Estimation of the Surface Vapor Pressure Based on the MODIS Images
Received date: 2010-01-01
Revised date: 2010-05-01
Online published: 2010-09-25
Surface vapor pressure (SVP) is a highly significant variable for physically based ecosystem, hydrology and climate modeling without available regional spatially representative data currently. Conventional field observation SVP data is spatial discontinuous and time-consuming, so MODIS images are used to estimate the mean daily SVPin the Haihe River basin. Firstly, correlation analysis is taken and it is found that there are significant correlations between the dataset of precipitable water vapor low in MOD07 images and field observed SVP. Secondly, comparison of the models based on correlation analysis shows that second-order polynomial regression is the most suitable one for evaluating SVP in the Haihe river area. Finally, a series of MOD07 images from January to April of 2009 are used to validate the proposed second-order polynomial model. The result shows that the estimated value is close to the observed value, and their slope and R2 of 1:1 line analysis are 0.918 and 0.83, respectively. The results indicated that the proposed PWV-SVP model is effective for obtaining SVP data at a regional scale.
Key words： Haihe River; MODIS; precipitable water vapor; surface vapor pressure
HUANG Yaohuan, JIANG Dong, ZHUANG Dafang, FU Jingying . Estimation of the Surface Vapor Pressure Based on the MODIS Images[J]. PROGRESS IN GEOGRAPHY, 2010 , 29(9) : 1137 -1142 . DOI: 10.11820/dlkxjz.2010.09.017
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