OpenStreetMap Research Articles

Characterizing behaviors of territorial-dispute-related mapping in OpenStreetMap

ABSTRACT OpenStreetMap (OSM) as one of the most successful projects of Volunteered Geographical Information (VGI) has attracted millions of contributors to work together and produces massive open geographical data. However, the co-work does not always run smoothly since mapping can involve conflicted understandings of the reality. In this paper, we investigate behaviors of mapping related to territorial disputes to reveal the characteristics of contributions and examine the contradictions between ground truth as the vision of OSM and the theory of critical cartography. We perform our experiments from the perspectives of entities, changesets, and contributors using the full history data of OSM. The experiments show that territorial-dispute-related contributions have substantially different characteristics from various aspects but they cannot be treated as outliers either, considering that most contributors do not focus on disputed boundaries. Interpreting OSM data as a converging state to ground truth or equally opinions can both be inaccurate. We also find that mapping disputes may not be absolutely negative in a VGI project.

Energy Saving-Oriented Multi-Depot Vehicle Routing Problem with Time Windows in Disaster Relief

This paper studies the distribution of emergency relief for electric vehicles (EVs), which considers energy saving, multi-depot, and vehicle routing problems with time windows, and the named energy saving-oriented multi-depot vehicle routing problem with time windows (ESMDVRPTW). Our aim is to find routes for EVs such that all the shelter demands are fulfilled during their time windows and the total cost traveled by the fleet is minimized. To this end, we formulate the ESMDVRPTW as a mixed-integer linear programming model. Since the post-disaster transportation network contains a large number of vertices and arcs composed of vertices, we propose a two-stage approach to solve the ESMDVRPTW. The first stage is to obtain the minimal travel cost between any two vertices in real-time on a post-disaster transportation network using the proposed Floyd algorithm combined with the neighboring list (Floyd-NL algorithm). In the second stage, we develop the genetic algorithm (GA) incorporating large neighborhood search (GA-LNS), which determines the delivery scheme of shelters. Simulation results of the MDVRPTW benchmark illustrate that the performance of the GA-LNS is better than GA, simulated annealing (SA) and tabu search (TS). Finally, case studies are constructed on two real cases acquired from the OpenStreetMap (OSM) generated by the Quantum Geographic Information System (QGIS) in Ichihara city, Japan, and the test results of case studies show the effectiveness of the proposed two-stage approach.

Automatic Extraction of Urban Impervious Surface Based on SAH-Unet

Increases in the area of impervious surfaces have occurred with urbanization. Such surfaces are an important indicator of urban expansion and the natural environment. The automatic extraction of impervious surface data can provide useful information for urban and regional management and planning and can contribute to the realization of the United Nations Sustainable Development Goal 11—Sustainable Cities and Communities. This paper uses Google Earth Engine (GEE) high-resolution remote sensing images and OpenStreetMap (OSM) data for Chengdu, a typical city in China, to establish an impervious surface dataset for deep learning. To improve the extraction accuracy, the Small Attention Hybrid Unet (SAH-Unet) model is proposed. It is based on the Unet architecture but with attention modules and a multi-scale feature fusion mechanism. Finally, depthwise-separable convolutions are used to reduce the number of model parameters. The results show that, compared with other classical semantic segmentation networks, the SAH-Unet network has superior precision and accuracy. The final scores on the test set were as follows: Accuracy = 0.9159, MIOU = 0.8467, F-score = 0.9117, Recall = 0.9199, Precision = 0.9042. This study provides support for urban sustainable development by improving the extraction of impervious surface information from remote sensing images.

Modeling of Parking Violations Using Zero-Inflated Negative Binomial Regression: A Case Study for Berlin

Parking violations cause numerous problems, thus affecting daily mobility. Nevertheless, there are no extensive statistics on illegal parking in Germany, implying that the causes of this misconduct are still unexplored. The objective of this paper is to present a count data modeling approach for parking violations based on video footage taken from the windshields of driving vehicles, incorporating spatial data from OpenStreetMap (OSM). The main benefit of this data source is the transferability of the data collection procedure just by installing a recording device in vehicles of municipal services like waste collection. Moreover, the data from OSM are freely available for all cities. To account for excess zero counts in the street segments, a zero-inflated negative binomial distribution model was used to explain the number of violations per 100 m. “Excess” zeros were modeled using the logit part of the model, whereas the remaining counts of parking violations were fitted by the negative binomial model. Much effort was made to present the results of the count data models in an interpretable way. The most intuitive way seemed to be predictions of parking violations per 100 m (incidence rate) for different settings. Incidence rates were predicted for variations in explanatory variables, holding all other variables constant. We found parking violations per 100 m to be highest in main shopping streets. In addition, free parking spaces negatively- and the number of points of interest (such as buildings, craft stores, and shops) positively affected illegal parking.

Automated Interpretation of Place Descriptions: Determining Entity Types for Querying OSM

This paper is concerned with interpretation of natural language place descriptions, as they are a rich source of geographic information. A place description is interpreted by matching geographic entities occurring in the text against the OpenStreetMap (OSM) database. This paper is mainly concerned with interpretation of paraphrased places, i.e., entities for which no name is given and which may only by described. Our objective is to determine suitable entity types that allow querying the OpenStreetMap database for the respective place. For example, if we wish to identify a place to eat, we have to check for entities of an a-priori unknown type (cafe, restaurant, etc.). Challenges arise from the open-endedness of language, its ambiguity, and context-sensitivity as well as from mismatches between human conceptualization of place and database ontologies. The contributions of this paper are, first, to present a hard problem that is key to geo-information retrieval beyond named entities. Second, we propose context-sensitive methods for identifying place types based on semantic word similarity. We evaluate the methods on text extracted from Wikipedia and travel blogs, revealing their contribution to advancing automated interpretation of place descriptions to paraphrased places.

Coupling coordination analysis of urbanization and the ecological environment based on urban functional zones.

Urbanization is an inevitable process in human social progress; additionally, the ecological environment is the carrier and foundation of human social development. Considering central Shanghai, China, as an example, this study quantitatively analyzed the coupling coordination relationship between urbanization and the ecological environment based on urban functional zones; remote sensing images, Open Street Map roads, and point of interest data were analyzed for the urban functional zones via the remote sensing-based ecological index (RSEI), comprehensive nighttime light index (CNLI), and coupling coordination degree (D). The results revealed that urban functional zones in central Shanghai were mainly mixed functional zones and comprehensive functional zones, which formed a spatial structure that gradually radiated outward from the urban core. Additionally, CNLI values were high; the proportion of CNLI between 0.6 and 1 was 94.37%. Moreover, the RSEI showed spatial differentiation; it was low in the center and gradually increased outward. Additionally, D was at the primary coordination level. The coupling coordination type in the core area corresponded to an ecological environment lag, which gradually transitioned to a state of systematic balanced development from the core area outward, but showed sluggish urbanization in some areas. This quantitative analysis of the coupling coordination between urbanization and the ecological environment based on urban functional zones provides effective scientific references for optimization of spatial planning.

A city-wide examination of fine-grained human emotions through social media analysis.

The proliferation of Social Media and Open Web data has provided researchers with a unique opportunity to better understand human behavior at different levels. In this paper, we show how data from Open Street Map and Twitter could be analyzed and used to portray detailed Human Emotions at a city wide level in two cities, San Francisco and London. Neural Network classifiers for fine-grained emotions were developed, tested and used to detect emotions from tweets in the two cites. The detected emotions were then matched to key locations extracted from Open Street Map. Through an analysis of the resulting data set, we highlight the effect different days, locations and POI neighborhoods have on the expression of human emotions in the cities.

Urban advanced noise indicator mapping relying on street categorization and measurements

In order to more accurately estimate health outcomes related to environmental noise exposure such as sleep disturbance and noise annoyance, indicators beyond long-term equivalent sound pressure levels might be needed (such as statistical levels, number of events, psycho-acoustical indices etc). In urban noise mapping, predicting these more advanced noise indicators is especially challenging. In the current work, an open source noise mapping code (NoiseModelling) is combined with micro-traffic simulations. However, in most cities, traffic data availability is poor, especially in low traffic streets. To overcome this issue, the noise mapping procedure developed here assumes no access at all to traffic information and fully relies on Open Street Map street categorization. These street categorizations were then assigned sets of plausible traffic compositions, counts and speeds; various scenarios were explicitly simulated. In a next step, these traffic scenarios were weighted to best fit a set of 29 noise indicators on 23 measurement stations deployed in the city of Barcelona, during various periods of the day. It was shown that this procedure leads to adequate assessments of a wide range of noise indicators in a specific city.

