An Analysis of an Area’s Vulnerability to the Emergence of Land-Use Conflicts

Cieślak, Iwona; Biłozor, Andrzej

doi:10.3390/land10111173

Cited by 4 publications

(3 citation statements)

References 56 publications

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“…Andonegi et al 2021;König et al 2021;St John et al 2021), and this is expected to increase due to the growing availability of relevant big data (Haslam 2020). However, the uni cation of indicator-driven results at a particular level of a certain scale is less commonly performed than, for instance, in the broader eld of land use con icts (Cieślak 2019;Cieślak and Biłozor 2021;Dong et al 2021). In the new conditions, we argue that a multiperspective assessment of the dataset and the entire process is required to maintain validity of multi-level PA con ict analysis.…”

Section: Introductionmentioning

confidence: 99%

Does secondary data suffice? Protected area conflict analysis in the era of the COVID-19 pandemic

Rechciński

Tusznio

Akhshik

et al. 2022

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The COVID-19 pandemic has affected an established way of analysing protected area (PA) conflicts. A compelled turn towards a broader use of secondary data evokes doubts about validity of the results unless restrictive assessment procedures are implemented. To address this need, we propose a three-fold (theory-, method-, and cross-scale simulation-driven) approach to assess usefulness of a state register dataset and a group of methods of the indicator analysis for recognizing PA conflict determinants at the regional and local level. With the ultimate aim to inform case study selection, we used 187 relevant indicators from the Polish Central Statistical Office register for a Lesser Poland region and processed them using principal component/exploratory factor and cluster analyses. We distinguished five types of PA conflict determinants in a region (‘urbanity’, ‘agriculture’, ‘tourism’, ‘small-scale entrepreneurship’ and ‘sprawl’) and respective groups of clusters comprising local-level units. Then, we selected one cluster to juxtapose the results with secondary data from another source (Internet content) for a specific PA. We confirmed that reported conflict issues corresponded with indicator-derived descriptors of the cluster. However, secondary data from the state register failed to address the key prerequisites of PA conflicts (parties’ interests and their mutual perception). Overall, our approach can serve as a proxy for a multi-level PA conflict determinant analysis in crisis conditions such as COVID-19, provided it synthesises the results of various methodological approaches, followed by in-person inquiries in the selected case studies.

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Section: Introductionmentioning

confidence: 99%

Does secondary data suffice? Protected area conflict analysis in the era of the COVID-19 pandemic

Rechciński

Tusznio

Akhshik

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…27 However, the uni cation of indicator-driven results at a particular level of a certain scale is less commonly performed than, for instance, in the broader eld of land use con icts. [28][29][30] In the new conditions, we argue that a multi-perspective assessment of the dataset and the entire process is required to maintain validity of multi-level PA con ict analysis.…”

Section: Introductionmentioning

confidence: 99%

Does secondary data suffice? Protected area conflict analysis in the era of the COVID-19 pandemic.

Rechciński

Tusznio

Akhshik

et al. 2022

Preprint

View full text Add to dashboard Cite

The COVID-19 pandemic has challenged protected area (PA) conflict analyses. A compelled shift towards broader use of secondary data evokes doubts about the validity of the results unless restrictive assessment procedures are implemented. To address this need, we propose a three-fold (theory-, method-, and cross-scale simulation-driven) approach to assess the usefulness of the utilized state register dataset and the indicator analysis methodology for the multi-level recognition of PA conflict determinants. With the ultimate aim to inform case study selection, we processed 187 relevant indicators from the Polish Central Statistical Office register for a Lesser Poland region. We distinguished five types of PA conflict determinants in Lesser Poland (‘urbanity’, ‘agriculture’, ‘tourism’, ‘small-scale entrepreneurship’, and ‘sprawl’) and respective groups of 15 clusters comprising local-level units. For one cluster we juxtaposed the obtained results with secondary data from another source (Internet content) and for a specific PA (Tatra National Park). Although the reported conflict issues corresponded with indicator-derived descriptors of the cluster, in the theory-driven phase of the assessment the state register failed to address the key prerequisites of PA conflicts. We proved that the proposed method can serve as a proxy for a multi-level PA conflict determinant analysis in crisis conditions such as COVID-19, provided it synthesizes the results of various methodological approaches, followed by in-person inquiries in the selected case studies.

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“…Analysis of susceptibility to land-use conflict aimed at developing a procedure for evaluating the risk of conflict in land management based on the specific attributes of land with the use of databases, GIS tools and statistical data-processing methods [7].…”

mentioning

confidence: 99%