Based on the same data source of Landsat TM/ETM+ in 1990s, 2000s and 2010s, all urban built-up areas in China are mapped mainly by human interpretation. Mapping results were checked and refined by the same analyst with the same set of criteria. The results show during the last 20 years urban areas in China have increased exponentially more than 2 times. The greatest area of urbanization changed from Northeastern provinces in 1990s to the Southeast coast of China in Jiangsu, Guangdong, Shandong, and Zhejiang in 2010s. Urban areas are mostly converted from croplands in China. Approximately 17750 km² croplands were converted into urban lands. Furthermore, the conversion from 2000 to 2010 doubled that from 1990 to 2000. During the 20 years, the most urbanized provinces are Jiangsu, Guangdong, Shandong and Zhejiang. We also analyzed built-up areas, gross domestic production (GDP) and population of 147 cities with a population of greater than 500000 in 2009. The result shows coastal cities and resource-based cities are with high economic efficiency per unit of built-up areas, resource-based cities have the highest population density, and the economic efficiency of most coastal provinces are lower than central provinces and Guangdong. The newly created urban expansion dataset is useful in many fields including trend analysis of urbanization in China; simulation of urban development dynamics; analysis of the relationship among urbanization, population growth and migration; studies of carbon emissions and climate change; adaptation of climate change; as well as land use and urban planning and management.

The positive response of wetland methane (CH₄) emissions to climate change is an important yet uncertain Earth-system feedback that amplifies atmospheric CH₄ concentrations. Here, using a wetland model, we report intensified wetland CH₄ emissions during 2000–2021, corresponding with 2020 and 2021 being exceptional years of growth. Our results highlight the need for sustained monitoring and observations of global wetland CH₄ fluxes to document emerging trends, variability and underlying drivers.

Wetlands are responsible for 20%–31% of global methane (CH₄) emissions and account for a large source of uncertainty in the global CH₄ budget. Data‐driven upscaling of CH₄ fluxes from eddy covariance measurements can provide new and independent bottom‐up estimates of wetland CH₄ emissions. Here, we develop a six‐predictor random forest upscaling model (UpCH4), trained on 119 site‐years of eddy covariance CH₄ flux data from 43 freshwater wetland sites in the FLUXNET‐CH4 Community Product. Network patterns in site‐level annual means and mean seasonal cycles of CH₄ fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash‐Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH₄ emissions of 146 ± 43 TgCH₄ y⁻¹ for 2001–2018 which agrees closely with current bottom‐up land surface models (102–181 TgCH₄ y⁻¹) and overlaps with top‐down atmospheric inversion models (155–200 TgCH₄ y⁻¹). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH₄ fluxes has the potential to produce realistic extra‐tropical wetland CH₄ emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid‐to‐arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ORNLDAAC/2253).