1. Geospatial Development with Python

2. Writing a Program in Python
A program is a collection of Python statements, functions, etc.
A script is a list of commands which are run by a program written in a specific language such as Python
Scripts can be edited by text editors or preferably by a specialized editor that also allows the script to run
We can use Python command line in Windows
However, the use of the command line is limited (it does not support testing scripts)
So, instead we use the Python script editor (an IDE) that has a better interface than the command line mode

3. IDLE
We will also continue using the IDLE environment for Python scripting
IDLE is available with Python download
Using the interactive Python interpreter is great for writing small code
However, it is not meant to be saved!
For larger, more complex multi-line code, it is better to write it as a script (rather than using the interactive Python interpreter, e.g., IDLE)

4. Writing Script > File > New Window
This gives you a new ‘Untitled’ scripting window
There is no Python prompt in this window
Try: print (“Hello Python World”) in the window
Because the script is not interactive, nothing would happen
It needs to be run as a program (script) to do anything
So, let’s save it
> File >Save As
Save it as “hello.py” in:
C:\Python27\ArcGIS10.1\My Scripts

5. Write and Run the hello.py Script
Type: print “Hello Python World” in IDLE; save it in the directory in your Python 27 download directory
After saving the script, run it in IDLE
> Run > Run Module
We get the following window

6. Install PythonWin
For the textbook exercises you need to download PythonWin editor
Download it from:
Starting from ArcGIS 10.x you can also use Python in ArcGIS for Desktop application

7. Scripting
Scripting in ArcGIS allows you to write a program to run a sequence of tools
Python is a primary, text-based scripting language in ArcGIS
Scripts can be used as a tool, by adding them to your toolbox or as stand alone programs
Scripts can handle complex tasks, like:
Looping through and inserting between records in a database
Error handling
Allowing applications (e.g., MS Excel and R statistical package) to interoperate and communicate
Scripts can be programmed to automatically run at a specific time

8. Running an ArcGIS tool in Python
Insert the book’s DVD in your optical drive, and install it by double clicking the esri executable application.
Download data and exercises in ESRIPress

9. Geospatial Data
Information about an object located on the surface of Earth using coordinates
e.g., location of an antenna, shape of a river, outline of a stratigraphic unit
Geospatial data associate information with a specific location
e.g., salinity or temperature of water in a well
The data are defined by a series of coordinates (lat, long) in addition to other information about the attributes of the spatial object (e.g., temperature, type, elevation, …)
Data also comes with metadata, about:
datum, projection, coordinate system, units of data, date file was created, …
These geospatial data are stored in a geodatabase
e.g., data about parks, Chattahoochee River, and roads in Atlanta
We can query the geodatabase and find:
What is the area of the Piedmont Park
How many bridges are there across the Chattahoochee
How fat is GSU from the Airport

10. GIS Data Formats Raster format Vector format
Used to store bitmapped images, e.g., aerial photograph
e.g., DEM
In DEM, each pixel represents height of a point on Earth surface
Vector format
Represent spatial data with points, lines, and polygon
such as ESRI’s shapefile (e.g., Atlanta.shp) or Simple Features, which is an openGIS standard for storing point, line, and polygon, and their attributes

11. Tools
Tools such as PostGIS or ArcCatalog allow us to develop geodatabase and find answers to these questions
We can also use Web services, for example, to find the coordinate of each point, e.g., using:
And then use an application to find the distance between the two points, using Python

12. Python Libraries for Geospatial Development
There are two popular Python libraries for raster and vector data:
GDAL (Geospatial Data Abstraction Library)
Is for raster-based geospatial data; aailable for download at:
Windows user use Frank Warmerdam’s “FWTools” open source GIS binaries for Windows (32 bit); available at:
# includes gdal and ogr
OGR
Is for vector-based geospatial data and is available for download at:
NOTE: These are now merged together and are downloaded together under the common name GDAL

13. GDAL Data Model GDAL’s data model includes:
Dataset, which hold the raster data in a collection of raster bands
Raster Band: represents a band, channel, or layer within an image (e.g., RGB image has red, green, and blue components of the image)
Raster size: specifies the width of the image in pixels and overall height of the image in lines
Georeferencing transform converts from x,y coordinates into georeferenced coordinates (on the surface of Earth)
Affine transformation mathematical formula allowing operations such as X offset, Y offset, X scale, Y scale, horizontal shear, vertical shear
Coordinate system includes the projection and datum
Metadata provide additional information about the dataset

14. GDAL example Python code
Use GDAL to calculate the average of the height values contained in a DEM:
from osgeo import gdal, gdalconst
dataset = gdal.Open(”DEM.dat”)
band = dataset.GetRAsterBand(1)
fmt= “<“ + (“h” * band.XSize)
totHeight = 0
for y in range (band.Ysize):
scanline = band.ReadRaster (0, y, band.Xsize, 1, band.Xsize, 1, band.DataType)
values = struct.unpack(fmt, scanline)
for value in values:
totHeight = totHeight + value
average = totHeight / (band.xSize * band.YSize)
print “Average height = “, average

15. OGR Datasource: represents the file (e.g., a country), has many:
Layers: sets of related data, e.g., terrain, contour lines, roads layers
Spatial reference: specifies datum and projection
Attributes: additional metadata about the feature
Geometry: specifies the shape and location of the feature. Are recursive, i.e., can have sub-geometries

16. OGR example Python code
import osgeo.ogr from osgeo import ogr shapefile = ogr.Open(“TM_WORLD_BORDERS-0.3.shp”) layer = shapefile.GetLayer (0) for i in range (layer.GetFeatureCount()): feature = layer.GetFeature(i) name = feature.GetField(“NAME”) geometry = feature.GetGeometryRef() print i, name, geometry.GetGeometryName()

17. Projections We need to know which projection our data uses
Projection: deals with mapping geospatial position onto a 2D Cartesian plane with special cartographic algorithms
Also need to know the datum assumed by the data
Datum: model of the Earth shape
The good thins is that Python does the conversion of projections and datums into each other with its pyproj library. Pyproj is available at:

18. Projections A process that maps the 3D Earth into a 2D map
There are hundreds of projection algorithms, but none is perfect; all have distortions to area, shape, length, angle, etc.
We need to choose one whose distortion does not matter for our purpose
For our geo-spatial analysis (plotting or doing calculations), we need to know what type of projection was used to create the data!

