ALBERT

Note: Erscheinungsjahr in Vorlageform:1928

Note: Contents Preface to the Second Edition Preface to the First Edition 1. Images, Arrays, and Matrices 1.1 Multispectral Satellite Images 1.2 Algebra of Vectors and Matrices 1.2.1 Elementary Properties 1.2.2 Square Matrices 1.2.3 Singular Matrices 1.2.4 Symmetric, Positive Definite Matrices 1.2.5 Linear Dependence and Vector Spaces 1.3 Eigenvalues and Eigenvectors 1.4 Singular Value Decomposition 1.5 Vector Derivatives 1.6 Finding Minima and Maxima 1.7 Exercises 2. Image Statistics 2.1 Random Variables 2.1.1 Discrete Random Variables 2.1.2 Continuous Random Variables 2.1.3 Normal Distribution 2.2 Random Vectors 2.3 Parameter Estimation 2.3.1 Sampling a Distribution 2.3.2 Interval Estimation 2.3.3 Provisional Means 2.4 Hypothesis Testing and Sample Distribution Functions 2.4.1 Chi-Square Distribution 2.4.2 Student-t Distribution 2.4.3 F-Distribution 2.5 Conditional Probabilities, Bayes' Theorem, and Classification 2.6 Ordinary Linear Regression 2.6.1 One Independent Variable 2.6.2 More Than One Independent Variable 2.6.3 Regularization, Duality, and the Gram Matrix 2.7 Entropy and Information 2.7.1 Kullback-Leibler Divergence 2.7.2 Mutual Information 2.8 Exercises 3. Transformations 3.1 Discrete Fourier Transform 3.2 Discrete Wavelet Transform 3.2.1 Haar Wavelets 3.2.2 Image Compression 3.2.3 Multiresolution Analysis 3.2.3.1 Dilation Equation and Refinement Coefficients 3.2.3.2 Cascade Algorithm 3.2.3.3 Mother Wavelet 3.2.3.4 Daubechies D4 Scaling Function 3.3 Principal Components 3.3.1 Primal Solution 3.3.2 Dual Solution 3.4 Minimum Noise Fraction 3.4.1 Additive Noise 3.4.2 Minimum Noise Fraction Transformation in ENVI 3.5 Spatial Correlation 3.5.1 Maximum Autocorrelation Factor 3.5.2 Noise Estimation 3.6 Exercises 4. Filters, Kernels, and Fields 4.1 Convolution Theorem 4.2 Linear Filters 4.3 Wavelets and Filter Banks 4.3.1 One-Dimensional Arrays 4.3.2 Two-Dimensional Arrays 4.4 Kernel Methods 4.4.1 Valid Kernels 4.4.2 Kernel PCA 4.5 Gibbs-Markov Random Fields 4.6 Exercises 5. Image Enhancement and Correction 5.1 Lookup Tables and Histogram Functions 5.2 Filtering and Feature Extraction 5.2.1 Edge Detection 5.2.2 Invariant Moments 5.3 Panchromatic Sharpening 5.3.1 HSV Fusion 5.3.2 Brovey Fusion 5.3.3 PCA Fusion 5.3.4 DWT Fusion 5.3.5 A Trous Fusion 5.3.6 Quality Index 5.4 Topographic Correction 5.4.1 Rotation, Scaling, and Translation 5.4.2 Imaging Transformations 5.4.3 Camera Models and RFM Approximations 5.4.4 Stereo Imaging and Digital Elevation Models 5.4.5 Slope and Aspect 5.4.6 Illumination Correction 5.5 Image-Image Registration 5.5.1 Frequency-Domain Registration 5.5.2 Feature Matching 5.5.2.1 High-Pass Filtering 5.5.2.2 Closed Contours 5.5.2.3 Chain Codes and Moments 5.5.2.4 Contour Matching 5.5.2.5 Consistency Check 5.5.2.6 Implementation in IDL 5.5.3 Resampling and Warping 5.6 Exercises 6. Supervised Classification: Part 1 6.1 Maximum a Posteriori Probability 6.2 Training Data and Separability 6.3 Maximum Likelihood Classification 6.3.1 ENVI's Maximum Likelihood Classifier 6.3.2 Modified Maximum Likelihood Classifier 6.4 Gaussian Kernel Classification 6.5 Neural Networks 6.5.1 Neural Network Classifier 6.5.2 Cost Functions 6.5.3 Backpropagation 6.5.4 Overfitting and Generalization 6.6 Support Vector Machines 6.6.1 Linearly Separable Classes 6.6.1.1 Primal Formulation 6.6.1.2 Dual Formulation 6.6.1.3 Quadratic Programming and Support Vectors 6.6.2 Overlapping Classes 6.6.3 Solution with Sequential Minimal Optimization 6.6.4 Multiclass SVMs 