Geo-Spatial Information Science

Top Research Topics at Geo-spatial Information Science?

The aim of the journal is to expand the discussion of research in Artificial intelligence, Remote sensing, Data mining, Computer vision and Global Positioning System. The studies tackled, which mainly focus on Artificial intelligence, apply to Pattern recognition as well. Geo-spatial Information Science dives deep in exploring the relationship between the study of Remote sensing and Satellite.

Most of the works presented in the journal deals with Data mining but it intersects with the subject of Spatial analysis. The work tackled in Geo-spatial Information Science goes beyond the discipline of Global Positioning System as it also encompasses Geodesy.

• Artificial intelligence (17.59%)
• Remote sensing (14.97%)
• Data mining (13.27%)

What are the most cited papers published in the journal?

• Earth observation in service of the 2030 Agenda for Sustainable Development (151 citations)
• The GWmodel R package: further topics for exploring spatial heterogeneity using geographically weighted models (126 citations)
• A survey on vision-based UAV navigation (101 citations)

Research areas of the most cited articles at Geo-spatial Information Science:

The journal articles mostly deal with topics like Artificial intelligence, Remote sensing, Hydrology, Data mining and Land use. The journal publications deal with Artificial intelligence in conjunction with Pattern recognition and similar fields in Kernel (image processing). Issues in Remote sensing were discussed in the journal publications, taking into consideration concepts from other disciplines like Data processing, Satellite and Urban area.

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

• Artificial intelligence
• Statistics
• Machine learning

The previous edition focused in particular on these issues:

The journal mostly deals with topics like Remote sensing (archaeology), Remote sensing, Photogrammetry, Artificial intelligence and China. The studies on Remote sensing (archaeology) discussed can also contribute to research in the domains of Environmental planning, Cadastre, Social media, Estimation and Food security. Topics in Remote sensing explored in the journal were investigated in conjunction with research in Satellite technology, Satellite constellation and Earth observation system.

Geo-spatial Information Science investigates Artificial intelligence research which frequently intersects with Computer vision. It explores research in Graph model and overlapping concepts in Point cloud to expand the discourse in Computer vision. While work presented in it provided substantial information on China, it also covered topics in Climatology and Order (business).

The most cited articles from the last journal are:

• Urban sprawl and its impact on sustainable urban development: a combination of remote sensing and social media data (16 citations)
• China’s high-resolution optical remote sensing satellites and their mapping applications (8 citations)
• Advances in spaceborne hyperspectral remote sensing in China (5 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.

Top authors and change over time

The top authors publishing in Geo-spatial Information Science (based on the number of publications) are:

• Li Deren (32 papers) absent at the last edition,
• Gong Jianya (29 papers) absent at the last edition,
• Liu Jingnan (19 papers) absent at the last edition,
• Deren Li (15 papers) published 7 papers at the last edition, 6 more than at the previous edition,
• Wenbin Shen (15 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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Geo-spatial Information Science (based on the number of publications) are:

• Wuhan University (384 papers) published 17 papers at the last edition, 12 more than at the previous edition,
• Chinese Academy of Sciences (42 papers) published 1 paper at the last edition the same number as at the previous edition,
• Huazhong University of Science and Technology (18 papers) absent at the last edition,
• Hong Kong Polytechnic University (14 papers) published 1 paper at the last edition,
• The Chinese University of Hong Kong (13 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 2021 edition, 7.41% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 38.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 10.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 16.00% of all publications and 36.00% 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.

Career Opportunities in Geo-spatial Information Science

One aspect that the article could delve deeper into is the career opportunities available to those with a degree or knowledge in Geo-spatial Information Science. A better understanding of potential career paths could be of interest to those considering starting or continuing studies in this field and wanting to know about job prospects. Geo-spatial Information Science is a vast area, with potential career paths in both the public and private sector. Depending on your interest areas within Geo-spatial Information Science, you could consider roles such as a geo-spacial analyst, cartographer, GIS developer, or surveyor. While most of these roles can be found in various industries, education is another sector where such knowledge can be harnessed. For instance, in certain states like West Virginia, a background in Geo-spatial Information Science could lead to a teaching role in private schools, offering students a new perspective on geography, technology, and data interpretation. Establishing a career as an educator in the private sector might require specific requisites. If you're wondering "do private school teachers need a degree in West Virginia", an exploration of the regulations and requirements for that particular state might prove beneficial. In conclusion, having a background in Geo-spatial Information Science opens up a plethora of opportunities across various sectors, making it a worthwhile field of study.