Mining Flickr to Better Understand Tourist Behavior

2022 ◽  
pp. 686-707
Author(s):  
Maria Giovanna Brandano ◽  
Ludovico Iovino ◽  
Daniele Mantegazzi
Keyword(s):  
Temporal Distribution ◽  
Specific Area ◽  
Spatial And Temporal Distribution ◽  
Tourism Research ◽  
Tourist Attractions ◽  
Tourist Behavior ◽  
Automated Instrument ◽  
International Visitors ◽  
Tourism Services ◽  
Over Time

The aim of this chapter is to present an automated instrument collecting the enormous amount of information available online allowing urban planners, public administrations, tourism services suppliers, and researchers to easily understand the spatial and temporal distribution of tourist behaviors towards tourist attractions in a specific area. Geo-located photos provided by Flickr are used to identify points of interest (POIs). The developed application has been tested with data automatically retrieved and collected in L'Aquila province (Italy) during the years 2005-2018. Given the richness of information, these data are able to show how POIs changed over time and how tourists reacted to the 2009 earthquake. Results demonstrate the importance of using analytics and big data in tourism research. Moreover, by using the province of L'Aquila as pilot study, it emerges that tourist behaviors change over time and space, varying among different typologies of tourists: residents, domestic, and international visitors.

scholarly journals Spatial and temporal distribution of bats (Chiroptera) in bright summer nights

2016 ◽  
Vol 66 (1) ◽  
pp. 65-80 ◽  
Author(s):  
Tore Christian Michaelsen
Keyword(s):  
Spatial Distribution ◽  
Distribution Pattern ◽  
Temporal Distribution ◽  
Spatial Distribution Pattern ◽  
Spatial And Temporal Distribution ◽  
Pronounced Increase ◽  
Low Salinity ◽  
Non Linear ◽  
Over Time

Most bat species show plasticity in their choice of habitat and landscape. This study focuses on the distribution and activity of bats along the hillsides and onto the shores of a low salinity marine Norwegian fiord at 62°N. Ultrasound was recorded using D500 detectors in June and July at 42 different sites from the shoreline and up the hillsides to around 200 m. Detectors were placed in well-preserved woodlands. OnlyPipistrellussp., northern batsEptesicus nilssoniiand bats of theMyotisgenus were common. There was a clear non-linear spatial distribution pattern along these slopes, with a pronounced increase in the number of recorded bats at short distances from the shore. On all six nights, the detector closest to the shore had the highest number of recorded bats. A pattern was also seen in bat distribution over time.Pipistrellussp., northern bats andMyotisspecies all had a peak near the shore during the darkest part of the night, which is around 01.35 h in mid-summer at this latitude. At greater distances,Pipistrellussp. and northern bats had a peak around 40 minutes to one hour before the darkest part of the night, respectively. Here,Myotisspp. peaked about an hour after 01.35.

Digital pattern of life based tourist behaviour analysis system

2020 ◽  
Vol 5 ◽  
pp. 78-83
Author(s):  
S.A. Mikhailov ◽  
Keyword(s):  
Neural Networks ◽  
Tourism Industry ◽  
Data Sources ◽  
Tourist Behavior ◽  
Behaviour Analysis ◽  
Travel Experience ◽  
Digital Pattern ◽  
Analysis System ◽  
Tourist Behaviour ◽  
Tourism Services

The tourism industry has grown rapidly in recent years, and IT technology is also having a big impact on tourists. Tourism services, information generated by tourists and other sources can be used to build models of tourist behavior. These models can improve the travel experience in various ways. The author presents the system for analyzing tourist behavior based on the concept of a digital pattern of life. The system determines the tourist, possible data sources, ways of storing and presenting data, as well as tools for analyzing behavior. The author used artifi cial neural networks to analyze behavior from a dataset of tourist travels made with cars. One scenario of tourist behavior using artifi cial neural networks is presented. The collected results will be used for improving tourist services.

scholarly journals Intercepted Photosynthetically Active Radiation (PAR) and Spatial and Temporal Distribution of Transmitted PAR under High-Density and Super High-Density Olive Orchards

Agriculture ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 351
Author(s):  
Adolfo Rosati ◽  
Damiano Marchionni ◽  
Dario Mantovani ◽  
Luigi Ponti ◽  
Franco Famiani
Keyword(s):  
Spatial Variability ◽  
Photosynthetically Active Radiation ◽  
Temporal Distribution ◽  
High Density ◽  
Radiation Use Efficiency ◽  
Spatial And Temporal Distribution ◽  
Active Radiation ◽  
Use Efficiency ◽  
And Performance ◽  
Radiation Use

We quantified the photosynthetically active radiation (PAR) interception in a high-density (HD) and a super high-density (SHD) or hedgerow olive system, by measuring the PAR transmitted under the canopy along transects at increasing distance from the tree rows. Transmitted PAR was measured every minute, then cumulated over the day and the season. The frequencies of the different PAR levels occurring during the day were calculated. SHD intercepted significantly but slightly less overall PAR than HD (0.57 ± 0.002 vs. 0.62 ± 0.03 of the PAR incident above the canopy) but had a much greater spatial variability of transmitted PAR (0.21 under the tree row, up to 0.59 in the alley center), compared to HD (range: 0.34–0.43). This corresponded to greater variability in the frequencies of daily PAR values, with the more shaded positions receiving greater frequencies of low PAR values. The much lower PAR level under the tree row in SHD, compared to any position in HD, implies greater self-shading in lower-canopy layers, despite similar overall interception. Therefore, knowing overall PAR interception does not allow an understanding of differences in PAR distribution on the ground and within the canopy and their possible effects on canopy radiation use efficiency (RUE) and performance, between different architectural systems.

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