Joint Deep Learning: A novel framework for urban land cover and land use classification

Zhang, Ce and Pan, Xin and Li, Huapeng and Zhang, Shuqing and Atkinson, Peter (2020) Joint Deep Learning: A novel framework for urban land cover and land use classification. In: GISRUK 2020, 2020-07-212020-07-23.

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Abstract

The majority of existing research on urban land cover and land use (LULC) classification from remotely sensed imagery is to differentiate at a specific level (either land cover (LC) or land use (LU)) and at a specific scale. The spatial and hierarchical relationships between LC and LU were not considered in the previous paradigm. This paper proposed Joint Deep Learning as a novel framework for urban LULC classification. Three state-of-the-art methods were compared under the framework, including JDL, SS-JDL and a newly proposed Cross GAN. Experimental results demonstrate the superiority of Cross GAN in terms of classification accuracy and robustness.

Item Type:
Contribution to Conference (Paper)
Journal or Publication Title:
GISRUK 2020
ID Code:
145896
Deposited By:
Deposited On:
13 Aug 2020 15:30
Refereed?:
Yes
Published?:
Published
Last Modified:
25 Sep 2020 06:46