Extraction of Urban Built-Up Areas Using Nighttime Light (NTL) and Multi-Source Data: A Case Study in Dalian City, China
The rapid urban development associated with China’s reform and opening up has been the source of many urban problems. To understand these issues, it is necessary to have a deep understanding of the distribution of urban spatial structure. Taking the six districts of Dalian as an example, in this stu...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/12/2/495 |
| _version_ | 1797619912675426304 |
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| author | Xueming Li Yishan Song He Liu Xinyu Hou |
| author_facet | Xueming Li Yishan Song He Liu Xinyu Hou |
| author_sort | Xueming Li |
| collection | DOAJ |
| description | The rapid urban development associated with China’s reform and opening up has been the source of many urban problems. To understand these issues, it is necessary to have a deep understanding of the distribution of urban spatial structure. Taking the six districts of Dalian as an example, in this study, we integrated the enhanced vegetation index, points of interest, and surface temperature data into night light data. Furthermore, herein, we analyze the kernel density of the points of interest and construct three indices using image geometric mean: a human settlement index (HSI), a HSI-POI (HP) index, and a HSI-POI-LST (HPL) index. Using a support vector machine to identify the land type in Dalian’s built-up area, 1000 sampling points were created for verification. Then, the threshold boundary corresponding to the highest overall accuracy of each index and kappa coefficient was selected. The relevant conclusions are as follows: As compared with the other three types of data, the HPL index constructed in this study exhibited natural and social attributes, and the built-up area extracted using this method had the highest accuracy, a high image spatial resolution, and was able to overcome the omission issues observed when using one or two data sources. In addition, this method produces richer spatial details of the actual built-up area and provides more choices for assessing small-scale urban built-up areas in future research. |
| first_indexed | 2024-03-11T08:33:47Z |
| format | Article |
| id | doaj.art-9ac875547cfe4d72a2d7e99856e43107 |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-11T08:33:47Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-9ac875547cfe4d72a2d7e99856e431072023-11-16T21:38:06ZengMDPI AGLand2073-445X2023-02-0112249510.3390/land12020495Extraction of Urban Built-Up Areas Using Nighttime Light (NTL) and Multi-Source Data: A Case Study in Dalian City, ChinaXueming Li0Yishan Song1He Liu2Xinyu Hou3School of Geography, Liaoning Normal University, Dalian 116029, ChinaSchool of Geography, Liaoning Normal University, Dalian 116029, ChinaSchool of Geography, Liaoning Normal University, Dalian 116029, ChinaSchool of Geography, Liaoning Normal University, Dalian 116029, ChinaThe rapid urban development associated with China’s reform and opening up has been the source of many urban problems. To understand these issues, it is necessary to have a deep understanding of the distribution of urban spatial structure. Taking the six districts of Dalian as an example, in this study, we integrated the enhanced vegetation index, points of interest, and surface temperature data into night light data. Furthermore, herein, we analyze the kernel density of the points of interest and construct three indices using image geometric mean: a human settlement index (HSI), a HSI-POI (HP) index, and a HSI-POI-LST (HPL) index. Using a support vector machine to identify the land type in Dalian’s built-up area, 1000 sampling points were created for verification. Then, the threshold boundary corresponding to the highest overall accuracy of each index and kappa coefficient was selected. The relevant conclusions are as follows: As compared with the other three types of data, the HPL index constructed in this study exhibited natural and social attributes, and the built-up area extracted using this method had the highest accuracy, a high image spatial resolution, and was able to overcome the omission issues observed when using one or two data sources. In addition, this method produces richer spatial details of the actual built-up area and provides more choices for assessing small-scale urban built-up areas in future research.https://www.mdpi.com/2073-445X/12/2/495built-up area extractionPOIHSILSTDalian city |
| spellingShingle | Xueming Li Yishan Song He Liu Xinyu Hou Extraction of Urban Built-Up Areas Using Nighttime Light (NTL) and Multi-Source Data: A Case Study in Dalian City, China Land built-up area extraction POI HSI LST Dalian city |
| title | Extraction of Urban Built-Up Areas Using Nighttime Light (NTL) and Multi-Source Data: A Case Study in Dalian City, China |
| title_full | Extraction of Urban Built-Up Areas Using Nighttime Light (NTL) and Multi-Source Data: A Case Study in Dalian City, China |
| title_fullStr | Extraction of Urban Built-Up Areas Using Nighttime Light (NTL) and Multi-Source Data: A Case Study in Dalian City, China |
| title_full_unstemmed | Extraction of Urban Built-Up Areas Using Nighttime Light (NTL) and Multi-Source Data: A Case Study in Dalian City, China |
| title_short | Extraction of Urban Built-Up Areas Using Nighttime Light (NTL) and Multi-Source Data: A Case Study in Dalian City, China |
| title_sort | extraction of urban built up areas using nighttime light ntl and multi source data a case study in dalian city china |
| topic | built-up area extraction POI HSI LST Dalian city |
| url | https://www.mdpi.com/2073-445X/12/2/495 |
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