Mualliflar

  • Erkinova M.L

DOI:

https://doi.org/10.71337/inlibrary.uz.tinnint.112046

Kalit so‘zlar:

Key words: Land cadastre change bibliometric analysis research trends network analysis global research.

Annotasiya

Abstract 
 In this article, particularly the global research status of cadastre was evaluated 
by using bibliometric analysis. This article is based on the analysis of research topics, 
scientific production, collaboration among countries and authors. Furthermore, most 
cited papers on cadastre research which obtained from database of Scopus during the 
time period from 2012 to 2023. Land use changes, as a practical and advanced space 
exploration technology, offered a lot of valuable data about the earth surface for global 
analysis.  This  study  is  concentrated  on  the  analysis  of  scientific  outputs,  research 
directions, source journals, author performance and their contribution, the distribution 
of  research  countries/territories  as  well  as  institutions  and  their  collaboration  and 
temporal trends in keywords usage.  


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BASIC GLOBAL RESEARCH TRENDS ON CADASTRE: A

BIBLIOMETRIC ANALYSIS (2014-2018)

Erkinova M.L

Assistant Professor, Karshi

State Technical University

Erkinova@uzdavyerloyiha.uz

Abstract

In this article, particularly the global research status of cadastre was evaluated

by using bibliometric analysis. This article is based on the analysis of research topics,
scientific production, collaboration among countries and authors. Furthermore, most
cited papers on cadastre research which obtained from database of Scopus during the
time period from 2012 to 2023. Land use changes, as a practical and advanced space
exploration technology, offered a lot of valuable data about the earth surface for global
analysis. This study is concentrated on the analysis of scientific outputs, research
directions, source journals, author performance and their contribution, the distribution
of research countries/territories as well as institutions and their collaboration and
temporal trends in keywords usage.

Key words:

Land cadastre change, bibliometric analysis, research trends,

network analysis, global, research.

Introduction

The key to understanding the development of modern cadastre is realizing the

importance of cadastres in the relationship between humankind and land. With the
advent of the digital age, the field of cadastral research has developed through
innovations in land management and ownership based on land parcels (2D) and floor
plans (3D).(1-5). Owning to information and communication technology (LCT)
advancements, cadastral research has advanced through collaboration with other fields.
(6-7).(Zhichkin et al., 2020a) Research shows that the development of cadastral
research is strongly correlated with the adaptation of advancements in the information
and communication industry in developing countries.(8).In particular, the scope of
cadastral research has been enlarged from laws and systems to include geographical-
spatial information using new technologies and services. With the help of technological
developments, this has changed the previously government-friendly role.(Klimova et
al., 2021a)

2.Methodology

In this paper, bibliometric and literature analyses were adopted

to explore land cadastre analysis at agriculture. More than four hundread Scopus


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indexed documents were retrieved and analyzed using the Scopus database online tool.
Many studies that used this database alone were found in the literature (Malanski et al.,
2021; Neelam & Sood, 2020; Sun & Yuan, 2020; Karmaoui, 2022a and 2022b; and
Karmaoui et al., 2021a). (Zhichkin et al., 2020b)This method allowed exploring the
most pertinent and updated studies in land cadastre exploring the most influential
authors, countries, affiliations, and funding agencies. Six key terms were used and are
formulated as processed by the Scopus tool: “((Land AND land cadastre) AND (in
register AND land accaunting AND analysis)) AND (for AND agriculture)”.(Zhichkin
et al., 2022) This research produced 400 document results (Fig. 1). To explore the most
relevant publications, only the first 2000 papers of the period 2013–2022 were
retrieved (2013 is the year with available publications in the field using the
abovementioned keywords). The extracted data is exported in CSV excel (It can be
also exported using text. file) including information, such as citation, abstract,
keywords, authors and their countries, affiliations, year of publication, funding details,
type of publication, and citation. This exported data was processed using specialized
software, the VOSViewer, to calculate the occurrence, the links, and trends of key
terms.(Zhichkin et al., 2020b)

Bibliometric analysis

In this step, the main types of analysis available in the software were carried-

out, co-occurrence, co-authorship, and citations. For each sort, the three existing
categories of visualization were processed: network visualization, density, and trends.
Classification of the key terms following their meanings (Klimova et al., 2021b)This
classification aims to highlight more details and identify more aspect not provided by
VOSviewer. This software allows classification of the key-terms in not named clusters
but only linked statistically while the proposed classification is based on the
organization of these words using their meanings. For example, all the key terms that
comp For example, all the key terms that comprise “cadastre” will be gathered and
classified based on their occurrence and link. (Bičík et al., 2015)This allows to include
the key terms: land cadastre,water cadastre, forest cadastre, environmental cadastre,
cadastre handling, cadstre data acquisition, data fusion, database, metadata, open data,
data visualization, and cadastre data integration in one single category. (Kijowska-
Strugała et al., 2018)This categorization method was used, cadastre vocabulary,
cadastre register approaches, used tools, agricultural components, management aspect,
space vocabulary, resources, geographic information aspect, methods, and
Mathematics and computer science. Further analysis was performed to highlight and
discuss examples of studies using Cadastre particularly for agricultural suitability,
agricultural productivity, and for cropping pattern analysis.(Cho, 2022)

Scopus database

From 2012 to 2024 (1998 papers)

Selected years

Research base


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Figure 1. Methodology flowchart for the research

In this flowchart, the issues researched in this article are presented in an orderly

and systematic way according to the following 6 directions. These are research base,
selected years, language, subject area, key words, statistical analysis.

