Application of a Combined Optical-Passive Microwave Method to Retrieve Soil Moisture at Regional Scale Over Chile

被引:14
作者
Santamaria-Artigas, Andres [1 ,2 ]
Mattar, Cristian [1 ]
Wigneron, Jean-Pierre [3 ]
机构
[1] Univ Chile, Dept Environm Sci & Renewable Nat Resources, Lab Anal Biosphere, Santiago 1058, Chile
[2] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
[3] Inst Natl Rech Agronom, F-33140 Bordeaux, France
关键词
ERA-Interim; Moderate Resolution Imaging Spectroradiometer (MODIS); Normalized Difference Vegetation Index (NDVI); Soil Moisture and Ocean Salinity (SMOS); Soil Moisture (SM); L-BAND EMISSION; SMOS; VEGETATION; PRODUCTS; PERFORMANCE; MODIS; RADIOMETER; FORESTS; MODEL; INDEX;
D O I
10.1109/JSTARS.2015.2512926
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This work presents the calibration and evaluation of an optical-passive microwave method for retrieving soil moisture (SM) at regional scale using remote sensing and reanalysis data. Several data sets were used, such as the bipolarized brightness temperature provided by SM and Ocean Salinity (SMOS) L3 brightness temperature product, the Normalized Difference Vegetation Index (NDVI) from moderate resolution imaging spectroradiometer (MODIS), the soil temperature and water content of the first 0-7 cm of depth from the ERA-Interim reanalysis, and 13 land cover classes obtained from the ECOCLIMAP database. The method was applied over Chile between 28 degrees S and 43 degrees S for 2010-2012. The data set was used to calibrate and evaluate a semiempirical approach for estimating SM, first by using only the data from SMOS and ERA-Interim and then also including the MODIS vegetation indicator. Results were analyzed for every land cover class using the determination coefficient (r(2)), the coefficients obtained from the regressions, and the unbiased root-mean-square difference (ubRMSD). Results showed an increase in the average r(2) for all classes when a vegetation index was used in the calibration of the approach. The increases in r(2) ranged from 3% for the crop class, to 49% for the closed shrubland class. The ubRMSD presented a decrease in its value of up to 1% m(3)/m(3) for the woodlands, open shrublands, and woody shrublands classes and up to 2% m(3)/m(3) for the closed shrubland class. These results contribute to the use of single linear and semiempirical regressions to estimate SM at regional scale based on SMOS L-band bipolarized brightness temperature.
引用
收藏
页码:1493 / 1504
页数:12
相关论文
共 42 条
[21]   Multilayer Soil Moisture Mapping at a Regional Scale from Multisource Data via a Machine Learning Method [J].
Zeng, Linglin ;
Hu, Shun ;
Xiang, Daxiang ;
Zhang, Xiang ;
Li, Deren ;
Li, Lin ;
Zhang, Tingqiang .
REMOTE SENSING, 2019, 11 (03)
[22]   A Performance Analysis of Soil Dielectric Models over Organic Soils in Alaska for Passive Microwave Remote Sensing of Soil Moisture [J].
Zhang, Runze ;
Chan, Steven ;
Bindlish, Rajat ;
Lakshmi, Venkataraman .
REMOTE SENSING, 2023, 15 (06)
[23]   Spatio-temporal evaluation of resolution enhancement for passive microwave soil moisture and vegetation optical depth [J].
Gevaert, A. I. ;
Parinussa, R. M. ;
Renzullo, L. J. ;
van Dijk, A. I. J. M. ;
de Jeu, R. A. M. .
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2016, 45 :235-244
[24]   Application of artificial neural networks for the soil moisture retrieval from active and passive microwave spaceborne sensors [J].
Santi, Emanuele ;
Paloscia, Simonetta ;
Pettinato, Simone ;
Fontanelli, Giacomo .
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2016, 48 :61-73
[25]   Microwave retrievals of soil moisture and vegetation optical depth with improved resolution using a combined constrained inversion algorithm: Application for SMAP satellite [J].
Gao, Lun ;
Sadeghi, Morteza ;
Ebtehaj, Ardeshir .
REMOTE SENSING OF ENVIRONMENT, 2020, 239
[26]   Estimating leaf moisture content at global scale from passive microwave satellite observations of vegetation optical depth [J].
Forkel, Matthias ;
Schmidt, Luisa ;
Zotta, Ruxandra-Maria ;
Dorigo, Wouter ;
Yebra, Marta .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 2023, 27 (01) :39-68
[27]   SMOS soil moisture product evaluation over West-Africa from local to regional scale [J].
Louvet, Samuel ;
Pellarin, Thierry ;
al Bitar, Ahmad ;
Cappelaere, Bernard ;
Galle, Sylvie ;
Grippa, Manuela ;
Gruhier, Claire ;
Kerr, Yann ;
Lebel, Thierry ;
Mialon, Arnaud ;
Mougin, Eric ;
Quantin, Guillaume ;
Richaume, Philippe ;
de Rosnay, Patricia .
REMOTE SENSING OF ENVIRONMENT, 2015, 156 :383-394
[28]   An improved method for estimating soil moisture over cropland using SAR and optical data [J].
Luo, Dayou ;
Wen, Xingping ;
Li, Shuling .
EARTH SCIENCE INFORMATICS, 2023, 16 (2) :1909-1916
[29]   Evaluation of soil moisture derived from passive microwave remote sensing over agricultural sites in Canada using ground-based soil moisture monitoring networks [J].
Champagne, Catherine ;
Berg, Aaron ;
Belanger, Jon ;
McNairn, Heather ;
De Jeu, Richard .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2010, 31 (14) :3669-3690
[30]   VALIDATION OF FIVE PASSIVE MICROWAVE REMOTELY SENSED SOIL MOISTURE PRODUCTS OVER THE QINGHAI-TIBET PLATEAU, CHINA [J].
Liu, Jin ;
Chai, Linna ;
Lu, Zheng ;
Qu, Yuquan ;
Wang, Jian ;
Yang, Shiqi .
2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, :6182-6185