In recent years, sedimentation conditions in Dongting Lake have varied greatly because of signifi cant changes in runoff and sediment load in the Changjiang(Yangtze) River following the construction of Three Gorges Dam. The topography of the lake bottom has changed rapidly because of the intense exchange of water and sediment between the lake and the Changjiang River. However, time series information on lake-bottom topographic change is lacking. In this study, we introduced a method that combines remote sensing data and in situ water level data to extract a record of Dongting Lake bottom topography from 2003 to 2011. Multi-temporal lake land/water boundaries were extracted from MODIS images using the linear spectral mixture model method. The elevation of water/land boundary points were calculated using water level data and spatial interpolation techniques. Digital elevation models of Dongting Lake bottom topography in different periods were then constructed with the multiple heighted waterlines. The mean root-mean-square error of the linear spectral mixture model was 0.036, and the mean predicted error for elevation interpolation was-0.19 m. Compared with fi eld measurement data and sediment load data, the method has proven to be most applicable. The results show that the topography of the bottom of Dongting Lake has exhibited uneven erosion and deposition in terms of time and space over the last nine years. Moreover, lake-bottom topography has undergone a slight erosion trend within this period, with 58.2% and 41.8% of the lake-bottom area being eroded and deposited, respectively.
Lake surface water temperature （SWT） is an important indicator of lake state relative to its water chemistry and aquatic ecosystem,in addition to being an important regional climate indicator.However,few literatures involving spatial-temporal changes of lake SWT in the Qinghai-Tibet Plateau,including Qinghai Lake,are available.Our objective is to study the spatial-temporal changes in SWT of Qinghai Lake from 2001 to 2010,using Moderate-resolution Imaging Spectroradiometer （MODIS） data.Based on each pixel,we calculated the temporal SWT variations and long-term trends,compared the spatial patterns of annual average SWT in different years,and mapped and analyzed the seasonal cycles of the spatial patterns of SWT.The results revealed that the differences between the average daily SWT and air temperature during the temperature decreasing phase were relatively larger than those during the temperature increasing phase.The increasing rate of the annual average SWT during the study period was about 0.01℃/a,followed by an increasing rate of about 0.05℃/a in annual average air temperature.The annual average SWT from 2001 to 2010 showed similar spatial patterns,while the SWT spatial changes from January to December demonstrated an interesting seasonal reversion pattern.The high-temperature area transformed stepwise from the south to the north regions and then back to the south region from January to December,whereas the low-temperature area demonstrated a reversed annual cyclical trace.The spatial-temporal patterns of SWTs were shaped by the topography of the lake basin and the distribution of drainages.
Perennial waterlogged soil（PWS） is induced by the high level of groundwater, and has a persistent impact on natural ecosystems and agricultural production. Traditionally, distribution information regarding PWS is mainly collected from in situ measurements through groundwater level surveys and physicochemical property analyses. However, in situ measurements of PWS are costly and time-consuming, only rough estimates of PWS areas are available in some regions. In this paper, we developed a method to monitor the perennial waterlogged cropland using time-series moderate resolution imaging spectroradiometer（MODIS） data. The Jianghan Plain, a floodplain located in the middle reaches of the Yangtze River, was selected as the study area. Temporal variations of the enhanced vegetation index（EVI）, night land surface temperature（LST）, diurnal LST differences（ΔLST）, albedo, and the apparent thermal inertia（ATI） were used to analyze the ecological and thermodynamic characteristics of the waterlogged croplands. To obtain pure remote sensing signatures of the waterlogged cropland from mixed pixels, the croplands were classified into different types according to soil and land cover types in this paper, and a linear mixing model was developed by fitting the signatures using the multiple linear regression approach. Afterwards, another linear spectral mixing model was used to get the proportions of waterlogged croplands in each 1 km×1 km pixel. The result showed an acceptable accuracy with a root-mean-square error of 0.093. As a tentative method, the procedure described in this paper works efficiently as a method to monitor the spatial patterns of perennial sub-surface waterlogged croplands at a wide scale.
XIAO FeiLI Yuan-zhengDU YunLING FengYAN YiFENG QiBAN Xuan
