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Disputas: Ulrike Bayr

Ph.d.-kandidat Ulrike Bayr ved Institutt for geofag, Det matematisk-naturvitenskapelige fakultet, vil forsvare avhandlingen Survey techniques in landscape monitoring: testing new quantitative methods to assess landscape change for graden Philosophiae Doctor.

Ulrike Bayr. Foto: Erling Fløistad/NIBIO

Ulrike Bayr. Foto: Erling Fløistad/ NIBIO

Disputas og prøveforelesning avholdes digitalt ved bruk av Zoom. Verten av Zoom-møtet vil moderere det tekniske mens disputasleder moderer disputasen. 

Prøveforelesning

Som opptak:

The potential and limitations of using social media for landscape research

Kreeringssammendrag

Landskapsovervåking gir et viktig grunnlag for å kunne følge landskapsendringer over lang tid. Det er også en forutsetning for å evaluere effekt av politiske virkemidler og ulike tiltak. Avhandlingen viser hvordan etablerte overvåkingsprogrammer kan dra nytte av å inkludere nye metoder og teknologier som har blitt tilgjengelige de siste årene. Samtidig setter avhandlingen lys på utfordringene med å iverksette endringer i metodikken uten å true dataintegritet og kontinuiteten i datagrunnlaget.

Hovedfunn

Populærvitenskapelig artikkel om Bayrs avhandling:

Survey techniques in landscape monitoring: testing new quantitative methods to assess landscape change

Long-term landscape monitoring plays an important role in assessing the state of landscapes, identifying trends and drivers of landscape change and in evaluating the effectiveness of political instruments. Despite the technological advances of the past years, many well-established monitoring programs still rely on rather conventional approaches as they ensure data integrity and consistency.
The aim of this dissertation was to test and examine the use of modern quantitative methods in landscape monitoring, with focus on the Norwegian monitoring program for agricultural landscapes (3Q). The program utilizes a broad range of conventional data sources such as aerial photographs, terrestrial repeat photographs and field inventories of birds and plants.

Monoplotting is one of the methods that were tested on repeat landscape photographs to extract geospatial data. In addition, machine learning approaches were applied on repeat landscape photographs (Convolutional Neural Network) and field registrations of breeding birds (Random Forest). Findings showed that the tested methods provided good results on the respective data sources, but they also showed some limitations in the practical usability for landscape monitoring on the national scale. As the used methods focused on improving data analysis of already existing data sources, data integrity and consistency can be maintained.

Bildet kan inneholde: gjøre, parallell, diagram.
This map shows the role of landscape monitoring as information system for landscape policy. The present dissertation can be placed at the interface between landscape monitoring and research. The enhancement of methods in landscape monitoring contributes to a better understanding of landscape dynamics and interrelationships between human activities and the environment. Figure: Ulrike Bayr

Foto og annen informasjon:

Pressefoto: Ulrike Bayr, portrett; 500px. Foto: Erling Fløistad/NIBIO

Annet bildemateriale: Figur med beskrivelse og kreditering som spesifisert i artikkelen over, størrelse 1000px.

Publisert 25. jan. 2022 20:20 - Sist endret 7. juni 2022 10:16