Urban boundaries, an essential property of cities, are widely used in many urban studies. However, extracting urban boundaries from satellite images is still a great challenge, especially at a global scale and a fine resolution. In this study, we developed an automatic delineation framework to generate a multi-temporal dataset of global urban boundaries (GUB) using 30 m global artificial impervious area (GAIA) data. First, we delineated an initial urban boundary by filling inner non-urban areas of each city. A kernel density estimation approach and cellular-automata based urban growth modeling were jointly used in this step. Second, we improved the initial urban boundaries around urban fringe areas, using a morphological approach by dilating and eroding the derived urban extent. We implemented this delineation on the Google Earth Engine platform and generated a 30 m resolution global urban boundary dataset in seven representative years (i.e. 1990, 1995, 2000, 2005, 2010, 2015, and 2018). Our extracted urban boundaries show a good agreement with results derived from nighttime light data and human interpretation, and they can well delineate the urban extent of cities when compared with high-resolution Google Earth images. The total area of 65 582 GUBs, each of which exceeds 1 km², is 809 664 km² in 2018. The impervious surface areas account for approximately 60% of the total. From 1990 to 2018, the proportion of impervious areas in delineated boundaries increased from 53% to 60%, suggesting a compact urban growth over the past decades. We found that the United States has the highest per capita urban area (i.e. more than 900 m²) among the top 10 most urbanized nations in 2018. This dataset provides a physical boundary of urban areas that can be used to study the impact of urbanization on food security, biodiversity, climate change, and urban health. The GUB dataset can be accessed from http://data.ess.tsinghua.edu.cn.

Four wetland maps for all China have been produced, based on Landsat and CBERS-02B remote sensing data between 1978 and 2008 (1978, 1990, 2000 and 2008). These maps were mainly developed by manual interpretation and validated by substantial field investigation in 2009. Based on these maps, we analyzed the 2008 wetland distribution in China and discussed wetland changes and their drivers over the past 30 years. (i) There were about 324097 km² of wetlands in 2008, for which inland marshes or swamps were the most common wetland type (35%), with lakes (26%) second. Most of the wetlands were in Heilongjiang, Inner Mongolia, Qinghai and Tibet, occupying about 55% of the national wetland area. (ii) From 1978 to 2008, China’s wetland area continually and significantly decreased, by about 33% based on changes in the wetland map. This was in sharp contrast to the increase in artificial wetlands, which increased by about 122%. Inland marshes accounted for the main loss of total wetlands from 1978 to 2000. From 2000 through 2008, riverine and lacustrine wetlands constituted the main wetland loss. Fortunately however, the rate of wetland loss decreased from 5523 to 831 km²/a. (iii) The change ratio of lost natural wetlands (including inland and coastal wetlands) to non-wetlands has decreased slightly over the past 30 years. From 1978 to 1990, nearly all natural wetlands (98%) lost were transformed into non-wetlands. However, the ratio declined to 86% from 1990 to 2000, and to 77% from 2000 to 2008. (iv) All Chinese provinces were divided into three groups according to patterns of wetland changes, which could relate to the driving forces of such changes. Tibet was completely different from other provinces, as it was one representative example in which there was a net wetland increase, because of global warming and decreased human activity since 1990. Increased economic development caused considerable wetland loss in most eastern provinces, and artificial wetlands increased.