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Article

Expert Knowledge as Basis for Assessing an Automatic Matching Procedure

Department of Cartographic, Geodetic Engineering and Photogrammetry, University of Jaén, 23071 Jaén, Spain
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Academic Editor: Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2021, 10(5), 289; https://doi.org/10.3390/ijgi10050289
Received: 24 February 2021 / Revised: 29 April 2021 / Accepted: 30 April 2021 / Published: 2 May 2021
The continuous development of machine learning procedures and the development of new ways of mapping based on the integration of spatial data from heterogeneous sources have resulted in the automation of many processes associated with cartographic production such as positional accuracy assessment (PAA). The automation of the PAA of spatial data is based on automated matching procedures between corresponding spatial objects (usually building polygons) from two geospatial databases (GDB), which in turn are related to the quantification of the similarity between these objects. Therefore, assessing the capabilities of these automated matching procedures is key to making automation a fully operational solution in PAA processes. The present study has been developed in response to the need to explore the scope of these capabilities by means of a comparison with human capabilities. Thus, using a genetic algorithm (GA) and a group of human experts, two experiments have been carried out: (i) to compare the similarity values between building polygons assigned by both and (ii) to compare the matching procedure developed in both cases. The results obtained showed that the GA—experts agreement was very high, with a mean agreement percentage of 93.3% (for the experiment 1) and 98.8% (for the experiment 2). These results confirm the capability of the machine-based procedures, and specifically of GAs, to carry out matching tasks. View Full-Text
Keywords: machine learning; expert knowledge; automatic matching; spatial data accuracy; automatic assessment machine learning; expert knowledge; automatic matching; spatial data accuracy; automatic assessment
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MDPI and ACS Style

Ruiz-Lendínez, J.J.; Ariza-López, F.J.; Ureña-Cámara, M.A. Expert Knowledge as Basis for Assessing an Automatic Matching Procedure. ISPRS Int. J. Geo-Inf. 2021, 10, 289. https://doi.org/10.3390/ijgi10050289

AMA Style

Ruiz-Lendínez JJ, Ariza-López FJ, Ureña-Cámara MA. Expert Knowledge as Basis for Assessing an Automatic Matching Procedure. ISPRS International Journal of Geo-Information. 2021; 10(5):289. https://doi.org/10.3390/ijgi10050289

Chicago/Turabian Style

Ruiz-Lendínez, Juan J., Francisco J. Ariza-López, and Manuel A. Ureña-Cámara 2021. "Expert Knowledge as Basis for Assessing an Automatic Matching Procedure" ISPRS International Journal of Geo-Information 10, no. 5: 289. https://doi.org/10.3390/ijgi10050289

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