Map Symbols Research Articles

Automated Icon Extraction from Tourism Maps: A Synergistic Approach Integrating YOLOv8x and SAM

Map symbols play a crucial role in cartographic representation. Among these symbols, icons are particularly valued for their vivid and intuitive designs, making them widely utilized in tourist maps. However, the diversity and complexity of these symbols present significant challenges to cartographic workflows. Icon design often relies on manual drawing, which is not only time-consuming but also heavily dependent on specialized skills. Automating the extraction of symbols from existing maps could greatly enhance the map symbol database, offering a valuable resource to support both symbol design and map production. Nevertheless, the intricate shapes and dense distribution of symbols in tourist maps complicate the accurate and efficient detection and extraction using existing methods. Previous studies have shown that You Only Look Once (YOLO) series models demonstrate strong performance in object detection, offering high accuracy and speed. However, these models are less effective in fine-grained boundary segmentation. To address this limitation, this article proposes integrating YOLO models with the Segment Anything Model (SAM) to tackle the challenges of combining efficient detection with precise segmentation. This article developed a dataset consisting of both paper-based and digital tourist maps, with annotations for five main categories of symbols: human landscapes, natural sceneries, humans, animals, and cultural elements. The performance of various YOLO model variants was systematically evaluated using this dataset. Additionally, a user interaction mechanism was incorporated to review and refine detection results, which were subsequently used as prompts for the SAM to perform precise symbol segmentation. The results indicate that the YOLOv8x model achieved excellent performance on the tourist map dataset, with an average detection accuracy of 94.4% across the five symbol categories, fully meeting the requirements for symbol detection tasks. The inclusion of a user interaction mechanism enhanced the reliability and flexibility of detection outcomes, while the integration of the SAM significantly improved the precision of symbol boundary extraction. In conclusion, the integration of YOLOv8x and SAM provides a robust and effective solution for automating the extraction of map symbols. This approach not only reduces the manual workload involved in dataset annotation, but also offers valuable theoretical and practical insights for enhancing cartographic efficiency.

Assessment of how uncertainty representation in flood maps can affect geographic-based decisions

Flood maps that show predicted flood extents will always be uncertain regardless of how the modelling is conducted. It is therefore important that these uncertainties are represented and communicated in the maps, and that map users understand the presented information. Through an online user survey, this study evaluates how users make geographic decisions based on nine flood uncertainty maps, represented and designed according to data scheme and semantics associated with their values (dual-ended, sequential and binary), and applied with different mapping techniques (continuous surface, choropleth and graduated symbol mapping). The results show that the type of map and the visual variable used for representation (in terms of colours and values) became important when deciding locations. Higher decision confidence was shown when dual-ended and sequential probability maps were used. Medium-to-dark blue regions in these maps made participants avoid locations, while white, brown and the lightest blue colours made them select locations. The usage of a sequential map represented by grey scale colour showed to be less intuitive for the participants, leading to lower task performance and less confidence in decisions. Despite the different backgrounds of participants, comprehension of the uncertainty maps and the tasks did not vary much from each other. Differences among them were observed in location preferences and time to solve the tasks. The user group that had the most professional experience with maps and GIS was most conservative in their site choices, and took longest time to solve the tasks. Students, on the other hand, opted to take more risk in their decisions and preferred more uncertain locations. Apparently, the effectiveness of the flood uncertainty maps used in this study varied mainly on the representations used. Appropriate design made them comprehendible by different users. However, making decisions based on these maps, as well as confidence in decisions and time to solve the task, may also be dependent on other factors such as domain knowledge, line of work, practical experience in handing problems or making decisions, and possibly culture.

A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: A Case Study for California and Oklahoma.

Undocumented Orphaned Wells (UOWs) are wells without an operator that have limited or no documentation with regulatory authorities. An estimated 310,000 to 800,000 UOWs exist in the United States (US), whose locations are largely unknown. These wells can potentially leak methane and other volatile organic compounds to the atmosphere, and contaminate groundwater. In this study, we developed a novel framework utilizing a state-of-the-art computer vision neural network model to identify the precise locations of potential UOWs. The U-Net model is trained to detect oil and gas well symbols in georeferenced historical topographic maps, and potential UOWs are identified as symbols that are further than 100 m from any documented well. A custom tool was developed to rapidly validate the potential UOW locations. We applied this framework to four counties in California and Oklahoma, leading to the discovery of 1301 potential UOWs across >40,000 km2. We confirmed the presence of 29 UOWs from satellite images and 15 UOWs from magnetic surveys in the field with a spatial accuracy on the order of 10 m. This framework can be scaled to identify potential UOWs across the US since the historical maps are available for the entire nation.

