Advantages and Limitations of Using Mobile Apps for Protected Area Monitoring and Management

Digital technologies, including participatory Internet mapping, social media and smartphones, provide new avenues for research in outdoor recreation and tourism. The potential to reach a greater audience and collect visitation data on a broader scale, with less costs than traditional paper surveys, are key advantages that have increased the use of these novel technologies. Using of mobile apps for data collection is still at the experimental stage. We evaluate previous attempts to use apps for monitoring recreation and tourism in protected areas, as an alternative to other in situ or online methods. We present a pilot study implemented in Jotunheimen National Park (Norway), where we developed a mobile app for visitor monitoring and real-time mapping of values and experiences. We present the lessons learned, give suggestions on how and for what apps can be used, and discuss the advantages and limitations of using smartphones for visitor monitoring in protected areas.     

Automatic analysis of positional plausibility for points of interest in OpenStreetMap using coexistence patterns

In the past decade, Volunteered Geographic Information (VGI) has emerged as a new source of geographic information, making it a cheap and universal competitor to existing authoritative data sources. The growing popularity of VGI platforms, such as OpenStreetMap (OSM), would trigger malicious activities such as vandalism or spam. Similarly, wrong entries by unexperienced contributors adds to the complexities and directly impact the reliability of such databases. While there are some existing methods and tools for monitoring OSM data quality, there is still a lack of advanced mechanisms for automatic validation. This paper presents a new recommender tool which evaluates the positional plausibility of incoming POI registrations in OSM by generating near real-time validation scores. Similar to machine learning techniques, the tool discovers, stores and reapplies binary distance-based coexistence patterns between one specific POI and its surrounding objects. To clarify the idea, basic concepts about analysing coexistence patterns including design methodology and algorithms are covered in this context. Furthermore, the results of two case studies are presented to demonstrate the analytical power and reliability of the proposed technique. The encouraging results of this new recommendation tool elevates the need for developing reliable quality assurance systems in OSM and other VGI projects.     

Travel impedance agreement among online road network data providers

ABSTRACT

Online mapping providers offer unprecedented access to spatial data and analytical tools; however, the number of analytical queries that can be requested is usually limited. As such, Volunteered Geographic Information (VGI) services offer a viable alternative, provided that the quality of the underlying spatialtheir data is adequate. In this paper, we evaluate the agreement in travel impedance between estimates from MapQuest Open, which embraces OpenStreetMap (OSM) data–a is based on VGI datasetfrom OpenStreetMap (OSM), and estimates from two other popular commercial providers, namely Google Maps? and ArcGIS? Online. Our framework is articulated around three components, which simulates potentialcalculates shortest routes, estimates their travel impedance using a routing service Application Program Interface (API), and extracts the average number of contributors for each route. We develop an experimental setup with a simulated dataset for the state of North Carolina. Our results suggest a strong correlation of travel impedance among all three road network providers. and that travel impedanceThe agreement is the greatest in areas with a denser road network and the smallest for routes of shorter distances. Most importantly, tTravel estimates from MapQuest Open are nearly identical to both commercial providers when the average number of OSM contributors along the route is larger. The latter finding contributes to a growing body of literature on Linus’s law, recognizing that a larger group of contributors holds the potential to validate and correct inherent errors to the source dataset.     

Relationships between spatial and non-spatial preferences and place-based values in national forests

The management of multiple-use public lands such as national forests in the U.S. is controversial because of the wide range of potential uses and contested public values for these lands. Previous research on national forest values and management preferences examined these relationships non-spatially. The development of public participation GIS (PPGIS) and volunteered geographic information (VGI) systems provide new opportunities to assess spatial relationships between perceived national forest values and preferred uses. This research used empirical data collected from a PPGIS/VGI study for three national forests in California to examine spatial and non-spatial relationships between place-based forest values and preferred uses. The relationships suggest public participants translated some of their non-spatial forest values and preferences into behavioral choices when mapping place-specific values and preferred uses. The empirical relationships between place-based forest values and uses were generally consistent with previous survey research results. Positive, non-spatial attitudes toward extractive uses of national forests were correlated with participant mapping of economic values and related extractive uses, while nonmaterial forest attitudes were correlated with participant mapping of amenity values and conservation-related uses. Further, spatial preferences for extractive forest uses such as timber harvesting were mapped proximate to economic values, while nonmaterial spatial preferences were mapped proximate to amenity-related forest values. PPGIS offers the potential to translate philosophical and ideology-based national forest preferences into place-specific discourse about forest management activities where public accommodation may be more achievable.     

