ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Citation
Articles | Volume X-5-2024
https://doi.org/10.5194/isprs-annals-X-5-2024-25-2024
https://doi.org/10.5194/isprs-annals-X-5-2024-25-2024
11 Nov 2024
 | 11 Nov 2024

Circinus: An AI-Based Technical Description Plotting

James Earl Cubillas and Rolyn Daguil

Keywords: Land Survey Map, Convolutional Neural Networks, Automation, Computer Vision, Digitization, Opensource software

Abstract. The digitization of maps poses a significant challenge for GIS operators and engineers, particularly in encoding bearings and distances into GIS software. This study, titled “Circinus: An AI-Based Technical Description Plotting,” represents a substantial advancement in the digitization process of land records. Leveraging artificial intelligence, this application enhances the efficiency of digitizing land survey maps, potentially surpassing the laborious manual input required for geographic information. By expediting the encoding process of scanned maps, the application enhances the accessibility and availability of digital land records. This advancement holds considerable benefits for effective land asset planning and improved financial operations, particularly benefiting prospective homebuyers and landowners. The tool offers streamlined encoding through its semi-automated features, facilitating ease of use. Additionally, its optimization features have the potential to significantly enhance the productivity of engineers and GIS operators involved in encoding scanned land survey maps.