Laajuus: 5

Aikataulu: 08.01.2019 - 13.02.2019

Vastuuopettaja (voimassa 01.08.2018-31.07.2020): 

Martin Vermeer

Opetusperiodi (voimassa 01.08.2018-31.07.2020): 

III (spring term)

Osaamistavoitteet (voimassa 01.08.2018-31.07.2020): 

To understand fundamentals of least-squares adjustment, network geometry, observation equations, linearization, datums and transformations. To be able to program (Matlab) least-squares adjustment for photogrammetric tasks: exterior orientation, relative orientation, and space intersection. To understand how the least-squares adjustment is established and solved for block adjustment and camera calibration. To  understand how least-squares adjustment is applied for positioning techniques (GNSS) as well as to understand observation geometry and dilution of precision in navigation cases. To  understand least-squares collocation in gravity field modelling. To  understand network quality, precision and reliability,  variance-covariance matrix and precision criteria, statistical testing  and hypotheses (chi-squared and data snooping), test significance and power, reliability metrics, redundancy, confidence areas or regions, and  error seeking. To  understand and apply Wiener-, Kalman-, particle filters, and real-time estimation in mapping platform navigation and airborne gravimetry. To understand the theory and application of stochastic processes. To understand advanced statistical techniques as applied in geosciences, like Bayesian inference and information criteria (Akaike).

Sisältö (voimassa 01.08.2018-31.07.2020): 

The  course focuses on applying least-squares adjustment for geodetic and  photogrammetric tasks. In geodesy, this aims at obtaining optimal  results from network measurement, gravity field modelling and positioning, for example. In photogrammetry, a typical application is to  solve the unknown model parameters of imaging geometries, such as interior and exterior orientation, instrument calibration, space  intersection, aerial triangulation, and feature extraction.

Toteutus, työmuodot ja arvosteluperusteet (voimassa 01.08.2018-31.07.2020): 

Examination and exercises

Työmäärä toteutustavoittain (voimassa 01.08.2018-31.07.2020): 

Lectures (20 h), assignments (68 h), self-study (20 h), preparation for examination + examination (27 h)

Oppimateriaali (voimassa 01.08.2018-31.07.2020): 

Lecture notes and additional literature

Korvaavuudet (voimassa 01.08.2018-31.07.2020): 

Maa-57.3120 Analyyttinen fotogrammetria (4 op)

Kurssin kotisivu (voimassa 01.08.2018-31.07.2020):

Esitiedot (voimassa 01.08.2018-31.07.2020): 

Basic statistics and probability

Lisätietoja (voimassa 01.08.2018-31.07.2020): 

From teachers: Martin Vermeer, Petri Rönnholm, Ulla Kallio

Opintojakson kuvaus

Ilmoittautuminen ja lisätiedot