This study calculated the land water storage using the time-varying monthly gravity data from the GRACE (Gravity Recovery and Climate Experience) gravity satellite combined with Gaussian smoothing filter. The characteristics of spatiotemporal variations of long-term regional land water storage derived from the linear fitting method were then examined from January 2003 to December 2013. The results showed that the water storage over the huang-huai-hai plain showed an overall declining trend from 2003 to 2013 and the average declining rate is about 2.86 mm/a. The comparison between the GEACE calculation results with the soil moisture content products from the global land data assimilation system (GLDAS) showed that they are very highly consistent. The variations of regional mean soil moisture over the huang-huai-hai plain also exhibited a downward trend from 2003 to 2013 with an average declining rate about 0.74 mm/a. Based on water balance equation, we obtained the change of average groundwater storage and it showed a decreasing variability with a general declining trend with an average rate about 2.22 mm/a. In addition, the retrieved groundwater data was proven to be accurate compared to observations from groundwater wells measurement with high consistency and correlations. . Further investigations focused on analyzing the impacts of precipitation factors on groundwater variations, implying that the human influences are the main reasons for the decline in groundwater.
With the increasingly prevalent and far-reaching application of remote sensing, several algorithms have been put forward for land surface temperature retrieval. However, there is still no consensus on the calculation of land surface emissivity (LSE), which is one of the significant parameters in land surface temperature (LST) retrieval. In this paper, two methods of estimating LSE based on thematic mapper data were introduced: Van’s empirical formula method and the mixed pixels method. Based on the detailed introduction to Van’s empirical formula and the mixed pixels decomposing method in computing surface emissivity, Landsat-8 thermal infrared data and the radiative transfer equation method were used to obtain the land surface temperature in Taihu region. In this paper, atmospheric parameters are based on real-time atmospheric profile to reduce the LST error brought by the atmospheric profile. Two figures were acquired, which represented the LST of Van’s empirical formula and the mixed pixels decomposing method respectively. The relationship between land surface temperature and land cover was also studied.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.