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Home > Programming > Geospatial Analysis > QGIS Python Programming Cookbook, Second Edition
QGIS Python Programming Cookbook, Second Edition
QGIS Python Programming Cookbook, Second Edition

QGIS Python Programming Cookbook, Second Edition: Automating geospatial development , Second Edition

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QGIS Python Programming Cookbook, Second Edition

Chapter 2. Querying Vector Data

In this chapter, we will cover the following recipes:

  • Loading a vector layer from a file sample
  • Loading a vector layer from a geodatabase
  • Examining vector layer features
  • Examining vector layer attributes
  • Filtering a layer by geometry
  • Filtering a layer by attributes
  • Buffering a feature
  • Measuring the distance between two points
  • Measuring distance along a line
  • Calculating the area of a polygon
  • Creating a spatial index
  • Calculating the bearing of a line
  • Loading data from a spreadsheet
  • Accessing layer metadata

Introduction

This chapter demonstrates how to work with vector data through Python in QGIS. We will first work through loading different sources of vector data. Next, we'll move on to examining the contents of the data. Then, we'll spend the remainder of the chapter performing spatial and database operations on vector data.

Loading a vector layer from a file sample

Vector data stored in a local file is one of the most common geospatial data formats. Vector data typically stores geometry with associated attributes. In this recipe, we'll load a vector data file, in this case a shapefile, as a vector layer in QGIS.

Getting ready

For ease of following the examples in this book, it is recommended that you create a directory called qgis_data in your root or user directory,which will provide a short pathname. This setup will help prevent the occurrence of any frustrating errors resulting from path-related issues on a given system. In this recipe, and others, we'll use a point shapefile of the New York City museums, which you can download from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip this file and place the shapefile's contents in a directory named nyc within your qgis_data directory.

How to do it...

Now, we'll walk through the steps of loading a shapefile...

Loading a vector layer from a geodatabase

The PostGIS geodatabase is based on the open source Postgres database. The geodatabase provides powerful geospatial data management and operations. PyQGIS fully supports PostGIS as a data source. In this recipe, we'll add a layer from a PostGIS database.

Getting ready

Installing and configuring PostGIS is beyond the scope of this book, so we'll use a sample geospatial database interface from the excellent service http://www.qgiscloud.com/. It has its own Python plugin called QGIS Cloud. You can sign up for free and create your own geodatabase online by following the site's instructions, or you can use the example used in this recipe.

How to do it...

Perform the following steps to load a PostGIS layer into a QGIS map:

  1. First, create a new DataSourceURI instance:
            uri = QgsDataSourceURI()
  2. Next, create the database connection string:
            uri.setConnection("spacialdb.com", "9999", "lzmjzm_hwpqlf&quot...

Examining vector layer features

Once a vector layer is loaded, you may want to investigate the data. In this recipe, we'll load a vector point layer from a shapefile and take a look at the x and y coordinates of the first point.

Getting ready

We'll use the same New York City Museums layer from the Loading a vector layer from a file recipe of this chapter. You can download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In this recipe, we will load the layer, get the features, grab the first feature, obtain its geometry, and take a look at the values for the first point:

  1. First, load the layer:
            layer = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp",
                               "New York City Museums", "ogr")
  2. Next...

Examining vector layer attributes

A true GIS layer contains both spatial geometry and non-spatial attributes. In this recipe, we'll access a vector point layer's attributes in PyQGIS. We'll use a file-based layer from a shapefile, but once a layer is loaded in QGIS, every vector layer works the same way.

Getting ready

Once again, we'll use the same New York City Museums layer from the Loading a vector layer from a file recipe in this chapter. You can download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In the following steps, we'll load the layer, access the features iterator, grab the first feature, and then view the attributes as a Python list:

  1. First, load the shapefile as a vector layer:
            layer = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp...

Introduction

This chapter demonstrates how to work with vector data through Python in QGIS. We will first work through loading different sources of vector data. Next, we'll move on to examining the contents of the data. Then, we'll spend the remainder of the chapter performing spatial and database operations on vector data.

