المؤلفون: Tian, Yuanyuan, Li, Wenwen, Wang, Sizhe, Gu, Zhining

المصدر: Transactions in GIS (2023)

مصطلحات موضوعية: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Information Retrieval

الوصف: Initiated by the University Consortium of Geographic Information Science (UCGIS), GIS&T Body of Knowledge (BoK) is a community-driven endeavor to define, develop, and document geospatial topics related to geographic information science and technologies (GIS&T). In recent years, GIS&T BoK has undergone rigorous development in terms of its topic re-organization and content updating, resulting in a new digital version of the project. While the BoK topics provide useful materials for researchers and students to learn about GIS, the semantic relationships among the topics, such as semantic similarity, should also be identified so that a better and automated topic navigation can be achieved. Currently, the related topics are either defined manually by editors or authors, which may result in an incomplete assessment of topic relationship. To address this challenge, our research evaluates the effectiveness of multiple natural language processing (NLP) techniques in extracting semantics from text, including both deep neural networks and traditional machine learning approaches. Besides, a novel text summarization - KACERS (Keyword-Aware Cross-Encoder-Ranking Summarizer) - is proposed to generate a semantic summary of scientific publications. By identifying the semantic linkages among key topics, this work provides guidance for future development and content organization of the GIS&T BoK project. It also offers a new perspective on the use of machine learning techniques for analyzing scientific publications, and demonstrate the potential of KACERS summarizer in semantic understanding of long text documents.

الوصول الحر: http://arxiv.org/abs/2305.09877Test

المؤلفون: Wang, Sizhe, Li, Wenwen, Gu, Zhining

مصطلحات موضوعية: Computer Science - Human-Computer Interaction

الوصف: Knowledge graphs are a key technique for linking and integrating cross-domain data, concepts, tools, and knowledge to enable data-driven analytics. As much of the worlds data have become massive in size, visualizing graph entities and their interrelationships intuitively and interactively has become a crucial task for ingesting and better utilizing graph content to support semantic reasoning, discovering hidden knowledge discovering, and better scientific understanding of geophysical and social phenomena. Despite the fact that many such phenomena (e.g., disasters) have clear spatial footprints and geographical properties, their location information is considered only as a textual label in existing graph visualization tools, limiting their capability to reveal the geospatial distribution patterns of the graph nodes. In addition, most graph visualization techniques rely on 2D graph visualization, which constraints the dimensions of information that can be presented and lacks support for graph structure examination from multiple angles. To tackle the above challenges, we developed a novel 3D map-based graph visualization algorithm to enable interactive exploration of graph content and patterns in a spatially explicit manner. The algorithm extends a 3D force directed graph by integrating a web map, an additional geolocational force, and a force balancing variable that allows for the dynamic adjustment of the 3D graph structure and layout. This mechanism helps create a balanced graph view between the semantic forces among the graph nodes and the attractive force from a geolocation to a graph node. Our solution offers a new perspective in visualizing and understanding spatial entities and events in a knowledge graph.

الوصول الحر: http://arxiv.org/abs/2304.09864Test

المؤلفون: Gu, Zhining, Li, Wenwen, Hanemann, Michael, Tsai, Yushiou, Wutich, Amber, Westerhoff, Paul, Landes, Laura, Roque, Anais D., Zheng, Madeleine, Velasco, Carmen A., Porter, Sarah

