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Over the past decade, nighttime lights have become a widely used proxy for measuring economic activity. This paper examines the potential for high frequency nighttime lights data to provide "near real-time" tracking of the economic impacts of the COVID-19 crisis in Morocco. At the national level, there exists a strong correlation between quarterly movements in Morocco's overall nighttime light intensity and movements in its real GDP. This finding supports the use of lights data to track the economic impacts of the COVID-19 crisis at higher temporal frequencies and at the subnational level, for which GDP data are unavailable. Consistent with large economic impacts of the crisis, Morocco experienced a large drop in the overall intensity of its lights in March 2020, from which it has subsequently struggled to recover, following the country's first COVID-19 case and the introduction of strict lockdown measures. At the subnational level, while all regions shared in March's national decline in nighttime light intensity, Rabat - Sale - Kenitra, Tanger - Tetouan - Al Hoceima, and Fes - Meknes suffered much larger declines than others. Since then, the relative effects of the COVID-19 shock across regions have largely persisted. Overall, the results suggest that, at least for Morocco, changes in nighttime lights can help to detect the timing of changes in the direction of real GDP, but caution is needed in using lights data to derive precise quantitative estimates of changes in real GDP.

Conflict and Development --- Coronavirus --- COVID-19 --- Disaster Management --- Disease Control and Prevention --- Economic Activity --- Hazard Risk Management --- Health, Nutrition and Population --- Industrial Economics --- Industry --- Nighttime Light Intensity --- Real-Time Monitoring

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This paper estimates the impact of a differential relaxation of COVID-19 containment policies on aggregate economic activity in India. Following a uniform national lockdown, the Government of India classified all districts into three zones with varying containment measures in May 2020. Using a difference-in-differences approach, the paper estimates the impact of these restrictions on nighttime light intensity, a standard high-frequency proxy for economic activity. To conduct this analysis, pandemic-era, district-level data from a range of novel sources are combined - monthly nighttime lights from global satellites; Facebook's mobility data from individual smartphone locations; and high-frequency, household-level survey data on income and consumption, supplemented with data from the Indian Census and the Reserve Bank of India. The analysis finds that nighttime light intensity in May was 12.4 percent lower for districts with the most severe restrictions and 1.7 percent lower for districts with intermediate restrictions, compared with districts with the least restrictions. The differences were largest in May, when the different policies were in place, and slowly tapered in June and July. Restricted mobility and lower household income are plausible channels for these results. Stricter containment measures had larger impacts in districts with greater population density of older residents, as well as more services employment and bank credit.

Coronavirus --- COVID-19 --- Disease Containment --- Disease Control and Prevention --- Economic Activity --- Economic Stabilization --- Health, Nutrition and Population --- Lockdown --- Macroeconomics and Economic Growth --- Nighttime Light Intensity --- Policy Relaxation --- Re-Opening

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Studying and managing regional economic development in the current globalization era demands prompt, reliable, and comparable estimates for a region’s economic performance. Night-time lights (NTL) emitted from residential areas, entertainment places, industrial facilities, etc., and captured by satellites have become an increasingly recognized proxy for on-ground human activities. Compared to traditional indicators supplied by statistical offices, NTLs may have several advantages. First, NTL data are available all over the world, providing researchers and official bodies with the opportunity to obtain estimates even for regions with extremely poor reporting practices. Second, in contrast to non-standardized traditional reporting procedures, the unified NTL data remove the problem of inter-regional comparability. Finally, NTL data are currently globally available on a daily basis, which makes it possible to obtain these estimates promptly. In this book, we provide the reader with the contributions demonstrating the potential and efficiency of using NTL data as a proxy for the performance of regions.

Research & information: general --- population reorganization --- population density --- spatiotemporal patterns --- DMSP-OLS --- NPP-VIIRS --- Chongqing --- education inequality --- nighttime light --- urbanization --- sustainable development --- human development --- urban hotspot delineation --- Zipf’s law --- intra-urban scaling --- street nodes --- VIIRS imagery --- kernel density estimation --- Luojia 1-01 satellite --- spatial resolution --- searching radius threshold --- urban built-up area --- attention-augmented CNN --- nightlight --- fine-grained GDP estimation --- daytime satellite imagery --- arbitrary area representation --- Luojia 1-01 --- MNUACI --- urban area --- urban remote sensing --- VIIRS --- DMSP --- GDP --- nighttime lights --- cross-sectional --- time-series --- economic statistics --- n/a --- functional urban areas (FUAs) --- boundaries --- multiple regression modelling --- artificial light-at-night (ALAN) --- optimal threshold --- shadow economy --- Iran --- sanctions --- JCPOA --- economic inequality --- nighttime light emissions --- spatial measurement --- Zipf's law

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• The aim of this Special Issue is to examine the current major topics concerning the use of social media and big data in sustainable tourism practices and to encourage interdisciplinary discussion among researchers regarding these issues. • This Special Issue covers all relevant areas of the debate, including 15 selected papers based on the following core ideas: smart tourism and big data, social media in the tourism industry, and online reviews and tourist behaviors. • This Special Issue discusses wide-ranging topics and research questions with regard to the smart tourism city, the impact of social media, online reviews, and tourist behaviors, and it represents a call to action for scholars to engage with broader social issues.

