The magnitude of human alterations of the Earth's land surface as a consequence of human activities has become currently unprecedented at global to local scales. Arguably, such human-driven land alterations significantly affect different aspects of the Earth system via contributing, among others, to local and regional climate change, driving negative changes in biodiversity patterns and altering ecosystem services.
As part of the sustainable development of our planet's resources, it is important to consider how to manage the land without significantly compromising socio-economic activities. Remote Sensing provides a non-precedential opportunity to observe and monitor the Earth’s surface and its changes in detail and continuously, and thus, provide the required valuable information for policy, decision-making and sustainable land management. During the last decade, a large number of Earth Observation (EO) satellites with passive (optical) and active (radar) sensors have been launched that are used for environmental monitoring and Earth System dynamics modelling as well as for sustainable development programs. All this has resulted in the availability of massive EO image data archives, from which mining and retrieving spatial information are challenging but extremely useful for Earth system research.
Against this background, my main research focus lies in understanding land surface dynamics processes with Remote Sensing. Especially I am interested in researching a wide array of EO application fields with a focus on terrestrial ecosystem variations and processes to increase the knowledge about how the systems operate and interact in the landscapes. For this, it is important not only to apply existing and develop novel Remote Sensing methods but also to apply inter-and transdisciplinary methods where Remote Sensing data is assimilated in the models (such as land surface, vegetation or climate models) or used for socio-economic studies. Topic-wise, I am interested in the application of Remote Sensing and geospatial analysis for vegetation studies, land degradation monitoring, disaster risk reduction (droughts, floods, landslides), biodiversity mapping, crop yield modelling and other similar application in the land domain. Geographically, I have been mostly focusing on Southern and Eastern Africa, Central and Eastern Europe and Central Asia, with a most recent focus on global level analysis.
I welcome supervision requests from Bachelor's / Master's students or prospective PhD candidates on topics that intersect with one or more of the below or related themes and are methodologically based on Remote Sensing and/or geospatial analysis (e.g., GIS) :
land use and land cover change
vegetation dynamics monitoring
hazard (e.g, droughts, floods, landslides) monitoring
pixels & people
Urban remote sensing
Current topics of MSc research linked to the SEBAS project:
- Predicting plant species diversity in grasslands with UAV imagery.
- Predicting plant species composition in grasslands with UAV imagery.
- Predicting plant species diversity in grasslands with Planet imagery.
- Predicting plant species composition in grasslands with Planet imagery.
If you are interested in working on one of the outlined topics or have your own topics connected to the field of Remote Sensing and GIS, please send me an email (Email: Olena.Dubovyk@uib.no).
Olena Dubovyk on Google Scholar
Olena Dubovyk on ResearchGate
Peer-reviewed journal articles
- Hoffmann, J.; Muro, J.; Dubovyk, O. Predicting Species and Structural Diversity of Temperate Forests with Satellite Remote Sensing and Deep Learning. Remote Sensing 2022, 14, 1631.
- Abdel-Hamid, A., Dubovyk, O., and Greve, K., 2021. The potential of sentinel-1 InSAR coherence for grasslands monitoring in Eastern Cape, South Africa. International Journal of Applied Earth Observation and Geoinformation, 98, 102306.
- Akinyemi, F. O., Ghazaryan, G. and Dubovyk, O., 2021. Assessing UN indicators of Land Degradation Neutrality and proportion of degraded land over Botswana using Remote Sensing based national level metrics. Land Degradation & Development, 32, 158-172.
- Reith, J., Ghazaryan, G., Muthoni, F. and Dubovyk, O., 2021. Assessment of Land Degradation in Semiarid Tanzania—Using Multiscale Remote Sensing Datasets to Support Sustainable Development Goal 15.3. Remote Sensing, 13, 1754.
- Rezaei, E. E., Ghazaryan, G., González, J., Cornish, N., Dubovyk, O.., Siebert S., 2021. The use of remote sensing to derive maize sowing dates for large-scale crop yield simulations. International Journal of Biometeorology, 65, 565–576.
- Rezaei, E. E., Ghazaryan, G., González, J., Cornish N., Dubovyk O., Siebert S.2021. Crop harvested area, not yield, drives variability in crop production in Iran. Environmental Research Letters, 16, 064058.
- Abdel-Hamid, A., Dubovyk, O., Graw, V. and Greve, K., 2020. Assessing the impact of drought stress on grasslands using multi-temporal SAR data of Sentinel-1: a case study in Eastern Cape, South Africa. European Journal of Remote Sensing, 1-14.
