Guest Scientist: Olga Degtyareva

Guest Scientist: Olga Degtyareva

October 9, 2017

We welcome Olga in Würzburg at our Department again. She visits us the second time in order to work and gain new expertise with colleagues from our university on modeling of rice yields, which is one of the tasks of the LaVaCCA project. In 2013 she graduated as Master of Engineering Sciences in specialty Cartograph at the Al-Farabi Kazakh National University, Almaty, Kazakhstan. The theme of the master’s thesis was Web GIS technology for thematic mapping of the Akmola region based on remote sensing data. Her research topics remote sensing and GIS were multi-sensor and multi-scale land use/ land cover, mapping, nonitoring of agriculture, building GIS database.

She participates in the LaVaCCA project as a PhD student from 20015 to 2017. Her PhD topic is:  Space monitoring of rice production on Syr-Darya lower reaches area: Indicators for agricultural and environmental change. The research project deals with modeling yields in rice crops. It also examines the use of land, the stage of abandonment and restoration of previously plowed land in the Kazalinsky region, Kyzylorda region.

 

follow us and share it on:

you may also like:

Remote sensing insights into biogas flowering mixtures

Remote sensing insights into biogas flowering mixtures

Perennial wildflower mixtures are gaining importance as an alternative to maize in biogas production. As highlighted in the praxis-agrar article on crop diversification with biogas flowering mixtures, they combine agricultural use with clear ecological benefits....

PhD submitted by Julia Rieder

PhD submitted by Julia Rieder

We are pleased to share that our PhD student Julia Rieder has successfully submitted her doctoral thesis! Her dissertation, entitled “Abiotic and biotic drivers of drought responses in European beech (Fagus sylvatica L.) inferred from field and LiDAR data”,...

New Funded Project on Automated Detection of Mining Areas

New Funded Project on Automated Detection of Mining Areas

In a newly launched research project funded by the KSB Foundation, we focus on the automated identification of mining areas based on remote sensing data. The aim is to systematically detect large-scale mining activities and to track their spatial and temporal...

Share This