5. Visualization

This section will give an overview of the visualization of images in different forms.
The outputs provided by DroneNaksha are discussed in detailed in this section.
The output of the image processing are:
Orthomosaic images
Plant Health
DSM / DTM
Point Cloud
3D models
The details about all these are discussed in the next section.

5.1 Ortho Image

An orthomosaic is a huge, high-resolution image created by stitching together multiple smaller images known as orthophotos.
Orthomosaic map will be generated after the completion of task created in DroneNaksha. The procedure to open orthomosaic map is as follows:
  • Open the project in which the orthomosaic map is stored.
  • Open the plan from the list of plans in a project.
  • Click on the map option as indicated in the following image.
Open Map
  • The list of map will be displayed. Select the required one and click to open that map.
  • The map will open as shown in the following image.
Ortho image
At the center bottom, the user can see different options to open the map like Ortho, Plant Health, and DSM. Select one to open the desired output.
Plant Health:
Healthy plants reflect light differently than diseased plants. Plants that are in good health tend to reflect more green light than red light, which is why they appear green. Plants also emit near-infrared light, which is invisible to the naked eye but detectable by near-infrared sensors.
Plant health algorithms such as NDVI and VARI assess the proportions of light collected across different bands (red, green, blue, and occasionally near-infrared) to compute numerical values for each pixel or area in a given drone map. Maps with plant health algorithms are then colored based on those numerical values, making it easy to distinguish between healthy and unhealthy areas.

NDVI image (Normalized Difference Vegetation Index)

NDVI or greenness index is an indicator that shows the greenness, density, and health of vegetation in each pixel of a satellite image.
NDVI is a widely and commonly used remote sensing technology for identifying vegetation and assessing plant health. NDVI has been the industry standard for understanding plant health from many years. To quantify healthy plant life under a variety of situations, NDVI compares near infrared light.
Value
Indication
< 0
Inanimate / dead material such as roads, buildings, soils, or dead plants
0 to 0.33
Unhealthy plant material
0.33 to 0.66
Healthy Plant Material
> 0.66
Very Healthy Plant Material
NDVI index Value
You can see the NDVI image by clicking on the NDVI tab at the center bottom of the screen. A plant health popup will be seen.
Image after applying NDVI
The user can select any one of the algorithm provided. DroneNaksha support the following algorithms:
  • vNDVI
A genetic algorithm that is used to create a new visible index (visible NDVI; vNDVI) to calculate NDVI values from RGB cameras installed on UAVs that have not been calibrated.
  • Visible Atmospherically Resistant (VARI) Index
An index of vegetation originally developed for satellite images is called the Visual Atmospheric Resistance Index. It is minimally affected by atmospheric effects, allowing it to estimate vegetation in a wide range of environments.
VARI=((GreenRed))/((Green+RedBlue))VARI=((Green-Red))/((Green+Red-Blue) )
Image after applying VARI
  • Excess Green (EXG)
  • Triangular Greenness Index (TGI)
It uses the area of a triangle in the spectral features of the chlorophyll region. Triangular Greenness Index (TGI) is an RGB indicator for chlorophyll sensitivity.
TGI=((Green(0.39Red)(0.61Blue)))/((NormalizedtomaxvalueofRGBbands))TGI=((Green-(0.39*Red)-(0.61*Blue)))/((Normalized to max value of RGB bands))
After Applying TGI Algorithm
  • Green Leaf Index (GLI)
If the value is positive, it is either green leaves or stems; if it is negative, soil or another nonliving object.
GLI=(2GreenRedBlue)/(2Green+Red+Blue)GLI=(2Green-Red-Blue)/(2Green+Red+Blue)
After Applying GLI Algorithm

DSM Image (Digital Surface Models)

A digital surface model (DSM) is an elevation model that contains the elevation of the terrain as well as above-ground features such as buildings, vegetation, towers, and other infrastructure.
- By clicking on the DSM tab at the bottom of the screen, a small pop-up will be displayed which will show DSM & DTM tabs (as shown in the image below).
- You can see the DSM image by clicking on the DSM option.
DSM Image

DTM (Digital Terrain Model)

In some countries, a DTM is actually synonymous with a DEM. This means that a DTM is simply an elevation surface representing the bare earth referenced to a common vertical datum. In the United States and other countries, a DTM has a slightly different meaning. A DTM is a vector data set composed of regularly spaced points and natural features such as ridges and break lines. A DTM augments a DEM by including linear features of the bare-earth terrain.
By clicking on DTM tab, you can open DTM image.
DTM Image