In keltoskytoi/detectATE: Detecting Alpine Treeline Ecotones - an Automated Remote Sensing Approach

Abstract

The proposed workflow in this thesis paper was developed in the framework of the Project Seminar 'Treelines of the World'. The overall objective of this project was to detect Treelines using an automated remote sensing approach. To approach this question, an overview of methodological approach to the detection of ATEs was laid down in Chapter 2 - Overview, to understand how this question has been approached so far. It was found that the fundamental step towards the automated detection of ATEs is the detection of trees.

Thus the aim of the proposed combined workflow developed in this project was to detect trees with shallow learning. An Object-based Image Analysis (OBIA) sub-workflow was developed to detect trees in LiDAR data sets and a Pixel-based Image Analysis (PBIA) to detect trees in Aerial or Satellite Imagery. If both data sets are available, then the results of the 'Classification' can be compared with the result of the 'Segmentation' based on cell-statistics.

keltoskytoi/detectATE documentation built on June 7, 2022, 11:41 p.m.