eng Oriental Scientific Publishing Company Biosciences Biotechnology Research Asia 0973-1245 2016-06-21 12 Spl.Edn.2 547 557 10.13005/bbra/2232 13100 article Saken Nurzhanuly Duisekov 1 Azimbai Otarov 2 Sagynbai Kaldybaevich Kaldybaev 3 Maksat Nurbaiuly Poshanov 4 Shakhislam Uzakbaevich Laiskhanov 5 Kazakh National Agrarian University, Abai ave. 8, 050010, Almaty city, Republic of Kazakhstan. 2U.U. Uspanov Kazakh Research Institute of Soil Sciences and Agricultural Chemistry, Al-Farabi ave. 75 B, 050060, Almaty city, Republic of Kazakhstan. 3Kazakh National Agrarian University, Abai ave. 8, 050010, Almaty city, Republic of Kazakhstan. U.U. Uspanov Kazakh Research Institute of Soil Sciences and Agricultural Chemistry, Al-Farabi ave. 75 B, 050060, Almaty city, Republic of Kazakhstan Al-Farabi Kazakh National University , Al-Farabi ave. 71, 050040, Almaty city, Republic of Kazakhstan. Nowadays, the use of satellite images and digital soil mapping techniques become increasingly important in soil studies. In the world practice, the use of space monitoring of soil salinity is currently one of the most topical areas of the soil science. In this regard, the main objective of this work is to develop an operational method for large-scale salt survey and to make the corresponding map of soil salinity based on the research of connection patterns between soil salinity levels and spectral properties of a satellite image, using the methods of space monitoring and digital soil mapping. The object of the study are soils of the southern part of the Akdalinsky irrigation array. The goal of the work is to develop an operational method of large-scale salt survey of soil based on the research of connection patterns between soil salinity levels and spectral properties of satellite images. This work is conducted with the use of both traditional ground-based and space methods of soil research. Based on the study on the connection between spectral properties of satellite images – vegetation indices and the ratio of the different bands QuickBird images and electrical conductivity of soils, we revealed the possibility of using these indicators as interpretive signs of soil salinity levels. At the same time, it was found that the tone of the image in separate bands of a QuickBird image is sufficiently informative to assess soil salinity; the most informative ratios appeared to be the ratios of the tones of individual shooting bands and vegetation indices. Using the ratio values of the image tone in different bands and the values of vegetation indices, we compiled regression equations between the value of electrical conductivity, measured in the field, and the spectral properties of different bands of a QuickBird image. Statistically reliable regression equations were obtained for barley and wheat crops. At the next stage, with the use of the obtained regression equations in the GIS environment, we charted a map of soil salinity under crops of barley and wheat. It should be noted that for alfalfa and rice crops, we failed to obtain statistically reliable regression equations that describe the dependence of the spectral properties of a QuickBird image with soil salinity and this is mainly due to the timing of satellite imagery. More careful selection of the shooting time, which may be the subject of research at the next stages of the works, can correct the situation. The main conclusion is that the success of the developed approach is largely predetermined by the timing of shooting and, accordingly, the timing of the field sample survey. https://www.biotech-asia.org/vol12_nospl_edn2/the-operational-method-of-conducting-large-scale-salt-survey-and-drawing-salinity-level-maps-of-irrigated-lands-of-the-akdalinsky-array/ Salinization; Satellite images; Vegetation indices; Decoding of satellite images; Soil salinity map