Identification of rodents locations in fields for organization of protective measures in agronomy

<ns0:p>One of the main problems of the agricultural sector of Ukraine is the reduction of yields due to the impact of pests, in particular mouse-like rodents. According to experts, in Ukraine, annual crop losses from rodents can be up to 20% depending on the level of the pest population. Accordingly, damage to grain crops due to rodent activity in 2020 was estimated at over 1.2 million tons, which in financial terms is more than 400 million hryvnias (according to the Ministry of Agrarian Policy and Food of Ukraine). The results of the article are the preparation and analysis of data from monitoring the terrain relief to identify mounds created by rodents. Microrelief analysis and construction of its DBSCAN model using synthetic LiDAR data, clustering of anomalous elevations by the method and saving the results for further analysis using the R programming language.</ns0:p>

Publication Details

Journal
Energy and automation
Published
2025-08-28
DOI
https://doi.org/10.31548/energiya2(78).2025.158
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Identification of rodents locations in fields for organization of protective measures in agronomy

Energy and automation
Cell Image Analysis Techniques
article

Identification of rodents locations in fields for organization of protective measures in agronomy

article en

Abstract

<ns0:p>One of the main problems of the agricultural sector of Ukraine is the reduction of yields due to the impact of pests, in particular mouse-like rodents. According to experts, in Ukraine, annual crop losses from rodents can be up to 20% depending on the level of the pest population. Accordingly, damage to grain crops due to rodent activity in 2020 was estimated at over 1.2 million tons, which in financial terms is more than 400 million hryvnias (according to the Ministry of Agrarian Policy and Food of Ukraine). The results of the article are the preparation and analysis of data from monitoring the terrain relief to identify mounds created by rodents. Microrelief analysis and construction of its DBSCAN model using synthetic LiDAR data, clustering of anomalous elevations by the method and saving the results for further analysis using the R programming language.</ns0:p>

Energy and automation
Zero hunger
Openalex Percentile: Top 34%
Cell Image Analysis Techniques
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