This page is dedicated to explaining ways you are able to use to correlate the Latitude and Longitude information from the location tab in UFED Physical Analyzer after you have extracted the information from the device and exported the location data to Microsoft Excel file (aka xlsx) > after which you would then open the Excel file and save this file as a csv, with the standard delimiter of comma (,). (This method applies if you are using our application
Alternatively, this page would also explain how you are able to import the Excel file into other tools to make more sense of the data.
**NOTE: Using our application you would need to first save the excel file as a CSV first and then import it into this application, which would then format the data into a format that it understands and then plot the points (using the lat and long columns, if they are available) and label them.
Pro: Able to show the correlation using lines and also helps to show you which row the points was based on, and helps you to understand this user's travel route, etc better.
Downside: Need to save the Excel file as a CSV first
The V0.3 was based solely on the standard format of the CSV exported from the location tab, with all the headers and so on fixed, which may cause a problem if the imported CSV does not have exactly 20 columns.
Pro: Able to show the correlation using lines and also helps to show you which row the points was based on, and helps you to understand this user's travel route, etc better.
Downside: Need to save the Excel file as a CSV first
Fixed the logic in the codes such that the user can define the location of the header and the location after the header, this way we are able to dynamically generate the datagridview based on the number of columns available in the imported CSV.
In addition, fixed the logic error that was caused by certain address having a comma between them, e.g Ang Mo Kio Avenue 3, Singapore 523212. This makes sure that all the lat and long are accounted for.
Lastly, added numbering for each point plotted, so that you can easily refer to the table to see which event was that point for and also added coloring for columns that are without lat and long, so that you can easily see which data the points on the map was based from.
Pro: Able to show the correlation using lines and also helps to show you which row the points was based on, and helps you to understand this user's travel route, etc better. It also shows the timing at each point for easier correlation by using the table below
Downside: Need to save the Excel file as a CSV first
In addition to the fixes in V1.1, V1.2 also includes some fix to the logic, ensuring that all data (points, location number & date time) is accurately correlated.
https://drive.google.com/drive/folders/1rfKzZDcoQYdOCPt7bz3LtrrI9SXSdT48?usp=sharing
Pro: Able to show the correlation using lines and also helps to show you which row the points was based on, and helps you to understand this user's travel route, etc better.
Downside: Need to save the Excel file as a CSV first
Our app allows for the user to define the location of the header and the location after the header, this way we are able to dynamically generate the table to display based on the number of columns available in the imported CSV and this also ensures that all the lat and long are accounted for.
https://drive.google.com/drive/folders/1bB7BM97BaLpRtOS_gJZ91BFt_g3DZi4c?usp=sharing
This application is using the logic from the previously mentioned applications to format and display the contents of the CSV file, this app was created as a baseline and test for the logic.
https://drive.google.com/drive/folders/1LaogmRoV6H_jPQrHbuj7J_nFJvQrYujN?usp=sharing
The methods listed below requires you to export the location data as Excel before importing these Excel files (xlsx) file into the respective applications
Pro: Dont need to open the Excel file and then save it as a CSV, can just import the Excel file directly
Downside: Does not help you to understand anything much
Using this way you are able to get some form of Intensity/Bubble Map and it also allows you to create queries and make more sense of the location data
Like a bubble map that encompasses all the points
Pro: Dont need to open the Excel file and then save it as a CSV, can just import the Excel file directly
Downside: No linking of location points, have to manually link them.
Link to Sample: https://drive.google.com/open?id=1h9lVxt9TbrYmk-QnQ7L8KKKgu5qmF1WD&usp=sharing
Pro: Dont need to open the Excel file and then save it as a CSV, can just import the Excel file directly to GeoTime
Downside: Is a paid application, even the demo requires you to enter your contact information (and they would contact you before providing you the demo).