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1. DESCRIBE THE SKILLS REQUIRED TO BE A GIS ANALYST

To be a GIS analyst, there are skills that are needed in them to be one. First, a GIS analyst needs to have a strong knowledge of GIS applications. This is because with the proper knowledge of the applications, it will boost their work on analyzing something while using those applications. Next, a GIS analyst should have an understanding of the data. This includes how the data is collected and organized and how a problem of the data can be solved. A GIS analyst should also have outstanding skills in visualizing and imaging the outcome of a problem. They should be able to visualize the data use, method use and even the types of maps need to be used to solve a problem.

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2. EXPLAIN THE IMPORTANCE OF SPATIAL ANALYSIS IN REAL WORLD     MODELLING

Spatial analysis is important because it allows us to solve complex location-oriented problems and gain a deeper understanding of where and what is happening in your world. It enables us to research the properties of various locations and their connections. For example, spatial analysis can be used to determine the location of resources, such as schools and hospitals. Real-world modelling relies on spatial analysis for a better understanding of the spatial relationships and patterns between different features and objects.

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- Scheme Of Work
- Study Calendar
- Assignments/Project/Test

Spatial Analysis, Geospatial Data Models And Data Query

GIS Project:
1. Data Acquisition
2. Data Processing
3. Result Analysis
4. Outcome

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3. WHY GIS IS ESSENTIAL TO HELP ON DECISION MAKING ON CLIMATE CHANGE FORECASTING.

GIS is essential for helping decision making on climate changes because it can helps us to predict the outcome of the situation. For example, when flood is happening, data such as rainfall data, population data and elevation data are essential for GIS to predict the outcome of area affected by flood. GIS can process raw data and convert it into valuable information. GIS can also be used to identify and explore the patterns, trends, and relationships in environmental data. This can assist us to make a better decision on climate change and be well prepared.