System Spatial Analysis Research Articles

Discretization of the Urban and Non-Urban Shape: Unsupervised Machine Learning Techniques for Territorial Planning

One of the goals of the scientific community is to equip the discipline of spatial planning with efficient tools to handle huge amounts of data. In this sense, unsupervised machine learning techniques (UMLT) can help overcome this obstacle to further the study of spatial dynamics. New machine-learning-based technologies make it possible to simulate the development of urban spatial dynamics and how they may interact with ecosystem services provided by nature. Modeling information derived from various land cover datasets, satellite earth observation and open resources such as Volunteered Geographic Information (VGI) represent a key structural step for geospatial support for land use planning. Sustainability is certainly one of the paradigms on which planning and the study of past, present and future spatial dynamics must be based. Topics such as Urban Ecosystem Services have assumed such importance that they have become a prerogative on which to guide the administration in the difficult process of transformation, taking place not only in the urban context, but also in the peri-urban one. In this paper, we present an approach aimed at analyzing the performance of clustering methods to define a standardized system for spatial planning analysis and the study of associated dynamics. The methodology built ad hoc in this research was tested in the spatial context of the city of L’Aquila (Abruzzo, Italy) to identify the urbanized and non-urbanized area with a standardized and automatic method.

Spatiotemporal Characteristics and Influencing Factors of Tourism-Urbanization-Technology-Ecological Environment on the Yunnan-Guizhou-Sichuan Region: An Uncoordinated Coupling Perspective.

The tourism, urbanization, technology, and the ecological environment both promote and restrict each other. Coordinating the relationship between the four is of great significance to the realization of high-quality sustainable regional development. Taking the Yunnan–Guizhou–Sichuan region as an example, this paper constructs an uncoordinated coupling model for the tourism–urbanization–technology–ecological environment system. Using exploratory spatial analysis and geographic information systems, this paper reveals the temporal and spatial evolution law affecting the uncoordinated coupling relationship between tourism, urbanization, technology and the ecological environment in the Yunnan–Guizhou–Sichuan region from 2010 to 2020, before establishing a panel Tobit model that is used to explore the factors affecting the four systems. The research shows the following: (1) The level of comprehensive development for tourism, urbanization, technology, and the ecological environment in Yunnan, Guizhou, and Sichuan has increased rapidly. Of all these, the tourism industry was the most affected by COVID-19 in 2020, while the level of urbanization, technology, and ecological environment developments in the three provinces has become similar over time. (2) Uncoordinated development between cities is a prominent problem; while the uncoordinated coupling spatial agglomeration in various regions is relatively stable, the proportion of cities with no significant agglomeration form amounts to more than 70%, with mostly low–low (L–L) and high–high (H–H) agglomeration types. (3) The degree to which uncoordinated coupling exists among the four systems in the Yunnan–Guizhou–Sichuan region is affected by many factors. Only eco-environmental pressure has a significant positive correlation with the degree of uncoordinated coupling, while the tourism scale, economic urbanization, eco-environmental response, and investment in technology have a significant negative correlation. These results provide a theoretical basis and practical references for strengthening the government’s macro-control and promoting collaborative regional development.

Grade Division and Benchmark Price of Forestlands Using Geospatial Technology: A Case Study of Southeastern China

Forestlands not only provide the conditions that support forested environments, but they also generate natural resources and ecosystem services that support human survival and social development. Using benchmark price to evaluate the economic value of forests is fast and efficient, which can function as an important tool for the improvement of forest resources management. However, information remains limited on how to establish a unified and complete benchmark price for forestland resources in China. Therefore, this study aimed to grade the forestlands and formulate the corresponding benchmark price to improve the statistical management efficiency of forestlands resources. We conducted our study in Longquan County, Zhejiang Province, where we implemented a survey and collected data focusing on forest resources planning. We classified forest resources in this area to establish a benchmark price using geographic information system (GIS) spatial analysis technology. Based on the characteristics of the survey data and the local economic and social situation, the correction coefficient of forestland price was formulated, and the economic value of forestlands resource assets was calculated accordingly. Results indicate that: (1) the forestland can be divided into five grades. The number and area of forestland increased firstly and then decreased from Grade I to Grade V. Forestland resources were concentrated in Grade II and Grade III, accounting for 62.0% of the total area. (2) The benchmark price of forestland in Longquan County was 10380, 9493, 8708, 7827 and 6771 Chinese Yuan (CNY)·hm−2 from Grade I to Grade V, respectively. The benchmark price of forestland in different grades could reflect the quality of forestland. (3) The price correction coefficient was formulated to match the benchmark price of forestland according to the forestland particularity and the external embodiment of forestland productivity level, and then, the economic value of forestland resource assets in the study area was calculated to be 22.48 million CNY accordingly. The method used in this study has the advantages of simple operation, high efficiency and a low cost. This study can provide methods for the evaluation and accounting of forestland resources, give technical support for the audit of natural resource assets of government departments, help to prepare the balance sheet of natural resources, and further prompt references for the statistical management of forest resources in similar regions and countries.

