A Spatiotemporally Constrained Interpolation Method for Missing Pixel Values in the Suomi-NPP VIIRS Monthly Composite Images: Taking Shanghai as an Example
文献类型：期刊论文
| 作者 | Liu, Qingyun; Fan, Junfu1; Zuo, Jiwei; Li, Ping; Shen, Yunpeng; Ren, Zhoupeng1; Zhang, Yi2 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023-05-08 |
| 卷号 | 15期号:9页码:2480 |
| 关键词 | NPP-VIIRS time series interpolation spatiotemporally constrained interpolation time continuity constraint spatial correlation constraints accuracy comparison |
| DOI | 10.3390/rs15092480 |
| 文献子类 | Article |
| 英文摘要 | The Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS/DNB) nighttime light data is a powerful remote sensing data source. However, due to stray light pollution, there is a lack of VIIRS data in mid-high latitudes during the summer, resulting in the absence of high-precision spatiotemporal continuous datasets. In this paper, we first select nine-time series interpolation methods to interpolate the missing images. Second, we construct image pixel-level temporal continuity constraints and spatial correlation constraints and remove the pixels that do not meet the constraints, and the eliminated pixels are filled with the focal statistics tool. Finally, the accuracy of the time series interpolation method and the spatiotemporally constrained interpolation method (STCIM) proposed in this paper are evaluated from three aspects: the number of abnormal pixels (NP), the total light brightness value (TDN), and the absolute value of the difference (ADN). The results show that the images simulated by the STCIM are more accurate than the nine selected time series interpolation methods, and the image interpolation accuracy is significantly improved. Relevant research results have improved the quality of the VIIRS dataset, promoted the application research based on the VIIRS DNB long-time series night light remote sensing image, and enriched the night light remote sensing theory and method system. |
| 学科主题 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS关键词 | NIGHTTIME LIGHTS ; ECONOMIC-ACTIVITY ; TIME-SERIES ; CHINA ; URBANIZATION ; POPULATION ; DYNAMICS ; SCALES |
| 语种 | 英语 |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/193432]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Shandong Univ Technol, Sch Civil & Architectural Engn, Zibo 255000, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 3.Cent South Univ, Sch Geosci & Infophys, Changsha 410083, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Qingyun,Fan, Junfu,Zuo, Jiwei,et al. A Spatiotemporally Constrained Interpolation Method for Missing Pixel Values in the Suomi-NPP VIIRS Monthly Composite Images: Taking Shanghai as an Example[J]. REMOTE SENSING,2023,15(9):2480. |
| APA | Liu, Qingyun.,Fan, Junfu.,Zuo, Jiwei.,Li, Ping.,Shen, Yunpeng.,...&Zhang, Yi.(2023).A Spatiotemporally Constrained Interpolation Method for Missing Pixel Values in the Suomi-NPP VIIRS Monthly Composite Images: Taking Shanghai as an Example.REMOTE SENSING,15(9),2480. |
| MLA | Liu, Qingyun,et al."A Spatiotemporally Constrained Interpolation Method for Missing Pixel Values in the Suomi-NPP VIIRS Monthly Composite Images: Taking Shanghai as an Example".REMOTE SENSING 15.9(2023):2480. |
入库方式： OAI收割
来源：地理科学与资源研究所
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