Geospatial Space Research Articles

A Spatiotemporal Empowerment Framework for China’s National 3D Mapping Program 3dRGLM

Abstract. China has launched a national 3D mapping program to build 3D Realistic geospatial Landscape Model (3dRGLm) over the whole country, covering both cities and countryside. The 3dRGLM is a digital description and representation of the real 3D geospatial spaces, and is defined as a new generation geospatial data product with 3D structures, realistic scenes, and geospatial entities. Such a national or local 3dRGLm will set up a digital 3D realistic geospatial space which can facilitate the vital connection with the real geospatial space, and will serve as a new generation of geospatial information infrastructure for our society. With the acquisition of complex 3D spatial data continues to advance, managing and utilizing the massive volumes of 3D data to provide spatiotemporal empowerment applications has become a significant technological challenge. This paper analyzes the technical characteristics of 3d realistic geospatial landscape model, and then proposes the main content and basic structure of a 3d realistic geospatial landscape model database, as well as the spatiotemporal service empowerment methods based on the database. Finally, a case analysis is provided to serve as a reference for the construction and application of 3d realistic geospatial landscape.

Green Innovation Efficiency Measurement Based on Sensor Data: Evidence from China

Based on the theoretical knowledge of technological innovation, this paper designs a sensor data value incubation model and a sensor data collection model to collect the original data on green innovation efficiency. In order to explore the spatial and temporal differentiation characteristics of China’s provincial green innovation efficiency and the spatial spillover effect of China’s provincial green innovation efficiency, the entropy weight TOPSIS model is adopted to measure the green innovation efficiency of China’s 30 provinces (cities) from 2005 to 2021 and analyze its temporal and spatial evolution characteristics. This paper uses an exploratory spatial data analysis method to prove the agglomeration phenomenon of China’s provincial green innovation efficiency in the ground space. Finally, a spatial econometric model is introduced to study the impact of government R&D investment, green supervision, and green innovation efficiency on spatial spillover effects. The study found the following three conclusions: First, the efficiency of green innovation in China’s provinces has been fluctuating in stages, and the overall trend has been increasing year by year. The overall efficiency of green innovation in China’s provinces is low, and the overall development is uneven and uncoordinated. Second, from the results of the spatial autocorrelation test, there is a clear and positive spatial correlation between China’s provincial green innovation efficiency and agglomeration in the geospatial space. Third, government R&D inputs and different types of green regulations have a significant impact on green innovation efficiency and have significant spatial spillover effects. Along from the eastern region to the central region, then to the northeast and western regions, the degree of effect on green innovation efficiency and the intensity of spatial spillover effects have gradually weakened. It is believed that the government should reduce R&D investment in the eastern region and increase green sewage charges. Instead, the government should raise R&D investment in the central, northeast, and western regions and offer enterprises green innovation subsidies.

Spatial Metaphor of Thelma & Louise from the Perspective of Feminism

Based on the expression of the theme of female subject consciousness, Thelma & Louise combines the openness of road films in terms of environment and landscape, casting feminism into spatial construction, effectively realizing the combination of Hollywood genre films and feminism. From a feminist perspective, this paper highlights the interactive construction between female body space, narrative space and the psychological space of two protagonists. As for the narrative space, the female body of two main characters deconstructed the solidified label of screen women. For the geospatial space, the static space and the dynamic space respectively shows the women’s circumstances under a patriartical society and the wokeness of the female mentality. In the term of the psychological space, the journey of the two main characters symbolized the liberate of the women’s desire, expressed the dilemma between living and happiness. The film realizes the interactive construction of the female body, narrative and psychological space.

Research on Urban Road Network Evaluation Based on Fractal Analysis

The structure of the urban road network affects the mode of urban development and the position of urban social and economic activities, families, and employment centers. Therefore, it is necessary to consider the supply inequality of urban road network and its impact on urban development so as to form a sustainable and fair urban development model in cities. Based on the fractal analysis, this paper seeks the evaluation index of urban road network layout and internal structure characteristics to guide the optimization and adjustment of the urban road network, which is of great significance for guiding urban land use, effectively utilizing geospatial space, and promoting sustainable urban development, and attempts to apply the fractal analysis concept to evaluate the urban road network in Harbin, China. It is found that there is a good relationship between the length of the urban road network and the build-up area. Therefore, fractal analysis is used to reasonably determine the spatial demand of incremental road networks, considering the impact of road network increase on development mode. This paper argues that fractal analysis is an auspicious tool for the evaluation of urban road networks, including solving the problem of supply inequality in urban road networks, which is very suitable for the gradual construction of road networks in urban situations, especially in the development environment of road networks with scarce resources.

