Abstract
In recent decades, it is easy to obtain remote sensing images which have been successfully applied to various applications, such as urban planning, hazard monitoring, etc. In particular, high resolution (HR) remote sensing (RS) images can better monitor our living environment from a broader spatial perspective. However, raw remote sensing images provide no labeling information to train a classifier, which usually is exploited to generate remote sensing maps. Based on our previous work, in the paper, an automatic classification system is proposed to classify high resolution urban RS images using deep neural networks, in particular, convolutional neural networks and fully convolutional networks. The labeling information is assigned on the context of both social media photos and HR remote sensing images by significantly reducing the cost of manual labeling without the necessity of remote sensing experts. The experiments carried out on high resolution remote sensing images acquired in the city Frankfurt taken by the Jilin-1 satellites confirm the effectiveness of the proposed strategy compared to the state of the art.
Original language | English |
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Title of host publication | 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings |
Place of Publication | Valencia |
Publisher | IEEE |
Pages | 7243-7246 |
Number of pages | 4 |
ISBN (Electronic) | 9781538671504 |
DOIs | |
Publication status | Published - 31 Oct 2018 |
Event | 38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018: Observing, Understanding and Forcasting the Dynamics of Our Planet - Feria Valencia Convention & Exhibition Center, Valencia, Spain Duration: 22 Jul 2018 → 27 Jul 2018 Conference number: 38 https://www.igarss2018.org/ |
Publication series
Name | International Geoscience and Remote Sensing Symposium (IGARSS) |
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Volume | 2018-July |
Conference
Conference | 38th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 |
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Abbreviated title | 2018 |
Country/Territory | Spain |
City | Valencia |
Period | 22/07/18 → 27/07/18 |
Internet address |
Keywords
- Deep neural networks
- High resolution
- Social media photos
- Urban remote sensing images
- 22/3 OA procedure