Using 10-year (2001 10) monthly evaporation, precipitation, and sea surface salinity (SSS) datasets, the relationship between local freshwater flux and SSS in the north Indian Ocean (NIO) is evaluated quantitatively. ...Using 10-year (2001 10) monthly evaporation, precipitation, and sea surface salinity (SSS) datasets, the relationship between local freshwater flux and SSS in the north Indian Ocean (NIO) is evaluated quantitatively. The results suggest a highly positive linear correlation between freshwater flux and SSS in the Arabian Sea (correlation coefficient, R=0.74) and the western equatorial Indian Ocean (R=0.73), whereas the linear relationships are relatively weaker in the Bay of Bengal (R=0.50) and the eastern equatorial Indian Ocean (R=0.40). Additionally, the interannual variations of freshwater flux and SSS and their mutual relationship are investigated in four sub- regions for pre-monsoon, monsoon, and post-monsoon seasons separately. The satellite retrievals of SSS from the Soil Moisture and Ocean Salinity (SMOS) and Aquarius missions can provide continuous and consistent SSS fields for a better understanding of its variability and the differences between the freshwater flux and SSS signals, which are commonly thought to be linearly related.展开更多
We plan to estimate global net primary production (NPP) of vegetation using the Advanced Earth Observing Satellite\|Ⅱ (ADEOS\|Ⅱ) Global Imager (GLI) multi\|spectral data. We derive an NPP estimation algorithm from g...We plan to estimate global net primary production (NPP) of vegetation using the Advanced Earth Observing Satellite\|Ⅱ (ADEOS\|Ⅱ) Global Imager (GLI) multi\|spectral data. We derive an NPP estimation algorithm from ground measurement data on temperate plants in Japan. By the algorithm, we estimate NPP using a vegetation index based on pattern decomposition (VIPD) for the Mongolian Plateau. The VIPD is derived from Landsat ETM+ multi\|spectral data, and the resulting NPP estimation is compared with ground data measured in a semi\|arid area of Mongolia. The NPP estimation derived from satellite remote sensing data agrees with the ground measurement data within the error range of 15% when all above\|ground vegetation NPP is calculated for different vegetation classifications.展开更多
Forest-height inversion using airborne double-antenna synthetic aperture radar(SAR)systems has been widely researched,leading to increasing accuracy.Polarimetric SAR Interferometry(PolInSAR)data from spaceborne single...Forest-height inversion using airborne double-antenna synthetic aperture radar(SAR)systems has been widely researched,leading to increasing accuracy.Polarimetric SAR Interferometry(PolInSAR)data from spaceborne single-antenna SAR systems,which are influenced by temporal decorrelation,have difficulty inverting forest height.Given the temporal decorrelation effect,the classical random volume over ground(RVoG)model has been proven to invert forest height with significant errors,using repeat-pass PolInSAR data.In consideration of this problem,the temporal decorrelation RVoG(TD-RVoG;based on the RVoG)model was proposed.In this study,an improved TD-RVoG model is presented,with a new temporal decorrelation function.Compared with TD-RVoG,the new model has fewer unknown parameters and can be applied in a three-stage inversion procedure.Validity of the new model is demonstrated by Advanced Land Observing Satellite/Phased Array type L-band SAR(ALOS/PALSAR)data.Results show that the improved TD-RVoG has better accuracy,with inversion error less than 1.5m.展开更多
It is a well known fact that ionospheric delay error is a predominant factor which influences the positioning accuarcy of GNSS.Although the main part of the first-order ionospheric delay error can be removed by the fr...It is a well known fact that ionospheric delay error is a predominant factor which influences the positioning accuarcy of GNSS.Although the main part of the first-order ionospheric delay error can be removed by the frequency-dependent behaviors of the ionosphere,the second-order ionospheric delay error must be eliminated to achieve millimetre-scale positioning accuracy.Due to COSMIC occultation providing electron density profiles on the global scale,the paper presents the first-order and the second-order ionospheric delay error analysis on the global scale using the inversion of electron density profiles from COSMIC occultation data during 2009–2011.Firstly,because of the special geographical location of three ISR(incoherent scatter radar),the first-order and the second-order ionospheric delay errors are calculated and discussed;the paper also shows and analyzes the diurnal,seasonal,semi-annual variation of ionospheric delay error with respect to signal direction.Results show that for the L1 signal path,the first-order ionospheric delay error is the largest near the equator,which is circa 7 m;the maximum second-order ionospheric delay error are circa 0.6 cm,0.8 cm and 0.6 cm respectively for L1 signals coming from the zenith,the north and the south at 10 degree elevation angles.The second-order ionospheric delay error on the L1 signal path from zenith are the symmetry between 15°and 15°with respect to magnetic equator,and are nearly zero at the magnetic equator.For the first time,the second-order ionospheric delay error on the global scale is presented,so this research will greatly contribute to analysing the higher-order ionospheric delay error characteristics on the global scale.展开更多
文摘Using 10-year (2001 10) monthly evaporation, precipitation, and sea surface salinity (SSS) datasets, the relationship between local freshwater flux and SSS in the north Indian Ocean (NIO) is evaluated quantitatively. The results suggest a highly positive linear correlation between freshwater flux and SSS in the Arabian Sea (correlation coefficient, R=0.74) and the western equatorial Indian Ocean (R=0.73), whereas the linear relationships are relatively weaker in the Bay of Bengal (R=0.50) and the eastern equatorial Indian Ocean (R=0.40). Additionally, the interannual variations of freshwater flux and SSS and their mutual relationship are investigated in four sub- regions for pre-monsoon, monsoon, and post-monsoon seasons separately. The satellite retrievals of SSS from the Soil Moisture and Ocean Salinity (SMOS) and Aquarius missions can provide continuous and consistent SSS fields for a better understanding of its variability and the differences between the freshwater flux and SSS signals, which are commonly thought to be linearly related.
