Regional information on the spatial distribution of soil salinity can be used as guidance in avoiding the continued degradation of land and water resources. However, most regional soil salinity maps are produced through a conventional direct-linking method derived from historic observations. Such maps lack spatial details and are limited in describing the evolution of soil salinization in particular instances. In anthropogenic regions, soil change, and soil formation and degradation, have accelerated, jeopardizing soil quality and health. The need for up-to-date soil and environmental data that characterize the physicochemical, biological, and hydrological conditions of arid ecosystems across continents has intensified (e.g. soil salinization in arid land). Digital soil mapping (DSM) and modeling techniques have been widely used in the past few decades. To overcome these limitations, we employed a method that included an integrative hierarchical-sampling strategy (IHSS) and the Soil Land Inference Model (SoLIM) to map soil salinity over a regional area. This case study, the Xinjiang Uygur Autonomous Region of China, demonstrates that the employed method can produce soil salinity maps at a higher level of spatial detail and accuracy. Twenty-three representative points are determined. The results show that: (1) the prediction is accurate in Kuqa Oasis (R²=0.70, RPD=1.55, RMSE=12.86) and Keriya Oasis (R²=0.75, RPD=1.66, RMSE=10.92), and performed a little better than in Fukang Oasis (R²=0.77, RPD=2.01, RMSE=6.32), according to the evaluation criteria. (2) Based on all validation samples from three oases, accuracy estimation shows that the employed method (R²= 0.74, RPD=1.67, RMSE=11.18) performed better than the multiple linear regression model (R²=0.60, RPD= 1.47, RMSE=14.45). Finally, this study concludes that the employed method can serve as an alternative model for soil salinity mapping on a large scale.

Central Asia, which is an arid inland area, has the most severe water-resource problems in the world. This paper reviews the literature on water issues in Central Asia published in the last 15 years (i.e., since 2000), covering the quantity of literature, the research institutes involved, the research approaches, and the major issues in the subject. The following conclusions can be reached based on the literature: (1) Water issues in Central Asia are an important area of geographical research. Many studies from China, Germany, the USA, and other countries have focused on the responses of water cycling processes to climate change, and on the hydrological environment of the catchment. In addition, Chinese researchers have tended to focus their studies on trans-boundary river management. (2) Temperature rise and precipitation increase are the fundamental features of climate change in Central Asia. Terrestrial water storage and river runoff have an obvious decrease as a result of temperature rise. (3) Soil salinization, land degradation and water pollution have been worsened by irrational utilization of water resources, and all of these have increased the pressures on the environment of the catchment. (4) Complicated geopolitics makes it difficult for the international community to manage the trans-boundary rivers in Central Asia. The water utilization situation in Central Asian countries is getting worse, which causes a series of ecological problems and even endangers the stability of social and economic development. Important future directions for studies on water issues in Central Asia include the relationships between population, resources and environment; the interaction mechanism of hydrology, methodological, social and political aspects; as well as the collection of basic hydrological data.

Geomorphic evolution often presents a spatial pattern of a "young to old" distribution under certain natural environment condition, whereby sampling the geomorphic types and characteristics in spatial sequence can provide some evidence for the evolution of the individual geomorphologic object. This so-called space-for-time substitution has been a methodology in geomorphology research. This paper firstly introduced the basic concepts and background of space-for-time substitution, then a full review has been conducted of recent research progress in geomorphic evolution based on space-for-time substitution, such as fluvial landform, structural landform, estuarine landform and coastal landform. Finally, the explicit terms like suitable conditions, influencing factors and classifications have been summarized so that the research paradigm of space-for-time substitution was proposed. We argued that in the future, the researchers should focus on a full use of massive geographic data for geomorphic evolution research at multi-spatial scales, as well as an effective combination with physical mechanisms and statistical laws for a comprehensive geomorphic evolution modelling.

Due to its rapid economic development in recent years, China is becoming ever more urbanized. With this background of urbanization, land use and land cover change are complex in urban-rural continuum where the land is characterized by both town and country usages. The urban-rural continuum of Harbin City, Heilongjiang Province was chosen as the study area. Impervious surface from the Harbin urban-rural continuum was extracted by a linear spectral mixture analysis method based on the Landsat TM image acquired in the years of 1984, 1993, 2002 and 2010. The temporal and spatial variations of the urban impervious surface were examined. A boosted regression tree was employed to identify the most important factor that has been affecting the expansion of the impervious surface since 1984 from among eight factors, i.e. slope, aspect, DEM, distance to river, distance to expressway, distance to railway, distance to main road, and distance to the central city in 1984. The results indicate that the proportion of impervious surfaces in the Harbin rural-urban continuum was 3.9% in 1984, 6.6% in 1993, 9.0% in 2002, and 16.52% in 2010. The distribution patterns of impervious surface coverage from 1984 to 2010 showed obvious spatial variations. Traffic factors, including expressways, railways, and main roads, have been propelling the development of surrounding area, and inducing the rapid expansion of cities along the roads.