18 research outputs found
DIGITALIZATION OF PROJECT MANAGEMENT IN UZBEKISTAN AND FOREIGN EXPERIENCE
No full textThe article discusses project management in the digital economy, implying the use of well-known and widely used in modern technologies methods and tools such as the use of Artificial Intelligence (AI), the use of cloud tools and flexible methodologies for planning, execution and control of projects related to the digitalization of business, IT development, creation of digital infrastructure and the provision of online services
Achievements And Problems in Further Development of The Digital Economy in UzbekistanScientific Considerations
No full textIn the 21st century, digital technologies and innovative business models cover all spheres of society's life and improve structural changes in the quality of economic activity. As a result, the digital economy, characterized by the active use of digital technologies and the circulation of unique digital information, is passing its judgment as a separate mechanism of the traditional economy. Today, when science and information-communication and digital technologies are developing rapidly, digital technologies are used in the developed countries of the world in public and social management, economy, industry, social protection, education, medicine, employment, agriculture, defense, security, tourism and other fields. and the widespread use of artificial intelligence capabilities is being taken as a model. The level of development of the digital economy is directly related to the competitiveness of each country, requiring countries to pay special attention to its development. Digitization is applied to social processes, and the advanced achievements of the information society depend on it. Uzbekistan does not take the leading place in the world in terms of the level of development of the digital economy, but it is increasing its position in this field year by year
Framework for agricultural performance assessment based on MODIS multitemporal data
No full textWe present a hierarchical classification framework for automated detection and
mapping of spatial patterns of agricultural performance using satellite-based Earth observation
data exemplified for the Aral Sea Basin (ASB) in Central Asia. The core element of the framework
is the derivation of a composite agricultural performance index which is composed of
different subindicators taking into account cropping intensity, crop diversity, crop rotations, fallow
land frequency, land utilization, water use efficiency, and water availability.We derive these
subindicators from net primary productivity and evapotranspiration data obtained from the
MODIS sensor on board the Terra satellite during the observation period from 2000 to 2016,
as well as from cropland maps created through multiannual classification of normalized difference
vegetation index (NDVI). We classified pixel-based NDVI time series covering more than
8 × 106 ha of irrigated cropland based on a hierarchical approach concatenating unsupervised
and supervised classification techniques to automatically generate and refine training labels,
which are then used to train a decision fusion classifier, achieving an average overall accuracy
of 78%. The results give unprecedented insights into spatial patterns of agricultural performance
in the ASB. The proposed method is transferable and applicable for global-scale mapping, and
the results of this remote sensing-aided assessment can provide important information for
regional agricultural planning purposes
Controlled Subsurface Drainage as a Strategy for Improved Water Management in Irrigated Agriculture of Uzbekistan
No full textPerformance evaluation of the BUDGET model in simulating cotton and wheat yield and soil moisture in Fergana valley
No full textCotton (Gossypium hirsutum L.) and wheat (Triticum aestivum L.) are major crops grown in Uzbekistan and water shortage is considered as the main limiting factor for crop growth as well as sustainable economic development. The objective of this study was to adapt and test the ability of the soil water balance model BUDGET (ver. 6.2) to simulate cotton as well as wheat yield and soil water content under current agronomic practices in the Fergana Valley. Crop yield and soil moisture content data, collected and measured from sites in 2010 and 2011, were compared with model simulations. Results showed that the BUDGET can be used to predict cotton yield and soil water content with acceptable accuracy using the minimum approach. However, predicted wheat yield was high compared to the observed and reported yield. Overall, relationship between the observed and predicted cotton and wheat yield for both sites combined produced R2 of 0.91 and 0.15, RMSE of 0.24 and 1.64 t ha−1, relative Nash-Sutcliffe efficiency (Erel) of 0.71 and -5.68 and index of agreement (d) of 0.48 and -0.54, respectively. Similarly, comparison of the observed and simulated soil moisture contents at the top 0-30 cm soil layer and soil water contents in 90 cm profile yielded R2 of 0.88 and 0.71-0.88, RMSE of 2.74 %vol. and 21.4-28.7 mm, Erel of 0.87 and 0.53-0.81, respectively and d around 1.0. Consequently, the BUDGET can be a valuable tool for simulating both cotton yield and soil water content, particularly considering the fact that the model requires relatively minimal input data. Predicted soil water balance can be used to improve current practice of irrigation water management, whereas simulated soil moisture content can be used to estimate capillary rise from groundwater in the UPFLOW model. However, performance of the model has to be evaluated under a wider range of agro-climatic and soil conditions in the future
STATE REGULATION OF THE DIGITAL TRANSFORMATION OF THE ECONOMY
