Web Map Research Articles

Implementing the map task in applied linguistics research: What, how, and why

The “map task” is an interactive, goal-driven, real-time conversational task used to elicit semi-controlled natural language production data. We present recommendations for creating a bespoke map task that can be tailored to individual research projects and administered online using a chat interface. As proof of concept, we present a case study exemplifying our own implementation, designed to elicit informal written communication in either English or Spanish. Eight experimental maps were created, manipulating linguistic factors including lexical frequency, cognate status, and semantic ambiguity. Participants (N = 40) completed the task in pairs and took turns (i) providing directions based on a pre-traced route, or (ii) following directions to draw the route on an empty map. Computational measures of image similarity (e.g., structural similarity index) between pre-traced and participant-traced routes showed that participants completed the task successfully; we describe use of this method for measuring task success quantitatively. We also provide a comparative analysis of the language elicited in English and Spanish. The most frequently used words were roughly equivalent in both languages, encompassing primarily commands and items on the maps. Similarly, abbreviations, swear words, and slang present in both datasets indicated that the task successfully elicited informal communication. Interestingly, Spanish turns were longer and displayed a wider range of morphologically complex forms. English, conversely, displayed strategies mostly absent in Spanish, such as the use of cardinal directions as a communicative strategy. We consider the online map task as a promising method for examining a variety of phenomena in applied linguistics research.

How to transform urban institutional green spaces into Ancillary Botanic Gardens to expand informal botanical learning opportunities in cities

Since many cities lack botanical gardens, we introduced the concept of Ancillary Botanic Gardens (ABG), which builds on the premise that organizations can expand informal botanical learning by adding a secondary function to their institutional green spaces. This study guides the application of the ABG concept in various spatial and functional contexts by offering practical and interpretive tools to organizations who are less used to working with nature but are interested in mitigating urban residents’ detachment from nature. Online maps of 220 botanic gardens were reviewed to define types of plant collections and produce an exhaustive list of physical botanic garden elements. The collected information was developed into an ABG field checklist that was tested on three case studies in Lebanon and then used to develop guidelines for ABG establishment. The guidelines and checklist are meant to empower and guide organizations interested in establishing an ABG.

Landscape features shape people’s perception of ecosystem service supply areas

Landscapes have typically been produced by varied, diverse, and long-term interactions between people and nature. However, most landscape planning and ecosystem service mapping approaches focus on the biophysical aspects of landscapes rather the social. Spatial representations of people’s perceptions, mental models, and local knowledge of ecosystem services can be created using participatory mapping. This study uses participatory mapping to identify how peoples’ perceptions of provisioning, regulating and cultural ecosystem service supply areas coincide or mismatch with the landscapes features of two Mediterranean river basin areas in north-eastern Catalonia, Spain. We found that the random forest and geographically weighted regression techniques are able to strongly associate landscape features with stakeholders’ perceptions of ecosystem supply areas. These results demonstrate that the stakeholders associate various geographic elements with different types of ecosystem service supply areas. Visible geographical features, such as a reservoir, mountains, wetlands, showed great importance in the perception of supply areas of ecosystem services, compared to ecological or biophysical indicators, when mapping and spatially associating certain benefits to ecosystem services supply areas. These findings reveal that, often, the ecological processes and dynamics of functioning of ecosystems are invisible and not fully understood. We argue that integrating these aspects into participatory landscape planning, policies and practice can make the invisible visible and, consequently, increase the understanding for a more targeted and effective management. This could allow stakeholders to better understand the ecological processes behind the visible geographic features of the landscape, fostering a shared knowledge and better environmental management outcomes.

‘Secrecy, Trust, Safety’: a Multi-stakeholder Situation Assessment of Gendered and Contextual Vulnerabilities and Service Level Responsiveness to the Needs of Women Who Use Drugs in Egypt

AbstractWomen account for one in every three people who use drugs worldwide and tend to progress to drug use disorders in a shorter time than men. There is limited understanding of the situation of women who use drugs in the Middle East and North Africa. A multi-stakeholder rapid situation assessment (RSA) was conducted which aimed to investigate gendered and contextual vulnerabilities and service level responsiveness to the needs of women who use drugs (WWUD) in Egypt. An updated profile of female service user characteristics was sought via mapping of addiction and harm reduction services in the National Drug Observatory system. In-depth interviews were conducted with a purposive sample of representatives of UN agencies and health professionals providing treatment/harm reduction (government, private, community) (n = 21). Focus groups were facilitated with a convenience sample of women in treatment, accessing HIV services and community harm reduction services (n = 75). Thematic analysis and triangulation across data sources occurred. Eight themes emerged: profile of women who use drugs; access to drugs and settings for female drug use; dimensions of stigma; trauma and drivers of female drug use; networks and intimate partner relationships; high-risk behaviours and harms; barriers to help-seeking and accessing services; and enhancing gender-responsive and gender-transformative evidence-based services. This RSA yields a contemporary insight into the vulnerabilities, traumas, discrimination and stigma-related challenges experienced by WWUD in Egypt. Recommendations are made to enhance harm reduction awareness and uptake and to integrate gender-responsive care within existing maternal, addiction and harm reduction service structures.

