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A Synergetic Algorithm for Mid-Morning Land Surface Soil and Vegetation Temperatures Estimation Using MSG-SEVIRI Products and TERRA-MODIS Products
Zhao, Wei1,2; Li, Ainong1; Bian, Jinhu1; Jin, Huaan1; Zhang, Zhengjian1
Corresponding AuthorAinong Li
2014
Source PublicationREMOTE SENSING
EISSN2072-4292
Volume6Issue:3Pages:2213-2238
SubtypeArticle
AbstractLand surface is normally considered as a mixture of soil and vegetation. Many applications, such as drought monitoring and crop-yield estimation, benefit from accurate retrieval of both soil and vegetation temperatures through satellite observation. A preliminary study has been conducted in this study on the estimation of land surface soil and vegetation component temperature using the geostationary satellite data acquired by Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) and TERRA-MODIS data. A synergetic algorithm is proposed to derive soil and vegetation temperatures by using the temporal and spatial information in SEVIRI and MODIS products. The approach is applied to both simulation data and satellite data. For simulation data, the component temperatures are well estimated with root mean squared error (RMSE) close to 0 K. For satellite data application, reasonable spatial distributions of the soil and vegetation temperatures are derived for eight cloud-free days in the Iberian Peninsula from June to August 2009. An evaluation is performed for the estimated vegetation temperature against the near surface air temperature. The correlation analysis between two datasets is found that the R-squareds are from 0.074 to 0.423 and RMSEs are within 4 K. Considering the impact of fraction of vegetation cover (FVC) on the validation, the pixels with FVC less than 30% are excluded in the total data comparison, and an obvious improvement is achieved with R-squared from 0.231 to 0.417 and RMSE from 2.9 K to 2.58 K. The validation indicates that the proposed algorithm is able to provide reasonable estimations of soil and vegetation temperatures. It is a potential way to map soil and vegetation temperature for large areas.
KeywordModis Component Temperature Seviri
Subject Area摄影测量与遥感技术
WOS HeadingsScience & Technology ; Technology
DOI10.3390/rs6032213
WOS Subject ExtendedRemote Sensing
Indexed BySCI
WOS KeywordSPLIT-WINDOW ALGORITHM ; THERMAL INFRARED RADIANCE ; REMOTELY-SENSED DATA ; URBAN HEAT ISLANDS ; COMPONENT TEMPERATURES ; AIR-TEMPERATURE ; REGIONAL EVAPOTRANSPIRATION ; EMISSIVITY RETRIEVAL ; MSG1-SEVIRI DATA ; WATER CONTENT
Language英语
Quartile2区
TOP
WOS SubjectRemote Sensing
WOS IDWOS:000334797000023
Funding OrganizationChinese Academy of Sciences(KZZD-EW-08-01 ; National natural science foundation(41271433) ; BIC ; Youth foundation of IMHE ; KZZD-EW-TZ-06 ; GJHZ201320)
Citation statistics
Cited Times:8[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/6875
Collection数字山地与遥感应用中心
Affiliation1.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, 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
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
Zhao, Wei,Li, Ainong,Bian, Jinhu,et al. A Synergetic Algorithm for Mid-Morning Land Surface Soil and Vegetation Temperatures Estimation Using MSG-SEVIRI Products and TERRA-MODIS Products[J]. REMOTE SENSING,2014,6(3):2213-2238.
APA Zhao, Wei,Li, Ainong,Bian, Jinhu,Jin, Huaan,&Zhang, Zhengjian.(2014).A Synergetic Algorithm for Mid-Morning Land Surface Soil and Vegetation Temperatures Estimation Using MSG-SEVIRI Products and TERRA-MODIS Products.REMOTE SENSING,6(3),2213-2238.
MLA Zhao, Wei,et al."A Synergetic Algorithm for Mid-Morning Land Surface Soil and Vegetation Temperatures Estimation Using MSG-SEVIRI Products and TERRA-MODIS Products".REMOTE SENSING 6.3(2014):2213-2238.
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