6.6.5 Kernel Substitution 6.6.6 Modified SVM Classifier 6.7 Exercises 7. Supervised Classification: Part 2 7.1 Postprocessing 7.1.1 Majority Filtering 7.1.2 Probabilistic Label Relaxation 7.2 Evaluation and Comparison of Classification Accuracy 7.2.1 Accuracy Assessment 7.2.2 Model Comparison 7.3 Adaptive Boosting 7.4 Hyperspectral Analysis 7.4.1 Spectral Mixture Modeling 7.4.2 Unconstrained Linear Unmixing 7.4.3 Intrinsic End-Members and Pixel Purity 7.5 Exercises 8. Unsupervised Classification 8.1 Simple Cost Functions 8.2 Algorithms That Minimize the Simple Cost Functions 8.2.1 K-Means Clustering 8.2.2 Kernel K-Means Clustering 8.2.3 Extended K-Means Clustering 8.2.4 Agglomerative Hierarchical Clustering 8.2.5 Fuzzy K-Means Clustering 8.3 Gaussian Mixture Clustering 8.3.1 Expectation Maximization 8.3.2 Simulated Annealing 8.3.3 Partition Density 8.3.4 Implementation Notes 8.4 Including Spatial Information 8.4.1 Multiresolution Clustering 8.4.2 Spatial Clustering 8.5 Benchmark 8.6 Kohonen Self-Organizing Map 8.7 Image Segmentation 8.7.1 Segmenting a Classified Image 8.7.2 Object-Based Classification 8.7.3 Mean Shift 8.8 Exercises 9. Change Detection 9.1 Algebraic Methods 9.2 Postclassification Comparison 9.3 Principal Components Analysis 9.3.1 Iterated PCA 9.3.2 Kernel PCA 9.4 Multivariate Alteration Detection 9.4.1 Canonical Correlation Analysis 9.4.2 Orthogonality Properties 9.4.3 Scale Invariance 9.4.4 Iteratively Reweighted MAD 9.4.5 Correlation with the Original Observations 9.4.6 Regularization 9.4.7 Postprocessing 9.5 Decision Thresholds and Unsupervised Classification of Changes 9.6 Radiometrie Normalization 9.7 Exercises Appendix A: Mathematical Tools A.l Cholesky Decomposition A.2 Vector and Inner Product Spaces A.3 Least Squares Procedures A.3.1 Recursive Linear Regression A.3.2 Orthogonal Linear Regression Appendix B: Efficient Neural Network Training Algorithms B.1 Hessian Matrix B.1.1 R-Operator B.1.1.1 Determination of Rv{n} B.1.1.2 Determination of Rv{δo} B.1.1.3 Determination of Rv{δh} B.1.2 Calculating the Hessian B.2 Scaled Conjugate Gradient Training B.2.1 Conjugate Directions B.2.2 Minimizing a Quadratic Function B.2.3 Algorithm B.3 Kaiman Filter Training B.3.1 Linearization B.3.2 Algorithm B.4 A Neural Network Classifier with Hybrid Training Appendix C: ENVI Extensions in IDL C.1 Installation C.2 Extensions C.2.1 Kernel Principal Components Analysis C.2.2 Discrete Wavelet Transform Fusion C.2.3 A Trous Wavelet Transform Fusion C.2.4 Quality Index C.2.5 Calculating Heights of Man-Made Structures in High-Resolution Imagery C.2.6 Illumination Correction C.2.7 Image Registration C.2.8 Maximum Likelihood Classification C.2.9 Gaussian Kernel Classification C.2.10 Neural Network Classification C.2.11 Support Vector Machine Classification C.2.12 Probabilistic Label Relaxation C.2.13 Classifier Evaluation and Comparison C.2.14 Adaptive Boosting a Neural Network Classifier C.2.15 Kernel K-Means Clustering C.2.16 Agglomerative Hierarchical Clustering C.2.17 Fuzzy K-Means Clustering C.2.18 Gaussian Mixture Clustering C.2.19 Kohonen Self-Organizing Map C.2.20 Classified Image Segmentation C.2.21 Mean Shift Segmentation C.2.22 Multivariate Alteration Detection C.2.23 Viewing Changes C.2.24 Radiometric Normalization Appendix D: Mathematical Notation References Index

Note: Erscheinungsjahr in Vorlageform:c 2010

Note: Auch online als: Deutsche Geodätische Kommission bei der Bayerischen Akademie der Wissenschaften : Reihe C ; 644 , Zugl.: Hannover, Univ., Diss., 2009 , Zsfassung in dt. und engl.

