QGIS and Applications in Water and Risks

Nicolas Baghdadi, French Research Institute of Science and Technology for Environment and Agriculture, France. Clement Mallet, ING, France. Mehrez Zribi, CNRS and CESBIO, France.

Introduction xi Chapter 1. Monitoring Coastal Bathymetry Using Multispectral Satellite Images at High Spatial Resolution 1 Bertrand LUBAC 1.1. Definition, context and objective 1 1.2. Description of the methodology 3 1.2.1. Step 1: selection and preprocessing of MSI images 5 1.2.2. Step 2: calibration of the bathymetry inversion model 7 1.2.3. Step 3: preparation and application of the masks 8 1.2.4. Step 4: characterization of the morphological evolution of the main sedimentary structures 9 1.3. Practical application 10 1.3.1. Software and data 10 1.3.2. Step 1: extraction of the region of interest and preprocessing 13 1.3.3. Step 2: calculation of bathymetry 20 1.3.4. Step 3: preparation and application of masks 25 1.3.5. Step 4: characterization of the morphological evolution of the main submarine sedimentary structures 31 1.4. Bibliography 33 Chapter 2. Contribution of the Integrated Topo-bathymetric Model for Coastal Wetland Evolution: Case of Geomorphologic and Biological Evolution of Ichkeul Marshes (North Tunisia) 35 Zeineb KASSOUK, Zohra LILI-CHABAANE, Benoit DEFFONTAINES, Mohammad EL HAJJ and Nicolas BAGHDADI 2.1. Coastal wetland dynamic 35 2.2. Ichkeul marshes wetland 36 2.3. Object-oriented classification method integrating the topo-bathymetric terrain model 39 2.3.1. Construction of the topo-bathymetric DTM 40 2.3.2. Image preprocessing 44 2.3.3. Segmentation 48 2.3.4. Classification 49 2.3.5. Limitations of the methodology 51 2.3.6. Case example of topo-bathymetric transect with the associated vegetation communities 51 2.3.7. Conclusion 53 2.4. From a practical point of view in QGIS 53 2.4.1. Software and data 53 2.4.2. Computation of the topo-bathymetric DTM 55 2.4.3. Image preprocessing 58 2.4.4. Segmentation 65 2.4.5. Classification 71 2.5. Bibliography 76 Chapter 3. Reservoir Hydrological Monitoring by Satellite Image Analysis 77 Paul PASSY and Adrien SELLES 3.1. Context and scientific issue 77 3.1.1. Scientific issue 77 3.1.2. Physical and human context 77 3.1.3. The importance of water resources in Central India 78 3.2. Methods and data set 78 3.2.1. Methods 78 3.2.2. Data set 79 3.2.3. Data set preparation 80 3.3. Extraction and quantification of the Singur reservoir area 82 3.3.1. Calculation of the AWEI Index. 82 3.3.2. Construction of the water-land binary raster 83 3.3.3. Vectorization of the binary raster 84 3.3.4. Selection of water polygons 85 3.3.5. Calculation of the water area of the reservoir 86 3.4. Characterization of vegetation 88 3.4.1. Choosing an indicator of the state of vegetation 88 3.4.2. Calculation of the SAVI on the study area 88 3.4.3. Creating a land-water mask 89 3.4.4. Statistics of the SAVI land surface index 90 3.5. Automation of the processing chain via the construction of a QGIS model 91 3.5.1. Model setting 91 3.5.2. Construction of the chain of treatments for the extraction of the reservoir 92 3.6. Conclusions 103 3.7. Bibliography 103 Chapter 4. Network Analysis and Routing with QGIS 105 Herve PELLA and Kenji OSE 4.1. Introduction 105 4.2. General notions 105 4.2.1. Definition of a network 105 4.2.2. Network topology 106 4.2.3. Topological relationships 107 4.2.4. Graph traversal - example of the shortest path (Dijkstra) 109 4.3. Examples of development and analysis of hydrographic networks 109 4.4. Thematic analysis 111 4.4.1. Introduction 111 4.4.2. Useful data 112 4.4.3. Step 1: verification of network consistency 113 4.4.4. Step 2: routes organization 119 4.4.5. Step 3: alignment of points on a network 121 4.4.6. Step 4: network classification 123 4.4.7. Step 5: stations characterization 124 4.4.8. Step 6: distance calculation between observation points 129 4.4.9. Step 7: upstream path and drainage basins calculation 133 4.4.10. Step 8: downstream path 135 4.4.11. Step 9: calculation of availability areas 140 4.5.