Open surface water bodies play an important role in agricultural and industrial production, and are susceptible to climate change and human activities. Remote sensing data has been increasingly used to map open surface water bodies at local, regional, and global scales. In addition to image statistics-based supervised and unsupervised classifiers, spectral index- and threshold-based approaches have also been widely used. Many water indices have been proposed to identify surface water bodies; however, the differences in performances of these water indices as well as different sensors on water body mapping are not well documented. In this study, we reviewed and compared existing open surface water body mapping approaches based on six widely-used water indices, including the tasseled cap wetness index (TCW), normalized difference water index (NDWI), modified normalized difference water index (mNDWI), sum of near infrared and two shortwave infrared bands (Sum457), automated water extraction index (AWEI), land surface water index (LSWI), as well as three medium resolution sensors (Landsat 7 ETM+, Landsat 8 OLI, and Sentinel-2 MSI). A case region in the Poyang Lake Basin, China, was selected to examine the accuracies of the open surface water body maps from the 27 combinations of different algorithms and sensors. The results showed that generally all the algorithms had reasonably high accuracies with Kappa Coefficients ranging from 0.77 to 0.92. The NDWI-based algorithms performed slightly better than the algorithms based on other water indices in the study area, which could be related to the pure water body dominance in the region, while the sensitivities of water indices could differ for various water body conditions. The resultant maps from Landsat 8 and Sentinel-2 data had higher overall accuracies than those from Landsat 7. Specifically, all three sensors had similar producer accuracies while Landsat 7 based results had a lower user accuracy. This study demonstrates the improved performance in Landsat 8 and Sentinel-2 for open surface water body mapping efforts.

Land use change is one of the main drivers of biodiversity loss. In the last 20 years, China’s land use pattern has undergone profound changes. This study constructs an Ecosystem Comprehensive Anthropogenic Disturbance Index (ECADI) to assess disturbance impacts of land use change between 1990 and 2010 on biodiversity conservation priority areas at national and regional scales. Four levels of biodiversity conservation areas were categorized: generally important areas, moderately important areas, important areas, and very important areas. The results indicated a higher ECADI value in 2010 in Central and Eastern China than in Western China, and the values of the moderately important, important and very important regions were lower than the average value of the whole country at all levels. Notably, in recent 20 years, the change extent of ECADI values in Central and Eastern China were much greater compared with that in Western China, and ECADI values in the moderately important, important and very important biodiversity conservation areas all showed increasing trends, with the increasing extent lower than that of whole China at all levels. Due to human activities such as urbanization in Eastern China and cropland reclamation in Northeast China and Xinjiang, ECADI values showed a medium increase trend (the change rate was about 1%–5% in 10 years), which indicated the need for more conservation efforts in those regions. However, ECADI values in the Loess Plateau presented a low decline trend (the change rate was about −1% to −0.1% in 10 years) after 2000 because of the obvious effectiveness of Green for Grain Project. Furthermore, the variation was negligible in the Tibetan Plateau.