مصطلحات موضوعية: Statistics - Applications

الوصف: This paper explores the application of machine learning to enhance our understanding of water accessibility issues in underserved communities called Colonias located along the northern part of the United States - Mexico border. We analyzed more than 2000 such communities using data from the Rural Community Assistance Partnership (RCAP) and applied hierarchical clustering and the adaptive affinity propagation algorithm to automatically group Colonias into clusters with different water access conditions. The Gower distance was introduced to make the algorithm capable of processing complex datasets containing both categorical and numerical attributes. To better understand and explain the clustering results derived from the machine learning process, we further applied a decision tree analysis algorithm to associate the input data with the derived clusters, to identify and rank the importance of factors that characterize different water access conditions in each cluster. Our results complement experts' priority rankings of water infrastructure needs, providing a more in-depth view of the water insecurity challenges that the Colonias suffer from. As an automated and reproducible workflow combining a series of tools, the proposed machine learning pipeline represents an operationalized solution for conducting data-driven analysis to understand water access inequality. This pipeline can be adapted to analyze different datasets and decision scenarios.
Comment: 26 pages, 7 figures, accepted by Computers, Environment and Urban Systems (CEUS)

الوصول الحر: http://arxiv.org/abs/2303.17048Test

المؤلفون: Li, Wenwen, Wang, Sizhe, Chen, Xiao, Tian, Yuanyuan, Gu, Zhining, Lopez-Carr, Anna, Schroeder, Andrew, Currier, Kitty, Schildhauer, Mark, Zhu, Rui

المصدر: Li , W , Wang , S , Chen , X , Tian , Y , Gu , Z , Lopez-Carr , A , Schroeder , A , Currier , K , Schildhauer , M & Zhu , R 2023 , ' GeoGraphVis : A Knowledge Graph and Geovisualization Empowered Cyberinfrastructure to Support Disaster Response and Humanitarian Aid ' , ISPRS International Journal of Geo-Information , vol. 12 , no. 3 , 112 . https://doi.org/10.3390/ijgi12030112Test

مصطلحات موضوعية: big data, cyberinfrastructure, disaster response, humanitarian aid, knowledge graph, semantics, spatial decision support, storytelling, visual analytics, visualization

الوصف: The past decade has witnessed an increasing frequency and intensity of disasters, from extreme weather, drought, and wildfires to hurricanes, floods, and wars. Providing timely disaster response and humanitarian aid to these events is a critical topic for decision makers and relief experts in order to mitigate impacts and save lives. When a disaster occurs, it is important to acquire first-hand, real-time information about the potentially affected area, its infrastructure, and its people in order to develop situational awareness and plan a response to address the health needs of the affected population. This requires rapid assembly of multi-source geospatial data that need to be organized and visualized in a way to support disaster-relief efforts. In this paper, we introduce a new cyberinfrastructure solution—GeoGraphVis—that is empowered by knowledge graph technology and advanced visualization to enable intelligent decision making and problem solving. There are three innovative features of this solution. First, a location-aware knowledge graph is created to link and integrate cross-domain data to make the graph analytics-ready. Second, expert-driven disaster response workflows are analyzed and modeled as machine-understandable decision paths to guide knowledge exploration via the graph. Third, a scene-based visualization strategy is developed to enable interactive and heuristic visual analytics to better comprehend disaster impact situations and develop action plans for humanitarian aid.

العلاقة: https://research-information.bris.ac.uk/en/publications/23b6700d-8cfa-4c9c-ba1a-fae1cf86de32Test

الإتاحة: https://doi.org/10.3390/ijgi12030112Test
https://hdl.handle.net/1983/23b6700d-8cfa-4c9c-ba1a-fae1cf86de32Test
https://research-information.bris.ac.uk/en/publications/23b6700d-8cfa-4c9c-ba1a-fae1cf86de32Test
http://www.scopus.com/inward/record.url?scp=85150747686&partnerID=8YFLogxKTest

