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Analysis of relationships between NDVI and land surface temperature in coastal area
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Paper Abstract

Using Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager and Thermal Infrared Sensor imagery of the Yellow River Delta, this study analyzed the relationships between NDVI and LST (land surface temperature). Six Landsat images comprising two time series were used to calculate the land surface temperature and correlated vegetation indices. The Yellow River Delta area has expanded substantially because of the deposited sediment carried from upstream reaches of the river. Between 1986 and 2015, approximately 35% of the land use area of the Yellow River Delta has been transformed into salterns and aquaculture ponds. Overall, land use conversion has occurred primarily from poorly utilized land into highly utilized land. To analyze the variation of land surface temperature, a mono-window algorithm was applied to retrieve the regional land surface temperature. The results showed bilinear correlation between land surface temperature and the vegetation indices (i.e., Normalized Difference Vegetation Index, Adjusted-Normalized Vegetation Index, Soil-Adjusted Vegetation Index, and Modified Soil-Adjusted Vegetation Index). Generally, values of the vegetation indices greater than the inflection point mean the land surface temperature and the vegetation indices are correlated negatively, and vice versa. Land surface temperature in coastal areas is affected considerably by local seawater temperature and weather conditions.

Paper Details

Date Published: 1 September 2017
PDF: 7 pages
Proc. SPIE 10405, Remote Sensing and Modeling of Ecosystems for Sustainability XIV, 104050K (1 September 2017); doi: 10.1117/12.2271589
Show Author Affiliations
Jicai Ning, Yantai Institute of Coastal Zone Research (China)
Zhiqiang Gao, Yantai Institute of Coastal Zone Research (China)
Maosi Chen, USDA UV-B Monitoring and Research Program (United States)


Published in SPIE Proceedings Vol. 10405:
Remote Sensing and Modeling of Ecosystems for Sustainability XIV
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)

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