Loading a vector layer from a file sample

Vector data stored in a local file is one of the most common geospatial data formats. Vector data typically stores geometry with associated attributes. In this recipe, we'll load a vector data file, in this case a shapefile, as a vector layer in QGIS.

Getting ready

For ease of following the examples in this book, it is recommended that you create a directory called qgis_data in your root or user directory,which will provide a short pathname. This setup will help prevent the occurrence of any frustrating errors resulting from path-related issues on a given system. In this recipe, and others, we'll use a point shapefile of the New York City museums, which you can download from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip this file and place the shapefile's contents in a directory named nyc within your qgis_data directory.

How to do it...

Now, we'll walk through the steps of loading a shapefile and adding it to the map...

Loading a vector layer from a geodatabase

The PostGIS geodatabase is based on the open source Postgres database. The geodatabase provides powerful geospatial data management and operations. PyQGIS fully supports PostGIS as a data source. In this recipe, we'll add a layer from a PostGIS database.

Getting ready

Installing and configuring PostGIS is beyond the scope of this book, so we'll use a sample geospatial database interface from the excellent service http://www.qgiscloud.com/. It has its own Python plugin called QGIS Cloud. You can sign up for free and create your own geodatabase online by following the site's instructions, or you can use the example used in this recipe.

How to do it...

Perform the following steps to load a PostGIS layer into a QGIS map:

  1. First, create a new DataSourceURI instance:

            uri = QgsDataSourceURI()

  2. Next, create the database connection string:

            uri.setConnection("spacialdb.com", "9999", "lzmjzm_hwpqlf",
                          "lzmjzm_hwpqlf...

Examining vector layer features

Once a vector layer is loaded, you may want to investigate the data. In this recipe, we'll load a vector point layer from a shapefile and take a look at the x and y coordinates of the first point.

Getting ready

We'll use the same New York City Museums layer from the Loading a vector layer from a file recipe of this chapter. You can download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In this recipe, we will load the layer, get the features, grab the first feature, obtain its geometry, and take a look at the values for the first point:

  1. First, load the layer:

            layer = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp",
                               "New York City Museums", "ogr")

  2. Next, get an iterator of the layer's features:

            features ...

Examining vector layer attributes

A true GIS layer contains both spatial geometry and non-spatial attributes. In this recipe, we'll access a vector point layer's attributes in PyQGIS. We'll use a file-based layer from a shapefile, but once a layer is loaded in QGIS, every vector layer works the same way.

Getting ready

Once again, we'll use the same New York City Museums layer from the Loading a vector layer from a file recipe in this chapter. You can download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In the following steps, we'll load the layer, access the features iterator, grab the first feature, and then view the attributes as a Python list:

  1. First, load the shapefile as a vector layer:

            layer = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp",
                            ...

Filtering a layer by geometry

In this recipe, we'll perform a spatial operation to select the subset of a point layer based on the points contained in an overlapping polygon layer. We'll use shapefiles in both the cases, with one being a point layer and the other a polygon. This kind of subset is one of the most common GIS operations.

Getting ready

We will need two new shapefiles that have not been used in the previous recipes. You can download the point layer from https://github.com/GeospatialPython/Learn/raw/master/MSCities_Geo_Pts.zip.

Similarly, you can download the geometry layer from https://github.com/GeospatialPython/Learn/raw/master/GIS_CensusTract.zip.

Unzip these shapefiles and place them in a directory named ms within your qgis_data directory, within your root or home directory.

How to do it...

In this recipe, we will perform several steps to select features in the point layer that fall within the polygon layer, as follows:

  1. First, load the point layer:

            lyrPts = QgsVectorLayer...

Filtering a layer by attributes

In addition to the spatial queries outlined in the previous recipe, we can also subset a layer by its attributes. This type of query resembles a more traditional relational database query and, in fact, uses SQL statements. In this recipe, we will filter a point shapefile-based layer by an attribute.

