4.1 The following information on the Klei Dam at Q (block G8) on the topographic map is provided: Location: 34°21'45"S 19°12'45"E Depth: 10 m 4.1.1 Is the Klei Dam at Q in block G8 a point, line or polygon feature? Answer: 4.1.2 State whether the following are spatial data or attribute data - NSC Geography - Question 4 - 2021 - Paper 2

The depth of the Klei Dam at Q is an example of attribute data, as it provides specific characteristics or information about the dam.

The location of the Klei Dam at Q is considered spatial data, as it pertains to the geographical positioning of the dam on the map.

Determining the depth of the Klei Dam is crucial for various reasons:

1. Water Holding Capacity: A deeper dam can retain more water, which is vital for irrigation, especially during dry seasons.

2. Risk Management: Knowing the depth aids in flood prevention strategies, allowing farmers to take precautionary measures when necessary.

3. Evaporation Rates: Shallow water bodies tend to experience higher evaporation rates, resulting in less water availability for farming practices. Thus, the depth can directly influence agricultural productivity.

A data layer is a representation of a specific theme or geographic feature on a map. It can include various types of data, such as topography, demographics, and infrastructure, each providing distinct information relevant to analysis.

The omitted data layer from the insert is related to infrastructure, particularly transport routes. This layer is critical for understanding connectivity and accessing resources.

The infrastructure data layer plays a significant role in economic development for several reasons:

1. Transportation: It aids in the movement of agricultural products from farms to markets, enhancing sales opportunities for farmers.

2. Accessibility to Services: Improved transport routes allow farmers to access necessary agricultural services, such as equipment, seeds, and fertilizers, efficiently.

3. Tourism Potential: Well-developed transport infrastructure can attract tourists to the area, providing additional income sources for the farming community.

A GIS specialist would utilize data querying techniques to assess water quality by:

1. Activity Mapping: Mapping human activities that may impact water quality, such as industrial runoff or agricultural practices.

2. Data Analysis: Collecting and analyzing water quality data to identify contaminants and changes over time.

3. Correlational Studies: Examining the relationship between land use and water quality metrics to determine sources of pollution.

4. Recommendation Formulation: Providing suggestions for pollution mitigation based on data outcomes, ultimately leading to better water management practices.