6. Answering Questions with Visibility Analysis | QGIS By Example

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QGIS By Example

By : Daria Svidzinska

4.5 (4)

QGIS By Example

4.5 (4)

By: Daria Svidzinska

Overview of this book

If you are a beginner or an intermediate GIS user, this book is for you. It is ideal for practitioners, data analysts, and application developers who have very little or no familiarity with geospatial data and software.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

1. Handling Your Data

1. Handling Your Data

Installing QGIS

GUI elements and customization

Extending functionality through plugins

Loading data into QGIS

Dealing with projections

Loading layers to a spatial database

Summary

2. Visualizing and Styling the Data

2. Visualizing and Styling the Data

Loading layers from the spatial database

Grouping and reordering layers

Developing your own styles

Adding labels

Managing styles

Adding base maps

Summary

3. Presenting Data on a Print Map

3. Presenting Data on a Print Map

Print composer

The initial setup – page format and other essentials

Adding and customizing a map

Adding and customizing a legend

Other map items

Working with multiple maps and overviews

Managing print composers

Summary

4. Publishing the Map Online

4. Publishing the Map Online

Registering for the QGIS Cloud service

The QGIS Cloud plugin

Creating a database

Publishing the map

Viewing your map in QGIS and a browser

Deleting unused maps

Summary

5. Answering Questions with Density Analysis

5. Answering Questions with Density Analysis

Density analysis and heatmaps

Creating heat maps with the Heatmap plugin

Mapping density with a hexagonal grid

Summary

6. Answering Questions with Visibility Analysis

6. Answering Questions with Visibility Analysis

The basics of visibility analysis

Step 1 – converting a buildings' vector layer to raster

Step 2 – combining the DEM and buildings layers

Step 3 – defining observation points

Step 4 – creating viewshed coverages

Step 5 – finding scenic points

Step 6 – styling the results in 3D

Summary

7. Answering Questions with Suitability Analysis

7. Answering Questions with Suitability Analysis

Basics of suitability analysis

Step 1 – define the goal and objectives of our analysis

Step 2 – analyze the available data and define its relevance

Step 3 – define the criteria of analysis

Step 4 – Analyze and prepare the data

Step 5 – overlay the data and interpret the results

Summary

8. Automating Analysis with Processing Models

8. Automating Analysis with Processing Models

The QGIS Processing framework

Graphical Modeler

Adding inputs

Implementing the workflow

Filling model metadata and saving

Editing models

Sharing models

Summary

9. Automating Analysis with Processing Scripts

9. Automating Analysis with Processing Scripts

Python scripts in Processing

Defining inputs and outputs

Implementing the algorithm

Writing help and saving

Sharing scripts

Summary

10. Developing a Python Plugin – Select by Radius

10. Developing a Python Plugin – Select by Radius

QGIS plugins

Creating the plugin's skeleton

Designing the plugin's GUI

Using Designer UI files in the plugin

Implementing feature selection

Adding translations

Preparing the plugin for publishing

Summary

Index

Index

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Step 1 – converting a buildings' vector layer to raster

We are going to deal with a highly urbanized landscape, whose primary features have been greatly transformed by humans. In the context of visibility analysis, this means that lines of sight are blocked mainly by buildings, while the original relief features play only a minor role. In our dataset, we have two layers that describe the area of interest, exterior, and appearance:

lidar_dem: This represents the bare earth only, and provides a description of the general relief
building_footprints: These are polygons that depict all buildings, and they also contain information about a building's height in feet above the bare earth's surface in the height_roo attribute field

We need to add their values in order to obtain a meaningful result, but these layers use different data models: DEM is a raster coverage, and building footprints is a vector polygon layer. That is why before adding them, we should first take layers to a single common data...

Visually different images

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Programming languages

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