Urban development analysis using built-up area maps based on multiple high-resolution satellite data

International Journal of Applied Earth Observations and Geoinformation

卷:103

Xueshuang Gong¹  Haibo Wang²  Bingbing Wang³  Qiong Cao³  Chao Deng³ 

[1] China Centre for Resources Satellite Data and Application, Beijing 100864, PR China;

[2] Beijing Key Laboratory of Digital Media, School of Computer Science and Engineering, Beihang University, Beijing 100191, PR China;

关键词: Urban development;    Built-up area;    Remote sensing;    Transfer learning;   

DOI  :  

来源: DOAJ

【 摘 要 】

Analysis of built-up areas—the most significant artificial urban areas—reveals physical development processes. Unlike previous research involving medium-resolution remote sensing (RS) images, this study used built-up area maps generated from multiple high-resolution RS images with abundant built-up area edge information to analyze development in Zhengzhou. A transferable built-up area extraction (TBUAE) algorithm was developed to map the built-up area maps. The algorithm allows the developed deep learning model used on a certain satellite image to be eligible for other types of satellite images by altering the data distribution with adaptive Wallis filtering (DT-AWF). The proposed method alleviates the pressure of deep learning on the demand for new satellite image samples that are time-consuming and laborious. Additionally, the accuracy of built-up area mapping using this method exceeds 90%. Quantitative and qualitative analyses were conducted on the map results to observe the urban development of Zhengzhou from 2016 to 2020. We found that Zhengzhou has expanded rapidly since it was defined as a central city in central China in 2016. Additionally, the suburban built-up area has expanded rapidly and developed together with the central city. Further, affected by the policy, the built-up areas in different regions of Zhengzhou has changed differently, the urban edge is more simplified, and the urban internal structure is more compact.

【 授权许可】

Unknown