A travel time matrix data set for the Helsinki region 2023 that is sensitive to time, mode and interpersonal differences, and uses open data and novel open-source software.

Travel times between different locations form the basis for most contemporary measures of spatial accessibility. Travel times allow to estimate the potential for interaction between people and places, and is therefore a vital measure for understanding the functioning, sustainability, and equity of cities. Here, we provide an open travel time matrix dataset that describes travel times between the centroids of all cells in a grid (N = 13,132) covering the metropolitan area of Helsinki, Finland.

Cyclists' exposure to air pollution, noise, and greenery: a population-level spatial analysis approach.

Urban travel exposes people to a range of environmental qualities with significant health and wellbeing impacts. Nevertheless, the understanding of travel-related environmental exposure has remained limited. Here, we present a novel approach for population-level assessment of multiple environmental exposure for active travel.

A 24-hour population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland.

In this article, we present temporally dynamic population distribution data from the Helsinki Metropolitan Area, Finland, at the level of 250 m by 250 m statistical grid cells. An hourly population distribution dataset is provided for regular workdays (Mon - Thu), Saturdays and Sundays. The data are based on aggregated mobile phone data collected by the biggest mobile network operator in Finland.

Quantitative conservation geography.

Ongoing biodiversity loss represents the erosion of intrinsic value of living nature, reduces the contributions nature provides to people, and undermines efforts to move towards sustainability. We propose the recognition of quantitative conservation geography as a subfield of conservation science that studies where, when, and what conservation actions could be implemented in order to mitigate threats and promote sustainable people-nature interactions. We outline relevant methods and data needed in quantitative conservation geography.

COVID-19 is spatial: Ensuring that mobile Big Data is used for social good.

The mobility restrictions related to COVID-19 pandemic have resulted in the biggest disruption to individual mobilities in modern times. The crisis is clearly spatial in nature, and examining the geographical aspect is important in understanding the broad implications of the pandemic. The avalanche of mobile Big Data makes it possible to study the spatial effects of the crisis with spatiotemporal detail at the national and global scales.

Environmental exposure during travel: A research review and suggestions forward.

Daily travel through the urban fabric exposes urban dwellers to a range of environmental conditions that may have an impact on their health and wellbeing. Knowledge about exposures during travel, their associations with travel behavior, and their social and health outcomes are still limited. In our review, we aim to explain how the current environmental exposure research addresses the interactions between human and environmental systems during travel through their spatial, temporal and contextual dimensions.

Exploring human-nature interactions in national parks with social media photographs and computer vision.

Understanding the activities and preferences of visitors is crucial for managing protected areas and planning conservation strategies. Conservation culturomics promotes the use of user-generated online content in conservation science. Geotagged social media content is a unique source of in situ information on human presence and activities in nature.

Using Wikipedia to measure public interest in biodiversity and conservation.

The recent growth of online big data offers opportunities for rapid and inexpensive measurement of public interest. Conservation culturomics is an emerging research area that uses online data to study human-nature relationships for conservation. Methods for conservation culturomics, though promising, are still being developed and refined.

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

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].

Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) statement.

Spatial lifecourse epidemiology is an interdisciplinary field that utilizes advanced spatial, location-based, and artificial intelligence technologies to investigate the long-term effects of environmental, behavioural, psychosocial, and biological factors on health-related states and events and the underlying mechanisms. With the growing number of studies reporting findings from this field and the critical need for public health and policy decisions to be based on the strongest science possible, transparency and clarity in reporting in spatial lifecourse epidemiologic studies is essential. A task force supported by the International Initiative on Spatial Lifecourse Epidemiology (ISLE) identified a need for guidance in this area and developed a Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) Statement.

Longitudinal spatial dataset on travel times and distances by different travel modes in Helsinki Region.

Comparable data on spatial accessibility by different travel modes are frequently needed to understand how city regions function. Here, we present a spatial dataset called the Helsinki Region Travel Time Matrix that has been calculated for 2013, 2015 and 2018. This longitudinal dataset contains travel time and distance information between all 250 metres statistical grid cell centroids in the Capital Region of Helsinki, Finland.

Assessing global popularity and threats to Important Bird and Biodiversity Areas using social media data.

