This page has only limited features, please log in for full access.

Unclaimed
Wei Zhu
Key Lab of Urban Environment and Health, Institute of Urban Environment Chinese Academy of Sciences, 85406 Xiamen, Fujian, China

Basic Info

Basic Info is private.

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 18 February 2021 in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Reads 0
Downloads 0

The COVID-19 pandemic caused drastic changes in human activities and nighttime light (NTL) at various scales, providing a unique opportunity for exploring the pattern of the extreme responses of human community. This study used daily NTL data to examine the spatial variations and temporal dynamics of human activities under the influence of COVID-19, taking Chinese mainland as the study area. The results suggest that the change in the intensity of NTL is not correlated to the number of confirmed cases, but reflects the changes in human activities and the intensity of epidemic prevention and control measures within a region. During the outbreak period, the major provincial capitals and urban agglomerations were affected by COVID-19 more than smaller cities. During the recovery, different regions showed different recovery processes. The cities in West and Northeast China recovered steadily while the recovery in coastal cities showed relatively greater fluctuations due to an increase in imported cases. Wuhan, the most seriously affected city in China, did not recover until the end of March. Nevertheless, as of 31 March, the overall NTL across China had recovered to an 89.5% level of the same period in the previous year. The high consistency between the big data of travel intensity and NTL further proved the validity of the results of this study. These findings imply that daily NTL data are effective for rapidly monitoring the dynamic changes in human activities, and can help evaluate the effects of control measures on human activities during major public health events.

ACS Style

Ting Lan; Guofan Shao; Lina Tang; Zhibang Xu; Wei Zhu; Lingyu Liu. Quantifying Spatiotemporal Changes in Human Activities Induced by COVID-19 Pandemic Using Daily Nighttime Light Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021, 14, 2740 -2753.

AMA Style

Ting Lan, Guofan Shao, Lina Tang, Zhibang Xu, Wei Zhu, Lingyu Liu. Quantifying Spatiotemporal Changes in Human Activities Induced by COVID-19 Pandemic Using Daily Nighttime Light Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2021; 14 (99):2740-2753.

Chicago/Turabian Style

Ting Lan; Guofan Shao; Lina Tang; Zhibang Xu; Wei Zhu; Lingyu Liu. 2021. "Quantifying Spatiotemporal Changes in Human Activities Induced by COVID-19 Pandemic Using Daily Nighttime Light Data." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14, no. 99: 2740-2753.

Journal article
Published: 18 October 2018 in Sustainability
Reads 0
Downloads 0

The construction of a reasonable evaluation index system for low-carbon cities is an important part of China’s green development strategy in urban areas. In this study, based on the theoretical framework for the concept of low-carbon cities, the perspectives from three index systems—that is, the Drivers, Pressures, State, Impact, Response model of intervention (DPSIR), a complex ecosystem, and a carbon source/sink process—were integrated to extract common indicators from existing evaluation index systems for low-carbon cities. Subsequently, a standardized evaluation index system for low-carbon cities that contained five indicators—carbon emission, low carbon production, low carbon consumption, low-carbon policy, and social economic development—was established. Thereafter, Xiamen was selected for an empirical analysis by determining the indicator weight with an entropy weight method and by carrying out a comprehensive evaluation using a linear summation model. The results showed that the weights of the five selected primary indicators for the evaluation of low-carbon cities were: low-carbon production > low-carbon consumption > social economic development > carbon emission > low-carbon policy. Among the secondary indicators, the average entropy weight of “pollution emission” was the highest at 0.1591, while the average entropy weight of “urbanization rate” was the lowest at 0.0360. Furthermore, the comprehensive index of low-carbon development in 2015 was higher than that in 2010, while the rate of economic growth was greater than the growth rate of carbon emission, which indicated that the relative decoupling of economic growth from carbon emission was basically achieved.

ACS Style

Longyu Shi; Xueqin Xiang; Wei Zhu; Lijie Gao. Standardization of the Evaluation Index System for Low-Carbon Cities in China: A Case Study of Xiamen. Sustainability 2018, 10, 3751 .

AMA Style

Longyu Shi, Xueqin Xiang, Wei Zhu, Lijie Gao. Standardization of the Evaluation Index System for Low-Carbon Cities in China: A Case Study of Xiamen. Sustainability. 2018; 10 (10):3751.

Chicago/Turabian Style

Longyu Shi; Xueqin Xiang; Wei Zhu; Lijie Gao. 2018. "Standardization of the Evaluation Index System for Low-Carbon Cities in China: A Case Study of Xiamen." Sustainability 10, no. 10: 3751.