Cross-Antenna Polyphase Interleaving and Inversion scheme to reduce the PAPR of MIMO-FBMC/OQAM system

Filter Bank Multi-Carrier with Offset Quadrature Amplitude symbol mapping called as FBMC/OQAM is presented as a potential successor of Orthogonal Frequency Division Multiplexing OFDM. Combined with Multiple-Input Multiple- Output (MIMO), MIMO-FBMC/OQAM is a promising modulation scheme for high performance broadband wireless communications. However, one major drawback of MIMO-FBMC/OQAM is the high peak-to-average power ratio (PAPR) of the output signals. Latinovic et al. Proposed a PAPR reduction method called Polyphase Interleaving and Inversion (PII) for MIMOOFDM systems under the use of the space-frequency block coding (SFBC) [1]. In this investigation, we suggest two schemes called Cross Antenna Polyphase Interleaving and Inversion 1 and 2 (CAPII1/(CAPII2) PAPR reduction schemes for Space Frequency Block Coding MIMO-FBMC systems which consequently utilizes additional degrees of freedom by employing multiple antennas and generating more patterns leading to more signal candidates to transmit, while requiring a limited amount of side information. The simulation results show that both the proposed CAPII schemes experience remarkable gain in PAPR.

A note on the space of all Toeplitz operators

Abstract We study Toeplitz operators on the space of all real analytic functions on the real line and the space of all holomorphic functions on finitely connected domains in the complex plane. In both cases, we show that the space of all Toeplitz operators is isomorphic, when equipped with the topology of uniform convergence on bounded sets, with the symbol algebra. This is surprising in view of our previous results, since we showed that the symbol map is not continuous in this topology on the algebra generated by all Toeplitz operators. We also show that in the case of the Fréchet space of all holomorphic functions on a finitely connected domain in the complex plane, the commutator ideal is dense in the algebra generated by all Toeplitz operators in the topology of uniform convergence on bounded sets.

Spatial configuration of warehouses of different sizes in the City of Cape Town municipality

Background: Various metropolitan areas have become key centres for logistics activities, leading to a significant increase in the number of warehouses. However, there is a gap in the literature regarding the locational patterns of warehouses of different sizes in Africa.Objectives: To analyse the locational patterns of warehouses of different sizes within the City of Cape Town municipality, South Africa. The analysis focuses on the main factors influencing the placement of warehouses: transport infrastructure, land availability, proximity to customers and land-use zoning.Method: The study categorised warehouses based on their building footprint sizes, using the classifications of xx-small, x-small, small, medium, x-large and mega. A total of 396 warehouses were categorised accordingly. Proportional symbol mapping was then conducted in ArcGIS 10.1, assigning each warehouse type a specific weighting.Results: The study found that the areas surrounding the Port of Cape Town predominantly accommodated x-small warehouses. A diverse concentration of warehouses was identified along the railway, near the junctions of regional and national roads and within the areas enclosed by these roads. In addition, warehouses of diverse sizes were primarily situated in the main industrial zones of the municipality.Conclusion: The City of Cape Town municipality is encouraged to promote the consolidation of particularly large warehouses in strategic locations. These include industrial areas not geographically near the Port of Cape Town but with railway access to the port.Contribution: The study will contribute towards enhancing the sustainability and efficiency of logistics processes within the City of Cape Town.

Polarized APSK modulation system with polymorphic SC signals

AbstractThis paper discusses a new symbol modulation scheme known as polarized amplitude and phase shift keying, (‐APSK) modulation with four rings in its basic form. The new scheme maps power‐polarized symbol pairs on its constellation in order to increase the number of data symbols. ‐APSK exploits a symbol mapper based on a conjugate power splitting algorithm. Product modulation is applied, where a voltage signal of a specified amplitude and phase is multiplied by another current signal of a specified amplitude and phase, thus forming polymorphic signals in the product constellation. At the receiver, an isolated detection is performed, where the voltage signal is detected independently of the received current signal. A selection combining scheme is then used. The results depict unity peak‐to‐average power ratio and low average symbol energy, which is desirable for Green communications in 5G networks. It presents lower bit error rates when compared with the state‐of‐the art ‐ary quadrature amplitude modulation, with a signal‐to‐noise ratio gap of at least . The proposed analytical framework closely matches the simulations for bit error rates under .

An additive variant of the differential symbol maps

An additive variant of the differential symbol maps

Visualization of explainable artificial intelligence for GeoAI

Shapley additive explanations are a widely used technique for explaining machine learning models. They can be applied to basically any type of model and provide both global and local explanations. While there are different plots available to visualize Shapley values, there is a lack of suitable visualization for geospatial use cases, resulting in the loss of the geospatial context in traditional plots. This study presents a concept for visualizing Shapley values in geospatial use cases and demonstrate its feasibility through an exemplary use case—predicting bike activity in a rental bike system. The visualizations show that visualizing Shapley values on geographic maps can provide valuable insights that are not visible in traditional plots for Shapley additive explanations. Geovisualizations are recommended for explaining machine learning models in geospatial applications or for extracting knowledge about real-world applications. Suitable visualizations for the considered use case are a proportional symbol map and a mapping of computed Voronoi values to the street network.