Management Implications at a Protected, Peri-Urban, Salt Lake Ecosystem: The Case of Larnaca’s Salt Lakes (Cyprus)

Larnaca’s salt lakes constitute one of the most important protected areas in Cyprus and in the southeast Mediterranean. It is in continuity with the urban area of Larnaca city, being the major green infrastructure in the area, supporting (among others) biodiversity, recreation, culture, and food production. The present study aims to provide an overview of the area’s ecosystem types and their potential to provide ecosystem services, focusing on assessing the water ecosystem condition and drafting the relevant baseline accounts. The results of the study include an ecosystem type map of the area, followed by potential supply maps of ecosystem services, for the three major categories (i.e., provisioning, regulating and maintenance, and cultural) and the estimation and assessment of ecosystem condition variables for wetlands, as proposed by the EU-wide methodology to map and assess the ecosystem condition, in line with the System of Environmental Economic Accounting—Ecosystem Accounting (SEEA EA). A critical exceedance (over 10%) of the imperviousness and the increase in the soil moisture deficit within the wider salt lakes area have been identified and can constitute useful variables associated with the anthropogenic, climatic, and other effects on the condition of the salt lakes. Discussion for integrating this information to existing knowledge is provided toward supporting scientifically informed decision and policymaking for the sustainable development of protected areas.

A 3D Lidar SLAM System Based on Semantic Segmentation for Rubber-Tapping Robot

Simultaneous localization and mapping (SLAM) in rubber plantations is a challenging task for rubber-tapping robots. Due to the long-term stability of tree trunks in rubber plantations, a SLAM system based on semantic segmentation, called Se-LOAM, is proposed in this work. The 3D lidar point cloud datasets of trunks collected in rubber plantations of Hainan University are used to train the semantic model, and the model is used to extract features of trunk point clouds. After clustering the trunk point clouds, each single rubber tree instance is segmented based on the Viterbi algorithm. The point clouds of tree instances are fitted to the cylindrical trunk models for semantic cluster association and positional estimation, which are used for lidar odometry and mapping. The experimental results show that the present SLAM system is accurate in establishing online mapping, and the location of the trunk in the map is clearer. Specifically, the average relative pose error is 0.02 m, which is better than the positioning performance of LOAM and LeGO-LOAM. The average error of estimating the diameter at breast height (DBH) is 0.57 cm, and it only takes 401.4 kB to store a map of the area of approximately 500 m2, which is about 10% less than other classic methods. Therefore, Se-LOAM can meet the requirements of online mapping, providing a robust SLAM method for rubber-tapping robots.

Cyberinformatics tool for in-season crop-specific land cover monitoring: Design, implementation, and applications of iCrop

Cyberinformatics tools have supported decision makings in agriculture through cutting-edge big data, artificial intelligence/machine learning (AI/ML), and high-performance computing technologies. An open and easy-to-use agricultural cyberinformatics tool based on the findable, accessible, interoperable, reusable (FAIR) data principle is essential for the efficient distribution of crop-specific land cover information. This paper introduces iCrop, a new cyberinformatics tool to enable in-season crop type monitoring for the Conterminous United States (CONUS). As a web-based geographic information system (GIS), iCrop not only delivers three sets of new ML-based field-level crop-specific land cover geospatial data, including pre-season crop cover maps, in-season crop cover maps, and Refined Cropland Data Layer (R-CDL), but also provides a suite of mapping and geoprocessing functionalities through the FAIR geospatial data standards, such as Web Map Service (WMS), Web Coverage Service (WCS), and Web Processing Service (WPS). Meanwhile, we outline several use cases to highlight iCrop's applications under various agricultural operation scenarios, its functionality for land use change analysis, and its interoperability with generic web-based and desktop GIS software (e.g., GeoPlatform and QGIS). Our experimental results show that the new cyberinformatics tool can provide timely and unique crop-specific land cover information through the geoprocessing functionalities to facilitate U.S. agricultural information management and decision support. Moreover, this paper can be used as a systematic guidance for the design and implementation of the cyberinformatics tool to disseminate agro-geoinformation based on the FAIR data principle.

