![]() ![]() The flights were performed at an altitude of 30 m in the central hours of the day, when the sun’s rays strike nearly perpendicular to the terrain, minimizing shadows that distort the spectral information. To address the potential issues of scale heterogeneity due to low-altitude flights and steep terrain, and to obtain the most accurate information possible, the flight routes were planned using UgCS PRO software. Four of the 12 circular plots were covered in each flight. ![]() Ī total of six drone flights (three flights for RGB and three for multispectral sensors) were made on May 2021, with a multicopter DJI Matrice 210 RTK V2 (Da-Jiang Innovations, Shenzhen, China). the pixel size of the information obtained from remote sensing. Most remote sensing studies have included field validations, although some appear to be biased due to the differences in the scale of the field sampling vs. Given these advantages, numerous studies have used spectral indices derived from remote sensing to estimate vegetation cover. Compared to traditional methods, remote sensing allows the estimation of vegetation condition over larger areas with greater accuracy and efficiency, optimizing the assessment of vegetation response to practices such as prescribed burning. In recent years, a wide variety of remote sensing satellites and sensors with different spatial, spectral, and temporal resolutions have been developed, providing high-quality spatial and temporal data at a range of scales. Rapid technological advances in remote sensing have enabled an increase in its application in numerous scientific disciplines related to natural resource assessment. These results suggest that in semi-arid environments, the drone might underestimate vegetation cover in low-cover shrublands. Diversity and slope did not affect the accuracy of the cover estimates, while errors were larger in plots with greater richness. This estimate varied between cover classes, with the error rate being higher in low-cover shrublands, and lower in high-cover alfa grass steppe (normalized RMSE 33% vs. The coverage estimated using a drone was strongly correlated with that obtained by vegetation sampling (R 2 = 0.81). We explored how this accuracy varies in different types of coverage (low-, moderate- and high-cover shrublands, and high-cover alfa grass steppe) as well as with diversity, plant richness, and topographic slope. ![]() We compared drone-based vegetation cover estimates with those based on traditional vegetation sampling in ninety-six 1 m 2 plots. In this study, we evaluated the accuracy of vegetation cover estimation by drones in Mediterranean semi-arid shrublands (Sierra de Filabres Almería southern Spain) after prescribed burns (2 years). The use of drones for vegetation monitoring allows the acquisition of large amounts of high spatial resolution data in a simple and fast way. ![]()
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