DEVELOPMENT OF A LINEAR REGRESSION MODEL BASED ON VEGETATION INDICES OF AGRICULTURAL CROPS
Journal Title: Scientific Journal of Astana IT University - Year 2023, Vol 15, Issue 15
Abstract
The article is devoted to the study of vegetation indices for assessing the productivity of agricultural crops of the North Kazakhstan Agricultural Experimental Station (NKAES) LLP. The research was carried out using a modern software package for processing satellite images, EOS Land Viewer. The work used images from the Landsat 8 (USA) and Sentitel 2 (European Space Agency) spacecraft. Digitized Earth remote sensing data for the last 3 years are presented, showing changes in the amount of moisture reserves on the territory of NKAES LLP. Time series of distribution of the studied coefficients were constructed according to different phases of active vegetation biomass in the study area. The resulting time series made it possible to identify annually repeating patterns, a linear trend of increasing and decreasing NDWI and NDVI on the territory of the NKAES LLP. Review of studies over the past 5 years, published in highly rated foreign journals, on various vegetation indices, including indices designed to assess moisture content in vegetation and soil. It is noted that the first normalized water index, NDWI, using the SWIR infrared channel, unlike the widely used NDVI vegetation index, actually penetrates 80% of the atmosphere. Analysis of the obtained NDWI allowed us to identify dry, moderately dry and fairly humid periods on the territory of the NKAES LPP from 2020 to 2023. Based on the research carried out, the feasibility of using normalized difference water indicators and normalized vegetation indices for further use in forecasting yields in the conditions of the North Kazakhstan region is substantiated. Next, using vegetation indices and additional agrometeorological factors, a linear model for predicting crop yields was developed. The coefficient of determination of the resulting model is 0.90 which indicates that the selected trend line reliably approximates the process under study.
Authors and Affiliations
Aigul Mimenbayeva, Azat Yessen, Aiman Nurbekova, Raya Suleimenova, Tleugaisha Ospanova, Akmaral Kasymova, Rozamgul Niyazova
Keywords
Related Articles
- EP ID EP723062
- DOI -
- Views 39
- Downloads 0
A MODEL OF AN AUTONOMOUS SMART LIGHTING SYSTEM USING SENSORS
Traditional street lighting systems receive data about daylight levels and adjust the lighting. However, in such conditions, energy consumption increases since the sensors of such systems receive data on only one indicat...
DETERMINATION OF THE MOST POLLUTED ATMOSPHERIC AIR POLLUTION CATEGORY OF ALMATY CITY
This article discusses the impact of suspended particles on human health, by providing small definitions of PM2.5, including how they appear, what particles they consist of, and how they harm the respiratory and circul...
SYSTEMATIC DATA PROCUREMENT IN AN OWL-EMBEDDED INFORMATION AND ANALYTICAL FRAMEWORK FOR THE MONITORING OF WATER RESOURCES IN THE ILE-BALKHASH BASIN
The world is facing an escalating water shortage crisis, with dire consequences for ecosystems, human health, and socio-economic development. This article explores the multifaceted nature of the water shortage problem of...
INFORMATION TECHNOLOGY OF INTEGRATED RISK MANAGEMENT OF SCIENTIFIC PROJECTS UNDER UNCERTAINTY AND BEHAVIORAL ECONOMY
The relevance of the topic is that currently the development of information technology allows to implement integrated risk management of scientific projects, which, in turn, expands the range of opportunities for projec...
MODEL OF POPULATION MIGRATION IN AGGLOMERATIONS WITHIN THE FRAMEWORK OF THE “SMART CITY” PARADIGM
The urban agglomeration is a multitude of united settlements according to economic, labor, cultural, household, and recreational characteristics. Agglomeration is perceived as an integral territorial union; therefore,...