19. Coordinate System Projected Coordinate System
3D Earth is projected onto the 2D Cartesian plane, and then puts points on that plane
The coordinates refer to a point on a 2D map that represent 3D Earth
Need to define an origin and map units
Unprojected Coordinate System
These directly and accurately refer to a point on the 3D Earth surface, but make it difficult to calculate distance
Latitude and longitude are examples of unprojected coor. Sys.

20. UTM Both types of coordinate systems require a reference,
For unprojected lat/long origin is at the Greenwich observatory, and zero latitude represents equator
Universal Transverse Mercator (UTM) coordinate system divides the Earth into 60 zones; each with a different map projection to minimize error
The reference point (origin) is at the intersection of the equator and the central meridian for each zone
False northing and false easting are added to the distance in m from this reference to avoid negative numbers

21. Types of Projection There are 3 main groups: Cylindrical
3D Earth (imagine it is a small, lit spherical lantern) is put inside a cylinder, and projected (2D) mathematically onto the cylinder
The cylinder is then unwrapped
Conic
The 3D Earth is projected onto a cone surface
E.g., Albers Equal-Area Projection
Azimuthal
The 3D Earth is projected directly onto a flat surface
The Earth is seen as if we look at it from space

22. pyproj Library The pyproj library includes two classes: Proj and Geod
Is a transformation class that converts lat, long to cartographic native map x,y coordinates (default is m), and vice versa
The following instantiates a Proj object:
projection = pyproj.Proj (proj=‘tmerc’, ellipse=‘WGS84’)
The transform() function converts one projection into another

23. pyproj Example Python Code
import pyproj UTM_X = # UTM coordinates UTM_Y = #Use two Proj objects to define the UTM and lat/long projections srcProj = pyproj.Proj (proj = “utm”, zone = “17”, ellips=“clrk66”, units=“m”) dstProj = pyproj.Proj (proj = ‘longlat’, ellips=‘WGS84’, datum=‘WGS84’) #transform the coordinates into latitude and longitude values long, lat = pyproj.transform (srcProj, dstProj, UTM_X, UTM_Y) print “UTM zone 17 coordinate (%0.4f, %0.4f) = %0.4f, %0.4f” % (UTM_X, UTM_Y, lat, long)

24. Geod
Performs great circle distance (between two points on Earth) and angle calculations
The fwd() function starts from a point, and given an azimuth and distance, finds the ending point and returns the back azimuth (angle from the end to the beginning point; ccw back azimuth is negative, e.g., azimuth=30, backazimuth is -150)
The inv() function takes the coordinates of two points and returns the forward and backward azimuth

25. Geod example Python Code
#given a lat, long position of a point, uses a geod object to calculate another point 10 km northeast of the first point
angle = 15 #15 degrees from N
distance = 10000
geod – pyproj.Geod(ellips=‘clrk66’)
long2, lat2, invAngle = geod.fwd(long, lat, angle, distance)
print “%o.4f, %0.4f is 10 km northeast of %0.4f, %0.4f” %(lat2, long2, lat, long)

26. Shapely Package http://trac.gispython.org/lab/wiki/Shapely
Shapely is a python library for working and analyzing 2D geospatial geometries in the Cartesian plane
import shapely.geometry
pt = shapely.geometry.point (0, 0)
circle=pt.buffer(1.0)
square= shapely.geometry.polygon ([ (0, 0), (1, 0),
(1, 1), (0, 1),
(0, 0)])
intesect = circle.intersection(square)
for x,y in instersect.exterior.coords:
print x, y

27. Example
# location of two points given by their coordinates # It is best if the locations are stored in a geodatabase Import pyproj lat1, long1 = ( , ) lat2, long2 = ( , ) geod = pyproj.Geod (ellips =“WGS84”) # WGS84 is a Datum angle1, angle2, distance = geod.inv (long1, lat1, long2, lat2) Print “Distance is %0.2f m” % distance Distance is m

28. Mapping Applications
Mapnik takes geospatial data in any format (supported by GDAL/OGR) and renders them in a map
It provides rules and symbolizers to control how objects appear on the map
Mapnik supports Python

29. Mapnik Mapnik is available from: http://mapnik.org Import mapnik
symbolizer=mapnik.PolygonSymbolizer(mapnik.color(“darkgreen”)
rule = mapnik.rule()
rule.symbols.append(symbolizer)
style = mapnik.style()
style.rules.append(rule)
layer = mapnik.Layer(“mapLayer”)
layer.datasource = mapnik.Shapefile (file=“TM_WORLD_BORDERS-0.3.shp”)
layer.style.append(“mapstyle”)
map = mapnik.Map(800, 400)
map.background = mapnik.Color(“Steelblue”)
map.append_style(“mapStyle”, style)
map.layers.append(layer)
map.zoom_all()
mapnik.render_to_file (map, “map.png”, “png”)
Mapnik is available from:

30. Work with geospatial data with Python
Before anything, download the following:
Make sure the download is for the version of the Python which is on your computer (e.g., v. 2.7) and for your machine (32 bit vs. 64 bit)
GDA/OGR
pyproj
Shapely