Quality assessment of building footprint data using a deep autoencoder network

Volunteered geographic information (VGI), OpenStreetMap (OSM), has been used in many applications, especially when official spatial data are unavailable or outdated. However, the quality of VGI remains a valid concern. In this paper, we use the matched results between OSM building footprints and official data as the samples for training an autoencoder network, which encodes and reconstructs the sample populations according to unknown complex multivariate probability distributions. Then, the OSM data are assessed based on the theory that small probability samples contribute little to the autoencoder network and that they can be recognized by the higher reconstructed errors during training. In the method described here, the selected measures, including data completeness, positional accuracy, shape accuracy, semantic accuracy and orientation consistency between OSM and official data, are used as the inputs for a deep autoencoder network. Finally, building footprint data from Toronto, Canada, are evaluated, and experiments show that the proposed method can assess the OSM data comprehensively, objectively and accurately.     

Measuring Change in Place Values for Environmental and Natural Resource Planning Using Public Participation GIS (PPGIS): Results and Challenges for Longitudinal Research

Landscape values are a type of place value and are identified and mapped using public participation GIS (PPGIS). PPGIS engages nonexperts to identify important spatial information for environmental or natural resource planning. In 1998, we used PPGIS to identify landscape values for the Chugach National Forest (Alaska) plan revision process. In 2012, we conducted a longitudinal study of the same national forest using Internet PPGIS to identify changes in landscape values. The empirical results indicate stability in landscape values both in importance and spatial distribution. However, the use of different PPGIS methods (paper map vs. Internet) in the longitudinal study also introduced challenges in interpreting and explaining the spatial results. We discuss trade-offs in conducting longitudinal PPGIS research using mixed methods. PPGIS appears well suited for public lands planning, and national forest planning in particular, but barriers to use, such as regulatory approval, remain formidable.     

Analysis of collaboration networks in OpenStreetMap through weighted social multigraph mining

This paper aims to qualify the behaviour of contributors to OpenStreetMap (OSM), a volunteered geographic information (VGI) project, through a multigraph approach. The main purpose is to reproduce contributor’s interactions in a more comprehensive way. First, we define a multigraph that combines existing spatial collaboration networks from the literature with new graphs that illustrate collaboration based on specific aspects of the VGI modes of contribution through semantics, geometry and topology. Indeed, the ways that contributors interact with one another through editing, completion, or even consumption may provide additional information on each user’s operation mode and therefore, on the quality of the contributed data. Social collaborations drawn from indirect criteria – for example, comparisons between contributors’ activity areas – can also be contemplated under another network. Second, the resulting multigraph is analysed using data mining approaches to characterise individuals and identify behavioural groups. The implementation of a multiplex network based on an OSM data sample and an initial analysis make it possible to identify useful behaviours for data qualification. The initial results characterise some contributors as pioneers, moderators and truthful contributors, according to their special roles in the graphs. Mapping elements that include these contributors’ participation are likely to be reliable data     

The importance of spatial nested data in understanding the relationship between visitor use and landscape impacts

As managers and researchers of protected natural areas continue to seek balance in promoting visitor use but limiting negative experiential and natural resource impacts, the integration of social and physical spatial data may play a critical role in understanding how visitors and the community interface with the landscape within these protected areas. These spatial considerations are important for inventorying, monitoring, and managing the conditions of natural resources within parks. Specifically related to the visitor impacts of natural resources in parks are the use and condition of multiple-use trails. Technology such as GPS and GIS may allow for a unique assessment of the relationship between factors that influence this resource. This paper focuses on how visitor use distribution (measured through GPS tracking), activity type, and trail design influence the impacts to trail conditions. This paper also addresses statistical concerns related to spatial dependency. Results suggest that failure to account for spatial dependency can lead to erroneous Type I findings. Additionally, activity type (specifically horseback riders) and trail design were found to best predict trail impacts when controlling for spatial dependency.     

