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Titre : Remote sensing and GIS Type de document : Guide/Manuel Auteurs : Basudeb Bhatta, Auteur Mention d'édition : 3ème édition Editeur : Oxford, Londres, ... : Oxford University Press Année de publication : 2021 Importance : 752 p. Format : 24 x 18 cm ISBN/ISSN/EAN : 978-0-19-949664-8 Note générale : Bibliographie
additional reading material with Oxford arealLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Télédétection
[Termes IGN] acquisition d'images
[Termes IGN] airborne multispectral scanner
[Termes IGN] analyse spatiale
[Termes IGN] Global Navigation Satellite System
[Termes IGN] image hyperspectrale
[Termes IGN] image thermique
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] Lidar
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] modélisation 3D
[Termes IGN] orthorectification
[Termes IGN] Passive and Active L and S band Sensor
[Termes IGN] photographie aérienne
[Termes IGN] Satellite Microwave Radiometer
[Termes IGN] scène 3D
[Termes IGN] stéréoscopie
[Termes IGN] système d'information géographique
[Termes IGN] traitement d'image
[Termes IGN] visualisation 3DIndex. décimale : 35.00 Télédétection - généralités Résumé : (Editeur) Beginning with the history and basic concepts of remote sensing and GIS, the book gives an exhaustive coverage of optical, thermal, and microwave remote sensing, global navigation satellite systems (such as GPS and IRNSS), digital photogrammetry, visual image analysis, digital image processing, spatial and attribute data model, geospatial analysis, and planning, implementation, and management of GIS. It also presents the modern trends of remote sensing and GIS with an illustrated discussion on its numerous applications. Note de contenu : 1. Concept of Remote Sensing
1.1 Introduction
1.2 Distance of Remote Sensing
1.3 Definition of Remote Sensing
1.4 Remote Sensing: Art and/or Science
1.5 Data
1.6 Remote Sensing Process
1.7 Source of Energy
1.8 Interaction with Atmosphere
1.9 Interaction with Target
1.9.1 Hemispherical Absorptance, Transmittance, and Reflectan
1.10 Interaction with the Atmosphere Again
1.11 Recording of Energy by Sensor
1.12 Transmission, Reception, and Processing
1.13 Interpretation and Analysis
1.14 Applications of Remote Sensing
1.15 Advantages of Remote Sensing
1.16 Limitations of Remote Sensing
1.17 Ideal Remote Sensing System
2. Types of Remote Sensing and Sensor Characteristics
2.1 Introduction
2.2 Types of Remote Sensing
2.3 Characteristics of Images
2.4 Orbital Characteristics of Satellite
2.5 Remote Sensing Satellites
2.6 Concept of Swath
2.7 Concept of Nadir
2.8 Sensor Resolutions
2.9 Image Referencing System
2.9.1 Path
2.9.2 Row
2.9.3 Orbital Calendar
3. History of Remote Sensing and Indian Space Program
3.1 Introduction
3.2 The Early Age
3.3 The Middle Age
3.4 The Modern Age or Space Age
3.5 Indian Space Program
4. Photographic Imaging
4.1 Introduction
4.2 Camera Systems
4.3 Types of Camera
4.4 Filter
4.5 Film
4.6 Geometry of Aerial Photography
4.7 Ideal Time and Atmosphere for Aerial Remote Sensing
5. Digital Imaging
5.1 Introduction
5.2 Digital Image
5.3 Sensor
5.4 Imaging by Scanning Technique
5.5 Hyper-spectral Imaging
5.6 Imaging By Non-scanning Technique
5.7 Thermal Remote Sensing
5.8 Other Sensors
6. Microwave Remote Sensing
6.1 Introduction
6.2 Passive Microwave Remote Sensing
6.3 Active Microwave Remote Sensing
6.4 Radar Imaging
6.5 Airborne Versus Space-Borne Radars
6.6 Radar Systems
7. Ground-truth Data and Global Positioning System
7.1 Introduction
7.2 Requirements of Ground-Truth Data
7.3 Instruments for Ground Truthing
7.4 Parameters of Ground Truthing
7.5 Factors of Spectral Measurement
7.6 Global Navigation Satellite System
8. Photogrammetry
8.1 Introduction
8.2 Development of Photogrammetry
8.3 Classification of Photogrammetry
8.4 Photogrammetric Process
8.5 Acquisition of Imagery and its Support Data
8.6 Orientation and Triangulation
8.7 Stereo Model Compilation
