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Learning how to acquire high-quality spatial data from open-source repositories and manage attribute tables effectively.
What if you could combine a global health database with a local street map in seconds to predict the next disease outbreak?
In advanced GIS, we rarely create all our data from scratch. Instead, we rely on Open Data Portals—publicly accessible repositories provided by governments and NGOs. High-quality data usually comes in formats like Shapefiles (.shp), GeoJSON, or KML. When sourcing data, you must evaluate its Metadata, which is the 'data about the data.' Metadata tells you the scale, the date of collection, and the coordinate system used. Reliable sources include the United Nations Environment Programme (UNEP), World Bank Open Data, and local municipal portals. Always check for the Temporal Resolution (how recent the data is) to ensure your analysis of sustainable development is current and accurate.
Quick Check
Why is checking the 'Metadata' of a sourced dataset critical before starting an analysis?
Answer
Metadata provides essential context such as the data's age, source, and coordinate system, ensuring the data is fit for the specific purpose of the study.
Often, the spatial data (the map) and the attribute data (the statistics) live in separate files. To connect them, we use a Table Join. This process links two tables based on a common field called a Primary Key. For a join to work, the values in the key field must match exactly. We distinguish between Joins and Relates based on Cardinality. A Join is best for One-to-One () or Many-to-One () relationships, where each map feature matches one row of data. A Relate is used for One-to-Many () or Many-to-Many () relationships, where one map feature might link to multiple records, such as one city having multiple annual rainfall records.
1. You have a Shapefile of South African provinces. The attribute table has a column 'Prov_ID'. 2. You have an Excel sheet with population data and a column 'P_Code'. 3. You identify that 'Prov_ID' and 'P_Code' contain the same unique identifiers (e.g., 'GP' for Gauteng). 4. You perform a Join using these keys. Now, your map can be symbolized to show population density across provinces.
Quick Check
If you have one forest plot that contains fifty different species of trees, should you use a Join or a Relate?
Answer
A Relate, because it is a One-to-Many () relationship.
Raw data is often 'dirty.' It may contain Null values, inconsistent naming (e.g., 'New York' vs 'NY'), or incorrect Data Types. In GIS, data types are strict: a String (text) cannot be used for mathematical calculations, while an Integer or Float (decimal) can. Before joining, you must ensure the Primary Keys in both tables have the exact same data type. For example, if your map ID is a String '01' and your table ID is an Integer '1', the join will fail. Cleaning involves removing duplicates, standardizing text, and ensuring no leading or trailing spaces exist in your key fields.
1. Open your CSV in a spreadsheet editor. 2. Check the 'Income' column. If it contains '' and ',' so the GIS reads it as a Float rather than a String. 3. Standardize the 'City_Name' column to UPPERCASE to avoid 'London' not matching 'london'. 4. Save the file as a CSV (Comma Separated Values) to ensure maximum compatibility across different GIS software platforms.
Imagine you have a layer of 'Pollution Sensors' (points) and a layer of 'City Neighborhoods' (polygons). The sensors do not have a 'Neighborhood_ID' in their table. 1. You must perform a Spatial Join. 2. The GIS calculates which neighborhood polygon each sensor point falls inside. 3. The software then appends the neighborhood's attributes to the sensor's data based on their physical location ( coordinates). 4. This allows you to calculate the average pollution level per neighborhood even though the original data tables had no common key.
Which data type is required if you want to perform a calculation, such as finding the average crop yield?
What is the result of a join if the Primary Key in Table A is '101' (String) and in Table B is 101 (Integer)?
A 'Spatial Join' uses geographic location instead of a common attribute field to link two datasets.
Review Tomorrow
In 24 hours, try to recall the difference between a Join and a Relate, and why data types matter for Primary Keys.
Practice Activity
Find a local government open data portal and download one Shapefile and one CSV. Try to identify a common field that could serve as a Primary Key.