[HTML][HTML] Reconstruction and efficient visualization of heterogeneous 3D city models

M Buyukdemircioglu, S Kocaman - Remote Sensing, 2020‏ - mdpi.com
The increasing efforts in develo** smart city concepts are often coupled with three-
dimensional (3D) modeling of envisioned designs. Such conceptual designs and planning …

Automation of building permission by integration of BIM and geospatial data

PO Olsson, J Axelsson, M Hooper, L Harrie - ISPRS International Journal …, 2018‏ - mdpi.com
The building permission process is to a large extent an analogue process where much
information is handled in paper format or as pdf files. With the ongoing digitalisation in …

Virtual scene construction of wetlands: A case study of Poyang Lake, China

S Lu, C Fang, X **ao - ISPRS International Journal of Geo-Information, 2023‏ - mdpi.com
Due to the complexity of wetland ecosystems, wetlands have a wide area of alternating land
and water zones and complex vegetation composition, making it challenging to achieve …

Confidence of a k-nearest neighbors Python algorithm for the 3D visualization of sedimentary porous media

M Bullejos, D Cabezas, M Martín-Martín… - Journal of Marine …, 2023‏ - mdpi.com
In a previous paper, the authors implemented a machine learning k-nearest neighbors
(KNN) algorithm and Python libraries to create two 3D interactive models of the stratigraphic …

[HTML][HTML] Using python libraries and k-Nearest neighbors algorithms to delineate syn-sedimentary faults in sedimentary porous media

M Martín-Martín, M Bullejos, D Cabezas… - Marine and Petroleum …, 2023‏ - Elsevier
This paper introduces a methodology based on Python libraries and machine learning k-
Nearest Neighbors (KNN) algorithms to create an interactive 3D HTML model …

[HTML][HTML] A K-nearest neighbors algorithm in Python for visualizing the 3D stratigraphic architecture of the Llobregat River Delta in NE Spain

M Bullejos, D Cabezas, M Martín-Martín… - Journal of Marine …, 2022‏ - mdpi.com
The k-nearest neighbors (KNN) algorithm is a non-parametric supervised machine learning
classifier; which uses proximity and similarity to make classifications or predictions about the …

Identification of altitude profiles in 3D geovisualizations: the role of interaction and spatial abilities

P Kubíček, Č Šašinka, Z Stachoň… - … Journal of Digital …, 2019‏ - Taylor & Francis
Three-dimensional geovisualizations are currently pushed both by technological
development and by the demands of experts in various applied areas. In the presented …

[HTML][HTML] A Python application for visualizing the 3D stratigraphic architecture of the onshore Llobregat River Delta in NE Spain

M Bullejos, D Cabezas, M Martín-Martín, FJ Alcalá - Water, 2022‏ - mdpi.com
This paper introduces a Python application for visualizing the 3D stratigraphic architecture of
porous sedimentary media. The application uses the parameter granulometry deduced from …

[HTML][HTML] Dynamic 3D simulation of flood risk based on the integration of spatio-temporal GIS and hydrodynamic models

Y Wu, F Peng, Y Peng, X Kong, H Liang… - … International Journal of …, 2019‏ - mdpi.com
Dynamic visual simulation of flood risk is crucial for scientific and intelligent emergency
management of flood disasters, in which data quality, availability, visualization, and …

[HTML][HTML] Identification of the best 3D viewpoint within the BIM model: Application to visual tasks related to facility management

R Neuville, J Pouliot, R Billen - Buildings, 2019‏ - mdpi.com
Visualizing building assets within building information modeling (BIM) offers significant
opportunities in facility management as it can assist the maintenance and the safety of …