8.8 Stereoscopic 3D Viewing
8.9 Stereoscopic Measurement
8.10 DTM/DEM Generation
8.11 Contour Map Generation
8.12 Orthorectification
8.13 3D Feature Extraction
8.14 3D Scene Modelling
8.15 Photogrammetry and LiDAR
8.16 Radargrammetry and Radar Interferometry
8.17 Limitations of Photogrammetry
9. Visual Image Interpretation
9.1 Introduction
9.2 Information Extraction by Human and Computer
9.3 Remote Sensing Data Products
9.4 Border or Marginal Information
9.5 Image Interpretation
9.6 Elements of Visual Image Interpretation
9.7 Interpretation Keys
9.8 Generation of Thematic Maps
9.9 Thermal Image Interpretation
9.10 Radar Image Interpretation
10. Digital Image Processing
10.1 Introduction
10.2 Categorization of Image Processing
10.3 Image Processing Systems
10.4 Digital Image
10.5 Media for Digital Data Recording, Storage, and Distribution
10.6 Data Formats of Digital Image
10.7 Header Information
10.8 Display of Digital Image
10.9 Pre-processing
10.10 Image Enhancement
10.11 Image Transformation
10.12 Image Classification
11. Data Integration, Analysis, and Presentation
11.1 Introduction
11.2 Multi-approach of Remote Sensing
11.3 Integration with Ground Truth and Other Ancillary Data
11.4 Integration of Transformed Data
11.5 Integration with GIS
11.6 Process of Remote Sensing Data Analysis
11.7 The Level of Detail
11.8 Limitations of Remote Sensing Data Analysis
11.9 Presentation
12. Applications of Remote Sensing
12.1 Introduction
12.2 Land Cover and Land Use
12.3 Agriculture
12.4 Forestry
12.5 Geology
12.6 Geomorphology
12.7 Urban Applications
12.8 Hydrology
12.9 Mapping
12.10 Oceans and Coastal Monitoring
12.11 Monitoring of Atmospheric Constituents
PART II Geographic Information Systems and Geospatial Analysis
13. Concept of Geographic Information Systems
13.1 Introduction
13.2 Definitions of GIS
13.3 Key Components of GIS
13.4 GIS-An Integration of Spatial and Attribute Information
13.5 GIS-Three Views of Information System
13.6 GIS and Related Terms
13.7 GIS-A Knowledge Hub
13.8 GIS-A Set of Interrelated Subsystems
13.9 GIS-An Information Infrastructure
13.10 Origin of GIS
14. Functions and Advantages of GIS
14.1 Introduction
14.2 Functions of GIS
14.3 Application Areas of GIS
14.4 Advantages of GIS
14.5 Functional Requirements of GIS
14.6 Limitations of GIS
15. Spatial Data Model
15.1 Introduction
15.2 Spatial, Thematic, and Temporal Dimensions of Geographic Data
15.3 Spatial Entity and Object
15.4 Spatial Data Model
15.5 Raster Data Model
15.6 Vector Data Model
15.7 Raster versus Vector
15.8 Object-Oriented Data Model
15.9 File Formats of Spatial Data
16. Attribute Data Management and Metadata Concept
16.1 Introduction
16.2 Concept of Database and DBMS
16.3 Advantages of DBMS
16.4 Functions of DBMS
16.5 File and Data Access
16.6 Data Models
16.7 Database Models
16.8 Data Models in GIS
16.9 Concept of SQL
16.10 Concept of Metadata
17. Process of GIS
17.1 Introduction
17.2 Data Capture
17.3 Data Sources
17.4 Data Encoding Methods
17.5 Linking of Spatial and Attribute Data
17.6 Organizing Data for Analysis
18. Geospatial Analysis
18.1 Introduction
18.2 Geospatial Data Analysis
18.3 Integration and Modelling of Spatial Data
18.4 Geospatial Data Analysis Methods
18.5 Database Query
18.6 Geospatial Measurements
18.7 Overlay Operations
18.8 Network Analysis
18.9 Surface Analysis
18.10 Geostatistics
18.11 Geovisualization
19. Planning, Implementation, and Management of GIS
19.1 Introduction
19.2 Planning of Project
19.3 Implementation of Project
19.4 Management of Project
19.5 Keys for Successful GIS
19.6 Reasons for Unsuccessful GIS
20. Modern Trends of GIS
20.1 Introduction
20.2 Local to Global Concept in GIS
20.3 Increase in Dimensions in GIS
20.4 Linear to Non-linear Techniques in GIS
20.5 Development in Relation between Geometry and Algebra in GIS
20.6 Development of Common Techniques in GIS
20.7 Integration of GIS and Remote Sensing
20.8 Integration of GIS and Multimedia
20.9 3D GIS
20.9.1 Virtual Reality in GIS
