Introduction to Spatial Analysis (Furqan Alim from Section U).pptx

,..

1. Group 2 (Section U) 8) Mashood Shahid Awan 9) Farhan 10) Ahmad Khan 12) Abdul Hadi 13) Muzamil 14) Furqan Alim 15) Waseem 1

2. Introduction to Spatial Analysis

3. What is Spatial Analysis Spatial analysis is the process of examining geographic data to uncover patterns, relationships, and trends. It involves using specialized software tools to analyze and manipulate spatial data, such as maps, satellite imagery, and GPS data. Spatial analysis can be used in a wide range of fields, including urban planning, environmental science, public health, and business intelligence. The goal of spatial analysis is to gain insights into the relationships between different geographic features and to identify patterns that can inform decision-making. 3

4. Spatial Analysis in QGIS QGIS is a free and open-source geographic information system that allows for spatial analysis. Spatial analysis is the process of examining geographic data to find patterns, relationships, and trends. With QGIS, you can perform spatial analysis on a variety of data types, including vector and raster data. Analysis Procedure in QGIS Data collection and preparation Spatial data visualization Spatial analysis techniques Practical Example in QGIS A practical example of spatial analysis in QGIS would be analyzing population density and transportation infrastructure in a city. This could involve collecting and preparing data on population density, roads, highways, and public transportation routes. Using spatial analysis techniques in QGIS, you could then identify areas with high population density and poor transportation access, and use this information to inform urban planning decisions.

5. Analysis Procedure in Qgis Step 1: Data Import Import the data to be analyzed into Qgis . This can be done by using the 'Add Vector Layer' button on the toolbar or by dragging and dropping the file into the Qgis window. Step 2: Data Preparation Before conducting any analysis, it is important to prepare the data. This includes cleaning and filtering the data, as well as transforming it into a format that can be used for analysis. Step 3: Analysis Once the data is prepared, the analysis can be conducted using various tools and techniques available in Qgis . This can include spatial statistics, spatial regression, and spatial clustering. PRESENTATION TITLE 5 May 21, 20XX

6. Real World Applications Spatial analysis has a wide range of applications across various industries. It can be used to analyze and visualize data in a geographic context, providing valuable insights and informing decision-making processes. Urban planning and development: Spatial analysis can be used to analyze population density, land use patterns, and transportation systems to inform urban planning and development decisions. Environmental management: Spatial analysis can be used to analyze and monitor environmental data, such as air and water quality, to inform environmental management decisions. Business and marketing: Spatial analysis can be used to analyze customer demographics, market trends, and competition in a geographic context to inform business and marketing strategies.

7. Data Collection and Preparation Data Collection The first step in spatial analysis is to collect data. This can be done through various means, including surveys, satellite imagery, and GPS data. It is important to ensure that the data collected is accurate and relevant to the analysis being conducted. Data Preparation The data has been collected, it must be prepared for analysis. This involves cleaning the data, removing any errors or inconsistencies, and organizing it into a format that can be easily analyzed. Spatial data may also need to be converted into a specific projection or coordinate system to ensure accuracy in the analysis. ​ PRESENTATION TITLE 7 May 21, 20XX

8. Spatial Data Visualization Heat Maps Heat maps are a type of data visualization that represent the density of a particular phenomenon using colors. They are particularly useful for visualizing trends and patterns in spatial data. Choropleth Maps Choropleth maps are another type of data visualization that represent data using colors. They are often used to show how a particular variable varies across different geographic regions, such as states or counties. 3D Visualization 3D visualization is a powerful tool for visualizing spatial data in three dimensions. It can be used to create realistic representations of landscapes, buildings, and other features, allowing analysts to gain a better understanding of the spatial relationships between different objects and features. 8

9. Spatial Analysis Techniques Spatial analysis involves examining the relationships between geographic features and using that information to make informed decisions. There are several techniques used in spatial analysis, including: Spatial autocorrelation: This technique examines the degree to which spatially proximate features are similar to each other. Spatial interpolation: This technique uses known values to estimate unknown values at other locations within a geographic area. Spatial regression: This technique examines the relationship between a dependent variable and one or more independent variables, taking into account spatial relationships between the variables. 9

10. Practical Example in QGIS To illustrate the power of spatial analysis in QGIS, let's consider a practical example. Suppose we want to analyze the distribution of crime incidents in a city. We can start by importing the crime data into QGIS and plotting it on a map. We can then use various spatial analysis techniques such as kernel density estimation and hot spot analysis to identify areas with high crime rates. We can also overlay other spatial data such as demographic data and land use data to gain additional insights. For example, we may find that areas with high crime rates also have a high concentration of low-income households or are located near commercial areas. 10

11. Conclusion

12. PRESENTATION TITLE 12 May 21, 20XX