An overview of the commonly applied evapotranspiration (ET) models using remotely sensed data is given to provide insight into the estimation of ET on a regional scale from satellite data. Generally, these models vary greatly in inputs, main assumptions and accuracy of results, etc. Besides the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, must rely to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale. We discuss the main inputs, assumptions, theories, advantages and drawbacks of each model. Moreover, approaches to the extrapolation of instantaneous ET to the daily values are also briefly presented. In the final part, both associated problems and future trends regarding these remotely sensed ET models were analyzed to objectively show the limitations and promising aspects of the estimation of regional ET based on remotely sensed data and ground-based measurements.

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Understanding the spatio-temporal dynamics of urban development at regional and global scales is increasingly important for urban planning, policy decision making and resource use and conservation. Continuous satellite derived observations of anthropogenic lighting signal at night provide consistent and efficient proxy measures of demographic and socioeconomic dynamics in the urbanization process. Previous studies have demonstrated significant positive correlations between the nocturnal light brightness, mainly derived from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS), and population and economic variables. Quantitative measurements of artificial lighting emissions at night therefore can be indicative of the overall degree of socioeconomic development at regional to country levels. The spatio-temporal characteristics of anthropogenic night-time lighting, potentially connected to the dynamic patterns of spatially expanding human settlement and economic activities during the urban expansion process, however, has received less attention largely because of diversity of both socioeconomic activity and urban forms. Based upon the quadratic relationship between the pixel-level night-time light radiance and corresponding brightness gradient (i.e. the rate of maximum local change) at the local scale, we here proposed a spatially explicit approach for partitioning DMSP/OLS night-time light images into five types of night-time lighting areas for individual cities: low, medium-low, medium, medium-high and high, generally associated with urban sub-areas experienced distinctly different forms and human activity. At the country scale, our findings suggest that significant rises are commonly found in these five types of night-time lighting areas with different growth rates across 271 China's cities from 1992 to 2012. At the urban scale, however, five types of night-time lighting areas show various trends for individual cities in relation to the urban size and development levels. The marked increase in high night-time lighting area is highly prevalent in most of China's cities with rapid urbanization over the past 21 years while significantly decreased low and medium-low night-time lighting areas are most likely to occur in large and extra-large cities. Moreover, the transition between different types of night-time lighting areas could further portray the spatiotemporal characteristics of urban development. Analyzing results indicate that the spatial expansions of gradually intensified night-time light brightness correspond geographically with the rural-urban gradients following a stepwise transition of night-time light brightness during the urban expansion.