Geographic Information Applications Research Articles

An ontology‐based semantic description model of ubiquitous map images

AbstractMap images with various themes and cartographic representations have become ubiquitous on the Internet. Such ubiquitously and openly accessible data, named ubiquitous map images in this study, are a potential resource for many geographic information applications such as cartographic design. However, there is a semantic gap between the simple physical form and the complex connotation of ubiquitous map images, which hinders their further applications. To mitigate such barrier, this article develops an ontology‐based semantic description model for ubiquitous map images. First, we discuss the design concerns and principles of the semantic description model of ubiquitous map images. Second, three semantic layers of the semantic description model are proposed, that is, image semantic description layer, cognitive tool layer, and information source layer, and detailed semantic description items are defined for each layer. Furthermore, a formalized semantic description model for ubiquitous map images is developed using ontology construction tools, which lays the foundation for automated and fine‐grained reasoning with the information embedded in map images. We construct a small test dataset consisting of weather maps, and use three types of constraints, namely “time‐topic,” “region‐topic,” and “map auxiliary elements” for the semantic retrieval experiments. The experiments show that the proposed semantic ontology model can enable complex semantic retrieval of ubiquitous map images. Finally, the scalability of the model is discussed from three perspectives: the depth of description, the combination with intelligent methods, and the integration with other open knowledge bases. The proposed model provides a semantic label system for applying data‐driven approaches to decode ubiquitous map images, which also paves the path to the development of cartographic theory in the era of information and communications technologies.

A Building Extraction Method for High-Resolution Remote Sensing Images with Multiple Attentions and Parallel Encoders Combining Enhanced Spectral Information

Accurately extracting pixel-level buildings from high-resolution remote sensing images is significant for various geographical information applications. Influenced by different natural, cultural, and social development levels, buildings may vary in shape and distribution, making it difficult for the network to maintain a stable segmentation effect of buildings in different areas of the image. In addition, the complex spectra of features in remote sensing images can affect the extracted details of multi-scale buildings in different ways. To this end, this study selects parts of Xi’an City, Shaanxi Province, China, as the study area. A parallel encoded building extraction network (MARS-Net) incorporating multiple attention mechanisms is proposed. MARS-Net builds its parallel encoder through DCNN and transformer to take advantage of their extraction of local and global features. According to the different depth positions of the network, coordinate attention (CA) and convolutional block attention module (CBAM) are introduced to bridge the encoder and decoder to retain richer spatial and semantic information during the encoding process, and adding the dense atrous spatial pyramid pooling (DenseASPP) captures multi-scale contextual information during the upsampling of the layers of the decoder. In addition, a spectral information enhancement module (SIEM) is designed in this study. SIEM further enhances building segmentation by blending and enhancing multi-band building information with relationships between bands. The experimental results show that MARS-Net performs better extraction results and obtains more effective enhancement after adding SIEM. The IoU on the self-built Xi’an and WHU building datasets are 87.53% and 89.62%, respectively, while the respective F1 scores are 93.34% and 94.52%.

AI for Computational Vision, Natural Language Processing, and Geoinformatics

The rapid development of artificial intelligence technology has had a huge impact on the fields of computer vision, natural language processing, and geographic information applications [...]

Inconsistency Detection in Cross-Layer Tile Maps with Super-Pixel Segmentation

The consistency of geospatial data is of great significance for the application and updating of geographic information in web maps. Due to the multiple data sources and different temporal versions, the tile web maps usually meet the inconsistency question across different layers. This study tries to develop a method to detect this kind of inconsistency utilizing a raster-based scaling approach. Compared with vector-based handling, this method can be directly available for multi-level tile images in a pixel representation form. The proposed cross-layer raster tile map rendering method (CRTMRM) consists of four primary aspects: geographic object separation, consistency rendering rules, data scaling and derivation with super-pixel segmentation, and inconsistency detection. The scale transformation strategy with the super-pixel attempts to obtain a simplified representation. Taking the scale lifespan variation and geometric consistency rules into account, the inconsistency detection of tile maps is conducted between temporal versions, multi-sources, and different scales through actual and derived data overlay analysis. The experiment focuses on features of cross-layer water or vegetation areas with Level 9 to Level 14 in Baidu Maps, Amap, and Google Maps. This method is able to serve as a basis for massive unstructured web map data inconsistency detection and support intelligent web map rendering.