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.

LBS Tag Cloud: A Centralized Tag Cloud for Visualization of Points of Interest in Location-Based Services

Taking location-based service (LBS) as the research scenario and aiming at the limitation of visualizing LBS points of interest (POI) in conventional web maps, this article proposes a visualization method of LBS-POI based on tag cloud, which is called “LBS tag cloud”. In this method, the user location is taken as the layout center, and the name of the POI is converted into a text tag and then placed around the center. The tags’ size, color, and placement location are calculated based on other attributes of the POI. The calculation of placement location is at the core of the LBS tag cloud. Firstly, the tag’s initial placement position and layout priority are calculated based on polar coordinates, and the tags are placed in the initial placement position in the order of layout priority. Then, based on the force-directed model, a repulsive force is applied to the tag from the layout center to make it move to a position without overlapping with other tags. During the move, the quadtree partition of the text glyph is used to optimize the detection of overlaps between tags. Taking scenic spots as an example, the experimental results show that the LBS tag cloud can present the attributes and distribution of POIs completely and intuitively and can effectively represent the relationship between the POIs and user location, which is a new visualization form suitable for spatial cognition.

Map preference for finding one's home and neighboring homes

This paper shares findings from two surveys suggesting that people in the U.S. prefer the online map type with the satellite image over the road map for a location task of finding their residential home and neighboring homes. While satellite images were preferred, adding more detail to the that map type, such as frontal views of neighboring homes or additional identifiers on those homes did not increase preference. For road maps, we found some indication that adding elements such as the front picture of homes was more preferred by younger adults than older adults. Respondent education level or the characteristics of the neighborhood where the respondent lived did not affect map preference for this self-location task in any meaningful pattern. This preference for satellite maps matches other research findings where these maps are preferred for self-location tasks.

Penyuluhan Pencegahan Pernikahan Dini pada Usia Remaja di Sekolah Menengah Pertama

This service aims to provide education as an effort to prevent early marriage at a young age for students at SMP Negeri 4 Selong, East Lombok. This service is carried out using the Participatory Action Research (PAR) method with the following stages: (1) initial mapping, (2) building communication with teachers and students, (3) determining service topics and mapping problems, (5) compiling technical activities, ( 6) carry out community service activities, (7) form discussion groups, (8) reflect. The results of the participant satisfaction survey for this community service activity showed very positive results. One of them is shown by the number of questions asked by the participants, related to the material presented. In addition, the participants also shared their personal experiences with those closest to them who were under direct pressure from their parents to marry early. The satisfaction of the participants was also inseparable from the speakers presented who were competent and focused on social issues, humble in nature so that they could place themselves well in the midst of teenage students.

ABLA: Application-Based Load-Balanced Approach for Adaptive Mapping of Datacenter Networks

Cloud-based services are growing more rapidly than ever, and so does the management challenge on their providers’ side. Cloud-based datacenter networks are built with nodes of huge processing power, connected by high bandwidth capacities to carry their interior traffic requirements. However, such cloud networks still have limits that are imposed not necessarily by their physical components, but by the schemes of resource management being deployed. Traditionally, for an institute to provide services, it needs to have its own datacenter facility that interconnects its servers through a topology that matches its desired administrative policies and scaling objectives. With the theme of cloud-based IaaS, such datacenter topologies can be created virtually over the cloud. Nowadays, a significant part of those institutes who provide us with our daily services have their infrastructures hosted over cloud ones. Therefore, resources of such cloud networks need to be efficiently utilized, in order to keep their performance and hosting prices competitive. A typical datacenter network mainly consists of server nodes and network links. Besides the resources of the server nodes, the network bandwidth resources are considered a crucial key determinant for the whole datacenter performance. Indeed, a server without sufficient bandwidth capacities is almost useless. Proposals in the literature present schemes for resource utilization on either side of the problem at a time: the nodes or the links. Working in isolation can never deliver efficient mapping solutions. ABLA is an Application-Based, and Load balancing Approach for adaptive mapping proposal. ABLA’s methodology tackles both sides of the datacenter, the nodes and links. It starts by (1) breaking down the node’s resource requirement for the requested applications to be hosted over the virtual server machines besides (2) reading the topological connectivity and bandwidth requirements for each virtual node to all other nodes in the virtual datacenter topology. Compared to other models in the literature, the simulation results show that our proposed ABLA model provides for complete mapping services via load-balanced hosting networks. This allows for competitive hosting prices, with higher performance and service satisfaction rates.

