Machine Learning Python on ppc64le Platforms
To estimate tree count with devised area of interest
To estimate tree count with devised area of interests:
- with the devised area of interests in irregular shapes, we need to estimate the land coverage using method like Maximum likelihood estimation.
- With the land coverage of the area of interests, we need to find out the estimated map area in Rai.
- with the estimated map area in Rai, we are basing on stocking of 400 trees per Rai (for stock spacing at 2 meter x 2 meter) and 256 trees per Rai (for stock spacing at 2.5 meter x 2.5 meter) to devise the estimated tree counts for each space stocking.
To Present vegetation index image with label(web applications development)
Based on coordination we have, we need to generate landsat8 map images to devise the vegetation index analysis image on NDVI and NDWI.
From there, using image segetation method, we need to devise the area of interests.
These area of interests are multiple smaller irregular shapes, which each of them will form up a label.
In our frontend, we have a table of the list of labels. Upon clicking on each of these labels, it will show the location on each of these area of interests.