Phenological changes caused by urbanization may provide evidence of how vegetation responds to global warming. However, the phenological characteristics of vegetation in metropolitan areas have been poorly studied, especially in terms of spatiotemporal variations. In this study, we explored the applicability of Local Climate Zones (LCZs) to investigate the spatiotemporal variations in urban vegetation phenology by linking MODIS-derived phenology metrics with LCZs in the Austin metropolitan area in Texas, USA. We extracted three vegetation phenology metrics from MODIS data between 2008 and 2018, including the start of growing season, end of growing season, and length of the growing season (i.e. SOS, EOS, and LOS, respectively). The results showed that during the study period, the EOS and SOS gradually advanced, while LOS showed no obvious change. Statistical analysis was conducted to examine the spatiotemporal variations of the phenology metrics among different LCZs and along “Urban-Rural Gradients” (URGs). There were 37.5%, 75.0%, and 74.3% pairs of LCZs, indicating statistically significant phenological differences in terms of SOS, EOS, and LOS in 2012, respectively. In contrast, most pairs of URGs showed almost no differences in phenological metrics, especially in EOS. Geographically, SOS showed a fluctuating change with an advancing tendency, whereas the EOS decreased very slowly with distance from the city center (i.e. along the URGs). LCZs can be used to help identify distinctive phenology metrics with statistically significant differences, especially in EOS and LOS. Compared to URGs, LCZs offer a unique analytical framework for studying urban ecosystem patterns, functions, and dynamics. Lastly, LCZs can enable the identification of sensitive areas for ecological protection in support of sustainable urban development and environmental stewardship.

Acquired Immune Deficiency Syndrome (AIDS) has become one of the most severe public health issues and nowadays around 38 million people are living with the human immunodeficiency virus (HIV). Ensuring healthy lives and promoting well-being is one of 17 United Nations Sustainable Development Goals. Here, we used the Markov chain matrix and geospatial clustering to comprehensively quantify the trends of the AIDS epidemic at the provincial administrate level in the mainland of China from 2005 to 2017. The Geographically Weighted Regression (GWR) model was further adopted to explore four groups of potential influencing factors (i.e., economy, traffic and transportation, medical care, and education) of the AIDS incidence rate in 2017 and their spatially distributed patterns. Results showed that the AIDS prevalence in southeastern China had been dominant and become prevalent in the past decade. The AIDS intensity level had been increasing between 2008 and 2011 but been gradually decreasing afterward. The analysis of the Markov chain matrix indicated that the AIDS epidemic has been generally in control on the Chinese mainland. The economic development was closely related to the rate of AIDS incidence on the Chinese mainland. The GWR result further suggested that medical care and the education effects on AIDS incidence rate can vary with different regions, but significant conclusions cannot be directly demonstrated. Our findings contribute an analytical framework of understanding AIDS epidemic trends and spatial variability of potential underlying factors throughout a complex extent to customize scientific prevention.