Creating virtual models for designing port complexes based on lidar data

Abstract

The design of port complexes is a process that requires considering geographical and economic features of the territory. It is necessary to aggregate the characteristics of coastal landscapes, seascapes, artificial elements, dangerous objects, etc. The experience of implementing such projects (for example, in Sabetta) suggests that all participants in the design process need highly precise geographical information to optimize the location of coastal facilities, infrastructure solutions, power supply lines, water conduits, product pipelines, and related structures. As for now, the best method of geoinformation support of such projects is LIDAR (with simultaneous nadir and perspective aerial surveys). In the future, these materials, combined with space-based remote sensing data on the surrounding areas, would be used for creating virtual models with tools adapted for users with an average and low-level GIS data experience. Nowadays geoinformation systems have a number of disadvantages. First and foremost, it is difficult for non-specialists to master them. Full-featured GIS packages are expensive and cannot be used by a significant number of specialists, dispersed over various settlements only using high-speed internet connections (designing port complexes requires the efforts of heterogeneous specialists living in different cities and working in different industries). The approach proposed in this paper allows to solve this problem without using GIS packages. We consider it possible to use virtual environments that are closed from editing and access to the source data. An area of 2400 km² in the territory of Kamchatka Peninsula near Bechevinka Bay was chosen as a test site. The resulting virtual model of the territory of the future port complex is a convenient tool for increasing the spatial awareness of users, closed from unauthorized access. The work has successfully achieved the functionality and usability of this model on conventional computers, combined with the high spatial accuracy of the model.