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Samenvatting Teledetectie Toepassingen | Fotogrammetrie & Machine Learning | UGent | 2024/25

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Studiemateriaal voor het vak Teledetectie Toepassingen uit de Master Geografie en Geomatica aan de Universiteit Gent. Het document behandelt twee kernthema's: fotogrammetrie (DEM-productie, orthorectificatie, virtuele reconstructie) en kartering van bodembedeekking via machine learning classificatie (random forests, supervised learning, beeldclassificatie). Deze aantekeningen bieden een solide basis voor examenvoorbereiding en praktische toepassingen, met uitgebreide behandeling van algoritmen, methodologie en technische parameters.

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Fotogrammetrie
doel: produceren van topografische informatie vanuit stereo en multi-
scopische beelden

eindproducten: DEM en relëfsmodellen, orthofotoplans, contourlijnen,
virtuele objectmodellen




parallax

- orthorectifying of relief displacements

- image distortion due to the unstability of the platform

7 parameters need to be corrected: scale; X, Y, Z; κ, θ, ω

deriving heights from stereo viewing

Voorwaarden fotogrammetrische opnamen
B/H verhouding: luchtfoto’s, terrestrische opnames en ruimteopnames

, metrische camera’s
relatie opname- (S = f/H of f/L) vs. restitutieschaal (uiteindelijke schaal van
het einddocument)
sluiereffect  FMC: Forward Movement Compensation

Restitutie
block en stereoparen




interne oriëntatie  compenseren van de lensvervormingen

niet-metrische fotogrammetrie (niet-gecalibreerde camera’s)

relatieve oriëntatie

RMSE op absolute oriëntatie: min. 6 GCP bij een restitutie zonder
interne oriëntatie

epipolaire beelden




beeldmatching

DEM

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Uploaded on
May 31, 2026
Number of pages
8
Written in
2024/2025
Type
SUMMARY

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