Riverine flood potential assessment at municipal level in Slovakia

Study regionSlovakia – 2927 municipalities. Study focusThis study maps and assesses the riverine flood potential in municipalities of Slovakia using the vector-based spatial multi-criteria analysis and geographic information systems (GIS). The flood potential index (FPI) in municipalities was computed based on eight flood factors, which were normalized, weighted and aggregated into the FPI index. Furthermore, we analyzed the spatial clusters of riverine flood potential using the local Moran’s coefficient of spatial autocorrelation. New hydrological insights for the regionThe very high and high FPI (767 municipalities) was recorded mostly in municipalities of northern and eastern Slovakia. Very low and low FPI (1452 municipalities) dominates in western and southern Slovakia while moderate FPI (708 municipalities) was mainly recorded in municipalities of central Slovakia. The number of statistically significant high-high and low-low spatial clusters of riverine flood potential was 16 (524 municipalities) and 18 (487 municipalities), respectively. Clusters of positive spatial autocorrelation are mostly located in the northern and eastern Slovakia, one cluster in western Slovakia and seven clusters in central Slovakia. Clusters of negative spatial autocorrelation are mostly located in western and southern Slovakia and three clusters in eastern Slovakia. The proposed methodology can be useful for regular updating of Preliminary Flood Risk Assessment (PFRA) in Slovakia under the EU Floods Directive.

Urban spatial structure features in Qinling mountain area based on ecological network analysis-case study of Shangluo City

Since the 20th century, the world is facing two major problems: the serious deterioration of the ecological environment and the accelerated decline of living quality of people residing in the urban environment. Urban development policies, ecological patterns, production and consumption modes have an important impact on global environmental changes that threaten the future living of mankind. The focus of urban space construction has also turned to the fields of ecological security, energy development, resource management and urban ecological virtuous circulation. Investigating urban spatial structure features from the perspective of urban metabolic system is important for ecological security and resource management. Shangluo urban space in Qinling area is used as the research object and an analysis system of urban spatial structure based on ecological network analysis is proposed in this study. First, an ecological network model of urban space was constructed from the research perspective of ecological network analysis and the system metabolic level was evaluated using metabolic scale, intensity, and efficiency. Second, the system structure of urban metabolic network and its functional relations were analyzed. On this basis, interactive relationships among different components in the metabolic system were explored via symbiosis index and symbiotic, competitive, predatory, and control relations. Meanwhile, the ecological network analysis method is used to construct an analysis system for urban spatial structure in the Qinling mountain area. Finally, the analysis system of urban spatial structure in the Qinling mountain area is applied to examine the urban spatial structure of Shangluo, Qinling Mountains, China. Results showed that resource utilization efficiency of Shangluo City presents a rising trend and the city is located in a strong structural center in the regional space. Predatory and control relations played a dominant role among ecological relations in the urban metabolic structure, and the urban space presented a clear uniaxially extended spatial structure. Sensitivity of internal environment was extremely evident, and the natural spatial structure was an important basis for urban space development in Shangluo. The urban spatial structure analysis system in this research is constructed with the three aspects of “metabolic level”, “ecological relationship” and “compartment weight” of the spatial structure information, which solves the problem that the conventional spatial structure analysis system is difficult to quantify the ecological network information, and it provides a new idea to explain the internal component interaction mechanism and spatial structure composition of the urban system. The results of this study can provide not only useful reference for urban spatial structure analysis of underdeveloped ecological capital areas in China but also a basis for sustainable development planning of urban spaces.

