Spatio-temporal Characteristics of Area Coverage and Observation Geometry of the MISR Land-surface BRF Product: A Case Study of the Central Part of Northeast Asia
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摘要
The Multi-angle imaging spectroradiometer(MISR) land-surface(LS) bidirectional reflectance factor(BRF) product(MILS_BRF) has unique semi-simultaneous multi-angle sampling and global coverage. However, unlike on-satellite observations, the spatio-temporal characteristics of MILS_BRF data have rarely been explicitly and comprehensively analysed. Results from 5-yr(2011–2015) of MILS_BRF dataset from a typical region in central Northeast Asia as the study area showed that the monthly area coverage as well as MILS_BRF data quantity varies significantly, from the highest in October(99.05%) through median in June/July(78.09%/75.21%) to lowest in January(18.97%), and a large data-vacant area exists in the study area during four consecutive winter months(December through March). The data-vacant area is mainly composed of crop lands and cropland/natural vegetation mosaic. The amount of data within the principal plane(PP) ±30°(nPP) or cross PP ±30°(nCP), varies intra-annually with significant differences from different view zeniths or forward/backward scattering directions. For example, multiple off-nadir cameras have nPP but no nCP data for up to six months(September through February), with the opposite occurring in June and July. This study provides explicit and comprehensive information about the spatio-temporal characteristics of product coverage and observation geometry of MILS_BRF in the study area. Results provide required user reference information for MILS_BRF to evaluate performance of BRDF models or to compare with other satellite-derived BRF or albedo products. Comparing this final product to on-satellite observations, what was found here reveals a new perspective on product spatial coverage and observation geometry for multi-angle remote sensing.
The Multi-angle imaging spectroradiometer(MISR) land-surface(LS) bidirectional reflectance factor(BRF) product(MILS_BRF) has unique semi-simultaneous multi-angle sampling and global coverage. However, unlike on-satellite observations, the spatio-temporal characteristics of MILS_BRF data have rarely been explicitly and comprehensively analysed. Results from 5-yr(2011–2015) of MILS_BRF dataset from a typical region in central Northeast Asia as the study area showed that the monthly area coverage as well as MILS_BRF data quantity varies significantly, from the highest in October(99.05%) through median in June/July(78.09%/75.21%) to lowest in January(18.97%), and a large data-vacant area exists in the study area during four consecutive winter months(December through March). The data-vacant area is mainly composed of crop lands and cropland/natural vegetation mosaic. The amount of data within the principal plane(PP) ±30°(nPP) or cross PP ±30°(nCP), varies intra-annually with significant differences from different view zeniths or forward/backward scattering directions. For example, multiple off-nadir cameras have nPP but no nCP data for up to six months(September through February), with the opposite occurring in June and July. This study provides explicit and comprehensive information about the spatio-temporal characteristics of product coverage and observation geometry of MILS_BRF in the study area. Results provide required user reference information for MILS_BRF to evaluate performance of BRDF models or to compare with other satellite-derived BRF or albedo products. Comparing this final product to on-satellite observations, what was found here reveals a new perspective on product spatial coverage and observation geometry for multi-angle remote sensing.
The Multi-angle imaging spectroradiometer(MISR) land-surface(LS) bidirectional reflectance factor(BRF) product(MILS_BRF) has unique semi-simultaneous multi-angle sampling and global coverage. However, unlike on-satellite observations, the spatio-temporal characteristics of MILS_BRF data have rarely been explicitly and comprehensively analysed. Results from 5-yr(2011–2015) of MILS_BRF dataset from a typical region in central Northeast Asia as the study area showed that the monthly area coverage as well as MILS_BRF data quantity varies significantly, from the highest in October(99.05%) through median in June/July(78.09%/75.21%) to lowest in January(18.97%), and a large data-vacant area exists in the study area during four consecutive winter months(December through March). The data-vacant area is mainly composed of crop lands and cropland/natural vegetation mosaic. The amount of data within the principal plane(PP) ±30°(nPP) or cross PP ±30°(nCP), varies intra-annually with significant differences from different view zeniths or forward/backward scattering directions. For example, multiple off-nadir cameras have nPP but no nCP data for up to six months(September through February), with the opposite occurring in June and July. This study provides explicit and comprehensive information about the spatio-temporal characteristics of product coverage and observation geometry of MILS_BRF in the study area. Results provide required user reference information for MILS_BRF to evaluate performance of BRDF models or to compare with other satellite-derived BRF or albedo products. Comparing this final product to on-satellite observations, what was found here reveals a new perspective on product spatial coverage and observation geometry for multi-angle remote sensing.
