Engineering & Technologies 1 (2015 8) 133-140 ~ ~ ~ УДК 528.88:577.3 Assessment of Agroecosystem Productivity Based on Satellite Data and a Mathematical Model Tamara I. Pisman*, Irina Y. Botvich and Aleksander F. Sidko Institute of Biophysics of the Siberian Branch of RAS 50 Akademgorodok, Krasnoyarsk, 660050, Russia Received 04.12.2014, received in revised form 21.01.2015, accepted 03.02.2015 The possibility of determining seasonal dynamics of agroecosystem productivity was estimated based on the combined use of satellite data and results of a mathematical model study. <...> The study showed a qualitative agreement between normalized difference vegetation index (NDVI) and the total aboveground phytomass of the wheat and oat agroecosystem. <...> Analysis of the mathematical model proved the possibility of prediction and improvement of the crop yield estimate. <...> A distinction has been made between the vegetative and reproductive biomass of the agroecosystem. <...> Results of mathematical modeling were in good agreement with ground-truth data in the case of nutrient (nitrogen) limitation. <...> Keywords: agroecosystems, satellite remote sensing, a mathematical model, vegetative and reproductive biomass. <...> Отмечено качественное совпадение нормализованного вегетационного индекса (NDVI) и общей наземной фитомассы агроценоза. <...> All rights reserved * Corresponding author E-mail address: pech@ibp.ru # 133 # Tamara I. Pisman, Irina Y. Botvich… Assessment of Agroecosystem Productivity Based on Satellite Data… совпадение результатов математического моделирования с данными наземных исследований при лимитировании биогенным элементом (азотом). <...> Satellite methods, which are used in many countries, offer an effective way to resolve these problems [13]. <...> Satellite images may be used to facilitate collection of agricultural statistics, by enhancing the accuracy, uniformity, objectivity, and frequency of monitoring. <...> They help researchers improve methods of crop monitoring and forecasting on the local and global scales [4, 5]. <...> A number of studies have shown that the cumulative seasonal normalized difference vegetation index (NDVI) values were signifi cantly correlated with reported crop yields [6, 7]. <...> Doraiswamy and Cook [8] demonstrated that cumulative NDVI values for spring wheat during the grainfi ll period improved estimates of crop yields in North Dakota. <...> Moges et al. [9] analyzed correlations between normalized difference vegetative indices <...>