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  • 1
    Unknown
    Champaign, Ill : Project Gutenberg
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  • 2
    Call number: M 08.0370
    In: Fortschritt-Berichte VDI
    Type of Medium: Monograph available for loan
    Pages: IX, 139 S. : graph. Darst.
    Edition: Als Ms gedr.
    ISBN: 3183244152
    Series Statement: Fortschritt-Berichte VDI : Reihe 15, Umwelttechnik 244
    Location: Upper compact magazine
    Branch Library: GFZ Library
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  • 3
    Call number: G 7194
    Type of Medium: Monograph available for loan
    Pages: 124 S. : graph. Darst., Kt.
    Location: Upper compact magazine
    Branch Library: GFZ Library
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  • 4
    Call number: MOP Per 763/CM(70)
    In: Report
    Type of Medium: Monograph available for loan
    Pages: 35 S.
    Series Statement: Report / Department of Meteorology, University of Stockholm. International Meteorological Institute in Stockholm CM-70
    Location: MOP - must be ordered
    Branch Library: GFZ Library
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  • 5
    Monograph available for loan
    Monograph available for loan
    Leiden : Nijhoff
    Associated volumes
    Call number: IASS 17.92082/6
    In: The yearbook of polar law, volume 6
    Type of Medium: Monograph available for loan
    Pages: xv, 649 Seiten , Illustrationen
    ISBN: 9789004271548
    Language: English
    Branch Library: IASS Library
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  • 6
    Monograph available for loan
    Monograph available for loan
    Geneva : World Meteorological Organization
    Associated volumes
    Call number: MOP Per 800(526) ; MOP Per 800(526, 2. Ex.)
    In: WMO
    In: Technical note
    Type of Medium: Monograph available for loan
    Pages: XV,52 S.
    ISBN: 926310526X
    Series Statement: WMO / World Meteorological Organization 526
    Location: MOP - must be ordered
    Location: MOP - must be ordered
    Branch Library: GFZ Library
    Branch Library: GFZ Library
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  • 7
    Call number: MOP Per 800(532) ; MOP Per 800(532, 2. Ex.)
    In: WMO
    In: Technical note
    Type of Medium: Monograph available for loan
    Pages: IV,46 S. : Ill.
    ISBN: 9263105324
    Series Statement: WMO / World Meteorological Organization 532
    Location: MOP - must be ordered
    Location: MOP - must be ordered
    Branch Library: GFZ Library
    Branch Library: GFZ Library
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  • 8
    Keywords: drones ; robots
    Description / Table of Contents: Chapter 1: Computational Aeroelasticity of Flying Robots with Flexible Wings by Sergio Preidikman, Bruno Antonio Roccia, Marcos Leonardo Verstraete, Marcelo Federico Valdez, Dean T. Mook and Balakumar Balachandran --- Chapter 2: Overview of Coandă MAV as an Aerial Robotic Platform by Harijono Djojodihardjo --- Chapter 3: Innovative Propulsion Systems and CFD Simulation for Fixed Wings UAVs by Esteban Valencia and Victor Hidalgo --- Chapter 4: Comparison between Semiempirical and Computational Techniques in the Prediction of Aerodynamic Performance of the Rotor of a Quadcopter by Andres Mauricio Pérez Gordillo --- Chapter 5: Nonlinear Dynamics and Control of Aerial Robots by Mahmut Reyhanoglu and Muhammad Rehan --- Chapter 6: Design and Development of Aerial Robotic Systems for Sampling Operations in Industrial Environment by Rodrigo Munguia, Edmundo Guerra, Sarquis Urzua, Yolanda Bolea and Antoni Grau --- Chapter 7: On-Board High-Performance Computing For Multi-Robot Aerial Systems by Leonardo Camargo Forero, Pablo Royo and Xavier Prats --- Chapter 8: Unmanned Aerial Systems (UASs) for Environmental Monitoring: A Review with Applications in Coastal Habitats by Daniele Ventura, Andrea Bonifazi, Maria Flavia Gravina and Gian Domenico Ardizzone
    Pages: Online-Ressource (192 Seiten)
    ISBN: 9789535134640
    Language: English
