Comparison of selected vegetation indices and determination of suitability for yield description on agricultural field

Abstract

Abstract. Vegetation indices, as a non-destructive and low-cost method, represent an effective approach to vegetation cover evaluation. The simple mathematical formulas used describe wide spectra of conditions (water and nutrition saturation, influence of topography). Remote sensing data are used to derive vegetation indices. Calculations are performed using specialized software when operating with particular bands of electromagnetic spectra. The results contribute to adjustment of current agricultural management that becomes more economically efficient while having lower negative impact on the environment. The paper deals with selected vegetation indices and examines their suitability for yield prediction. Study area was 11.5 ha agricultural plot in Praha-Ruzyně. The experiment was conducted on wheat (2005, 2011) and oat (2006, 2010) having spatially related yield data. The selected indices were derived from LANDSAT 5 imagery with 30 m spatial resolution using SW ENVI. Specific values were obtained using SW ArcGIS. Correlation analysis was conducted to examine the relation between particular VI and the yield data or the Topography Wetness Index. The results indicated relation between vegetation indices and yield in all cases. The Moisture Stress Index reached -0.835 in 2011 as the maximal value of the correlation coefficient, while the minimum was performed by value 0.495 of the Chlorophyll Vegetation Index in 2005. The analysis also indicated relation of the yield to the topographic conditions of the agricultural plot. The Simple Ratio Vegetation Index in 2010 had the strongest correlation with the Topography Wetness Index, the correlation coefficient reached 0,6. Conversely, the minimal value was observed by the Chlorophyll Vegetation Index in 2005, namely 0.19. The Normalized Difference Vegetation Index, as the last of the selected indices, showed average results. Nevertheless, the data were evaluated in terms of the weather conditions as well. The influence of temperature and precipitation in particular growth stages was discussed. At the end, the conclusion was drawn that selected vegetation indices are suitable to describe the yield despite the fact they were derived from 30 m spatial resolution imagery.Keywords: yield, remote sensing, LANDSAT 5, spatial resolution. IntroductionThe fact about increasing world population is generally known. While there were 7.3 billion citizens in 2015, the latest estimates predict to be 8.5 billion citizens in 2030 and 11.2 billion in 2100 [1]. Related to this the question sustainability becomes even more actual. The demand for quality resources is increasing, while the space for production remains limited [2]. Sustainability of important resources must be therefore solved by changing the attitude and also by using new technologies to make the primary production more effective.Precision agriculture is an approach that is developing since about the last three decades. Modern technologies and latest knowledge are used to make agricultural management more economically effic...