course aims in Estonian
Kursuse eesmärk on anda ülevaade kaugseire võimalustest ehitusprotsesside kaardistamiseks. Andmehõive plaani koostamine vastavalt kaugseire läbiviimise eesmärgist. Andmetöötluse rakenduslikud vaated lähtuvalt võrdlusinfost (infomudeliga võrdlemine, joondamine). Ülevaade punktipilve klassifitseerimise ning segmenteerimise tööprotsessidest (tehisintellekti kaasamine).
course aims in English
The aim of the course is to provide an overview of remote sensing options for mapping construction processes. Preparation of a data acquisition plan according to the purpose of conducting remote sensing. Applied views of data processing based on reference information (comparison with information model, alignment). Overview of the work processes of point cloud classification and segmentation (inclusion of artificial intelligence).
learning outcomes in the course in Est.
Aine läbinud üliõpilane:
- omab baasteadmisi kaugseire rakenduslikust vaatest ehitusprotsesside kaardistamiseks;
- rakendab kaugseire andmehõivet (aeroskaneerimine, drooniseire, mobiilne skaneering) ehitusprotsesside kaardistamiseks, võrdlusinfo koostamiseks.
learning outcomes in the course in Eng.
After completing this course the student:
- has basic knowledge of the applied view of remote sensing for mapping construction processes;
- applies remote sensing data acquisition (aerial scanning, drone monitoring, mobile scanning) for mapping construction processes and compiling comparative information.
brief description of the course in Estonian
Sissejuhatus kaugseiresse. Kaugseire rakenduslikud vaated ehitusektorile fookusega ehitusprotsesside jooksvaks kaardistamiseks. Kaugseire andmehõive plaani koostamine lähtuvalt kasutusjuhust, eesmärgist. Kaugseire andmete töötlus ning sobitamine ehitusprotsessi esitavasse infomudelisse. Drooniseire kasutamise praktilised näited. LiDAR sensoriga nutiseadme (iPhone, iPAD) kasutamise praktilised näited.
brief description of the course in English
Introduction to remote sensing. Applied views of remote sensing for the construction sector with a focus on the ongoing mapping of construction processes. Preparation of a remote sensing data acquisition plan based on the use case and purpose. Processing and matching remote sensing data into an information model representing the construction process. Practical examples of using drone surveillance. Practical examples of using a smart device (iPhone, iPad) with a LiDAR sensor.
type of assessment in Estonian
Hindeline arvestus
type of assessment in English
Graded assessment
independent study in Estonian
-
independent study in English
-
study literature
E-õppe materjalid Moodle'is
study forms and load
daytime study: weekly hours
2.0
session-based study work load (in a semester):
lecturer in charge
Raido Puust, kaasprofessor tenuuris (EA - ehituse ja arhitektuuri instituut)