Near‐real‐time one‐kilometre Soil Moisture Active Passive soil moisture data product. Issue 21 (4th August 2020)
- Record Type:
- Journal Article
- Title:
- Near‐real‐time one‐kilometre Soil Moisture Active Passive soil moisture data product. Issue 21 (4th August 2020)
- Main Title:
- Near‐real‐time one‐kilometre Soil Moisture Active Passive soil moisture data product
- Authors:
- Yin, Jifu
Zhan, Xiwu
Liu, Jicheng
Moradkhani, Hamid
Fang, Li
Walker, Jeffrey P. - Abstract:
- Abstract: The coarse resolution soil moisture (SM) data from NASA SMAP mission have been steadily produced with the expected performance since April 2015. These coarse resolution observations could be downscaled to fine resolution using fine scale observations of SM sensitive quantities from existing satellite sensors. For operational users who need near‐real‐time (NRT) high resolution SM data, the downscaling approach should be feasible for operational implementation, requiring limited ancillary information and primarily depending on readily available satellite observations. Based on these principles, nine potential candidate downscaling schemes were selected for developing an optimal downscaling strategy. Using remotely sensed land surface temperature (LST) and enhanced vegetation index (EVI) observations, the optimal downscaling approach was tested for operational producing a NRT 1 km SM data product from SMAP. Comprehensive assessments on the 1 km SM product were conducted based on agreement statistics with in‐situ SM measurements. Statistical results show that the accuracy of the original coarse spatial resolution SMAP SM product can be significantly improved by 8% by the downscaled 1 km SM. With respect to the in‐situ measurements, the 1 km SM mapping capability developed here presents a clear advantage over the SMAP/Sentinel SM data product; and it also provides better data availability for users. This study suggests that a NRT 1 km SMAP SM data product could beAbstract: The coarse resolution soil moisture (SM) data from NASA SMAP mission have been steadily produced with the expected performance since April 2015. These coarse resolution observations could be downscaled to fine resolution using fine scale observations of SM sensitive quantities from existing satellite sensors. For operational users who need near‐real‐time (NRT) high resolution SM data, the downscaling approach should be feasible for operational implementation, requiring limited ancillary information and primarily depending on readily available satellite observations. Based on these principles, nine potential candidate downscaling schemes were selected for developing an optimal downscaling strategy. Using remotely sensed land surface temperature (LST) and enhanced vegetation index (EVI) observations, the optimal downscaling approach was tested for operational producing a NRT 1 km SM data product from SMAP. Comprehensive assessments on the 1 km SM product were conducted based on agreement statistics with in‐situ SM measurements. Statistical results show that the accuracy of the original coarse spatial resolution SMAP SM product can be significantly improved by 8% by the downscaled 1 km SM. With respect to the in‐situ measurements, the 1 km SM mapping capability developed here presents a clear advantage over the SMAP/Sentinel SM data product; and it also provides better data availability for users. This study suggests that a NRT 1 km SMAP SM data product could be routinely generated from SMAP at the centre for Satellite Applications and Research of NOAA NESDIS for operational users. Abstract : Process flow of producing a near real time 1 km downscaled SMAP soil moisture data. … (more)
- Is Part Of:
- Hydrological processes. Volume 34:Issue 21(2020)
- Journal:
- Hydrological processes
- Issue:
- Volume 34:Issue 21(2020)
- Issue Display:
- Volume 34, Issue 21 (2020)
- Year:
- 2020
- Volume:
- 34
- Issue:
- 21
- Issue Sort Value:
- 2020-0034-0021-0000
- Page Start:
- 4083
- Page End:
- 4096
- Publication Date:
- 2020-08-04
- Subjects:
- downscale -- near real time -- SMAP -- soil moisture -- spatial resolution
Hydrology -- Periodicals
Hydrology -- Research -- Periodicals
Hydrologic models -- Periodicals
Hydrological forecasting -- Periodicals
631.432 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/hyp.13857 ↗
- Languages:
- English
- ISSNs:
- 0885-6087
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4347.625600
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14259.xml