Use of remote sensing data to identify damage and contamination of agricultural land by explosive ordnance
DOI:
https://doi.org/10.17721/1728-2713.114.08Keywords:
remote sensing, PlanetScope, spectral analysis, spectral signatures, NDVI, BI, BCI spectral indicesAbstract
Background. Military operations in Ukraine have caused large-scale damage to the natural environment. Agricultural fields are among the most vulnerable components under wartime conditions, as they are affected by mechanical damage, unsafe soil cultivation, contamination with toxic substances, and subsequent loss of fertility. These negative processes pose a threat to food security due to the withdrawal of large areas of fertile land from agricultural use and the risk of producing crops contaminated with toxic substances. To develop a strategy for the restoration of land resources, it is necessary to carry out a quantitative assessment of the damage caused. Field surveys are undoubtedly the most accurate method for assessing soil condition; however, under current conditions, these would expose researchers to grave danger. Therefore, a much safer alternative is the application of remote methods, particularly GIS and remote sensing technologies.
Methods. The study was based on the use of multispectral PlanetScope satellite imagery and included spectral analysis, calculation of spectral indices, selection of threshold values, and detection of local anomalies to identify damaged agricultural land.
Results. The study was conducted within the Orikhiv territorial hromada of the Polohy district, Zaporizhzhia region. Particular attention was paid to the application of a semi-automated method for identifying the impact of military operations on agricultural land using GIS and remote sensing data. Potential shell impact sites were detected for the active vegetation period and the early autumn period, while pyrogenically damaged areas were identified separately. Based on the analysis, the potential area of damaged agricultural land was calculated.
Conclusions. The results confirm the feasibility of using the proposed methods to identify war-induced damage to agricultural land.
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