A new method for classification of built-up areas with deep learning technique

Lei Chen; Yingcheng Li; Yanli Xue; Zhongyuan Geng; Xinzhi Li; Yafeng Ren; Yanhui Wang; Dongmei Ye; Yahui Wang

doi:10.1117/12.2628638

22 April 2022 A new method for classification of built-up areas with deep learning technique

Lei Chen, Yingcheng Li, Yanli Xue, Zhongyuan Geng, Xinzhi Li, Yafeng Ren, Yanhui Wang, Dongmei Ye, Yahui Wang

Proceedings Volume 12174, International Conference on Internet of Things and Machine Learning (IoTML 2021); 121741H (2022) https://doi.org/10.1117/12.2628638
Event: International Conference on Internet of Things and Machine Learning (IoTML 2021), 2021, Shanghai, China

Abstract

The high-precision classification of built-up areas was extracted by the management departments with the development of social economy. Traditional classification methods cannot discriminate the types of built-up areas very well. The paper proposed a new method for classification of built-up areas with deep learning technique, namely VGG-DeepLab-UNet, which is based on the UNet network. The feature generation part of VGGNet was selected as the encoder of UNet and the upsampling part of DeepLab network was selected as the decoder of UNet. In this paper, Xinjiang was selected as the experimental area, and the new model was used to extract the classification information of built-up areas. The experimental results showed that VGG-Deep-UNet can be used to extract the classification information of built-up areas with high precision. Compared with the manual annotation results, it is pointed out that the classification information of built-up areas can be extracted with higher precision with deep learning technique, which can effectively reduce manual operation and improve the efficiency of extraction.

Citation Download Citation

Lei Chen, Yingcheng Li, Yanli Xue, Zhongyuan Geng, Xinzhi Li, Yafeng Ren, Yanhui Wang, Dongmei Ye, and Yahui Wang "A new method for classification of built-up areas with deep learning technique", Proc. SPIE 12174, International Conference on Internet of Things and Machine Learning (IoTML 2021), 121741H (22 April 2022); https://doi.org/10.1117/12.2628638

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KEYWORDS

Remote sensing

Convolution

RGB color model

Image classification

Statistical modeling

Vegetation

Image analysis

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