{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:22:44Z","timestamp":1760235764321,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2021,9,28]],"date-time":"2021-09-28T00:00:00Z","timestamp":1632787200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>During road construction investments, the key issue affecting the structure\u2019s safety is accurate subsoil recognition. Identifying subsoil variability zones or natural voids can be performed using geophysical methods, and ground-penetrating radar (GPR) is recommended for this task as it identifies the location and spatial range karst formations. This paper describes the methodology of acquisition and processing of GPR data for ground recognition for road investment. Additional subsoil research was performed after karst phenomena were identified in the investment area, formations not revealed by geological recognition from earlier studies during the pre-design stage. Mala Ramac CU II radar with a 250 MHz antenna and a Leica DS2000 with 250 and 700 MHz antennas with real-time geopositioning were used to obtain the data. Regarding GPR data postprocessing, we present a method of converting spatial visualization into a point cloud that allows for GPR and geodetic data integration and confrontation. This approach enabled us to determine the locations of control trenches, the results of which were used for material validation, which is necessary to improve the reliability of subsoil recognition. The results showed a high correlation between the recorded GPR signals and the subsoil structure. Additionally, differences in the quality of results for measurements conducted before laying supporting layers with slag and on the completed road structure surface are illustrated.<\/jats:p>","DOI":"10.3390\/rs13193886","type":"journal-article","created":{"date-parts":[[2021,9,28]],"date-time":"2021-09-28T21:39:29Z","timestamp":1632865169000},"page":"3886","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Subsoil Recognition for Road Investment Supported by the Integration of Geodetic and GPR Data in the Form of a Point Cloud"],"prefix":"10.3390","volume":"13","author":[{"given":"\u0141ukasz","family":"Ortyl","sequence":"first","affiliation":[{"name":"Faculty of Mining Surveying and Environmental Engineering, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Krak\u00f3w, Poland"}]},{"given":"Marta","family":"Gabry\u015b","sequence":"additional","affiliation":[{"name":"Faculty of Mining Surveying and Environmental Engineering, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Krak\u00f3w, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5","DOI":"10.2478\/s11600-009-0030-9","article-title":"High resolution seismic investigations for the determination of water flow directions during sulphur deposits exploitation","volume":"58","author":"Dec","year":"2010","journal-title":"Acta Geophys."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1002\/nsg.12102","article-title":"Four-dimensional electrical resistivity tomography for continuous, near-real-time monitoring of a landslide affecting transport infrastructure in British Columbia, Canada","volume":"18","author":"Holmes","year":"2020","journal-title":"Near Surf. 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