20.10 Integration of 3D GIS and Web GIS
20.11 4D GIS and Real-time GIS
20.12 Mobile GIS
20.12.1 Mobile mapping
20.13 Collaborative GIS (CGIS)
21. Change Detection and Geosimulation
21.1 Visual change detection
21.2 Thresholding
21.3 Image difference
21.4 Image regression
21.5 Image ratioing
21.6 Vegetation index differencing
21.7 Principal component differencing
21.8 Multi-temporal image stock classification
21.9 Post classification comparison
21.10 Change vector analysis
21.12 Cellular automata simulation
21.13 Multi-agent simulation
21.14 ANN learning in simulation
Appendix A - Concept of Map, Coordinate System, and Projection
Appendix B - Concept on Mathematical TopicsNuméro de notice : 26518 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/POSITIONNEMENT Nature : Manuel de cours DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97342
Titre : The measurement of productive efficiency and productivity growth Type de document : Monographie Auteurs : Harold O. Fried, Éditeur scientifique ; C. A. Knox Lovell, Éditeur scientifique ; Shelton S. Schmidt, Éditeur scientifique Editeur : Oxford, Londres, ... : Oxford University Press Année de publication : 2008 Importance : 638 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-0-19-518352-8 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques
[Termes IGN] efficacité
[Termes IGN] inférence statistique
[Termes IGN] productivitéIndex. décimale : 23.60 Statistiques et probabilités Résumé : (éditeur) "This is an excellent collection of book-length essays on the three main approaches to productivity and efficiency measurement: the econometric, the nonparametric, and the index number approach. The authors, who are experts in the various domains, succeed in providing highly readable surveys of the rich flow of literature that started in the late 1970s, and in giving introductions that are primarily aimed at newcomers but also interesting for experienced researchers. The many applications that are spread through the chapters give the reader a good idea of how to carry out performance assessment in practice. This book has a lot to offer a variety of readers."--Bert M. Balk, Statistics Netherlands and RSM Erasmus University
"Efficiency and productivity involve the 'best' use of scarce resources, which is the foundation of economic performance. The top specialists who have contributed to this volume unravel a fundamental but unresolved issue of economic performance--that extensive real-world variability in firms' economic performance belies the homogeneity implied by economic theory. They evaluate the pieces of the puzzle--inefficiencies involving technical, cost and revenue optimization--that cause firms to deviate from best-practice operation, and explain how such deviations can be measured and explained to further business performance and competitiveness. This is an excellent and comprehensive reference for any researcher interested in the analysis of economic performance, and the recent advances made and challenges still ahead in this field."--Catherine J. Morrison Paul, Professor, Department of Agricultural and Resource Economics, University of California, Davis and member of the Giannini FoundationNote de contenu : 1. Efficiency and Productivity / Harold O. Fried, C.A. Knox Lovell, and Shelton S. Schmidt
2. The Econometric Approach to Efficiency Analysis / William H. Greene
3. Data Envelopment Analysis : The Mathematical Programming Approach to Efficiency Analysis / Emmanuel Thanassoulis, Maria C.S. Portela, and Ozren Despić
4. Statistical Inference in Nonparametric Frontier Models : Recent Developments and Perspectives / Léopold Simar and Paul W. Wilson
5. Efficiency and Productivity : Malmquist and More / Rolf Färe, Shawna Grosskopf, and Dimitri MargaritisNuméro de notice : 17032 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE Nature : Recueil / ouvrage collectif Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=66958 Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 17032-01 23.60 Livre Centre de documentation Mathématiques Disponible
