Tree species diversity is a key parameter to describe forest ecosystems. It is, for example, important for issues such as wildlife habitat modeling and close-to-nature forest management. 

http://www.mdpi.com/2072-4292/4/9/2661

A combination of spectral and structural information is a promising basis for tree species identification. A hyperspectral sensor in conjunction with a lidar scanner can deliver these data state of the art.

In the context of the previous answer you might have a look at the following article dealing with the use of low cost drone imagery and photogrammetrie for forest characterization:

http://www.sciencedirect.com/science/article/pii/S0034425713001326

(open access article)

Thanks Florian your answer is helpful

Due to the high diversity, it is very difficult to solve this problem, because, we should take plots of these forests and use them as a single identity or land use. For forests the use of bands is normal: blue, green and infrared.

You can try using laser scanning data such as the TLS and ALS i.e terrestrial laser scanner and airborne laser scanner. They are mostly point cloud data which after the data collection one can further process and filter it to remove the noise and unwanted objects.

Airborne hyperspectral sensing is the best for tropical forest individual species identification based on my research experiences