Image processing and GIS for remote sensing: techniques and applications
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
WILEY Blackwell
2016
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| Ausgabe: | Second edition |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | xii, 457 Seiten Diagramme, Illustrationen, Karten (überwiegend farbig) |
| ISBN: | 9781118724200 1118724208 |
Internformat
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| 100 | 1 | |a Liu, Jianguo |d 1963- |0 (DE-588)1013697766 |4 aut | |
| 245 | 1 | 0 | |a Image processing and GIS for remote sensing |b techniques and applications |c Jian Guo Liu and Philippa J. Mason, Department of Earth Science and Engineering, Imperial College London |
| 250 | |a Second edition | ||
| 264 | 1 | |a New York, NY |b WILEY Blackwell |c 2016 | |
| 300 | |a xii, 457 Seiten |b Diagramme, Illustrationen, Karten (überwiegend farbig) | ||
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| 700 | 1 | |a Mason, Philippa J. |4 aut | |
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Datensatz im Suchindex
| _version_ | 1804176084743225345 |
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| adam_text | Contents
R
Overview of the book, xi
Part I Image processing
1 Digital image and display, 3
1.1 What is a digital image?, 3
1.2 Digital image display, 4
1.2.1 Monochromatic display, 4
1.2.2 Tristimulus colour theory and RGB (red,
green, blue) colour display, 5
1.2.3 Pseudo-colour display, 6
1.3 Some key points, 8
1.4 Questions, 8
2 Point operations (contrast enhancement), 9
2.1 Histogram modification and lookup table, 9
2.2 Linear contrast enhancement (LCE), 11
2.2.1 Derivation of a linear function
from two points, 12
2.3 Logarithmic and exponential contrast
enhancement, 13
2.3.1 Logarithmic contrast enhancement, 13
2.3.2 Exponential contrast enhancement, 14
2.4 Histogram equalisation (HE), 14
2.5 Histogram matching (HM) and Gaussian stretch, 15
2.6 Balance contrast enhancement technique
(BGET), 16
2.6.1 Derivation of coefficients a, b and c for a
BCET parabolic function (Liu 1991), 17
2.7 Clipping in contrast enhancement, 18
2.8 Tips for interactive contrast enhancement, 18
2.9 Questions, 19
3 Algebraic operations (multi-image point
operations), 21
3.1 Image addition, 21
3.2 Image subtraction (differencing), 22
3.3 Image multiplication, 22
3.4 Image division (ratio), 22
3.5 Index derivation and supervised enhancement, 26
3.5.1 Vegetation indices, 26
3.5.2 Iron oxide ratio index, 27
3.5.3 TM clay (hydrated) mineral ratio index, 27
3.6 Standardization and logarithmic residual, 29
3.7 Simulated reflectance, 29
3.7.1 Analysis of solar radiation balance and
simulated irradiance, 29
3.7.2 Simulated spectral reflectance image, 30
3.7.3 Calculation of weights, 31
3.7.4 Example: ATM simulated reflectance
colour composite, 31
3.7.5 Comparison with ratio and logarithmic
residual techniques, 33
3.8 Summary, 33
3.9 Questions, 34
4 Filtering and neighbourhood processing, 35
4.1 FT: Understanding filtering in image frequency, 35
4.2 Concepts of convolution for image filtering, 37
4.3 Low pass filters (smoothing), 38
4.3.1 Gaussian filter, 39
4.3.2 # nearest mean filter, 39
4.3.3 Median filter, 40
4.3.4 Adaptive median filter, 41
4.3.5 K nearest median filter, 41
4.3.6 Mode (majority) filter, 41
4.3.7 Conditional smoothing filters, 41
4.4 High pass filters (edge enhancement), 42
4.4.1 Gradient filters, 43
4.4.2 Laplacian filters, 44
