Analysis of urban distribution and its expansion using remote sensing data has received increasing attention in the past three decades, but little research has examined spatial patterns of urban distribution and expansion with buffer zones in different directions. This research selected Hangzhou metropolis as a case study to analyze spatial patterns and dynamic changes based on time-series urban impervious surface area (ISA) datasets. ISA was developed from Landsat imagery between 1991 and 2014 using a hybrid approach consisting of linear spectral mixture analysis, decision tree classifiers, and post-processing. The spatial patterns of ISA distribution and its dynamic changes in eight directions—east, southeast, south, southwest, west, northwest, north, and northeast—at the temporal scale were analyzed with a buffer zone-based approach. This research indicated that ISA can be extracted from Landsat imagery with both producer and user accuracies of over 90%. ISA in Hangzhou metropolis increased from 146 km² in 1991 to 868 km² in 2014. Annual ISA growth rates were between 15.6 km² and 48.8 km² with the lowest growth rate in 1994–2000 and the highest growth rate in 2005–2010. Urban ISA increase before 2000 was mainly due to infilling within the urban landscape, and, after 2005, due to urban expansion in the urban-rural interfaces. Urban expansion in this study area has different characteristics in various directions that are influenced by topographic factors and urban development policies.

An urban net all-wave radiation parameterization scheme is evaluated using annual datasets for 2010 recorded at a Beijing urban observation site. The statistical relationship between observed data and simulation data of net radiation has a correlation coefficient of 0.98 and model efficiency of 0.93. Therefore, it can be used to simulate the radiation balance of Beijing. This study analyzes the variation in the radiation balance for different underlying surfaces. To simulate radiation balance differences, we set four pure land-cover types (forest, grass, roads, and buildings). Keeping all other conditions inputted unchanged, we model the radiation balance by changing the land-cover type. The results show that the effects of different underlying surfaces on radiation differ, and that there is much upward long-wave radiation, accounting for 84.3% of the total radiation energy falling incident on the land surface. The annual averages of net radiation for the four land-cover types are in the range of 38.2–53.4 W/m². The net radiation of the grass surface is minimal while that of the roads surface is maximal. Additionally, with urbanization the net radiation values of common types of land-cover change, such as conversion from forest to roads, grass to roads, and grass to buildings, all have increasing trends, indicating that net radiation usually increases with urban sprawl.

Rapid urbanization has occurred in northwestern China, threatening the sustainability of its fragile dryland ecosystems. A lack of precise urban land-cover information has limited our understanding on the urbanization in the dryland. Here, we examined urban land-cover changes from 2000 to 2014 in 21 major cities that comprise over 50% of the developed land in arid China, using Landsat Enhanced Thematic Mapper Plus and Operational Land Imager data, and a hybrid classification method. The 15-m resolution urban land-cover products (including impervious surfaces, vegetation, bare soil, and water bodies) had an overall accuracy of 90.37%. Based on these new land use products, we found the urbanization in arid China was characterized by the dramatic expansion of impervious surface (+13.23%) and reduction of bare soil (−13.41%), while the proportions of vegetation (+0.27%) and water (−0.10%) remained stable. The observed dynamic equilibrium of vegetated ratio implies an increasing harmonization of urbanization and greening, which was particularly important for the sustainability of fragile urban ecosystems in arid regions. From an economic perspective, gross domestic product and population were significantly correlated with impervious surfaces, and oasis cities displayed a stronger ability to attract new residents than desert cities.

Understanding the historical change of agricultural landscape patterns is the basis for promoting the sustainable development of cultivated land, as well as appropriate decision-making. In order to analyze spatio-temporal changes of cultivated land in Sanjiang Plain, from 1985–2015, Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) were used to reconstruct satellite data of land use and land cover. Additionally, twelve landscape indices were selected to analyze landscape pattern changes and to compare the differences of cultivated landscape changes between the agricultural region and the reclamation region. Studies suggested that during the past 30 years, cultivated land in the study area grew rapidly, with a rapid growth of paddy fields and a slow reduction of dry farmland. This trend was more obvious in the reclamation region than it was in the agricultural region, where both dry farmland and paddy fields showed a growth trend in the past 30 years. Our study showed that paddies have become the dominant agricultural landscape and that fragmentation of paddy fields has decreased, while dry farmland has increased over the past 30 years, within the entire study area. Different management modes have caused major differences between the agricultural region and the reclamation region.

Rapid cropland reclamation is underway in Cold China in response to increases in food demand, while the lack analyses of time series cropping pattern mappings limits our understanding of the acute transformation process of cropland structure and associated environmental effects. The Cold China contains different agricultural systems (state and private farming), and such systems could lead to different cropping patterns. So far, such changes have not been revealed yet. Based on the Landsat images, this study tracked cropping information in five-year increments (1990–1995, 1995–2000, 2000–2005, 2005–2010, and 2010–2015) and predicted future patterns for the period of 2020–2050 under different agricultural systems using developed method for determining cropland patterns. The following results were obtained: The available time series of Landsat images in Cold China met the requirements for long-term cropping pattern studies, and the developed method exhibited high accuracy (over 91%) and obtained precise spatial information. A new satellite evidence was observed that cropping patterns significantly differed between the two farm types, with paddy field in state farming expanding at a faster rate (from 2.66 to 68.56%) than those in private farming (from 10.12 to 34.98%). More than 70% of paddy expansion was attributed to the transformation of upland crop in each period at the pixel level, which led to a greater loss of upland crop in state farming than private farming (9505.66 km² vs. 2840.29 km²) during 1990–2015. Rapid cropland reclamation is projected to stagnate in 2020, while paddy expansion will continue until 2040 primarily in private farming in Cold China. This study provides new evidence for different land use change pattern mechanisms between different agricultural systems, and the results have significant implications for understanding and guiding agricultural system development.