Geodetic Data Processing Using Soft Computing Techniques

Abstract

Geodetic data processing involves using mathematical and computational techniques to analyze and interpret geospatial data about the Earth’s surface and the objects and features that exist on it. This data is collected through satellite imagery, aerial photography, and surveying instruments such as total stations and GPS receivers. The applications of geodetic data processing are diverse and include land surveying, mapping, navigation, environmental monitoring, and disaster management. It is crucial to understand and manage the Earth’s resources and address global challenges such as climate change, natural disasters, and urbanization. In recent years, the information technology industry has undergone a considerable transformation that has significantly impacted the development of various disciplines. Intelligent systems, powerful tools for understanding and solving complex engineering issues, have become increasingly important in this context. Soft computing techniques, including artificial neural networks, fuzzy logic, and evolutionary algorithms, are used more frequently in geodetic data processing due to their ability to handle complex, imprecise, and uncertain data. This study discusses using soft computing techniques in geodetic data processing and examines the challenges and future directions in using soft computing techniques in geodetic data processing.