Evaluation of ten machine learning methods for estimating terrestrial evapotranspiration from remote sensing
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: 2019DOI: 10.1016/j.jag.2019.01.020
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Evaluation of ten machine learning methods for estimating terrestrial evapotranspiration from remote sensing
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| contributor author | Carter, Corinne, and Shunlin Liang. | |
| date accessioned | 2020-03-16T15:55:08Z | |
| date available | 2020-03-16T15:55:08Z | |
| date issued | 2019 | |
| identifier issn | 0303-2434 | |
| identifier other | OaUSiQoJZPAf9qzHEo8t8CGTaovk0YqovGfjvgqFS5pxVvmDJ9.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/2327598?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | Elsevier BV | |
| title | Evaluation of ten machine learning methods for estimating terrestrial evapotranspiration from remote sensing | |
| type | Journal Paper | |
| contenttype | Fulltext | |
| contenttype | Fulltext | |
| identifier padid | 15363275 | |
| identifier doi | 10.1016/j.jag.2019.01.020 | |
| coverage | Academic | |
| pages | 86-92 | |
| filesize | 425047 | |
| citations | 1 |