Comparison of model-based above ground biomass predictions from LiDAR
Nikolaeva, Ekaterina (2014)
Diplomityö
Nikolaeva, Ekaterina
2014
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2014052025930
https://urn.fi/URN:NBN:fi-fe2014052025930
Tiivistelmä
In order to reduce greenhouse emissions from forest degradation and deforestation the international programme REDD (Reducing Emissions from Deforestation and forest Degradation) was established in 2005 by the United Nations Framework Convention on Climate Change (UNFCCC). This programme is aimed to financially reward to developing countries for any emissions reductions.
Under this programm the project of setting up the payment system in Nepal was established. This project is aimed to engage local communities in forest monitoring.
The major objective of this thesis is to compare and verify data obtained from di erect
sources - remotely sensed data, namely LiDAR and field sample measurements made by two groups of researchers using two regression models - Sparse Bayesian Regression and Bayesian Regression with Orthogonal Variables.
Under this programm the project of setting up the payment system in Nepal was established. This project is aimed to engage local communities in forest monitoring.
The major objective of this thesis is to compare and verify data obtained from di erect
sources - remotely sensed data, namely LiDAR and field sample measurements made by two groups of researchers using two regression models - Sparse Bayesian Regression and Bayesian Regression with Orthogonal Variables.