Humanities --- Social interaction --- shared short-term rental --- sustainable tourism --- online reviews --- purchase decisions --- social networks --- social media --- Twitter --- tourism --- volunteered geographic information --- OpenStreetMap --- nighttime light remote sensing --- social media usage characteristics --- Big Five personality traits --- personality characteristics --- social characteristics --- information characteristics --- e-WOM --- trust --- brand equity --- brand awareness --- brand image --- topic modeling --- latent Dirichlet allocation --- tourism 4.0 --- online travel agency --- online review --- text analytics --- improve customer satisfaction --- inductive approach --- dimensions of interest --- era of big data --- cultural consensus --- cultural consonance --- online hotel reviews --- trustworthiness --- technology acceptance model --- Generation Y --- overtourism --- organization-public relationship --- place-visitor relationship --- crowdfunding --- consumption value --- inner innovativeness --- perceived risk --- the intention to visit festival --- oblique photography --- mobile applications --- musicals --- city branding --- SNSs --- orientation --- smart tourism city --- smart tourism --- smart city --- sustainable development --- COVID-19 --- tourist destinations --- destination image --- stakeholders --- rural tourism --- social networking service --- theory of planned behavior --- social media use --- graffiti --- text mining --- social network analysis --- travel reality variety program --- viewing motivation --- viewing satisfaction --- presence --- attitude toward tourism destination --- spatial variance --- multiscale GWR --- sharing economy --- Airbnb --- shared short-term rental --- sustainable tourism --- online reviews --- purchase decisions --- social networks --- social media --- Twitter --- tourism --- volunteered geographic information --- OpenStreetMap --- nighttime light remote sensing --- social media usage characteristics --- Big Five personality traits --- personality characteristics --- social characteristics --- information characteristics --- e-WOM --- trust --- brand equity --- brand awareness --- brand image --- topic modeling --- latent Dirichlet allocation --- tourism 4.0 --- online travel agency --- online review --- text analytics --- improve customer satisfaction --- inductive approach --- dimensions of interest --- era of big data --- cultural consensus --- cultural consonance --- online hotel reviews --- trustworthiness --- technology acceptance model --- Generation Y --- overtourism --- organization-public relationship --- place-visitor relationship --- crowdfunding --- consumption value --- inner innovativeness --- perceived risk --- the intention to visit festival --- oblique photography --- mobile applications --- musicals --- city branding --- SNSs --- orientation --- smart tourism city --- smart tourism --- smart city --- sustainable development --- COVID-19 --- tourist destinations --- destination image --- stakeholders --- rural tourism --- social networking service --- theory of planned behavior --- social media use --- graffiti --- text mining --- social network analysis --- travel reality variety program --- viewing motivation --- viewing satisfaction --- presence --- attitude toward tourism destination --- spatial variance --- multiscale GWR --- sharing economy --- Airbnb

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• The aim of this Special Issue is to examine the current major topics concerning the use of social media and big data in sustainable tourism practices and to encourage interdisciplinary discussion among researchers regarding these issues. • This Special Issue covers all relevant areas of the debate, including 15 selected papers based on the following core ideas: smart tourism and big data, social media in the tourism industry, and online reviews and tourist behaviors. • This Special Issue discusses wide-ranging topics and research questions with regard to the smart tourism city, the impact of social media, online reviews, and tourist behaviors, and it represents a call to action for scholars to engage with broader social issues.

shared short-term rental --- sustainable tourism --- online reviews --- purchase decisions --- social networks --- social media --- Twitter --- tourism --- volunteered geographic information --- OpenStreetMap --- nighttime light remote sensing --- social media usage characteristics --- Big Five personality traits --- personality characteristics --- social characteristics --- information characteristics --- e-WOM --- trust --- brand equity --- brand awareness --- brand image --- topic modeling --- latent Dirichlet allocation --- tourism 4.0 --- online travel agency --- online review --- text analytics --- improve customer satisfaction --- inductive approach --- dimensions of interest --- era of big data --- cultural consensus --- cultural consonance --- online hotel reviews --- trustworthiness --- technology acceptance model --- Generation Y --- overtourism --- organization-public relationship --- place-visitor relationship --- crowdfunding --- consumption value --- inner innovativeness --- perceived risk --- the intention to visit festival --- oblique photography --- mobile applications --- musicals --- city branding --- SNSs --- orientation --- smart tourism city --- smart tourism --- smart city --- sustainable development --- COVID-19 --- tourist destinations --- destination image --- stakeholders --- rural tourism --- social networking service --- theory of planned behavior --- social media use --- graffiti --- text mining --- social network analysis --- travel reality variety program --- viewing motivation --- viewing satisfaction --- presence --- attitude toward tourism destination --- spatial variance --- multiscale GWR --- sharing economy --- Airbnb