4.4.3 Edge-sharpening filters, 45
4.5 Local contrast enhancement, 45
4.6 FFT selective and adaptive filtering, 46
4.6.1 FFT selective filtering, 47
4.6.2 FFT adaptive filtering, 47
4.7 Summary, 52
4.8 Questions, 52
5 RGB-IHS transformation, 55
5.1 Colour co-ordinate transformation, 55
5.2 IHS de-correlation stretch, 57
5.3 Direct de-correlation stretch technique, 58
5.4 Hue RGB colour composites, 60
5.5 Derivation of RGB-IHS and IHS-RGB
transformation based on 3D geometry of the
RGB colour cube, 63
v
vi Contents
5.5.1 Derivation of RGB-IHS transformation, 63
5.5.2 Derivation of IHS-RGB transformation, 64
5.6 Mathematical proof of DDS and its properties, 65
5.6.1 Mathematical proof of DDS, 65
5.6.2 The properties of DDS, 65
5.7 Summary, 67
5.8 Questions, 67
6 Image fusion techniques, 69
6.1 RGB-IHS transformation as a tool for data
fusion, 69
6.2 Brovey transform (intensity modulation), 71
6.3 Smoothing filter-based intensity modulation, 71
6.3.1 The principle of SFIM, 71
6.3.2 Merits and limitations of SFIM, 73
6.3.3 An example of SFIM pan-sharpen
of Landsat 8 OLI image, 75
6.4 Summary, 75
6.5 Questions, 75
7 Principal component analysis, 77
7.1 Principle of the PCA, 77
7.2 PC images and PC colour composition, 79
7.3 Selective PCA for PC colour composition, 82
7.3.1 Dimensionality and colour confusion
reduction, 83
7.3.2 Spectral contrast mapping, 83
7.3.3 FPCS spectral contrast mapping, 83
7.4 De-correlation stretch, 84
7.5 Physical property orientated coordinate
transformation and tasselled cap
transformation, 85
7.6 Statistical methods for band selection, 87
7.6.1 Review of Chavez s and Sheffield s
methods, 87
7.6.2 Index of three-dimensionality, 88
7.7 Remarks, 88
7.8 Questions, 89 8
8 Image classification, 91
8.1 Approaches of statistical classification, 91
8.1.1 Unsupervised classification, 91
8.1.2 Supervised classification, 91
8.1.3 Classification processing
and implementation, 91
8.1.4 Summary of classification approaches, 92
8.2 Unsupervised classification (iterative clustering), 92
8.2.1 Iterative clustering algorithms, 92
8.2.2 Feature space iterative clustering, 93
8.2.3 Seed selection, 94
8.2.4 Cluster splitting along PCI, 95
8.3 Supervised classification, 96
8.3.1 Generic algorithm of supervised
classification, 96
8.3.2 Spectral angle mapping classification, 96
8.4 Decision rules: Dissimilarity functions, 97
8.4.1 Box classifier, 97
8.4.2 Euclidean distance: Simplified
maximum likelihood, 97
8.4.3 Maximum likelihood, 97
8.4.4 Optimal multiple point re-assignment
(OMPR), 98
8.5 Post-classification processing: Smoothing and
accuracy assessment, 98
8.5.1 Class smoothing process, 98
8.5.2 Classification accuracy assessment, 98
8.6 Summary, 101
8.7 Questions, 101
9 Image geometric operations, 103
9.1 Image geometric deformation, 103
9.1.1 Platform flight coordinates, sensor status
and imaging position, 103
9.1.2 Earth rotation and curvature, 105
9.2 Polynomial deformation model and image
warping co-registration, 106
9.2.1 Derivation of deformation model, 106
9.2.2 Pixel DN re-sampling, 108
9.3 GCP selection and automation of image
co-registration, 109
9.3.1 Manual and semi-automatic GCP
selection, 109
9.3.2 Automatic image co-registration, 109
9.4 Summary, 110
9.5 Questions, 110
10 Introduction to interferometric synthetic aperture
radar technique, 113
10.1 The principle of a radar interferometer, 113
10.2 Radar interferogram and DEM, 115
10.3 Differential InSAR and deformation