引文
Abdou W A,Pilorz S H,Helmlinger M C et al.,2006.Sua Pan surface bidirectional reflectance:a case study to evaluate the effect of atmospheric correction on the surface products of the Multi-angle Imaging SpectroRadiometer(MISR)during SAFARI 2000.IEEE Transactions on Geoscience and Remote Sensing,44(7):1699-1706.doi:10.1109/TGRS.2006.876031
Angal A,Xiong X X,Wu A S,2017.Monitoring the on-orbit calibration of terra MODIS reflective solar bands using simultaneous terra MISR observations.IEEE Transactions on Geoscience and Remote Sensing,55(3):1648-1659.doi:10.1109/TGRS.2016.2628704
Armston J D,Scarth P F,Phinn S R et al.,2007.Analysis of multi-date MISR measurements for forest and woodland communities,Queensland,Australia.Remote Sensing of Environment,107(1-2):287-298.doi:10.1016/j.rse.2006.11.003
Bruegge C J,Val S,Diner D J et al.,2014.Radiometric stability of the multi-angle imaging spectroradiometer(MISR)following 15 years on-orbit.In:Proceedings of the SPIE 9218,Earth Observing Systems XIX.San Diego,California,USA:SPIE,9218:92180N.doi:10.1117/12.2062319
Bull M,Matthews J,McDonald D et al.,2011.MISR Data Product Specifications Document(JPL D-13963,Revision S).Pasadena:Jet Propulsion Laboratory,California Institute of Technology.
Chen Yongmei,Wang Jindi,Liang Shunlin et al.,2009.Comparison of MISR and MODIS bidirectional reflectance products.Journal of Remote Sensing,13(5):808-820.(in Chinese)
Chen Y M,Wang J D,Liang S L et al.,2008.The bidirectional reflectance signature of typical land surfaces and comparison of MISR and MODIS BRDF products.In:Proceedings of2008 IEEE International Geoscience and Remote Sensing Symposium.Boston,MA,USA:IEEE,III-1099-III-1102.doi:10.1109/IGARSS.2008.4779546
Czapla-Myers J,Thome K,Anderson N et al.,2014.The absolute radiometric calibration of Terra imaging sensors:MODIS,MISR,and ASTER.In:Proceedings of the SPIE 9218,Earth Observing Systems XIX.San Diego,California,USA,9218:92180Y.doi:10.1117/12.2062529
Diner D J,Martonchik J V,Borel C et al.,2008.Multi-angle Imaging SpectroRadiometer(MISR)Level 2 Surface Retrieval Algorithm Theoretical Basis(JPL D-11401,Revision E).Pasadena:Jet Propulsion Laboratory,California Institute of Technology.
He T,Liang S L,Wang D D,2017.Direct estimation of land surface albedo from simultaneous MISR data.IEEE Transactions on Geoscience and Remote Sensing,55(5):2605-2617.doi:10.1109/TGRS.2017.2648847
Hu B X,Lucht W,Li X W et al.,1997.Validation of kernel-driven semiempirical models for the surface bidirectional reflectance distribution function of land surfaces.Remote Sensing of Environment,62(3):201-214.doi:10.1016/S0034-4257(97)00082-5
Huang X Y,Jiao Z T,Dong Y D et al.,2013.Analysis of BRDFand albedo retrieved by kernel-driven models using field measurements.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,6(1):149-161.doi:10.1109/JSTARS.2012.2208264
Liao Yao,LüDaren,He Qing,2014.Intercomparison of albedo product retrieved from MODIS,MISR and POLDER.Remote Sensing Technology and Application,29(6):1008-1019.(in Chinese)
Liu X,Kafatos M,2007.MISR multi-angular spectral remote sensing for temperate forest mapping at 1.1-km resolution.International Journal of Remote Sensing,28(2):459-464.doi:10.1080/01431160601075491
LP DAAC,2017.Land cover type yearly L3 global 500 m SINGrid.https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mcd12q1
Lucht W,1998.Expected retrieval accuracies of bidirectional reflectance and albedo from EOS-MODIS and MISR angular sampling.Journal of Geophysical Research:Atmospheres,103(D8):8763-8778.doi:10.1029/98JD00089
Lucht W,Lewis P,2000.Theoretical noise sensitivity of BRDFand albedo retrieval from the EOS-MODIS and MISR sensors with respect to angular sampling.International Journal of Remote Sensing,21(1):81-98.doi:10.1080/014311600211000
Mahtab A,Sridhar V N,Navalgund R R,2008.Impact of surface anisotropy on classification accuracy of selected vegetation classes:an evaluation using multidate multiangular MISR data over parts of Madhya Pradesh,India.IEEE Transactions on Geoscience and Remote Sensing,46(1):250-258.doi:10.1109/TGRS.2007.906157
MISR-Science-Team,2015a.Terra/MISR Level 2 land surface data,version 2 retrieved from March 31,2016 to March 30,2017,from NASA ASDC.doi:10.5067/Terra/MISR/MIL2ASLS_L2.002
MISR-Science-Team,2015b.Terra/MISR level 2 TOA/Cloud classifiers,version 3 retrieved from Dec 31,2017 to Feb 28,2018,from NASA Atmospheric Science Data Center(ASDC).doi:10.5067/Terra/MISR/MIL2TCCL_L2.003
Moroney C,DiGirolamo L,Jones A,2014.MISR Data Products Specifications for the MISR Level 2 Classifiers Product(JPLD-81127,Revision A).Pasadena:Jet Propulsion Laboratory,California Institute of Technology.