Results and Discussion.

Temporal Evolution of Annual Publications After the

first publication in SCI-E database in 2012, the annual output of research on cadastre
in Russian increased exponentially (Figure 2) with an average annual growth rate of
9.45%. Specifically, we divided the annual output into three rising periods: 1) ready-
to-grow period: steady with slight rising from 2012 to 2024 with 58 publications
totally; 2) steady growth period: publications were risen to 563 during 2001–2010, with
an average annual growth rate of 87%; 3) explosive growth period: there were 1,957
publications from 2012 to 2020, with nearly 200 papers published per year.(Khadanga
and Jain, 2020) The remarkable growth occurred after 2012, during which time 71.8%
of the total outputs were published.

Figure 2. In this figure 2, the scientists who have conducted the most research in the

filed of cadastre in the world are cited in the range of increase and decrease. These

0

1

2

3

4

5

6

7

8

9

Earth and Planetary, Environmental and Agricultural Science

“cadastre”

Microsoft Excel

Document types, years, authors, countries, sources, subject

areas, funding sponsors and affiliations of published papers

English

VOSviewer

Co-authors, keywords

Language

Subject area

Key words

Statistical analysis


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are the following scholars: Podhrazska J, Janus J, Slamova M, Zahichkina L, Bozek

P, Kour-Bera K, Nosov V, szturc J, Kavasek P.

Figure 4. In this figure 4 show about cadastre researching types, for example: article,

Conference paper, book chapter, review, conference rewiew, book, erratum, note.

Among them, the article holds the highest index.

This might be explained that researchers started to pay more attention to

scientific research on deserts in this period, leading to a synchronous growth between
outputs and citations under the circumstance that a relative small number of
publications exists. (Mekush et al., 2021)The remarkable decrease in citations occurred
after 2004, whereas annual production of publications increased rapidly during this
period.

0

50

100

150

200

250

300

350

0

1

2

3

4

5

6

7

8

9


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The output numbers are listed in parentheses. Frontiers in Earth Science |

www.frontiersin.org 4 November 2021 | Volume 9 | Article 777626 Shi et al.
Bibliometrics of Russian’s cadastre their influence as they are replaced by more recent
publications (Cimprič et al., 2013)Therefore, what should be noted is that our analysis
showed only the current citations of newly published papers and could not show their
peak number of citations. Altogether, because of the continuing growth of outputs in
cadastre research in Russian, it’s not surprising that the average number of citations
per output decreased graduall.

Conclusion.

Using a bibliometric method, our study was the first to analyze the

publications of the research done on deserts in Russian over the past 12 years. It
provided a qualitive and quantitative overview of the past work in this field, and
highlighted the future prospects. (Ilyushina et al., 2018)The results showed that the
three agricultural lands cadastre that were the most studied. About Land. The number
of publications produced annually increased exponentially, especially after 2012. This
growth coincided with the general trend in science across the world and in Russian In
addition, we predict that the number of annual publications will continuous to increase
in the next several years.

References

1.

Bičík, I., Kupková, L., Jeleček, L., Kabrda, J., Štych, P., Janoušek, Z.,
Winklerová, J., 2015. Land use changes in selected model areas, in: Springer
Geogr. Springer, pp. 171–193. https://doi.org/10.1007/978-3-319-17671-0_7

2.

Cho, S.G., 2022. Agriculture, in: Stud. Econimic His. Springer, pp. 287–372.
https://doi.org/10.1007/978-981-15-3874-2_7

3.

Cimprič, T., Lamovšek, A.Z., Lisec, A., 2013. An analysis of land development
tax for the conversion of agricultural land to urban use in Slovenia after 1979.
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Vestn.

57,

561–577.

https://doi.org/10.15292/geodetski-

vestnik.2013.03.561-577

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Demir, O., Inan, H.I., Biyik, C., Uzun, B., 2015. Land management for erosion
prevention: A case study for a Turkish nature reserve. Land Use Policy 47, 394–
400. https://doi.org/10.1016/j.landusepol.2015.01.036

5.

Ilyushina, T.V., Noszczyk, T., Hernik, J., 2018. Cadastral system in the Russian
federation after the modern transformation. Surv. Rev. 50, 437–446.
https://doi.org/10.1080/00396265.2017.1308700

6.

Khadanga, G., Jain, K., 2020. Agriculture Parcel Boundary Detection from
Remotely Sensed Images, in: Chaudhuri B.B., Chaudhuri B.B., Nakagawa M.,
Khanna P., Kumar S. (Eds.), Adv. Intell. Sys. Comput. Presented at the Advances
in Intelligent Systems and Computing, Springer Science and Business Media
Deutschland GmbH, pp. 307–312. https://doi.org/10.1007/978-981-32-9088-
4_26


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Ta'lim innovatsiyasi va integratsiyasi

https://scientific-jl.com

47-son_3-to’plam_Iyun -2025

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ISSN:3030-3621

7.