measurement, 117
10.4 Multi-temporal coherence image and random
change detection, 119
10.5 Spatial de-correlation and ratio coherence
technique, 121
10.6 Fringe smoothing filter, 123
10.7 Summary, 124
10.8 Questions, 125
Contents vii
11 Sub-pixel technology and its applications, 127
11.1 Phase correlation algorithm, 127
11.2 PC scanning for pixel-wise disparity
estimation, 132
11.2.1 Disparity estimation by PC scanning, 132
11.2.2 The median shift propagation
technique for disparity refinement, 133
11.3 Pixel-wise image co-registration, 134
11.3.1 Basic procedure of pixel-wise image
co-registration using PC, 135
11.3.2 An example of pixel-wise image
co-registration, 135
11.3.3 Limitations, 136
11.3.4 Pixel-wise image co-registration-based
SFIM pan-sharpen, 136
11.4 Very narrow-baseline stereo matching and 3D
data generation, 139
11.4.1 The principle of stereo vision, 139
11.4.2 Wide-baseline vs, narrow-baseline
stereo, 140
11.4.3 Narrow-baseline stereo matching
using PC, 140
11.4.4 Accuracy assessment and application
examples, 141
11.5 Ground motion/deformation detection
and estimation, 143
11.6 Summary, 146
Part II Geographical information systems
12 Geographical information systems, 151
12.1 Introduction, 151
12.2 Software tools, 152
12.3 GIS, cartography and thematic mapping, 152
12.4 Standards, inter-operability and
metadata, 153
12.5 GIS and the internet, 154
13 Data models and structures, 155
13.1 Introducing spatial data in representing
geographic features, 155
13.2 How are spatial data different from other
digital data?, 155
13.3 Attributes and measurement scales, 156
13.4 Fundamental data structures, 156
13.5 Raster data, 157
13.5.1 Data quantisation and storage, 157
13.5.2 Spatial variability, 159
13.5.3 Representing spatial relationships, 159
13.5.4 The effect of resolution, 160
13.5.5 Representing surface phenomena, 160
13.6 Vector data, 161
13.6.1 Vector data models, 162
13.6.2 Representing logical relationships
through geometry and feature
definition, 162
13.6.3 Extending the vector data
model, 167
13.6.4 Representing surfaces, 168
13.7 Data conversion between models and
structures, 171
13.7.1 Vector to raster conversion
(rasterisation), 171
13.7.2 Raster to vector conversion
(vectorisation), 173
13.8 Summary, 174
13.9 Questions, 175
14 Defining a coordinate space, 177
14.1 Introduction, 177
14.2 Datums and projections, 177
14.2.1 Describing and measuring the
earth, 177
14.2.2 Measuring height: The geoid, 179
14.2.3 Coordinate systems, 179
14.2.4 Datums, 180
14.2.5 Geometric distortions and projection
models, 181
14.2.6 Major map projections, 183
14.2.7 Projection specification, 187
14.3 How coordinate information
is stored and accessed, 188
14.4 Selecting appropriate coordinate systems, 189
14.5 Questions, 189
15 Operations, 191
15.1 Introducing operations on spatial data, 191
15.2 Map algebra concepts, 192
15.2.1 Working with Null data, 192
15.2.2 Logical and conditional processing, 193
15.2.3 Other types of operator, 193
15.3 Local operations, 194
15.3.1 Primary operations, 195
15.3.2 Unary operations, 195
15.3.3 Binary operations, 198
15.3.4 N-ary operations, 198
15.4 Neighbourhood operations, 199
15.4.1 Local neighbourhood, 199
15.4.2 Extended neighbourhood, 206
viii Contents
15.5 Vector equivalents to raster map algebra, 206
15.5.1 Buffers, 207
15.5.2 Dissolve, 207
15.5.3 Clipping, 208
15.5.4 Intersection, 208
15.6 Automating GIS functions, 209
15.7 Summary, 209
15.8 Questions, 210
