This article evaluates the effect of terrain morphometric parameters calculated from the digital elevation model (ASTER GDEM, 30 m) on the spatial variability of soil properties and the normalized difference vegetation index (NDVI) of a forb–oat mix. According to regression analysis, the morphometric parameters contribute 42% to the spatial variability of soil moisture; 59 and 46% to physical clay and humus content, respectively; and 86% to the NDVI of the oat-herb mixture. Indicators of moisture and physical clay and humus content in a plow layer of agro-grey soil of the transitional part of the slope are lower when compared with the alluvial part of the slope. In our opinion, this is a result of the development of erosional processes on the sloped terrain site, less favorable hydrothermal conditions, and human economic activities. The statistical relationships between soil properties and morphometric parameters of the terrain make it possible to build a predictive map of the soil properties.

The relationships between the morphometric parameters (MPs) of topography calculated on the basis of digital elevation model (АSTER GDEM, 30 m) and the properties of the plow layer of agrogray soils on a slope were analyzed. The contribution of MPs to the spatial variability of the soil moisture reached 42%; to the content of physical clay (<0.01 mm particles), 59%; to the humus content, 46%; to the total nitrogen content, 31%; to the content of nitrate nitrogen, 28%; to the content of mobile phosphorus, 40%; to the content of exchangeable potassium, 45%; to the content of exchangeable calcium, 67%; to the content of exchangeable magnesium, 40%; and to the soil pH, 42%. A comparative analysis of the plow layer within the eluvial and transitional parts of the slope was performed with the use of geomorphometric methods and digital soil mapping. The regression analysis showed statistically significant correlations between the properties of the plow layer and the MPs describing surface runoff, geometric forms of surface, and the soil temperature regime.

The informativeness of NDVI for predictive mapping of the physical and chemical properties of plow horizons of soils on different slope positions within the first (280–310 m a.s.l.) and second (240–280 m a.s.l.) altitudinal steps has been examined. This index is uninformative for mapping soil properties in small hollows, whose factual width is less than the Landsat image resolution (30 m). In regression models, NDVI index explains 52% of variance in the content of humus; 35 and 24% of variance in the contents of total and nitrate nitrogen; 19 and 29% of variance in the contents of total and available phosphorus; 25 and 50% of variance in the contents of exchangeable calcium and manganese; and 30 and 29% of variance in the contents of fine silt and soil water, respectively. On the basis of the models obtained, prognostic maps of the soil properties have been developed. Spatial distribution patterns of NDVI calculated from Landsat 8 images (30-m resolution) serve as the cartographic base and the main indicator of the soil properties. The NDVI values and the contents of humus, physical clay (<0.01 mm) and fine silt particles, total and nitrate nitrogen, total phosphorus, and exchangeable calcium and manganese in the soils of the first altitudinal step are higher than those in the soils of the second altitudinal step. An opposite tendency has been found for the available phosphorus content: in the soils of the second altitudinal step and the hollow, its content is higher than that in the soils of the first altitudinal step by 1.8 and 2.4 times, respectively. Differences in the pH of soil water suspensions, easily available phosphorus, and clay in the soils of the compared topographic positions (first and second altitudinal steps and the hollow) are statistically unreliable.

1. Материалы Всероссийской семинара «Современные информационные технологии для фундаментальных научных исследований РАН в области наук о Земле», 8–11 апреля 2010 г. Владивосток. URL: http://seminar2010.fegi.ru/. 2. Жижимов О. Л., Федотов А. М., Юданов Ф. Н. Модель управления информационными ресурсами организации // Вестн. Новосиб. гос. ун-та. 2010. Серия Информационные технологии. Т. 8, вып. 4. С. 81–95. 3. Шокин Ю. И., Пестунов И. А., Смирнов В. В., Синявский Ю. Н., Добротворский Д. И., Скачкова А. П. Корпоративная информационная система СО РАН сбора, хранения и обработки спутниковых данных // Горный информационно-аналитический бюллетень. 2009. Отдельный выпуск «Кузбасс 2». С. 3–10. 4. Пестунов И. А., Смирнов В. В., Жижимов О. Л., Синявский Ю. Н., Скачкова А. П., Дубров И. С. Каталог пространственных данных для решения задач регионального мониторинга // Вычислительные технологии. 2008. T. 13. Вестн. Казан. гос. ун-та. им. аль-Фараби. Серия: Математика, механика, информатика. 2008. № 4 (59). Совместный вып. по материалам Междунар. конф. «Вычислительные и информационные технологии в науке, технике и образовании». Ч. 3. С. 71–76. 5. Добротворский Д. И., Куликова Е. А., Пестунов И. А., Синявский Ю. Н. Веб-сервисы для непараметрической классификации спутниковых данных // Сб. матер. VI Междунар. научн. конгресса «ГЕО-Сибирь-2010». Новосибирск: СГГА, 2010. Т. 1, ч. 2. С. 171–175. 6. Жижимов О. Л., Мазов Н. А. Принципы построения распределенных информационных систем на основе протокола Z39.50. Новосибирск: ОИГГМ СО РАН; ИВТ СО РАН, 2004. 361 с. 7. ANSI/NISO Z39.50-2003. Information Retrieval (Z39.50): Application Service Definition and Protocol Specification // NISO Press, Bethesda, Maryland, U.S.A. 267 p. 8. Catalogue Interoperability Protocol (CIP) Specification – Release B // CEOS/WGISS/ICS/CIP-B, Is. 2.4.75. April 2005.