World's Best Scientists 2026 revealed!
Computers, Environment and Urban Systems
H-index 35

Computers, Environment and Urban Systems

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 208 46 70 26
Social Sciences and Humanities 332 21 34 12
Engineering and Technology 626 19 36 14

Additional Metrics

Number of Best Scientists*: 140
Documents by Best Scientists*: 182
Top 100 Ranked Scientists*: 5
SCIMAGO H-index: 118
SCIMAGO SJR: 2.523
Impact Factor: 8.3

Overview

Top Research Topics at Computers, Environment and Urban Systems?

Computers, Environment and Urban Systems investigates areas of study like Geographic information system, Cartography, Operations research, Data mining and Urban planning. Geographic information system research featured in it incorporates concerns from various other topics such as Environmental resource management, Spatial analysis, Information system and Data science. The study on Cartography presented is investigated in conjunction with research in Land use.

Topics in Operations research were tackled in line with various other fields like Decision support system and Process (engineering).

  • Geographic information system (14.92%)
  • Cartography (12.95%)
  • Operations research (11.43%)

What are the most cited papers published in the journal?

  • Using neural networks and GIS to forecast land use changes: a Land Transformation Model (536 citations)
  • High-resolution integrated modelling of the spatial dynamics of urban and regional systems (498 citations)
  • The role of spatial metrics in the analysis and modeling of urban land use change (440 citations)

Research areas of the most cited articles at Computers, Environment and Urban Systems:

The main points discussed in the published articles deal with Geographic information system, Cartography, Operations research, Land use and Urban planning. The most cited publications explore topics in Geographic information system which can be helpful for research in disciplines like Spatial analysis, Decision support system, Data mining, Geospatial analysis and Data science. Context (language use) and Information system are some topics wherein Operations research research discussed in the journal papers has an impact.

What topics the last edition of the journal is best known for?

  • Law
  • Artificial intelligence
  • Statistics

The previous edition focused in particular on these issues:

Statistical hypothesis testing, Road user, Pedestrian, Overtaking and Simulation are among the topics commonly tackled in Computers, Environment and Urban Systems. The work on Statistical hypothesis testing tackled in Computers, Environment and Urban Systems brings together disciplines like Space model, Statistical dispersion and Traffic dynamics.

The most cited articles from the last journal are:

  • Associations between mobility and socio-economic indicators vary across the timeline of the Covid-19 pandemic (1 citations)
  • Simulation of dispersion effects by considering interactions of pedestrians and bicyclists using an agent space model (0 citations)
  • An extended patch-based cellular automaton to simulate horizontal and vertical urban growth under the shared socioeconomic pathways (0 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in Computers, Environment and Urban Systems (based on the number of publications) are:

  • Richard Langendorf (62 papers) absent at the last edition,
  • Jantien Stoter (15 papers) absent at the last edition,
  • Paul A. Longley (14 papers) absent at the last edition,
  • Robert Laurini (12 papers) absent at the last edition,
  • Keith C. Clarke (12 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in Computers, Environment and Urban Systems (based on the number of publications) are:

  • Wuhan University (60 papers) published 1 paper at the last edition, 9 less than at the previous edition,
  • University College London (43 papers) absent at the last edition,
  • Delft University of Technology (39 papers) absent at the last edition,
  • Arizona State University (33 papers) absent at the last edition,
  • University of Melbourne (33 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2022 edition, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 20.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 40.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 20.00% of all publications and 20.00% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

How to Contribute to the Journal

Are you interested in computers, environment, and urban systems? This journal might just be the right platform to publish your research work. We have a few steps that you might find helpful in your quest for knowledge and discovery. First, focus on broad topics within the scope of our journal. Research on topics like Geographic Information Systems, Cartography, Operations Research, Data Mining, and Urban Planning are welcomed and encouraged. Second, the quality of research is imperative. One way to ensure this is to maintain high standards in your investigating methods. Feel free to refer to the most cited papers in our journal for examples of high-quality research and writing. Third, as we recognize research as an ongoing collaborative effort, it is important to respect previous works in your area. Properly citing them enhances the reliability of your work and helps to build a more robust and interwoven scientific community. Finally, keep abreast with our latest research topics. This will help you plan your research in line with our journal's interest. For those in the mental health field interested in furthering their career, there are many paths to explore. One example would be to become a marriage and family therapist, which involves specialized education and training. For details on this career path, refer to our comprehensive guide on How to become a marriage and family therapist in Oklahoma. By following these guidelines, you are contributing not just to our journal, but also to the wider research community. Let's advance our knowledge and work together for development and innovation in the field of computers, environment, and urban systems.

Top Publications

  • Portraying the spatial dynamics of urban vibrancy using multisource urban big data

    Wei Tu;Tingting Zhu;Jizhe Xia;Yulun Zhou

    (2020)
    216 Citations
  • Understanding spatio-temporal heterogeneity of bike-sharing and scooter-sharing mobility

    Rui Zhu;Xiaohu Zhang;Dániel Kondor;Paolo Santi

    (2020)
    153 Citations
  • Urban function classification at road segment level using taxi trajectory data: A graph convolutional neural network approach

    Sheng Hu;Song Gao;Liang Wu;Yongyang Xu

    (2021)
    145 Citations
  • Classification of urban morphology with deep learning: Application on urban vitality

    Wangyang Chen;Abraham Noah Wu;Filip Biljecki

    (2021)
    141 Citations
  • Uncovering inconspicuous places using social media check-ins and street view images

    Fan Zhang;Jinyan Zu;Mingyuan Hu;Di Zhu

    (2020)
    129 Citations
  • Modeling urban growth using spatially heterogeneous cellular automata models: Comparison of spatial lag, spatial error and GWR

    Chen Gao;Chen Gao;Yongjiu Feng;Xiaohua Tong;Zhenkun Lei

    (2020)
    112 Citations
  • Using graph structural information about flows to enhance short-term demand prediction in bike-sharing systems

    Yuanxuan Yang;Yuanxuan Yang;Alison J. Heppenstall;Andy Turner;Alexis J. Comber

    (2020)
    100 Citations
  • Desirable streets: Using deviations in pedestrian trajectories to measure the value of the built environment

    Arianna Salazar Miranda;Zhuangyuan Fan;Fabio Duarte;Fabio Duarte;Carlo Ratti

    (2021)
    90 Citations
  • Global Building Morphology Indicators

    (2022)
    71 Citations

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Best Scientists Contributing to This Journal

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