The project addresses the challenges of advancing geospatial technologies for mass acquisition of geographical data and geospatial AI. It focuses on spatial modeling as support for natural and built environment management. The goal of the project is to develop innovative methods for Earth observation, model spatial phenomena, and integrate modern geospatial technologies, AI, and large-scale data processing into geospatial analytics.
As part of the project, we are tackling the processing and analysis of large 3D point cloud scans. Our work focuses on segmentation and classification of data, visualization via mesh reconstructions, Gaussian splatting and neural rendering, information retrieval from 4D environmental scans, and the development of algorithms for geospatial analytics.
@inproceedings{283195651,
author = {Gorup, Gorazd and Bohak, Ciril},
booktitle = {EnvirVis 2026 : Workshop on {Visualisation} in {Environmental} {Sciences} : Nottingham, {UK}, {June} 8-- 12, 2026},
doi = {10.2312/envir.20261004},
year = {2026},
pages = {1--7},
title = {Visualization of temporal changes in environmental point cloud scans},
}
@inproceedings{288392707,
author = {Gorup, Gorazd and Bohak, Ciril},
booktitle = {WSCG 2026 : 34. {International} {Conference} on {Computer} {Graphics}, {Visualization} and {Computer} {Vision} : [{May} 26 - 28, 2026, {Plzen}, {Czech} {Republic}]},
year = {2026},
pages = {1--11},
title = {Volume change analysis in environmental point clouds},
}