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.

Online Destinations Map using Google Maps API Based on the Private Database

Online mapping applications have undergone a radical change as a result of the widespread use of the Internet,and an interested in the developing of the online mapping services due to the use of the Google Maps Application Programming Interface (API), Yahoo Maps API, and ESRI ArcGIS API, as well as the support for maps by operating systems on tablets and smartphones. One of the most helpful technologies for identifying locations and providing information about roads is online mapping. Although these applications are simple to use, they have a limited amount of the data that may be inaccurate, and the mapping technology does not have sophisticated or detailed characteristics of the required places. As a result, developers and programmers use maps as a platform to create features that are tailored to the needs of the user by using various programming languages. The goal of this paper is to develop the Google API by connecting it to a local, private database that houses data that is regularly gathered and developed. It also aims to create opportunities that make it easier for clients to access information stored on particular servers that can provide a variety of locations and details in order to meet their needs.

Assessment and cultural ecosystem service mapping in mountain protected areas – “Pirin” National park

The assessment and mapping of ecosystems and their services is considered an important action that effectively contributes to proper understanding of how ecosystems support human well-being, and furthermore – to promote the sustainable use of natural resources. The diversity of cultural landscapes, especially in mountain areas, is a significant prerequisite for a variety of cultural ecosystem services that are valuable for the society. This evaluation is the basis for environmental management practices and policymaking. The study presents an approach for assessment and mapping of cultural ecosystem service (CES) “Cultural heritage” that is recognised as important and is provided by mountain protected areas (PAs) in “Pirin” National Park. The data from the Management Plan of “Pirin” NP were used for characterization and biophysical assessment of the condition of forest ecosystems and their potential to provide CESs. The analysis of the results revealed that the conservation regime allowed the territories to preserve a high degree of naturalness and a very good ecological condition as 94.80% of forest ecosystems are assessed with score 4 –“good” condition and 0.44% are with “very good” condition – score 5. The majority of forest ecosystems with “very good” ecological condition are Pinus peuce forests, located mainly on the territory of the reserves “Bayuvi Dupki- Dzhindzhiritsa” and “Yulen”, proving the importance of the protective regime of the territories. Forest ecosystems with average and high capacity to provide ES "Cultural heritage" prevailed, which is consistent with well-preserved and unique nature, the diversity of landscapes, and species richness. Considerable areas were assessed with score 5 – very high capacity, mostly on the territory of the reserves “Bayuvi Dupki- Dzhindzhiritsa” and “Yulen”, and at the foothill of the huts.

Modeling risks in marine protected areas: Mapping of habitats, biodiversity, and cultural ecosystem services in the southernmost atlantic coral reef

Marine Protected Area (MPA) is a fundamental strategy for the maintenance of ocean ecological processes worldwide and, consequently, their associated ecosystem services. Nevertheless, the quality of the services provided by MPAs, including cultural services such as recreational activities, depends on the effective management of marine habitats and biodiversity. Here, we performed an ecosystemic assessment in reef environments within a subtropical MPA, modeling the potential risks for their habitats and their recreational activities. The Queimada Grande Island (QGI), southeastern Brazil, was used as the model area since this island encompasses a unique and irreplaceable marine habitat, the Southernmost Atlantic coral reef. We firstly assessed and mapped the habitats, the biodiversity, and the recreational activities associated with QGI reefs. Next, we considered different scenarios of management for the modeling risks across the study area. We found that the coral reef and its adjacent habitats, such as the rhodolith bed, make the sheltered face of the island an important area for the provision of the cultural ecosystem services and overlapping uses such as onboard recreational fishing, spearfishing, and recreational diving. This area was also evaluated as the one under the highest risk of impact, considering the current scenario of management. The most successful scenario modeling to reduce these risks was the hypothetical implementation of a 66% reduction of all activities over all QGI habitats. Despite that, the scenario simulating the application of the regulations present in the MPA management plan was enough to reduce almost half the maximum risk value. Therefore, we concluded that to provide a balance among conservation, uses, and the local economy, the application of these regulations is the better management scenario modeled for the study area. Such results provided useful information and tools for local management and decision-making in this singular marine environment, also being an example for mapping ecosystem services and modeling risks in MPAs worldwide.