المؤلفون: Potort, Francesco, Torres-Sospedra, Joaquín, Quezada Gaibor, Darwin, Jiménez, Antonio Ramón, Seco, Fernando, Perez-Navarro, Antoni, Ortiz, Miguel, Zhu, Ni, Renaudin, Valerie, Ichikari, Ryosuke, Shimomura, Ryo, Kaichi, Tomoya, Zhou, Baoding, Liu, Xu, Gu, Zhining, Yang, Chengjing, Wu, Zhiqian, Xie, Doudou, Huang, Can, Zheng, Lingxiang, Peng, Ao, Jin, Ge, Wang, Qu, Luo, Haiyong, Xiong, Hao, Bao, Linfeng, Zhang, Pushuo, Zhao, Fang, Yu, Chia-An, Hung, Chung-Hao, Antsfeld, Leonid, Chidlovskii, Boris, Jiang, Haitao, Xia, Ming, Yan, Dayu, Li, Yuhang, Dong, Yitong, Silva, Ivo, Pendão, Cristiano, Meneses, Filipe, Nicolau, Maria João, Costa, António, Moreira, Adriano, De Cock, Cedric, Plets, David, Opiela, Miroslav, Dzama, Jakub, Zhang, Liqiang, Li, Hu, Chen, Boxuan, Liu, Yu, Yean, Seanglidet, Lim, Bo Zhi, Teo, Wei Jie, Lee, Bu Sung, OH, HL, ohta, nozomu, Nagae, Satsuki, Kurata, Takeshi, dongyan, wei, Ji, Xinchun, Zhang, Wenchao, Kram, Sebastian, Stahlke, Maximilian, Mutschler, Christopher, Crivello, Antonino, Barsocchi, Paolo, GIROLAMI, MICHELE, Palumbo, Filippo, Chen, Ruizhi, Wu, Yuan, Li, Wei, Yu, Yue, Xu, Shihao, Huang, Lixiong, Liu, Tao, Kuang, Jian, Niu, Xiaoji, Yoshida, Takuto, Nagata, Yoshiteru, Fukushima, Yuto, Fukatani, Nobuya, Hayashida, Nozomi, Asai, Yusuke, Urano, Kenta, Ge, Wenfei, Lee, Nien-Ting, Fang, Shih-Hau, Jie, You-Cheng, Young, Shawn-Rong, Chien, Ying-Ren, Yu, Chih-Chieh, Ma, Chengqi, Wu, Bang, Zhang, Wei, Wang, Yankun, Fan, Yonglei, Poslad, Stefan, Selviah, David, Wang, Weixi, Yuan, Hong, Yonamoto, Yoshitomo, Yamaguchi, Masahiro

المساهمون: Universitat Oberta de Catalunya (UOC)

مصطلحات موضوعية: indoor positioning and navigation, evaluation, smartphone-based positioning, foot-mounted IMU, positioning in industrial scenarios and factories, vehicle-positioning, navegación y posicionamiento en interiores, evaluación, posiciónamiento basado en teléfonos inteligentes, IMU con patas, posicionamiento en escenarios industriales y fábricas, posicionamiento del vehículo, navegació i posicionament en interiors, evaluació, posicionament basat en teléfons inteligents, IMU amb cames, posicionament en escenaris industrials i fabriques, posicionament del vehicle, electronics in navigation, electrònica en la navegació, electrónica en la nevagación

الوصف: Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoorpositioning andnavigationpurposes.Throughfaircomparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1m for the Smartphone Track and 0.5m for the Footmounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements

وصف الملف: application/pdf

العلاقة: IEEE Sensors Journal, 2022, 22(6); https://www.doi.org/10.1109/JSEN.2021.3083149Test; http://hdl.handle.net/10609/147005Test

الإتاحة: https://doi.org/10.1109/JSEN.2021.3083149Test
http://hdl.handle.net/10609/147005Test