Khlystun, V.N., 2019. Development of Land Relations in the Agroindustrial
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Russ.

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89,

325–332.

https://doi.org/10.1134/S1019331619040038

8.

Kijowska-Strugała, M., Bucała-Hrabia, A., Demczuk, P., 2018. Long-term
impact of land use changes on soil erosion in an agricultural catchment (in the
Western Polish Carpathians). Land Degrad. Dev. 29, 1871–1884.
https://doi.org/10.1002/ldr.2936

9.

Tello, E., Badia-Miró, M., 2018. Land-use and rural inequality profiles in the
province of Barcelona in mid-nineteenth century. Hist. Agrar. 157–188.
https://doi.org/10.26882/histagrar.076e05b

10.

Yomralioglu, T., Cete, M., 2017. Cadastre or land administration: A case study
of Turkey, in: Cadastre: Geo-Information Innovations in Land Administration.
Springer International Publishing, pp. 23–31. https://doi.org/10.1007/978-3-319-
51216-7_3

11.

Zhichkin, K., Nosov, V., Lakomiak, A., Zhichkina, L., 2020a. Cadastral
valuation of lands dedicated to perennial plantings: Features and practice, in:
Apakashev R., Simisinov D., Glebov A. (Eds.), E3S Web Conf. Presented at the
E3S

Web

of

Conferences,

EDP

Sciences.

https://doi.org/10.1051/e3sconf/202017704002

12.

Zhichkin, K., Nosov, V., Zhichkina, L., Moiseeva, O., Denisova, I., Shapovalov,
N., 2022. Land Plots Clustering and Its Impact on the Agricultural Land Cadastral
Valuation, in: Beskopylny A., Shamtsyan M. (Eds.), Lect. Notes Networks Syst.
Presented at the Lecture Notes in Networks and Systems,

Bibliografik manbalar

References

Bičík, I., Kupková, L., Jeleček, L., Kabrda, J., Štych, P., Janoušek, Z.,

Winklerová, J., 2015. Land use changes in selected model areas, in: Springer

Geogr. Springer, pp. 171–193. https://doi.org/10.1007/978-3-319-17671-0_7

Cho, S.G., 2022. Agriculture, in: Stud. Econimic His. Springer, pp. 287–372.

Cimprič, T., Lamovšek, A.Z., Lisec, A., 2013. An analysis of land development

tax for the conversion of agricultural land to urban use in Slovenia after 1979.

Geod. Vestn. 57, 561–577. https://doi.org/10.15292/geodetski-

vestnik.2013.03.561-577

Demir, O., Inan, H.I., Biyik, C., Uzun, B., 2015. Land management for erosion

prevention: A case study for a Turkish nature reserve. Land Use Policy 47, 394–

Ilyushina, T.V., Noszczyk, T., Hernik, J., 2018. Cadastral system in the Russian

federation after the modern transformation. Surv. Rev. 50, 437–446.

Khadanga, G., Jain, K., 2020. Agriculture Parcel Boundary Detection from

Remotely Sensed Images, in: Chaudhuri B.B., Chaudhuri B.B., Nakagawa M.,

Khanna P., Kumar S. (Eds.), Adv. Intell. Sys. Comput. Presented at the Advances

in Intelligent Systems and Computing, Springer Science and Business Media

Deutschland GmbH, pp. 307–312. https://doi.org/10.1007/978-981-32-9088-

_26

Khlystun, V.N., 2019. Development of Land Relations in the Agroindustrial

Complex. Her. Russ. Acad. Sci. 89, 325–332.

Kijowska-Strugała, M., Bucała-Hrabia, A., Demczuk, P., 2018. Long-term

impact of land use changes on soil erosion in an agricultural catchment (in the

Western Polish Carpathians). Land Degrad. Dev. 29, 1871–1884.

Tello, E., Badia-Miró, M., 2018. Land-use and rural inequality profiles in the

province of Barcelona in mid-nineteenth century. Hist. Agrar. 157–188.

Yomralioglu, T., Cete, M., 2017. Cadastre or land administration: A case study

of Turkey, in: Cadastre: Geo-Information Innovations in Land Administration.

Springer International Publishing, pp. 23–31. https://doi.org/10.1007/978-3-319-

-7_3

Zhichkin, K., Nosov, V., Lakomiak, A., Zhichkina, L., 2020a. Cadastral

valuation of lands dedicated to perennial plantings: Features and practice, in:

Apakashev R., Simisinov D., Glebov A. (Eds.), E3S Web Conf. Presented at the

E3S Web of Conferences, EDP Sciences.

Zhichkin, K., Nosov, V., Zhichkina, L., Moiseeva, O., Denisova, I., Shapovalov,

N., 2022. Land Plots Clustering and Its Impact on the Agricultural Land Cadastral

Valuation, in: Beskopylny A., Shamtsyan M. (Eds.), Lect. Notes Networks Syst.

Presented at the Lecture Notes in Networks and Systems,