Openstreetmap

The appearance of OpenStreetMap (OSM) in 2004 sparked a phenomenon known as Volunteered Geographic Information (VGI). Today, VGI comes in many flavours (e.g. toponyms, GPS tracks, geo-tagged photos, micro-blogging or complete topographic maps) and from various sources. One subject that has attracted research interest from the early days of VGI is how good such datasets are and how to combine them with authoritative datasets. To this end, the paper explores three intertwined subjects from a quality point of view First, we examine the topo-semantic consistency of OSM data by evaluating a number of rules between polygonal and linear features and then paying special attention to quality of Points of Interest (POIs). A number of topo-semantic rules will be used to evaluate the valididy of features’ location. The focus then turns to the use of geo-tagged photos to evaluate the location and type of OSM data and to disambiguate topological issues that arise when different OSM layers overlap.

OpenStreetMap (OSM) is a free map of the world which can be edited by global volunteers. Existing studies have showed that completeness of OSM road data in some developing countries (e.g. China) is much lower, resulting in concern in utilizing the data in various applications. But very few have focused on investigating what types of road are still poorly mapped. This study aims not only to investigate the completeness of OSM road datasets in China but also to investigate what types of road (called omission roads) have not been mapped, which is achieved by referring to both Street Map and Street View. Sixteen prefecture-level divisions in the urban areas of Hubei (China) were used as study areas. Results showed that: (1) the completeness for most prefecture-level divisions was at a low-to-medium level; most roads (in the Street Map), however, with traffic conditions had already been mapped well. (2) Most of the omission OSM roads were either private roads, or public roads not having yet been named and with only one single lane, indicating their minor importance in the urban road network. We argue that although the OSM road datasets in China are incomplete, they may still be used for several applications such as traffic flow analysis, road map representation, and backbone structure detection.

As the world is digitizing fast, the increase in Big and Small Data offers opportunities to enrich official statistics for reporting on Sustainable Development Goals (SDG). However, survey data coming from an increased number of organizations (Small Data) and Big Data offer challenges in terms of data heterogeneity. This paper describes a methodology for combining various data sources to create a more comprehensive dataset on SDG 6.1.1. (proportion of population using safely managed drinking water services). We enabled digital volunteers to trace buildings on satellite imagery and used the traces on OpenStreetMap to facilitate visual detection of water points on Unmanned Aerial Vehicle (UAV) imagery and estimate the number of people served per water point. Combining data on water points identified on our UAV imagery with data on water points from field surveys improves the overall quality in terms of removal of inconsistencies and enrichment of attribute information. Satellite image...

This paper is an Editorial for the Special Issue titled “OpenStreetMap as a multidisciplinary nexus: perspectives, practices and procedures”. The Special Issue is largely based on the talks presented in the 2019 and 2020 editions of the Academic Track at the State of the Map conferences. As such, it represents the most pressing and relevant issues and topics considered by the academic community in relation to OpenStreetMap (OSM)—a global project and community aimed to create and maintain a free and editable database and map of the world. In this Editorial, we survey the papers included in the Special Issue, grouping them into three research perspectives: applications of OSM for studies within other disciplines, OSM data quality, and dynamics in OSM. This survey reveals that these perspectives, while being distinct, are also interrelated. This calls for the formalization of an ‘OSM science’ that will provide the conceptual grounds to advance the scientific study of OSM, not as a set of individualized efforts but as a unified approach.

Complex systems have been widely studied by social and natural scientists in terms of their dynamics and their structure. Scholars of cities and urban planning have incorporated complexity theories from qualitative and quantitative perspectives. From a structural standpoint, the urban form may be characterized by the morphological complexity of its circulation networks – particularly their density, resilience, centrality, and connectedness. This dissertation unpacks theories of nonlinearity and complex systems, then develops a framework for assessing the complexity of urban form and street networks. It introduces a new tool, OSMnx, to collect street network and other urban form data for anywhere in the world, then analyze and visualize them. Finally, it presents a large empirical study of 27,000 street networks, examining their metric and topological complexity relevant to urban design, transportation research, and the human experience of the built environment.

