Techniques for acquisition of geometrical data can be as follows:
a) Resurvey. This technique embraces field (GPS, total station and other traditional), or photogrammetric data acquisition and total reprocessing of the data resulted.
b) Numerical revision of map. This involves the total reprocessing of the results of the original measurements and of those carried out since then as an extension, for example calculation of coordinates of points on the basis of field notes.
c) Manual digitization of maps and other graphical documents. This technique embraces measurements point by point on the table of digitization or from the display.
d) Scanning of maps. This process of work consist of scanning i.e. automated digitization and the subsequent vectorization.
e) Mixed techniques. Combination of the enlisted and eventual other techniques.
If acquisition of attribute data was carried out on the basis of a valid standard, rules, instruction, the publisher and year of publication are to name.
Geometrical quality of the data is characterized by the following items:
a) The required accuracy of the data is given by the expected mean square error. The threefold value of the mean square error is the limit of error.
b) We can get information about the actual accuracy of the data by
Quality requirements of geometrical data of the digital
large scale basic map can be classified on the basis of their
content feature into the following four classes:
T1 class of tolerance: cities, prominent resort and industrial areas,
T2 class of tolerance: villages,
T3 class of tolerance: intensively cultivated rural areas,
T4 class of tolerance: extensively cultivated rural areas and those with drawn from cultivation.
The points of the digital large scale basic map can be:
The expected positional mean square error of the detail points (in dimension cm) is as follows:
The expected positional mean square error relates to the neighboring geodetic control point, regarded as errorless. If a detail point is simultaneously also a boundary point, then of the potential expected mean square error the stricter one prevails.
The expected mean square error of the dimensions should be computed from the expected positional mean square error of the individual points by applying the rule of error propagation. When computing the individual points are to consider independent. The expected mean square error (in unit of measurement cm) of the dimensions is as follows:
T1 class of tolerance
T2 class of tolerance
T3 class of tolerance
T4 class of tolerance
Also the value of the expected reliability is to prescribe. The value of the expected reliability is threefold the value of the expected mean square error.
When the digital large scale basic maps are not produced by resurvey, the accuracy and reliability requirements here specified are only partly to meet. Then the host of data may also permit other allowable accuracy and reliability values on the basis of special initiative. The fact and value of reduced permitted accuracy and reliability prescriptions has to be let known unambiguously to the users of the product.
The expected mean square error of the height of the vertical detail points or boundary and other detail points having height too:
The changes occurred at boundary points H1 and H2 have to be registered within one month subsequent the changes in the data subset of the digital map.
The revision of the digital basic maps are recommended
in order to ensure the proper data quality, at intervals as follows:
|T1 class of tolerance (cities, prominent resort and industrial areas)||5 years|
|T2 class of tolerance (villages)||10 years|
|T3 class of tolerance (intensively cultivated rural areas)||15 years|
|T4 class of tolerance (extensively cultivated rural and from cultivation withdrawn areas)||20 years|
For the digital terrain model the length of the grid cells is to chose that the error of the terrain model is within the allowable vertical bias. That can be ensured by applying a length of 0.5-3 m for the grid cells in function of the declination angle of the terrain.