- Ghazaryan, G., König, S., Rezai, E. E., Siebert S., Dubovyk O., 2020. Analysis of Drought Impact on Croplands from Global to Regional Scale: A Remote Sensing Approach. Remote Sensing, 12, 4030.
- Ghazaryan, G., Dubovyk, O., Graw, V., Kussul, N. and Schellberg, J., 2020. Local-scale agricultural drought monitoring with satellite-based multi-sensor time-series. GIScience & Remote Sensing, 57, 704-718.
- Graw, V., Ghazaryan, G., Schreier, j., Gonzalez, j., Abdel-Hamid, A., Walz, Y., Dall, K., Post, J., Jordaan, A. and Dubovyk, O., 2020. Timing is Everything–Drought Classification for Risk Assessment. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 428-433.
- Landmann, T., Dubovyk, O., Ghazaryan, G., Kimani, J., and Abdel-Rahman, E.M., 2020. Wide-area invasive species propagation mapping is possible using phenometric trends. ISPRS Journal of Photogrammetry and Remote Sensing 159, 1-12.
- Liu, D., Chen, W., Menz, G. and Dubovyk, O., 2020. Development of integrated wetland change detection approach: In case of Erdos Larus Relictus National Nature Reserve, China. Science of The Total Environment, 731, 139166.
- Schreier, J., Ghazaryan, G. and Dubovyk, O., 2020. Crop-Specific Phenomapping by Fusing Landsat and Sentinel Data with Modis Time Series. European Journal of Remote Sensing, 1-12.
- Walz, Y., Min, A., Dall, K., Duguru, M., Villagran de Leon, J.-C., Graw, V., Dubovyk, O., Sebesvari, Z., Jordaan, A. & Post, J., 2020. Monitoring progress of the Sendai Framework using a geospatial model: The example of people affected by agricultural droughts in Eastern Cape, South Africa. Progress in Disaster Science, 5, 100062.
- Dubovyk, O., Ghazaryan, G., Löw, F., Graw, V., Schrier J., 2019. Drought hazard in Kazakhstan in 2000-2016: a remote sensing perspective. Environmental Monitoring and Assessment 191, 510.
- Dimov, D., Löw, F., Uhl, J., Kenjabaev, S., Dubovyk, O., Ibrakhimov, M., Chandrashekhar, B., 2019. A Framework for Agricultural Productivity Assessment based on MODIS multitemporal data. Applied Remote Sensing 13, 1-31.
- Ghazaryan, G., Dubovyk, O., Löw, F., Lavreniuk, M., Kolotii, A., Schellberg, J., Kussul, N., 2018. A rule-based approach for crop identification using multi-temporal and multi-sensor phenological metrics. European Journal of Remote Sensing 51, 511-524.
- Löw, F., Prishchepov, A., Waldner, F., Dubovyk, O., Akramkhanov, A., Biradar, C., Lamers, J., 2018. Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series. Remote Sensing 10, 159.
- Abdel-Hamid, A., Dubovyk, O., Abou El-Magd, Menz, G., 2018. Mapping Mangroves Extents on the Red Sea Coastline in Egypt using Polarimetric SAR and High-Resolution Optical Remote Sensing Data. Sustainability 10, 646.
- Löw, F., Biradar, C., Dubovyk, O., Fliemann, E., Akramkhanov, A. Narvaez Vallejo, A., Waldner, F., 2018. Regional-scale monitoring of cropland intensity and productivity with multi-source satellite image time series. GIScience & Remote Sensing 55, 539-567.
- Zimmermann, S., Dubovyk, O., Oldenburg, C., Pape, R., Löffler, J., 2018. Lichen Cover Mapping in Southern Norway – An Analysis with Remote Sensing and GIS. GIS Science, 2, 60–71.
- Dubovyk, O., 2017. The role of Remote Sensing in land degradation assessments: opportunities and challenges. European Journal of Remote Sensing, 50(1), 601-613.
- Graw, V.G., Dall, K., Delgado Gómez, A., Abdel-Hamid, A., Jordaan, A., Piroska, R., Post, J., Szarzynski, J., Walz, Y., Dubovyk, O., 2017. Drought Dynamics and Vegetation Productivity in Different Land Management Systems of Eastern Cape, South Africa—A Remote Sensing Perspective Sustainability, 9(1728).
- Liu, D., Cao, C., Dubovyk, O., Tian, R., Chen, W., Zhuang, Q., Zhao, Y., Menz, G., 2017. Using fuzzy analytic hierarchy process for spatio-temporal analysis of eco-environmental vulnerability change during 1990–2010 in Sanjiangyuan region, China. Ecological Indicators 73, 612-625.
