Dataset Information

The green view dataset for the capital of Finland, Helsinki.

ABSTRACT: Recent studies have incorporated human perspective methods like making use of street view images and measuring green view in addition to more traditional ways of mapping city greenery [1]. Green view describes the relative amount of green vegetation visible at street level and is often measured with the green view index (GVI), which describes the percentage of green vegetation in a street view image or images of a certain location [2]. The green view dataset of Helsinki was created as part of the master's thesis of Akseli Toikka at the University of Helsinki [3]. We calculated the GVI values for a set of locations on the streets of Helsinki using Google Street View (GSV) 360° panorama images from summer months (May through September) between 2009 and 2017. From the available images, a total of 94 454 matched the selection criteria. These were downloaded using the Google application programming interface (API). We calculated the GVI values from the panoramas based on the spectral characteristics of green vegetation in RGB images. The result was a set of points along the street network with GVI values. By combining the point data with the street network data of the area, we generated a dataset for GVI values along the street centre lines. Streets with GVI points within a threshold distance of 30 meters were given the average of the GVI values of the points. For the streets with no points in the vicinity (∼67%), the land cover data from the area was used to estimate the GVI, as suggested in the thesis [3]. The point and street-wise data are stored in georeferenced tables that can be utilized for further analyses with geographical information systems.

SUBMITTER: Toikka A

PROVIDER: S-EPMC7200931 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Most tick-related studies in Europe have been conducted in nonurban areas, but ticks and tick-borne pathogens also occur in urban green spaces. From a public health perspective, risks regarding tick-borne infections should be studied in these urban areas, where contacts between infected ticks and humans may be more frequent than elsewhere, due to high human activity. We examined the risk of encountering an infected tick in urban green spaces in Helsinki, Finland. We collected ticks at nine sites throughout Helsinki, recorded the prevalence of several pathogens and identified areas with a high potential for contacts between infected ticks and humans. Moreover, we explored the relationship between the density of Borrelia burgdorferi sensu lato-infected ticks and locally diagnosed cases of borreliosis and compared the potential for human-tick encounters in Helsinki to those in nonurban areas in south-western Finland. During 34.8 km of cloth dragging, 2,417 Ixodes ricinus were caught (402 adults, 1,399 nymphs and 616 larvae). From analysed nymphs, we found 11 distinct tick-borne pathogens, with 31.5% of nymphs carrying at least one pathogen. Tick activity was highest in August and September, leading to the density of nymphs infected with B. burgdorferi s.l., and concurrently infection risk, to also be highest during this time. Nymph densities varied between the sampling sites, with obvious implications to spatial variation in infection risk. While ticks and tick-borne pathogens were found in both Helsinki and nonurban areas in south-western Finland, the estimates of human activity were generally higher in urban green spaces, leading to a higher potential for human-tick contacts therein. The presence of ticks and tick-borne pathogens and high local human activity in urban green spaces suggest that they form potential foci regarding the acquisition of tick-borne infections. Risk areas within cities should be identified and knowledge regarding urban ticks increased.

Project description:Antimicrobial resistance profiling of pathogens helps to identify the emergence of rare or new resistance threats and prioritize possible actions to be taken against them. The analysis of wastewater (WW) can reveal the circulation of antimicrobial-resistant bacteria (ARB) and antimicrobial resistance genes (ARG) among the catchment communities. Here, we analyzed WW influent samples to determine the prevalence of carbapenemase genes-carrying Gram-negative bacteria (Carba-GNB) in Helsinki, Finland. This study set important historical reference points from the very early stage of the carbapenemase era, during the period 2011-2012. A total of 405 bacterial isolates grown on CHROMagarKPC (n = 195) and CHROMagarESBL (n = 210) from WW influent samples were collected between October 2011 and August 2012 and were analyzed. The bacterial DNA from the isolates was extracted, and the prevalence of carbapenemases genes bla KPC, bla NDM, bla GES, bla OXA-48, bla IMP, bla IMI, and bla VIM were screened with multiplexed PCR. All carbapenemase-positive isolates were identified taxonomically to species or genus level with matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). The nucleic acid extraction was successful for 399 isolates, of which 59 (14.8%) were found to carry carbapenemase genes. A total of 89.8% of the carbapenemase positive isolates (53 out of 59) were obtained from CHROMagarKPC plates and only 10.2% (six out of 59) were obtained from CHROMagar ESBL plates. Among the Carba-GNB isolates, 86.4% were bla GES (51 out of 59), 10.2% were bla KPC (six out of 59), and 3.4% were bla VIM (two out of 59). The most common carba-gene, bla GES, was carried by 10 different bacterial species, including Aeromonas spp., Enterobacter spp., and Kluyvera spp.; the bla KPC gene was carried by Escherichia coli, Klebsiella pneumoniae, and Kluyvera cryocescens; and the bla VIM gene was carried by Aeromonas hydrophila/caviae and Citrobacter amalonaticus. This study emphasizes that wastewater surveillance (WWS) can be an additional tool for monitoring antimicrobial resistance (AMR) at the population level.

Dataset Information

The green view dataset for the capital of Finland, Helsinki.

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