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Bathymetry has been traditionally charted via shipboard echo sounding. Alhough able to generate accurate depth measurements at points or along transects, this method is constrained by its high operating cost, inefficiency, and inapplicability to shallow waters. By comparison, remote sensing methods offer more flexible, efficient and cost-effective means of mapping bathymetry over broad areas. Remote sensing of bathymetry falls into two broad categories: non-imaging and imaging methods. The non-imaging method (as typified by LiDAR) is able to produce accurate bathymetric information over clear waters at a depth up to 70 m. However, this method is limited by the coarse bathymetric sampling interval and high cost. The imaging method can be implemented either analytically or empirically, or by a combination of both. Analytical or semi-analytical implementation is based on the manner of light transmission in water. It requires inputs of a number of parameters related to the properties of the atmosphere, water column, and bottom material. Thus, it is rather complex and difficult to use. By comparison, empirical implementation is much simpler and requires the input of fewer parameters. Both implementations can produce fine-detailed bathymetric maps over extensive turbid coastal and inland lake waters quickly, even though concurrent depth samples are essential. The detectable depth is usually limited to 20 m. The accuracy of the retrieved bathymetry varies with water depth, with the accuracy substantially lower at a depth beyond 12 m. Other influential factors include water turbidity and bottom materials, as well as image properties.

With ever intensifying land use, land degradation is becoming an increasingly important issue around the world, especially in China. This paper evaluates the extent and underlying causes of rangeland degradation on the Qinghai‐Tibet Plateau in China through a comprehensive review of the literature. Diverse forms and differing intensities of rangeland degradation have been reported in several regions of the Plateau. Rangeland degradation is particularly severe in South Qinghai, North Tibet and the Qaidam Basin. Anthropogenic activities, especially changing land use practices, are identified as the primary force driving rangeland degradation. Dissimilar to climate change‐induced degradation, such anthropogenic degradation is a rather short‐term process altering the abiotic properties of the underlying soil. On the basis of these findings, we assessed the prospects of rehabilitating degraded rangeland to productive uses. Different measures are proposed to rehabilitate rangelands that have been degraded by different mechanisms. Reduction in grazing intensity is prescribed to rehabilitate reversibly degraded rangelands. Targeted human intervention in the forms of selective planting of grasses and artificial seeding, in conjunction with ecological and biological control of the plateau rodent population, is recommended to rehabilitate ‘irreversibly’ degraded rangelands. Our studies suggest it is very difficult or even impossible to rehabilitate new assemblage of species which appear as a result of climate change. Copyright © 2011 John Wiley & Sons, Ltd.

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Quantification of quality parameters of inland and near shore waters by means of remote sensing has encountered varying degrees of success in spite of the high variability of the parameters under consideration and limitations of remote sensors themselves. This paper comprehensively evaluates the quantification of four types of water quality parameters: inorganic sediment particles, phytoplankton pigments, coloured dissolved organic material and Secchi disk depth. It concentrates on quantification requirements, as well as the options in selecting the most appropriate sensor data for the purpose. Relevant factors, such as quantification implementation and validation of the quantified results are also extensively discussed. This review reveals that the relationship between in situ samples and their corresponding remotely sensed data can be linear or nonlinear, but are nearly always site-specific. The quantification has been attempted from terrestrial satellite data largely for suspended sediments and chlorophyll concentrations. The quantification has been implemented through integration of remotely sensed imagery data, in situ water samples and ancillary data in a geographic information system (GIS). The introduction of GIS makes the quantification feasible for more variables at an increasingly higher accuracy. Affected by the number and quality of in situ samples, accuracy of quantification has been reported in different ways and varies widely.