Titre : Modeling reality: how computers mirror life Type de document : Guide/Manuel Auteurs : Iwo Bialynicki-Birula, Auteur ; Iwona Bialynicka-Birula, Auteur Editeur : Oxford, Londres, ... : Oxford University Press Année de publication : 2004 Importance : 180 p. Format : 16 x 24 cm + cédérom ISBN/ISSN/EAN : 978-0-19-853100-5 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] algorithme génétique
[Termes IGN] automate cellulaire
[Termes IGN] entropie
[Termes IGN] intelligence artificielle
[Termes IGN] modèle mathématique
[Termes IGN] objet fractal
[Termes IGN] probabilités
[Termes IGN] réalité virtuelle
[Termes IGN] réseau neuronal artificiel
[Termes IGN] théorie des graphes
[Termes IGN] théorie des jeuxRésumé : (Auteur) This book originated from a series of lectures delivered by the first author at the Warsaw School of Social Psychology and at Warsaw University over the last six years. The purpose of these lectures was to give a very broad overview of various aspects of modeling for a mixed audience, from students of mathematics, computer science, and physics to students of biology and social sciences. Considering the different levels of mathematical literacy among those who attended the lectures, we have relied only on the mathematical concepts known to high school graduates. Therefore, our book can be understood by a wide spectrum of readers - from ambitious high school students to graduate students of all specialities. We were trying to keep the mathematics at the high school level; however, some chapters may require an additional effort since they describe modern advances in computer modeling. Note de contenu : I. From building blocks to computers : Models and modeling
2. The game of life : A legendary cellular automaton
3. Heads or tails : Probability of an event
4. Galton's board : Probability and statistics
5. Twenty questions : Probability and information
6. Snowflakes : The evolution of dynamical systems
7. The Lorenz butterfly : Deterministic chaos
8. From Cantor to Mandelbrot : Selfsimilarity and fractals
9. Typing monkeys : Statistical linguistics
10. The bridges of Königsberg : Graph theory
11. Prisoner's dilemma : Game theory
12. Let the best man win : Genetic algorithms
13. Computers can learn : Neural networks
14. Unpredictable individuals : Modeling society
15. Universal computer : The Turing machine
16. Hal, R2D2, and Number 5 : Artificial intelligenceNuméro de notice : 16440 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Manuel de cours Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=55163
Titre : A casebook for spatial statistical data analysis : A compilation of analyses of different thematic data sets Type de document : Monographie Auteurs : Daniel A. Griffith, Auteur ; Larry J. Layne, Auteur Editeur : Oxford, Londres, ... : Oxford University Press Année de publication : 1999 Collection : Spatial informtion systems Importance : 506 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-0-19-510958-0 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] agriculture
[Termes IGN] analyse de données
[Termes IGN] analyse spatiale
[Termes IGN] blé (céréale)
[Termes IGN] données localisées numériques
[Termes IGN] épidémie
[Termes IGN] jeu de données localisées
[Termes IGN] krigeage
[Termes IGN] pollution
[Termes IGN] ressources naturelles
[Termes IGN] socio économie
[Termes IGN] statistique mathématiqueNote de contenu : PART 1 : THEORETICAL BACKGROUND
1. Introduction
1. 1.Parallels between Spatial Autoregression and Geostatistics
1.2. The Many Faces of Spatial Autocorrelation
1.3. The Moran Coefficient Scatterplot Tool
1.4. Multivariate Spatial Association
1.5. Heterogeneity and Locational Information
1.6. The Semivariogram Plot Tool
1.7. Computer Code for Implementing Spatial Statistical Analyses
Appendix 1-A : SAS Code for Computing MC Using Standard Regression Techniques.