ГОРИЗОНТАЛЬНОЕ ВРАЩЕНИЕ ДЕФОРМИРОВАННЫХ ЭЛЕМЕНТОВ ЗЕМНОЙ ПОВЕРХНОСТИ

The structural composition and properties of the horizontal rotation of the elements of the Earth's surface, which is part of the skew-symmetric part of the geomechanical distortion tensor, are investigated. It is established that it consists of a real rotation, showing the rotation of a deformed area element in geospatial space, and a virtual one, displaying its artificial rotation. The decomposition of angular deformations into components leading to real and virtual rotation, as well as the calculation of their angles, is carried out according to the presented nomogram and the formulas attached to it. Practical examples show the deformation and rotation of complex contours of man-made mining facilities located on differently moving blocks of the Earth's surface.

The Spatiotemporal Evolutionary Trend and Driving Factors of the Coupling Coordinated Development between Regional Green Finance and Ecological Environment

Based on the 30 inland provincial samples of China from 2003 to 2019, this article analyzes the evolutionary characteristics of the coupling coordination between green finance and the ecological environment (CCFE) using ArcGIS 10.5 software and employs the spatial Durbin model to analyze the driving factors of the CCFE. The results can be concluded as follows: (1) the CCFE of China is at a moderately low level, with a fluctuating upward trend. Spatially, it presents a spatial distribution pattern—higher in the east and lower in other regions. In terms of types, the regions of the CCFE are more in primary coordination and basic un-coordination and less in moderate un-coordination and moderate coordination. There are more regions of the green finance lagged type, and relatively few regions have achieved the financial ecological synchronization type. (2) The CCFE hotspots are concentrated in the Pearl River Delta, with a spatial “increase–decrease” development trend. Additionally, the CCFE cold spots are concentrated in the upper Yellow River Basin, with a relatively stable spatial scope. (3) The CCFE shows a positive spillover effect and accumulative delivery effect in the economic geospatial space. The population urbanization rate and the number of granted patent applications have a significant positive impact on the CCFE, and the percentage of secondary industries to GDP has a negative impact accordingly. Spatially, the percentage of secondary industries to GDP and the number of granted patent applications of nearby provinces in the economic geospatial space have a negative impact on the local CCFE. (4) The impact and spatial effect of different factors on the CCFE are obviously different. Finally, policy implications on the coordinated development of green finance and the ecological environment are also made.

Research on Spatial-temporal Spread and Risk Profile of the COVID-19 Epidemic Based on Mobile Phone Trajectory Data.

The COVID-19 epidemic poses a significant challenge to the operation of society and the resumption of work and production. How to quickly track the resident location and activity trajectory of the population, and identify the spread risk of the COVID-19 in geospatial space has important theoretical and practical significance for controlling the spread of the virus on a large scale. In this study, we take the geographical community as the research object, and use the mobile phone trajectory data to construct the spatiotemporal profile of the potential high-risk population. First, by using the spatiotemporal data collision method, identify, and recover the trajectories of the people who were in the same area with the confirmed patients during the same time. Then, based on the range of activities of both cohorts (the confirmed cases and the potentially infected groups), we analyze the risk level of the relevant places and evaluate the scale of potential spread. Finally, we calculate the probability of infection for different communities and construct the spatiotemporal profile for the transmission to help guide the distribution of preventive materials and human resources. The proposed method is verified using survey data of 10 confirmed cases and statistical data of 96 high-risk neighborhoods in Chengdu, China, between 15 January 2020 and 15 February 2020. The analysis finds that the method accurately simulates the spatiotemporal spread of the epidemic in Chengdu and measures the risk level in specific areas, which provides an objective basis for the government and relevant parties to plan and manage the prevention and control of the epidemic.

Exploring spatiotemporal changes in the multi-granularity emotions of people in the city: a case study of Nanchang, China

In the Internet age, emotions exist in cyberspace and geospatial space, and social media is the mapping from geospatial space to cyberspace. However, most previous studies pay less attention to the multidimensional and spatiotemporal characteristics of emotion. We obtained 211,526 Sina Weibo data with geographic locations and trained an emotion classification model by combining the Bidirectional Encoder Representation from Transformers (BERT) model and a convolutional neural network to calculate the emotional tendency of each Weibo. Then, the topic of the hot spots in Nanchang City was detected through a word shift graph, and the temporal and spatial change characteristics of the Weibo emotions were analyzed at the grid-scale. The results of our research show that Weibo’s overall emotion tendencies are mainly positive. The spatial distribution of the urban emotions is extremely uneven, and the hot spots of a single emotion are mainly distributed around the city. In general, the intensity of the temporal and spatial changes in emotions in the cities is relatively high. Specifically, from day to night, the city exhibits a pattern of high in the east and low in the west. From working days to weekends, the model exhibits a low center and a four-week high. These results reveal the temporal and spatial distribution characteristics of the Weibo emotions in the city and provide auxiliary support for analyzing the happiness of residents in the city and guiding urban management and planning.