VGTrust: measuring trust for volunteered geographic information

Volunteered Geographic Information (VGI) has emerged as a large, up-to-date, and easily accessible data source. VGI can allow authoritative mapping agencies to undertake continuous improvement of their own data, adding a currency dimension previously unattainable due to high associated costs. VGI also benefits scientific and social research by facilitating quick and low-cost research data capture by the public. VGI, however, through its diversity of authorship, presents a quality assurance risk to the use of this data. This research presents a formulaic model that addresses VGI quality issues, by quantifying trust in VGI. Our ‘VGTrust’ model assesses information about a data author, and the spatial and temporal trust associated with the data they create, to produce an overall VGTrust rating metric. This metric is both easy to understand and interpret. A facilitated case study, ‘Building Our Footprints’ is presented which tests the feasibility of VGTrust model in a real-world data capture exercise run by Land Information New Zealand, New Zealand’s mapping organisation. By overcoming the trust issues in VGI, this research will allow the integration of VGI and authoritative data and potentially expand the application of VGI, thereby leveraging the power of the crowd for productive and innovative re-use.     

Coverage inequality and quality of volunteered geographic features in Chinese cities: Analyzing the associated local characteristics using geographically weighted regression

The volunteered geographic information (VGI) gains increasing popularity with the general public and scientific community. However, the optimism about the VGI has been tempered by two critical issues: inequality in data coverage (social justice) and data quality. It therefore requires a better understanding of the mechanism driving VGI contributions and content quality. With a case of China, this paper demonstrates one potential avenue, examining the associations between VGI coverage/quality and local demographic and socioeconomic characteristics. In particular, VGI data are harvested from the OpenStreetMap for 333 cities in China. VGI coverage is measured by the total volume of different geographic features (point, line and polygon); and VGI quality is described from two aspects: completeness and accuracy. Geographically weighted regression (GWR) shows that both demographic and socioeconomic factors have statistically significant influences on VGI coverage and quality. More specifically, densely populous cities with more young, educated and non-agricultural people enjoy higher VGI coverage and quality. Cities with lower VGI coverage and quality are primarily located in the western and southwestern regions where the ethnic minorities concentrate. High VGI coverage and quality are possibly observed in economically developed cities with high marketization degree. Besides, possibility of high VGI coverage and quality occurs in cities with more labor in scientific research and greater percentage of employers in the tertiary industry. The GWR also demonstrates that the strength and nature of the obtained relationships vary across the 333 cities. The spatial non-stationary relationships may partially answer for the controversial empirical conclusions in earlier case studies at different scales. Quantitative analysis (Gini index, Lorenz curve and Moran's I index) further evidences the great inequality in VGI coverage and quality. It can be safely inferred that the differences in engagement and use of VGI, as a new digital divide, can raise troubling concerns on the social justice implications.     

Combining conventional and volunteered geographic information to identify and model forest recreational resources

It is now common for researchers in natural resource management and economics to develop spatial models of recreation demand for the purposes of valuation and planning. Such an approach has significant advantages but requires access to relatively detailed spatial data. In the absence of official data concerning resources, researchers may benefit from employing increasingly available volunteered geographic information (VGI) as a central source of data or to complement more traditional data sources. This paper describes the development of a map of forest recreational resources in Ireland by combining conventional forest cover data and VGI of recreational trails. As an extension the new map is combined with household survey data to explore respondent's ability to identify local recreational forests and models the impact of the characteristics of the closest forest on their annual visitation. The results suggest that VGI can be a useful resource to researchers in both the identification and characterisation of recreational resources. In addition, this paper finds that the distance to and characteristics of the nearest recreational forest has a significant impact on total annual visitation by members of the public.     

Assessing similarity matching for possible integration of feature classifications of geospatial data from official and informal sources

One difficulty in integrating geospatial data sets from different sources is variation in feature classification and semantic content of the data. One step towards achieving beneficial semantic interoperability is to assess the semantic similarity among objects that are categorised within data sets. This article focuses on measuring semantic and structural similarities between categories of formal data, such as Ordnance Survey (OS) cartographic data, and volunteered geographic information (VGI), such as that sourced from OpenStreetMap (OSM), with the intention of assessing possible integration. The model involves ‘tokenisation’ to search for common roots of words, and the feature classifications have been modelled as an XML schema labelled rooted tree for hierarchical analysis. The semantic similarity was measured using the WordNet::Similarity package, while the structural similarities between sub-trees of the source and target schemas have also been considered. Along with dictionary and structural matching, the data type of the category itself is a comparison variable. The overall similarity is based on a weighted combination of these three measures. The results reveal that the use of a generic similarity matching system leads to poor agreement between the semantics of OS and OSM data sets. It is concluded that a more rigorous peer-to-peer assessment of VGI data, increasing numbers and transparency of contributors, the initiation of more programs of quality testing and the development of more directed ontologies can improve spatial data integration.     