Note: Inhalt = Content 1. Vorwort = Introduction 2. Ausgewählte Forschungsthemen = Selected research topics Methanemission aus dem Permafrost im Lena-Delta = Methane emission from permafrost in the Lena River Delta / Torsten Sachs, Julia Boike Neue Biomarker belegen Schwankungen der arktischen Meereisbedeckung während der letzten 30.000 Jahre = New biomarkers reveal fluctuations in Arctic sea ice cover during the past 30,000 years / Juliane Müller, Rüdiger Stein Die Stabilität des Westantarktischen Eisschildes – Ergebnisse der ANDRILL Tiefbohrungen = The stability of the West Antarctic ice sheet – results of ANDRILL deep drilling operations / Gerhard Kuhn, Frank Niessen Meeresalgen global - detaillierter Blick aus dem All = Detailed view from space – marine algae globally observed / Astrid Bracher, Tilman Dinter, Ilka Peeken, Bettina Schmitt Was verrät der Jahreszyklus über die Klimaentwicklung der letzten Millionen Jahre? = What does the annual cycle tell us about climate change in the last millions of years? / Thomas Laepple, Gerrit Lohmann Der Puls der Atmosphäre: Dekadisches Auf und Ab / The pulse of the tmosphere: The decadal Ups and Downs / Dörthe Handorf, Klaus Dethloff, Sascha Brand, Matthias Läuter Das Eisendüngungsexperiment LOHAFEX = The Iron Fertilization Experiment LOHAFEX / Philipp Assmy, Christine Klaas, Victor Smetacek, Dieter Wolf-Gladrow Ein nützliches genetisches Erbe - Wie alte Gene das Überleben in neuen Lebensräumen ermöglichen = A convenient genetic heritage - How ancestral genes help to survive in new habitats / Doris Abele, Ellen Weihe, Magnus Lucassen, Christoph Held, Kevin Pöhlmann Verursacher von Muschelvergiftungen identifiziert = Cause of Shellfish Poisoning Identified / Urban Tillmann, Malte Elbrächter, Bernd Krock, Uwe John, Allan Cembella Mikrobielle Stoffumsätze im Klimawandel = Climate change and the microbial cycling of organic matter / Anja Engel, Judith Piontek, Mascha Wurst, Nicole Händel, Mirko Lunau, Corinna Borchard 3. Forschung = Research PACES 3.1 TOPIC 1: The changing Arctic and Antarctic 3.2 TOPIC 2: Coastal change 3.3 TOPIC 3: Lehrstunden aus der Erdgeschichte = Lessons from the past 3.4 TOPIC 4: Das Erdsystem aus polarer Perspektive = The Earth System from a Polar Perspective 4. Helmholtz-Nachwuchsgruppen = Helmholtz Young Investigator Groups 5. Entwicklungen in den Fachbereichen = Progresses in the scientific divisions 6. Tiefseeökologie und -technologie (HGF-MPG) = Deep-sea ecology and technology (HGF-MPG) 7. Logistik und Forschungsplattformen = Logistics and research platforms 8. Nationale und internationale Zusammenarbeit = National and international cooperation 9. Wissenschaftliches Rechenzentrum = Scientific data processing centre 10. Bibliothek = Library 11. Technologietransfer = Technology transfer 12. Kommunikation und Medien = Communications and Media 13. Schulprojekt = School project 14. Personeller Aufbau und Haushaltsentwicklung = Personnel structure and budget trends 15. Veröffentlichungen, Patente = Publications, patents Anhang = Annex , In deutscher und englischer Sprache

Note: Beitr. teilw. dt., teilw. engl.

