Interpolating data means collecting new data points within the area of data of known points. In other words, it is gathering data that is scattered with known points on a survey map. Interpolation of data helps in many ways. It helps in creating new plans for redevelopment with the help of set algorithms that are readily available. Many properties have considerable problems with incorrect locations, miscalculation of previous land survey, etc. Interpolating survey data helps in reorganizing the important points on the terrain and can assist in the efficient development of the area. It is a major consideration for accuracy while creating Section Drawings.
Interpolation help in including new elements or data between existing objects that is a prerequisite in section drawing of the longitudinal section. Interpolation of data at regular intervals can be unfeasible due to many unforeseen circumstances and this makes it a little unreliable. However, the cost of interpolating data is inexpensive and can provide with a lot of benefits while surveying a particular area.
There are many advantages to interpolate data. They are:
Ø Interpolation helps in gathering scattered data points on the survey drawing with known data points.
Ø Interpolated data are regularly produced and assists in contouring and other calculations as well.
Ø Smoothing the estimated terrain variability.
Ø Interpolation of survey data also has a few disadvantages. They are:
Ø Based on previous survey data, calculations brought in for new information points can be inaccurate. This is due to the inaccuracy in the previous survey data already.
Ø Remodeling discontinuities can be a problem with this method.
Ø Interpolation of data may create unrealistic data values for different surfaces. This is due to the inaccurate information on the previous area survey drawing.
Ø Applying many types of interpolation for optimizing data can be disastrous as Interpolation requires accumulation of new data.
Ø When data points are deleted from a given data model, the points that are retained can take up the characteristics of the deleted data. This may lead to inaccurate interpolation of data.
The scattered data consists of two data points on a survey map, and there are no objects or obstacles between the two points. There are various methods to interpolate data. The one that is majorly used is the ‘Delaunay Triangulation of the points’. There are many websites and software’s that can help you in Interpolation of data for a terrain survey. Interpolation software is majorly used to achieve good accuracy while surveying land or any terrains. In spite of the many disadvantages while performing interpolation of data, it is still widely used to get the most relevant data for surveying land.
One of the characteristics of interpolation of data is that it always passes through existing data points. Hence, this type of calculation is different from curve/surface fitting. In surface fitting, the function does not pass through existing data points always. This is one of the major distinctions between the two procedures. Interpolating data points also help the accuracy of the new terrain mapping.
Riya Sood
I’m an independent blogger and writer. In this article I explain the benefits of interpolation software in Survey Drawing.