16 Extracting information from point
data: Geostatistics, 211
16.1 Introduction, 211
16.2 Understanding the data, 211
16.2.1 Histograms, 212
16.2.2 Spatial auto-correlation, 212
16.2.3 Variograms, 213
16.2.4 Underlying trends and natural
barriers, 214
16.3 Interpolation, 214
16.3.1 Selecting sample size, 216
16.3.2 Interpolation methods, 217
16.3.3 Deterministic interpolators, 217
16.3.4 Stochastic interpolators, 221
16.4 Summary, 224
16.5 Questions, 225
17 Representing and exploiting surfaces, 227
17.1 Introduction, 227
17.2 Sources and uses of surface data, 227
17.2.1 Digital elevation models, 227
17.2.2 Vector surfaces and objects, 229
17.2.3 Uses of surface data, 230
17.3 Visualising surfaces, 230
17.3.1 Visualising in two dimensions, 231
17.3.2 Visualising in three dimensions, 233
17.4 Extracting surface parameters, 236
17.4.1 Slope: Gradient and aspect, 236
17.4.2 Curvature, 238
17.4.3 Surface topology: Drainage networks
and watersheds, 241
17.4.4 Viewshed, 242
17.4.5 Calculating volume, 245
17.5 Summary, 245
17.6 Questions, 246
18 Decision support and uncertainty, 247
18.1 Introduction, 247
18.2 Decision support, 247
18.3 Uncertainty, 248
18.3.1 Criterion uncertainty, 248
18.3.2 Threshold uncertainty, 249
18.3.3 Decision rule uncertainty, 249
18.4 Risk and hazard, 250
18.5 Dealing with uncertainty in GIS-based spatial
analysis, 250
18.5.1 Error assessment (criterion
uncertainty), 251
18.5.2 Fuzzy membership (threshold and
decision rule uncertainty), 251
18.5.3 Multi-criteria decision making
(decision rule uncertainty), 252
18.5.4 Error propagation and
sensitivity analysis (decision rule
uncertainty), 253
18.5.5 Result validation (decision rule
uncertainty), 254
18.6 Summary, 254
18.7 Questions, 255
19 Complex problems and multi-criterion
evaluation, 257
19.1 Introduction, 257
19.2 Different approaches and models, 258
19.2.1 Knowledge-driven (conceptual), 258
19.2.2 Data-driven (empirical), 258
19.2.3 Data-driven (neural network), 259
19.3 Evaluation criteria, 259
19.4 Deriving weighting coefficients, 260
19.4.1 Rating, 260
19.4.2 Ranking, 261
19.4.3 Pairwise comparison, 261
19.5 Multi-criterion combination methods, 263
19.5.1 Boolean logical combination, 263
19.5.2 Index-overlay and algebraic
combination, 264
19.5.3 Weights of evidence modelling based
on Bayesian probability theory, 264
19.5.4 Belief and Dempster-Shafer
Theory, 266
19.5.5 Weighted factors in linear combination
(WLC), 267
19.5.6 Fuzzy logic, 269
19.5.7 Vectorial fuzzy modelling, 270
19.6 Summary, 272
19.7 Questions, 272
Contents ix
Part ill Remote sensing applications
20 Image processing and GIS operation strategy, 275
20.1 General image processing strategy, 276
20.1.1 Preparation of basic working
dataset, 277
20.1.2 Image processing, 279
20.1.3 Image interpretation and map
composition, 283
20.2 Remote sensing-based GIS projects: From
images to thematic mapping, 284
20.3 An example of thematic mapping based on
optimal visualisation and interpretation of
multi-spectra] satellite imagery, 284
20.3.1 Background information, 285
20.3.2 Image enhancement for visual
observation, 285
20.3.3 Data capture and image
interpretation, 288
20.3.4 Map composition, 290
20.4 Summary, 292
21 Thematic teaching case studies in SE Spain, 293
21.1 Thematic information extraction (1): Gypsum
natural outcrop mapping and quarry change
assessment, 293
21.1.1 Data preparation and general
visualisation, 293
21.1.2 Gypsum enhancement and extraction