Cameroon has known, in recent years, a very important urban growth. This growth often took place amid messy, characterized, among other things, by the lack of tracking system in cities. Users of these towns very often find themselves facing difficulties of tracking and orientation. A lack of addresses has several consequences, as the difficulty, or even impossibility to receive mail at home, guide visitors, to taxi to a specific address, to receive relief quickly, etc... The difficulties are also at the level of local authorities who are often unable to geographically locate their constituents. SOGEFI has set up an addressing system that assigns an address to each parcel or dwelling in the Cameroonian territory. During our stay in business, we have addressed the issues related to the use of this system in a simple way by every Cameroonian. From there was born, an engineering project software, including design and development of a mobile application allowing to exploit the addressing set in place by SOGEFI system. The application must allow users to exploit their geographical data and their addresses. It will also give the opportunity to the authorities to easily communicate with their constituents and above all, will have to make the most of new technologies of information and communication.

Keywords: Cameroon, POSITION, mobile application, addressing system, new technologies

Urban scholars have studied street networks in various ways, but there are data availability and consistency limitations to the current urban planning/street network analysis literature. To address these challenges, this article presents OSMnx, a new tool to make the collection of data and creation and analysis of street networks simple, consistent, automatable and sound from the perspectives of graph theory, transportation, and urban design. OSMnx contributes five significant capabilities for researchers and practitioners: first, the automated downloading of political boundaries and building footprints; second, the tailored and automated downloading and constructing of street network data from OpenStreetMap; third, the algorithmic correction of network topology; fourth, the ability to save street networks to disk as shapefiles, GraphML, or SVG files; and fifth, the ability to analyze street networks, including calculating routes, projecting and visualizing networks, and calculating metric and topological measures. These measures include those common in urban design and transportation studies, as well as advanced measures of the structure and topology of the network. Finally, this article presents a simple case study using OSMnx to construct and analyze street networks in Portland, Oregon.

Route planning for transportation of goods is an es
sential task. Determining a route for e.g. a truck
is simple
if the road network including the legal and technic
al limitations like truck ban or weight restriction
are
known. Planning of multi-modal routes is a bit more
complex. The change of mode of transportation is o
nly
possible at specific locations. This change takes t
ime and is often subjet to additional technical or
legal
restrictions. Thus the different networks, e.g., ro
ad and rail, need to be connected.
An obvious approach for multi-modal transport plann
ing would be the use of Open Street Map (OSM) data
since it does not only contain information about ro
ads but also about trains and rivers. In this pape
r we first
present some existing solutions for multi-modal tra
nsport planning and then discuss the use of OSM dat
a in
such a process. We identify missing elements in OSM
and show opportunities for further development and
interventions.

In recent years, a web phenomenon known as Volunteered Geographic Information (VGI) has produced large crowdsourced geographic data sets. OpenStreetMap (OSM), the leading VGI project, aims at building an open-content world map through user contributions. OSM semantics consists of a set of properties (called ‘tags’) describing geographic classes, whose usage is defined by project contributors on a dedicated Wiki website. Because of its simple and open semantic structure, the OSM approach often results in noisy and ambiguous data, limiting its usability for analysis in information retrieval, recommender systems and data mining. Devising a mechanism for computing the semantic similarity of the OSM geographic classes can help alleviate this semantic gap. The contribution of this paper is twofold. It consists of (1) the development of the OSM Semantic Network by means of a web crawler tailored to the OSM Wiki website; this semantic network can be used to compute semantic similarity through co-citation measures, providing a novel semantic tool for OSM and GIS communities; (2) a study of the cognitive plausibility (i.e. the ability to replicate human judgement) of co-citation algorithms when applied to the computation of semantic similarity of geographic concepts. Empirical evidence supports the usage of co-citation algorithms—SimRank showing the highest plausibility—to compute concept similarity in a crowdsourced semantic network.

