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| Type: | Resource | |
| Storage: | The size of this resource is 9.1 MB | |
| Created: | Feb 07, 2020 at 3:12 p.m. | |
| Last updated: | Feb 07, 2020 at 6:22 p.m. | |
| DOI: | 10.4211/hs.f0091cf90bcc4487bf401ca19783d1eb | |
| Citation: | See how to cite this resource | |
| Content types: | Geographic Raster Content |
| Sharing Status: | Published |
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| Views: | 1666 |
| Downloads: | 258 |
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Abstract
Monthly soil moisture predictions over a region of interest centered on Oklahoma and surrounded areas from January 2000 to September 2012. Data were acquired from the European Space Agency Climate Change Initiative soil moisture product version 4.5, 0.25-degrees spatial resolution. The modeled product aims to fill soil moisture spatial gaps from the original product over the region of Interest. Soil moisture values were calculated based on three methods, e.g. Ordinary Kriging, Regression Kriging and Generalized Linear Model. Reference monthly soil moisture layers were generated based on daily soil moisture estimates over each 0.25-degrees pixel in the region of interest. Three different sampling approaches were considered to model soil moisture estimates, using 100% of available data from the original satellite data, 75% and 50% of available soil moisture estimates respectively. Data were randomly removed to simulate different scenarios of gap presence in the original ESA CCI product. Soil Moisture values were validated by means of 10-fold cross validation and ground-truth validation with records from the North American Soil Moisture Data Base. Detailed methods and code cab be found in: Llamas, R.M; Guevara, Mario; Rorabaugh, Danny; Taufer, Michela; Vargas, Rodrigo. "Spatial Gap-Filling of ESA CCI Satellite-Derived Soil Moisture based on Geostatistical Techniques and Multiple Regression", Remote Sensing (accepted)
Subject Keywords
Coverage
Spatial
Content
Data Services
Related Resources
| This resource is referenced by | Llamas, R.M; Guevara, Mario; Rorabaugh, Danny; Taufer, Michela; Vargas, Rodrigo. "Spatial Gap-Filling of ESA CCI Satellite-Derived Soil Moisture based on Geostatistical Techniques and Multiple Regression", Remote Sensing (accepted) |
| The content of this resource is derived from | https://www.esa-soilmoisture-cci.org/node/237 |
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| National Science Foundation | OAC grant | 1724843 |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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