Zhou Y.,CAS Institute of Geographical Sciences and Natural Resources Research |
Ma T.,CAS Institute of Geographical Sciences and Natural Resources Research |
Ma T.,Jiangsu Center For Collab Innovation In Geographical Information Resource Development And Applied |
Zhou C.,CAS Institute of Geographical Sciences and Natural Resources Research |
And 2 more authors.
Remote Sensing | Year: 2015
Satellite-derived nighttime light (NTL) data have been extensively used as an efficient proxy measure for monitoring urbanization dynamics and socioeconomic activity. This is because remotely sensed NTL signals can be quantitatively connected to demographic and socioeconomic variables at regional and global scales. The recently composited cloud-free NTL imagery derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite provides spatially detailed observations of human settlements. We quantitatively estimated socioeconomic development inequalities across 30 provinces and municipalities in mainland China using VIIRS NTL data associated with both regional gross domestic product (GDP) and population census data. We quantitatively investigated relations between NTL, GDP, and population using a linear regression model. Our results suggest that NTL radiances have significant positive correlations with GDP and population at different levels. Several inequality coefficients, commonly used in economics, were derived from VIIRS NTL data and statistical data at multiple spatial scales. Compared with the statistical data, NTL-derived inequality coefficients enabled us to elicit more detailed information on differences in regional development at multiple levels. Our study of provinces and municipalities revealed that county-level inequality was more significant than city-level inequality. The results of population-weighted NTL inequality indicate an obvious regional disparity with NTL distribution being more unequal in China's undeveloped western regions compared with more developed eastern regions. Our findings suggest that given the timely and spatially explicit advantages of VIIRS, NTL data are capable of providing comprehensive information regarding inequality at multiple levels, which is not possible through the use of traditional statistical sources. Source
Lu N.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research |
Lu N.,Jiangsu Center For Collab Innovation In Geographical Information Resource Development And Applied |
Trenberth K.E.,U.S. National Center for Atmospheric Research |
Qin J.,CAS Institute of Tibetan Plateau Research |
And 4 more authors.
Journal of Climate | Year: 2015
Long-term trends in precipitable water (PW) are an important component of climate change assessments for the Tibetan Plateau (TP). PW products from Moderate Resolution Imaging Spectroradiometer (MODIS) are able to provide good spatial coverage of PW over the TP but limited in time coverage, while the meteorological stations in the TP can estimate long-term PWbut unevenly distributed. To detect the decadal trend in PWover the TP, Bayesian inference theory is used to construct long-term and spatially continuous PW data for the TP based on the station and MODIS observations. The prior information on the monthly-mean PWfrom MODIS and the 63 stations over the TP for 2000-06 is used to get the posterior probability knowledge that is utilized to build a Bayesian estimation model. This model is then operated to estimate continuous monthly-mean PW for 1970-2011 and its performance is evaluated using the monthly MODIS PW anomalies (2007-11) and annual GPS PW anomalies (1995-2011), with RMSEs below 0.65 mm, to demonstrate that the model estimation can reproduce the PW variability over the TP in both space and time. Annual PW series show a significant increasing trend of 0.19 mm decade-1 for the TP during the 42 years. The most significant PW increase of 0.47 mm decade-1 occurs for 1986-99 and an insignificant decrease occurs for 2000-11. From the comparison of the PW data from JRA-55, ERA-40, ERA-Interim, MERRA, NCEP-2, and ISCCP, it is found that none of them are able to show the actual long-term trends and variability in PW for the TP as the Bayesian estimation. © 2015 American Meteorological Society. Source
Cheng L.,Nanjing University |
Tong L.,Nanjing University |
Wu Y.,Nanjing University |
Chen Y.,Nanjing University |
And 2 more authors.
