An Efficient Visualization Method for Polygonal Data with Dynamic Simplification

Wu, Minxian; Chen, Taisheng; Zhang, Kun; Jing, Zhimin; Han, Yan; Chen, Menglin; Hong, Wang; Lv, Guonian

doi:10.3390/ijgi7040138

Cited by 5 publications

(3 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Authors in [39] propose a novel algorithm that they term locally adaptive line simplification (LOCALIS) for GPU-based geographic polyline data visualization at scale with quality guarantees. Similar work appears in [40], where a method for Level-of-Details (LoD) visualization for polygonal data was designed, which incorporates a polygon simplification method that is based on the DP algorithm. Ref.…”

Section: Applications Of Line Simplification In Approximate Geospatia...mentioning

confidence: 99%

Polygon Simplification for the Efficient Approximate Analytics of Georeferenced Big Data

Al Jawarneh,

Foschini,

Bellavista

2023

Sensors

View full text Add to dashboard Cite

The unprecedented availability of sensor networks and GPS-enabled devices has caused the accumulation of voluminous georeferenced data streams. These data streams offer an opportunity to derive valuable insights and facilitate decision making for urban planning. However, processing and managing such data is challenging, given the size and multidimensionality of these data. Therefore, there is a growing interest in spatial approximate query processing depending on stratified-like sampling methods. However, in these solutions, as the number of strata increases, response time grows, thus counteracting the benefits of sampling. In this paper, we originally show the design and realization of a novel online geospatial approximate processing solution called GeoRAP. GeoRAP employs a front-stage filter based on the Ramer–Douglas–Peucker line simplification algorithm to reduce the size of study area coverage; thereafter, it employs a spatial stratified-like sampling method that minimizes the number of strata, thus increasing throughput and minimizing response time, while keeping the accuracy loss in check. Our method is applicable for various online and batch geospatial processing workloads, including complex geo-statistics, aggregation queries, and the generation of region-based aggregate geo-maps such as choropleth maps and heatmaps. We have extensively tested the performance of our prototyped solution with real-world big spatial data, and this paper shows that GeoRAP can outperform state-of-the-art baselines by an order of magnitude in terms of throughput while statistically obtaining results with good accuracy.

show abstract

Section: Applications Of Line Simplification In Approximate Geospatia...mentioning

confidence: 99%

Polygon Simplification for the Efficient Approximate Analytics of Georeferenced Big Data

Al Jawarneh,

Foschini,

Bellavista

2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Finally M. Wu et al [23] present an article about "An Efficient Visualization Method for Polygonal Data with Dynamic Simplification". The polygonal data often require rendering with symbolization and simplification in geovisualization.…”

Section: Hci and Gis In This Issuementioning

confidence: 99%

Guest Editor’s Editorial “Cognitive Aspects of Human-Computer Interaction for GIS”

Fritsch

2019

IJGI

View full text Add to dashboard Cite

show abstract

“…A great deal of previous research of vector presentation in GIS has focused on fast rendering vector points, polylines [33,34] and polygon data [35]. It is well known among GIS researchers that the time-consuming steps of real-time vector mapping is querying spatial data, retrieving them and rendering geometric graphics [36].…”

Section: Introductionmentioning

confidence: 99%

An Accurate and Efficient Quaternion-Based Visualization Approach to 2D/3D Vector Data for the Mobile Augmented Reality Map

Wang

Huang

Shi

2022

IJGI

View full text Add to dashboard Cite

Increasingly complex vector map applications and growing multi-source spatial data pose a serious challenge to the accuracy and efficiency of vector map visualization. It is true especially for real-time and dynamic scene visualization in mobile augmented reality, with the dramatic development of spatial data sensing and the emergence of AR-GIS. Such issues can be decomposed into three issues: accurate pose representation, fast and precise topological relationships computation and high-performance acceleration methods. To solve these issues, a novel quaternion-based real-time vector map visualization approach is proposed in this paper. It focuses on precise position and orientation representation, accurate and efficient spatial relationships calculation and acceleration parallel rendering in mobile AR. First, a quaternion-based pose processing method for multi-source spatial data is developed. Then, the complex processing of spatial relationships is mapped into simple and efficient quaternion-based operations. With these mapping methods, spatial relationship operations with large computational volumes can be converted into efficient quaternion calculations, and then the results are returned to respond to the interaction. Finally, an asynchronous rendering acceleration mechanism is also presented in this paper. Experiments demonstrated that the method proposed in this paper can significantly improve vector visualization of the AR map. The new approach, when compared to conventional visualization methods, provides more stable and accurate rendering results, especially when the AR map has strenuous movements and high frequency variations. The smoothness of the user interaction experience is also significantly improved.

show abstract

An Efficient Visualization Method for Polygonal Data with Dynamic Simplification

Cited by 5 publications

References 35 publications

Polygon Simplification for the Efficient Approximate Analytics of Georeferenced Big Data

Polygon Simplification for the Efficient Approximate Analytics of Georeferenced Big Data

Guest Editor’s Editorial “Cognitive Aspects of Human-Computer Interaction for GIS”

An Accurate and Efficient Quaternion-Based Visualization Approach to 2D/3D Vector Data for the Mobile Augmented Reality Map

Contact Info

Product

Resources

About