Processing Uav and Lidar Point Clouds in Grass Gis

Abstract

ABSTRACT:Today's methods of acquiring Earth surface data, namely lidar and unmanned aerial vehicle (UAV) imagery, non-selectively collect or generate large amounts of points. Point clouds from different sources vary in their properties such as number of returns, density, or quality. We present a set of tools with applications for different types of points clouds obtained by a lidar scanner, structure from motion technique (SfM), and a low-cost 3D scanner. To take advantage of the vertical structure of multiple return lidar point clouds, we demonstrate tools to process them using 3D raster techniques which allow, for example, the development of custom vegetation classification methods. Dense point clouds obtained from UAV imagery, often containing redundant points, can be decimated using various techniques before further processing. We implemented and compared several decimation techniques in regard to their performance and the final digital surface model (DSM). Finally, we will describe the processing of a point cloud from a low-cost 3D scanner, namely Microsoft Kinect, and its application for interaction with physical models. All the presented tools are open source and integrated in GRASS GIS, a multi-purpose open source GIS with remote sensing capabilities. The tools integrate with other open source projects, specifically Point Data Abstraction Library (PDAL), Point Cloud Library (PCL), and OpenKinect libfreenect2 library to benefit from the open source point cloud ecosystem. The implementation in GRASS GIS ensures long term maintenance and reproducibility by the scientific community but also by the original authors themselves.

Development of complex methodology of processing heterogeneous data in intelligent decision support systems

“…In [6], an approach to processing various types of data obtained from an unmanned aerial vehicle, implemented in the GRASS GIS software environment, is presented. This approach is based on three-dimensional raster methods of image processing with a subsequent reduction of their redundancy.…”

Development of an algorithm for complex processing of geospatial data in the special-purpose geoinformation system in conditions of diversity and uncertainty of data

“…In [6], an approach for processing various types of data obtained from an unmanned aerial vehicle implemented in the GRASS GIS software environment was presented. This approach is based on three-dimensional raster image processing techniques with a further reduction of their redundancy.…”

Особливості Використання Геоінформаційних Технологій В Задачах Забезпечення Ефективного Застосування Безпілотної Авіації При Охороні Кордону

“…Обробка зображень, отриманих з безпілотних літальних апаратів з метою 3D-моделювання і отримання інформації для внесення до географічної інформаційної системи, розглядається також у роботі [6]. У дослідженні [7] для отримання точних тримірних даних про місцевість та об'єкти розглянуто використання технології лазерного сканування.…”