title
Author / Creator
Publisher
Basel: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Basel: MDPI AG
Subjects
More information
Scope and Contents
Contents
There has been little rigorous investigation of the transferability of existing empirical water clarity models developed at one location or time to other lakes and dates of imagery with differing conditions. Machine learning methods have not been widely adopted for analysis of lake optical properties such as water clarity, despite their successful...
Alternative Titles
Full title
Remote Sensing of Lake Water Clarity: Performance and Transferability of Both Historical Algorithms and Machine Learning
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_767b08f68a7640f08fcc64fd777a9f86
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_767b08f68a7640f08fcc64fd777a9f86
Other Identifiers
ISSN
2072-4292
E-ISSN
2072-4292
DOI
10.3390/rs13081434
