The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Download
Citation
Articles | Volume XL-5/W3
https://doi.org/10.5194/isprsarchives-XL-5-W3-139-2013
https://doi.org/10.5194/isprsarchives-XL-5-W3-139-2013
07 Jan 2014
 | 07 Jan 2014

COMPARISONS BETWEEN DIFFERENT INTERPOLATION TECHNIQUES

G. Garnero and D. Godone

Keywords: DTM, Accuracy, IntesaGIS, LIDAR, Modelling, Specifications, Validation

Abstract. Digital terrain models are key tools in land analysis and management as they are directly employable in GIS systems and other specific applications like hydraulic modelling, geotechnical analyses, road planning, telecommunication, and many others. TIN generation, from different kind of measurement techniques, is ruled by specific regulations. Interpolation techniques to compute a regular grid from a TIN, are, instead, still lacking in specific regulations: a unitary and shared methodology has not already been made compulsory in order to be used in cartographic production while generating digital models. Such ambiguity obviously involves non univocal results and can affect precision, which can lead to divergent analyses on the same territory.

In the present study different algorithms will be analysed in order to spot an optimal interpolation methodology. The availability of the recent digital model produced by the Regione Piemonte with airborne LIDAR and the presence of sections of testing realized with higher resolutions and the presence of independent digital models on the same territory allow to set a series of analysis with consequent determination of the best methodologies of interpolation.

The analysis of the residuals on the test sites allows to calculate the descriptive statistics of the computed values: all the algorithms have furnished interesting results; all the more interesting, notably for dense models, the IDW (Inverse Distance Weighing) algorithm results to give best results in this study case. Moreover, a comparative analysis was carried out by interpolating data at different input point density, with the purpose of highlighting thresholds in input density that may influence the quality reduction of the final output in the interpolation phase.