气候变化领域集成服务门户(CCPortal): Enhancing Land Surface Temperature Reconstruction: An Improved Interpolation of Mean Anomalies Based on the Digital Elevation Model (DEM-IMA)

CCPortal

DOI	10.1109/JSTARS.2024.3378711
	Enhancing Land Surface Temperature Reconstruction: An Improved Interpolation of Mean Anomalies Based on the Digital Elevation Model (DEM-IMA)
	Guo, Jianhua; Wang, Shidong; Peng, Jinyan; Liu, Jinping
发表日期	2024
ISSN	1939-1404
EISSN	2151-1535
起始页码	17
卷号	17
英文摘要	Surface temperature is a key parameter in scientific studies, encompassing areas, such as resource environment, climate change, and terrestrial ecosystems. The moderate-resolution imaging spectroradiometer land surface temperature (MODIS LST) products play a critical role in research related to land surface temperature (LST). However, these products are often plagued with data loss or distortion, attributable to atmospheric conditions or technical impediments. Unfortunately, there is a shortage of fast LST reconstruction methods that consider both the temporal relationships between close images and the LST variation characteristics in complex, heterogeneous terrain. To address this, the present study proposed a novel method, the improved interpolation of the mean anomalies based on the digital elevation model (DEM-IMA), seeking to fill in missing temperature values. The model suggested in this research was evaluated by comparing it to conventional methods, such as interpolation of mean anomalies (IMA) and gap fill (GF), using a combination of simulation data and actual satellite data. The results suggest that the DEM-IMA model enhances LST reconstruction, particularly for heterogeneous landscapes. The approach effectively restored missing data, displaying a remarkable level of accuracy overall. It surpassed both the IMA and GF methods in the task of filling small, medium, and large cloud gaps in day and night LST data. It reduced the root-mean-square error by 17%, with its accuracy higher at night than during the day. The findings of this study have the potential to provide valuable technical support for enhancing the utilization of MODIS LST products and for conducting quantitative analysis and assessment of regional climate resources with greater effectiveness.
英文关键词	Land surface temperature; Surface reconstruction; MODIS; Land surface; Temperature measurement; Interpolation; Statistical analysis; Satellite images; Root mean square; Climate change; Spectroradiometers; Terrain mapping; Anomaly detection; Digital elevation model (DEM); interpolation of the mean anomalies based on the digital elevation model (DEM-IMA); land surface temperature (LST); spatial interpolation
语种	英语
WOS研究方向	Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:001197839900013
来源期刊	IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/290279
作者单位	Henan Polytechnic University; North China University of Water Resources & Electric Power; KU Leuven
推荐引用方式 GB/T 7714	Guo, Jianhua,Wang, Shidong,Peng, Jinyan,et al. Enhancing Land Surface Temperature Reconstruction: An Improved Interpolation of Mean Anomalies Based on the Digital Elevation Model (DEM-IMA)[J],2024,17.
APA	Guo, Jianhua,Wang, Shidong,Peng, Jinyan,&Liu, Jinping.(2024).Enhancing Land Surface Temperature Reconstruction: An Improved Interpolation of Mean Anomalies Based on the Digital Elevation Model (DEM-IMA).IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,17.
MLA	Guo, Jianhua,et al."Enhancing Land Surface Temperature Reconstruction: An Improved Interpolation of Mean Anomalies Based on the Digital Elevation Model (DEM-IMA)".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 17(2024).