- Basukala, A.K., Oldenburg, C., Schellberg, J., Sultanov, M., Dubovyk, O., 2017. Towards improved land use mapping of irrigated croplands: performance assessment of different image classification algorithms and approaches. European Journal of Remote Sensing, 50(1), 187-201.
- Santos, F., Dubovyk, O., Menz, G., 2017. Monitoring Forest Dynamics in the Andean Amazon: The Applicability of Breakpoint Detection Methods Using Landsat Time-Series and Genetic Algorithms. Remote Sensing 9(1), 68.
- Parplies, A., Dubovyk, O., Tewes, A., Mund, J.-P., Schellberg, J., 2016. Phenomapping of rangelands in South Africa using time series of RapidEye data. International Journal of Applied Earth Observation and Geoinformation 53, 90-102.
- Ghazaryan, G., Dubovyk, O., Kussul, N., Menz, G., 2016. Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013. Remote Sensing 8, 617.
- Dubovyk, O., Menz, G., Khamzina, A., 2016. Land suitability assessment for afforestation with Elaeagnus Angustifolia L. in degraded agricultural areas of the lower Amu Darya river basin. Land Degradation & Development 27, 1831–1839.
- Dubovyk, O., Landmann, T., Dietz, A., Menz, G., 2016. Quantifying the Impacts of Environmental Factors on Vegetation Dynamics over Climatic and Management Gradients of Central Asia. Remote Sensing 8, 600.
- Tewes, A., Frank Thonfeld, F., Schmidt , M., Oomen, R.J., Zhu, X., Dubovyk, O., Menz, G., Schellberg, J., 2015. Using RapidEye and MODIS data fusion to monitor vegetation dynamics in semi-arid rangelands in South Africa. Remote Sensing 7, 6510-6534.
- Dubovyk, O., Menz, G., Lee, A., Schellberg, J., Thonfeld, F., Khamzina, A., 2015. SPOT-Based Sub-Field Level Monitoring of Vegetation Cover Dynamics: A Case of Irrigated Croplands. Remote Sensing 7, 6763-6783.
- Dubovyk, O., Landmann, T., Erasmus, B.F.N., Tewes, A., Schellberg, J., 2015. Monitoring vegetation dynamics with medium resolution MODIS-EVI time series at sub-regional scale in southern Africa. International Journal of Applied Earth Observation and Geoinformation 38, 175-183.
- Tüshaus, J., Dubovyk, O., Khamzina, A., Menz, G., 2014. Comparison of Medium Spatial Resolution ENVISAT-MERIS and Terra-MODIS Time Series for Vegetation Decline Analysis: A Case Study in Central Asia. Remote Sensing 6, 5238-5256.
- Landmann, T., Dubovyk, O., 2014. Spatial analysis of human-induced vegetation productivity decline over eastern Africa using a decade (2001–2011) of medium resolution MODIS time-series data. International Journal of Applied Earth Observation and Geoinformation 33, 76-82.
- Conrad, C., Dech, S., Dubovyk, O., Fritsch, S., Klein, D., Löw, F., Schorcht, G., Zeidler, J., 2014. Derivation of temporal windows for accurate crop discrimination in heterogeneous croplands of Uzbekistan using multitemporal RapidEye images. Computers and Electronics in Agriculture 103, 63-74.
- Dubovyk, O., Menz, G., Conrad, C., Thonfeld, F., Khamzina, A., 2013. Object-based identification of vegetation cover decline in irrigated agro-ecosystems in Uzbekistan. Quaternary International 311, 163-174.
- Dubovyk, O., Menz, G., Conrad, C., Lamers, J., Lee, A., Khamzina, A., 2013. Spatial targeting of land rehabilitation: a relational analysis of cropland productivity decline in arid Uzbekistan. Erdkunde 67, 167-181.
- Dubovyk, O., Menz, G., Conrad, C., Kan, E., Machwitz, M., Khamzina, A., 2013. Spatio-temporal analyses of cropland degradation in the irrigated lowlands of Uzbekistan using remote-sensing and logistic regression modeling. Environmental Monitoring and Assessment 185, 4775-4790.
- Dubovyk, O., Sliuzas, R., Flacke, J., 2011. Spatio-temporal modelling of informal settlement development in Sancaktepe district, Istanbul, Turkey. ISPRS Journal of Photogrammetry and Remote Sensing 66, 235-246.