Note: Erscheinungsjahr in Vorlageform:2010

Note: Contents Preface 1 Introduction 1.1 The necessity for measurements 1.2 Definition of a measurement 1.3 Historical aspects 2 Measurement basics 2.1 Overview of methods 2.1.1 Direct and indirect methods 2.1.2 In-situ and remote sensing methods 2.1.3 Instantaneous and integrating methods 2.1.4 On-line and off-line methods, post-processing 2.1.5 Flux measurements 2.2 Main measurement principles 2.3 Measurements by inversion 2.3.1 Inversion with one variable 2.3.2 Inversion with more than one variable 2.3.3 Well-posed and ill-posed problems 2.4 Measurement instruments 2.4.1 Active and passive instruments 2.4.2 Analogue and digital instruments 2.5 Measurement platforms 2.6 Measurement variables 2.7 General characteristics of measured data 2.8 Data logging 2.9 Quality assurance/quality control 3 In-situ measurements of state variables 3.1 Thermometers 3.1.1 Liquid-in-glass thermometers 3.1.2 Bimetal thermometers 3.1.3 Resistance thermometers, thermistors 3.1.4 Thermocouples, thermopiles 3.1.5 Sonic thermometry 3.1.6 Measurement of infrared radiation 3.1.7 Soil thermometer 3.1.8 Recommendations for temperature measurements 3.2 Measuring moisture 3.2.1 Hygrometer 3.2.2 Psychrometers 3.2.3 Dewpoint determination 3.2.4 Capacitive methods 3.2.5 Recommendations for humidity measurements 3.3 Pressure sensors 3.3.1 Barometers 3.3.2 Hypsometers 3.3.3 Electronic barometers 3.3.4 Microbarometer 3.3.5 Pressure balance 3.3.6 Recommendations for pressure measurements 3.4 Wind measurements 3.4.1 Estimation from visual observations 3.4.2 Wind direction 3.4.3 Cup anemometer 3.4.4 Pressure tube 3.4.5 Hot wire anemometer 3.4.6 Ultrasonic anemometer 3.4.7 Propeller anemometer 3.4.8 Recommendations for wind measurements 4 In-situ methods for observing liquid water and ice 4.1 Precipitation 4.1.1 Rain sensors (Present Weather Sensors) 4.1.2 Rain gauges (totalisators) 4.1.3 Pluviographs 4.1.4 Disdrometer 4.1.5 Special instruments for snow 4.1.6 Recommendations for precipitation measurements 4.2 Soil moisture 4.2.1 Gravimetric methods 4.2.2 Neutron probes 4.2.3 Time domain reflectrometry (TDR) 4.2.4 Tensiometers 4.2.5 Resistance block tensiometer 4.2.6 Recommendations for soil moisture measurements 5 In-situ measurement of trace substances 5.1 Measurement of trace gases 5.1.1 Physical methods 5.1.2 Chemical methods 5.1.3 Recommendations for the measurement of trace gases 5.2 Particle measurements 5.2.1 Determination of the particle mass 5.2.2 Measuring particle size distributions 5.2.3 Measurement of the chemical composition of particles 5.2.4 Measuring the particle structure 5.2.5 Saltiphon 5.2.6 Recommendations for particle measurements 5.3 Olfactometry 5.4 Radioactivity 5.4.1 Counter tubes 5.4.2 Scintillation counters 5.4.3 Recommendations for radioactivity monitoring 6 In-situ flux measurements 6.1 Measuring radiation 6.1.1 Measuring direct solar radiation 6.1.2 Measuring shortwave irradiance 6.1.3 Measuring longwave irradiance 6.1.4 Measuring the total irradiance 6.1.5 Measuring chill 6.1.6 Sunshine recorder 6.1.7 Recommendations for radiation measurements 6.2 Visual range 6.3 Micrometeorological flux measurements 6.3.1 Cuvettes 6.3.2 Surface chambers 6.3.3 Mass balance method 6.3.4 Inferential method 6.3.5 Gradient method 6.3.6 Bowen-ratio method 6.3.7 Flux variance method 6.3.8 Dissipation method 6.3.9 Eddy covariance method 6.3.10 Eddy accumulation methods 6.3.11 Disjunct eddy covariance method 6.3.12 Recommendations for the measurement of turbulent fluxes 6.4 Evaporation Atmometers 6.4.2 Lysimeters 6.4.3 Evaporation pans and tanks 6.4.4 Recommendations for evaporation measurements 6.5 Soil heat flux 6.6 Inverse emission flux modelling 7 Remote sensing methods 7.1 Basics of remote sensing 7.2 Active sounding methods 7.2.1 RADAR 7.2.2 Windprofilers 7.2.3 SODAR 7.2.4 RASS 7.2.5 LIDAR 7.2.6 Further LIDAR techniques 7.3 Active path-averaging methods 7.3.1 Scintillometers 7.3.2 FTIR 7.3.3 DOAS 7.3.4 Quantum cascade laser 7.4 Passive methods 7.4.1 Radiometers 7.4.2 Photometers 7.4.3 Infrared-Interferometer 7.5 Tomography 7.5.1 Simultaneous Iterative Reconstruction Technique 7.5.2 Algebraic Reconstruction Technique (ART) 7.5.3 Smooth Basis Function Minimization (SBFM) 8 Remote sensing of atmospheric state variables 8.1 Temperature 8.1.1 Near-surface temperatures 8.1.2 Temperature profiles 8.2 Gaseous humidity 8.2.1 Integral water vapour content 8.2.2 Vertical profiles 8.2.3 Large-scale humidity distribution 8.3 Wind and turbulence 8.3.1 Small-scale near-surface turbulence 8.3.2 Horizontal wind fields 8.3.3 Vertical wind profiles 8.3.4 Turbulence profiles 8.3.5 Cloud winds 8.3.6 Ionospheric winds 8.4 Mixing-layer heights 8.4.1 LIDAR 8.4.2 SODAR 8.5 Turbulent fluxes 8.6 Ionospheric electron densities 8.7 Recommendations for remote sensing of state variables 9 Remote sensing of water and ice 9.1 Precipitation 9.1.1 RADAR 9.1.2 Precipitation measurements from satellites 9.2 Clouds 9.2.1 Cloud base 9.2.2 Cloud cover 9.2.3 Cloud movement 9.2.4 Water content 9.3 Recommendations for remote sensing of liquid water and ice 10 Remote sensing of trace substances 10.1 Trace gases 10.1.1 Horizontal path-averaging methods 10.1.2 Vertical column densities 10.1.3 Sounding methods 10.2 Aerosols 10.2.1 Aerosol optical depths (AOD) 10.2.2 Sounding methods 10.3 Recommendations for remote sensing of trace substances 11 Remote sensing of surface properties 11.1 Properties of the solid surface 11.1.1 Surface roughness 11.1.2 Land surface temperature 11.1.3 Soil moisture 11.1.4 Vegetation 11.1.5 Snow and ice 11.1.6 Fires 11.2 Properties of the ocean surface 11.2.1 Altitudes of the sea surface 11.2.2 Wave heights 11.2.3 Sea surface temperature 11.2.4 Salinity 11.2.5 Ocean currents 11.2.6 Ice cover, size of ice floes 11.2.7 Algae and suspended sediment concentrations 12 Remote sensing of electrical phenomena 12.1 Spherics 12.1.1 Directional analyses 12.1.2 Distance analyses 12.2 Optical lightning detection 13 Outlook on new developments Literature Subject index Appendix: Technical guidelines and standards Index to the Appendix

