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  • 1
    Keywords: Natural disasters. ; Geotechnical engineering. ; Emergency medical services. ; Industrial Management. ; Political science. ; Natural Hazards. ; Geotechnical Engineering and Applied Earth Sciences. ; Emergency Services. ; Industrial Management. ; Governance and Government.
    Description / Table of Contents: Preface -- Before the Disaster -- During the Disaster -- After the Disaster -- Ways to Create Resilience in the Economic Activities.
    Abstract: This book recognizes Mexico's effects and challenges in a natural disaster and offers empirical risk-reduction methods in critical cases. The proposals considered here include real and detailed analysis, a set of models, frameworks, strategies, and findings in the three stages of the disaster (before–during–after). This book: describes the methodology to find secure locations for the Regional Humanitarian Response Depot; offers recommendations for the sites and creation of an Export Logistics Cluster; shows how to use available technology and information to locate volunteers in the right spots describes mathematical models to help to allocate procedure of resources for restoring the affected community and proposes actions to create resilience in the country's main economic sectors, including agriculture and industry. The processes applied at recent disasters such as the 19S earthquake and their results are used as case studies, identifying possibilities for further improvement. The book also describes new trends for Mexico due to climate change and makes suggestions for mitigating future disasters. The proposals are also replicable to other highly populated societies with similar socio-economic structures. Finally, this book is the basis for generating more innovative recommendations by researchers, graduate students, academics, professionals, and practitioners to obtain better planning and better collaboration between all the humanitarian chain actors. This book intends to be of interest as a fundamental tool for decision-makers, governments, non-governmental organizations, and enterprises.
    Type of Medium: Online Resource
    Pages: XII, 380 p. 108 illus., 66 illus. in color. , online resource.
    Edition: 1st ed. 2021.
    ISBN: 9783030672959
    DDC: 551
    Language: English
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  • 2
    Online Resource
    Online Resource
    Cham :Springer International Publishing :
    Keywords: Soil science. ; Earth sciences. ; Philosophy of nature. ; Geography. ; Agriculture. ; Biotic communities. ; Soil Science. ; Earth Sciences. ; Philosophy of Nature. ; Geography. ; Agriculture. ; Ecosystems.
    Description / Table of Contents: Soil classification systems and Kuwait soil taxonomy hierarchy -- The soil that we attempt to classify -- Horizons, layers and characteristics diagnostics for the higher categories of soil classification in Kuwait -- Families and series differentia -- Identification of the taxonomic class of a soil -- Kuwait soil taxonomy hierarchy – Soil families and soil series -- Laboratory soil procedures for Kuwait soil taxonomy.
    Abstract: This book provides guidelines to key soil taxa in the deserts of Kuwait and guidance to associated procedures for laboratory analyses of soils, leading to land use planning on informed decisions. Soils are essential to provide food, feed, and fiber in addition to multiple ecosystem services that sustain life on earth. To achieve the above services sustainably, it is essential to use soils rationally based on their potential for specific uses. This requires establishing national soil classification systems to assess soils locally and to provide guidance to other countries where similar soils may be occurring. Once soil classification is established, it becomes easier to adopt technologies established on similar soils and environmental conditions without conducting long-term and expensive experimental trial. The taxa are established based on soil’s morphological, physical, chemical, and mineralogical properties and climatic factors. It offers opportunities to maintain future soil surveys and their correlation to the soils of Kuwait. The book is useful in other arid region countries where similar soil and environmental conditions are existing, such as Bahrain, Oman, Qatar, and Saudi Arabia. The book also has international relevance, as it was prepared by extracting definitions from USDA-NRCS keys to soil taxonomy, and sections related to soils of Kuwait are added in the book. The book is a unique and excellent addition to the international soil literature.
    Type of Medium: Online Resource
    Pages: XLI, 149 p. 54 illus., 49 illus. in color. , online resource.
    Edition: 1st ed. 2022.
    ISBN: 9783030952976
    DDC: 631.4
    Language: English
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  • 3
    Series available for loan
    Series available for loan
    Hanover, NH : U.S. Army Cold Regions Research and Engineering Laboratory
    Associated volumes
    Call number: ZSP-201-82/8
    In: CRREL Report, 82-8
    Description / Table of Contents: A detailed analysis of methods for calculating the thermal conductivity of soils is presented, and trends in the predic­tions of these methods are compared. The influence of changes in the moisture content on the calculated thermal con­ductivity of a soil (at constant dry density) is shown, as is the sensitivity of this calculated value to changes in dry den­sity or in the soil solids’ thermal conductivity. The methods are evaluated to determine the extent of agreement of their predictions with measured values obtained on soils of known composition and properties. The deviations of the predicted values are determined for soils that are unfrozen or frozen, coarse or fine, unsaturated, saturated or dry. The applicability of each of the methods under various conditions is determined and recommendations are made as to the best method for each condition.
    Type of Medium: Series available for loan
    Pages: vi, 90 Seiten , Illustrationen
    Series Statement: CRREL Report 82-8
    Language: English
    Note: CONTENTS Abstract Preface Nomenclature Introduction Analysis of methods for calculating thermal conductivity Introduction Influence of moisture content on thermal conductivity Influence of dry density on thermal conductivity Influence of soil solids’ thermal conductivity Comparison of the various methods Evaluation of methods for calculating thermal conductivity Soils data used for evaluation Computer program Applicability of the methods Discussion and conclusions Applicability to unfrozen soils Applicability to frozen soils Applicability to saturated soils Effect of soil mineral composition Applicability to dry soils Summary of applicability of methods Literature cited Appendix A: Properties of some test soils Appendix B: Comparison of thermal conductivity values computed by the various methods and of their deviations from the values measured
    Location: AWI Archive
    Branch Library: AWI Library
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  • 4
    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
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  • 5
    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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  • 6
    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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  • 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
    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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  • 9
    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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  • 10
    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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