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- Publisher Website: 10.1007/978-1-4020-6450-0_12
- Scopus: eid_2-s2.0-84900063330
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Conference Paper: Data assimilation methods for land surface variable estimation
| Title | Data assimilation methods for land surface variable estimation |
|---|---|
| Authors | |
| Issue Date | 2008 |
| Publisher | Springer |
| Citation | 9th International Symposium on Physical Measurements and Signatures in Remote Sensing, 1 October 2005. In Liang, S (Ed.), Advances in Land Remote Sensing: System, Modeling, Inversion and Application, p. 313-339. Dordrecht: Springer, 2008 How to Cite? |
| Abstract | Estimating land surface variables from remote sensing data is an ill-posed problem. Integration of observations from multiple satellite sensors with different spectral, spatial, temporal and angular signatures is now an important research frontier. Data assimilation (DA), integrating not only remotely sensed data products, but also other measurements and land dynamic models, is an advanced set of techniques for innovative parameter estimation. After a brief introduction, we describe the basic principles of DA, and then provide in-depth discussions of some relevant issues while using DA. The latest applications of DA for estimation of soil moisture, energy balance, carbon cycle and agricultural productivity are summarized. © Springer Science + Business Media B.V., 2008. |
| Persistent Identifier | http://hdl.handle.net/10722/321582 |
| ISBN |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Liang, Shunlin | - |
| dc.contributor.author | Qin, Jun | - |
| dc.date.accessioned | 2022-11-03T02:20:01Z | - |
| dc.date.available | 2022-11-03T02:20:01Z | - |
| dc.date.issued | 2008 | - |
| dc.identifier.citation | 9th International Symposium on Physical Measurements and Signatures in Remote Sensing, 1 October 2005. In Liang, S (Ed.), Advances in Land Remote Sensing: System, Modeling, Inversion and Application, p. 313-339. Dordrecht: Springer, 2008 | - |
| dc.identifier.isbn | 9781402064494 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/321582 | - |
| dc.description.abstract | Estimating land surface variables from remote sensing data is an ill-posed problem. Integration of observations from multiple satellite sensors with different spectral, spatial, temporal and angular signatures is now an important research frontier. Data assimilation (DA), integrating not only remotely sensed data products, but also other measurements and land dynamic models, is an advanced set of techniques for innovative parameter estimation. After a brief introduction, we describe the basic principles of DA, and then provide in-depth discussions of some relevant issues while using DA. The latest applications of DA for estimation of soil moisture, energy balance, carbon cycle and agricultural productivity are summarized. © Springer Science + Business Media B.V., 2008. | - |
| dc.language | eng | - |
| dc.publisher | Springer | - |
| dc.relation.ispartof | Advances in Land Remote Sensing: System, Modeling, Inversion and Application | - |
| dc.title | Data assimilation methods for land surface variable estimation | - |
| dc.type | Conference_Paper | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1007/978-1-4020-6450-0_12 | - |
| dc.identifier.scopus | eid_2-s2.0-84900063330 | - |
| dc.identifier.spage | 313 | - |
| dc.identifier.epage | 339 | - |
| dc.publisher.place | Dordrecht | - |