Abstract 6128: Establishment of spatial transcriptomics assay to study the mechanism of immune therapy against tumors

Abstract Background: Effective cancer immunotherapy is significantly affected by intratumoral heterogeneity, not only in different cell types and functions but also in the spatial pattern of immune cells within the tumor tissue. While most single-cell RNA sequencing technologies could enable the exploration of gene expression heterogeneity at the single-cell level, they cannot reveal spatial information within the tumor for us to map the whole transcriptome with morphological context. Spatial transcriptomics is an in situ capturing technique, which profiles gene expression at the RNA level, whilst preserving the spatial information of histological tissue sections. Thus we try to develop our spatial transcriptomics assay through a serial of validation experiments and to explore the mechanism of immune therapy against tumors. Material and Method: Firstly, the tumor was frozen and sections were cryosectioned at 10 μm thickness. Sections processing including H&E staining, tissue optimization, permeabilization, reverse transcription, and cDNA library preparation was carried out following the user guide of Visium Spatial Gene Expression Reagent Kits (10X Genomics). And the final cDNA libraries were sequenced using the Illumina Novaseq instrument. Using gene expression matrix and aligned H&E image processed by Cell Ranger and Loupe Browser with default parameters, we performed data QC, normalization, dimensionality reduction, and clustering by Seurat and cell components identification in tumor microenvironment based on a multistep approach. Differential gene expression and spatial heterogeneity were analyzed in each cluster. Results: Here we established a reliable system for spatial transcriptomics assay to elucidate the mechanism of anti-PD1 treatment in MC38 syngeneic colorectal tumor. Using this system, we constructed the gene expression spatial patterns of tumor cells and immune cells, including periphery and center of tumor cell, immune-cell enrichment area, and tumor cell surrounding the immune cell. Furthermore, we explored the cell-cell interactions in which the tumor cells directly interact with adjacent non-tumor cells, for example, macrophages. Using this system, we tried to investigate the mechanism of anti-PD-1 therapy against the tumors by comparing the spatial transcriptome profiles after the treatment with anti-PD-1 or isotype control in colorectal cancer models. Interestingly, changes in both gene-level and spatial levels were observed, and it will help reveal how the immune therapy may shake up the complex ecosystem. Summary: We established a reliable system for spatial transcriptomics analysis and explored the mechanism of anti-PD-1 treatment against the colorectal cancer by using this system. Citation Format: Panpan Wang, Huacheng He, Qiyao Zhang, Jingjing Wang, Dan Lu, Fei Duan, Qiangqiang Fan, Qingyang Gu, Qunsheng Ji. Establishment of spatial transcriptomics assay to study the mechanism of immune therapy against tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6128.

Mapping Highway Mobile Carbon Source Emissions Using Traffic Flow Big Data: A Case Study of Guangdong Province, China

The continuously growing transportation sector has become the second largest, yet increasing, industrial emissions source of CO2, posing serious challenges to global environmental security. Among the various transport modes, road transportation yields the highest cumulative level of CO2 emissions. However, these emissions have not been sufficiently investigated in previous studies, especially with respect to analyses from the perspective of vehicle emission sources. This can make source management and emissions reduction difficult. To address these methodological issues, this study aims to build a highway traffic carbon emissions monitoring and spatial analysis system, employing the mobile carbon sources concept, and establish a carbon emissions model encompassing all types of passenger and freight vehicles based on interstation O-D traffic flow data recorded by the toll collection network, to calculate vehicle carbon emissions and create a mobile carbon source emissions map. Empirical analyses in Guangdong Province revealed that, compared with conventional studies, the mobile carbon source emission mapping approach can accurately identify vehicle types with higher emissions while assisting with source management. Of the average total daily carbon emissions from all types of vehicles that use highways (15,311 t), 57.10% originated from freight vehicles (8,743 t) while passenger vehicles contributed 42.90%. By specific vehicle type, emissions mainly originated from small and medium-sized vehicles, including Class I passenger vehicles (i.e., cars) and Class I and III freight vehicles. Further, the proposed method could locate road sections characterized by high carbon emissions. High-emission sections in Guangdong Province were mainly spatially autocorrelated, with peak aggregations on national highways; near economically developed and densely populated areas; and adjacent to surrounding airports, ports, and overpass roads. This study improves the scientific and spatial analytical accuracy for carbon emissions measurements of highway vehicles, thus informing source management and sustainable development, as well as providing technical support for attaining carbon neutrality in China.

Rural Tourism Opportunity Spectrum: Linking People and Landscape for Spatial Planning

Abstract The aim of the study was to develop a low-cost method for tourism opportunity spectrum evaluation in rural landscapes. The method uses the geographic information system (GIS) for spatial analysis of the problem. Open source materials are used in the evaluation. Three principal indices derived from spatial data are evaluated: attraction index, view index, and access index. These form the basis for tourism suitability and opportunity spectrum evaluation. The analysis is realized for two types of tourists: those using cars, and hikers. The method permits the current state of tourism to be identified, and points out possible ways for further development as well as identifying valuable but overexploited zones which should be conserved. The obtained results can improve the sustainable management of landscapes and enhance the profits of rural areas.

