Abstract
Point-based standard methodologies (PBSM) suggest using ‘at least 20’ check points in order to assess the positional accuracy of a certain spatial dataset. However, the reason for decreasing the number of checkpoints to 20 is not elaborated upon in the original documents provided by the mapping agencies which develop these methodologies. By means of theoretical analysis and experimental tests, several authors and studies have demonstrated that this limited number of points is clearly insufficient. Using the point-based methodology for the automatic positional accuracy assessment of spatial data developed in our previous study Ruiz-Lendínez, et al (2017) and specifically, a subset of check points obtained from the application of this methodology to two urban spatial datasets, the variability of National Standard for Spatial Data Accuracy (NSSDA) estimations has been analyzed according to sample size. The results show that the variability of NSSDA estimations decreases when the number of check points increases, and also that these estimations have a tendency to underestimate accuracy. Finally, the graphical representation of the results can be employed in order to give some guidance on the recommended sample size when PBSMs are used.
Highlights
The position is the basis of mapping and navigation, which are essential for engineering, natural sciences, land management, etc
Regarding the behavior of the curve obtained, it presents a clear tendency, approaching the theoretical value when the sample size is increased. This curve can be employed in order to give some guidance on the recommended sample size when point-based standard methodologies (PBSM) are used, when automatic positional accuracy assessment (APAA) methods are used for evaluating the positional quality of urban geospatial database (GDB)
The use of a point-based procedure for the automatic positional accuracy assessment of spatial data has provided a population of errors large enough to extract samples with a range of sizes that allows us to analyze the variability of National Standard for Spatial Data Accuracy (NSSDA) results according to the conditions established in the aforementioned experiment
Summary
The position is the basis of mapping and navigation, which are essential for engineering, natural sciences, land management, etc. Positional quality is determined by positional accuracy [3] which, in turn, is evaluated by means of statistical methods based on measuring positional discrepancies between the location of “well-defined point entities” stored in a geospatial database (GDB) and their true (real world) location [1]. AAllll tthheessee PPBBSSMM aarree ddiiffffeerreenntt ffrroomm eeaacchh ootthheerr aanndd ggiivvee rreessuullttss iinn vvaarriieedd wwaayyss. [T1h6]e,swe ahpopsruogagcheests qaureanbtaisfyedinognththeepmoseitthioondaloaf cdceufrinacinygopf oasicteiortnaainl aGccDuBrabcyy mpreoapsousreindgbtyheGdoioffdecrehnilcdesanbedtwHeuenntethr e[1l6o]c,awtiohnossoufgsgpeasttiaqlueanntittiifeysinstgorthede pinotshitaitoGnaDlBac(ncuamraecdy oasf atecseterdtaoinr aGsDseBssbeydmdaetaassuoruinrcgetsh)eanddifftehreeinr lcoecsabtieotnwsedeentethrme lionceadtiboynasnooftshpeartGiaDl eBn(tnitaimesesdtoarserdefienrethnacteGdaDtBa s(onuamrceesd) oasf gtreesatetedr oacrcausrsaecsys.eBdasdeadtaonsotuhrisce‘sn)ewan’dpatrhaediriglmoc,awtieonhsavdeedteervmeilnoepdedbay paoniontth-bearseGdDmBe(tnhaomdoeldogays reference data sources) of greater accuracy Based on this ‘new’ paradigm, we have developed a. Effects of the sample size and sample distribution on the automatic positional accuracy estimations by means NSSDA are presented and discussed .
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