Note: Zugl.: München, Techn. Univ., Diss., 2005 , Beitr. teilw. in dt. und teilw. in engl. Sprache

Note: Contents: Preface. - Introductory. - Geography. - Topography. - Valleys and Rivers. - Lakes. - Coast. - Landslips. - Surface. - Soil. - Frozen Ground. - Stratigraphy. - Hecla Hoek. - Devonian. - Culm. - Middle Carboniferous. - Upper Carboniferous. - Triassic. - Structure. - Post-Triassic History. - Jurassic-Tertiary. - The Quaternary Period. - Coal Deposits. - Devonian. - The Misery Series. - The Tunheim Series. - Culm. - Sections of Boreholes. - Quality of Coals. - Coal Reserves. - Fireclay . - Minerals. - Mining. - Drilling. - History of Bear Island. - Probable Norse Discovery in the Middle Ages. - Dutch Discovery, and Dutch and English Hunting in the 16th and 17th Centuries. - Russian Hunting in the 18th Cent. - Norwegian Hunting in the 18th and 19th Centuries and Keilhau's Voyage in 1827. - Scientific Expeditions in the 19th and 20th Centuries. - Scientific Investigations, Exploitation of the Coal Deposits, and Hunting in the 20th Century. - German Activity. - Russian Activity. - Norwegian Activity. - Summary. - Literature.

Note: Erscheinungsjahr in Vorlageform:2010