Nag S,Gatebe C K,de Weck O,2015.Observing system simulations for small satellite formations estimating bidirectional reflectance.International Journal of Applied Earth Observation and Geoinformation,43:102-118.doi:10.1016/j.jag.2015.04.022
Nag S,Gatebe C K,Hilker T,2017.Simulation of multiangular remote sensing products using small satellite formations.IEEEJournal of Selected Topics in Applied Earth Observations and Remote Sensing,10(2):638-653.doi:10.1109/Jstars.2016.2570683
Pinty B,Taberner M,Haemmerle V R et al.,2011.Global-scale comparison of MISR and MODIS land surface albedos.Journal of Climate,24(3):732-749.doi:10.1175/2010JCLI3709.1
Taberner M,Pinty B,Govaerts Y et al.,2010.Comparison of MISR and MODIS land surface albedos:methodology.Journal of Geophysical Research:Atmospheres,115(D5):D05101.doi:10.1029/2009jd012665
Wanner W,Strahler A H,Hu B et al.,1997.Global retrieval of bidirectional reflectance and albedo over land from EOSMODIS and MISR data:theory and algorithm.Journal of Geophysical Research:Atmospheres,102(D14):17143-17161.doi:10.1029/96jd03295
Wu A S,Angal A,Xiong X X,2014.Comparison of coincident MODIS and MISR reflectances over the 15-year period of EOS terra.In:Proceedings of the SPIE 9218,Earth Observing Systems XIX.San Diego,California,USA:SPIE,9218:92180W.doi:10.1117/12.2061117
Wu H Y,Liang S L,Tong L et al.,2011.Snow BRDF characteristics from MODIS and MISR data.In:Proceedings of 2011IEEE International Geoscience and Remote Sensing Symposium.Vancouver,BC,Canada:IEEE,3187-3190.doi:10.1109/IGARSS.2011.6049896
Angal A,Xiong X X,Wu A S,2017.Monitoring the on-orbit calibration of terra MODIS reflective solar bands using simultaneous terra MISR observations.IEEE Transactions on Geoscience and Remote Sensing,55(3):1648-1659.doi:10.1109/TGRS.2016.2628704
Armston J D,Scarth P F,Phinn S R et al.,2007.Analysis of multi-date MISR measurements for forest and woodland communities,Queensland,Australia.Remote Sensing of Environment,107(1-2):287-298.doi:10.1016/j.rse.2006.11.003
Bruegge C J,Val S,Diner D J et al.,2014.Radiometric stability of the multi-angle imaging spectroradiometer(MISR)following 15 years on-orbit.In:Proceedings of the SPIE 9218,Earth Observing Systems XIX.San Diego,California,USA:SPIE,9218:92180N.doi:10.1117/12.2062319
Bull M,Matthews J,McDonald D et al.,2011.MISR Data Product Specifications Document(JPL D-13963,Revision S).Pasadena:Jet Propulsion Laboratory,California Institute of Technology.
Chen Yongmei,Wang Jindi,Liang Shunlin et al.,2009.Comparison of MISR and MODIS bidirectional reflectance products.Journal of Remote Sensing,13(5):808-820.(in Chinese)
Chen Y M,Wang J D,Liang S L et al.,2008.The bidirectional reflectance signature of typical land surfaces and comparison of MISR and MODIS BRDF products.In:Proceedings of2008 IEEE International Geoscience and Remote Sensing Symposium.Boston,MA,USA:IEEE,III-1099-III-1102.doi:10.1109/IGARSS.2008.4779546
Czapla-Myers J,Thome K,Anderson N et al.,2014.The absolute radiometric calibration of Terra imaging sensors:MODIS,MISR,and ASTER.In:Proceedings of the SPIE 9218,Earth Observing Systems XIX.San Diego,California,USA,9218:92180Y.doi:10.1117/12.2062529
Diner D J,Martonchik J V,Borel C et al.,2008.Multi-angle Imaging SpectroRadiometer(MISR)Level 2 Surface Retrieval Algorithm Theoretical Basis(JPL D-11401,Revision E).Pasadena:Jet Propulsion Laboratory,California Institute of Technology.
