Geographic Information Systems Development in Python

Explore geographic information system application architecture and web-based interfaces accessed via browsers. See how HTML and JavaScript render maps from a GIS server to mobile and desktop devices.

Explore the two-part GIS architecture, detailing front-end presentation with HTML and JavaScript, back-end middleware and database logic, and how data flows through data and business logic layers.

Explore the GIS application architecture across the presentation (client-side), server-side, and database layers. Learn SQL and PL/SQL for databases, and identify essential back-end and front-end languages.

Set up the GIS development environment by installing Python 3.10, the Anaconda distribution, and GIS-specific modules like Fiona and pandas, then use conda, Anaconda prompt, and Jupyter Notebook for development.

Plan and implement a GIS workflow in Python by outlining the data flow, designing an algorithm, and transforming inputs into feature maps through code.

Explore the conditional algorithm as the computer's decision process, using flowcharts to compare two values and implement if statements in Python to determine the greater value.

Explore the loop algorithm in programming by initializing a counter, setting a termination condition, and incrementing, the three parts that prevent infinite loops.

Explore reusable functions in geographic information systems development, calling modules and APIs to process input parameters and produce outputs, without exposing inner algorithms, and assign results to an output variable.

Explore the abstract concepts of variables and data types, and see how input data becomes output information through memory storage and references in programming.

Learn how Python implicitly infers data types and how to check them with a print. Explore lists, sets, dictionaries, and booleans, including removing duplicates by converting lists to sets.

Explore Python conditional statements and indentation as you determine the value of x in if-else branches, printing results when x is less than ten or not.

Explore iteration in Python by using for loops over lists and ranges, printing values, and applying while loops with proper initialization and increments.

Explore how to extract geospatial data in Python using GeoPandas with Fiona, read GIS files or databases, convert to a pandas dataframe with geometry, and visualize maps with layered features.

Explore geospatial vector data with a focus on points defined by x and y coordinates, displayed as map markers for sampling sites, trees, and survey plots.

Examine geospatial vector lines and line strings used to define features such as rivers and roads. Build lines from connected points with x and y coordinates to model maps.

Define polygons and multipolygons as closed geospatial vector features with three or more vertices, used to outline lakes, oceans, and political boundaries on maps.

Draw points around a map to form a polygon that marks a danger area, connect the edges with lines, and close the polygon to its origin, illustrating boundary representation on maps.

Install Fiona, geo pandas, and Shibley Shibley in your Python environment to enable geospatial data types like points and polygons, then proceed with the course code described.

Read geospatial data from a GIS file or shapefile into a dataframe using read_file, exposing geometry and attributes for map layers. Save the GIS file in the same folder.

Explore geo data frame functions, including the geometry attribute display, geometry type, area calculations, and computing means for numeric columns such as population.

Filter the geo data frame by continent to display only African countries, and switch the continent value to Europe or Asia to see other regional subsets.

Create a programmatic world map from a geospatial data file using pandas and a GIS module in a Jupyter notebook, reading shapefiles and rendering a solid world map.

Filter the parent countries dataframe to Africa to create a child dataframe, then plot its map with the dataframe's plot method.

Plot filtered geospatial data to extract Europe’s geometry and create a Europe-only map with a blue background using geopandas and the plot method.

Programmatically generate a solid map of Egypt with Python and Jupyter Notebook by filtering the geo dataframe to Egypt. Adapt the geo filter for other countries.

Extract cities data from a GIS file and convert the city name column to a Python list, then print the list in a Jupyter notebook.

Extract and reverse the first geometry (a line string) from the first database record, and prepare it to add features to the map.

Create and print geometric objects using a rich Python geometry module, including points, polygons, and line strings, and demonstrate a point at (0, 0) and its type.

Create a polygon from coordinates and apply the distance method to compute the distance from the polygon to a point, yielding 1.4.

Explore spatial data relationships, focusing on within and contains, and implement these concepts in geographic information systems development in Python.

Learn how the crosses spatial relationship is used in geographic information systems with Python, and apply practical techniques for analyzing when features cross.

Explore the touches spatial relationship within geographic information systems development in Python in this course.

Explore how to identify and handle overlaps among spatial data using Python in geographic information systems development.

Learn to create geographic geometries for countries and cities in Python, and draw a line string to connect Kuwait City and Cairo on a map.

Test spatial relationships in GIS using within, contains, and intersects with real-world features like Cairo in Egypt and Kuwait, demonstrating true/false results and map line intersections.

Install GIS modules and set up the environment to create 3d maps in Python, import modules, create a map object, and display building coordinates for Egypt in a Jupyter Notebook.

Develop a multi-layer africa map by loading countries, rivers, and cities from gis data sources in a jupyter notebook, then plot and zoom to africa to visualize the features.

Use Python to annotate a map by looping over cities and placing labels at each city’s latitude and longitude, adjusting font size and offset for readability, with Casablanca as example.

Create an Africa map in Python by loading countries and cities GIS data, then plot a base map with rivers, a reverse layer, and a cities layer.

Explore building interactive maps using python in jupyter, install gis modules, import libraries, create a map object, and display layered 3d-style maps of egypt with building coordinates.

Identify and avoid behaviors that signal poor programming in interviews and the workplace, such as overreliance on others, ignoring documentation, overly complex code, and sticking to a single language.

Explore visualizing geospatial data with Microsoft Power BI by loading country population data from Excel and creating interactive maps that show year-based trends, without writing code.

Advance GIS development with Python by building a map editing app, modeling database entities with UML, saving to shape files, managing layers, locating coordinates, and displaying analysis results on map.