An AR Map Virtual–Real Fusion Method Based on Element Recognition

The application of AR to explore augmented map representation has become a research hotspot due to the growing application of AR in maps and geographic information in addition to the rising demand for automated map interpretation. Taking the AR map as the research object, this paper focuses on AR map tracking and registration and the virtual–real fusion method based on element recognition. It strives to establish a new geographic information visualization interface and application model. AR technology is applied to the augmented representation of 2D planar maps. A step-by-step identification and extraction method of unmarked map elements are designed and proposed based on the analysis of the characteristics of planar map elements. This method combines the spatial and attribute characteristics of point-like elements and line-like elements, extracts the color, geometric features, and spatial distribution of map elements through computer vision methods, and completes the identification and automatic extraction of map elements. The multi-target image recognition and extraction method based on template and contour matching, and the line element recognition and extraction method based on color space and area growth are introduced in detail. Then, 3D tracking and registration is used to realize the unmarked tracking and registration of planar map element images, and the AR map virtual–real fusion algorithm is proposed. The experimental results and results of an analysis of stepwise identification and extraction of unmarked map elements and map virtual–real fusion reveal that the stepwise identification of unmarked map elements and map model virtual–real fusion studied in this paper is effective. Through the analysis of map element step-by-step recognition efficiency and recognition rate, it is proved that the element step-by-step method in this paper is fast, its recognition efficiency meets the AR real-time requirements, and its recognition accuracy is high.

A graph-based approach for representing addresses in geocoding

Addresses, one of the most important geographical reference systems in natural languages, are usually used to search spatial objects in daily life. Geocoding concatenates text with georeferenced coordinates and is an essential middleware service in geographic information applications. Despite its importance, geocoding remains challenging with only text as input, hindering text matching in reference databases without the specific text. To optimize the storage and retrieval of addresses in databases, this work proposes a graph-based approach for representing addresses. The approach clarifies the characteristics of relative concepts, designs a graph structure and identifies modelling strategies. Furthermore, a schema is proposed to perform address matching and toponym disambiguation using an address graph. The model is implemented on a graph database, and experimental tasks are employed to demonstrate its effectiveness. The approach provides a new reference for developers when creating address databases.

A North–South Problem in Civic-Tech and Volunteered Geographic Information as Countermeasures of COVID-19: A Brief Overview

The aim of this paper is to archive the situation we are witnessing regarding the application of geographic information by civic tech and volunteers, who spontaneously organised themselves to fight this newly emerging disease. Moreover, the regional bias and clarify the existence of a kind of North–South problem in the characteristics of the mapping process is aimed to be pointed out. Specific keywords were searcher after which research was performed using citations and keywords in the papers. In repositories such as GitHub, the search was performed using the country name to ensure that there were no omissions. In response to CoV19, which suddenly engulfed the world, simultaneous anti-CoV19 dashboards created by citizens with computer skills were published within a month or two of the outbreak’s beginning. North–South problem of our world extends to the availability and accessibility of information. Information and economic disparities also tend to cast a shadow on the response phase of society.

TECHNOLOGICAL FRAMEWORK OF INTELLIGENT MANAGEMENT AND APPLICATION ON GEOGRAPHIC INFORMATION

Abstract. The traditional geographic information management and application mode cannot meet the needs of intelligent management and on demand application of massive multi-source heterogeneous data. Therefore, in this paper, we propose a technical framework of intelligent governance and application of geographic information. This technical framework is intended to realize the transformation of geographic information inspection from complexity to simplicity and stability, data management from isolated island to integration, and data application from single to on-demand. In the process of intelligent management of geographic information, this paper mainly carries out technical research from different links of collection, management, storage and apply, so as to optimize and improve the quality control, state detection, intelligent management and decision-making application of geographic information. The research contents include three parts, including quality intelligent control, multidimensional data management and life cycle intelligent monitoring.

