Remote Sensing in Hydrology and Water Management

Lieferzeit: Lieferbar innerhalb 14 Tagen

139,09 

ISBN: 3642640362
ISBN 13: 9783642640360
Herausgeber: Gert A Schultz/Edwin T Engman
Verlag: Springer Verlag GmbH
Umfang: xx, 483 S., 52 farbige Illustr., 483 p. 52 illus. in color.
Erscheinungsdatum: 08.10.2011
Auflage: 1/2000
Produktform: Kartoniert
Einband: KT

First comprehensive treatment of applications of remote sensing to hydrology and water managementChapters are written by well known expertsThe book contains 56 color plates and an overview of satellites and sensorsIncludes supplementary material: sn.pub/extras

Artikelnummer: 5645949 Kategorie:

Beschreibung

The book provides comprehensive information on possible applications of remote sensing data for hydrological monitoring and modelling as well as for water management decisions. Mathematical theory is provided only as far as it is necessary for understanding the underlying principles. The book is especially timely because of new programs and sensors that are or will be realised. ESA, NASA, NASDA as well as the Indian and the Brazilian Space Agency have recently launched satellites or developed plans for new sensor systems that will be especially pertinent to hydrology and water management. New techniques are presented whose structure differ from conventional hydrological models due to the nature of remotely sensed data.

Inhaltsverzeichnis

InhaltsangabePreface.- About the Editors.- Authors.- Section I: Overview and Basic Principles.- 1 Introduction.- 1.1 Introduction.- 1.2 Remote Sensing Defined.- 1.3 The Nature of Remote Sensing Data.- 1.4 Satellite Systems.- 1.4.1 Remote Sensing Platforms.- 1.4.2 Remote Sensing Sensors.- 1.4.3 Spatial Resolution.- 1.4.4 Temporal Resolution.- 1.5 Remote Sensing and Hydrology.- 1.6 Structure of the Book.- 2 Physical Principles and Technical Aspects of Remote Sensing.- 2.1 Introduction.- 2.2 The Electromagnetic Spectrum and Radiation Laws.- 2.3 Atmospheric Propagation.- 2.4 Reflection and Emission Characteristics of Natural Media.- 2.5 Sensor Principles.- 2.6 Summary of Current and Future Earth Observation Missions.- 3 Processing Remotely Sensed Data: Hardware and Software Considerations.- 3.1 Image Processing System Characteristics.- 3.1.1 The Central Processing Unit (CPU): Personal Computers, Workstations and Mainframes.- 3.1.2 Number of Analysts on a System and Mode of Operation.- 3.1.3 Serial versus Parallel Image Processing, Arithmetic Coprocessor, and Random Access Memory (RAM).- 3.1.4 Operating System and Software Compilers.- 3.1.5 Mass Storage.- 3.1.6 Screen Display Resolution.- 3.1.7 Screen Color Resolution.- 3.1.8 Image Scanning (Digitization) Considerations.- 3.2 Image Processing and GIS Software Requirement.- 3.2.1 Preprocessing.- 3.2.2 Display and Enhancement.- 3.2.3 Remote Sensing Information Extraction.- 3.2.4 Photogrammetric Information Extraction.- 3.2.5 Metadata and Image/Map Lineage Documentation.- 3.2.6 Image and Map Cartographic Composition.- 3.2.7 Geographic Information Systems (GIS).- 3.2.8 Utilities.- 3.3 Commercial and Publicly Available Digital Image Processing Systems.- 3.4 Summary.- 4 Integration of Remotely Sensed Data into Geographical Information Systems.- 4.1 Introduction.- 4.2 General Approach.- 4.2.1 Raster and Vector Data Structures.- 4.2.2 Current Approaches to the Integration.- 4.2.3 Errors Associated with Geographical Processing.- 4.3 Current Applications.- 4.3.1 Watershed Database Development.- 4.3.2 Integrated Use of Elevation Data.- 4.3.3 Land-use/Land-cover Change Detection.- 4.3.4 Modeling Watershed Runoff.- 4.3.5 Monitoring and Modeling of Water Quality.- 4.3.6 Soil Erosion Monitoring.- 4.4 Future Perspectives.- Section II: Remote Sensing Application to Hydrologic Monitoring and Modeling.- 5 Remote Sensing in Hydrological Modeling.- 5.1 Introduction.- 5.2 Remote Sensing in Operational Hydrologic Modeling.- 5.3 Remote Sensing in Coupled Water-Energy Balance Modeling.- 5.4 Remote Sensing Approach.- 5.4.1 Solar radiation.- 5.4.2 Do wnwelling longwave.- 5.4.3 Precipitation.- 5.4.4 Air Temperature.- 5.4.5 Surface Air Humidity.- 5.5 Modeling Example: The Red River Arkansas Basin.- 5.6 Future Directions.- Colour Plates of Chaps. 2-5.- 6 Precipitation 1ll.- 6.1 Introduction.- 6.2 General Approach.- 6.2.1 Ground-based radar.- 6.2.2 Use of visible and infrared satellite data.- 6.2.3 Use of passive microwave satellite data.- 6.2.4 Space-borne radar.- 6.3 Current Techniques.- 6.3.1 Single polarisation radar measurements of rainfall.- 6.3.2 Measurement of snowfall and hail.- 6.3.3 Multi-parameter radar.- 6.3.4 Satellite cloud indexing and life history methods of rainfall estimation.- 6.3.5 Bispectral techniques.- 6.3.6 Passive microwave estimates of rainfall from space.- 6.3.7 Sampling errors.- 6.4 The potential for improvement.- 6.4.1 Current performance levels.- 6.4.2 The future.- 7 Land-use and Catchment Characteristics.- 7.1 Introduction.- 7.2 Land cover Mapping with Remote Sensing.- 7.3 Vegetation Indices.- 7.3.1 Simple Vegetation Indices.- 7.3.2 Normalized Difference Vegetation Index (NDVI).- 7.3.3 Refined estimates.- 7.3.4 Multi-temporal Vegetation Index.- 7.4 Thematic Classification.- 7.4.1 Image Classification Methods.- 7.4.2 Maximum Likelihood Classification.- 7.4.3 Discussion.- 7.4.4 Probability estimation refinements.- 7.4.5 Segmentation.- 7.4.6 Case study in the Pantanal Area, Brazil.- 7.5 Radar.- 8

Das könnte Ihnen auch gefallen …