a b s t r a c tThe outbreak of the 2019 novel coronavirus disease has caused more than 100,000 people to be infected and has caused thousands of deaths. Currently, the number of infections and deaths is still increasing rapidly. COVID-19 seriously threatens human health, production, life, social functioning and international relations, and has caused widespread concern around the globe. In the fight against COVID-19, geographic information systems (GIS) and big data technologies have played an important role in many aspects, including the rapid aggregation of multisource big data, rapid visualization of epidemic information, spatial tracking of COVID-19, prediction of regional transmission, identification of the spatial allocation of risk and selection of the control level, balance and management of the supply and demand of medical resources, social-emotional guidance and panic elimination, the provision of solid spatial information support for decision-making about COVID-19 prevention and control, measures formulation, and assessment of the effectiveness of COVID-19 prevention and control. GIS has developed and matured relatively quickly and has a complete technological route for data preparation, platform construction, model construction, and map production. However, for the struggle against COVID-19, the main challenge is finding strategies to adjust traditional technical methods and improve speed and accuracy to provide accurate information for rapid social management. Additionally, in the era of big data, data no longer come mainly from the government but are gathered from more diverse enterprises. As a result, the use of GIS faces difficulties in data acquisition and the integration of heterogeneous data, which requires governments, businesses, and academic institutions to jointly promote the formulation of relevant policies. At the technical level, spatial analysis methods for big data are in the ascendancy. Currently and for a long time in the future, the development of GIS should be strengthened to form a data-driven system for rapid knowledge acquisition, which signifies that GIS should be used to reinforce the social operation parameterization of models and methods, especially when providing support for social management.

Inadequate water quality can mean that water is unsuitable for a variety of human uses, thus exacerbating freshwater scarcity. Previous large-scale water scarcity assessments mostly focused on the availability of sufficient freshwater quantity for providing supplies, but neglected the quality constraints on water usability. Here we report a comprehensive nationwide water scarcity assessment in China, which explicitly includes quality requirements for human water uses. We highlight the necessity of incorporating water scarcity assessment at multiple temporal and geographic scales. Our results show that inadequate water quality exacerbates China's water scarcity, which is unevenly distributed across the country. North China often suffers water scarcity throughout the year, whereas South China, despite sufficient quantities, experiences seasonal water scarcity due to inadequate quality. Over half of the population are affected by water scarcity, pointing to an urgent need for improving freshwater quantity and quality management to cope with water scarcity.

Abstract. Automated methods are important for automatically detecting mesoscale eddies in large volumes of altimeter data. While many algorithms have been proposed in the past, this paper presents a new method, called hybrid detection (HD), to enhance the eddy detection accuracy and the capability of recognizing eddy multi-core structures from maps of sea level anomaly (SLA). The HD method has integrated the criteria of the Okubo-Weiss (OW) method and the sea surface height-based (SSH-based) method, two commonly used eddy detection algorithms. Evaluation of the detection accuracy shows that the successful detection rate of HD is ∼ 96.6 % and the excessive detection rate is ∼ 14.2 %, which outperforms the OW and those methods using SLA extrema to identify eddies. The capability of recognizing multi-core structures and its significance in tracking eddy splitting or merging events have been illustrated by comparing with the detection results of different algorithms and observations in previous literature.

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China’s inland water quality has been markedly improved since 2003 notwithstanding regional variability.

Understanding the spatiotemporal dynamics of urban population is crucial for addressing a wide range of urban planning and management issues. Aggregated geospatial big data have been widely used to quantitatively estimate population distribution at fine spatial scales over a given time period. However, it is still a challenge to estimate population density at a fine temporal resolution over a large geographical space, mainly due to the temporal asynchrony of population movement and the challenges to acquiring a complete individual movement record. In this article, we propose a method to estimate hourly population density by examining the time-series individual trajectories, which were reconstructed from call detail records using BP neural networks. We first used BP neural networks to predict the positions of mobile phone users at an hourly interval and then estimated the hourly population density using log-linear regression at the cell tower level. The estimated population density is linearly correlated with population census data at the sub-district level. Trajectory clustering results show five distinct diurnal dynamic patterns of population movement in the study area, revealing spatially explicit characteristics of the diurnal commuting flows, though the driving forces of the flows need further investigation.

SUMMARY A super‐tall building with height of 420 m and 88 floors is located in central Hong Kong. Field monitoring of wind effects on the high‐rise structure was conducted during the passage of several typhoons on the basis of a wind and movement monitoring system installed in the building. Field data such as wind speed, wind direction, pressures on cladding, acceleration and displacement responses were simultaneously recorded during the typhoons and then analyzed. Typhoon wind parameters including turbulence intensity, gust factor, peak factor, turbulence integral length scale and power spectral density were presented and discussed. The dynamic properties of the high‐rise structure were determined from the field measurements and compared with those calculated at the design stage. The damping ratios of the super‐tall building were evaluated by a random decrement technique, which demonstrates amplitude‐dependent characteristics. The relationships between the structural dynamic responses and the approaching wind speed were analyzed. Wind tunnel tests were conducted to investigate the wind effects on the super‐tall building. The field‐measured acceleration responses were found to be consistent with the model test results. Finally, the serviceability performance of the super‐tall building during the typhoons was assessed on the basis of the field measurement results. The findings of the paper are expected to be of considerable interest and practical use to professionals and researchers involved in wind‐resistant designs of super‐tall buildings. Copyright © 2013 John Wiley & Sons, Ltd.

A direct asymmetric dearomative amination of tryptamines with O-(2,4-dinitrophenyl)hydroxylamine (DPH) was achieved using CuBr-bisoxazoline complex as a catalyst, affording 3a-amino-pyrroloindolines in good to excellent enantioselectivity under mild reaction conditions. Furthermore, the synthetic value of this method was demonstrated in the total synthesis of (-)-psychotriasine in a highly concise manner.