Suitability evaluation method of urban and rural spatial planning based on artificial intelligence

Abstract In order to realize the sustainable development of urban overall space, aiming at the increasingly serious environmental problems in the process of contemporary rapid urbanization, based on the relationship between urban and rural space and environmental capacity, a suitability evaluation method of urban and rural spatial planning based on artificial intelligence is proposed. This paper constructs the theoretical system of sustainable development evaluation of urban and rural spatial resources and uses artificial intelligence technology to reasonably select evaluation factors and standardize the evaluation indicators so as to achieve the research goal of accurately evaluating the suitability of urban and rural spatial planning. It analyzes the influencing factors of urban–rural spatial standard regional division, develops the design of the spatial planning suitability analysis system, and establishes the urban-rural spatial suitability evaluation. The scope of sustainability evaluation was extended to the level of urban and rural spatial planning and design, and the preliminary work was done to solve the problems of urban spatial structure and decision-making. The experimental results show that the planning method has high environmental adaptability and rationality.

COVID-19 Outbreak in İstanbul.

OBJECTIVE The COVID-19 pandemic has demonstrated that the social determinants of health play a fundamental role in the course of the pandemic. This article aims to reveal the class dynamics of the COVID-19 epidemic in İstanbul, Turkey.Material and Methods Spatial analysis and geographic information system data provided by İstanbul Metropolitan Municipality for March and April 2020 were used. Public transport mobility and turnstile data were analyzed. The data obtained were collated into thematic maps.Results Between March 16 and 24, 2020, the use of public transportation declined with the tightening of movement restrictions. However, despite the restrictions, an increase in transportation density was observed between 6 and 9 am and between 5 and 7 pm. Although the overall mobility toward outside the city has fallen due to travel restrictions, it has been observed that exit mobility continued between Gebze and Kocaeli, both industrial centers where blue-collar jobs dominate. Most of the mobility in the city is observed in Avcılar, Bahçelievler, Esenyurt, and Küçükçekmece, which are mostly blue-collar residential districts. On the Asian side, activity was observed in Kurtköy, Pendik, Samandıra, Ümraniye, and Tuzla, areas where blue-collar workers predominantly reside. From March 25 to April 7, 2020, it was determined that the most intense activity areas of the blue-collar workers were Avcılar, Bahçelievler, Bağcılar, Çekmeköy, Esenyurt, Küçükçekmece, Ümraniye, and D-100 highway line.Conclusion The density in the use of public transportation rose during the hours corresponding to the working hours of the workers who had to continue working despite the pandemic. In addition, the physical movement of blue-collar workers continued despite the travel restrictions imposed along the city borders where they worked and resided. Our data point to the importance of social protection measures for workers in general, and blue-collar workers in particular, for the management of the pandemic.

Enabling Efficient Distributed Spatial Join on Large Scale Vector-Raster Data Lakes

Both the increasing number of GPS-enabled mobile devices and the geographic crowd-sourcing initiatives, such as Open Street Map, are determinants for the large amount of vector spatial data that is currently being produced. On the other hand, the automatic generation of raster data by remote sensing devices and environmental modeling processes was always leading to very large datasets. Currently, huge data generation rates are reached by improved sensor observation systems and data processing infrastructures. As an example, the Sentinel Data Access System of the Copernicus Program of the European Space Agency (ESA) was publishing 38.71 TB of data per day during 2020. This paper shows how the assumption of a new spatial data model that includes multi-resolution parametric spatial data types, enables achieving an efficient implementation of a large scale distributed spatial analysis system for integrated vector-raster data lakes. In particular, the proposed implementation outperforms the state-of-the-art Spark-based spatial analysis systems by more than one order of magnitude during vector-raster spatial join evaluation.