based on spectral analysis, 294
21.1.3 Gypsum quarry changes during
1984-2000, 296
21.1.4 Summary of the case study, 299
21.1.5 Questions, 299
21.2 Thematic information extraction (2): Spectral
enhancement and mineral mapping of
epithermal gold alteration and iron-ore
deposits in ferroan dolomite, 299
21.2.1 Image datasets and data
preparation, 299
21.2.2 ASTER image processing and analysis
for regional prospectivity, 300
21.2.3 ATM image processing and analysis for
target extraction, 304
21.2.4 Summary of the case study, 308
21.2.5 Questions, 308
21.3 Remote sensing and GIS: Evaluating
vegetation and landuse change in the Nijar
Basin, SE Spain, 308
21.3.1 Introduction, 308
21.3.2 Data preparation, 309
21.3.3 Highlighting vegetation, 309
21.3.4 Highlighting plastic greenhouses, 311
21.3.5 Identifying change between different
dates of observation, 315
21.3.6 Summary of the case study, 317
21.3.7 Questions, 318
21.3.8 References, 318
21.4 Applied remote sensing and GIS:,A combined
interpretive tool for regional tectonics,
drainage and water resources in the Andarax
basin, 318
21.4.1 Introduction, 318
21.4.2 Geological and hydrological
setting, 318
21.4.3 Case study objectives, 320
21.4.4 Landuse and vegetation, 321
21.4.5 Lithological enhancement
and discrimination, 325
21.4.6 Structural enhancement
and interpretation, 329
21.4.7 Summary of the case study, 332
21.4.8 Questions, 334
21.4.9 References, 334
22 Research case studies, 335
22.1 Vegetation change in the Three Parallel Rivers
region, Yunnan Province, China, 335
22.1.1 Introduction, 335
22.1.2 The study area and data, 335
22.1.3 NDVI Difference Red, Green
and Intensity (NDVI-D-RGI)
composite, 336
22.1.4 Data processing, 337
22.1.5 Interpretation of regional vegetation
changes, 339
22.1.6 Summary, 343
22.1.7 References, 345
22.2 GIS modelling of earthquake damage zones
using satellite imagery and digital elevation
model (DEM) data, 345
22.2.1 Introduction, 345
22.2.2 The models, 348
22.2.3 Derivation of input variables, 351
22.2.4 Earthquake damage zone modelling
and assessment, 362
22.2.5 Summary, 367
22.2.6 References, 368
x Contents
22.3 Predicting landslides using fuzzy geohazard
mapping: An example from Piemonte,
north-west Italy, 369
22.3.1 Introduction, 369
22.3.2 The study area, 370
22.3.3 A holistic GIS-based approach to
landslide hazard assessment, 371
22.3.4 Summary, 377
22.3.5 Questions, 379
22.3.6 References, 379
22.4 Land surface change detection in a desert area
in Algeria using multi-temporal ERS SAR
coherence images, 380
22.4.1 The study area, 380
22.4.2 Coherence image processing
and evaluation, 381
22.4.3 Image visualisation and interpretation
for change detection, 382
22.4.4 Summary, 387
22.4.5 References, 388
23 Industrial case studies, 389
23.1 Multi-criteria assessment of mineral
prospectivity in SE Greenland, 389
23.1.1 Introduction and objectives, 389
23.1.2 Area description, 389
23.1.3 Litho-tectonic context - why the
project s concept works, 391
23.1.4 Mineral deposit types evaluated, 392
23.1.5 Data preparation, 392
23.1.6 Multi-criteria spatial modeling, 399
23.1.7 Summary, 401
23.1.8 Questions, 404
23.1.9 Acknowledgements, 404
23.1.10 References, 404
23.2 Water resource exploration in Somalia, 405
23.2.1 Introduction, 405
23.2.2 Data preparation, 406
23.2.3 Preliminary geological enhancements
and target area identification, 407
23.2.4 Discrimination potential aquifer
lithologies using ASTER spectral