Understanding worldwide patterns of human use of sites of international significance for biodiversity conservation is crucial for meeting global conservation targets. However, robust global datasets are scarce. In this study, we used social media data, mined from Flickr and Twitter, geolocated in Important Bird and Biodiversity Areas (IBAs) to assess i) patterns of popularity; ii) relationships of this popularity with geographical and biological variables; and iii) identify sites under high pressure from visitors.

Identifying global centers of unsustainable commercial harvesting of species.

Overexploitation is one of the main threats to biodiversity, but the intensity of this threat varies geographically. We identified global concentrations, on land and at sea, of 4543 species threatened by unsustainable commercial harvesting. Regions under high-intensity threat (based on accessibility on land and on fishing catch at sea) cover 4.

Instagram, Flickr, or Twitter: Assessing the usability of social media data for visitor monitoring in protected areas.

Social media data is increasingly used as a proxy for human activity in different environments, including protected areas, where collecting visitor information is often laborious and expensive, but important for management and marketing. Here, we compared data from Instagram, Twitter and Flickr, and assessed systematically how park popularity and temporal visitor counts derived from social media data perform against high-precision visitor statistics in 56 national parks in Finland and South Africa in 2014. We show that social media activity is highly associated with park popularity, and social media-based monthly visitation patterns match relatively well with the official visitor counts.

Social media reveal that charismatic species are not the main attractor of ecotourists to sub-Saharan protected areas.

Charismatic megafauna are arguably considered the primary attractor of ecotourists to sub-Saharan African protected areas. However, the lack of visitation data across the whole continent has thus far prevented the investigation of whether charismatic species are indeed a key attractor of ecotourists to protected areas. Social media data can now be used for this purpose.

Health research needs more comprehensive accessibility measures: integrating time and transport modes from open data.

Background: In this paper, we demonstrate why and how both temporality and multimodality should be integrated in health related studies that include accessibility perspective, in this case healthy food accessibility. We provide evidence regarding the importance of using multimodal spatio-temporal accessibility measures when conducting research in urban contexts and propose a methodological approach for integrating different travel modes and temporality to spatial accessibility analyses. We use the Helsinki metropolitan area (Finland) as our case study region to demonstrate the effects of temporality and modality on the results.

Global priorities for national carnivore conservation under land use change.

Mammalian carnivores have suffered the biggest range contraction among all biodiversity and are particularly vulnerable to habitat loss and fragmentation. Therefore, we identified priority areas for the conservation of mammalian carnivores, while accounting for species-specific requirements for connectivity and expected agricultural and urban expansion. While prioritizing for carnivores only, we were also able to test their effectiveness as surrogates for 23,110 species of amphibians, birds, mammals and reptiles and 867 terrestrial ecoregions.

Complementarity and Area-Efficiency in the Prioritization of the Global Protected Area Network.

Complementarity and cost-efficiency are widely used principles for protected area network design. Despite the wide use and robust theoretical underpinnings, their effects on the performance and patterns of priority areas are rarely studied in detail. Here we compare two approaches for identifying the management priority areas inside the global protected area network: 1) a scoring-based approach, used in recently published analysis and 2) a spatial prioritization method, which accounts for complementarity and area-efficiency.

What Data to Use for Forest Conservation Planning? A Comparison of Coarse Open and Detailed Proprietary Forest Inventory Data in Finland.

The boreal region is facing intensifying resource extraction pressure, but the lack of comprehensive biodiversity data makes operative forest conservation planning difficult. Many countries have implemented forest inventory schemes and are making extensive and up-to-date forest databases increasingly available. Some of the more detailed inventory databases, however, remain proprietary and unavailable for conservation planning.

Global protected area expansion is compromised by projected land-use and parochialism.

Protected areas are one of the main tools for halting the continuing global biodiversity crisis caused by habitat loss, fragmentation and other anthropogenic pressures. According to the Aichi Biodiversity Target 11 adopted by the Convention on Biological Diversity, the protected area network should be expanded to at least 17% of the terrestrial world by 2020 (http://www.cbd.

Evaluating the impact of distance measures on deforestation simulations in the fluvial landscapes of amazonia.

Land use and land cover change (LUCC) models frequently employ different accessibility measures as a proxy for human influence on land change processes. Here, we simulate deforestation in Peruvian Amazonia and evaluate different accessibility measures as LUCC model inputs. We demonstrate how the selection, and different combinations, of accessibility measures impact simulation results.