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Record W4405035103 · doi:10.26565/2075-1893-2023-37-01

Monitoring of land use by Ukrainian territorial communities in the conditions of martial law

2023· article· en· W4405035103 on OpenAlexaboutno aff
Natalia Bubyr, Yuliia Prasul, Dariia Bachurina

Bibliographic record

VenueGeographical Education and Cartography · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLand Use and Management
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianMartial lawPolitical scienceLawGeographyLinguisticsPolitics

Abstract

fetched live from OpenAlex

The purpose of this article. The purpose of the article is to show the importance and determine the priority directions for land use monitoring by Ukrainian territorial communities in the conditions of martial law, while giving some examples of practical implementation of these directions for Natalyne Territorial Community (TC) in Krasnohrad District, Kharkiv Region. The main material. The article considers theoretical and methodological foundations of land use monitoring in Ukraine in the conditions of martial law. It includes the impact of martial law on the legal regulation of land relations in Ukraine, analysis of foreign experience in solving land use problems affected by military aggression. We selected the land fund of Natalyne TC in Kharkiv region as a territory of experimental research based on historical experience, existing capabilities of GIS and remote sensing technologies. Analyzing current trends in the land use development within EU countries, we formulated priority directions for land use monitoring of Ukrainian territorial communities. There are some examples of practical implementation of these directions for Natalyne TC in Kharkiv region. In the conditions of martial law, the regulation of land relations in Ukraine underwent certain changes. These are: a) restrictions on free access to cartographic materials and services of the state land cadastre; b) a new regulation of certain land legal relations. This includes simplified transfer of unallocated agricultural land to be used in sowing campaign, exemption from liability for misuse of land in case of its involvement for country’ food security needs, etc.; c) adoption of some legislation caused by hostilities and/or their consequences, in particular , prohibition to change the purpose for former Kakhovka Reservoir lands. The historical experience of the world’s leading countries, such as Canada, Great Britain, Germany and France, proves that real-time monitoring of land pollution with military-man-made substances during hostilities can significantly speed up the process of post-war land restoration. Nowadays, the level of GIS and remote sensing development allows us to carry out this monitoring in a remote mode, using it even in areas of intensive military operations. A prerequisite for monitoring is the available database of land plots in GIS format, which are part of a given territorial unit (community, district) and adjacent territories. The remote monitoring process itself involves updating this database with data on bombing sites and other information, cartographic visualization of affected/potentially affected lands, etc. If there is safe environment, we can clarify the obtained data during field monitoring studies. In general,the proposed priority directions for land use monitoring of Ukrainian territorial communities in the conditions of martial law include: a) identification of hostilities and their consequences. This includes, in particular, presence of mines, delimitation of minefields, etc.; b) enhanced monitoring of critically important objects and places; c) verification of forest belts, hydrotechnical structures; d) monitoring of illegal land occupation, overgrowing and other manifestations of irrational land use; e) timely recording of misused land cases. We tested our theoretical propositions on the territory of Natalyne TC in Kharkiv region. Its land fund is typical for the Ukrainian steppe natural zone: 79% of it is agricultural land, significantly less (about 9%) is forestry land, residential and public land accounts for 2% of the community’s land fund, and other lands, including industrial, energy, transport, etc., 9%. The lands of the nature reserve fund (Martyniv and Petrivka reserves) and the lands of the Kobziv and Zakhidno -Sosnovsk gas condensate fields, need enhanced monitoring. Developed GIS database of Natalyne TC lands includes data about existing land use types within the community and adjacent territories, the location of gas wells, objects of the nature reserve fund. The total number of objects is more than 9000. During the monitoring, we added the places directly affected by hostilities and identified the manifestations of irrational land use. The collected data is the necessary basis (information support) for the post-war renewal of the community’s territory, based on the concept of sustainable development and the principles of rational land use. Conclusions and further research. The real-time land use monitoring of Ukrainian territorial communities in the conditions of martial law is caused by the necessity to timely record the impact of hostilities on their territory, to identify bombing sites, pollution with substances of military-man-made origin, which, as the experience of the world’s leading countries shows, will significantly speed up the process of post-war land restoration. At the same time, along with recording the impact of hostilities or its consequences, this monitoring should identify the manifestations of irrational land use, such as illegal land occupation, overgrowing, misuse of land, etc. A prerequisite for monitoring is the creation a database of land plots in GIS format on the communities’ territory and adjacent lands, which contains quantitative and qualitative characteristics of lands, areas (objects) that require enhanced monitoring, in particular, critical infrastructure facilities, places of storage for chemical and other hazardous substances. The monitoring itself is the update of this database with information on the impact of hostilities and its consequences. On this basis, we created a GIS database for Natalyne TC (Krasnohrad district of Kharkiv region) land resources. This GIS database contains more than 9,000 objects. In the future, this collected data will serve as a basis for the post-war renewal of the community’s territory. The prospective direction of our research is to categorize this database into two parts: 1) for official use by staff (in case of increasing cartographic data’s accuracy according to the requirements for land cadastral cartographic materials), 2) for public monitoring of the land use.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.319
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2023
Admission routes1
Has abstractyes

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