indices, 408
23.2.5 Summary, 415
23.2.6 Questions, 415
23.2.7 References, 416
Part IV Summary
24 Concluding remarks, 419
24.1 Image processing, 419
24.2 Geographic information Systems, 422
24.3 Final remarks, 425
Appendix A Imaging sensor systems and remote
sensing satellites, 427
A.l Multi-spectral sensing, 427
A.2 Broadband multi-spectral sensors, 431
A.2.1 Digital camera, 431
A.2.2 Across-track mechanical scanner, 432
A.2.3 Along-track push-broom scanner, 433
A.3 Thermal sensing and TIR sensors, 434
A.4 Hyperspectral sensors (imaging
spectrometers), 434
A.5 Passive microwave sensors, 436
A. 6 Active sensing: SAR imaging systems, 437
Appendix B Online resources for information,
software and data, 441
B. 1 Software - proprietary, low cost and free
(shareware), 441
B.2 Information and technical information on
standards, best practice, formats, techniques
and various publications, 441
B.3 Data sources including online satellite imagery
from major suppliers, DEM data plus GIS
maps and data of all kinds, 442
References, 443
Index, 451
Image Processing and CIS
for Remote Sensing
TECHNIQUES AND APPLICATIONS
SECOND EDITION
Following the successful publication of the first edition in 2009, the second edition maintains its aim
to provide an application-driven package of essential techniques in image processing and GIS, together
with case studies for demonstration and guidance in remote sensing applications. The book therefore
has a “three in one” structure that pinpoints the intersection between these three individual disciplines
and successfully draws them together in a balanced and comprehensive manner.
The book conveys in-depth knowledge of image processing and GIS techniques in an accessible and
comprehensive manner, with clear explanations and conceptual illustrations used throughout to
enhance student learning. The understanding of key concepts is always emphasised with minimal
assumption of prior mathematical experience.
The book is heavily based on the authors’ own research. Many of the author-designed image processing
techniques are popular around the world. For instance, the smoothing filter-based intensity modulation
(SFIM) technique has long been used by Astrium for mass production of their standard “pan-sharpen”
imagery data. The new edition also includes a completely new chapter on sub-pixel technology and new
case studies, based on the authors’ recent research.
Jian Guo Liu received a PhD in 1991 in remote sensing and image processing from Imperial College
London, UK and an MSc in 1982 in remote sensing and geology from China University of Geosciences,
Beijing, China. He is a reader in remote sensing in the Department of Earth Science and Engineering,
Imperial College London. His current research activities include sub-pixel technology for image
registration, DEM generation and change detection; image processing techniques for data fusion,
filtering and InSAR; and GIS multi-data modelling for geohazard studies.
Philippa J. Mason completed a BSc in geology at Southampton University in 1987, an MSc in remote
sensing at University College London in 1993 and a PhD in 1998 at Imperial College London. She is a
lecturer in remote sensing and GIS at Imperial College London and a consultant in geological remote
sensing and image interpretation. Her research interests include the application of geospatial sciences
to geohazards, tectonic geomorphology, spectral geology and mineral exploration.
