Abstract
Badland reclamation and low productive farmlands always have been one of the most detrimental effects on the national economy, typically in agricultural sector of Uzbekistan. Nonetheless, such kind of lands has been used extensively for major crops like cotton and winter wheat. However, it is difficult to assessing real productivity of them. Advanced technologies as GIS and RS are vital tool for geospatially analysing and making decisions on this type of fields. This research was carried out for real-time crop monitoring and yield forecasting in case of low productive (3.5 ha) and high productive (8.3 ha) cotton areas of Jarkurgan district (Surkhandarya region, Uzbekistan) based on geospatial analyses of multi-temporal satellite images, condition of groundwater, soil salinity, and ground truth data. For monitoring vegetation phenology of cotton and forecasting its harvest, False Colour, NDVI (Normalized Difference Vegetation Index) and SI (Salinity Index) analyses of areas were carried out by using 6 temporal windows of multi-temporal Sentinel 2 from April through August 2019. Besides, groundwater condition data which was obtained from observation wells these located in massives consists of both cotton fields was analysed by IDW (Inverse Distance Weighting) interpolation algorithm method to determine groundwater’s effect to vegetation development and yield.
Highlights
Crop development monitoring and crop production estimate data is very important for all country in case of decision making on the food supply of the day-by-day growing population
From the models developed through the IDW interpolation algorithm (Figures 3A and 3B), it can be seen that in the research conducted low productive cotton field is located in 1.57-1.80 meters of groundwater levels and 1.40-1.60 g/l of groundwater mineralization part of massive
Taking into account the fact that the root of the cotton is the arrowroot and penetrates to a depth of 1.5-2.0 meters, the groundwater level is higher than the accepted norm and it was assumed that GW has a significant negative effect to cotton development
Summary
Crop development monitoring and crop production estimate data is very important for all country in case of decision making on the food supply of the day-by-day growing population. All major crop models including wheat, cotton, rice, maize etc., were calibrated for yield forecasting during initial to peak growing season and estimated near harvest time [3]. As well the quality and condition of irrigated lands are the main criteria affecting expected yields in the agricultural industry [4]. About 45% of the total irrigated agricultural lands of Uzbekistan are saline in various levels [5] and this indicator has a very high negative impact on the agricultural sector of the country
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