Methodology improvement for assessing the cadastral value of land plots in Republic of Kazakhstan

Introduction. The current methodology for assessing the cadastral value of agricultural land in the Republic of Kazakhstan requires modernization, taking into account market dynamics, inflationary processes, and agroecological characteristics. Soil fertility and territorial conditions must be considered to ensure a fair and transparent valuation. Purpose of the research. This study aims to develop and validate an improved methodology for determining the cadastral value of agricultural land using correction coefficients that reflect market conditions and soil quality (bonitet score). Materials and Methods. The study is based on the agricultural lands of the “Amir” farm in Katon-Karagay district, East Kazakhstan region. The research employed comparative analysis, normative base rate calculations, statistical methods, and cartographic and soil survey data. The methodology aligns with the Land Code of Kazakhstan, which allows a deviation of up to ±50% from the base land payment rates. Results. The cadastral value was calculated considering land location, water availability, soil types, and proximity to settlements. Correction coefficients were developed and tested, including factors for bonitet score and inflation. A bonitet rating scale was proposed to improve accuracy in valuation. Discussion. It was found that the current assessment methodology does not adequately reflect real soil characteristics or market realities. The implementation of correction factors leads to a more objective and reliable valuation system. Conclusion. The proposed method provides a fairer, more market-oriented approach to land valuation, suitable for Kazakhstan’s agricultural sector. Resume. The new methodology improves the accuracy of cadastral assessments and supports more informed land policy decisions. The approach may be applied by land management and tax authorities, as well as agricultural entities. Future research should focus on extending the model to other regions and integrating it into digital cadastral systems.