In modern agroecology, one of the most pressing problems is the problem of spatial data mapping. The development of information technology opens up a wide range of approaches for solving this problem. One of these approaches is based on the use of geostatistical methods. This study was carried out with the aim of developing ideas about the applicability of the ordinary kriging method for predicting the spatial distribution of the agro-ecological indicator with identifying the boundaries of in-field heterogeneity according to remote sensing data. For the model computational experiment, aerial photographs of the agricultural field in the red and near infrared ranges were used, which made it possible to obtain sets of uniformly distributed values of the vegetative index NDVI that were randomly generated. The high spatial resolution of the images allowed us to analyze the observational data for the studied agricultural field.
Перспективы использования данных дистанционного зондирования в оценке состояния мелиоративных систем и эффективности использования мелиорированных земель н. н. дубенок 1 , Ю. г. янко 2 , а. ф. петрушин 2 , р. в. калиниченко 1
A functional description of the hydrophysical properties of the soil as a capillary-porous medium is presented. The described functions of water retention capacity and hydraulic conductivity of the soil have common parameters, which are interpreted within the framework of physical and statistical concepts. The practical significance of the proposed functions lies in the fact that the volume of labor-intensive field measurements necessary, for example, for modeling the dynamics of soil moisture, is significantly reduced. To identify the parameters of these functions, it is sufficient to use data only on the water retention capacity of the soil. The parameters identified in this way can be used to predict the ratio of the hydraulic conductivity of the soil to the moisture filtration coefficient. The presented system of the hydrophysical functions of the soil is compared with world analogues using literature data on soils of different texture.
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