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019 ▼a 1026674885 ▼a 1027142357 ▼a 1027384374 ▼a 1027610586 ▼a 1028195874
020 ▼a 9781351650632
020 ▼a 1351650637
020 ▼z 9781498774338
020 ▼z 1498774334
020 ▼a 9781498774345
020 ▼a 1498774342
020 ▼a 9781315154602
020 ▼a 1315154609
035 ▼a 1729155 ▼b (N$T)
035 ▼a (OCoLC)1027166301 ▼z (OCoLC)1026674885 ▼z (OCoLC)1027142357 ▼z (OCoLC)1027384374 ▼z (OCoLC)1027610586 ▼z (OCoLC)1028195874
037 ▼a 9781351650632 ▼b Ingram Content Group
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050 4 ▼a GE45.R44 ▼b C43 2018
072 7 ▼a BUS ▼x 032000 ▼2 bisacsh
072 7 ▼a SOC ▼x 000000 ▼2 bisacsh
08204 ▼a 363.7/0630284 ▼2 23
1001 ▼a Chang, Ni-Bin.
24510 ▼a Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing.
260 ▼a Milton: ▼b Taylor and Francis, ▼c 2018.
300 ▼a 1 online resource (529 pages).
336 ▼a text ▼b txt ▼2 rdacontent
337 ▼a computer ▼b c ▼2 rdamedia
338 ▼a online resource ▼b cr ▼2 rdacarrier
500 ▼a 6.2.2 Mathematical Morphology.
504 ▼a Includes bibliographical references.
5050 ▼a Cover; Half Title; Title Page; Copyright Page; Contents; Preface; Acknowledgments; Authors; Chapter 1: Introduction; 1.1 Background; 1.2 Objectives and Definitions; 1.3 Featured Areas of the Book; References; Part I: Fundamental Principles of Remote Sensing; Chapter 2: Electromagnetic Radiation and Remote Sensing; 2.1 Introduction; 2.2 Properties of Electromagnetic Radiation; 2.3 Solar Radiation; 2.4 Atmospheric Radiative Transfer; 2.4.1 Principles of Radiative Transfer; 2.4.2 Reflection; 2.4.3 Refraction; 2.5 Remote Sensing Data Collection; 2.5.1 Atmospheric Windows for Remote Sensing.
5058 ▼a 2.5.2 Specific Spectral Region for Remote Sensing2.5.3 Band Distribution for Remote Sensing; 2.6 Rationale of Thermal Remote Sensing; 2.6.1 Thermal Radiation; 2.6.2 Energy Budget and Eartha?#x80;#x99;s Net Radiation; 2.7 Basic Terminologies of Remote Sensing; 2.8 Summary; References; Chapter 3: Remote Sensing Sensors and Platforms; 3.1 Introduction; 3.2 Remote Sensing Platforms; 3.2.1 Space-Borne Platforms; 3.2.2 Air-Borne Platforms; 3.2.3 Ground- or Sea-Based Platforms; 3.3 Remote Sensing Sensors; 3.3.1 Passive Sensors; 3.3.2 Active Sensors; 3.4 Real-World Remote Sensing Systems.
5058 ▼a 3.5 Current, Historical, and Future Important Missions3.5.1 Current Important Missions; 3.5.2 Historic Important Missions; 3.5.3 Future Important Missions; 3.6 System Planning of Remote Sensing Applications; 3.7 Summary; References; Chapter 4: Image Processing Techniques in Remote Sensing; 4.1 Introduction; 4.2 Image Processing Techniques; 4.2.1 Pre-Processing Techniques; 4.2.1.1 Atmospheric Correction; 4.2.1.2 Radiometric Correction; 4.2.1.3 Geometric Correction; 4.2.1.4 Geometric Transformation; 4.2.1.5 Resampling; 4.2.1.6 Mosaicking; 4.2.1.7 Gap Filling.
5058 ▼a 4.2.2 Advanced Processing Techniques4.2.2.1 Image Enhancement; 4.2.2.2 Image Restoration; 4.2.2.3 Image Transformation; 4.2.2.4 Image Segmentation; 4.3 Common Software for Image Processing; 4.3.1 ENVI; 4.3.2 ERDAS IMAGINE; 4.3.3 PCI Geomatica; 4.3.4 ArcGIS; 4.3.5 MATLABA?짰; 4.3.6 IDL; 4.4 Summary; References; Part II: Feature Extraction for Remote Sensing; Chapter 5: Feature Extraction and Classification for Environmental Remote Sensing; 5.1 Introduction; 5.2 Feature Extraction Concepts and Fundamentals; 5.2.1 Definition of Feature Extraction; 5.2.2 Feature and Feature Class.
5058 ▼a 5.2.3 Fundamentals of Feature Extraction5.3 Feature Extraction Techniques; 5.3.1 Spectral-Based Feature Extraction; 5.3.2 Spatial-Based Feature Extraction; 5.4 Supervised Feature Extraction; 5.5 Unsupervised Feature Extraction; 5.6 Semi-supervised Feature Extraction; 5.7 Image Classification Techniques with Learning Algorithms; 5.8 Performance Evaluation Metric; 5.9 Summary; References; Chapter 6: Feature Extraction with Statistics and Decision Science Algorithms; 6.1 Introduction; 6.2 Statistics and Decision Science-Based Feature Extraction Techniques; 6.2.1 Filtering Operation.
506 ▼a Owing to Legal Deposit regulations this resource may only be accessed from within National Library of Scotland on library computers. For more information contact enquiries@nls.uk. ▼5 StEdNL
520 ▼a "Automated image fusion processes involving cross-mission of multiple satellites with the aid of ground-based sensor networks and databases are critical to support environmental decision-making. This book is unique because it rests upon a smooth integration between image fusion and data mining for information retrieval and content-based mapping in the context of different environmental applications, and it focuses on environmental application issues at global and regional scale, while using local scale ground-truth data for calibration and validation. It has potential to be integrated with local scale data/image fusion based on local physical sensors and human observations."--Provided by publisher.
5880 ▼a Print version record.
590 ▼a Master record variable field(s) change: 050, 072, 082, 650 - OCLC control number change
650 0 ▼a Environmental sciences ▼x Remote sensing.
650 0 ▼a Environmental monitoring ▼x Remote sensing.
650 0 ▼a Content-based image retrieval.
650 0 ▼a Multisensor data fusion.
650 0 ▼a Multimedia data mining.
650 7 ▼a BUSINESS & ECONOMICS / Infrastructure. ▼2 bisacsh
650 7 ▼a SOCIAL SCIENCE / General. ▼2 bisacsh
650 7 ▼a Content-based image retrieval. ▼2 fast ▼0 (OCoLC)fst01748556
650 7 ▼a Environmental monitoring ▼x Remote sensing. ▼2 fast ▼0 (OCoLC)fst00913234
650 7 ▼a Environmental sciences ▼x Remote sensing. ▼2 fast ▼0 (OCoLC)fst00913503
650 7 ▼a Multimedia data mining. ▼2 fast ▼0 (OCoLC)fst01982691
650 7 ▼a Multisensor data fusion. ▼2 fast ▼0 (OCoLC)fst01029095
655 4 ▼a Electronic books.
7001 ▼a Bai, Kaixu,
77608 ▼i Print version: ▼a Chang, Ni-Bin. ▼t Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing. ▼d Milton : Taylor and Francis, 짤2018 ▼z 9781498774338
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