Remote Sensing | Year: 2015
A new automated approach to the high-accuracy registration of airborne and terrestrial LiDAR data is proposed, which has three primary steps. Firstly, airborne and terrestrial LiDAR data are used to extract building corners, known as airborne corners and terrestrial corners, respectively. Secondly, an initial matching relationship between the terrestrial corners and airborne corners is automatically derived using a matching technique based on maximum matching corner pairs with minimum errors (MTMM). Finally, a set of leading points are generated from matched airborne corners, and a shiftable leading point method is proposed. The key feature of this approach is the implementation of the concept of shiftable leading points in the final step. Since the geometric accuracy of terrestrial LiDAR data is much better than that of airborne LiDAR data, leading points corresponding to anomalous airborne corners could be modified for the improvement of the geometric accuracy of registration. The experiment demonstrates that the proposed approach can advance the geometric accuracy of two-platform LiDAR data registration effectively. Source
Guo Y.,Carbon Control |
Li Y.,Carbon Control |
Li Y.,Jiangsu Center For Collab Innovation In Geographical Information Resource Development And Applied |
Zhu L.,Satellite Environment Application Center |
And 3 more authors.
Remote Sensing | Year: 2015
Although remote sensing technology has been widely used to monitor inland water bodies; the lack of suitable data with high spatial and spectral resolution has severely obstructed its practical development. The objective of this study is to improve the unmixing-based fusion (UBF) method to produce fused images that maintain both spectral and spatial information from the original images. Images from Environmental Satellite 1 (HJ1) and Medium Resolution Imaging Spectrometer (MERIS) were used in this study to validate the method. An improved UBF (IUBF) algorithm is established by selecting a proper HJ1-CCD image band for each MERIS band and thereafter applying an unsupervised classification method in each sliding window. Viewing in the visual sense-the radiance and the spectrum-the results show that the improved method effectively yields images with the spatial resolution of the HJ1-CCD image and the spectrum resolution of the MERIS image. When validated using two datasets; the ERGAS index (Relative Dimensionless Global Error) indicates that IUBF is more robust than UBF. Finally, the fused data were applied to evaluate the chlorophyll a concentrations (Cchla) in Taihu Lake. The result shows that the Cchla map obtained by IUBF fusion captures more detailed information than that of MERIS. Source
Meng T.,Nanjing Normal University |
Meng T.,Jiangsu Provincial Key Laboratory of Materials Cycling and Pollution Control |
Zhu T.,Nanjing Normal University |
Zhu T.,Jiangsu Provincial Key Laboratory of Materials Cycling and Pollution Control |
And 8 more authors.
Journal of Environmental Sciences (China) | Year: 2015
Reductive soil disinfestation (RSD), namely amending organic materials and mulching or flooding to create strong reductive status, has been widely applied to improve degraded soils. However, there is little information available about sulfate (SO4 2-) transformation and sulfur (S) gas emissions during RSD treatment to degraded vegetable soils, in which S is generally accumulated. To investigate the effects of liming on SO4 2- transformation and S gas emissions, two SO4 2--accumulated vegetable soils (denoted as S1 and S2) were treated by RSD, and RSD plus lime, denoted as RSD0 and RSD1, respectively. The results showed that RSD0 treatment reduced soil SO4 2- by 51% and 61% in S1 and S2, respectively. The disappeared SO4 2- was mainly transformed into the undissolved form. During RSD treatment, hydrogen sulfide (H2S), carbonyl sulfide (COS), and dimethyl sulfide (DMS) were detected, but the total S gas emission accounted for <0.006% of total S in both soils. Compared to RSD0, lime addition stimulated the conversion of SO4 2- into undissolved form, reduced soil SO4 2- by 81% in S1 and 84% in S2 and reduced total S gas emissions by 32% in S1 and 57% in S2, respectively. In addition to H2S, COS and DMS, the emissions of carbon disulfide, methyl mercaptan, and dimethyl disulfide were also detected in RSD1 treatment. The results indicated that RSD was an effective method to remove SO4 2-, liming stimulates the conversion of dissolved SO4 2- into undissolved form, probably due to the precipitation with calcium. © 2015. Source