Building use and mixed-use classification with a transformer-based network fusing satellite images and geospatial textual information

Assigning detailed use categories to buildings is a challenging and relevant task in urban land use classification with applications in urban planning, digital city modelling and twinning. This study aims to provide the categorisation of buildings with detailed use information by considering the possibilities of mixed-use. Mixed-use combines different use forms, and serves as a new type of use category. We obtain attributive information by combining satellite imagery that reflects spatial information and textual information from publicly available point-of-interest data collected by citizens and available on online maps. We propose a multimodal transformer-based building-use classification method to capture and fuse these different data sources within an end-to-end learning workflow. We evaluate the effectiveness of our proposed method on four urban areas in China. Experiments show that the proposed method effectively maps building use according to eight types of fine-grain categories, with a Micro F1 score equal to 80.9%, and a Macro F1 score equal to 62% for Wuhan research area. The proposed method is able to harness the relationship between the features obtained from the different data sources and results in higher accuracy than the state-of-the-art fusion-based multimodal integration methods. The proposed method can effectively increase the attributive grain of building use resulting in high classification accuracy.

Australian National Species List: name identifier management and linkages

The Australian National Species List (AuNSL) is the provider of names and taxonomy for significant national biodiversity data infrastructures including the Atlas of Living Australia, the Terrestrial Ecosystem Research Network, the Biodiversity Data Repository, and the Species Profile and Threats Database. The AuNSL mints persistent identifiers for names covered by the codes of nomenclature and name-like objects such as phrase names. To ensure sustainability of identifiers, a mapping service is provided to always resolve all AuNSL identifiers including historical and deprecated forms. Names are used as the building blocks for recording taxon name usages and taxon concepts. We provide services for matching, disambiguation and taxonomic resolution of names. The AuNSL does not exist in a vacuum and supports identifier mappings to external resources and related systems such as the International Plant Name Index (IPNI), Zoobank, the Biodiversity Heritage Library. To enable this integration, persistent identifiers from original and/or significant sources are required and this data is currently limited and incomplete within the AuNSL. To address this issue, we need to look backwards for improved ways of matching to existing persistent identifiers and forward to improving capture of taxonomic novelties and name-like objects and their identifiers.

Assessment of Required Patient Travel to Receive Interventional Radiology Services in the Resource-Limited Setting of Tanzania

This study aimed to evaluate the geographic patient profile of a country’s first interventional radiology (IR) service in sub-Saharan Africa. From October 2018 to August 2022, travel time (1,339 patients) and home region (1,184 patients) were recorded from 1,434 patients who underwent IR procedures at Tanzania’s largest referral center. Distances traveled by road were calculated from the administrative capital of each region using a web mapping platform (google.com/maps). The effect of various factors on distance and time traveled were assessed. Patients from all 31 regions in Tanzania underwent IR procedures. The mean and maximum calculated distance traveled by patients were 241.6 km and 1,387 km, respectively (Sk2 = 1.66); 25.0% of patients traveled for over 6 hours for their procedure. Patients traveled furthest for genitourinary procedures (mean = 293.4 km) and least for angioplasty and stent placement (mean = 123.9 km) (P < .001). To increase population access and reduce travel times, geographic data should be used to decentralize services.

Catchment-Area Delineation Approach Considering Travel Purposes for Station-Level Ridership Prediction Task

Station-catchment-area delineation is a key component of direct ridership models for urban rail-transport systems as it can determine the relationship between the urban-rail-transit station-level ridership and the variables within the station catchment area. The neglect of differences in the passenger-flow distribution for different travel purposes in previous studies has led to low accuracy of the obtained walk-to-station distances. Therefore, this paper proposes a station-catchment-area delineation method which is based on web map data to obtain accurate walk-to-station distances and considers differences in the distance thresholds and the ridership attraction intensity (RAI) for six travel purposes (corresponding to commercial, medical, residential, educational, administrative, and recreational land uses). In the case study, the ridership data of Xi’an Metro, the 2015 Xi’an Residential Travel Survey data, and the corresponding Gaode Map data are employed to extract passengers’ walking-distance distribution for several travel purposes to delineate the station catchment areas and build direct ridership models. Several geographically weighted regression (GWR) models are constructed to evaluate and examine the effects of the various station-catchment-area delineation methods on the model findings. The obtained results show that the proposed station-catchment-area delineation method significantly improves the ridership prediction performance compared with the traditional circular-buffer method, with the entry and exit ridership prediction accuracy improving by 3.57% and 6.65% on average, respectively. Finally, this study will guide transportation planners on how to delineate station catchment areas when constructing direct-demand models for urban rail stations.