Getting ready

We'll use the same New York City Museums layer used in the previous recipes in this chapter. You can download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In this recipe, we'll filter the layer by an attribute, select the filtered features, and zoom to them, as follows:

  1. First, we load the point layer:

            lyrPts = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp",
                                "Museums", "ogr")

  2. Next, we add the layer...

Buffering a feature

Buffering a feature creates a polygon around a feature as a selection geometry or just a simple visualization. In this recipe, we'll buffer a point in a point feature and add the returned polygon geometry to the map.

Getting ready

Once again, we'll use the same New York City Museums layer. You can download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

This recipe involves both a spatial operation and multiple visualizations. To do this, perform the following steps:

  1. First, load the layer:

            lyr = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp",
              "Museums", "ogr")

  2. Next, visualize the layer on the map:

            QgsMapLayerRegistry.instance().addMapLayers([lyr])

  3. Access the layer's features:

            fts = lyr.getFeatures()

  4. Grab the first...

Measuring the distance between two points

In the QgsDistanceArea object, PyQGIS has excellent capabilities for measuring the distance. We'll use this object for several recipes, starting with measuring the distance between two points.

Getting ready

If you don't already have the New York City Museums layer used in the previous recipes in this chapter, download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In the following steps, we'll extract the first and last points in the layer's point order and measure the distance between them:

  1. First, import the library that contains the QGIS contents:

            from qgis.core import QGis

  2. Then, load the layer:

            lyr = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp",
                             "Museums", "ogr")

  3. Access the features:

    ...

Measuring distance along a line

In this recipe, we'll measure the distance along a line with multiple vertices.

Getting ready

For this recipe, we'll use a line shapefile with two features. You can download the shapefile as a .zip file from https://github.com/GeospatialPython/Learn/raw/master/paths.zip.

Unzip the shapefile into a directory named qgis_data/shapes within your root or home directory.

How to do it...

The steps for this recipe are fairly straightforward. We'll extract the geometry from the first line feature and pass it to the measurement object, as shown here:

  1. First, we must load the QGIS constants library:

            from qgis.core import QGis

  2. Load the line layer:

            lyr = QgsVectorLayer("/qgis_data/shapes/paths.shp", "Route", "ogr")

  3. Grab the features:

            fts = lyr.getFeatures()

  4. Get the first feature:

            route = fts.next()

  5. Create the measurement object instance:

            d = QgsDistanceArea()

  6. Then, we must configure the QgsDistanceArea object to...

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Key benefits

  • Delve into the undocumented features of the QGIS API
  • Get a set of user-friendly recipes that can automate entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes
  • This book has a complete code upgrade to QGIS 2.18 and 30 new, valuable recipes

Description

QGIS is a desktop geographic information system that facilitates data viewing, editing, and analysis. Paired with the most efficient scripting language—Python, we can write effective scripts that extend the core functionality of QGIS. Based on version QGIS 2.18, this book will teach you how to write Python code that works with spatial data to automate geoprocessing tasks in QGIS. It will cover topics such as querying and editing vector data and using raster data. You will also learn to create, edit, and optimize a vector layer for faster queries, reproject a vector layer, reduce the number of vertices in a vector layer without losing critical data, and convert a raster to a vector. Following this, you will work through recipes that will help you compose static maps, create heavily customized maps, and add specialized labels and annotations. As well as this, we’ll also share a few tips and tricks based on different aspects of QGIS.

Who is this book for?

This book is for geospatial analysts who want to learn more about automating everyday GIS tasks as well as programmers responsible for building GIS applications. The short, reusable recipes make concepts easy to understand and combine so you can build larger applications that are easy to maintain.

