Offer summary

Qualifications:

Hands-on experience in analyzing LiDAR data and mapping natural features., In-depth knowledge of point cloud processing techniques like ground classification and noise filtering., Proficiency with LiDAR processing tools such as LAStools, CloudCompare, ArcGIS Pro, QGIS, and Python., Experience with machine learning or deep learning for object detection in point clouds is a plus..

Key responsibilities:

Process and analyze large-scale LiDAR datasets to identify natural features.

Design and implement automated workflows and algorithms for feature extraction.

Utilize various software tools for tasks like classification, normalization, and feature detection.

Maintain data quality through error detection and correction strategies.

Job description

Key Responsibilities:

Process and analyze large-scale LiDAR point cloud datasets to detect and delineate specific natural features.
Design and implement automated workflows and algorithms for feature extraction and classification.
Utilize and optimize a range of tools and software for LiDAR data processing, including tasks like classification, normalization, and feature detection.
Maintain high standards of data quality by implementing robust error detection and correction strategies.

Qualifications & Experience:

Hands-on experience in analyzing LiDAR data, with a strong focus on identifying and mapping natural features.
In-depth knowledge of point cloud processing techniques such as ground classification, noise filtering, and feature extraction.
Proficient in using LiDAR tools and libraries such as LAStools, CloudCompare, ArcGIS Pro, QGIS, and Python (especially with Open3D or PDAL).
Capable of developing and deploying practical solutions, beyond just providing recommendations.
Experience with machine learning or deep learning techniques for object detection or segmentation in point cloud data is a strong advantage.