| Autor: |
R. Hernández‐Clemente, A. Hornero, V. Gonzalez‐Dugo, M. Berdugo, J. L. Quero, J. C. Jiménez, F. T. Maestre |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Remote Sensing in Ecology and Conservation, Vol 9, Iss 6, Pp 743-758 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2056-3485 |
| DOI: |
10.1002/rse2.340 |
| Popis: |
Abstract Models derived from satellite image data are needed to monitor the status of terrestrial ecosystems across large spatial scales. However, a remote sensing‐based approach to quantify soil multifunctionality at the global scale is missing despite significant research efforts on this topic. A major constraint for doing so is the availability of suitable global‐scale field data to calibrate remote sensing indicators (RSI) and, to a lesser extent, the sensitivity of spectral data of available satellite sensors to soil background and atmospheric conditions. Here, we aimed to develop a soil multifunctionality model to monitor global drylands coupling ground data on 14 soil functions of 222 dryland areas from six continents to 18 RSI derived from a time series (2006–2013) Landsat dataset. Among the RSI evaluated, the chlorophyll absorption ratio index was the best predictor of soil multifunctionality in single‐variable‐based models (r = 0.66, P |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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