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Proceedings Paper

Rain use efficiency changes and its effects on land surface phenology in the Songnen Plain, Northeast China
Author(s): Fang Huang; Ping Wang; Shuai Chang; Bo Li
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Paper Abstract

Rain-use efficiency (RUE) acts as a typical indicator of ecosystem function. Land surface phenology (LSP) assesses the vegetation activity during the growing season at the ecosystem level. The Songnen Plain (SNP) is located in semi-humid to semi-arid transition ecological fragile zone in Northeast China. RUE in growing season (May-September) was calculated using time series GIMMS NDVI3g images and precipitation data for the period of 1983-2012. The phenology metrics including the start (SOS) and end (EOS) dates of growing season for each year was extracted. Spatial trends of RUE and LSP were examined by applying a linear regression model with time. The correlation analysis was used to analyze the effects of RUE on LSP. The results showed that RUE increased slightly with an undulating trend. Spatially, the highest positive slopes indicating increased trend of RUE were observed in northern and eastern forest. The advanced in SOS was mainly distributed in northern forest areas. 12.2% of the landscape experienced highly increase trend in EOS with a rate of 0.38 days per year. The length of growing season (LOS) was prolonged in 14.2% of the total land. EOS dates in the southern salinized grassland and cropland were mainly negatively correlated with RUE. The results of the significance test show that 2.95% of the pixels were significantly and positively correlated with RUE, indicating that an increase in the RUE would delay the EOS. Increasing RUE promoted the extension of the LOS, particularly in the forest areas.

Paper Details

Date Published: 10 October 2018
PDF: 9 pages
Proc. SPIE 10783, Remote Sensing for Agriculture, Ecosystems, and Hydrology XX, 107830E (10 October 2018); doi: 10.1117/12.2325086
Show Author Affiliations
Fang Huang, Northeast Normal Univ. (China)
Ping Wang, Northeast Normal Univ. (China)
Shuai Chang, Northeast Normal Univ. (China)
Bo Li, Northeast Normal Univ. (China)

Published in SPIE Proceedings Vol. 10783:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XX
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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