Appendix 1-B : Directions for Using ArcInfo to Construct a Thiessen Polygon Surface Partitioning for a Set of Georeferenced Points.
Appendix 1-C : SAS Macros Used for Converting among Degrees, Decimal Degrees and Radians
2. Important Modeling Assumptions
2.1. The Relative Importance of the Principal Assumptions
2.2. Variable Transformations
2.3. Transforming in Search of Normality
2.4. Transforming in Search of Constant Variance
2.5. Linearity: Exploitation of Linear Relationships by Linear Statistical Models
2.6. An Absence of Independence: The Presence of Spatial Autocorrelation in Georeferenced Data
2.7. Exploring Residuals in Spatial Analysis
2.8. Other Statistical Frequency Distribution Assumptions
3. Popular Spatial Autoregressive and Geostatistical Models
3.1. Spatial Autoregressive Models
3.2. Geostatistical Models
3.3. Articulating Relationships Between Spatial Autoregressive and Geostatistical Models
3.4. Computer Code for Spatial Autoregressive and Semivariogram Modeling
Appendix 3-A : SAS Code for Estimating Equations (3.7ac) - the CAR Model
Appendix 3-B : SPSS Code for Estimating Equations (3.7ac) - the CAR Model
Appendix 3-C : SAS Code for Estimating Equations (3.8) & (3.9) - the SAR & AR Models
Appendix 3-D : SPSS Code for Estimating Equations (3.8) & (3.9) - the SAR & AR Models
Appendix 3-E : SAS Code for Selected Semivariogram Models
Appendix 3-F : SPSS Code for Selected Semivariogram Models
PART 2 : GEOREFERENCED DATA SET CASE STUDIES
4. Analysis of Georeferenced Socioeconomic Attribute Variables
4.1. The Cliff-Ord Eire Population Data
4.2. Urban Population Density
4.3. Residential Insurance Coverage in Chicago
4.4. Urban Crime in Columbus, Ohio
4.5. Geographic Distribution of Minorities across Syracuse, New York
4.6. Concluding Comments: Spatial Autocorrelation and Socioeconomic Attribute Variables
Appendix 4-A : Centroids Derived from a Digitized Version of Cliff and Ord's Map of Eire (1981, 207) Using ArcInfo
5. Analysis of Georeferenced Natural Resources Attribute Variables
5.1. Kansas Oil Wells Data
5.2. Natural Resources Inventory Data
5.3. Island Biogeography: Plant Species Data
5.4. Weather Station Rainfall Data
5.5. Drainage Basin Runoff Data
5.6. Digital Elevation Data
5.7. Preclassified Remotely Sensed Image Reflectance Data
5.8. Concluding Comments: Spatial Autocorrelation and Natural Resources Attribute Variables
6. Analysis of Georeferenced Agricultural Yield Variables
6.1. The Mercer-Hall Straw Yield Data
6.2. The Wiebe Wheat Yield Data
6.3. The Broadbalk Wheat and Straw Yield Data
6.4. Sugar Cane Production in Puerto Rico
6.5. Milk Production in Puerto Rico
6.6. Concluding Comments : Spatial Autocorrelation and Agricultural Yield Variables
7. Analysis of Georeferenced Pollution Variables
7.1. Southwestern Pennsylvania Coal Ash
7.2. EMAP Indicators of Ecological Condition
7.3. Great Smoky Mountains Water pH
7.4. Chemical Elements in Northwest Texas Groundwater
7.5. Hazardous Waste Contamination of Soil: Dioxin
7.6. Concluding Comments: Spatial Autocorrelation and Pollution Variables
8. Analysis of Georeferenced Epidemiological Variables
8.1. Glasgow Standardized Mortality Rates
8.2 Pediatric Lead Poisoning in Syracuse, New York
8.3. Fox Rabies in Germany
8.4. Concluding Comments : Spatial Autocorrelation and Epidemiological Variables
PART 3 : VISUALIZING WHAT IS NOT OBSERVED