What you will learn

  • Use Python and QGIS to produce captivating GIS visualizations and build complex map layouts
  • Find out how to effectively use the poorly-documented and undocumented features of the QGIS Python API
  • Automate entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes
  • Create, import, and edit geospatial data on disk or in-memory
  • Change QGIS settings programmatically to control default behavior
  • Automatically generate PDF map books
  • Build dynamic forms for field input
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Publication date : Mar 14, 2017
Length: 464 pages
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Language : English
ISBN-13 : 9781787124837
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Concepts :
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Vendor :
QGIS Development Team
Category :
Programming
Languages :
Python
Concepts :
Geospatial Analysis
Tools :
Eclipse

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Table of Contents

9 Chapters
1. Automating QGIS Chevron down icon Chevron up icon
1. Automating QGIS
Introduction
Installing QGIS 2.18 for development
Using the QGIS Python console for interactive control
Automatically starting the Python console
Using the Python's Script Runner plugin
Setting up your QGIS IDE
Debugging QGIS Python scripts
Navigating the PyQGIS API
Creating a traditional QGIS plugin
Creating a Processing Toolbox plugin
Distributing a plugin
Building a standalone application
Storing and reading global preferences
Storing and reading project preferences
Accessing the script path from within your script
2. Querying Vector Data Chevron down icon Chevron up icon
2. Querying Vector Data
Introduction
Loading a vector layer from a file sample
Loading a vector layer from a geodatabase
Examining vector layer features
Examining vector layer attributes
Filtering a layer by geometry
Filtering a layer by attributes
Buffering a feature
Measuring the distance between two points
Measuring distance along a line
Calculating the area of a polygon
Creating a spatial index
Calculating the bearing of a line
Loading data from a spreadsheet
Accessing layer metadata
3. Editing Vector Data Chevron down icon Chevron up icon
3. Editing Vector Data
Introduction
Creating a vector layer in memory
Adding a point feature to a vector layer
Adding a line feature to a vector layer
Adding a polygon feature to a vector layer
Adding a set of attributes to a vector layer
Adding a field to a vector layer
Joining a shapefile attribute table to a CSV file
Changing vector layer geometry
Changing a vector layer feature's attribute
Removing data from a vector layer
Deleting a vector layer feature's attribute
Reprojecting a vector layer
Converting a shapefile to KML or GeoJSON
Merging shapefiles
Splitting a shapefile
Generalizing a vector layer
Dissolving vector features
Performing a union on vector shapes
Rasterizing a vector layer
Exporting a layer to the GeoPackage format
4. Using Raster Data Chevron down icon Chevron up icon
4. Using Raster Data
Introduction
Loading a raster layer
Loading a NetCDF file
Getting the cell size of a raster layer
Obtaining the width and height of a raster
Counting raster bands
Swapping raster bands
Querying the value of a raster at a specified point
Reprojecting a raster
Creating an elevation hillshade
Creating vector contours from elevation data
Sampling a raster dataset using a regular grid
Adding elevation data to a line vertices using a digital elevation model
Creating a common extent for rasters
Resampling raster resolution
Counting the unique values in a raster
Mosaicing rasters
Converting a TIFF image to a JPEG image
Creating pyramids for a raster
Converting a pixel location to a map coordinate
Converting a map coordinate to a pixel location
Creating a KML image overlay for a raster
Classifying a raster
Converting a raster to a vector
Georeferencing a raster from control points
Clipping a raster using a shapefile
5. Creating Dynamic Maps Chevron down icon Chevron up icon
5. Creating Dynamic Maps
Introduction
Accessing the map canvas
Changing the map units
Iterating over layers
Symbolizing a vector layer
Setting a transparent layer fill
Using a filled marker symbol
Rendering a single band raster using a color ramp algorithm
Setting a feature's color using a column in a CSV file
Creating a complex vector layer symbol
Using icons as vector layer symbols
Using an outline for font markers
Using arrow symbols
Creating a graduated vector layer symbol renderer
Creating a categorized vector layer symbol
Using live layer effects
Creating inverted polygon shapeburst fills
Creating a map bookmark
Navigating to a map bookmark
Setting scale-based visibility for a layer
Using SVG for layer symbols
Using pie charts for symbols
Using the 2.5D renderer
Using XYZ tiled map services
Using Esri ArcGIS map services
Labeling a feature
Using null symbols
Change map layer transparency
Adding standard map tools to the canvas
Using a map tool to draw points on the canvas
Using a map tool to draw polygons or lines on the canvas
Building a custom selection tool
Creating a mouse coordinate tracking tool
6. Composing Static Maps Chevron down icon Chevron up icon
6. Composing Static Maps
Introduction
Creating the simplest map renderer
Using the Map Composer
Adding labels to a map for printing
Adding a scale bar to a map
Adding a North arrow to the map
Adding a logo to the map
Adding a vertical legend to the map
Adding a horizontal legend
Adding a custom shape to the map
Adding a grid to the map
Adding a table to the map
Adding a world file to a map image
Saving a map to a project
Loading a map from a project
7. Interacting with the User Chevron down icon Chevron up icon
7. Interacting with the User
Introduction
Using log files
Creating a simple message dialog
Creating a warning dialog
Creating an error dialog
Displaying a progress bar
Creating a simple text input dialog
Creating a file input dialog
Creating a combobox
Creating radio buttons
Creating checkboxes
Creating a dock widget
Displaying a message in the status bar
Pushing messages to the message bar
Pushing widgets to the message bar
Creating tabs
Stepping the user through a wizard
Keeping dialogs on top
8. QGIS Workflows Chevron down icon Chevron up icon
8. QGIS Workflows
Introduction
Creating an NDVI
Geocoding addresses
Creating raster footprints
Performing network analysis
Routing along streets
Tracking a GPS
Creating a mapbook
Finding the least cost path
Performing nearest neighbor analysis
Creating a DEM from LIDAR
Creating a heat map
Creating a dot density map
Collecting field data
Computing road slope using elevation data
Geolocating photos on the map
Image change detection
Adjusting imprecise building footprints
Visualizing multitemporal data
9. Other Tips and Tricks Chevron down icon Chevron up icon
9. Other Tips and Tricks
Introduction
Creating tiles from a QGIS map
Adding a layer to geojson.io
Rendering map layers based on rules
Creating a layer-definition file
Using NULL values in PyQGIS
Using generators for layer queries
Using alpha values to show data density
Using the __geo_interface__ protocol
Getting the output file names from processing algorithms
Generating points along a line
Using expression-based labels
Creating dynamic forms in QGIS
Calculating length for all selected lines
Using a different status bar CRS than the map
Creating HTML labels in QGIS
Using OpenStreetMap points of interest in QGIS
Changing the QGIS web proxy
Running QGIS scripts as scheduled tasks
Visualizing data in 3D with WebGL
Visualizing data on a globe
Make a globe-like azimuthal orthographic projection
Animating a layer