State of the Map featured a full day of academic talks. Building upon the motto of SotM 2019 in "Bridging the Map" the Academic Track session was aimed to provide the bridge to join together the experience, understanding, ideas, concepts and skills from different groups of researchers, academics and scientists from around the world. In particular, the Academic Track session was meant to build this bridge that connects members of the OpenStreetMap community and the academic community by providing an open passage for exchange of ideas, communication and opportunities for increased collaboration. These proceedings include 14 abstracts accepted as oral presentations and 6 abstracts presented as posters. Contributions were received from different academic fields, for example geography, remote sensing, computer and information sciences, geomatics, GIScience, the humanities and social sciences, and even from industry actors. We are particularly delighted to have included abstracts from both experienced researchers and students. Overall, it is our hope that these proceedings accurately showcase the ongoing innovation and maturity of scientific investigations and research into OpenStreetMap, showing how it as a research object converges multiple research areas together. Our aim is to show how the sum total of investigations of issues like Volunteered Geographic Information, geo-information, and geo-digital processes and representation shed light on the relations between crowds, real-world applications, technological developments, and scientific research.

OSMnx is a Python package for downloading OpenStreetMap street network data and then constructing it into NetworkX graphs. OSMnx can simplify and correct the network’s topology automatically to ensure that nodes actually exclusively represent intersections and dead-ends. Once the network is constructed and corrected, OSMnx can calculate shortest paths from one node to another. It can also calculate various network measures relevant to urban design and transportation as well as statistical physics, including intersection density, average intersection degree, edge density, average street segment length, circuity, clustering coefficients, betweenness centrality, closeness centrality, PageRank, and many more. Its built-in visualization capabilities leverage matplotlib to easily plot routes, one-way streets, dead-ends, high/low connectivity intersections, and figure-ground diagrams of street networks and urban form.

Defining the attributes of urban form which relate to city liveability has long been the research topic of a wide range of experts such as architects, urbanists, geographers, and, more recently, computational social scientists. Both qualitative and quantitative approaches have been developed to study this matter; however, the former often lack of generalizability, as results are mainly based on personal views, and replicability, as no systematic methodology has ever been presented. The latter, although being more generalizable, are still geographically constrained to relatively small regions (e.g., a neighbourhood, a city). Moreover, they focus on single aspects of urban form (e.g., density) rather than on multiple ones (e.g., accessibility, density, connectivity), as Urban Morphology predicates. In this thesis, I propose a quantitative approach to study the relationship between multiple aspects of urban form and city liveability indexes that is replicable and applicable to areas of arbitrarily large size. Metrics of urban form are derived from urban theories and extracted from openly accessible datasets such as census data and OpenStreetMap (OSM). These metrics are then used as independent variables in a linear regression model with a liveability index as dependent one. To test the proposed approach, I apply it to different urban regions of the United Kingdom (UK) to understand the relationship between urban form and different aspects of city liveability such as socio-economic deprivation, life expectancy, and childhood obesity. Models show adjusted R squared values up to 0.76, suggesting good model fit overall. Interpretations of model outcomes and regression coefficients, for the specific geographic context of the UK, suggest that neighbourhoods with worse liveability are characterised by tower block developments, low connectivity, and a predominantly regular street layout. Conversely, more liveable neighbourhoods tend to be characterised by more connectivity, a denser urban fabric, and an above-average presence of historic buildings.

Volunteered Geographic Information (VGI) is a growing area of research. This Special Issue aims to capture the main trends in VGI research based on 16 original papers, and distinguishes between two main areas, i.e., those that deal with the characteristics of VGI and those focused on applications of VGI. The topic of quality assessment and assurance dominates the papers on VGI characteristics, whereas application-oriented work covers three main domains: human behavioral analysis, natural disasters, and land cover/land use mapping. In this Special Issue, therefore, both the challenges and the potentials of VGI are addressed.