A framework for spatial analysis in 3D urban land administration – A case study for Victoria, Australia

The prolific growth in multi-story buildings in Victoria, Australia challenges the efficiency of 2D land administration system in dealing with spatially complex situations. Therefore, 3D digital approaches are being investigated to facilitate the management of rights, restrictions and responsibilities (RRRs) in cities. Previous research has focused on providing a general framework for 3D urban land administration. Generally, the main components are data capturing, data integration and modelling, validation, visualisation and spatial analysis. In order to provide future steps towards realising the 3D-enabled land administration system, an exact framework is also needed for each component; however, there is no comprehensive research to identify all the spatial analysis requirements and provide a general pathway for creating a unified spatial analysis system in urban land administration. Developing efficient mechanisms for spatial analysis can unlock the value of 3D RRR data, which would subsequently improve decision-making in complex urban environments. Therefore, this study provides a framework for spatial analysis in 3D urban land administration system. The paper’s methodology utilises a case study approach in which the existing regulations and legislations are investigated to identify the required spatial analysis. Then the capabilities of current 3D analytical approaches in terms of addressing regulatory requirements are assessed in order to gain a general view of the research gaps. By considering the identified 3D analytical requirements and knowledge gaps, a framework for spatial analysis will be provided.

Spatial Pattern and Influencing Factors of Outward Foreign Direct Investment Enterprises in the Yangtze River Economic Belt of China

This paper studies outward foreign direct investment (OFDI) enterprises in the Yangtze River Economic Belt. Using geographical information system (GIS) spatial analysis and SPSS correlation analysis methods, it analyzes the change in the spatial distribution of OFDI enterprises in 2010, 2014, and 2018. It explores the influencing factors that have an impact on this change. The results show the following: (1) The geographical distribution of OFDI enterprises in the Yangtze River Economic Belt is uneven. In the downstream region, OFDI enterprises have significant advantages in both quantity and quality over those in the mid- and up-stream regions. In recent years, a multi-core spatial pattern has gradually emerged. (2) The factors influencing the spatial distribution of OFDI enterprises have been gradually changing from one dominant factor, i.e., technological innovation capability, to four core factors, namely, urbanization level, economic development level, technological innovation capability, and degree of economic openness. The research results serve as an important reference for future policy adjustment in the Yangtze River Economic Belt. First, the Yangtze River Economic Belt should adjust industrial policies; comprehensively increase the level of OFDI; accelerate the upgrading and transformation of regional industries; and, at the same time, inject vitality into the development of the world economy. Moreover, the downstream region should fully play a leading role in the Yangtze River Economic Belt, especially in encouraging OFDI enterprises to establish global production networks. Meanwhile, enterprises in the upstream region are encouraged to establish regional production networks to accelerate the development of inland open highlands.

Mapping Buildings’ Energy-Related Features at Urban Level toward Energy Planning

To boost energy efficiency in the building sector at urban and district scales, the use of a Geographic Information System (GIS) for data collection and energy spatial analysis is relevant. As highlighted in many studies on this topic reported in literature, the correlation among available databases is complex due to the different levels of information. As the first part of a wide research aimed at estimating the energy demand of urban buildings, we present in this article a focus on the details of the GIS-based procedure developed to assess the main energy-related features of existing building stocks. The procedure is based on the elaboration of data from the Italian Topographic Databases, under provision at the national level according to the INSPIRE European Directive and the national General Census of Population and Houses. It enables one to calculate and map the urban built volume characterized by mostly diffuse use categories in an urban context (residential and offices), to which different equipment and building usage patterns can be associated, and by construction periods, featuring different technological solutions. The method has been applied to the city of Milan (Italy). An insight into the outcomes from the overall method of the wider research is also reported.

Geographic disparities in performance of pediatric polysomnography to diagnose obstructive sleep apnea in a universal access health care system

BackgroundDiagnostic polysomnography (PSG) is recommended prior to adenotonsillectomy (AT) for children with obstructive sleep apnea (OSA) and certain high-risk characteristics, but resource limitations often prevent this practice. ObjectiveWe performed a population-based assessment of children across Ontario, Canada to describe and quantify disparities in PSG. Methods and materialsThis retrospective cohort study was performed using provincial health administrative data held at ICES. We identified children 0–10 years old who underwent PSG and AT between 2009 and 2018, and those with a PSG within 18 months prior to and/or 12 months following AT. We calculated the odds of PSG prior to/following AT after adjustment for demographics, medical comorbidities, geographic and socioeconomic characteristics. Our main predictor was driving time/distance to the nearest pediatric sleep centre ascertained using spatial analysis and geographic information systems. ResultsWe identified 27,837 children <10 years old who underwent AT for OSA in Ontario. Only 12.8% had a PSG within 18 months prior and 5.7% had a PSG within 12 months following AT. Shorter driving time/distance, older age, male sex and certain comorbidities were associated with increased odds of PSG. ConclusionOnly a small proportion of children in our cohort underwent PSG prior to or following AT surgery despite universal access to healthcare. This study suggests a need to increase overall PSG access, particularly for those living distant from existing pediatric sleep centres. Future studies could determine if increased PSG testing in ‘underserviced areas’ would reduce overall surgery rates and/or improve health outcomes.