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Customer reviews

Rating distribution
Full star icon Half star icon Empty star icon Empty star icon Empty star icon 1.5
(2 Ratings)
5 star 0%
4 star 0%
3 star 0%
2 star 50%
1 star 50%
Leo Jul 30, 2017
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
The book is good, some small bugs but doesn't really affect reading and learning. However the bad thing is I find the same book on Packt website and it is only $10 with a more programmer friendly interface... I cannot even copy and test the code in kindle reader...
Amazon Verified review Amazon
宮崎 知与 Oct 02, 2021
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
バージョンが古く活用しすらいので、残念❗
Amazon Verified review Amazon

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About the author

Profile icon Joel Lawhead
Joel Lawhead
LinkedIn icon Github icon
Joel Lawhead is a PMI-certified Project Management Professional (PMP), a certified GIS Professional (GISP), and vice president of NVision Solutions, Inc., an award-winning firm specializing in geospatial technology integration and sensor engineering for NASA, FEMA, NOAA, the US Navy, and many other commercial and non-profit organizations. Joel began using Python in 1997 and started combining it with geospatial software development in 2000. He has authored multiple editions of Learning Geospatial Analysis with Python and QGIS Python Programming Cookbook, both from Packt. He is also the developer of the open source Python Shapefile Library (PyShp) and maintains a geospatial technical blog.
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What is the delivery time and cost of print books? Chevron down icon Chevron up icon

Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela