Web Mapping Application Research Articles

Development of a web-mapping application for storytelling with animations and guided interactions

Development of a web-mapping application for storytelling with animations and guided interactions

Multiscale Visualization of Surface Motion Point Measurements Associated with Persistent Scatterer Interferometry

Persistent scatterer interferometry (PSI) has been proven to be a robust method for studying complex and dynamic phenomena such as ground displacement over time. Proper visualization of PSI measurements is both crucial and challenging from a cartographic standpoint. This study focuses on the development of an interactive cartographic web map application, providing suitable visualization of PSI data, and exploring their geographic, cartographic, spatial, and temporal attributes. To this end, PSI datasets, generalized at different resolutions, are visualized in eight predefined cartographic scales. A multiscale generalization algorithm is proposed. The automation of this procedure, spurred by the development of a web application, offers users the flexibility to properly visualize PSI datasets according to the specific cartographic scale. Additionally, the web map application provides a toolset, offering state-of-the-art cartographic approaches for exploring PSI datasets. This toolset consists of exploration, measurement, filtering (based on the point’s spatial attributes), and exporting tools customized for PSI measurement. Furthermore, a graph tool, offering users the capability to interactively plot PSI time-series and investigate the evolution of ground deformation over time, has been developed and integrated into the web interface. This study reflects the need for appropriate visualization of PSI datasets at different cartographic scales. It is shown that each original PSI dataset possesses a suitable cartographic scale at which it should be visualized. Innovative cartographic approaches, such as web applications, can prove to be effective tools for users working in the domain of mapping and monitoring the dynamic behavior of surface motion.

Flood Risk Assessment of the Middle Reach of the Helmand River, Afghanistan

The middle reach of the Helmand River is prone to floods, and flood hazard analysis is necessary to manage the flood risk. As the study site is a less-developed basin where available geographical and hydrological data are limited, we must utilize available limited data to conduct the flood hazard analysis. A frequency analysis of the annual peak flow rate was performed using available hydrological data for making representative flood hydrographs. A land-use map is derived by classifying recent Landsat images. Digital elevation model derived by Advanced Land Observing Satellite, roughness coefficient correlated with the land-use map, and the representative flood hydrographs are fed into hydraulic model HEC-RAS 2D. Flood inundation area, depth, and velocity for different flood return periods are estimated. Based on local hazard intensity and vulnerability, risk maps for evacuation and vulnerability of crops on the floodplain are obtained. Spatial flood risk characteristics differ at the upstream and downstream reaches because of distinct floodplain topography. Flood countermeasures for each reach are proposed based on the spatial characteristics of the flood risk. To provide risk information for residents within the region, the flood hazard, risk, and damage maps derived in this study are published as a web map application and a mobile native application.

A Multifaceted Approach to Developing an Australian National Map of Protected Cropping Structures

As the global population rises, there is an ever-increasing demand for food, in terms of volume, quality and sustainable production. Protected Cropping Structures (PCS) provide controlled farming environments that support the optimum use of crop inputs for plant growth, faster production cycles, multiple growing seasons per annum and increased yield, while offering greater control of pests, disease and adverse weather. Globally, there has been a rapid increase in the adoption of PCS. However, there remains a concerning knowledge gap in the availability of accurate and up-to-date spatial information that defines the extent (location and area) of PCS. This data is fundamental for providing metrics that inform decision making around forward selling, labour, processing and infrastructure requirements, traceability, biosecurity and natural disaster preparedness and response. This project addresses this need, by developing a national map of PCS for Australia using remotely sensed imagery and deep learning analytics, ancillary data, field validation and industry engagement. The resulting map presents the location and extent of all commercial glasshouses, polyhouses, polytunnels, shadehouses and permanent nets with an area of >0.2 ha. The outcomes of the project revealed deep learning techniques can accurately map PCS with models achieving F-Scores > 0.9 and accelerate the mapping where suitable imagery is available. Location-based tools supported by web mapping applications were critical for the validation of PCS locations and for building industry awareness and engagement. The final national PCS map is publicly available through an online dashboard which summarises the area of PCS structures at a range of scales including state/territory, local government area and individual structure. The outcomes of this project have set a global standard on how this level of mapping can be achieved through a collaborative, multifaceted approach.

The Seasonal Migrants Spatially Affect the Park Green Space Accessibility and Equity under Different Travel Modes: Evidence from Sanya, China

The influx of seasonal migrants has a significant impact on public services in destination places and may reshape the spatial accessibility and equity patterns of park green space (PGS). However, the two-step floating catchment area (2SFCA) method and its extended forms neglect discrepancies between the travel behaviors of seasonal migrants and native residents and thus fail to delineate variations in PGS accessibility and equity in areas with seasonal migrants. To avoid this issue, this study drew on the case of Sanya, a city with large numbers of Houniao, who are primarily retirees leading seasonal migration between the north and the south of China. A multi-group, multi-mode Gaussian-based 2SFCA method was also proposed to evaluate the PGS accessibility and equity before and after the Houniao influx. The method considered the changes in the COVID-19 restrictions from a refined perspective, with fine-scale residential areas being the research units and travel time requested from the web map application programming interface. The results showed that most residential areas were found to have relatively low PGS accessibility and equity levels, except for those in the south-central and southwestern urban areas of Sanya. Both the Houniao influx and lifted COVID-19 restrictions affected the spatial patterns of PGS accessibility and equity. PGS accessibility and equity were decreased by the Houniao influx, whereas walking and public transport within a few residential areas outside Houniao gathering spots improved. This study can serve as a basis for the reasonable planning of PGS and other public services in cities receiving seasonal migrants, such as Sanya.

Web Mapping Applications Urban land uses in the city of Kirkuk-Iraq (Case study on Hay al Askari)

The research presents a study on how to prepare an advanced database and employ web maps available on the Internet through the application of the (GIS Online) system in the city of Kirkuk, a case study through designing effective maps on a website that allows the data to be displayed effectively in order to encourage the user to make a decision. This application was used to prepare land use maps (health, educational, recreational, religious, other, land area) over the research area, adopting open source data, and drawing spatial layers of land use on an individual basis through the use of spatial symbols available in the application interface. Then compiled into a final map that can be made available to decision makers.

Development of a multi scale interactive web-GIS system to monitor farming practices: A case study in Lemnos Island, Greece

The environmental impacts of agricultural activities result from a chain of processes, agricultural practices affect the quantity and quality of natural resources, including biodiversity. Geographic information systems contribute to the systematic recording and monitoring of these agricultural practices in terms of production and to associate these practices with impacts on biodiversity. This paper presents the design of a web GIS system that records farming practices on a web map application (FarmGeoBalance), which is used by the farmers to import, store, revise and visualize farming practices in field level and farm level. The web map application communicates with a GeoDatabase informed with the geographical location of the participating fields where spatial and non-spatial data from the application are stored and standardized. The case study is an extensive arable farming system on Lemnos island, Greece, which covers a surface of 482 km². The system consists of 12 producers with 678 fields, representing 1.7% of the total farmed land of the island. In this paper, we present the web map application architecture and the collected data for the cultivation periods of 2020–2021 and 2021–2022, which include farming practices like fertilization, plant protection, irrigation, soil management, etc., outputs, landscape features of the farms related to biodiversity. For all these, their spatial and non-spatial dimension is presented and they are related to elements of the natural geography of fields and soils. With the use of this system recording and monitoring farming practices can assess the impact on biodiversity at multiple scales. It also highlights the need to include the end users at different phases of the development of the services and the interface. Farmers and their participation are the key component of the effectiveness of this effort: they monitor their everyday and seasonal practices at the level that they are realized in their farms.

Understanding the mobility patterns of Mass Rapid Transit (MRT) passengers amid COVID‐19 in Singapore using smart card data

The Mass Rapid Transit (MRT) is one of the major modes of public transportation in Singapore. Understanding the mobility patterns of MRT passengers has implications for improving transportation efficiency. As a city‐state with a high population density, Singapore provides a representation of balanced urban dynamics that informs smart urban planning. In this paper, we investigated and visualized (using both static maps and dynamic web map applications) the spatiotemporal characteristics of Singapore's MRT commuting patterns before the COVID‐19 pandemic (January 2020) and during the first outbreak (May 2020) and the Omicron wave of the pandemic (February 2022), using MRT smart card data. We also investigated the relationship between the passenger flows of individual MRT stations and the nearby land use types. Our results showed that the spatial patterns of Singapore's MRT commuters match the polycentric urban structure. In addition to central areas, several regional centres were identified as passenger hotspots in multiple time periods. Furthermore, during the outbreak of the pandemic, especially in the period of the ‘circuit breaker’, there was a major decline in MRT passenger flows and a decrease in average MRT commuting distances during weekend/holiday peak hours. Lastly, correlations between passenger flows of MRT stations and the proportion of nearby land use types have been identified.

Investigating the relationship between spatial skills and web mapping application performance among university students

ABSTRACT Successfully performing a task using a web mapping application may not only depend on the application itself and how well it meets users’ needs but also on users’ spatial skills. Spatial ability is comprised of different spatial skills and high performance in one skill does not entail similar performance in another. Hence, we explored how university students’ performance in seven spatial skills (three small- and four large-scale skills) affects their performance in four tasks (such as finding the closest point of interest or finding the shortest path) using Google Maps, considering three groups of participants based on high, medium, and low spatial skills performance. Beyond exploring this relation for each spatial skill separately, we introduce a composite index for performance in spatial skills, considering them as either two separate clusters of small- and large-scale skills or as an amalgam of both. Results indicate that participants with higher small-scale, but not with higher large-scale, spatial skills, when these are separately assessed, perform better on Google Maps than the other two groups, especially the low spatial-skilled group. This also holds when small-scale skills are considered as a cluster and when all skills are considered as a whole.

Geovisualization of Historical Geospatial Data: A Web Mapping Application for the 19th-Century Kaupert’s Maps of Attica

This paper presents the development procedure and significance of a web mapping application designed for disseminating, exploring, and analyzing Kaupert’s 19th-century Maps of Attica, Greece. The application facilitates historical and geographical study by providing access to high-resolution map images and overlaying multiple vector layers of geospatial data. The paper outlines the methods used to create the application, which includes the process of interpreting, digitizing, and organizing the original mapped data, georeferencing the historical cartographic sheets, and developing the web-based mapping application. The results of this work include a comprehensive and interactive digital reference tool for studying the ancient topography of Attica, as well as a framework for future research. Overall, this work highlights the potential of digital technologies to transform the way we approach and study historical maps and other cultural artifacts.

MAPPING AND ASSESSMENT OF FLOOD EVACUATION SITES IN A GEOSPATIAL ENVIRONMENT: A CASE IN LAS NIEVES, AGUSAN DEL NORTE, PHILIPPINES

Abstract. The municipality of Las Nieves is one of the most vulnerable areas prone to flooding, usually caused by tropical cyclones. With these, preparing for an emergency response is relatively significant, and one strategic response is planning for systematic management of evacuation shelters. Hence, this study assessed the spatial exposure to flooding, the spatial capacity and mapped the suitability of evacuation shelters using Geographic Information System and site suitability analysis. This study also developed a web-based application that will address the needs of the Las Nieves LGU, specifically in providing the locality with spatial information and other flood-related data. Weighted Overlay Analysis was performed based on Multi-Criteria Decision Making and weights from related literature to generate a suitability map for flood evacuation shelters. Factors included slope, elevation, land use/land cover, road networks, distance to water sources, distance to electrical supplies, and proximity to fuel stations. The results indicated that 85.1% of the areas were moderately suitable, 0.3% were highly suitable, and 14.6% were low suitable for flood evacuation sites in Las Nieves. From the analysis of 11 existing evacuation centers, there are ten evacuation centers moderately suitable for use during an emergency, while only the Maningalao Evacuation Center was not suitable because the location of the center was affected by the 100-year flood event. Moreover, the web mapping application developed in this study will help the stakeholders and community of Las Nieves to effectively manage evacuation centers and access real-time spatial data regarding evacuation centers' status and spatial capacity.

Interactive Web Mapping Applications for 2D and 3D Geo-Visualization of Persistent Scatterer Interferometry SAR Data

Surface motion is a complex, dynamic phenomenon that draws significant scientific attention. This study focuses on the development of a cartographic toolset for the visualization of space-borne Persistent Scatterer Interferometry (PSI) surface motion measurements. The entire archive of Sentinel-1 Synthetic Aperture Radar (SAR) imagery over the broader Thessaloniki (Greece) area has been exploited to derive the PSI measurements utilizing the Surface motioN mAPPING (SNAPPING) service on the Geohazards Exploitation Platform (GEP). A collection of web map applications, interactive visualization tools, and an animated map were developed based on state-of-the-art approaches. This geo-visualization toolset consists of the following: (i) Three web map applications exploring PSI velocity rates, PSI time series, and a comparison of PSI with geodetic leveling data; (ii) Two interactive map tools focusing on 3D visualization of PSI time series and estimating velocity rates for predefined temporal frames; and (iii) An animated map of PSI time series. The utilization of the aforementioned visualization toolset provided useful conclusions about the variety of land displacement that occurs in different subareas of Northern Greece from different causes. More specifically, certain subareas with significant subsidence rates range from −2 mm/year up to −18 mm/year from 2015 to 2020. The magnitude of displacement and the underlying causes (subsidence, faults, landslides, human processes, etc.) varies across different subareas. On the other hand, a subarea of uplift trend exists in the north of the city of Thessaloniki with displacements up to 5 mm/year for the period between 2015–2020, despite being constrained by the fact that the geo-visualization platform is able to display SNAPPING PSI measurements from any location around the world, making it a useful tool for global exploration. The platform’s contents are available through a user-friendly graphical interface and are mostly addressed to domain experts as well as end-users. Opposed to similar approaches where static 2D maps and velocity rates web applications are presented through this platform, users can monitor and study the dynamic behavior of surface motion to a spatiotemporal extent more thoroughly.

Development of Spatial Uncertainty-Aware Visualization of Historical Traffic Queue Length

Traffic queue length at intersection is one of the most important measures of traffic signal performance and the traffic signal optimization. The spread of the ride-hailing services makes GPS data widely available with large area coverage, allowing us to quantify the queue length in a wide area without the need for additional installation cost like conventional sensors. Hence, queue length can be observed simultaneously and the relationship between intersections can be captured. Due to the current myriad of available queue length data, an analysis tool is needed to turn the data into useful knowledge to support traffic operations and management. However, the current queue length visualization only focuses on a real-time fashion, which cannot provide information about the change of the queue or its uncertainty. Such information is crucial for understanding the probability of the queue to be spillover, as well as determining the lengths of turning lanes to minimize blockage. In this research, we developed a spatial uncertainty-aware visualization by applying a conventional technique called box plot to visualize queue lengths on a map derived from taxi GPS data. A prototype of a web mapping application has been implemented and tested with users. The results indicated that participants with a statistics background have an advantage over those without a statistical background to understand the box plot. However, all of them were able to identify the uncertainty of the queue lengths as well as to compare the uncertainty between intersections and times.

Development of Spatial Uncertainty-Aware Visualization of Historical Traffic Queue Length

Traffic queue length at intersection is one of the most important measures of traffic signal performance and the traffic signal optimization. The spread of the ride-hailing services makes GPS data widely available with large area coverage, allowing us to quantify the queue length in a wide area without the need for additional installation cost like conventional sensors. Hence, queue length can be observed simultaneously and the relationship between intersections can be captured. Due to the current myriad of available queue length data, an analysis tool is needed to turn the data into useful knowledge to support traffic operations and management. However, the current queue length visualization only focuses on a real-time fashion, which cannot provide information about the change of the queue or its uncertainty. Such information is crucial for understanding the probability of the queue to be spillover, as well as determining the lengths of turning lanes to minimize blockage. In this research, we developed a spatial uncertainty-aware visualization by applying a conventional technique called box plot to visualize queue lengths on a map derived from taxi GPS data. A prototype of a web mapping application has been implemented and tested with users. The results indicated that participants with a statistics background have an advantage over those without a statistical background to understand the box plot. However, all of them were able to identify the uncertainty of the queue lengths as well as to compare the uncertainty between intersections and times.

Analysis of accessibility to hierarchical healthcare facilities in urban area: A case study in Shanghai

AbstractThe accessibility to healthcare facilities is closely linked to people's health and quality of life, which is especially evident in densely populated metropolises, such as Shanghai, China. Access to healthcare facilities is determined by various spatial and nonspatial factors, such as population, transportation modes, travel time, and the reputation of hospitals. In this research, with the consideration of all these factors mentioned above, a new approach based on the two‐step floating catchment area method and multi‐source datasets was proposed to measure the accessibility to these hierarchical healthcare facilities in Shanghai, China, including secondary hospitals and tertiary hospitals. In addition, a web mapping Application Programming Interface (API) was employed in this research to retrieve the traffic cost for different transportation modes and the analytic hierarchy process approach was also employed to help calculate the comprehensive accessibility in Shanghai considering both different types of hospitals and different modes of transportation. The results show that depending on modes of transportation, significant differences can be seen in accessibilities to different types of healthcare facilities. The calculated comprehensive accessibility reflects that the central regions in the research area have higher accessibility compared to the surrounding areas in Shanghai in general and more detailed spatial patterns could also been seen from the accessibility map. The research findings can also be utilized to support the better allocation of healthcare facilities at various levels.

A News-Based Framework for Uncovering and Tracking City Area Profiles: Assessment in Covid-19 Setting

In the last years, there has been an ever-increasing interest in profiling various aspects of city life, especially in the context of smart cities. This interest has become even more relevant recently when we have realized how dramatic events, such as the Covid-19 pandemic, can deeply affect the city life, producing drastic changes. Identifying and analyzing such changes, both at the city level and within single neighborhoods, may be a fundamental tool to better manage the current situation and provide sound strategies for future planning. Furthermore, such fine-grained and up-to-date characterization can represent a valuable asset for other tools and services, e.g., web mapping applications or real estate agency platforms. In this article, we propose a framework featuring a novel methodology to model and track changes in areas of the city by extracting information from online newspaper articles. The problem of uncovering clusters of news at specific times is tackled by means of the joint use of state-of-the-art language models to represent the articles, and of a density-based streaming clustering algorithm, properly shaped to deal with high-dimensional text embeddings. Furthermore, we propose a method to automatically label the obtained clusters in a semantically meaningful way, and we introduce a set of metrics aimed at tracking the temporal evolution of clusters. A case study focusing on the city of Rome during the Covid-19 pandemic is illustrated and discussed to evaluate the effectiveness of the proposed approach.

Multipurpose GIS Portal for Forest Management, Research, and Education

The main objective of this research was to develop a web-based geographic information system (GIS) based on a detailed analysis of user preferences from the perspective of forest research, management and education. An anonymous questionnaire was used to elicit user preferences for a hardware platform and evaluations of web-mapping applications, geographic data, and GIS tools. Mobile GIS was used slightly more often than desktop GIS. Web-mapping applications that provide information to the public and the present research results were rated higher than the forest management application. Orthophotos for general purposes and thematic layers such as forest stand maps, soils, protected areas, cadastre, and forest roads were preferred over highly specialized layers. Tools for data searching, map printing, measuring, and drawing on digital maps were rated higher than tools for online map editing and geographic analysis. The analysis of user preferences was used to design a new multipurpose GIS portal for the University Forest Enterprise. The GIS portal was designed with a three-tier architecture on top of the software library for managing user access, working interactively with digital maps, and managing web map applications. The web map applications focus on tools and geographic information not available elsewhere, specifically timber harvest and logistics, research plots, and hunting game management.

Daily Precipitation Data for the Mexico City Metropolitan Area from 1930 to 2015

The Metropolitan Zone of Mexico City, as well as the associated basin, includes the territories of Mexico City, some municipalities of the State of Mexico and the state of Hidalgo. In addition, this area is the most densely populated in Mexico. The region is influenced by mid-latitude and tropical weather systems and is vulnerable to extreme hydrometeorological events. In this context, we developed a dataset from the records of 136 geolocated sites that includes daily precipitation data from the CLImate COMputing (CLICOM) project and the Mexico City Water System. The data spans the period from 1930 to 2015 for the rainy months (June–October) from stations with records of 20 or more years. In each recording site, automatic and manual data quality control were performed to verify the consistency of the daily precipitation data. We believe that our highly dense precipitation dataset will be useful for climate, trend and extreme events analysis. Additionally, the data will allow validating simulations of numerical atmospheric models. The dataset is public, and it was previously used in other research to determine areas susceptible to flooding due to heavy rain events and to develop a web mapping application of daily precipitation data.

Isotopic composition of groundwater resources in arid environments

The availability and quality of limited groundwater resources in Egypt are negatively affected by both natural and anthropogenic forces. It is crucial to understand the recharge sources and mechanisms of country-scale aquifers in order to develop sustainable management scenarios for Egypt's groundwater resources. In this study, we compiled all historical hydrogen (δ2H) and oxygen (δ18O) stable isotopic compositions of 1618 ground- and surface-water samples collected for seven major aquifer and reservoir systems in Egypt. These data were then hosted in a public-domain web map application (https://bit.ly/3n9MtrM) that enables users to access, navigate, display, and analyze the isotopic composition of any water sample in Egypt. The developed application and customized web tools were then used to provide improved understanding of the country-wide water resources’ isotopic composition and to investigate the recharge sources and mechanisms of, and provide sustainable management scenarios for, the seven major Egyptian aquifer systems. Results indicate that (1) the alluvial and coastal aquifers are recharged from modern rainfall, floodwaters, and upward leakage from deep aquifers; (2) the Nile Valley and Delta, Moghra, and carbonate aquifers are receiving recharge from the Nile River, modern rainfall, irrigation canals and drains, and upward leakage from deep aquifers; (3) the Nubian aquifer receives modern recharge in areas of higher rainfall or close to surface water reservoirs; and (4) the fractured basement aquifers are recharged from modern rainfall and floodwaters. The developed cost-effective web application will guide locations and techniques for future field data collection; reduce time, efforts, and resources required for field activities; enable improved understanding the country-wide stable isotopic compositions of water resources; enhance understanding of nationwide recharge mechanisms; and enable the scientific community to address country-scale science questions in a unique way.

Determining the lithogeochemical background concentrations of 39 elements in Bavarian rocks

An approach is presented to establish a state-wide basis for geochemical background values from the available data of the Geological Survey of Bavaria. For this purpose, typical element background concentrations of rock units in Bavaria were statistically evaluated and presented in a lithogeochemical map derived from the geological map at a scale of 1:25,000. The elements comprise 39 geogenic main and trace elements (SiO2, Al2O3, Fe2O3, MnO, MgO, CaO, Na2O, K2O, TiO2, P2O5, Li, Be, Sc, V, Cr, Co, Ni, Cu, Zn, Ga, As, Rb, Sr, Y, Zr, Nb, Mo, Cd, Sn, Sb, Cs, Ba, La, Ce, Tl, Pb, Bi, Th, and U). The distributions of element concentrations in the lithogeochemical units follow closely lognormal patterns in a large majority of cases. Statistical parameters (10th, 25th, 50th, 75th, 90th percentiles) of investigated elements were determined using the cenfit function of the NADA package in the open-source R program. The investigation, based on 8,838 analysed samples, provided data for about 2/3 of the area of Bavaria. The lithogeochemical map with medians (50th percentiles) and background values (90th percentiles) of the investigated elements is available in a web map application. Thus, the regional geogenic background values of the investigated elements in Bavaria are publicly available for a large variety of applications, such as environmental issues and applied research questions.