A Survey on OD Data Visualization

<p indent=0mm>OD data is a type of data that provides origin and destination positions, and sparsely describes the movement trajectory of objects. Being the research hotspots in data visualization and geospatial analysis, visual analysis of OD data contributes to discovering group movement patterns, exploring spatial anomalies and hidden relationships, and in-depth analysis of various statistics attributes. It is started from the pair-point structure of OD data in geospatial space, and classical OD data visualization methods and principles are elaborated, such as OD matrix, OD map, OD flow, etc. Then from the perspective of spatial-temporal feature exploration, spatial and spatial-temporal joint dimensions, the visual analysis of OD data is performed, while its application scenarios and enhanced significance of feature expression, perception, extraction and presentation are researched. To solve the problem of visual clutter in large-scale OD data visualization, the visual simplification methods such as filtering, aggregation, and sampling are sorted out in the research methods of visual analysis of OD data. Finally, the applications and specific cases of OD data visual analysis technology are investigated in different domains, the challenging problems in the research of OD data visual analysis are summarized, and the trend of its future development is prospected.

Spatio-temporal characteristics of regional sustainable economic growth drivers of China

Intellectual capital (IC) has become a universal performance indicator for the socioeconomic development of countries and regions. Based on a review of national intellectual capital (NIC) and regional intellectual capital (RIC) evaluation literature, we used the regional intellectual capital indicator (RICI) as a model for China’s RIC evaluation to indirectly understand China’s potential economic growth drivers. Specifically, we collected statistical data of 31 provinces (including municipalities and autonomous regions) in China from 2004 to 2016 to measure RICI and analyze its dynamic characteristics from temporal and spatial perspectives. In this paper, Delphi analysis was used to construct RICI model, and cluster analysis and exploratory spatial data analysis were used to analyze the temporal and spatial characteristics of RICI in China. The results showed that RICI, which represents China’s overall economic growth drivers, increases annually and is consistent with economic development level during the study period. Regarding the geo-spatial space, RICI follows the trend of “high in the east and low in the west”, gradually decreasing from eastern to western China. For RIC structure, the shape of the radar chart of IC structure located in the eastern coastal areas is usually biased towards strong external relational capital, while that in western China is generally biased towards structural capital. For spatial correlation, China’s RICI has dependence on geographical adjacent space and economic space. Our research can provide policy suggestions for the sustainable development of regional economy from an IC perspective.

ПРОЕКТИРОВАНИЕ И УРАВНИВАНИЕ ПРОСТРАНСТВЕННЫХ ГЕОДЕЗИЧЕСКИХ ПОСТРОЕНИЙ, ПРЕДНАЗНАЧЕННЫХ ДЛЯ СОЗДАНИЯ ТРЕХМЕРНОГО КАДАСТРА

The article proposes a mathematical algorithm based on the least squares method for calculating the necessary measurement accuracy in a spatial geodetic construction intended for performing cadas-tral works when conducting a 3D cadastre in a territorial entity. The proposed algorithm allows, based on the specified accuracy of the relative position of real estate objects in the cadastral quarter, to select the necessary technological measuring equipment for building a spatial boundary density network (BDN) on the ground for geodetic support of cadastral works. The use of the developed algorithm for equalizing the results of geodetic measurements will ensure the reliability of the calculated parameters of capital construction objects and the creation on their basis of a single geospatial space necessary for solving various scientific and technical problems, the corresponding territorial entity.

