IMAGING ANALYSIS IN AGRICULTURAL LAND SURFACE CHARACTERIZATION - CASE STUDY ON WHEAT STUBBLE

Abstract

The study used imaging analysis (UAV images) to analyze and characterize an agricultural land area resulting from the harvest of the wheat crop. The researches were carried out in the framework of ARDS Lovrin, agricultural year 2021-2022. The agricultural land was worked with a disk, and the vegetable remains (straw, stubble) were partially incorporated into the soil. The images were taken with the drone (DJI Phantom 4) at variable heights, between H = 0.5 m and H = 50 m from the ground level (19 series of images from variable heights). The analysis of the images resulted in values in the RGB color system. Normalized values (rgb) and NDI and INT indices were calculated. The color parameter R (red) varied between R = 77.36 – 89.14±0.71, the color parameter G (green) varied between G = 71.29 – 81.99±0.60, and the color parameter B (blue) varied between B = 71.42 – 79.29±0.47. The values of the calculated indices varied between NDI = 0.040 – 0.048±0.0007, respectively INT = 73.357 – 83.217±0.582. Correlations of varying levels of intensity were recorded between color parameters, calculated indies and image retrieval height. High variability was recorded in the case of the NDI index (CV = 7.3156), and low value in the case of the normalized value g (CV = 0.4443). Polynomial equations described the variation of some color parameters in relation to the image retrieval height (p<0.001). The variation of the NDI index in relation to the image acquisition height was described by a spline model, under statistical safety conditions ( ). Associated with the image retrieval height, the NDI index presented four ranges of values, respectively uniform values on the 0.5 - 1 m height interval, and on the 25 - 50 m height interval; variation of 0.001 units on the height interval 2 - 8 m, and high variability on the height interval 9 - 20 m.