This article addresses the emergent phenomenon of carto-vandalism, the intentional defacement of collaborative cartographic digital artefacts in the context of volunteered geographic information. Through a qualitative analysis of reported incidents in WikiMapia and OpenStreetMap, a typology of this kind of vandalism is outlined, including play, ideological, fantasy, artistic and industrial carto-vandalism, as well as carto-spam. Two families of counter-strategies deployed in amateur mapping communities are discussed. First, the contributors organize forms of policing, based on volunteered community involvement, patrolling the maps and reporting incidents. Second, the detection of carto-vandalism can be supported by automated tools, based either on explicit rules or on machine learning.

OpenStreetMap (OSM) is currently an important source for building data, despite the existence of potential quality issues. Previous studies have assessed OSM data quality by comparing it with reference building data, which may not otherwise be readily available. This study assessed OSM building completeness using population data, and investigated the effectiveness of using population data for building reference data. We proposed various approaches, including type-based and regression-based approaches and their subtypes, and designed measures and methods to evaluate these approaches. Our evaluation examined four study areas in two countries, using global population data sets at three spatial resolutions (1-km, 100-m, and 30-m). Results showed that the type-based approach correctly classified approximately 80–99% of the assessed grid cells. The regression-based approach resulted in a high linear correlation (0.7 or greater) between the population counts and the referenced building count/building area size, with the strongest correlation present for the 1-km population dataset. We conclude that the use of population data as referenced building data is an effective method for the assessment of OSM building completeness. The paper concludes with the advantages and limitations of using both the type-based and the regression-based approaches.

This thesis evaluates the possibility to construct a web application, which operates solely within a geospatially enabled CouchDB  database. Its purpose is the matching of POIs from OpenStreetMap with a random set of points. To do so, a simplified matching  algorithm is constructed and evaluated.
Furthermore, a way to support legal decisions when using  OpenStreeMap data is implemented.

In this paper I trace the origins of “neogeography” (a constellation of new mapping practices and populations on the geospatial web) to its roots in computer hacker culture, notably through early mapping mashups, known originally as “map hacks”. I argue that a return to the figure of the hacker—via the proposed concept of hacker cartography—offers a productive lens for understanding the affordances and limitations of participatory knowledge production on the geoweb. Drawing on theorizations of hacker communities and the “hacker ethic” in the literature, I explore how hacker politics (and their critiques) can be observed on the geoweb, using specific examples from OpenStreetMap. I argue that the figure of the hacker—a highly expert individual who nonetheless frequently contributes labor without financial compensation, often producing software and data for his or her own use—presents a fresh way to rethink the expert/novice, professional/amateur and producer/consumer axes that have frustrated geographers' theorizations of participation on the geoweb. I show how the utopian ideals of the hacker ethic offer a promising yet problematic answer to the desires of Critical GIS and Participatory GIS to create more empowered users of geospatial technology.

The academic community frequently engages with OpenStreetMap (OSM) as a data source and research subject, acknowledging its complex and contextual nature. However, existing literature rarely considers the position of academic research in relation to the OSM community. In this paper we explore the extent and nature of engagement between the academic research community and the larger communities in OSM. An analysis of OSM-related publications from 2016 to 2019 and seven interviews conducted with members of one research group engaged in OSM-related research are described. The literature analysis seeks to uncover general engagement patterns while the interviews are used to identify possible causal structures explaining how these patterns may emerge within the context of a specific research group. Results indicate that academic papers generally show few signs of engagement and adopt data-oriented perspectives on the OSM project and product. The interviews expose that more complex perspectives and deeper engagement exist within the research group to which the interviewees belong, e.g., engaging in OSM mapping and direct interactions based on specific points-of-contact in the OSM community. Several conclusions and recommendations emerge, most notably: that every engagement with OSM includes an interpretive act which must be acknowledged and that the academic community should act to triangulate its interpretation of the data and OSM community by diversifying their engagement. This could be achieved through channels such as more direct interactions and inviting members of the OSM community to participate in the design and evaluation of research projects and programmes.

