Forecasting dryland vegetation condition months in advance through satellite data assimilation
Forecasting drought and its impact on agriculture and ecosystems is challenged by a lack of knowledge of vegetation access to deep moisture. Here the authors show that combining vegetation and water storage remote sensing can be used to infer this knowledge, allowing drought impact forecasts months...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2019-01-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-019-08403-x |
| _version_ | 1818342651070513152 |
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| author | Siyuan Tian Albert I. J. M. Van Dijk Paul Tregoning Luigi J. Renzullo |
| author_facet | Siyuan Tian Albert I. J. M. Van Dijk Paul Tregoning Luigi J. Renzullo |
| author_sort | Siyuan Tian |
| collection | DOAJ |
| description | Forecasting drought and its impact on agriculture and ecosystems is challenged by a lack of knowledge of vegetation access to deep moisture. Here the authors show that combining vegetation and water storage remote sensing can be used to infer this knowledge, allowing drought impact forecasts months in advance. |
| first_indexed | 2024-12-13T16:18:04Z |
| format | Article |
| id | doaj.art-afb25d8b12f44b40b62f2fe858714565 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-12-13T16:18:04Z |
| publishDate | 2019-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-afb25d8b12f44b40b62f2fe8587145652022-12-21T23:38:47ZengNature PortfolioNature Communications2041-17232019-01-011011710.1038/s41467-019-08403-xForecasting dryland vegetation condition months in advance through satellite data assimilationSiyuan Tian0Albert I. J. M. Van Dijk1Paul Tregoning2Luigi J. Renzullo3Research School of Earth Sciences, Australian National UniversityFenner School of Environment & Society, Australian National UniversityResearch School of Earth Sciences, Australian National UniversityFenner School of Environment & Society, Australian National UniversityForecasting drought and its impact on agriculture and ecosystems is challenged by a lack of knowledge of vegetation access to deep moisture. Here the authors show that combining vegetation and water storage remote sensing can be used to infer this knowledge, allowing drought impact forecasts months in advance.https://doi.org/10.1038/s41467-019-08403-x |
| spellingShingle | Siyuan Tian Albert I. J. M. Van Dijk Paul Tregoning Luigi J. Renzullo Forecasting dryland vegetation condition months in advance through satellite data assimilation Nature Communications |
| title | Forecasting dryland vegetation condition months in advance through satellite data assimilation |
| title_full | Forecasting dryland vegetation condition months in advance through satellite data assimilation |
| title_fullStr | Forecasting dryland vegetation condition months in advance through satellite data assimilation |
| title_full_unstemmed | Forecasting dryland vegetation condition months in advance through satellite data assimilation |
| title_short | Forecasting dryland vegetation condition months in advance through satellite data assimilation |
| title_sort | forecasting dryland vegetation condition months in advance through satellite data assimilation |
| url | https://doi.org/10.1038/s41467-019-08403-x |
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