Application of GIS and RS in real time crop monitoring and yield forecasting: a case study of cotton fields in low and high productive farmlands

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.

The Use of Gis Technologies in the Management and Monitoring of Land Resources

“…Data Availability and Quality: The availability and quality of spatial data, such as satellite imagery, aerial photographs, and ground surveys, are crucial for GIS applications. Incomplete, outdated, or inaccurate data can limit the accuracy and reliability of GIS analyses and decision-making [2].…”

A Study of the Effects of Soil Salinity on the Growth and Development of Maize (Zea Mays L.) by using Sentinel-2 Imagery

“…Multifunctional satellite sensors (Multi-Scanner Sensor Landsat (MSS), TM, ETM, Thermal Infrared Distance (TIR), Operational Land Visualizer (OLI) -can cover all growing seasons of crops and allow you to explore vast territories (Chen et al, 2008;Satir and Berberoglu, 2016). Space data from the Sentinel-2 satellite contributed to medium and large-scale research (Mamatkulov et al, 2021). Also, SPOTHRV (Wiegand et al, 1996), Indian Remote Sensing Satellites 324 (IRS), Linear Imaging Self-Scanning System III (ÇULLU, 2003), Earth-Observing One (EO-1), Hyperion (Hamzeh et al, 2013) performed works with the use of information is encountered.…”

“…Several papers have been published in this direction. Soil salinity can be determined using remote sensing data (ÇULLU, 2003;Satir and Berberoglu, 2016;Mamatkulov et al, 2021) on wheat (ÇULLU, 2003;Zahra, 2012;Yousfi et al, 2016;Satir and Berberoglu, 2016), maize (Satir and Berberoglu, 2016;Feng et al, 2017;Bose et al, 2018), cane (Wiegand et al, 1996;Hamzeh et al, 2013), clover (Tian et al, 2020). Also, their impact has been conducted.…”

Land Suitability Assessment for Cotton Cultivation - A Case Study of Kumkurgan District, Uzbekistan

“…This challenge that cannot always be met results in n reduction of soil fertility of the valuable lands and the harvest yield year by year (Conrad, 2016, Khaitov et al, 2014and Wojtaszek et al, 2021. Application of spatial evaluation techniques including remote sensing (RS) and geo-information system (GIS) for land suitability assessment can an promising mean for crop placement management on irrigated agricultural lands in Uzbekistan (Halder, 2013 andMamatkulov et al, 2021). ISSN 2673-0014 (Online) / © Geoinformatics International Land suitability assessment is generally explained as evaluation of land performance in specified goal which should involve surveys and studies on soil, climate, topography, vegetation and other parameters of land in order to identify and classify applicability in use (FAO, 1976 andSteiner, 1987).…”