Today, many citizen science projects make use of crowd-mapping. Apart from specially designed web map applications, the crowd-mapping application OpenStreetMap provides several advantages to citizen science projects. But, to improve quantity and quality of the data hold in OSM several challenges must be addressed: rise awareness on OSM across society, address volunteers' motivations and build volunteers' literacy skills. Introduction: The advances in information and communication technologies (ICT) open new possibilities and modes of participation. This refers, among others, to crowd-sourcing applications which allow citizens to contribute data and media on a voluntarily base (Newman et al., 2012). A growing number of citizen science projects takes advantage of crowd-mapping applications where citizens voluntarily add spatial data on features of interest (i.e. volunteered geographic information). For this many citizen science projects use specially designed web map applications. Another example of crowd-mapped data refers to OpenStreetMap OSM (www.osm. org). OSM is an online platform aiming at to collect spatial data on real world features by the help of the general public. Among existing crowd-mapping platforms OSM currently is the largest public collection of spatial data (Schneider, 2011). A growing number of initiatives spanning from research, spatial planning, and disaster management is making use of OSM data. But, how can and/ or is OSM used in the context of citizen science projects? Which challenges are related to its use? And how can these challenges be addressed? Background on OSM: The OSM project is based on Wikipedia's collaborative crowd-sourcing model. Registered users can voluntarily contribute new data to the OSM

In the Local Agenda 21 Planning Guide, which was developed out of the United Nations Rio Conference on the Environment in 1992, community-based mapping is identified as a best practice for locally-based sustainability planning. According to UN-Habitat (2012), the proportion of urban populations living in slums is highest in Sub-Saharan Africa (61.7%); meanwhile, De Soto (2003) estimates the amount of " dead " capital at $9.3 trillion. This capital is based mainly in slums. The paper presents two community mapping projects in urban areas of Nairobi and describes the advantages and disadvantages of the different methodologies used. Second, it explores the options for slum dwellers to map the areas where they live and the benefits of such mapping. Lastly, the paper shares the authors' visions for participatory mapping and participatory GIS, and their ideas on how to select the optimal mapping method. The authors would like to open the discussion about possible effects of community mapping on local development and unlocking the hidden potential in urban-slum areas. Can the unlocking be achieved by acquiring spatial information about urban slums so that the inhabitants can make full use of their property? The paper discusses possible future development in the area of community mapping and invites researchers as well as practitioners to discuss whether community mapping is the key towards the sustainable development.

This final degree Project involves the realization of a system that takes as input different sets of open data from the open data portal of the city of Madrid. The information contained in these data sets will be enriched with information in other sources such as DBpedia, esDBpedia and OpenStreetMap.

Subsequently, it will be published following the linked data principles, specifically in the RDF format.
Thanks to the linked data, structured and interconnected information can be published, which besides serving to nourish webpages for human use, extends its use to automatic reading by machines. This is a fundamental pillar of the Semantic Web. The generated RDF files will be the base of Madrid on You, an application which allows automatic random tours of the city of Madrid, most of which are of a tourist and cultural nature.

Note that all the resources used in the realization of this project (software, documentation, works, etc.) have free licenses.

A Map is the visual representation of the earth in meaningful way to serve specific purposes. With time it has developed from cave drawings to paper maps and then digital and finally web based maps. Web based online map services such as Google Maps, Yahoo maps, bing maps, OpenStreetMap (OSM), etc. are very important tools because of its various interactive qualities such as zoom and pan, highlighting specific objects and route planning etc. Most of online map services are normally commercial and authorized with restrictions on its data usage and accessibility whereas OSM is volunteer based with an open licensing model. The rate of collaborative collection of geo-data is increasing in terms of both quantity and quality in OSM. Hence, this data can be considered as an alternative source of data which can provide similar functionalities as other commercial online map services. Especially, it is the best data source for the area where the availability of the data is low, expensive and not updated regularly. According to the OSM license, OpenStreetMap project provides geo-data for all and can be used for any purpose. Osmosis is a Java command line tool for downloading and updating the data and the downloaded data is imported inside the PostGIS database using osm2pgsql utility tool. With the use of rendering software Mapnik, data is rendered depending upon the specific rendering rules set after the study of printed maps, web based maps, online survey and interviews of the local people to produce a cartographic map. The Tilelite serves on demand rendering web tiles. For web application, there is a OpenLayer JavaScript as user interface library which is powerful, community driven, open source library mainly for displaying map data in most modern web browsers. It implements an API for building rich web-based applications similar to the Google Maps. Finally, a web based cartographic rendered map is generated for serving specifically for local people. Since, the developed system uses data from OSM and all software packages are open-source and free, it is very economical and efficient way of producing up-to-date interactive cartographic web based map.

