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- Im, Jungho
- Intelligent Remote sensing and geospatial Information Science Lab.
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| DC Field | Value | Language |
|---|---|---|
| dc.citation.conferencePlace | KO | - |
| dc.citation.title | International Symposium on Remote Sensing | - |
| dc.contributor.author | Park, Seonyoung | - |
| dc.contributor.author | Im, Jungho | - |
| dc.contributor.author | Ke, Yinghai | - |
| dc.date.accessioned | 2023-12-19T21:06:28Z | - |
| dc.date.available | 2023-12-19T21:06:28Z | - |
| dc.date.created | 2017-06-17 | - |
| dc.date.issued | 2016-04-20 | - |
| dc.description.abstract | ABSTRACT Evapotranspiration (ET) is one of the essential factors to understand hydro-meteorological cycle and interaction between the land surface and atmosphere. Estimated ET has been widely used at local to regional scale for sustainable management water resource. Moderate Resolution Imaging Spectroradiometer (MODIS) provides 8-day and monthly global ET products (MOD16) at 1 km. Although MODIS provides ET with high temporal resolution, the application of MOD16 at local or field scale has limitation due to its course resolution. Therefore, ET estimation through data fusion is necessary to provide ET on a high spatiotemporal domain. This study aims at improving both spatial and temporal resolution of ET through fusing MODIS ET and Landsat 8 data. Results show that the rRMSE of the downscaled ET was within 20% and more consistent with in situ ET than MODIS ET. | - |
| dc.identifier.bibliographicCitation | International Symposium on Remote Sensing | - |
| dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/39679 | - |
| dc.language | 영어 | - |
| dc.publisher | International Symposium on Remote Sensing | - |
| dc.title | Mapping 8-day evapotranspiration at 30m spatial resolution by fusion of MODIS and Landsat data and machine learning approach | - |
| dc.type | Conference Paper | - |
| dc.date.conferenceDate | 2016-04-20 | - |
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