المؤلفون: Potorti, Francesco, Torres-Sospedra, Joaquín, Quezada-Gaibor, Darwin, Jimenez, Antonio Ramon, Seco, Fernando, Perez-Navarro, Antoni, Ortiz, Miguel, Zhu, Ni, Renaudin, Valerie, Ichikari, Ryosuke, Shimomura, Ryo, Ohta, Nozomu, Nagae, Satsuki, Kurata, Takeshi, Wei, Dongyan, Ji, Xinchun, Zhang, Wenchao, Kram, Sebastian, Stahlke, Maximilian, Mutschler, Christopher, Crivello, Antonino, Barsocchi, Paolo, Girolami, Michele, Palumbo, Filippo, Chen, Ruizhi, Wu, Yuan, Li, Wei, Yu, Yue, Xu, Shihao, Huang, Lixiong, Liu, Tao, Kuang, Jian, Niu, Xiaoji, Yoshida, Takuto, Nagata, Yoshiteru, Fukushima, Yuto, Fukatani, Nobuya, Hayashida, Nozomi, Asai, Yusuke, Urano, Kenta, Ge, Wenfei, Lee, Nien-Ting, Fang, Shih-Hau, Jie, You-Cheng, Young, Shawn-Rong, Chien, Ying-Ren, Yu, Chih-Chieh, Ma, Chengqi, Wu, Bang, Zhang, Wei, Wang, Yankun, Fan, Yonglei, Poslad, Stefan, Selviah, David R., Wang, Weixi, Yuan, Hong, Yonamoto, Yoshitomo, Yamaguchi, Masahiro, Kaichi, Tomoya, Zhou, Baoding, Liu, Xu, Gu, Zhining, Yang, Chengjing, Wu, Zhiqian, Xie, Doudou, Huang, Can, Zheng, Lingxiang, Peng, Ao, Jin, Ge, Wang, Qu, Luo, Haiyong, Xiong, Hao, Bao, Linfeng, Zhang, Pushuo, Zhao, Fang, Yu, Chia-An, Hung, Chun-Hao, Antsfeld, Leonid, Silva, Ivo Miguel Menezes, Pendão, Cristiano Gonçalves, Meneses, Filipe, Nicolau, Maria João, Costa, António, Moreira, Adriano, Cock, Cedric De, Plets, David, Opiela, Miroslav, Jakub Džama, Zhang, Liqiang, Li, Hu, Chen, Boxuan, Liu, Yu, Yean, Seanglidet, Lim, Bo Zhi, Teo, Wei Jie, Lee, Bu Sung, Oh, Hong Lye

مصطلحات موضوعية: Sensor phenomena and characterization, Indoor navigation, Testing, Standards, Satellite broadcasting, Recurrent neural networks, Received signal strength indicator, Indoor positioning and navigation, evaluation, smartphone-based positioning, foot-mounted IMU, positioning in industrial scenarios and factories, vehicle-positioning, Ciências Naturais::Ciências da Computação e da Informação, Science & Technology

الوصف: Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements. ; Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. ...

وصف الملف: application/pdf

العلاقة: info:eu-repo/grantAgreement/EC/H2020/813278/EU; info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00319%2F2020/PT; info:eu-repo/grantAgreement/FCT/POR_NORTE/PD%2FBD%2F137401%2F2018/PT; https://ieeexplore.ieee.org/document/9439493Test; F. Potortì et al., "Off-Line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences From IPIN 2020 Competition," in IEEE Sensors Journal, vol. 22, no. 6, pp. 5011-5054, 15 March15, 2022, doi:10.1109/JSEN.2021.3083149.; https://hdl.handle.net/1822/82092Test

الإتاحة: https://doi.org/10.1109/JSEN.2021.3083149Test
https://hdl.handle.net/1822/82092Test

المؤلفون: Janowicz, Krzysztof, Hitzler, Pascal, Li, Wenwen, Rehberger, Dean, Schildhauer, Mark, Zhu, Rui, Shimizu, Cogan, Fisher, Colby K., Cai, Ling, Mai, Gengchen, Zalewski, Joseph, Zhou, Lu, Stephen, Shirly, Gonzalez, Seila, Mecum, Bryce, Lopez-Carr, Anna, Schroeder, Andrew, Smith, David, Wright, Dawn, Wang, Sizhe, Tian, Yuanyuan, Liu, Zilong, Shi, Meilin, D’onofrio, Anthony, Gu, Zhining, Currier, Kitty

المصدر: Janowicz , K , Hitzler , P , Li , W , Rehberger , D , Schildhauer , M , Zhu , R , Shimizu , C , Fisher , C K , Cai , L , Mai , G , Zalewski , J , Zhou , L , Stephen , S , Gonzalez , S , Mecum , B , Lopez-Carr , A , Schroeder , A , Smith , D , Wright , D , Wang , S , Tian , Y , Liu , Z , Shi , M , D’onofrio , A , Gu , ....

