Generation of daily snow depth from multi-source satellite images and in situ observations
Abstract Snow depth (SD) is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensi...
Ausführliche Beschreibung
Autor*in: |
Cao, Guangzhen [verfasserIn] |
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Format: |
Artikel |
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Sprache: |
Englisch |
Erschienen: |
2015 |
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Schlagwörter: |
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Anmerkung: |
© Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag Berlin Heidelberg 2015 |
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Übergeordnetes Werk: |
Enthalten in: Journal of geographical sciences - Science Press, 2001, 25(2015), 10 vom: 05. Aug., Seite 1235-1246 |
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Übergeordnetes Werk: |
volume:25 ; year:2015 ; number:10 ; day:05 ; month:08 ; pages:1235-1246 |
Links: |
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DOI / URN: |
10.1007/s11442-015-1230-7 |
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Katalog-ID: |
OLC2051262853 |
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520 | |a Abstract Snow depth (SD) is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System (IMS). AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as “virtual” in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model (DEM) but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method. | ||
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10.1007/s11442-015-1230-7 doi (DE-627)OLC2051262853 (DE-He213)s11442-015-1230-7-p DE-627 ger DE-627 rakwb eng 910 VZ 14 ssgn 74.00$jGeographie$jAnthropogeographie: Allgemeines bkl Cao, Guangzhen verfasserin aut Generation of daily snow depth from multi-source satellite images and in situ observations 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag Berlin Heidelberg 2015 Abstract Snow depth (SD) is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System (IMS). AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as “virtual” in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model (DEM) but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method. data fusion daily snow depth multi-source satellite images passive microwave remote sensing IMS in situ observations Hou, Peng aut Zheng, Zhaojun aut Tang, Shihao aut Enthalten in Journal of geographical sciences Science Press, 2001 25(2015), 10 vom: 05. Aug., Seite 1235-1246 (DE-627)33352800X (DE-600)2055945-8 (DE-576)094642230 1009-637X nnns volume:25 year:2015 number:10 day:05 month:08 pages:1235-1246 https://doi.org/10.1007/s11442-015-1230-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-OAS SSG-OLC-MFO SSG-OPC-GGO GBV_ILN_4314 74.00$jGeographie$jAnthropogeographie: Allgemeines VZ 106417150 (DE-625)106417150 AR 25 2015 10 05 08 1235-1246 |
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10.1007/s11442-015-1230-7 doi (DE-627)OLC2051262853 (DE-He213)s11442-015-1230-7-p DE-627 ger DE-627 rakwb eng 910 VZ 14 ssgn 74.00$jGeographie$jAnthropogeographie: Allgemeines bkl Cao, Guangzhen verfasserin aut Generation of daily snow depth from multi-source satellite images and in situ observations 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag Berlin Heidelberg 2015 Abstract Snow depth (SD) is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System (IMS). AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as “virtual” in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model (DEM) but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method. data fusion daily snow depth multi-source satellite images passive microwave remote sensing IMS in situ observations Hou, Peng aut Zheng, Zhaojun aut Tang, Shihao aut Enthalten in Journal of geographical sciences Science Press, 2001 25(2015), 10 vom: 05. Aug., Seite 1235-1246 (DE-627)33352800X (DE-600)2055945-8 (DE-576)094642230 1009-637X nnns volume:25 year:2015 number:10 day:05 month:08 pages:1235-1246 https://doi.org/10.1007/s11442-015-1230-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-OAS SSG-OLC-MFO SSG-OPC-GGO GBV_ILN_4314 74.00$jGeographie$jAnthropogeographie: Allgemeines VZ 106417150 (DE-625)106417150 AR 25 2015 10 05 08 1235-1246 |
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10.1007/s11442-015-1230-7 doi (DE-627)OLC2051262853 (DE-He213)s11442-015-1230-7-p DE-627 ger DE-627 rakwb eng 910 VZ 14 ssgn 74.00$jGeographie$jAnthropogeographie: Allgemeines bkl Cao, Guangzhen verfasserin aut Generation of daily snow depth from multi-source satellite images and in situ observations 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag Berlin Heidelberg 2015 Abstract Snow depth (SD) is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System (IMS). AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as “virtual” in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model (DEM) but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method. data fusion daily snow depth multi-source satellite images passive microwave remote sensing IMS in situ observations Hou, Peng aut Zheng, Zhaojun aut Tang, Shihao aut Enthalten in Journal of geographical sciences Science Press, 2001 25(2015), 10 vom: 05. Aug., Seite 1235-1246 (DE-627)33352800X (DE-600)2055945-8 (DE-576)094642230 1009-637X nnns volume:25 year:2015 number:10 day:05 month:08 pages:1235-1246 https://doi.org/10.1007/s11442-015-1230-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-OAS SSG-OLC-MFO SSG-OPC-GGO GBV_ILN_4314 74.00$jGeographie$jAnthropogeographie: Allgemeines VZ 106417150 (DE-625)106417150 AR 25 2015 10 05 08 1235-1246 |
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10.1007/s11442-015-1230-7 doi (DE-627)OLC2051262853 (DE-He213)s11442-015-1230-7-p DE-627 ger DE-627 rakwb eng 910 VZ 14 ssgn 74.00$jGeographie$jAnthropogeographie: Allgemeines bkl Cao, Guangzhen verfasserin aut Generation of daily snow depth from multi-source satellite images and in situ observations 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag Berlin Heidelberg 2015 Abstract Snow depth (SD) is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System (IMS). AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as “virtual” in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model (DEM) but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method. data fusion daily snow depth multi-source satellite images passive microwave remote sensing IMS in situ observations Hou, Peng aut Zheng, Zhaojun aut Tang, Shihao aut Enthalten in Journal of geographical sciences Science Press, 2001 25(2015), 10 vom: 05. Aug., Seite 1235-1246 (DE-627)33352800X (DE-600)2055945-8 (DE-576)094642230 1009-637X nnns volume:25 year:2015 number:10 day:05 month:08 pages:1235-1246 https://doi.org/10.1007/s11442-015-1230-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-OAS SSG-OLC-MFO SSG-OPC-GGO GBV_ILN_4314 74.00$jGeographie$jAnthropogeographie: Allgemeines VZ 106417150 (DE-625)106417150 AR 25 2015 10 05 08 1235-1246 |
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Generation of daily snow depth from multi-source satellite images and in situ observations |
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Generation of daily snow depth from multi-source satellite images and in situ observations |
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Cao, Guangzhen |
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Journal of geographical sciences |
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Cao, Guangzhen Hou, Peng Zheng, Zhaojun Tang, Shihao |
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generation of daily snow depth from multi-source satellite images and in situ observations |
title_auth |
Generation of daily snow depth from multi-source satellite images and in situ observations |
abstract |
Abstract Snow depth (SD) is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System (IMS). AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as “virtual” in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model (DEM) but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method. © Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag Berlin Heidelberg 2015 |
abstractGer |
Abstract Snow depth (SD) is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System (IMS). AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as “virtual” in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model (DEM) but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method. © Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag Berlin Heidelberg 2015 |
abstract_unstemmed |
Abstract Snow depth (SD) is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System (IMS). AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as “virtual” in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model (DEM) but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method. © Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag Berlin Heidelberg 2015 |
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title_short |
Generation of daily snow depth from multi-source satellite images and in situ observations |
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https://doi.org/10.1007/s11442-015-1230-7 |
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Hou, Peng Zheng, Zhaojun Tang, Shihao |
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