9. Exploding Georeferenced Data When Maps Have Holes or Gaps : Estimating Missing Data Values and Kriging
9.1. An Introduction to EM Estimation
9.2. Estimating Missing Values: Two Simplified Georeferenced Data Illustrations
9.3. Estimating a Conspicuous Missing Data Value for the Coal-Ash Data Set
9.4. Estimating Conspicuous Missing Data Values for an Agricultural Experiment
9.5. Estimating Missing Median Family Income Data for Ottawa-Hull
9.6. Generalizing a Map Surface with Kriging
9.7. A Cross-Validation Example
9.8. Concluding Comments : Exploding Georeferenced Data
10. Concluding Comments
10.1. More about the Nature of Georeferenced Data
10.2. Reflections on Spatial Data Model Specifications
10.3. Implications regarding Relations between Spatial Autoregressive and Geostatistical Models
10.4. Reflections on Kriging
10.5. Spatial Statistics and GIS
10.6. Now Is the Time for All Good Spatial Scientists to ...
10.7. Some Questions Yet Unanswered : Future ResearchNuméro de notice : 13033 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Monographie Accessibilité hors numérique : Non accessible via le SUDOC Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=54855
Titre : Principles of Geographical Information Systems Type de document : Guide/Manuel Auteurs : Peter A. Burrough, Auteur ; R.A. Mcdonnell, Auteur Editeur : Oxford, Londres, ... : Oxford University Press Année de publication : 1998 Collection : Spatial information systems and geostatistics Importance : 333 p. Format : 18 x 24 cm + glossaire et index ISBN/ISSN/EAN : 978-0-19-823365-7 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes IGN] analyse spatiale
[Termes IGN] erreur aléatoire
[Termes IGN] erreur de mesure
[Termes IGN] erreur systématique
[Termes IGN] figure géométrique
[Termes IGN] géostatistique
[Termes IGN] interpolation spatiale
[Termes IGN] logique floue
[Termes IGN] modèle conceptuel de données localisées
[Termes IGN] objet géographique
[Termes IGN] primitive géométrique
[Termes IGN] propagation d'erreur
[Termes IGN] qualité des données
[Termes IGN] quantité discrète
[Termes IGN] sous ensemble flou
[Termes IGN] système d'information géographique
[Termes IGN] tessellationRésumé : (Documentaliste) Cet ouvrage didactique présente en anglais les notions fondamentales des Systèmes d'Information Géographique. Il explique les concepts mathématiques et informatiques nécessaires à la gestion de l'information géographique, des données aux traitements. Les outils de l'analyse spatiale dont la géostatistique, la qualité des données, les modèles numériques de terrain, le recours à la logique floue sont longuement exposés. Note de contenu : 1) Geographical information : society, science and systems
2) Data models and axioms : formal abstractions of reality
3) Geographical data in the computer
4) Data input, verifiation, storage and output
5) Creating continuous surfaces from point data
6) Optimal interpolation using geostatistics
7) The analysis of discrete entities in space
8) Spatial analysis using continuous fields
9) Errors and quality control
10) Error propagation in numerical modelling
11) Fuzzy sets ans fuzzy geographical objects
12) Current issues and trends in GISNuméro de notice : 68303 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Manuel de cours Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=49210