He T,Liang S L,Wang D D,2017.Direct estimation of land surface albedo from simultaneous MISR data.IEEE Transactions on Geoscience and Remote Sensing,55(5):2605-2617.doi:10.1109/TGRS.2017.2648847
Hu B X,Lucht W,Li X W et al.,1997.Validation of kernel-driven semiempirical models for the surface bidirectional reflectance distribution function of land surfaces.Remote Sensing of Environment,62(3):201-214.doi:10.1016/S0034-4257(97)00082-5
Huang X Y,Jiao Z T,Dong Y D et al.,2013.Analysis of BRDFand albedo retrieved by kernel-driven models using field measurements.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,6(1):149-161.doi:10.1109/JSTARS.2012.2208264
Liao Yao,LüDaren,He Qing,2014.Intercomparison of albedo product retrieved from MODIS,MISR and POLDER.Remote Sensing Technology and Application,29(6):1008-1019.(in Chinese)
Liu X,Kafatos M,2007.MISR multi-angular spectral remote sensing for temperate forest mapping at 1.1-km resolution.International Journal of Remote Sensing,28(2):459-464.doi:10.1080/01431160601075491
LP DAAC,2017.Land cover type yearly L3 global 500 m SINGrid.https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mcd12q1
Lucht W,1998.Expected retrieval accuracies of bidirectional reflectance and albedo from EOS-MODIS and MISR angular sampling.Journal of Geophysical Research:Atmospheres,103(D8):8763-8778.doi:10.1029/98JD00089
Lucht W,Lewis P,2000.Theoretical noise sensitivity of BRDFand albedo retrieval from the EOS-MODIS and MISR sensors with respect to angular sampling.International Journal of Remote Sensing,21(1):81-98.doi:10.1080/014311600211000
Mahtab A,Sridhar V N,Navalgund R R,2008.Impact of surface anisotropy on classification accuracy of selected vegetation classes:an evaluation using multidate multiangular MISR data over parts of Madhya Pradesh,India.IEEE Transactions on Geoscience and Remote Sensing,46(1):250-258.doi:10.1109/TGRS.2007.906157
MISR-Science-Team,2015a.Terra/MISR Level 2 land surface data,version 2 retrieved from March 31,2016 to March 30,2017,from NASA ASDC.doi:10.5067/Terra/MISR/MIL2ASLS_L2.002
MISR-Science-Team,2015b.Terra/MISR level 2 TOA/Cloud classifiers,version 3 retrieved from Dec 31,2017 to Feb 28,2018,from NASA Atmospheric Science Data Center(ASDC).doi:10.5067/Terra/MISR/MIL2TCCL_L2.003
Moroney C,DiGirolamo L,Jones A,2014.MISR Data Products Specifications for the MISR Level 2 Classifiers Product(JPLD-81127,Revision A).Pasadena:Jet Propulsion Laboratory,California Institute of Technology.
Nag S,Gatebe C K,de Weck O,2015.Observing system simulations for small satellite formations estimating bidirectional reflectance.International Journal of Applied Earth Observation and Geoinformation,43:102-118.doi:10.1016/j.jag.2015.04.022
Nag S,Gatebe C K,Hilker T,2017.Simulation of multiangular remote sensing products using small satellite formations.IEEEJournal of Selected Topics in Applied Earth Observations and Remote Sensing,10(2):638-653.doi:10.1109/Jstars.2016.2570683
Pinty B,Taberner M,Haemmerle V R et al.,2011.Global-scale comparison of MISR and MODIS land surface albedos.Journal of Climate,24(3):732-749.doi:10.1175/2010JCLI3709.1
Taberner M,Pinty B,Govaerts Y et al.,2010.Comparison of MISR and MODIS land surface albedos:methodology.Journal of Geophysical Research:Atmospheres,115(D5):D05101.doi:10.1029/2009jd012665
Wanner W,Strahler A H,Hu B et al.,1997.Global retrieval of bidirectional reflectance and albedo over land from EOSMODIS and MISR data:theory and algorithm.Journal of Geophysical Research:Atmospheres,102(D14):17143-17161.doi:10.1029/96jd03295
Wu A S,Angal A,Xiong X X,2014.Comparison of coincident MODIS and MISR reflectances over the 15-year period of EOS terra.In:Proceedings of the SPIE 9218,Earth Observing Systems XIX.San Diego,California,USA:SPIE,9218:92180W.doi:10.1117/12.2061117
Wu H Y,Liang S L,Tong L et al.,2011.Snow BRDF characteristics from MODIS and MISR data.In:Proceedings of 2011IEEE International Geoscience and Remote Sensing Symposium.Vancouver,BC,Canada:IEEE,3187-3190.doi:10.1109/IGARSS.2011.6049896