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  • 9
    Unknown
    Basel, Beijing, Wuhan : MDPI
    Keywords: remote sensing ; air pollution ; air pollutant emissions ; satellite data
    Description / Table of Contents: Belle, J.; Liu, Y. Evaluation of Aqua MODIS Collection 6 AOD Parameters for Air Quality Research over the Continental United States. Remote Sens. 2016, 8(10), 815; doi:10.3390/rs8100815. http://www.mdpi.com/2072-4292/8/10/815 --- Sun, K.; Chen, X.; Zhu, Z.; Zhang, T. High Resolution Aerosol Optical Depth Retrieval Using Gaofen-1 WFV Camera Data. Remote Sens. 2017, 9(1), 89; doi:10.3390/rs9010089. http://www.mdpi.com/2072-4292/9/1/89 --- Chen, X.; Yang, D.; Cai, Z.; Liu, Y.; Spurr, R. Aerosol Retrieval Sensitivity and Error Analysis for the Cloud and Aerosol Polarimetric Imager on Board TanSat: The Effect of Multi-Angle Measurement. Remote Sens. 2017, 9(2), 183; doi:10.3390/rs9020183. http://www.mdpi.com/2072-4292/9/2/183 --- Jiang, M.; Sun, W.; Yang, G.; Zhang, D. Modelling Seasonal GWR of Daily PM2.5 with Proper Auxiliary Variables for the Yangtze River Delta. Remote Sens. 2017, 9(4), 346; doi:10.3390/rs9040346. http://www.mdpi.com/2072-4292/9/4/346 --- Wang, Y.; Chen, L.; Li, S.; Wang, X.; Yu, C.; Si, Y.; Zhang, Z. Interference of Heavy Aerosol Loading on the VIIRS Aerosol Optical Depth (AOD) Retrieval Algorithm. Remote Sens. 2017, 9(4), 397; doi:10.3390/rs9040397. http://www.mdpi.com/2072-4292/9/4/397 --- Wang, W.; Mao, F.; Pan, Z.; Du, L.; Gong, W. Validation of VIIRS AOD through a Comparison with a Sun Photometer and MODIS AODs over Wuhan. Remote Sens. 2017, 9(5), 403; doi:10.3390/rs9050403. http://www.mdpi.com/2072-4292/9/5/403 --- Zhu, J.; Xia, X.; Wang, J.; Che, H.; Chen, H.; Zhang, J.; Xu, X.; Levy, R.; Oo, M.; Holz, R.; Ayoub, M. Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain. Remote Sens. 2017, 9(5), 432; doi:10.3390/rs9050432. http://www.mdpi.com/2072-4292/9/5/432 --- Dolgii, S.; Nevzorov, A.; Nevzorov, A.; Romanovskii, O.; Kharchenko, O. Intercomparison of Ozone Vertical Profile Measurements by Differential Absorption Lidar and IASI/MetOp Satellite in the Upper Troposphere–Lower Stratosphere. Remote Sens. 2017, 9(5), 447; doi:10.3390/rs9050447. http://www.mdpi.com/2072-4292/9/5/447 --- Liu, L.; Zhang, X.; Xu, W.; Liu, X.; Lu, X.; Wang, S.; Zhang, W.; Zhao, L. Ground Ammonia Concentrations over China Derived from Satellite and Atmospheric Transport Modeling. Remote Sens. 2017, 9(5), 467; doi:10.3390/rs9050467. http://www.mdpi.com/2072-4292/9/5/467 --- Chen, W.; Fan, A.; Yan, L. Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing. Remote Sens. 2017, 9(5), 496; doi:10.3390/rs9050496. http://www.mdpi.com/2072-4292/9/5/496 --- Osorio, M.; Casaballe, N.; Belsterli, G.; Barreto, M.; Gómez, Á.; Ferrari, J.; Frins, E. Plume Segmentation from UV Camera Images for SO2 Emission Rate Quantification on Cloud Days. Remote Sens. 2017, 9(6), 517; doi:10.3390/rs9060517. http://www.mdpi.com/2072-4292/9/6/517 --- Gu, J.; Chen, L.; Yu, C.; Li, S.; Tao, J.; Fan, M.; Xiong, X.; Wang, Z.; Shang, H.; Su, L. Ground-Level NO2 Concentrations over China Inferred from the Satellite OMI and CMAQ Model Simulations. Remote Sens. 2017, 9(6), 519; doi:10.3390/rs9060519. http://www.mdpi.com/2072-4292/9/6/519 --- Wang, Y.; Wang, J.; Levy, R.; Xu, X.; Reid, J. MODIS Retrieval of Aerosol Optical Depth over Turbid Coastal Water. Remote Sens. 2017, 9(6), 595; doi:10.3390/rs9060595. http://www.mdpi.com/2072-4292/9/6/595 --- Kim, D.; Lee, H.; Hong, H.; Choi, W.; Lee, Y.; Park, J. Estimation of Surface NO2 Volume Mixing Ratio in Four Metropolitan Cities in Korea Using Multiple Regression Models with OMI and AIRS Data. Remote Sens. 2017, 9(6), 627; doi:10.3390/rs9060627. http://www.mdpi.com/2072-4292/9/6/627 --- Qu, Y.; Han, Y.; Wu, Y.; Gao, P.; Wang, T. Study of PBLH and Its Correlation with Particulate Matter from One-Year Observation over Nanjing, Southeast China. Remote Sens. 2017, 9(7), 668; doi:10.3390/rs9070668. http://www.mdpi.com/2072-4292/9/7/668 --- Tosca, M.; Campbell, J.; Garay, M.; Lolli, S.; Seidel, F.; Marquis, J.; Kalashnikova, O. Attributing Accelerated Summertime Warming in the Southeast United States to Recent Reductions in Aerosol Burden: Indications from Vertically-Resolved Observations. Remote Sens. 2017, 9(7), 674; doi:10.3390/rs9070674. http://www.mdpi.com/2072-4292/9/7/674 --- Tao, M.; Wang, Z.; Tao, J.; Chen, L.; Wang, J.; Hou, C.; Wang, L.; Xu, X.; Zhu, H. How Do Aerosol Properties Affect the Temporal Variation of MODIS AOD Bias in Eastern China?. Remote Sens. 2017, 9(8), 800; doi:10.3390/rs9080800. http://www.mdpi.com/2072-4292/9/8/800 --- Wang, W.; Mao, F.; Du, L.; Pan, Z.; Gong, W.; Fang, S. Deriving Hourly PM2.5 Concentrations from Himawari-8 AODs over Beijing–Tianjin–Hebei in China. Remote Sens. 2017, 9(8), 858; doi:10.3390/rs9080858. http://www.mdpi.com/2072-4292/9/8/858 --- Yuchechen, A.; Lakkis, S.; Canziani, P. Linear and Non-Linear Trends for Seasonal NO2 and SO2 Concentrations in the Southern Hemisphere (2004−2016). Remote Sens. 2017, 9(9), 891; doi:10.3390/rs9090891. http://www.mdpi.com/2072-4292/9/9/891 --- Qin, K.; Rao, L.; Xu, J.; Bai, Y.; Zou, J.; Hao, N.; Li, S.; Yu, C. Estimating Ground Level NO2 Concentrations over Central-Eastern China Using a Satellite-Based Geographically and Temporally Weighted Regression Model. Remote Sens. 2017, 9(9), 950; doi:10.3390/rs9090950. http://www.mdpi.com/2072-4292/9/9/950
    Pages: Online-Ressource (X, 342 Seiten)
    Edition: Printed Edition of the Special Issue Published in Remote Sensing
    ISBN: 9783038426417
    Language: English
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  • 10
    Publication Date: 2019-08-28
    Description: The Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) mission presents new opportunities and new challenges in applying observations of two complementary multi-angle polarimeters for the space-based retrieval of global aerosol properties.Aerosol remote sensing from multi-angle radiometric-only observations enables aerosol characterization to a greater degree than single-view radiometers, as demonstrated by nearly two decades of heritage instruments. Adding polarimetry to the multi-angle observations allows for the retrieval of aerosol optical depth, Angstrom exponent,parameters of size distribution, measures of aerosol absorption, complex refractive index and degree of non-sphericity of the particles, as demonstrated by two independent retrieval algorithms applied to the heritage POLarization and Directionality of the Earth's Reflectance (POLDER) instrument. The reason why this detailed particle characterization is possible is because a multi-angle polarimeter measurement contains twice the number of Degrees of Freedom of Signal (DFS) compared to an observation from a single-view radiometer. The challenges of making use of this information content involve separating surface signal from atmospheric signal, especially when the surface is optically complex and especially in the ultraviolet portion of the spectrum where we show the necessity of polarization in making that separation. The path forward is likely to involve joint retrievalsthat will simultaneously retrieve aerosol and surface properties, although advances will berequired in radiative transfer modeling and in representing optically complex constituents in those models. Another challenge is in having the processing capability that can keep pace with the output of these instruments in an operational environment. Yet, preliminaryalgorithms applied to airborne multi-angle polarimeter observations offer encouraging results that demonstrate the advantages of these instruments to retrieve aerosol layer height, particle single scattering albedo, size distribution and spectral optical depth, and also show the necessity of polarization measurements, not just multi-angle radiometricmeasurements, to achieve these results.
    Keywords: Geosciences (General)
    Type: GSFC-E-DAA-TN71721 , Frontiers in Environmental Science (e-ISSN 2296-665X); 7; 94
    Format: application/pdf
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