Welcome to the “Trend Analysis” feature of LTPP InfoPave! This feature allows you to visually analyze data using different types of dynamically generated graphs and charts. With just a few clicks through this tour, you’ll be prepared to analyze LTPP Data using “Trend Analysis.”

Under the “Find Sections” panel on the left hand side of your screen,there are a number of filters that can assist you in narrowing down your search for LTPP sections. These filters include general information, structure, climate, traffic, and performance.

If you point your mouse over each filter, you will see a description that explains how each filter works. For example, you can filter to find sections that are more than 25 years old using the Age filter.

In the “Find Sections” panel bar, you will see different options under filter menu. If you filter your search criteria using “Find Sections,” you can save your filters by clicking on the “Save Filters” option in the “Filter Menu”. When you click on the “Save Filters” menu option, a new window will appear asking you to name your set of filters.

You can then open the saved filters by clicking on the “Open Filters” option in the “Filter Menu.” When you open a saved set of filters, InfoPave will automatically apply your saved filters.

Each data type available for analysis in this feature is assigned to one of four classifications: climate, performance, structure and traffic. Once a data classification is selected, the data type options are populated accordingly. Select a data classification and data type using the corresponding drop-down boxes.

The first visual analysis tool is “Bar Charts.” The bar chart divides each attribute into data ranges. Each bar represents the number of sections that fall within each data range. For Structure, Traffic and Performance data attributes, the latest available data from each test section is used to create these charts. But for Climate data attributes, average of all the available data for each test section is used.

In order to generate a bar chart, drag an attribute from the available attributes list to the data attribute window. If you hover your mouse pointer over a bar, the corresponding number of selected sections will be displayed.

The second visual analysis tool is “Scatter Plots.” The scatter plot compares two different attributes selected by the user. Only data corresponding to the selected sections will be plotted.

To generate a scatter plot, drag an attribute from the available attributes list to each of the x-axis and y-axis windows. InfoPave then plots a point for each instance that both data attributes are available for the selected sections. The legend above the scatter plot identifies the color of the points representing each test section. Click on the arrows to the right of the legend to scroll through the various colors. If you hover your mouse pointer over a point in the scatter plot, the corresponding test section and attribute values will be displayed.

You can change the number of sections that are plotted at a given time using the drop-down box below the scatter plot. If there are more selected sections than the number of sections displayed in the plot, change the view using the navigation arrows.

The third visual analysis tool is “Time Series.” The time series plot shows how a selected data attribute varies with time. Only data corresponding to the selected sections will be plotted.

To generate a time series plot, drag an attribute from the available attributes list to the data attribute window. InfoPave then plots every available data point for the selected data attribute and test sections. The legend above the time series plot identifies the color of the points representing to each test section. Click on the arrows to the right of the legend to scroll through the various colors. If you hover your mouse pointer over a point in the time series plot, the corresponding test section and attribute values will be displayed.

You can change the number of sections that are plotted at a given time using the drop-down box below the time series plot. If there are more selected sections than the number of sections displayed in the plot, change the view using the navigation arrows.