How do I view data?

Learn how to navigate SlantView's Map and Image Windows to view your data

Click here to see a quick tutorial video on how to navigate the SlantView windows to view your data!

Once a Dataset is Processed, SlantView's menus and toolbars offer a variety of options for gathering the information you need.

The data viewing interface is made up of two main windows: the Map Window shown on the left of Figure 1, and the Image Window shown on the right of Figure 1. The Map Window contains most of Slantview’s user controls, including controls for downloading data, Processing data, viewing data, editing data, and saving data.

The Map Window shows the map products that are the sum of all the imagery from a given flight; the Image Window shows the high resolution image of the area in the map outlined by the white box following the cursor.

When SlantView is first opened, the Map Window is active (the thin red border denotes the active window). Scroll your cursor through the Map Window to view high resolution images in the Image Window. The active window can be changed from the Map Window to the Image Window and back by double-clicking the left mouse button or pressing the Tab key. When control is passed from the Map Window to the Image Window, you can zoom, click, and drag the high resolution image.

Figure 1: SlantView Map and Image Windows

The Map Window

The primary features of the Map Window discussed in this section are:

  • The Title Bar
  • The Menu
  • The Toolbar
  • The Map Window display

The Title Bar

The Title Bar at the very top of the Map Window displays the latitude and longitude of the cursor’s location by default (pixel and UTM coordinates can be shown as well). The Stress, Vegetation fraction, Yield, or NDVI values at the cursor's current location are shown next to the coordinates depending on which map layer is active, Item A in Figure 2.

The Menu

The Menu includes the Data, Display, Settings, Sensor, and Help tabs, Item B in Figure 2

The Toolbar

The Toolbar includes hotkeys for many common SlantView operations including opening and saving data and switching between map layers. Various map layers are available for viewing in the Map Window depending on which Processing mode was selected, and which maps were generated in the Settings menu. To switch between the layers, select a layer's icon from the toolbar. Item C in Figure 2.

The Map Window display

Basic information about the map is displayed in the upper left corner of the Map Window including the field name, the acreage of the map, the date and time the data was collected, and the area of a Custom Boundary within the map (if one has been drawn), Item D in Figure 2.

To zoom in on the Map Window, scroll with your mouse wheel when the Map Window is active, or click on the plus and minus icons in the lower left corner of the window, Item E in Figure 2.

Figure 2: Map Window controls

The Image Window

The following primary features of the Image Window are discussed in this section.

  • Viewing high resolution data layers
  • Information displayed in the Title Bar
  • Introduction to Filtering

Viewing High Resolution Data Layers

In addition to the color image that is shown in the high-resolution window by default, the same layers that are available in the Map Window are available in the Image Window. To change the layer that is displayed in the Image Window, press the number keys 0-9 on your keyboard when the Image Window is active. (1) GNDVI, (2) RNDVI, (3) ReNDVI, (4) Stress, (5) Color, (6) Raw Green – Channel 1, (7) Raw Red – Channel 2, (8) Raw Red Edge – Channel 3, (9) Raw Near Infrared – Channel 4.

Information Displayed in the Title Bar

The Title Bar at the top of the Image Window, Item A in Figure 3, displays the directory path to the data in the open Workspace. It also displays the name of the individual .tif image that is being displayed, and the data layer that is being displayed in the Image Window.

To zoom in on the image, scroll with your mouse wheel when the Image Window is active, or click the plus and minus buttons in the lower left corner, Item B in Figure 3.

Figure 3: Image Window with various viewing options

Color – Left, Stress – Middle, Green NDVI - Right

The Map Products

Example Population analysis for early stage crops

Figure 4 is an example of a Population Dataset. Three maps are available for Datasets of crops in the Population stage: Weed Detections, Population Density, and Plant Size. Click the toolbar icons boxed in red to toggle between views. The Title Bar of the Map Window displays the plant density calculated for the active image. Zooming in on the Image Window, as seen on the right of Figure 4, shows weeds (orange) between rows of plants (green).

The Weed Detection Map available in this Population dataset is not to be confused with the Weed Detection Processing type described on the Process Data page. If Weed Detection Processing was chosen for this Dataset instead of Population Processing, every plant detected would show up as a weed. Weed Detection Processing implies that the field is unplanted or the crops are pre-emergent.

Figure 4: Population analysis for early stage crops

The Plant Size map is a relative measure of plant size (the area of each plant when viewed from above) to show where plants in a field are bigger and growing more quickly, vs smaller and getting a slower start. The colorbar on the left is set such that plants in the 75th percentile are assigned a size value of 1 and a color of green. From there a size of 0.8 means those plants are 80% as large as the plants in the 75th percentile, and 1.2 would be 120% as large as the plants in the green section.

Example Stress analysis for mature crops

Figure 5 is an example of a Stress Analysis Dataset gathered from a field of mature crops. The user is able view Green Normalized Differential Vegetation Index (Green NDVI), Red NDVI, Red Edge NDVI, Vegetation fraction, Stress, and Yield Potential if all are enabled in the settings menu.

The SlantRange Stress measurement is an absolute measurement that is a ratio of the four spectral bands measured by the sensor. It is our proprietary formula for identifying stress conditions with higher sensitivity and accuracy than can be achieved from industry standard two-band NDVI measurements. Given the variety of crops that our customers measure with their SlantRange sensors, the system has to be adjustable to display a broad range of reflectivity profiles and stress conditions in an intuitive map.