Analysis of positional uncertainty of road networks in volunteered geographic information with a statistically defined buffer-zone method

Volunteered geographic information (VGI) is crowdsourced information that can enrich and enhance research and applications based on geo-referenced data. However, the quality of VGI is of great concern, and positional accuracy is a fundamental basis for the VGI quality assurance. A buffer-zone method can be used for its assessment, but the buffer radius in this technique is subjectively specified; as result, different selections of the buffer radius lead to different positional accuracies. To solve this problem, a statistically defined buffer zone for the positional accuracy assessment in VGI is proposed in this study. To facilitate practical applications, we have also developed an iterative method to obtain a theoretically defined buffer zone. In addition to the positional accuracy assessment, we have derived a measure of positional quality, which comprises the assessment of positional accuracy and the level of confidence in such assessment determined with respect to a statistically defined buffer zone. To illustrate and substantiate the theoretical arguments, both numerical simulations and real-life experiments are performed using OpenStreetMap. The experimental results confirm the high significance of the proposed statistical approach to the buffer zone-based assessment of the positional uncertainty in VGI.     

Volunteered geographic information research in the first decade: a narrative review of selected journal articles in GIScience

ABSTRACT

More than 10 years have passed since the coining of the term volunteered geographic information (VGI) in 2007. This article presents the results of a review of the literature concerning VGI. A total of 346 articles published in 24 international refereed journals in GIScience between 2007 and 2017 have been reviewed. The review has uncovered varying levels of popularity of VGI research over space and time, and varying interests in various sources of VGI (e.g. OpenStreetMap) and VGI-related terms (e.g. user-generated content) that point to the multi-perspective nature of VGI. Content-wise, using latent Dirichlet allocation (LDA), this study has extracted 50 specific research topics pertinent to VGI. The 50 topics have been subsequently clustered into 13 intermediate topics and three overarching themes to allow a hierarchical topic review. The overarching VGI research themes include (1) VGI contributions and contributors, (2) main fields applying VGI, and (3) conceptions and envisions. The review of the articles under the three themes has revealed the progress and the points that demand attention regarding the individual topics. This article also discusses the areas that the existing research has not yet adequately explored and proposes an agenda for potential future research endeavors.     

自发地理信息在灾后恢复监测中的应用研究框架

文章探讨了如何有效利用自发地理信息（Volunteered Geographic Information, VGI）大数据促进灾后恢复监测工作。首先概述了国内外VGI相关研究的发展现状,明确了VGI用于灾后恢复监测研究的不足,然后提出了一个基于VGI大数据的灾后恢复监测应用的研究框架,助力于灾后恢复监测各类具体恢复目标（如旅游业恢复、工商业恢复、生活常态恢复）的实现。该研究框架包含数据获取、数据质量控制和数据挖掘3个核心组成部分。其中,数据获取对象以VGI为主,以传统官方权威数据为辅;数据质量控制主要是通过模糊逻辑专家系统和人工神经网络（深度学习）确保VGI适用性;数据挖掘则是以变革式范例为理论基础,利用定量和定性结合的方法调查灾区基建、经济和安全3个灾后恢复主要方面的状态。最后,文章还讨论了当前利用VGI大数据促进灾后恢复监测所存在的一些局限性,包括VGI来源的可持续性问题、各VGI平台应用程序接口的数据获取限制问题和VGI应用所涉及的用户隐私问题。     

OpenStreetMap and Food Security: A Case Study in the City of Philadelphia

OpenStreetMap (OSM) is an online public access database that allows for the collaborative collection of local geographic information. We employ this mapping technology to discuss a new social theory of poverty that moves away from income poverty to an economy that directly produces individuals' basic needs. Focusing on urban farming in Philadelphia as an example, we use OSM to support the argument that money, land, labor, and capital do not limit food production in the city. OSM is a type of “commons” that allows community members to depict features of interest to them that might otherwise be underrepresented in official or commercially produced maps such as Google Maps. Using the concept of facilitated volunteered geographic information (VGI) we developed an open framework for combining residents' local knowledge of food resources with expert guidance in data input. We believe this helps overcome problems with ad hoc data submission efforts to which collaborative online projects are susceptible. The program for “tagging” food resources in OSM was deployed in a public “map-a-thon” event we organized in Philadelphia, bringing together technical experts and food enthusiasts. To share the results, we present the Philly Fresh Food Map as an interactive online Web map that can be used and updated by the public.     

