Visualization and analysis of local and distant population flows on the Qinghai-Tibet Plateau using crowd-sourced data

Xu, Jing; Liu, Ju; Xu, Yang; Pei, Tao

doi:10.1007/s11442-021-1844-x

Cited by 7 publications

(4 citation statements)

References 35 publications

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“…When the stall and reproduction of information approach the limit that people can bear, information may become a burden [20]. Xu et al believe that data sports enable anyone to penetrate the data source, and people should publish structured, machine-readable data, putting aside the traditional "lots of text," data-centric sports form [21]. Zhu et al developed the geozuid4d system, which uses color, texture, and font to display multiple attributes of the 3D trajectory of underwater moving objects, but does not use some form of aggregation to simplify the data, so there are still problems such as excessive drawing and view occlusion [22].…”

Section: Related Workmentioning

confidence: 99%

Visual Management of Sports Based on Intelligent Analysis of Big Data

Dan-ya

Wang

Liu

2022

Mobile Information Systems

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After years of development, big data technology has become more mature and reliable in its application in various fields. With the explosive growth of data and the rise of data complexity, the processing and application of data have actually changed our daily life. The development of data in sports is very active in recent years, and the natural dependence of sports on data determines that the visualization of sports has a great creative space in data sports. Therefore, it is necessary to deeply study the visual management of sports under the background of big data technology. As we all know, in sports, competitive games occupy the vast majority, and the data generated by this is not limited to the score of the game. People are paying more and more attention to information related to sports, but these information are generally very complicated and huge. This is also an area with the widest audience, and the core of competitive sports is data. The final results and progress of most sports competitions are reflected through changes and comparisons of data. With the continuous development of big data information collection technology, the available sports data are more detailed, which also makes sports develop toward visualization. Therefore, with the help of the excellent ability of big data in screening data, this article proposes algorithms such as DTW and recurrent neural networks to reasonably and reliably analyze and process a large number of data generated in the process of sports and embeds an error analysis module in the designed model to ensure the accuracy requirements in data processing to a greater extent. The model designed in this article has been able to improve the accuracy by more than 86%. This will greatly facilitate our management and have a far-reaching impact on sports visualization.

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Section: Related Workmentioning

confidence: 99%

Visual Management of Sports Based on Intelligent Analysis of Big Data

Dan-ya

Wang

Liu

2022

Mobile Information Systems

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“…We found that the potentially suitable habitat of IAPs overlapped with areas of anthropogenic disturbance (such as croplands, roads, and railways) in the TP (Venter et al, 2018) (Figure 6). Over the past few decades, the intensity of human activities in the TP has increased by about 30% (Xu et al, 2020). Such anthropogenic disturbances may not only open new opportunities for IAPs to spread farther and to higher regions but also could destroy the original vegetation and create favourable conditions for the colonization of IAPs.…”

Section: The Dispersal Trend Of Iaps In the Tpmentioning

confidence: 99%

Risk of plant invasions and management planning in the Tibetan Plateau, China

Wei

Zhang

Liu

et al. 2023

Journal of Biogeography

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Aims Mountain environments have high biodiversity and face an accelerating plant invasion risk. Given the enormous ecological and economic value of these ecosystems, there is an urgent need to detect and rapidly respond to invasive species risk. Here, the Tibetan Plateau (TP) in China was selected to examine distribution patterns of invasive alien plants (IAPs) and propose management strategies. Location The Tibetan Plateau in China. Methods Based on native and non‐native occurrences of 123 IAPs alongside environmental variables, we assembled species distribution models and the MIGCLIM model to simulate suitable growth and dispersal areas under current climatic conditions. All IAPs were classified based on the predicted suitable area size, occurrence number and harm level to propose various management strategies. Results There was a significant separation between the climate niches of most IAPs and the climatic conditions of the TP, meaning the areas suitable for most IAPs were limited to low latitudes and elevations. These areas also have further dispersal risks and risks for new IAPs being introduced. Among 123 IAPs, 23 species had above‐average occurrences and suitable distribution areas; in the remaining 100 occurrences and distributions, at least one IAP was less than the average. Main Conclusions Suitable areas for IAPs in the TP are currently limited to low‐elevation regions, which are also at a higher risk of further expansion. Management measures should focus on potential high‐risk areas and diffusion pathways where IAPs can spread further. Efforts should prevent species that have not been established but have large potential suitable areas from being introduced, eradicate established IAPs with limited suitable areas, and control established IAPs. These results can provide a reference for developing more efficient and cost‐effective management strategies.

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“…To realize the visualization of the flow chart of data processing, we activate the call_map function of the heat map of the Baidu map API with the help of a web browser and realize the correlation of the BeiDou module positioning data, sensor module data, and Baidu map through Python programming [26,27]. Baidu map API can provide functions such as map display, search, and positioning, and thus it is suitable for the application and development of this system.…”

Section: Data Analysis and Visualizationmentioning

confidence: 99%

Fine-Granularity Urban Microclimate Monitoring Using Wearable Multi-Source Sensors

Ren

Jia

et al. 2021

Sustainability

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With the development of urbanization, the environment is the key to the safety of residents’ life and health and the United Nations’ Sustainable Development Goals (SDGs). Urban environmental changes and microclimate problems have attracted widespread attention. For the SDGs, monitoring the urban microclimate more accurately and effectively and ensuring residents’ environmental health and safety is particularly important when designing applications that can replace the traditional fixed-point urban environment or pollution monitoring. Based on the BeiDou Navigation Satellite System platform, this paper proposes a fine-granularity urban microclimate monitoring method using wearable multi-source (PM2.5, PM10, and other air pollutants) sensors innovatively, which includes the satellite position function by adopting the satellite pseudo-range differential positioning technology, environmental data perception through the embedded system and wireless transmission, as well as the GIS data processing and analysis system. The wearable sensor acquires position and service information data through the satellite positioning system and acquires environmental parameters through integrated mobile multi-source sensors. The data are cached and wirelessly transmitted to the cloud server for digital processing. The urban microclimate is evaluated and visualized through algorithm and map API. Mobile monitoring can be flexibly applied to complex and diverse urban spaces, effectively realizing all-weather, all-directional, and accurate microclimate monitoring of urban environmental quality.

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Visualization and analysis of local and distant population flows on the Qinghai-Tibet Plateau using crowd-sourced data

Cited by 7 publications

References 35 publications

Visual Management of Sports Based on Intelligent Analysis of Big Data

Visual Management of Sports Based on Intelligent Analysis of Big Data

Risk of plant invasions and management planning in the Tibetan Plateau, China

Fine-Granularity Urban Microclimate Monitoring Using Wearable Multi-Source Sensors

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