Qgis and Generic Tools

ISBN-13: 9781786301871 / Angielski / Twarda / 2018 / 310 str.

Nicolas Baghdadi; Mehrez Zribi; CL Ment Mallet

Opis

These four volumes present innovative thematic applications implemented using the open source software QGIS. These are applications that use remote sensing over continental surfaces. The volumes detail applications of remote sensing over continental surfaces, with a first one discussing applications for agriculture.

Spis treści

Introduction ix

Chapter 1. Introduction to QGIS 1
Nicolas MOYROUD and Frédéric PORTET

1.1. History 1

1.2. QGIS graphical user interface 2

1.2.1. Standard interface  2

1.2.2. Settings  3

1.2.3. Add layer 4

1.2.4. QGIS project. 5

1.2.5. Navigation  5

1.2.6. Attributes of entities  6

1.3. The processing module, the toolkit for spatial analysis 6

1.3.1. History and interest of the treatment module 6

1.3.2. Presentation of the toolbox and its algorithms 7

1.3.3. Example of an algorithm s execution   10

1.3.4. Adding custom Python scripts 11

1.3.5. The graphic modeler  13

1.3.6. Batch processing  16

Chapter 2. Introduction to GDAL Tools in QGIS 19
Kenji OSE

2.1. GDAL: the Swiss army knife of raster processing 19

2.1.1. What is GDAL used for? 19

2.1.2. Licenses 19

2.1.3. How is GDAL used?  20

2.1.4. How GDAL works in QGIS . 23

2.2. GDAL tools: practical examples . 26

2.2.1. Introduction 26

2.2.2. Useful data  27

2.2.3. Reading image metadata 29

2.2.4. Basic processing of raster files 33

2.2.5. Analysis tools 44

2.3. Bibliography 65

Chapter 3. GRASS GIS Software with QGIS  67
Bernard LACAZE, Julita DUDEK and Jérôme PICARD

3.1. Presentation  67

3.1.1. GRASS software: a modular GIS package  67

3.1.2. Vector functions (v.∗) 68

3.1.3. GIS raster functions (r.∗) 70

3.1.4. Imagery functions (i.∗ or r.∗) 73

3.1.5. Temporal functions 74

3.2. GRASS GIS download and GRASS plugin in QGIS  77

3.2.1. Operating systems for GRASS GIS software 77

3.2.2. QGIS interface for GRASS GIS 77

3.3. GRASS GIS capabilities  79

3.3.1. Definition of a GRASS GIS project: location and mapsets 79

3.3.2. Modifications of the GRASS region 80

3.3.3. Importing raster data into GRASS 81

3.3.4. Importing vector data into GRASS 83

3.3.5. Image georeferencing 84

3.3.6. Radiometric preprocessing of images   85

3.3.7. Pan–sharpening 86

3.3.8. Computation of spectral indices and biophysical parameters . 86

3.3.9. Classifications and segmentation 87

3.4. Using Grass GIS functions from QGIS 89

3.4.1. Creating, opening, closing a dataset and adding a raster file . 90

3.4.2. Creating, adding, editing a vector layer  95

3.4.3. Examples of image processing with QGIS–GRASS  97

3.5. Acknowledgments 106

3.6. Bibliography 106

Chapter 4. The Use of SAGA GIS Modules in QGIS 107
Paul PASSY and Sylvain THÉRY

4.1. SAGA GIS in QGIS 107

4.1.1. Development of SAGA GIS . 107

4.1.2. SAGA GIS interface in QGIS 108

4.2. Using SAGA GIS to work with multispectral satellite images 111

4.2.1. Methodology 111

4.2.2. Acquisition and presentation of used data  112

4.2.3. Correction of the satellite images 112

4.2.4. Cropping the images according to the study area  115

4.2.5. Color composites and exploration of the area 116

4.2.6. Calculation of indices in order to extract vegetation and water surfaces  119

4.3. Hydrological network extraction using SAGA GIS in QGIS 131

4.3.1. Interests  131

4.3.2. DEM preprocessing  132

4.3.3. Filling sinks 135

4.3.4. Hydrographic network extraction 137

4.4. Interpolation using SAGA GIS 140

4.4.1. Principle of the interpolation . 140

4.4.2. Interpolation of measures of water quality in the aquifers of the Seine basin  140

4.5. Bibliography 148

Chapter 5. Orfeo ToolBox Applications 151
Rémi CRESSON, Manuel GRIZONNET and Julien MICHEL

5.1. The Orfeo ToolBox 151

5.1.1. Introduction 151

5.1.2. History  151

5.1.3. Application features  153

5.1.4. Governance and community . 153

5.1.5. C++ library 155

5.1.6. Internal mechanisms  156

5.1.7. Download and installation 158

5.2. Using OTB applications  158

5.2.1. Interface 158

5.2.2. Command line interface 161

5.2.3. Graphical user interface 164

5.2.4. Use from QGIS 165

5.2.5. Python bindings 165

5.2.6. Monteverdi  166

5.3. Exercises 167

5.3.1. Basic tools  167

5.3.2. Applications for image preprocessing   190

5.3.3. Feature extraction applications 221

5.3.4. Classification 231

5.4. Conclusion  240

5.5. Acknowledgments 240

5.6. Bibliography 240

Chapter 6. Online Publication of a Land Cover Map Using LizMap 243
Jean–Baptiste LAURENT and Louise LEROUX

6.1. Context 243

6.2. Workflow to publish a map online using LizMap 244

6.2.1. Presentation of LizMap 245

6.2.2. Main steps for publishing a map online with LizMap 246

6.3. Implementation with QGIS 247

6.3.1. Setup a QGIS project for Web 247

6.3.2. Setup a QGIS project for LizMap 248

6.3.3. Publish the map by FTP 251

6.3.4. Some tips to go further 253

6.4. Bibliography 255

Chapter 7. GeoHealth and QuickOSM, Two QGIS Plugins for Health Applications 257
Vincent HERBRETEAU, Christophe RÉVILLION and Etienne TRIMAILLE

7.1. Background on the use of GIS for health and the development of dedicated plugins in QGIS  257

7.2. Methodology 258

7.2.1. Importing data 259

7.2.2. Case geolocation  260

7.2.3. Data anonymization ( blurring ) 260

7.2.4. Creating an incidence or density map   262

7.2.5. Importing data from the OSM database  262

7.2.6. Environmental analyses 264

7.2.7. Export 265

7.3. Implementation: GeoHealth, assisted mapping with QGIS 267

7.3.1. Installation of GeoHealth and QuickOSM plugins 267

7.3.2. Datasets  268

7.3.3. Producing an incidence map with the GeoHealth plugin 268

7.3.4. Blurring of point data with GeoHealth and QuickOSM plugins 271

7.3.5. Example of spatial analyzes for health studies 277

7.3.6. Contribution to the OSM database using satellite images 281

7.4. Bibliography 286

List of Authors 287

Index 289

Scientific Committee 293

O autorze

Nicolas Baghdadi, French Research Institute of Science and Technology for Environment and Agriculture, France  Mehrez Zribi, CNRS and CESBIO, France  Clément Maillet, ING, France