This paper examines OpenStreetMap data quality at different stages of a participatory mapping process in seven slums in Africa and Asia. Data were drawn from an OpenStreetMap-based participatory mapping process developed as part of a research project focusing on understanding inequalities in healthcare access of slum residents in the Global South. Descriptive statistics and qualitative analysis were employed to examine the following research question: What is the spatial data quality of collaborative remote mapping achieved by volunteer mappers in morphologically complex urban areas? Findings show that the completeness achieved by remote mapping largely depends on the morphology and characteristics of slums such as building density and rooftop architecture, varying from 84% in the best case, to zero in the most difficult site. The major scientific contribution of this study is to provide evidence on the spatial data quality of remotely mapped data through volunteer mapping efforts i...

The route planning solutions promise improvements in terms of the travel time for a route if they are familiar with the traffic congestion state in real-time. With current solutions, where most are static and based on, the cost of road segments, the first challenge is to obtain reliable estimates of traffic congestion for a city at different times of day, and for different days of the year. Overall, calculating this amount of data will take a long time, and have a high computational cost when evaluating the optimal routes based on dependencies.
In this paper, the feasibility of integrating a route recommendation system, a network simulator and a traffic simulator is studied. In parti- cular we study the integration of OMNeT ++ and SUMO, both widely known and used tools, with the ABATIS route server as a solution for route planning, allowing to investigate what are the different effects on vehicle flows densely populated urban areas. To achieve that goal the traffic patterns adopted are adjusted, following driver models ranging from real-time speed changes to changes in route selection. However, the number of vehicles that have to be introduced in the simulation is unknown, and thus we developed a heuristic to adjust the number of vehicles to be injected based on the number of vehicles detected on the different sensors placed along the main streets of Valencia, Spain. Initial results show that the proposed route server offers routes with similar quality compared to the tool integrated in SUMO, and that the use of alternative routes is likely to introduce significant changes on the travel times of vehicles.

As the volume of information available online continues to grow, there is an increasing problem with information overload. This issue is also escalating in the spatial domain as the amount of geo-tagged information expands. With such an abundance of geo-information, it is difficult for map users to find content that is relevant to them. The problem is intensified when considering Location-Based Services. These services, which are dependent upon a user's geographic location, generally operate on portable devices. These devices have a ...

In this work, we present a routing approach avoiding relatively dangerous areas within a city. The information of how dangerous some urban areas are is derived using volunteered geographic information (VGI), governmental open data for detecting properties and functionalities of the urban infrastructure and historical crime data from police departments for detecting crime hot spots. Therefore, we present the basics of crime mapping and analysis with GIS, the practical use of VGI for routing and describe our contribution within the field of routing solutions. Afterwards, we explore our test data in detail. For the practical use, we simplify all the urban infrastructure information and propose a safety index, which represents the relative safety in the investigation area. Additionally, historical crime hot spots are detected and used as routing obstacles. The arcs in the road network are weighted by our safety index and the historical crime hot spots are introduced as obstacle polygons. We test our safetyaware routing design on Los Angeles (LA) and assume its use during night times. In this regard, from two relatively far away situated origin and destination points, we calculate the least dangerous path and compare it with the calculated shortest path. Vehicle drivers without knowledge about the dangerous areas in the city may use the least dangerous path, which is based on our calculated safety index. Finally, we discuss the effectiveness of our method and consider further extensions using freely available geodata.

