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FUSION OF ACTIVE AND PASSIVE MICROWAVE OBSERVATIONS TO CREATE AN ESSENTIAL CLIMATE VARIABLE DATA RECORD ON SOIL MOISTURE
- Source :
- ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol I-7, Pp 315-321 (2012)
- Publication Year :
- 2012
- Publisher :
- Copernicus Publications, 2012.
-
Abstract
- Soil moisture was recently included in the list of Essential Climate Variables (ECVs) that are deemed essential for IPCC (Intergovernmental Panel on Climate Change) and UNFCCC (United Nations Framework Convention on Climate Change) needs and considered feasible for global observation. ECVs data records should be as long, complete and consistent as possible, and in the case of soil moisture this means that the data record shall be based on multiple data sources, including but not limited to active (scatterometer) and passive (radiometer) microwave observations acquired preferably in the low-frequency microwave range. Among the list of sensors that can be used for this task are the C-band scatterometers on board of the ERS and METOP satellites and the multi-frequency radiometers SMMR, SSM/I, TMI, AMSR-E, and Windsat. Together, these sensors already cover a time period of more than 30 years and the question is how can observations acquired by these sensors be merged to create one consistent data record? This paper discusses on a high-level possible approaches for fusing the individual satellite data. It is argued that the best possible approach for the fusion of the different satellite data sets is to merge Level 2 soil moisture data derived from the individual satellite data records. This approach has already been demonstrated within the WACMOS project (http://wacmos.itc.nl/) funded by European Space Agency (ESA) and will be further improved within the Climate Change Initiative (CCI) programme of ESA (http://www.esa-cci.org/).
Details
- Language :
- English
- ISSN :
- 21949042 and 21949050
- Volume :
- I-7
- Database :
- Directory of Open Access Journals
- Journal :
- ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.9a038cbfc65f4c09b82ff7f90f2a51dc
- Document Type :
- article
- Full Text :
- https://doi.org/10.5194/isprsannals-I-7-315-2012