![]() ![]() The RMSE was obtained as a function of the difference between the reference coordinates and the observed coordinates, for the three axes (x, y, and z), as presented in Equations (1)–(3), respectively. The ASPRS PASDGD standard was used for the analysis of geospatial datasets based on the Root Mean Square Error (RMSE) statistic of the checkpoints. 3.5.2 was used to evaluate the horizontal and vertical accuracy, where the coordinate data of the 20 checkpoints (reference and test) in each area were inserted through a file (.txt). This was possible because the vegetation had low heights in the four areas (0.25 m in areas 1 and 2 with mostly bare soil and 0.05 m in areas 3 and 4 with patches of bare soil). The assessment of the positional accuracy of the orthophotomosaics and the altimetric accuracy of the DEMs was based on the Positional Accuracy Standards for Digital Geospatial Data (PASDGD) (ASPRS 2014), considering open terrain and areas without vegetation (NVA classification). Also, according to the author, the insertion of this information optimizes the resolution of the DEM, improving the quality of the generated product. According to Hutchinson, the “Topo to Raster” uses known information from surface elevation, such as elevation points (such as in this work), contour lines, and water body delimitations, among others. This interpolation algorithm is based on iterative finite differences to generate a regular grid from elevation points and/or contour lines ESRI. To perform these operations, the “Topo to Raster” interpolator was used. In the GIS environment, Digital Elevation Models were generated and then contour lines and slope maps were derived. 2.8.4.0, exporting the attributes spreadsheet in text format and the “.txt” extension to ArcGis V. The polygonal and topographic irradiation data were processed using the GeoOffice Topographic 2008 software v. We surveyed the 15 control points and 20 checkpoints implemented in the field, as reference for the processes inherent to the aerial photogrammetric survey by RPA and subsequent validation in the quality control stage. The topographic survey aimed to register the relief variations of the areas for the production of DEMs, contour lines, and topographic slope maps, as shown in Figure 4 and Figure 5. The Hausdorff distance analysis allowed us to conclude that contour planting can be performed from data obtained via Remotely Piloted Aircraft, provided that vertical accuracy analysis controls the quality of the Digital Elevation Models. We observed that the similarity between the contour lines from topography and RPA yielded slope differences lower than 6.1% for at least 95% of all studied areas. These adjustments correspond, respectively, to the segments between the contour lines with the best and the worst individual similarity for each area. Also, the lowest altimetric differences observed in the Digital Elevation Models were associated with the smallest Hausdorff distance. The results show that there was a better similarity among the contour lines in areas with a very rugged relief than in a smooth relief. The contour lines obtained by both techniques were superimposed and their similarity was verified using the Hausdorff distance. From the acquired field data for the studied areas, the Digital Elevation Models were generated with a spatial resolution of 0.20 m and the contour lines with an equidistance of one meter. Data were acquired through a conventional topographic survey and an aerial photogrammetric survey by Remotely Piloted Aircraft. This study was carried out in the period between January 2020 and November 2021 in four localities in the State of Rio de Janeiro, Brazil: two areas located in the municipality of Bom Jardim and two areas in the municipality of Seropédica. Thus, the objective of this work was to analyze the similarities between contour lines from topography and Remotely Piloted Aircraft, using the Hausdorff distance algorithm. Currently, geotechnologies can provide more precise and fast data from relief than rudimentary data acquisition for agricultural management. Contour planting minimizes soil degradation, making agricultural production more sustainable. ![]()
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