Bayesian classification of forest ecological type from satellite data
Sharma, Sapna S. (2007)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe20071948
https://urn.fi/URN:NBN:fi-fe20071948
Tiivistelmä
The main objective of this study was todo a statistical analysis of ecological type from
optical satellite data, using Tipping's sparse Bayesian algorithm. This thesis uses "the
Relevence Vector Machine" algorithm in ecological classification betweenforestland and
wetland. Further this bi-classification technique was used to do classification of many
other different species of trees and produces hierarchical classification of entire subclasses
given as a target class.
Also, we carried out an attempt to use airborne image of same forest area. Combining it
with image analysis, using different image processing operation, we tried to extract good
features and later used them to perform classification of forestland and wetland.
optical satellite data, using Tipping's sparse Bayesian algorithm. This thesis uses "the
Relevence Vector Machine" algorithm in ecological classification betweenforestland and
wetland. Further this bi-classification technique was used to do classification of many
other different species of trees and produces hierarchical classification of entire subclasses
given as a target class.
Also, we carried out an attempt to use airborne image of same forest area. Combining it
with image analysis, using different image processing operation, we tried to extract good
features and later used them to perform classification of forestland and wetland.