Spatial Analysis and Geographic Information Systems as Tools for Sustainability Research

The multidisciplinary fields of study on sustainability, which relate to ecological, geophysical, societal and environmental research, demand for the availability and processing of data that is capable to represent spatial phenomena [...]

Comparative Analysis of Spark and Ignite for Big Spatial Data Processing

Recently, spatial data became one of the most interesting fields related to big data studies, in which the spatial data have been generated and consumed from different resources. However, the increasing numbers of location-based services and applications such as Google Maps, vehicle navigation, recommendation systems are the main foundation of the idea of spatial data. On the other hand, several researchers started to discover and compared spatial frameworks to understand the requirements for spatial database processing, manipulating, and analysis systems. Apache Spark, Apache Ignite, and Hadoop are the most widely known frameworks for large data processing. However, Apache Spark, Apache Ignite have integrated different spatial data operations and analysis queries, but each system has its advantages and disadvantages when dealing with spatial data. Dealing with a new framework or system that needs to integrate new functionality sometimes becomes a risky decision if we did not examine it well The main aim of this research is to conduct a comprehensive evaluation of big spatial data computing on two well-known data management systems Apache Ignite and Apache Spark. The comparative has been done on four different domains, experimental environment setup, supported features, supported functions and queries, and performance and execution time. The results show that GeoSpark has recorded more flexibility to use than SpatialIgnite. We thoroughly investigated and discovered that multiple factors affect the performance of both frameworks, such as CPU, Main memory, data set size the complexity of data type, and programming environment. spark is more advanced and equipped with several functionalities that made it well suitable with spatial data queries and indexing. such as kNN queries; in which these functionalities are not supported in SpatialIgnite.

Analysis on spatial distribution pattern of football fields: A case study in Wuhan, China

In order to promote the sustainable development of sports facilities, the statistical data of football fields in 13 districts of Wuhan city were selected. Based on geographic information system (GIS) and exploratory spatial data analysis (ESDA) technology, this paper analyzed the global and local autocorrelation of the number of football fields per capita in Wuhan city. The results indicate that: (1) Comparing to the new districts in Wuhan, the number of football fields per capita in the central districts was relatively few. (2) In the global scale, the number of football fields per capita in Wuhan presented a spatial aggregation pattern. (3) In the local scale, the regional discrepancy and spatial clusters were confirmed in the local spatial autocorrelation analysis for football fields in Wuhan. At the same time, the research results could provide reasonable references for the planning of football field facilities.

A Decision Support System for Spatial Analysis of Agricultural Production in Madagascar

In this article, our research aims to set up a geo-decisional system, more precisely we are particularly interested in the spatial analysis system of agricultural production in Madagascar. For this, we used the spatial data warehouse technique based on the SOLAP spatial analysis tool. After having defined the concepts underlying these systems, we propose to address the research issues related to them from four points of view: needs study of the Malagasy Ministry of Agriculture, modeling of a multidimensional conceptual model according to the MultiDim model and the implementation of the system studied using GeoKettle, PostGIS, GeoServer, SPAGO BI and Geomondrian technologies. This new system helps improve the decision-making process for agricultural production in Madagascar.

AR Book-Finding Behavior of Users in Library Venue

ARKit and ARCore, key technologies in recent augmented reality (AR) development, have allowed AR to become more integrated in our lives. However, how effective AR is in an auxiliary role in venue guidance and how to collect the actual behaviors of users in physical venues are worth exploring. This study used navAR, a spatial behavior analysis system app that our research team developed, to collect the actual behaviors of participants in physical space via a smartphone, such as time, distance travelled, and trajectory, and compared their book-finding behaviors in a library venue in a text scenario and an AR scenario without any additional sensors or cameras. The experiment results revealed that (1) AR targets made a significant difference in book search time, and the participants found some of the books significantly faster; (2) the participants presented no significant differences in distance travelled; (3) with an AR target, the book-finding trajectories of the participants were significantly more regular; (4) the AR guidance system had good usability. The results of this study can facilitate planning with AR in indoor venue routes, improve venue and exhibition tour experiences, and enable AR to be used for crowd flow diversion. Furthermore, this study provides a methodology for future analyses on user behavior in physical spaces.