Land Use/Land Cover Maps (LULCM), fundamental for many areas of application, are usually generated through the classification of satellite imagery. However, their creation is time consuming and therefore updated LULCM are seldom available. The OpenStreetMap (OSM) collaborative project collects a rich set of vector data provided by volunteers at a global scale. It has already been shown that OSM data may be converted into LULCM, but data quality issues in OSM raise some challenges for this conversion, such as overlapping features that should be assigned to different classes. Thus, the creation of LULCM using OSM requires a solution for handling these inconsistencies. In this article an automated methodology is proposed using rules of decision and spatial analysis in a GIS environment to convert OSM features into LULCM, which automatically solves the inconsistencies mentioned above. The methodology is applied to two areas in Europe and the results are compared to available LULCM.

The appearance of OpenStreetMap (OSM) in 2004 sparked a phenomenon known as Volunteered Geographic Information (VGI). Today, VGI comes in many flavours (e.g. toponyms, GPS tracks, geo-tagged photos, micro-blogging or complete topographic maps) and from various sources. One subject that has attracted research interest from the early days of VGI is how good such datasets are and how to combine them with authoritative datasets. To this end, the paper explores three intertwined subjects from a quality point of view First, we examine the topo-semantic consistency of OSM data by evaluating a number of rules between polygonal and linear features and then paying special attention to quality of Points of Interest (POIs). A number of topo-semantic rules will be used to evaluate the valididy of features' location. The focus then turns to the use of geo-tagged photos to evaluate the location and type of OSM data and to disambiguate topological issues that arise when different OSM layers overlap.

This paper examines OpenStreetMap data quality at different stages of a participatory mapping process in seven slums in Africa and Asia. Data were drawn from an OpenStreetMap-based participatory mapping process developed as part of a research project focusing on understanding inequalities in healthcare access of slum residents in the Global South. Descriptive statistics and qualitative analysis were employed to examine the following research question: What is the spatial data quality of collaborative remote mapping achieved by volunteer mappers in morphologically complex urban areas? Findings show that the completeness achieved by remote mapping largely depends on the morphology and characteristics of slums such as building density and rooftop architecture, varying from 84% in the best case, to zero in the most difficult site. The major scientific contribution of this study is to provide evidence on the spatial data quality of remotely mapped data through volunteer mapping efforts i...

The Rural Access Index (RAI) is beneficial to monitor accessibility in rural areas. However, the RAI cannot indicate how many rural people have not been served (called Not Served Rural Population or NSRP), and it has only been mapped at a national and/or regional scale. This study visualizes both the RAI and NSRP in Africa, and also visualizes the NSRP at a fine scale (i.e., 10km×10km grid). The results show that: First, the spatial pattern of the NSRP is quite different with that of the RAI, and thus we suggest to use the NSRP indicator as a supplement of the RAI. Second, the NSRP varies within a country, and the fine-scale mapping can be helpful for policy makers and planners to decide where there is a priority need to improve rural road accessibility.

Computational notebooks offer researchers, practitioners, students, and educators the ability to interactively conduct analytics and disseminate reproducible workflows that weave together code, visuals, and narratives. This article explores the potential of computational notebooks in urban analytics and planning, demonstrating their utility through a case study of OSMnx and its tutorials repository. OSMnx is a Python package for working with OpenStreetMap data and modeling, analyzing, and visualizing street networks anywhere in the world. Its official demos and tutorials are distributed as open-source Jupyter notebooks on GitHub. This article showcases this resource by documenting the repository and demonstrating OSMnx interactively through a synoptic tutorial adapted from the repository. It illustrates how to download urban data and model street networks for various study sites, compute network indicators, visualize street centrality, calculate routes, and work with other spatial data such as building footprints and points of interest. Computational notebooks help introduce methods to new users and help researchers reach broader audiences interested in learning from, adapting, and remixing their work. Due to their utility and versatility, the ongoing adoption of computational notebooks in urban planning, analytics, and related geocomputation disciplines should continue into the future.