文摘We plan to estimate global net primary production (NPP) of vegetation using the Advanced Earth Observing Satellite\|Ⅱ (ADEOS\|Ⅱ) Global Imager (GLI) multi\|spectral data. We derive an NPP estimation algorithm from ground measurement data on temperate plants in Japan. By the algorithm, we estimate NPP using a vegetation index based on pattern decomposition (VIPD) for the Mongolian Plateau. The VIPD is derived from Landsat ETM+ multi\|spectral data, and the resulting NPP estimation is compared with ground data measured in a semi\|arid area of Mongolia. The NPP estimation derived from satellite remote sensing data agrees with the ground measurement data within the error range of 15% when all above\|ground vegetation NPP is calculated for different vegetation classifications.
基金supported by the Chinese Ministry of Science and Technology(Grant Nos.2011AA120403,2010CB951403,and 2009CB723901)
文摘Forest-height inversion using airborne double-antenna synthetic aperture radar(SAR)systems has been widely researched,leading to increasing accuracy.Polarimetric SAR Interferometry(PolInSAR)data from spaceborne single-antenna SAR systems,which are influenced by temporal decorrelation,have difficulty inverting forest height.Given the temporal decorrelation effect,the classical random volume over ground(RVoG)model has been proven to invert forest height with significant errors,using repeat-pass PolInSAR data.In consideration of this problem,the temporal decorrelation RVoG(TD-RVoG;based on the RVoG)model was proposed.In this study,an improved TD-RVoG model is presented,with a new temporal decorrelation function.Compared with TD-RVoG,the new model has fewer unknown parameters and can be applied in a three-stage inversion procedure.Validity of the new model is demonstrated by Advanced Land Observing Satellite/Phased Array type L-band SAR(ALOS/PALSAR)data.Results show that the improved TD-RVoG has better accuracy,with inversion error less than 1.5m.
基金supported by the National Natural Science Foundation of China(Grant Nos.41174023,41374014 and 41304030)the National High Technology Research and Development Program of China(Grant No.2013AA122501)the Data analysis center(Grant No.GFZX0301040308-06)
文摘It is a well known fact that ionospheric delay error is a predominant factor which influences the positioning accuarcy of GNSS.Although the main part of the first-order ionospheric delay error can be removed by the frequency-dependent behaviors of the ionosphere,the second-order ionospheric delay error must be eliminated to achieve millimetre-scale positioning accuracy.Due to COSMIC occultation providing electron density profiles on the global scale,the paper presents the first-order and the second-order ionospheric delay error analysis on the global scale using the inversion of electron density profiles from COSMIC occultation data during 2009–2011.Firstly,because of the special geographical location of three ISR(incoherent scatter radar),the first-order and the second-order ionospheric delay errors are calculated and discussed;the paper also shows and analyzes the diurnal,seasonal,semi-annual variation of ionospheric delay error with respect to signal direction.Results show that for the L1 signal path,the first-order ionospheric delay error is the largest near the equator,which is circa 7 m;the maximum second-order ionospheric delay error are circa 0.6 cm,0.8 cm and 0.6 cm respectively for L1 signals coming from the zenith,the north and the south at 10 degree elevation angles.The second-order ionospheric delay error on the L1 signal path from zenith are the symmetry between 15°and 15°with respect to magnetic equator,and are nearly zero at the magnetic equator.For the first time,the second-order ionospheric delay error on the global scale is presented,so this research will greatly contribute to analysing the higher-order ionospheric delay error characteristics on the global scale.