Evaluation of Multi-Valued Data Transmission in Two-Dimensional Symbol Mapping using Linear Mixture Model

Evaluation of Multi-Valued Data Transmission in Two-Dimensional Symbol Mapping using Linear Mixture Model

The Principal Symbol Map for Lagrangian Distributions with Complex Phase

The present paper focus on Lagrangian distributions with complex phase. We provide an alternative construction of their principal symbol map, which allows us to compute the principal symbol after clean composition of Fourier integral operators with complex phase.

A step in a new direction: NVIDIA GPU kernel driver memory forensics

In the ever-expanding landscape of computation, graphics processing units have become one of the most essential types of devices for personal and commercial needs. Nearly all modern computers have one or more dedicated GPUs due to advancements in artificial intelligence, high-performance computing, 3D graphics rendering, and the growing demand for enhanced gaming experiences. As the GPU industry continues to grow, forensic investigations will need to incorporate these devices, given that they have large amounts of VRAM, computing power, and are used to process highly sensitive data. Past research has also shown that malware can hide its payloads within these devices and out of the view of traditional memory forensics. While memory forensics research aims to address the critical threat of memory-only malware, no current work focuses on video memory malware and the malicious use of the GPU. Our work investigates the largest GPU manufacturer, NVIDIA, by examining the newly released open-source GPU kernel modules for the development of forensic tool creation. We extend our impact by creating symbol mappings between open and closed-source NVIDIA software that enables researchers to develop tools for both “flavors” of software. We specifically focus our research on artifacts found in RAM, providing the foundational methods to detect and map NVIDIA Object Compiler Structures for forensic investigations. As a part of our analysis and evaluation, we examined the similarities between open-and-closed kernel modules by collecting structure sizes and class IDs to understand the similarities and differences. A standalone tool, NVSYMMAP, and Volatility plugins were created with this foundation to automate this process and provide forensic investigators with knowledge involving processes that utilized the GPU.

Research on the Movement Speed of Situational Map Symbols Based on User Dynamic Preference Perception

When designing situational maps, selecting distinct and visually comfortable movement speeds for dynamic elements is an ongoing challenge for designers. This study addresses this issue by conducting two experiments to measure the human eye’s ability to discern moving speeds on a screen and examines how symbol movement speeds within situational maps affect users’ subjective experiences, task performance, and visual comfort. The first experiment measured participants’ speed discrimination capabilities for Landolt Ring of varying sizes moving at 0–256°/s, yielding speed discrimination thresholds of 7–23% and a sensitive velocity range of 1–64°/s. The second experiment evaluated observers’ visual perceptions of moving elements within a cognitive task across the same range of 1–64°/s, identifying three significant benchmarks—8°/s, 16°/s, and 32°/s. These can be utilized to categorize slow-, moderate-, and fast-moving symbols in situational maps. The findings can aid in designing human–machine interface environments with improved viewer experience and visual comfort for both Air Traffic Control interfaces and situational maps.

Investigating the Readability of School Geographic Map Symbols Using Eye-Tracking Technology

Geography atlas is an educational material that is very important in geography education. For the eye tracking experiment, six mineral maps were selected from different geography atlases for high school students. The aim of this study was to analyze which design of conventional symbols is more understandable for high school students. We hope that the presented methodology and the case study will help mapmakers to create more effective school geographic maps.

A Segmented Sliding Window Reference Signal Reconstruction Method Based on Fuzzy C-Means

Reference signal reconstruction serves as a crucial technique for suppressing multipath interference and noise in the reference channel of passive radar. Aiming at the challenge of detecting Low-Slow-Small (LSS) targets using Digital Terrestrial Multimedia Broadcasting (DTMB) signals, this article proposes a novel segmented sliding window reference signal reconstruction method based on Fuzzy C-Means (FCM). By partitioning the reference signals based on the structure of DTMB signal frames, this approach compensates for frequency offset and sample rate deviation individually for each segment. Additionally, FCM clustering is utilized for symbol mapping reconstruction. Both simulation and experimental results show that the proposed method significantly suppresses constellation diagram divergence and phase rotation, increases the adaptive cancellation gain and signal-to-noise ratio (SNR), and in the meantime reduces the computation cost.

