Remote Sensing and Geographic Information System to Study the Dubas Bug Ommatissus lybicus de Bergevin Infestation in Oman

Abstract

<p>The Dubas bug <i>Ommatissus lybicus</i> de Bergevin is considered a serious pest affecting the productivity (quality and quantity) of the date palm <i>Phoenix dactylifera</i> Linnaeus, the main cultivated fruit crop in Oman and other Middle Eastern countries. The current study aimed to integrate modern technology, such as remote sensing (RS) and Geographic Information System (GIS), to study the <i>O. lybicus</i> infestation at multiple scales for potentially adapting these technologies in future research and in integrated pest management programs.</p> <p>High-resolution multispectral (MS) satellite image analysis results revealed that the reflectance decreased in the red edge and near-infrared (NIR) bands as the infestation level increased. The best vegetation indices that correlated with the <i>O. lybicus</i> were the Transformed Difference Vegetation Index (TDVI) and Tasselled Cap – Non-Such Index (TC-NSI) with correlation of <i>r</i>= −0.39. The overall accuracy of the supervised classification for detecting the infestation level was 68.3%, and the Kappa coefficient was 0.50. The study of identifying and counting the trees showed that a filter of 7-m window size was the best window to detect the date palm trees and had an overall estimation accuracy of 88.2%. The GWR model showed a good significant relationship between infestation and tree density in the spring season with <i>R²</i> = 0.59 and a medium significant relationship in the autumn season with <i>R²</i> = 0.30. The solar radiation showed a weak negative correlation between infestation and minimum solar radiation with the GWR model (<i>r²</i> = 0.28) and the OLS model (<i>r²</i> = 0.08, <i>p</i>< 0.05). The result of the microclimate vertical profile study showed the temperature increase from the ground level to the top levels with insignificant variance; however, the humidity decreased significantly. The result showed that the variance in the humidity vertical microclimate profile increases as the infestation decreases. The best models upon which to predicate DB infestation in relation to microclimate was mean daily accumulation of relative humidity (<i>R²</i> = 0.80), followed by daily minimum temperature (<i>R²</i> = 0.47). The regression of the most developed HTI was weak, and the highest correlation was found with HTI, computed from daily mean humidity and temperature. The results of the study examining the relationship of infestation with different environmental factors showed that the studied factors explained 61% of infestation variation with the GWR and only 50% with the OLS model. The percentage of side growing area, size of field area and distance to the nearest date palm field have a negative impact on infestation compared to all other factors.</p> <p>The research results suggest that RS is a potential technology to survey and locate <i>O. lybicus</i> infestation locations and to detect early infestation levels. The local maxima with a 7-m window approach was appropriate for date palm identification. Tree density had a positive impact on the <i>O. lybicus</i> population; however, solar radiation had a negative impact. High <i>O. lybicus</i> infestation was associated with humidity vertical profile constancy compared to the field significant variance in the vertical microclimate profile. The accumulation of daily temperature and humidity proved to be the best index that can be used to predict infestation. Spatial and temporal infestation was primarily due to the variation of the cultural practices and spatial characteristics of the date palm plantation’s environment.</p>