A master thesis from Aalborg University
An exploration of automatic detection of large-scale solar plants: application of machine learning-based image classification in Google Earth Engine
Author(s)
Term
4. term
Publication year
2019
Submitted on
2019-06-07
Pages
56 pages
Abstract
This thesis contains a study of automatic detection of large-scale solar plants from satellite imagery (Sentinel-1 and Sentinel-2) using geospatial cloud-based platform – Google Earth Engine. The thesis investigates to what extent and with what accuracy is possible to detect large-scale solar plants using specific remote sensing data. The study is connected with the existing research and approach and tries to provide a more accessible way using available processing tools. The approach and process are commented using coding samples, workflow scheme, and the results are compared using different machine learning classifiers. The analysis is conducted using Denmark as a study area with known ground-truth data, but the approach is ultimately transferred for detecting large-scale solar plants in the selected Germany state.
Keywords
Documents
Colophon: This page is part of the AAU Student Projects portal, which is run by Aalborg University. Here, you can find and download publicly available bachelor's theses and master's projects from across the university dating from 2008 onwards. Student projects from before 2008 are available in printed form at Aalborg University Library.
If you have any questions about AAU Student Projects or the research registration, dissemination and analysis at Aalborg University, please feel free to contact the VBN team. You can also find more information in the AAU Student Projects FAQs.