A COMPUTATIONAL TOOL TO EVALUATE THE SAMPLE SIZE IN MAP POSITIONAL ACCURACY

In many countries, the positional accuracy control by points in Cartography or Spatial data corresponds to the comparison between sets of coordinates of well-defined points in relation to the same set of points from a more accurate source. Usually, each country determines a maximum number of points which could present error values above a pre-established threshold. In many cases, the standards define the sample size as 20 points, with no more consideration, and fix this threshold in 10% of the sample. However, the sampling dimension (n), considering the statistical risk, especially when the percentages of outliers are around 10%, can lead to a producer risk (to reject a good map) and a user risk (to accept a bad map). This article analyzes this issue and allows defining the sampling dimension considering the risk of the producer and of the user. As a tool, a program developed by us allows defining the sample size according to the risk that the producer / user can or wants to assume. This analysis uses 600 control points, each of them with a known error. We performed the simulations with a sample size of 20 points (n) and calculate the associated risk. Then we changed the value of (n), using smaller and larger sizes, calculating for each situation the associated risk both for the user and for the producer. The computer program developed draws the operational curves or risk curves, which considers three parameters: the number of control points; the number of iterations to create the curves; and the percentage of control points above the threshold, that can be the Brazilian standard or other parameters from different countries. Several graphs and tables are presented which were created with different parameters, leading to a better decision both for the user and for the producer, as well as to open possibilities for other simulations and researches in the future

Análise comparativa de Modelos Digitais de Elevação

Information on the topography is of great importance for the planning and execution of engineering works. The Digital Elevation Models represent an important source of data on the physiographic features of the terrain (natural or human-induced), and its applications cover various types of studies and knowledge areas. Moreover, the DEMs are also fundamental in models of geometric correction and orthorectification of images of Remote Sensing. The representations of relief from the altimetry data are conventionally obtained through topographic or directly by aerophotogrammetric restitution. In most cases requires the arduous task of digitizing the contour lines and elevation points for the generation of DEM's in mapping physiographic relief. The opportunity to easily get the DEM significantly reduces the burden of building these mappings. Given the above, the objective is to compare the potential of DEM's obtained from different sensors in the characterization of the relief Macaparana County, located in the Zona da Mata Norte de Pernambuco.Pages: 2324-233

Retificação de imagens através de curvas paramétricas

The photograph is a central projection such that, compared with the mapping that is a normal projection, presents deformation. The procedure defined as rectification only fixes the projective effect assuming that the relief effect is negligible thus transforms the image so that it results a second image as if it had been obtained from that axis in a vertical position. Adjusters local, known as parametric curves, are more practical, since changes in control points are not spread throughout the curve. This paper shows an iterative method that uses parametric curves with application in image correction resulting in an root mean square, between what is desired and the obtained, for various forms of deformation, in the order of 10-5.Pages: 2271-227

A COMPUTATIONAL TOOL TO EVALUATE THE SAMPLE SIZE IN MAP POSITIONAL ACCURACY

Abstract: In many countries, the positional accuracy control by points in Cartography or Spatial data corresponds to the comparison between sets of coordinates of well-defined points in relation to the same set of points from a more accurate source. Usually, each country determines a maximum number of points which could present error values above a pre-established threshold. In many cases, the standards define the sample size as 20 points, with no more consideration, and fix this threshold in 10% of the sample. However, the sampling dimension (n), considering the statistical risk, especially when the percentages of outliers are around 10%, can lead to a producer risk (to reject a good map) and a user risk (to accept a bad map). This article analyzes this issue and allows defining the sampling dimension considering the risk of the producer and of the user. As a tool, a program developed by us allows defining the sample size according to the risk that the producer / user can or wants to assume. This analysis uses 600 control points, each of them with a known error. We performed the simulations with a sample size of 20 points (n) and calculate the associated risk. Then we changed the value of (n), using smaller and larger sizes, calculating for each situation the associated risk both for the user and for the producer. The computer program developed draws the operational curves or risk curves, which considers three parameters: the number of control points; the number of iterations to create the curves; and the percentage of control points above the threshold, that can be the Brazilian standard or other parameters from different countries. Several graphs and tables are presented which were created with different parameters, leading to a better decision both for the user and for the producer, as well as to open possibilities for other simulations and researches in the future