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Pipeline Detection with Satellite Images Using Machine Learning

Dasenbrock, Jan (2020) Pipeline Detection with Satellite Images Using Machine Learning. Master's, Carl von Ossietky Universität Oldenburg.

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Abstract

This thesis has been written in the framework of the SciGRID_gas project, which has the goal of creating an open-source network model for the European gas transport network. For the creation of the model, public data sources such as OpenStreetMap or press articles are currently used. These conventional data sources tend to be inaccurate or incomplete. For the correction of these inaccuracies and incompleteness, satellite images could play an important role. The aim of this thesis is to prove that a pipeline dataset can be automatically generated from satellite images using machine learning methods. For this, a deep learning 1model is trained to recognize pipeline courses on satellite images. Training data will first be generated using gas network data from Great Britain. Open-access satellite data will be used which is easily accessible, of adequate resolution, and is well documented. A suitable model will be trained with these data. The trained model will then be tested with satellite images from Northern Germany. The results will be evaluated and a possible future large-scale application of the model to the whole European area will be discussed.

Item URL in elib:https://elib.dlr.de/137734/
Document Type:Thesis (Master's)
Title:Pipeline Detection with Satellite Images Using Machine Learning
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Dasenbrock, Janjan.dasenbrock (at) gmail.comUNSPECIFIED
Date:4 November 2020
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Number of Pages:85
Status:Published
Keywords:SciGRID_gas, Machine Learning, Remote Sensing, Pipelines, Gas Transport Netz
Institution:Carl von Ossietky Universität Oldenburg
Department:Physik
HGF - Research field:Energy
HGF - Program:Technology, Innovation and Society
HGF - Program Themes:Renewable Energy and Material Resources for Sustainable Futures - Integrating at Different Scales
DLR - Research area:Energy
DLR - Program:E SY - Energy Systems Analysis
DLR - Research theme (Project):E - Energy Systems Technology (old)
Location: Oldenburg
Institutes and Institutions:Institute of Networked Energy Systems > Energy Systems Analysis, OL
Deposited By: Pluta, Adam
Deposited On:03 Dec 2020 11:39
Last Modified:26 Feb 2021 08:42

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