Challenges and advances in the assessment of damaged agricultural land using remote sensing

Abstract

Background. Wartime hostilities have resulted in large areas of Ukrainian land becoming temporarily inaccessible, damaged, or mined, thereby challenging the validity of conventional land valuation approaches, notably the Normative Monetary Valuation (NMV). The current NMV framework is ill-suited for current realities, as it does not incorporate factors such as physical destruction, cratering, and the extent of soil degradation resulting from military operations and the use of missile weaponry. Consequently, an investigation into the relevance and effectiveness of the NMV under martial law is crucial for taxation and for planning the country’s reconstruction.

The purpose of the study is to identify challenges in the assessment of damaged land, to substantiate the methodology for its operational monitoring and classification based on remote sensing (RS) data, and to develop practical recommendations for improving the mechanisms of NM through the introduction of a correction coefficient. The object of the study is the system of Normative Monetary Valuation of land in Ukraine under martial law. The subject is the relevance, effectiveness and challenges of using NMV of land under martial law, as well as ways to improve it.

Methods. This study employs a comprehensive approach, including: a systematic and comparative analysis of the legal and regulatory framework, cartographic modeling, and spatial and statistical data analysis. The key methods were geographic information technologies (GIS) and analysis of satellite images (Planet Labs, Google Earth) for the identification, vectorization and spatial assessment of the affected areas.

Results. It was confirmed that remote sensing is the most effective tool fora large-scale and safe damage assessment, enabling to record craters. During the study, a classification of missiles was developed according to the degree of damage done to the ground. Four main levels of damage were established (Low, Medium, High, and Critical), which correlate with the crater's diameter and depth, as well as with the approximate percentage of soil productivity loss. The introduction of the “Land Suitability Coefficient” (LSC) as a mandatory corrective amendment to the current NMV formula was proposed and justified. It has been established that the LSC should incorporate both the area of damage and the coefficient of destruction intensity (D), obtained on the basis of the classification of remote sensing. Improving the NMV model by incorporating the LSC ensures increased objectivity of the assessment and its compliance with the actual ecological condition of the land, which is necessary for fair land taxation and compensation calculation.

Conclusions. The findings of the study demonstrate the critical need to reform land valuation relations in wartime through the integration of geospatial data. The proposed approach based on remote sensing and the implementation of the LSC is a practical solution that allows authorities and cadastral services to promptly account for losses and fairly regulate financial relations in the field management, thereby contributing to effective planning of the recovery of the agricultural sector.