Date: 26th & 27th December 2019
Venue: INSTRUCT Lecture Hall, Bangalore
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Drone technology has developed rapidly over the past few years. From defense to civil sectors, drone technology has innumerable applications! At Huviair, we have been working intensely with survey applications of drones and have mastered them! We have created this course after gaining extensive knowledge in executing projects across various sectors such as renewable energy, Governments, NGOs, real estate and agriculture. It covers the basics of land surveying and how drones are now being used for it. We have detailed out all the steps involved in flight planning and execution. We also cover how you can go about processing the images captured to get outputs such as orthomosaics, digital surface models, contours and 3D models.
This course is especially useful for those of you who are beginners or aerial photographers who have little or no experience with drone surveying.
OBJECTIVES:
- The experts will give firsthand experience of the technology in various fields of Surveying like
- Master end to end drone surveying processes and techniques
- Tap into the multi billion dollar global land surveying industry! Understand the basics of land surveying and how you can transform this sector with drones
- Learn about surveying accuracy and how you can achieve the best possible accuracy
- Choose the best drones for aerial surveying
- Plan nadir and oblique automated flights using techniques that I have mastered over 3 years.
- Learn how to use kml/excel files and gps tagging apps to plan your flights
- Learn about safety and regulations for drone operations
- Internalize all practical aspects of flight execution – marking boundary points, choosing best take off points, adjusting flight parameters, image quality and coverage check, continuing flights midway in a mission
- Use image processing software to generate, analyze and visualize aerial survey outputs – orthomosaics, DSMs, 3Dmodelsand contours
- Practise flight planning and image processing steps with sample data sets