الوصف: Knowledge graphs (KGs) are a novel paradigm for the representation, retrieval, and integration of data from highly heterogeneous sources. Within just a few years, KGs and their supporting technologies have become a core component of modern search engines, intelligent personal assistants, business intelligence, and so on. Interestingly, despite large-scale data availability, they have yet to be as successful in the realm of environmental data and environmental intelligence. In this paper, we will explain why spatial data require special treatment, and how and when to semantically lift environmental data to a KG. We will present our KnowWhereGraph that contains a wide range of integrated datasets at the human–environment interface, introduce our application areas, and discuss geospatial enrichment services on top of our graph. Jointly, the graph and services will provide answers to questions such as “what is here,” “what happenedherebefore,”and“howdoesthisregioncompareto…”foranyregionon earth within seconds.

وصف الملف: application/pdf

العلاقة: https://research-information.bris.ac.uk/en/publications/be176aba-9dec-456c-9615-01a0e8556b7bTest

الإتاحة: https://doi.org/10.1002/aaai.12043Test
https://hdl.handle.net/1983/be176aba-9dec-456c-9615-01a0e8556b7bTest
https://research-information.bris.ac.uk/en/publications/be176aba-9dec-456c-9615-01a0e8556b7bTest
https://research-information.bris.ac.uk/ws/files/340460803/Full_text_PDF_final_published_version_.pdfTest
http://www.scopus.com/inward/record.url?scp=85134355262&partnerID=8YFLogxKTest

المؤلفون: Liu, Zilong, Gu, Zhining, Thelen, Thomas, Estrecha, Seila Gonzalez, Zhu, Rui, Fisher, Colby K., D'Onofrio, Anthony, Shimizu, Cogan, Janowicz, Krzysztof, Schildhauer, Mark, Stephen, Shirly, Rehberger, Dean, Li, Wenwen, Hitzler, Pascal

المساهمون: Renz, Matthias, Sarwat, Mohamed, Nascimento, Mario A., Shekhar, Shashi, Xie, Xing

المصدر: Liu , Z , Gu , Z , Thelen , T , Estrecha , S G , Zhu , R , Fisher , C K , D'Onofrio , A , Shimizu , C , Janowicz , K , Schildhauer , M , Stephen , S , Rehberger , D , Li , W & Hitzler , P 2022 , Knowledge explorer : exploring the 12-billion-statement KnowWhereGraph using faceted search (demo paper) . in M Renz , M Sarwat , M A Nascimento , S Shekhar & X Xie (eds) , 30th ACM SIGSPATIAL International Conference on Advances in Geographic ....

مصطلحات موضوعية: environmental intelligence, faceted search, knowledge graph, KnowWhereGraph, spatial query generation

الوصف: Knowledge graphs are a rapidly growing paradigm and technology stack for integrating large-scale, heterogeneous data in an AI-ready form, i.e., combining data with the formal semantics required to understand it. However, toolchains that support data synthesis and knowledge discovery through information organization, search, filtering, and visualization have been developed at a pace lagging knowledge graph technology. In this paper, we present Knowledge Explorer, an open-source faceted search interface that provides environmentally intelligent services for interactively browsing and navigating KnowWhereGraph. Currently one of the largest open knowledge graphs, KnowWhereGraph contains over 12 billion statements with rich spatial and temporal information from more than 30 data layers. With an extensive collection of facets, Knowledge Explorer enables spatial, temporal, full-text, and expert search with dereferencing functionality to support "follow-your-nose"exploration, and it allows users to narrow their search by selecting facets. Given the size of the underlying graph and dependency on GeoSPARQL, we have improved query performance by implementing Elasticsearch indexing, spatial query generation, and caching. Knowledge Explorer is capable of retrieving information within seconds, answering a wide variety of competency questions posed by researchers, humanitarian relief organizations, and the broader public, thus helping better perform tasks such as cross-gazetteer place retrieval and disaster assessment from global to local geographic scales.