Modelling Bias and Environmental Preferences in Archaeological Spatial Analysis

Point pattern analysis (PPA) has gained momentum in archaeological research that models large-scale distributions of sites and explanatory covariates. As such, there has been increased interest in the bias of archaeological distributions, which mostly have an impact due to modern land-use change. These interactions, however, have not yet been fully explored. In order to better understand archaeological point patterns as functions of explanatory covariates, we offer three different approaches: (i) environmental preference modelling of archaeological records in different chronological phases; (ii) a custom bias surface that represents the variability of the regional landscape; (iii) an R-package (rbias) allowing the generation of a fuzzified bias surface based on Open Street Map (OSM) data.

Suitability mapping of solid waste disposal sites in Obio/Akpor local government area: rivers state of Nigeria

Obio/Akpor Local Government Area of Rivers State have constantly witnessed Rapid City growth and increased urbanization due to persistence rural-urban migration and the quest for human to meet their needs and wants. This has increased solid waste generation and unregulated dumping of solid wastes in unapproved sites. This prompted the need for this study which is aimed at mapping the suitability of solid waste sites in the study area with the objective of identifying the spatial locations and development of a database of suitability or otherwise of solid waste disposal sites. Ground survey and Geospatial techniques were utilized for data acquisition, manipulation and processing. Garmin 78csx GNSS receiver was used in observing the coordinates of ground positions of all solid waste disposal sites in the study area, the obtain coordinates were charted on the Google earth imagery (2022) and Open Street Map (OSM) (2022) to ensure the positions falls within the shape-file of the study area, On-Screen vectorization was perform using the point, line and polygon spatial tools in the QGIS 3.22 bialowieza software environment to determine the position and extent of solid waste sites under study. Proximity analysis was performed in QGIS environment for buffer of 200m, 500m and 1km to ascertain the suitability of solid waste collection centers and dumpsites base on global standard and proximity maps were produced. A total of (114) solid waste disposal sites were mapped, with (27) legal and (73) illegal collection points and (2) suitable and (12) unsuitable dumpsites respectively. The study also revealed that Elelenwo community in ward 6 has the highest (12) whereas Egbelu Ozodo community in ward 16 has the lowest (1) number of collection sites in the study area. Immediate review and enforcement of solid waste disposal and management laws is needed to forestall likely environmental hazards resulting from indiscriminate dumping of refuse in the study area.

A Hierarchical Algorithm for In-city Parking Allocation Based on Open Street Map and AnyLogic Software

A Hierarchical Algorithm for In-city Parking Allocation Based on Open Street Map and AnyLogic Software

Development And Evaluation Of The Webgis Application To Support Volcanic Hazard Mitigation In The Southern Flank Of Merapi Volcano, Sleman Regency, Yogyakarta Province, Indonesia

Merapi Volcano is one of the active volcanoes in Indonesia, which is located in the Central Java and Yogyakarta Province. The eruption of Merapi Volcano is a threat to people living on the slopes of Merapi, especially on its denselypopulated southern flank. The purpose of this study was to build a webGIS to support volcanic hazard mitigation regarding Merapi Volcano and evaluate the webGIS system for determining the community’s perception. This research was the first to produce a product that is used by government agencies related to volcanic disaster mitigation. webGIS development was carried out using an open source platform. System evaluation was carried out using usability testing. The samples were obtained using systematic the random sampling method of respondents who lived in the villages on the southern flank of Merapi volcano. webGIS was built using LeafletJS and QGIS, combined with spatial data about the evacuation locations, health facilities, evacuation routes, government offices, educational facilities and worship facilities, with a basemap obtained from Openstreet Map and Google Satellite. WebGIS was equipped with a database query feature to make it easier for users to find geographical information. The usability testing results showed that as many as 83% of the respondents were very satisfied with the appearance and information of webGIS, while as many as 82% were very satisfied with the navigation offered via the webGIS display.

Self-Filtered Learning for Semantic Segmentation of Buildings in Remote Sensing Imagery With Noisy Labels

Not all building labels for training improve the performance of the deep learning model. Some labels can be falsely labeled or too ambiguous to represent their ground truths, resulting in poor performance of the model. For example, building labels in OpenStreetMap (OSM) and Microsoft Building Footprints (MBF) are publicly available training sources that have great potential to train deep models, but directly using those labels for training can limit the model's performance as their labels are incomplete and inaccurate, called noisy labels. This article presents self-filtered learning (SFL) that helps a deep model learn well with noisy labels for building extraction in remote sensing images. SFL iteratively filters out noisy labels during the training process based on loss of samples. Through a multiround manner, SFL makes a deep model learn progressively more on refined samples from which the noisy labels have been removed. Extensive experiments with the simulated noisy map as well as real-world noisy maps, OSM and MBF, showed that SFL can improve the deep model's performance in diverse error types and different noise levels.

ГЕОДЕЗІЯ, КАРТОГРАФІЯ І АЕРОФОТОЗНІМАННЯ

Nowadays, GIS Technologies are used in many areas of human life, both in everyday life and scientific research. The purpose of the presented study is to identify the relationship between the scale of topographic maps and the main hydrographic characteristics of the river based on the data of observations in the Siverskyi Donets basin. The study is based on the results of the identification of the hydrographic network, which was performed based on the Open Street Map in the GIS environment of the QGIS program using the method of A. N. Straller and I. N. Hartzman. The process of identifying, describing, and analyzing subcontracted connections consists in assigning its identification order to each element of the river network, which makes it possible to compare and standardize streams. Operating with a hierarchical "tree" of the channel network, the main characteristic of which is the number of elementary, unbranched streams, it is possible to identify and analytically describe the dependencies between the detailing of the map and the main characteristics of the river network structures, such as water discharges, network density, drainage basin area, and river length. The basis for describing these relationships was the method of B.V. Kindiuk, who introduced the concept of the coefficient of the river network structure or the fractional order of the stream as a basis for approximating the above-mentioned dependencies, which allows mathematically describing the obtained functions and obtaining numerical values of empirical parameters. Using QGIS made it possible to create maps of the Siverskyi Donets hydrographic network within Ukraine based on maps of scales 1:50 000 and 1:200, 000. With their help, as well as data from a 1:100,000 map, the number of elementary unbranched watercourses was calculated, and each element of the system was identified, where the order of the main river changes depending on the map scale. The change in these indicators shows a tendency to increase the density and complexity of the river network with increasing map detail, and, as a result, potential changes in indicators of the catchment area, water runoff, and river length. The identified dependencies were expressed mathematically in the form of functions, and are also characterized by high values of the approximation reliability coefficient, which made it possible to construct a general transitional graph from the order of the water flow to the scale of the map with the corresponding values of the calculation parameters. The novelty and practical significance lie in the fact that the use of modern GIS technologies in hydrological science significantly increases the quality of cartographic data and concerning the studied object - the Siverskyi Donets River creates a database in the form of digital maps for further use in hydrographic studies. This sub‑basin has not been previously studied using the methodology proposed by B. V. Kindiuk about the influence of map scales on the characteristics of the river network structure. Such study from a practical point of view, can significantly help the work of engineers, researchers, and designers with cartographic data. This study is designed to explain the peculiarities in the scaling of river networks and propose a mechanism for a scientifically based transition from the existing map scale to the desired one within the Siverskyi Donets sub-basin.

Tsunami Risk Assessment on Public Facilities in Southern Part of Bantul Regency, Yogyakarta

The southern part of Java Island is susceptible to tsunamis as its role as a subduction zone between Indo-Australian and Eurasian plates. On July 17, 2006, a tsunami struck Java's south coast triggered by an earthquake and affected more than 300 km of shoreline, as well as claimed more than 730 casualties. It is important to assess the risk in the southern part of Java. This research aims to analyze tsunami risk assessments on public facilities in the southern part of Bantul Regency, Yogyakarta. The Tsunami hazard map was created by using tsunami modeling from BMKG. Public facilities footprint such as health facilities, religious facilities and school were derived from data provided by Open Street Map (OSM). The Papathoma Tsunami Vulnerability Assessment (PTVA) model, specifically developed to estimate the relative vulnerability of buildings to tsunami hazards, is used to generate a building vulnerability map. A geographic information system (GIS) was utilized to calculate and visualize the hazard, vulnerability, and risk map. A total of 394 buildings were analyzed with the results that public facilities in three sub-districts, namely Srandakan, Sanden and Kretek, had varying levels of building vulnerability ranging from minor, moderate, average and high with RVI values ranging from 1.5 to 3.4. Additionally, tsunami risk assessment of public facilities indicates that buildings within Bantul Regency are categorized as having very high, high, moderate, or low levels of building risk.

