Color Detection for Danger factor Conversion

To reduce the risk of wildfires, we have to determine the risk. In order to do this, we created a parameter named "Danger Factor". On a scale from 0 to 10, we evaluate how dangerous the area is by the color of vegetations. The more greenish the area is, the lower the danger factor will be, vice versa.

With the help of the internet, I made a python code that's able to determine the risk factor on pixels I double-clicked on. Basically, it works as follows:

1. Get RGB data of pixel

2. Match closest color in the danger factor database

3. Return the danger factor value

The results are shown below:

Some improvements required in the future:

1. The danger factor database can be more precise, even introducing real-life experiments to refine the conversion.

2. Can determine grids by looking at a satellite image

3. Able to convert the danger factor of whole grid (average of every pixel's RGB value)

4. Refine method of determining danger factor.

5. With the help of 1. introduce danger factor with decimal digits.

6. Dry Grass~Land

References:

https://data-flair.training/blogs/project-in-python-colour-detection/