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International Journal of Engineering Technology and Construction, 2024, 5(1); doi: 10.38007/IJETC.2024.050103.

Surveying and Mapping Technology in Extreme Environments


Yi Jiang, Yang Yang

Corresponding Author:
Yang Yang

Shandong Provincial Institute of Land Surveying and Mapping, Jinan, Shandong, China


This paper provides a comprehensive overview of advances in surveying and mapping technology applicable to special terrains and extreme environments. Highlighting innovations such as LiDAR, Geographic Information Systems (GIS), autonomous drones, and the integration of Artificial Intelligence (AI) and Machine Learning (ML), it explores how these technologies are transforming the field of geospatial data collection. LiDAR technology has emerged as a pivotal tool, capable of generating precise 3D models and penetrating dense cover to produce accurate maps in visually obscured environments. GIS has enhanced the capacity for sophisticated data analysis, enabling more informed decision-making in multiple sectors, such as environmental management and urban planning. Additionally, the use of autonomous drones has revolutionized data collection, providing safe, efficient, and cost-effective means of accessing challenging terrains. The paper also discusses future trends, including the potential integration of virtual reality (VR) and augmented reality (AR) to create immersive data interaction experiences, and the application of cloud computing and the Internet of Things (IoT) to enhance real-time data accessibility and collaboration. These technologies promise to further advance the field of surveying and mapping, ensuring more accurate, efficient, and safer geographical data collection and analysis in complex environments.


Surveying and Mapping Technology; Special Terrain; Surveying and Mapping Engineering; Artificial Intelligence (AI); machine learning (ML)

Cite This Paper

Yi Jiang, Yang Yang. Surveying and Mapping Technology in Extreme Environments. International Journal of Engineering Technology and Construction (2024), Vol. 5, Issue 1: 18-28. https://doi.org/10.38007/IJETC.2024.050103.


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