العلاقة: https://research-information.bris.ac.uk/en/publications/d3c13652-6aeb-4e1a-96de-2d2e623a420eTest; urn:ISBN:9781450395298

الإتاحة: https://doi.org/10.1145/3557915.3561009Test
https://hdl.handle.net/1983/d3c13652-6aeb-4e1a-96de-2d2e623a420eTest
https://research-information.bris.ac.uk/en/publications/d3c13652-6aeb-4e1a-96de-2d2e623a420eTest
http://www.scopus.com/inward/record.url?scp=85143592300&partnerID=8YFLogxKTest

المؤلفون: Wutich, Amber, Jepson, Wendy, Velasco, Carmen, Roque, Anais, Gu, Zhining, Hanemann, Michael, Hossain, Mohammed Jobayer, Landes, Laura, Larson, Rhett, Li, Wen Wen, Morales‐Pate, Olga, Patwoary, Nargish, Porter, Sarah, Tsai, Yu‐shiou, Zheng, Madeleine, Westerhoff, Paul

المساهمون: National Science Foundation of Sri Lanka

المصدر: WIREs Water ; volume 9, issue 4 ; ISSN 2049-1948 2049-1948

الوصف: Since the late 1970s, the term “colonias” (in English) has described low‐income, peri‐urban, and rural subdivisions north of the U.S.‐Mexico border. These communities are in arid and semi‐arid regions—now in a megadrought—and tend to have limited basic infrastructure, including community water service and sanitation. Recent scholarship has demonstrated how colonias residents experience unjust and inequitable dynamics that produce water insecurity in the Global North. In this review, we explain why U.S. colonias are an important example for theorizing water insecurity in the United States and beyond in the Global North. Tracing the history of water infrastructure development in U.S. colonias, we show how colonias are legally and socially defined by water insecurity. We draw on the published literature to discuss key factors that produce water insecurity in U.S. colonias: political exclusion, municipal underbounding, and failures in water quality monitoring. We show that water insecurity had led to negative outcomes—including poor water access, risks to physical health, and mental ill‐health—in U.S. colonias. We present four possible approaches to improving water security in U.S. colonias: (1) soft paths & social infrastructure for water delivery, (2) decentralized water treatment approaches, such as point‐of‐use, point‐of‐entry, and fit‐for‐purpose systems; (3) informality, including infrastructural, economic, and socio‐cultural innovations; and (4) political, policy, and law innovations and reforms. At the same time, we reflect seriously on how water security can be ethically achieved in partnership and aligning with the visions of U.S. colonias residents themselves. This article is categorized under: Human Water > Water Governance Engineering Water > Water, Health, and Sanitation

الإتاحة: https://doi.org/10.1002/wat2.1595Test

المؤلفون: Li, Wenwen, Wang, Sizhe, Wu, Sheng, Gu, Zhining, Tian, Yuanyuan

المساهمون: National Science Foundation

المصدر: Computers, Environment and Urban Systems ; volume 98, page 101884 ; ISSN 0198-9715

مصطلحات موضوعية: Urban Studies, General Environmental Science, Ecological Modeling, Geography, Planning and Development

الإتاحة: https://doi.org/10.1016/j.compenvurbsys.2022.101884Test
https://api.elsevier.com/content/article/PII:S0198971522001284?httpAccept=text/xmlTest
https://api.elsevier.com/content/article/PII:S0198971522001284?httpAccept=text/plainTest