ISBN 978-1-118-72420-0
|
| any_adam_object | 1 |
| author | Liu, Jianguo 1963- Mason, Philippa J. |
| author_GND | (DE-588)1013697766 |
| author_facet | Liu, Jianguo 1963- Mason, Philippa J. |
| author_role | aut aut |
| author_sort | Liu, Jianguo 1963- |
| author_variant | j l jl p j m pj pjm |
| building | Verbundindex |
| bvnumber | BV043468082 |
| classification_rvk | RB 10104 RB 10232 RB 10239 |
| ctrlnum | (OCoLC)951787246 (DE-599)DNB1081670622 |
| discipline | Geographie |
| edition | Second edition |
| format | Book |
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| id | DE-604.BV043468082 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T07:26:34Z |
| institution | BVB |
| isbn | 9781118724200 1118724208 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028885167 |
| oclc_num | 951787246 |
| open_access_boolean | |
| owner | DE-703 DE-19 DE-BY-UBM DE-11 DE-M347 |
| owner_facet | DE-703 DE-19 DE-BY-UBM DE-11 DE-M347 |
| physical | xii, 457 Seiten Diagramme, Illustrationen, Karten (überwiegend farbig) |
| publishDate | 2016 |
| publishDateSearch | 2016 |
| publishDateSort | 2016 |
| publisher | WILEY Blackwell |
| record_format | marc |
| spelling | Liu, Jianguo 1963- (DE-588)1013697766 aut Image processing and GIS for remote sensing techniques and applications Jian Guo Liu and Philippa J. Mason, Department of Earth Science and Engineering, Imperial College London Second edition New York, NY WILEY Blackwell 2016 xii, 457 Seiten Diagramme, Illustrationen, Karten (überwiegend farbig) txt rdacontent n rdamedia nc rdacarrier Geoinformationssystem (DE-588)4261642-6 gnd rswk-swf Bildverarbeitung (DE-588)4006684-8 gnd rswk-swf Fernerkundung (DE-588)4016796-3 gnd rswk-swf Fernerkundung (DE-588)4016796-3 s Geoinformationssystem (DE-588)4261642-6 s Bildverarbeitung (DE-588)4006684-8 s DE-604 Mason, Philippa J. aut Erscheint auch als Online-Ausgabe Digitalisierung UB Bayreuth - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028885167&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Bayreuth - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028885167&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Liu, Jianguo 1963- Mason, Philippa J. Image processing and GIS for remote sensing techniques and applications Geoinformationssystem (DE-588)4261642-6 gnd Bildverarbeitung (DE-588)4006684-8 gnd Fernerkundung (DE-588)4016796-3 gnd |
| subject_GND | (DE-588)4261642-6 (DE-588)4006684-8 (DE-588)4016796-3 |
| title | Image processing and GIS for remote sensing techniques and applications |
| title_auth | Image processing and GIS for remote sensing techniques and applications |
| title_exact_search | Image processing and GIS for remote sensing techniques and applications |
| title_full | Image processing and GIS for remote sensing techniques and applications Jian Guo Liu and Philippa J. Mason, Department of Earth Science and Engineering, Imperial College London |
| title_fullStr | Image processing and GIS for remote sensing techniques and applications Jian Guo Liu and Philippa J. Mason, Department of Earth Science and Engineering, Imperial College London |
| title_full_unstemmed | Image processing and GIS for remote sensing techniques and applications Jian Guo Liu and Philippa J. Mason, Department of Earth Science and Engineering, Imperial College London |
| title_short | Image processing and GIS for remote sensing |
| title_sort | image processing and gis for remote sensing techniques and applications |
| title_sub | techniques and applications |
| topic | Geoinformationssystem (DE-588)4261642-6 gnd Bildverarbeitung (DE-588)4006684-8 gnd Fernerkundung (DE-588)4016796-3 gnd |
| topic_facet | Geoinformationssystem Bildverarbeitung Fernerkundung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028885167&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028885167&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT liujianguo imageprocessingandgisforremotesensingtechniquesandapplications AT masonphilippaj imageprocessingandgisforremotesensingtechniquesandapplications |