For example, say the sensor measures the reflectivity profile of healthy mature corn and computes stress values between .1 and .2. In another corn field, at an earlier growth stage, in a different part of the world with different soil, the sensor measures stress values between .4 and .5. In these extreme examples, the regions of corn with stress values of .1 and .4 are the healthiest areas from their respective fields. A particular field's conditions must be considered when comparing stress between different crops in different growth stages. At the moment, there is no library of multispectral reflectance signatures for stress conditions in every variant of every crop, in every type of soil, across the world, to reference when assessing the level of stress and causes of stress, in your field. The Stress map shown in SlantView shows the range of Stress values across a field and makes it easy to isolate areas that may require immediate attention or action, but determining what the Stress values measured by the sensor actually correspond to (such as a specific pest, nutrient deficiency, disease etc.) is a question best answered by the agronomist or grower. The SlantRange system can be referred to as a "rapid scouting tool", and the agronomist and grower are still an integral part of interpreting the data.

We allow users to adjust the application of our Stress Color Scale to the actual Stress values measured by the sensor (this can cause confusion about the absolute nature of the stress measurement) to show the differences in the measured Stress values in an intuitive way. Typically, we adjust the color scale to show the least stressed areas in shades of green and the most stressed areas in shades of red. To easily compare one field to another, the user simply has to make sure that a particular shade of green corresponds to the same measured stress value in both SlantView Map Windows using the buttons next to the color scale to make incremental adjustments (e.g. setting the darkest shade of green to a stress value of .1).

Typically, we adjust the Stress Color Scale to intuitively show the least stressed areas in shades of green and the most stressed areas in shades of red. The maps in the center, and right of Figure 5 show non-intuitively adjusted color scales. In center of Figure 5, the majority of the stress data (with measured stress values of .1 to .35) is mapped across shades of green. The areas of the field with the highest stress are shown in light green, and are difficult to distinguish from the healthy areas, also shown in green. Similarly, the example on the right has a color scale with the stressed and healthy areas mapped across shades of red. The well adjusted color scale of the map on the left intuitively shows the range of stress values measured in the field, with stressed areas clearly in yellow and red, and the healthy areas in green.

Figure 5: Stress analysis for mature crops

Annotating features

Features in the map can be annotated by following the three steps below, shown in Figure 6:

  • With the Map Window active, move your cursor over the feature of interest
  • Right-click and select Annotate feature
  • Enter the annotation into the text box and click OK

When you label a feature on the map using the annotation tool, the note will appear in the Map Window,as shown on the bottom of Figure 6, The Annotations will also be exported with the KMZ map file. To remove your annotations, select Display–Annotations–Clear, or to or hide them from view on the map, deselect the Show option.

Figure 6: Annotating features

Trimming content and maps

Click here to see a quick tutorial video on how to crop your maps and create annotations!

The Trim content tool allows the user to trim maps to a Custom Boundary. This tool can be used to eliminate data outside the boundary of the field. To create and trim a map to a Custom Boundary, follow these four steps:

  • While active in the Map Window, right-click and select Custom boundary—Polygon (or click the toolbar button boxed in red in the left panel of Figure 7)
  • Left-click to select the edges of your polygon.
  • Right-click on the final point to finish the polygon.
  • Right-click in the Map Window and select Trim content–Maps only–To custom boundary (Right panel of Figure 7).

The data can be hidden from view, or eliminated from the Workspace entirely based on which Trim Content option is selected. The Trim content-Maps only tool trims the map to the Custom Boundary, but all removed imagery remains with the Workspace and can be brought back upon clicking Recalculate Maps. Trim content-Workspace trims the maps and removes all data outside the boundary from the Workspace. If content was trimmed from the Workspace, you will have to Reprocessfrom scratch to bring it back.

To draw a rectangular or circular boundary quickly, right-click and select Custom boundary—Rectangle or Circle.

Figure 7: Custom map cropping

If unsatisfied with the polygon, right click to complete the drawing then Right-clickCustom boundaryDestroy to erase and redraw.

If you are viewing your cropped map and wish to return the map to its original size (and you did not crop the Workspace), click Recalculate maps on the far right of the toolbar, or select Settings—Processing—Recalculate maps.

To trim a Workspace to a Custom Boundary: Right-click—Trim content—Workspace—To custom boundary. If you trim a Workspace to a Custom Boundary, only the data within the boundary will be included when the Workspace is saved. This can be a handy tool if two fields have been flown in a single flight and the user wants to separate them into two unique Workspaces. Recalculating the maps or reopening the saved Workspace will not bring back the cropped content. However, the data is not removed from the original folder, so Reprocessing the data set from scratch will bring back any previously removed content.

To save a field boundary, Right-click—Custom boundary—Save. You will be prompted to enter a Grower and field name. The field boundary file is saved at C:\SlantRange\field definitions\[Grower]\[Field name]. A saved field boundary will be linked to the Dataset, and will show up whenver the Dataset is Reprocessed and whenever the Workspace is Recalculated. To view your saved custom boundaries, go to C:\SlantRange\field_definitions.

SlantView also has the ability to highlight contours using the custom boundary tools.

Adjust map transparency

The transparency of the maps on top of the satellite imagery in the Map Window can be adjusted by holding the Alt key and clicking the up and down arrow keys.