哈萨克斯坦农业数字化:区域经验

S. Pashkov, G. Mazhitova
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摘要

本文论述了农业数字化作为哈萨克斯坦作物生产集约化的决定性方向。实施数字化的主要条件是发展精准农业。我们的工作目的是研究哈萨克斯坦,特别是北哈萨克斯坦地区的农业数字化进程,这是最古老的雨养农业地区,在作物生产价值和雨养土地经济肥力方面处于领先地位。我们分析了国家计划(“哈萨克斯坦- 2050”、“数字哈萨克斯坦”)的主要条款,旨在将地理空间技术融入农业和作物生产,从而提高该行业的劳动生产率。在研究过程中,指出了卫星影像和无人机拍摄在精准农业中的特殊性;确定了阻碍在农业发展中引入数字技术的因素;对区域精准农业发展的环境和经济条件进行了SWOT分析。文章提出了该地区进一步发展农业数字化应采取的措施:创新(发展农业电力)和家长式(国家刺激农业形成等)。农业部门的数字化将基于高自然农业潜力和基于预测分析的先进地理空间技术,创建生态可持续的可编程农业系统。
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DIGITIZATION OF AGRICULTURE IN KAZAKHSTAN: REGIONAL EXPERIENCE
The article deals with digitization of agriculture as the determinative direction of crop production intensification in Kazakhstan. The main condition for the digitization to be implemented is the development of precision agriculture. The aim of our work is to study the process of agricultural digitization in Kazakhstan and particularly the North Kazakhstan region, which is the oldest territory of rainfed agriculture and the leading area in terms of crop production by value and in terms of economic fertility of rainfed land. We analyze the main provisions of state programs (‘Kazakhstan–2050’, ‘Digital Kazakhstan’) aimed at integrating geospatial technologies into farming and crop production, which is supposed to increase labor productivity in the industry. In the course of research, the peculiarities of using satellite imagery and shooting from unmanned aerial vehicles in precision agriculture were noted; factors that hinder the introduction of digital technologies in the development of agriculture were identified; SWOT analysis of environmental and economic conditions of the precision agriculture development in the region was carried out. The article proposes measures to be taken for further development of agricultural digitization in the region: both innovative (development of agrarian voltaics) and paternalistic ones (state stimulation of agrarian formations, etc.). The digitization of the agricultural sector will create econologically sustainable programmable system of farming based on high natural agricultural potential and advanced geospatial technologies resting on predictive analytics.
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