Формирование интегрированных систем с единым геопространством посредством унификации сведений, вносимых в информационные ресурсы ЕГРН и ИСОГД

Within the framework of effective territorial management, as one of the priority areas of state policy, optimal decisions should be made that focus on the sustainable development of the subjects territories of the Russian Federation, municipalities, including urban settlements and municipal districts, for this purpose, appropriate urban planning documentation is being developed, including territorial planning documents, as the only legal and technical basis for the system of land redistribution and the establishment of a legal regime for their use. Modern trends in the economic development of regions determine the choice of tools for state land man-agement in strict accordance with land and civil legislation, combined with the specifics of territorial entities. Thus, the main management tools are the accounting and registration, control and supervision sys-tems in the field of land use and protection, as well as the territorial planning system. Their structural components contain a significant amount of information that should be accumulated and reflected in a single geospatial space in order to improve the efficiency of land management. However, the contradictions between the current norms of industry legislation and the insufficient level of technology development prevent the creation of a well-functioning mechanism for integrating diverse ca-dastral and urban planning information.

Study on the Behaviors of Inbound Tourists based on Geotagged Photo Metadata – A Case of the City Group in the Upper Reach of the Yellow River in China

Abstract. The spatial distribution of geotagged photos is a projection of the tourist's tourism activities in the geospatial space, which contains spatial attributes and interrelationships of tourists’ activities. Using the Flickr photo sharing website, the paper utilizes new data mining technologies to discover and capture the metadata of geotagged photos uploaded by visitors from January 2008 to October 2018 in the upper reach of the Yellow River in China. The spatial information processing and expression of the collected data are processed and the characteristics of the inbound tourists’ behavior are explored by the P-DBSCAN, the path tracking technology and the UCINET network analysis. The main results are as follows: (1) By using the P-DBSCAN cluster analysis, the area of interest (AOI) has a feature of high agglomeration and forms a “V” shaped in the Xining-Lanzhou-Yinchuan area. The concentration of AOIs is closely related to the urban functional area and has a clear Urban functional orientation. (2) Using tracking analysis, the paper reveals single node trajectory, intraregional path trajectory and interregional path trajectory. Among them, 68.42% visitors chose single node trajectory, 9.78% visitors chose intraregional path trajectory and 21.80% tourists chose interregional path trajectory. (3) Ten cross-regional tourism mainstream lines are picked by the UCINET network analysis mode. It has been found that the tourists tend to visit those famous scenic spots (points) such as the Qinghai Lake, the YaDan Geological Park, the ‘Danxia’ Landform, the Zhenbeibu China West Film Studio. It is apparent that the Gansu-Qinghai Great Circle Tour is a hot tourist route that tourists are keen to choose. The research results have certain reference significance for improving the transformation and upgrading of tourism industry in the upper reach of the Yellow River.

Influence of Straw Burning on Urban Air Pollutant Concentrations in Northeast China.

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.

ARCHITECTURAL MODELLING OF “SOUND” PERGOLA

The article describes architectural solutions of pergolas adapted for the reproduction of synthesized acoustic space. The solution is represented by means of computer modelling and visualizes both processes and ob-jects on the example of construction and calculations. The project design of architectural models is an integral part in the practical reconstruction of the geospatial space studied by the architectural geography.

Reconstructing individual mobility from smart card transactions: a collaborative space alignment approach

Smart card transactions capture rich information of human mobility and urban dynamics and therefore are of particular interest to urban planners and location-based service providers. However, since most transaction systems are only designated for billing purpose, typically, fine-grained location information, such as the exact boarding and alighting stops of a bus trip, is only partially or not available at all, which blocks deep exploitation of this rich and valuable data at individual level. This paper presents a collaborative space alignment framework to reconstruct individual mobility history from a metropolitan-scale smart card transaction dataset. Specifically, we show that by delicately aligning the monetary space and geospatial space with the temporal space, we are able to extrapolate a series of critical domain-specific constraints. Later, these constraints are naturally incorporated into a semi-supervised conditional random field (CRF) to infer the exact boarding and alighting stops of all transit routes, where the features of the CRF model consist of not only pre-defined indicator features extracted from individual trips but also latent features crafted from different users’ trips using collaborative filtering. Here, we consider two types of collaborative features: (1) the similarity in terms of users’ choices of bus lines and (2) latent temporal patterns of users’ commuting behaviors. Extensive experimental results show that our approach achieves a high accuracy, e.g., given only 10 % trips with known alighting/boarding stops, and we successfully inferred more than 79 % alighting and boarding stops from all unlabeled trips. In particular, we validated that the extracted collaborative features significantly contribute to the accuracy of our model. In addition, we have demonstrated that by applying our approach to enrich the data, the performance of a conventional method for identifying users’ home and work places can be dramatically improved (with 83 % improvement on home detection and 38 % improvement on work place detection). The proposed method offers the possibility to mine individual mobility from common public transit transactions, and showcases how uncertain data can be leveraged with domain knowledge and constraints, to support cross-application data-mining tasks.