Research on the Development and Typical Application of Surveying and Mapping Geographic Information under the Background of Big Data

Research on the Development and Typical Application of Surveying and Mapping Geographic Information under the Background of Big Data

ChineseTR: A weakly supervised toponym recognition architecture based on automatic training data generator and deep neural network

AbstractToponym recognition is used to extract toponyms from natural language texts, which is a fundamental task of ubiquitous geographic information applications. Existing toponym recognition methods with state‐of‐the‐art performance mainly leverage supervised learning (i.e., deep‐learning‐based approaches) with parameters learned from massive, labeled datasets that must be annotated manually. This is a great inconvenience when model training needs to fit different domain texts, especially those of social media messaging. To address this issue, this article proposes a weakly supervised Chinese toponym recognition (ChineseTR) architecture that leverages a training dataset creator that generates training datasets automatically based on word collections and associated word frequencies from various texts and an extension recognizer that employs a basic bidirectional recurrent neural network based on particular features designed for toponym recognition. The results show that the proposed ChineseTR achieves a 0.76 F1 score in a corpus with a 0.718 out‐of‐vocabulary rate and a 0.903 in‐vocabulary rate. All comparative experiments demonstrate that ChineseTR is an effective and scalable architecture that recognizes toponyms.

Retraction Note to: UI design of visual communication of coastal city landscape based on embedded network system and remote sensing data

Now the development speed of cities is getting faster and faster, and many cities have reached the stage of urban landscape design. At this stage, the requirements for the urban landscape are mainly in the transmission of information, which can be summarized as the identification of information, the requirements for ideology and readability, which clearly tells urban planners that they need to receive information from the perspective of vision To design the urban landscape. After investigation, it is found that under the current technological development trend, the application of geographic information based on smart mobile terminals has become a development trend and has become one of the research hotspots in the field of geographic information science. With more and more methods of acquiring geographic information, such as smart phones, drones, and remote sensing satellites, a large amount of spatial data is continuously presented at an extremely fast speed. In recent years, the rapid development of the computer hardware manufacturing industry has made great contributions to the performance of embedded devices in improving computing speed and expanding memory. In this high-speed development environment, the fittest will survive, and the inadequate will be eliminated. Under the background of the information age, any new field will face the problem of short life cycle. Although UI also has it, the development of UI still has a long way to go. Therefore, the UI design industry still has great development prospects.

Application of Surveying and Mapping and Geographic Information New Technology in Mine Survey

Application of Surveying and Mapping and Geographic Information New Technology in Mine Survey

Tracing the source of heavy metal pollution in water sources of Tourist Attractions Based on GIS remote sensing

To effectively prevent heavy metal pollution in water sources in tourist attractions, clarify the degree of control of heavy metal pollution sources, and improve the accuracy of tracing results, a GIS-based remote sensing method of heavy metal pollution in tourist attractions is proposed. Using GIS spatial analysis method, the DEM elevation data monitored by remote sensing is obtained, the watershed geographic information is compiled, and the GPS obtains the longitude and latitude coordinates to locate the source of heavy metal pollution. The plug-in application framework is designed, and the watershed geographic information and plug-in application framework are integrated to build the pollution tracing platform. According to the mixing direction of pollutants after entering the water source, the migration and diffusion coordinate system of heavy metal pollution in the water source is established. The spatial-temporal distribution function model of heavy metal pollutants in water sources is constructed through the migration, transformation, and concentration of heavy metal pollutants in water sources. The tracing results of heavy metal pollution in water sources of scenic spots are obtained. The results showed that the order of variation coefficient of heavy metal pollution elements was Cr > Cd > Cu > Ni > Zn > Pb. The spatial distribution of heavy metal pollution elements was extremely uneven. There was a certain positive correlation between Ni and Cr, and the correlation coefficient of Cu and Zn was 0.78. The positive correlation was very significant, and the homology was very strong. Moreover, the identification result of the proposed method is very close to the real value, which can accurately trace the source of heavy metal pollution in the water source of tourist attractions, with small tracing error and high accuracy of tracing result evaluation.