Measuring the timing between public transport provision and residential development in greenfield estates

The timing of public transport provision in newly established suburbs on the urban fringe is a major concern for residents. It is argued that if public transport were available when residents start moving to a new suburb, they are more likely to use it. Despite this, the timing of public transport service provision relative to residential development is generally unknown. Using a case study of Melbourne, Australia, this article provides a methodology to measure the timing of bus provision relative to residential development. Information from Precinct Structure Plans, Census data, public transport timetables, and a spatial analysis based on Open Street Map, Metromap and Google Earth, were used. Results show that new communities on Melbourne’s urban fringe had to wait 3–4 years on average for a bus service to be implemented. About one quarter (24%) of the communities were already served by a bus service when residents started to move in, 12% had to wait up to a year, and about two-thirds (64%) had to wait for longer than a year, as much as 14 years. For those waiting more than one year, bus provision comes too late to capitalise on the higher likelihood of public transport use through early delivery. To improve public transport delivery in those areas and understand where issues exist, government agencies should monitor the waiting time of communities and support an earlier delivery of public transport through improved land use and transport integration.

Performance Analysis of Mobile Ad Hoc Routing Protocols in Vehicular Ad Hoc Networks using NS3

Vehicular Ad hoc Networks (VANET) is an emerging technology that brings tremendous technological advancement in the method of communication among smart vehicles. Due to its complex infrastructure and vehicle speed, data routing remains difficult at VANET. A VANET is also considered similar to Mobile Ad Hoc Network (MANET), and MANET routing protocols can be adapted for VANETs for performance evaluation. In this work, we have selected a real world scenario from our locality with high traffic issues, Nanthoor Mangalore City Karnataka, India and a Map is generated using Open Street Map using SUMO and the MANET routing protocols AODV, OLSR, DSDV and OLSR are evaluated using NS3.

ОРГАНИЗАЦИЯ СКРИНИНГА В ЭПИДЕМИЧЕСКИХ ТУБЕРКУЛЕЗНЫХ ОЧАГАХ В СУБЪЕКТАХ РОССИЙСКОЙ ФЕДЕРАЦИИ С НИЗКИМ УРОВНЕМ ЗАБОЛЕВАЕМОСТИ ТУБЕРКУЛЕЗОМ

Significance. In Russia, from 2001 to the beginning of the Covid-19 pandemic, the incidence of tuberculosis was decreasing on an annual basis, equaling to 41.2 per 100,000 population in 2019 (87.1 per 100,000 population in 2001). At the same time, the Covid-19 pandemic, which lasted for about two years (2020-2021), had a negative impact on the organization of screening aimed at early TB detection in the population. During the Covid-19 pandemic, the share of the Russian population covered with screening decreased to 66.7% and 70.8%, which was comparable to the one in 2014-2016. As a result, in 2020-2021, the incidence of tuberculosis in Russia decreased to 32.4 and 31.1 per 100,000 population, respectively. Therefore, the indicator decline is due to the reduced timing of TB screening because of the restrictive measures during the pandemic rather than improvements in the epidemic situation. Currently, in order to overcome the consequences of the pandemic, there is an urgent need to increase coverage of the population with TB screening to a pre-pandemic level within the shortest possible time. Purpose: organization of TB screening in epidemic foci of tuberculosis in the subjects of the Russian Federation with a low TB incidence. Material and methods. The study was conducted in 2 stages, in the first stage the structure of 76 newly detected TB patients and contingents who were under the medical follow-up at TB facilities in the Borovsky district and Obninsk of the Kaluga region in 2019-2020 was analyzed. The information was obtained from federal statistical observation forms No. 8 and No. 33. The age and proportion of patients with pulmonary tuberculosis were determined including bacterial excretion, multiple drug resistance, destruction of lung tissue and TB-HIV co-infection. In the second stage, spatial distribution of epidemic foci of tuberculosis in the above-mentioned settlements was analyzed. The study used information about actual residence of 53 patients with tuberculosis, newly diagnosed in 2019-2020, as well as 8 patients from the contingents with tuberculosis with bacterial excretion. Statistical analysis was carried out using the program Stat Tech v.2.8.8 (developer - Stattech LLC, Russia). Pearson's Chi-squared criterion was used for data analysis. The differences were recognized as significant at a value of p <0.05. The analysis of medical cartographic data was carried out using spatial statistics (GIS) tools and data management of ArcGIS version 10.0, available through the ArcToolbox interface: Calculate areas, Analyze the nearest neighborhood, Integration, Collect events. The OpenStreetMap (OSM) cartographic web service is used as a cartographic basis. Results. The structure analysis of 76 tuberculosis patients detected both among the permanent population and migrant workers in the Borovsky district and Obninsk of the Kaluga region in 2019-2020 showed that the main sources of tuberculosis infection, including with multidrug-resistant pathogen, or its donors, were patients with chronic pulmonary tuberculosis with the sustained bacterial excretion after treatment and unclosed lung decay cavities. In addition, more than half of the patients with pulmonary tuberculosis with bacterial excretion, newly detected among the permanent population in the Borovsky district and 1/3 of those in Obninsk, were also sources or donors of the TB in the population. Patients with tuberculosis, newly detected among migrant workers, on the contrary, were mostly recipients of tuberculosis infection, living in the same areas as the above-mentioned sources of TB infection with a high probability of contacts with them, both close and accidental ones. The spatial analysis of TB epidemic foci distribution shows that against the background of the decreased TB incidence, there is a clear tendency towards merging and forming clusters with clearly defined boundaries, which facilitates organization of screening and more comprehensive coverage of the cluster population. Places of residence of migrant workers who first contracted tuberculosis in 2019-2020 in both settings were located near or within buffer zones formed around the TB epidemic foci in the permanent population, increasing the risk of tuberculosis among migrants due to the high probability of contacts, both close and accidental ones, with sources of tuberculosis infection. Conclusion. In the subjects of the Russian Federation with a low incidence of tuberculosis, the use of a GIS-based cartographic method to organize screening among the population living near epidemic foci of TB, including their buffer zones, can make a significant contribution to overcoming the consequences of the pandemic by increasing the screening coverage of the population to the pre-pandemic level in a short time

