Yingchun Fu); zhezhu@usgs.gov (Zhe Zhu). ABSTRACT:Remote sensing has proven a useful way of evaluating long-term trends in vegetation -greenness‖ through the use of vegetation indices like Normalized Differences Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In particular, analyses of greenness trends have been performed for large areas (continents, for example) in an attempt to understand vegetation response to climate. These studies have been most often used coarse resolution sensors like Moderate Resolution Image Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR). However, trends in greenness are also important at more local scales, particularly in and around cities as vegetation offers a variety of valuable ecosystem services ranging from minimizing air pollution to mitigating urban heat island effects.To explore the ability to monitor greenness trends in and around cities, this paper presents a new way for analyzing greenness trends based on all available Landsat 5, 7, and 8 images and applies it to Guangzhou, China. This method is capable of including the effects of land cover change in the evaluation of greenness trends by separating the effects of abrupt and gradual changes, and providing information on the timing of greenness trends.An assessment of the consistency of surface reflectance from Landsat 8 with past Landsat sensors indicates biases in the visible bands of Landsat 8, especially the blue band. Landsat 8 NDVI values were found to have a larger bias than the EVI values; therefore, EVI was used in the analysis of greenness trends for Guangzhou. In spite of massive amounts of development in Guangzhou from 2000 to 2014, greenness was found to increase, mostly as a result of gradual change. Comparison of the greening magnitudes estimated from the approach presented here and a Simple Linear Trend (SLT) method indicated large differences for certain time intervals as the SLT method does not include consideration for abrupt land cover changes. Overall, this analysis demonstrates the importance of considering land cover change when analyzing trends in greenness from satellite time series in areas where land cover change is common.

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The COVID‐19 pandemic has profoundly affected people in urban areas. This article reports on a comparative empirical study of the pandemic in Guangzhou and Xi’an in 2021 and analyses how residents responded to social media during the crisis. Using Baidu’s hot search time machine to search for hot topics related to the spread of disease during each outbreak of COVID‐19, we collected 35 and 41 hashtags for Guangzhou’s and Xi’an’s epidemics, respectively. Based on a thematic analysis of those hashtags, we considered how residents reconstructed expressions of urban identity in both cities. We found that China’s unique official accountability system in local anti‐epidemic practices led to stricter forms of top‐down urban governance and that urban residents deployed forms of bottom‐up agency in response. Our work provides a refined agenda for geographers and other social scientists to examine the interconnections among urban resilience, urban social responses to major public crises, and urban culture.

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