No full textThe digital transformation of society in the country, having formed the necessary basis for ensuring technological sovereignty, requires the executive and legislative authorities to accelerate the comprehensive regulatory support of state policy in this area. The state policy of digital transformation of Uzbekistan and its regulatory support are focused on the best world practices, claim to be an integrated approach, but a number of problems still remain: insufficient consistency, high volatility of the legal sector, insufficient development of technical regulation, the presence of contradictions in legislation, standards and technical regulations. The regulatory and legal framework for the digital transformation of business models in the economy of the republic, despite the measures taken, has not yet been formed at a level sufficient to solve the tasks set, which retains a number of barriers to digital development
Monitoring biophysical parameters of irrigated rice production in the lowlands of the Aral Sea Basin from space
No full textRice production in the lowlands of the Aral Sea Basin (ASB) contributes to the national food baskets of Kazakhstan and Uzbekistan. However, due to the exposure to water scarcity in the downstream location of the river systems and enormous land degradation problems, a high risk of crop failure exist. Early and area-wide information on irregularities in rice crop growth through remote sensing could help to reduce this risk. In this study, statistical relations between vegetation indices (VIs) from Landsat 8 surface reflectance and biophysical in situ measurements (plant height, crop density, green biomass, fraction of absorbed photosynthetically active radiation and leaf area index) of broadcast sown and transplanted rice were investigated. Special attention laid on the accurate derivation of the LAI. Field experiments conducted in three different irrigation subsystems of the ASB during the growing period of rice in 2015 revealed enormous spatial variations in observed rice biophysical parameters, both among the fields and sites owing to different land, water and crop management. Linear regression analysis techniques of paired variables comprising each one biophysical parameter and one out of six VIs showed diverse coefficients of determination. Tasseled Cap Greenness (TCG) was superior to all other indices in its explanatory power. Multivariate linear regression and particularly Classification and Regression Trees exhibited stronger statistical relations between four VIs (TCG, Normalized Difference Vegetation Index - NDVI, Transformed Vegetation Index - TVI and Green Chlorophyll Index - GCI) and LAI than the univariate assessments. The multi-location field experiments can be concluded to be useful for estimating certain effects of crop management on modeling biophysical parameters of rice. The results suggest furthering multivariate assessments of rice biophysical parameters and promoting remote sensing techniques to support local and regional policies and planning approaches in the irrigated lowland of the ASB
PERFORMANCE EVALUATION OF THE BUDGET MODEL IN SIMULATING COTTON AND WHEAT YIELD AND SOIL MOISTURE IN FERGANA VALLEY
No full textCotton (Gossypium hirsutum L.) and wheat (Triticum aestivum L.) are major crops grown in Uzbekistan and water shortage is considered as the main limiting factor for crop growth as well as sustainable economic development. The objective of this study was to adapt and test the ability of the soil water balance model BUDGET (ver. 6.2) to simulate cotton as well as wheat yield and soil water content under current agronomic practices in the Fergana Valley. Crop yield and soil moisture content data, collected and measured from sites in 2010 and 2011, were compared with model simulations. Results showed that the BUDGET can be used to predict cotton yield and soil water content with acceptable accuracy using the minimum approach. However, predicted wheat yield was high compared to the observed and reported yield. Overall, relationship between the observed and predicted cotton and wheat yield for both sites combined produced R² of 0.91 and 0.15, RMSE of 0.24 and 1.64 t ha-1, relative Nash-Sutcliffe efficiency (Erel) of 0.71 and -5.68 and index of agreement (d) of 0.48 and -0.54, respectively. Similarly, comparison of the observed and simulated soil moisture contents at the top 0-30 cm soil layer and soil water contents in 90 cm profile yielded R² of 0.88 and 0.71-0.88, RMSE of 2.74 %vol. and 21.4-28.7 mm, Erel of 0.87 and 0.53-0.81, respectively and d around 1.0. Consequently, the BUDGET can be a valuable tool for simulating both cotton yield and soil water content, particularly considering the fact that the model requires relatively minimal input data. Predicted soil water balance can be used to improve current practice of irrigation water management, whereas simulated soil moisture content can be used to estimate capillary rise from groundwater in the UPFLOW model. However, performance of the model has to be evaluated under a wider range of agro-climatic and soil conditions in the future
Geodatabase and atlas: Kyzylorda Region, Kazakhstan
No full textThis product highlights the collaborative efforts undertaken to develop a comprehensive geodatabase and atlas for the Kyzylorda Region, Kazakhstan. It encapsulates spatial data, analyses, and knowledge products aimed at addressing the challenges posed by arid climate conditions, water resource scarcity, and sustainable regional development. Utilizing modern tools like GIS, remote sensing, and climate modeling, this activity provides decision-makers with actionable insights for improving water use efficiency, land management, and ecological resilience in the region
Geodatabase and atlas: Khorezm Province, Uzbekistan
No full textThis product highlights the collaborative efforts undertaken to develop a comprehensive geodatabase and atlas for the Khorezm Province, Uzbekistan. It encapsulates spatial data, analyses, and knowledge products aimed at addressing the challenges posed by arid climate conditions, water resource scarcity, and sustainable regional development. Utilizing modern tools like GIS, remote sensing, and climate modeling, this activity provides decision-makers with actionable insights for improving water use efficiency, land management, and ecological resilience in the region
