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ROBUST ASSESSMENT OF AN OPERATIONAL ALGORITHM FOR THE RETRIEVAL OF SOIL MOISTURE FROM AMSR-E DATA IN CENTRAL ITALY
- Source :
- IEEE Geoscience and Remote Sensing Symposium-IGARSS 2015, pp. 1288–1291, Milano, 26/07/2015-31/07/2015, info:cnr-pdr/source/autori:Santi, E.; Paloscia, S.; Pettinato, S.; Brocca, L.; Ciabatta, L./congresso_nome:IEEE Geoscience and Remote Sensing Symposium-IGARSS 2015/congresso_luogo:Milano/congresso_data:26%2F07%2F2015-31%2F07%2F2015/anno:2015/pagina_da:1288/pagina_a:1291/intervallo_pagine:1288–1291, IGARSS 2015, pp. 1288–1291, 2015, info:cnr-pdr/source/autori:Santi, E.; Paloscia, S.; Pettinato, S.; Brocca, L.; Ciabatta, L./congresso_nome:IGARSS 2015/congresso_luogo:/congresso_data:2015/anno:2015/pagina_da:1288/pagina_a:1291/intervallo_pagine:1288–1291, IGARSS, IEEE journal of selected topics in applied earth observations and remote sensing, 9 (2016): 2478–2492. doi:10.1109/JSTARS.2016.2575361, info:cnr-pdr/source/autori:Santi, Emanuele; Paloscia, Simonetta; Pettinato, Simone; Brocca, Luca; Ciabatta, Luca/titolo:Robust Assessment of an Operational Algorithm for the Retrieval of Soil Moisture from AMSR-E Data in Central Italy/doi:10.1109%2FJSTARS.2016.2575361/rivista:IEEE journal of selected topics in applied earth observations and remote sensing (Print)/anno:2016/pagina_da:2478/pagina_a:2492/intervallo_pagine:2478–2492/volume:9
- Publication Year :
- 2015
- Publisher :
- IEEE Service Center [distributor], Piscataway, NJ , Stati Uniti d'America, 2015.
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Abstract
- In this study, the soil moisture content (SMC) derived from the AMSR-E acquisitions by using the “HydroAlgo” algorithm, which is based on artificial neural networks (ANN), is compared with simulated data obtained from the application of a soil water balance model (SWBM) in central Italy. All the overpasses available for the 9-year lifetime of AMSR-E have been considered for this comparison, which was carried out point by point over a grid of 91 nodes spaced at 0.1° × 0.1°, roughly corresponding to the Umbria region. HydroAlgo includes a disaggregation technique (smoothing filter-based intensity modulation), which allowed obtaining an SMC product with enhanced spatial resolution (0.1°) that is expected to be more suitable for hydrological applications. The main purpose of this study is to exploit the potential of AMSR-E sensors for hydrological studies, and in particular for SMC monitoring on a regional scale in heterogeneous landscapes typical of Mediterranean environment. Slightly different results were obtained using ascending or descending overpasses; however, the overall correlation coefficient between the SMC retrieved by HydroAlgo and the SMC simulated by SWBM was higher than 0.8 and the corresponding root mean square error was less than 0.055 m3/m3. Based on these successful results, HydroAlgo is going to be implemented for current multifrequency microwave radiometers (AMSR2) in order to obtain a high-resolution SMC product suitable to be assimilated into flood- and landslide-related modeling in central Italy.
- Subjects :
- Atmospheric Science
010504 meteorology & atmospheric sciences
Mean squared error
Correlation coefficient
Meteorology
genetic structures
0211 other engineering and technologies
02 engineering and technology
01 natural sciences
Data modeling
Point (geometry)
Computers in Earth Sciences
Image resolution
Water content
Artificial Neural Networks
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Remote sensing
Soil water balance
Radiometer
Artificial neural network
Soil Moisture Content
AMSR-E
Grid
soil water balance model
Environmental science
Scale (map)
Algorithm
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- IEEE Geoscience and Remote Sensing Symposium-IGARSS 2015, pp. 1288–1291, Milano, 26/07/2015-31/07/2015, info:cnr-pdr/source/autori:Santi, E.; Paloscia, S.; Pettinato, S.; Brocca, L.; Ciabatta, L./congresso_nome:IEEE Geoscience and Remote Sensing Symposium-IGARSS 2015/congresso_luogo:Milano/congresso_data:26%2F07%2F2015-31%2F07%2F2015/anno:2015/pagina_da:1288/pagina_a:1291/intervallo_pagine:1288–1291, IGARSS 2015, pp. 1288–1291, 2015, info:cnr-pdr/source/autori:Santi, E.; Paloscia, S.; Pettinato, S.; Brocca, L.; Ciabatta, L./congresso_nome:IGARSS 2015/congresso_luogo:/congresso_data:2015/anno:2015/pagina_da:1288/pagina_a:1291/intervallo_pagine:1288–1291, IGARSS, IEEE journal of selected topics in applied earth observations and remote sensing, 9 (2016): 2478–2492. doi:10.1109/JSTARS.2016.2575361, info:cnr-pdr/source/autori:Santi, Emanuele; Paloscia, Simonetta; Pettinato, Simone; Brocca, Luca; Ciabatta, Luca/titolo:Robust Assessment of an Operational Algorithm for the Retrieval of Soil Moisture from AMSR-E Data in Central Italy/doi:10.1109%2FJSTARS.2016.2575361/rivista:IEEE journal of selected topics in applied earth observations and remote sensing (Print)/anno:2016/pagina_da:2478/pagina_a:2492/intervallo_pagine:2478–2492/volume:9
- Accession number :
- edsair.doi.dedup.....b74e2fff785ec941713ee505b4cadb61