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Document type:
Misc
Author(s):
Liebel, Lukas
Title:
Deep Convolutional Neural Networks for Semantic Segmentation of Multispectral Sentinel-2 Satellite Imagery: An Open Data Approach to Large-Scale Land Use and Land Cover Classification
Abstract:
In this thesis, the applicability of deep convolutional neural network s (CNNs) for large-scale land use and land cover (LULC) classification is evaluated. A state-of-the-art image recognition CNN architecture was adapted and re-trained from scratch using a novel dataset. LULC classification is a common task in remote sensing. Large-scale LULC maps are mainly used for scientific analyses and serve as a basis for decision making by governments and non-governmental organizations (NGOs). Several pr...    »
Keywords:
lulc
Month:
Jul
Year:
2017
TUM-Einrichtung:
Lehrstuhl für Methodik der Fernerkundung
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