Kai Yao
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Kai Yao has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Bing Tu
Institute of Optics and Electronics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
1 shared publication - Bohong Zheng
School of Architecture and Art, Central South University, Changsha 410075, China
1 shared publication - Jiawei Yang
School of Information Science and Technology, Hunan Institute of Science and Technology, Yueyang 414000, China
1 shared publication - Qianming Li
School of Information Science and Engineering, Hunan Institute of Science and Technology, Yueyang, China
1 shared publication - Wei Jiang
School of Information Science and Technology, Hunan Institute of Science and Technology, Yueyang 414000, China
1 shared publication - Yusheng Yang
School of Architecture and Art, Central South University, Changsha 410083, China
1 shared publication
Latest Publications
- Open Access
- 2 June 2020
- Published by MDPI AG in Remote Sensing
- Vol. 12 (11) , 1797
Refining Urban Built-Up Area via Multi-Source Data Fusion for the Analysis of Dongting Lake Eco-Economic Zone Spatiotemporal Expansion
Rapid urbanization has given rise to serious urban problems. It is crucial to understand the urbanization process to accurately and quickly identify boundary changes in urban built-up areas and implement planning schemes and adjustments in scientific and effective ways. This study proposes a new method to automate and refine the extraction of urban built-up areas by using Landsat and nighttime light (NTL) imagery. The urban agglomeration of Dongting Lake Ecological Economic Zone (UADLEEZ) Landsat data are mapped to NTL data using resampling, superpixel segmentation, and assigning the blank part with the Euclidean distance method. We then compared our findings with those produced via traditional threshold extraction methods. In total, 33 built-up areas of UADLEEZ boundary maps were produced between 1992 and 2018. Thus, we reached the following conclusions: (1) the urban built-up areas obtained via our proposed method are finer than those obtained via other threshold extraction methods; (2) we applied the extraction method to UADLEEZ, and analyzed the expansion of the urban agglomeration based on expansion scale, gravity center offset, and landscape pattern index, the analysis of expansion process is consistent with the actual situation; (3) the proposed method can be used to draw long-term dynamic maps of urban extents in units of years, and the results can be used to update the existing products. This study can serve as a reference for future urban planning, and provide both adjustment programs for relevant departments, and an objective basis for governmental decision-making.
- 2 June 2020
- Published by MDPI AG in Remote Sensing
- Vol. 12 (11) , 1797
Open AccessRefining Urban Built-Up Area via Multi-Source Data Fusion for the Analysis of Dongting Lake Eco-Economic Zone Spatiotemporal Expansion
Rapid urbanization has given rise to serious urban problems. It is crucial to understand the urbanization process to accurately and quickly identify boundary changes in urban built-up areas and implement planning schemes and adjustments in scientific and effective ways. This study proposes a new method to automate and refine the extraction of urban built-up areas by using Landsat and nighttime light (NTL) imagery. The urban agglomeration of Dongting Lake Ecological Economic Zone (UADLEEZ) Landsat data are mapped to NTL data using resampling, superpixel segmentation, and assigning the blank part with the Euclidean distance method. We then compared our findings with those produced via traditional threshold extraction methods. In total, 33 built-up areas of UADLEEZ boundary maps were produced between 1992 and 2018. Thus, we reached the following conclusions: (1) the urban built-up areas obtained via our proposed method are finer than those obtained via other threshold extraction methods; (2) we applied the extraction method to UADLEEZ, and analyzed the expansion of the urban agglomeration based on expansion scale, gravity center offset, and landscape pattern index, the analysis of expansion process is consistent with the actual situation; (3) the proposed method can be used to draw long-term dynamic maps of urban extents in units of years, and the results can be used to update the existing products. This study can serve as a reference for future urban planning, and provide both adjustment programs for relevant departments, and an objective basis for governmental decision-making.