Spatio-temporal constraints of carer-workers in the Greater Toronto and Hamilton Area: An exploratory analysis using potential path areas

Carer-workers are individuals providing regular unpaid care to an adult dependent while simultaneously employed in the paid labour market, and the group represents a significant portion of the Canadian adult population. Despite the prevalence of unpaid care in Canada, very limited research has explored the spatio-temporal tensions that carer-workers experience. The objective of this study is to explore the space–time constraints experienced by carer-workers. One way of measuring both space and time constraints on an individual is the foundational time geography concept of the Space-Time Prism, and its two-dimensional counterpart, the Potential Path Area (PPA). We collected three to seven day-long trip diaries of 25 carer-workers in the Greater Toronto and Hamilton Area in 2017–18, including all trips made over the diary period and whether the trip involved care work. We developed a customized Python tool and used Open Street Maps to derive PPAs for 12 of the sample carer-workers, which were aggregated to form daily PPAs. Descriptive analyses of the PPAs are presented, and comparisons of PPA size, and therefore, daily accessibility, across carer-workers’ sociodemographic and economic indicators, days of the week, and level of caregiving intensity are examined. Through its ability to represent, quantitatively and visually, the accessibility differences across various population groups, and to fill a gap in our understanding of carer-workers, the PPA represents an important methodological avenue for continuing research into carer-workers in Canada and around the world.

A Pipeline to Construct a Real-World Question and GeoSPARQL Query Dataset for Geo-Analytical Question Answering over OpenStreetMap Data

An immense pull of data led to the growth of the QA (Question Answering) system. With the growth of comprehensive QA systems, KBQA (QA over Knowledge Base) demonstrates an effective way of answering questions based on knowledge sources. GeoQA (Geographic Question Answering), in turn, still lacks its research and advancement, even with the rapid increase in geospatial data. There is only one full set of question and SPARQL query pair datasets specific to GeoQA, limiting its potential to become a comprehensive GeoQA system. In order to build a comprehensive GeoQA system, this paper proposes a pipeline to construct a real-world question and GeoSPARQL query pair datasets for geo-analytical questions over OSM (OpenStreetMap) data. Through utilizing the real-world MS MARCO (Machine Reading Comprehensive) question dataset, we classify them into geometry and operation combinations and generate a geo-analytical workflow for further query generation. We evaluate a detailed comparison with the existing Geospatial Gold Standard 201 question, query pair dataset to give context as well.