Application of mapping geographic information in emergency mapping

With the continuous development of geographic information surveying and mapping technology, emergency surveying and mapping puts forward higher requirements for surveying and mapping work. Whenever an emergency occurs, emergency investigation and geographic mapping provide effective and reliable information for the emergency situation. In addition, emergency surveying puts forward higher requirements for mapping geographic information. Analyzing the application of surveying and mapping geographic information technology in emergency surveying and mapping, such as the application of data collection technology and virtual reality technology, can effectively enhance the role of geographic information technology in emergency surveying and mapping, and improve the ability of emergency response. This paper mainly analyzes the application of geographic information in emergency surveying and mapping and related technical fields, and explores the main application trends of emergency surveying and mapping.

SCA-CDNet: a robust siamese correlation-and-attention-based change detection network for bitemporal VHR images

ABSTRACT Change detection is a key step in various geographic information applications such as land cover change monitoring, agricultural assessment, natural disaster evaluation, and illegal building investigation. In practice, discovering, or outlining these changes is labour intensive and time-consuming. To address this problem, a novel end-to-end Siamese correlation-and-attention-based change detection network (SCA-CDNet) is proposed for bitemporal very-high-resolution images in this paper. In this method, five strategies are adopted to improve the final change detection results. First, data augmentation is used to reduce the overfitting effectively and improve the generalization ability of the training model. Second, in encoding, classic networks (e.g. ResNet) are introduced to extract the multiscale features of the image and make full use of the existing pretraining weights of the network to reduce the difficulty of subsequent model training. Third, a new correlation module is designed to stack the above bitemporal features correspondingly and extract change features with smaller dimensions. Fourth, an attention model is introduced between the correlation module and the decoder module to make the network pay more attention to areas or channels with a greater effect on change analysis. Fifth, a new weighted cross-entropy loss function is designed, which enables training to focus on error detection and improve the final accuracy of the training model. Finally, extensive experimental results on three public data sets including the evaluation of data augmentation, ablation study, and comparison with the state of the art demonstrate the effectiveness and superiority of our proposed method, achieving an intersection of union (IoU) of 84.15%, 83.50%, and 77.29% on the three data sets, respectively.

RESEARCH AND ENGINEERING PRACTICE OF EMERGENCY GEOGRAPHIC INFORMATION COLLABORATIVE SERVICE MODE WITH CROWDSOURCED DATA

Abstract. China is a disaster prone country. In recent years, the national functional departments have been committed to the construction of emergency surveying and mapping support capacity. However, the data owned by government departments are often systematic, accurate and authoritative, but the real-time is not enough. The improvement of data update efficiency requires a lot of resources. The main body of emergency management is also mainly government departments, which lacks public participation and interaction. The application of volunteer geographic information in China's emergency management has not yet formed a scale. This article will mainly studies the mechanism of volunteer information in emergency management, the multi-source emergency geographic information collaborative service mode with volunteer participation, and take specific engineering practices as an example to introduce the national Geographic Information Public Service Platform for Disaster Emergency, and try to solve the problems about real-time disaster site information acquisition, multi-source information online integration and collaborative services, and rapid customization and release of user-oriented emergency topics in multiple emergency scenarios Issues.

