Successful PhD Defense within the Doctoral College “GIScience” at Z_GIS

Earth's surface is constantly changing due to natural processes, such as erosion, glacier retreat, natural hazards and human disturbances at different spatio-temporal scales depending on the interacting processes. Earth observation (EO) offers a wide variety of multisensory platforms, including radar and optical remote sensing, which plays a vital role in mapping and understanding patio-temporal dynamics of Earth's surface changes.

In her doctoral thesis, entitled “Investigation and Evaluation of Radar and Optical Earth Observation Data in an Object-based Image Analysis Framework”, Zahra Dabiri aimed to investigate the potential of radar and optical EO data to map and monitor geographical features. She developed a framework for combining synthetic aperture radar (SAR) and optical EO data using an expert knowledge approach and an object-based image analysis (OBIA) framework.

OBIA not only serves as a platform for the integration of various data and relies on segmentation and classification. It also offers a platform for integrating knowledge-based and machine learning (ML) algorithms for converting candidate objects into target objects using statistical attributes, contextual, morphological, and hierarchical information. Thus, Ani used the OBIA framework as the main framework compared to the pixel­based image analysis.

The research focused on the following sub-topics and was published in seven peer-reviewed journal papers:

- Investigation of the problem of scale definitions among GIScience communities.

- Investigation of spectral and spatial complexity reduction techniques for (semi-) automated geographical features using very high (VH) resolution hyperspectral data in the OBIA framework.

- Investigation of the applicability of SAR data and optical EO data for mapping and monitoring geomorphological features using the OBIA framework.

The overall contribution of this research was to find the applicability of SAR and optical EO data, to elaborate data quality and applicability for efficient feature extraction, and better understand the geomorphological changes through time and space in the OBIA framework.

We wish Ani all the best for her future endeavours!