Kurzpräsentation
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Mehr InformationenInformation zum
Modul
Dr. Ivan Tomljenović, Mag
Dr.rer. nat. Mag. ing. geod. et geoinf. Ivan Tomljenović currently is a head of Remote Sensing and GIS Laboratory within Oikon ltd – Institute of Applied Ecology. He has a Master degree in Geodesy and Geoinformatics from University of Zagreb and a Doctoral degree in Applied Geoinformatics obtained from the University of Salzburg.
Specialized in LiDAR/UAV/Satellite (Sentinel 1 & 2) Remote Sensing, Geoinformatics and Geodesy. His professional interests evolve around topics of Object-Based Image Analysis (OBIA), Airborne and Satellite LiDAR platforms, Advanced Remote Sensing, WebGIS design, Land Cover Mapping, Automated Classification, Machine Learning, Mobile App Design and Development. He is a professional with strong communications and technical skills, he is known for his interactive presentation style.
In free time he is also an artist expressing himself through surreal forms that challenge the way we view our surroundings. Sample of his works can be seen at https://500px.com/itomljenovic87
- To understand and define LiDAR platform and the building blocks behind the platform
- To separate and define sub-categories of LiDAR sensory platforms as to gain a deeper insight into the areas of application and the development.
- To gain hands-on experience in dealing with LiDAR data products and information extraction.
Core UNIGIS modules 1-3 or equivalent understanding of GIS, data modeling, data structures and data acquisition. If you are not sure whether you qualify, please contact martin.loidl@plus.ac.at.
This module is structured around the principle of using recorded video instructions that guide the students into the subject matter. Each lecture contains video material with the delivery of the topic and additional presentation files for commenting and follow-up.
We would like to inform you that this is an exclusively English language module, hence any kind of communication with the module lecturer should be in English. A discussion forum is maintained in Moodle in order to support efficient module instruction. You are requested to submit all your questions related to this module to this forum only. The lecturer will check all incoming comments on a regular basis. He will answer your questions or provide you with pointers for solving your problems. The module is delivered in form of an instructed self-study that is based on explorative learning process and process. Theoretical concepts are complemented with practice-oriented examples demonstrated with help of multimedia elements. Upon completion of the module students are requested to evaluate the module, which is a part of our quality assurance policy and practice.
Trimble eCognition Developer, FugroViewer and ArcGIS Pro
Windows 10 or higher, 64-bit environment with min 8GB or RAM and 64GB of free disk space.
The assessment is based on your completed assignments. They must be submitted in written format (.PDF) to the Dropbox within the required time period. If assignments are submitted late, the lecturer is not obligated to grade them. It will be listed as such on your transcript.
Dauer
Sprache
Wertigkeit
Kosten
The module is free of charge for UNIGIS students working to meet their elective subject requirements. Included are:
- all related study materials
- supervision and assessment
- module accreditation according to the curriculum
ClubUNIGIS members can register at a price of € 420,-.
Included are:
- all related study materials
- supervision and assessment
- course certificate upon completion of the module
Lektionen
des Moduls
Lektion 1 – Introduction to LiDAR
This lesson provides an introduction to the topic of LiDAR and its use. It provides a quick historic overview of how the whole Platform came to life and what are the basics of each platform
Lektion 2 – LiDAR platform elements
This lesson is a direct continuation of the previous lesson and it provides a deeper look into the topics of LiDAR platform elements. It discusses each of the main components into details and explains to the student what is an Inertial Measurement Unit, Global Positioning System and Laser Ranger (IMU, GPS, LR).
Lektion 3 – Introduction to LiDAR metrics
This lesson is the final part of the introductory lessons and it focuses on the topic of the data formats and expected outputs. The main part of the lesson is focused on the core of the LiDAR methodology, which is the multiple returns recording of the pulse. In the last section, an differentiation of the topics of digital elevation models and digital surface models is provided to the student.
Lektion 4 – Spaceborne LiDAR systems
After the introduction, we begin analysing each of the main LiDAR sub-systems by providing the historic overview of the systems and the main principles of their function. Additionally, we paint the picture on how the data from such platform is used. For lesson 4, we talk about spaceborne LiDAR systems. We learn about the various types of spaceborne LiDAR sensors available out there and about spaceborne system builders (NASA, etc). Additionally, we learn about various use scenarios for spaceborne LiDAR data.
Lektion 5 – Airborne LiDAR systems
For lesson 5, we talk about airborne LiDAR systems, about the various types of airborne LiDAR platforms and their pros and cons over the others. We discuss the use cases for these platforms and when would it be more appropriate to use one over the other.
Lektion 6 – UAV LiDAR systems
For lesson 6, we talk about UAV LiDAR systems and about UAV LiDAR platform and how it integrates with the existing UAVs. We learn for which use cases it is the best technology to go for and when it should be avoided. Additionally, we learn about error sources and what to keep in mind when using this technology.
Lektion 7 – Terrestrial LiDAR systems
For lesson 7, we talk about terrestrial LiDAR systems, about the usual terrestrial LiDAR platforms and their benefits over other surveying systems. We showcase of some typical projects done with the terrestrial LiDAR systems and learn on when to use it and when should it be avoided in project work.
Lektion 8 – Bathymetric LiDAR systems
For lesson 8, we talk about bathymetric LiDAR systems, learning about underwater LiDAR scanning and the special type of LiDAR laser beam which is green or blue. We learn about the various carrier systems and existing solutions and show a typical look of a Bathymetric LiDAR data.
Lektion 9 – Special Types of LiDAR systems
In this lesson we are learning of the new development when it comes to the use of LiDAR platforms in a multispectral filed, about how they are built and what do we use them for and about the existing multispectral projects.
Lektion 10 – Management of LiDAR data
After gaining an detailed overview of the existing platforms, we switch our focus to the topics of learning about various LiDAR data formats and the type of information they contain. We talk about the compression algorithm and why or how one should use it. Additionally, we learn about the organisation of the LiDAR data and about LAS and LAZ data formats.
Lektion 11 – LiDAR Applications for building extraction
In this lesson we go into more practical topics and use theory to cover the approach to the problematic of building extraction and how to think when wanting to deal with the topic. We focus on what is important when working with buildings, necessary point cloud density and how to think when buildings are in the main focus for data collection.
Lektion 12 – LiDAR Applications in forestry
Similar to the previous lesson, In this lesson, we go into more practical topics and use theory to cover the approach to the problematic of forest parameter extraction and how to think when wanting to deal with the topic. We focus on what is important when it comes to forestry applications, necessary parameters for data analysis and ways to approach the problematics.
Lektion 13 – Other LiDAR data applications overview
This lecture talks about the general segregation of various application cases and it’ss advantages or disadvantages over other use cases.
Lektion 14 – LiDAR Accuracy and data corrections
Ever wanted to know answers to questions like: What are the typical sources of error for LiDAR platforms, how big is the cumulative error pool, how can we correct it and minimise the error rate, how to clean the data and edit it, or even what are some of the typical LiDAR misconceptions? Then this lesson is the perfect lesson for you!
Lektion 15 – LiDAR visualization in the web
The final lesson of the series will introduce you to the topic of massive point cloud visualization on the web and steer you towards the proper way of thinking when working with such data.