Frequency Offset Estimation for UWB-OFDM System using Weight and Exhaustiveness based Monarch Butterfly Optimization Approach

The performance of an OFDM system has limitation because the carrier frequency offset (CFO) and sampling frequency offset (SFO) is not estimated correctly. Current methods propose the way of obtaining frequency estimation by using the evolutionary algorithm, but the evolution algorithm suffers from the premature convergence problem. In order to provide efficient frequency offset estimation, this paper proposed weight and exhaustiveness based monarch butterfly optimization approach. First, on the transmitter block, for modulating an input symbol, the Hybrid-Quadrature Phase-Shift Keying modulation scheme is used. Brunn’s IFFT is done at each transmitter for symbol mapping and then in each transmitter block cyclic prefix is inserted. After that, WE-MBO algorithm estimates the frequency offset. On receiver side, the inverse operation of the transmitter is performed. After comparison of proposed system with the existing system, the proposed system gave better performance.

The significance of the cartographic sign: influences of symbol shape on intuitive judgments

ABSTRACT Some of the maps we encounter in our daily lives have become simpler and smaller, to the extent that they may employ only a single symbol to depict a particular incident. As maps and their symbols are never neutral, research on visual semiotics emphasizes the importance of exploring the implicit, connotative effects of signs on human responses. This study, therefore, aimed to assess the influence of simple monothematic web maps on map users’ judgments. It examined how the severity of negative geospatial events was perceived when represented by cartographic point symbols that varied in shape. In total, 72 maps (12 negative topics, each depicted by six map symbols) were rated by 82 participants. The results showed that asymmetric star symbols led to the highest estimates of the events’ perceived severity, followed by symmetric star symbols. Triangle and rhomb led to the lowest ratings. Circle and square showed the most variable results: they led to high and low ratings depending on the map topic. The findings demonstrate that map symbols influence how people imagine geospatial events. These findings call for a more vigorous focus on the connotative meanings of visual signs in cartographic research and practice.

Fixation-related potentials during mobile map assisted navigation in the real world: The effect of landmark visualization style.

An often-proposed enhancement for mobile maps to aid assisted navigation is the presentation of landmark information, yet understanding of the manner in which they should be displayed is limited. In this study, we investigated whether the visualization of landmarks as 3D map symbols with either an abstract or realistic style influenced the subsequent processing of those landmarks during route navigation. We utilized a real-world mobile electroencephalography approach to this question by combining several tools developed to overcome the challenges typically encountered in real-world neuroscience research. We coregistered eye-movement and EEG recordings from 45 participants as they navigated through a real-world environment using a mobile map. Analyses of fixation event-related potentials revealed that the amplitude of the parietal P200 component was enhanced when participants fixated landmarks in the real world that were visualized on the mobile map in a realistic style, and that frontal P200 latencies were prolonged for landmarks depicted in either a realistic or abstract style compared with features of the environment that were not presented on the map, but only for the male participants. In contrast, we did not observe any significant effects of landmark visualization style on visual P1-N1 peaks or the parietal late positive component. Overall, the findings indicate that the cognitive matching process between landmarks seen in the environment and those previously seen on a map is facilitated by more realistic map display, while low-level perceptual processing of landmarks and recall of associated information are unaffected by map visualization style.

Symbol of Communication between Worship Leader and Music Priest in Maintaining Harmonization of Worship Music at GBI Lembang Bandung

Music has an important role in Christian worship. Harmonious music is solemnity if the Worship leader and musician church can carry out their duties properly. Worship leader and musician communicate using symbols when leading worship. This research aims to determine how the meaning of the communication symbols of church music groups in maintaining the harmonization of worship music. This research uses qualitative method with a symbolic interaction study approach. Data was collected through observation, interviews and documentation. The informant determination technique used is purposive sampling.. The results of the study found 2 parts of the symbol. Namely song map and keytone. The song map symbol is a part of a song element that is used when the music is already running and is given when the musical verse is about to end, with the aim of bridging every movement of the musical verse. Keytone symbols are used to align the chords. The language used verbally and nonverbally. The key tone is used by worship leaders to music priests, and music priests to one another. The music priest has a dominant role according to the symbol of the song map. The keyboardist has a role on the cooling down section, guitarist on interlude, drums on full music and overtones. Worship leaders and music priests must have spiritual criteria as pulpit ministers, because spiritual criteria are the main key to be good to God.

How can children best learn map skills? a step-by-step approach

ABSTRACT This study contributes to our understanding of children's development of map-reading skills through a systematic ‘step-by-step approach’. Utilising an ecological research design, we investigated how children perceive and utilise maps in a large-scale outdoor environment. A total of 156 children, aged 5–11 (both boys and girls), participated in the study, tasked with locating ten controls in the terrain using five different types of maps. The study measured accuracy in wayfinding (the number of correctly identified controls) and efficiency in wayfinding (the time spent on the task). The results revealed that children exhibited better mastery of perspective maps compared to symbolic maps, with older children demonstrating significantly greater proficiency with symbolic maps than younger children. Notably, there were no significant differences in performance between boys and girls.