Exploring the relationship between density and completeness of urban building data in OpenStreetMap for quality estimation

OpenStreetMap (OSM) is a free spatial data source based on crowd sourced data. Although the OSM data have a range of applications, such as generating 3D models, and routing and navigation, quality issues are still significant concerns when using the data. Several studies have undertaken quality assessments by comparing OSM data with reference data. However, reference data are not always available due to high costs or licensing restrictions, and very few studies have quantitatively estimated the quality of OSM data under conditions where the corresponding reference data are not available. This study proposed the use of a building density (or building coverage ratio) indicator as a proxy, and designed a series of experiments involving different study areas to quantitatively explore the relationship between building density and building completeness for OSM data in urban areas. The residuals (estimated building completeness and reference building completeness) were also analyzed. Two main results were found from the experiments. (1) There was an approximate linear relationship between building density and building completeness in the OSM data. More precisely, the building completeness of OSM data was approximately 3.4–4 times the building density of OSM data. (2) Approximately 70–80% of the absolute residuals were smaller than 10%, and 80–90% of them were smaller than 20%. This shows that, in most cases, estimated building completeness was close to the corresponding reference building completeness. Therefore, we concluded that the building density indicator is a potential proxy for the quantitative completeness estimation of OSM building data in urban areas. The limitations of using this indicator were also addressed.     

Fine-resolution population mapping using OpenStreetMap points-of-interest

Data on population at building level is required for various purposes. However, to protect privacy, government population data is aggregated. Population estimates at finer scales can be obtained through areal interpolation, a process where data from a first spatial unit system is transferred to another system. Areal interpolation can be conducted with ancillary data that guide the redistribution of population. For population estimation at the building level, common ancillary data include three-dimensional data on buildings, obtained through costly processes such as LiDAR. Meanwhile, volunteered geographic information (VGI) is emerging as a new category of data and is already used for purposes related to urban management. The objective of this paper is to present an alternative approach for building level areal interpolation that uses VGI as ancillary data. The proposed method integrates existing interpolation techniques, i.e., multi-class dasymetric mapping and interpolation by surface volume integration; data on building footprints and points-of-interest (POIs) extracted from OpenStreetMap (OSM) are used to refine population estimates at building level. A case study was conducted for the city of Hamburg and the results were compared using different types of POIs. The results suggest that VGI can be used to accurately estimate population distribution, but that further research is needed to understand how POIs can reveal population distribution patterns.     

Toward mapping land-use patterns from volunteered geographic information

A large number of applications have been launched to gather geo-located information from the public. This article introduces an approach toward generating land-use patterns from volunteered geographic information (VGI) without applying remote-sensing techniques and/or engaging official data. Hence, collaboratively collected OpenStreetMap (OSM) data sets are employed to map land-use patterns in Vienna, Austria. Initially the spatial pattern of the landscape was delineated and thereafter the most relevant land type was assigned to each land parcel through a hierarchical GIS-based decision tree approach. To evaluate the proposed approach, the results are compared with the Global Monitoring for Environment and Security Urban Atlas (GMESUA) data. The results are compared in two ways: first, the texture of the resulting land-use patterns is analyzed using texture-variability analysis. Second, the attributes assigned to each land segment are evaluated. The achieved land-use map shows kappa indices of 91, 79, and 76% agreement for location in comparison with the GMESUA data set at three levels of classification. Furthermore, the attributes of the two data sets match at 81, 67, and 65%. The results demonstrate that this approach opens a promising avenue to integrate freely available VGI to map land-use patterns for environmental planning purposes.     

Location‐based social media behavior and perception: Views of university students

Location‐based social media (LBSM), a specific type of volunteered geographic information (VGI), is increasingly being used as a spatial data source for researchers in geography and related disciplines. Many questions, though, have been raised about VGI data in terms of its quality and its contributors. While a number of studies have explored users’ demographics and motivations for contribution to explicitly geographic forms of VGI, such as OpenStreetMap and Wikimapia, few have focused on these aspects with implicitly geographic forms of VGI, such as LBSM (for example, Twitter and Instagram). This study, through use of an online survey, specifically assesses the LBSM behavior and perceptions of 253 university students, noting differences found in gender, race, and academic standing. We find that the greatest differences are those between males and females, rather than through race or academic standing, and LBSM appears less biased than other forms of VGI.