RETRACTED ARTICLE: UI design of visual communication of coastal city landscape based on embedded network system and remote sensing data

Now the development speed of cities is getting faster and faster, and many cities have reached the stage of urban landscape design. At this stage, the requirements for the urban landscape are mainly in the transmission of information, which can be summarized as the identification of information, the requirements for ideology and readability, which clearly tells urban planners that they need to receive information from the perspective of vision To design the urban landscape. After investigation, it is found that under the current technological development trend, the application of geographic information based on smart mobile terminals has become a development trend and has become one of the research hotspots in the field of geographic information science. With more and more methods of acquiring geographic information, such as smart phones, drones, and remote sensing satellites, a large amount of spatial data is continuously presented at an extremely fast speed. In recent years, the rapid development of the computer hardware manufacturing industry has made great contributions to the performance of embedded devices in improving computing speed and expanding memory. In this high-speed development environment, the fittest will survive, and the inadequate will be eliminated. Under the background of the information age, any new field will face the problem of short life cycle. Although UI also has it, the development of UI still has a long way to go. Therefore, the UI design industry still has great development prospects.

Design of tourism application for Morotai island

Morotai Island Regency is one of the new districts located in the eastern tip of North Maluku Province, Northern Indonesia. Morotai Island has several beautiful tourist spots that attracts the attention of foreign and local tourists to visit the places. The aim of the research was to discuss the use of internet technology as a medium for the introduction of Morotai Island tourism. The research intended to make a mobile application for tour packages and location-based services (LBS) so that it could find out routes and locations to destinations easily and quickly. The mobile application used some media or storage assistance in MySQL for databases on the Web server. The search application also had the main feature that could find the easiest and closest destination location based on where the user’s location was located just by utilising GPS technology. The results of the research present a geographic information system (GIS) or application for Morotai Island tourist destinations and show that this information media is feasible. The app is for tourists to know and find the location of attractions easily and quickly.

A Risk Management Database Framework Implementation for Transportation Asset Management

A 2017 survey of the state of practice on how agencies are developing their risk-based asset management plan shows that state highway agencies are increasingly adapting the way they do business to include explicit considerations of risks. At the moment, this consideration of risk is not linked to data. Hence, there is a lack of integration of risk management in driving strategic cross-asset programming and decision-making. This paper proposes and implements a risk management database framework as the missing piece in the full implementation of a risk-based transportation asset management program. This risk management database framework utilizes Geographic Information Systems (GIS) and Application Programming Interface (API) to implement a risk management database of all the relevant variables an agency needs for risk modeling to improve risk monitoring, risk register updates, and decision-making. This approach allows the use of existing enterprise as well as legacy data collection systems, which eliminates the need for any capital-intensive implementation cost. Furthermore, it provides transportation agencies with the ability to track risk in quantitative terms, a framework for prioritizing risk, and the development of an actionable plan for risk mitigation. In this paper, the implementation of the fully integrated GIS-enabled risk management database employs the Iowa department of transportation (DOT) data and risk register.

State-of-the-Art Geospatial Information Processing in NoSQL Databases

Geospatial information has been indispensable for many application fields, including traffic planning, urban planning, and energy management. Geospatial data are mainly stored in relational databases that have been developed over several decades, and most geographic information applications are desktop applications. With the arrival of big data, geospatial information applications are also being modified into, e.g., mobile platforms and Geospatial Web Services, which require changeable data schemas, faster query response times, and more flexible scalability than traditional spatial relational databases currently have. To respond to these new requirements, NoSQL (Not only SQL) databases are now being adopted for geospatial data storage, management, and queries. This paper reviews state-of-the-art geospatial data processing in the 10 most popular NoSQL databases. We summarize the supported geometry objects, main geometry functions, spatial indexes, query languages, and data formats of these 10 NoSQL databases. Moreover, the pros and cons of these NoSQL databases are analyzed in terms of geospatial data processing. A literature review and analysis showed that current document databases may be more suitable for massive geospatial data processing than are other NoSQL databases due to their comprehensive support for geometry objects and data formats and their performance, geospatial functions, index methods, and academic development. However, depending on the application scenarios, graph databases, key-value, and wide column databases have their own advantages.