- König, S., Schultz, J., Dubovyk, O., Thonfeld, F., 2020. Assessment of Drought Effects on Forests using Non-Parametric Methods and Satellite Imagery. In: Publikationen der DGPF, 29, pp. 1-12. 40. Wissenschaftlich-Technische Jahrestagung der DGPF, 04.-06. März 2020, Stuttgart, Deutschland.
- Dubovyk, O., Ghazaryan, G., Graw, V., Löw, F., & Schreier, J., 2019. Spatial Assessment of Drought Hazard in Kazakhstan: Towards A Countrywide Drought Monitoring System. In: Proc. IEEE International Geoscience and Remote Sensing Symposium, 28 July-2 August 2019, Tokyo.
- Ghazaryan, G., Dubovyk, O., Graw, V., and Schellberg, J., 2018. Vegetation monitoring with satellite time series: an integrated approach for user-oriented knowledge extraction. In: Proc. SPIE Remote Sensing, 10-13 September 2018, Berlin.
- Graw, V., Ghazaryan, G., Schreier, J., Gonzalez, J., Abdel-Hamid, A., Walz, Y., Dall, K., Post, J., Jordaan, A., Dubovyk, O., 2018. Timing is Everything - Drought Classification for Risk Assessment. In: Proc. IEEE International Geoscience and Remote Sensing Symposium, 22-27 July 2018, Valencia.
- Lavreniuk, M., Kussul, N., Shelestov, A., Dubovyk, O., Löw, F., 2018. Object-Based postprocessing method for crop classification maps. In: Proc. IEEE International Geoscience and Remote Sensing Symposium, 22-27 July 2018, Berlin.
- Landmann, T., Dubovyk, O., Ghazaryan, G., Kimani, J., Abdel-Rahman, E., 2017. Wide-area mapping of invasive species propagation and containment zones in Somaliland using phenometric trends and generalized linear modeling. In: Proc. IEEE International Geoscience and Remote Sensing Symposium, 23-28 July 2017, Milan.
- Zimmermann, S.; Oldenburg, C.; Pape, R., Dubovyk, O., Löffler, J., 2017. Lichen cover mapping in southern Norway - a multi-scale analysis with remote sensing and GIS. In: Proc. Environmental Informatics, EnviroInfo 2017, 13-5 September, Luxemburg.
- Dubovyk, O., Landmann, T., Erasmus, B., Thonfeld, F., Schellberg, J., Menz, G., 2015. Observing vegetation dynamics at medium spatial scale: Lessons from Africa and Asia. In: Proc. IEEE International Geoscience and Remote Sensing Symposium, 27-31 July 2015, Milan.
- Thonfeld, F., Schmidt, M., Dubovyk, O., Menz, G., 2015. On the relevance of radiometric normalization of dense Landsat time series for forest monitoring. In: Proc. IEEE International Geoscience and Remote Sensing Symposium, 27-31 July 2015, Milan.
- Landmann, T., and Dubovyk, O., 2013. Mapping vegetation productivity dynamics and degradation trends over East Africa using a decade of medium Resolution MODIS time-series data. In: Proc. IEEE International Geoscience and Remote Sensing Symposium, 21-26 July 2013, Melbourne.
- Dubovyk, O., Conrad, C., Menz, G., and Khamzina, A., 2013. Object-Based Retro-Classification of Agricultural Land Use: A Case Study of Irrigated Croplands. In: Proc. ESA Living Planet Symposium 2013, (ESA SP-722, December 2013), 9-13 September 2013, Edinburgh.
- Dubovyk, O., Menz, G., and Khamzina, A., 2012. Trend analysis of MODIS time-series using different vegetation indices for monitoring of cropland degradation and abandonment in Central Asia. In: Proc. IEEE International Geoscience and Remote Sensing Symposium, 22-27 July 2012, Munich.
- Dubovyk, O., Menz, G., Conrad, C., & Khamzina, A., 2012. Object-based cropland degradation identification: a case study in Uzbekistan. In: Proc. SPIE Remote Sensing (vol. 8538), 24-27 September 2012, Edinburgh.
- Dubovyk, O., Tüschaus, J., Menz, G., and Khamzina, A., 2012. Monitoring vegetation trends with MERIS time series in arid irrigated landscapes of Central Asia. In: Proc. The 3rd MERIS/(A) ATSR&OLCI / SLSTR Preparatory Workshop, 15-19 October 2012, Frascati.
- Graw, V., Dubovyk, O., Duguru, M., Heid, P., Ghazaryan, G., Villagrán de León, J.C., Post, J., Szarzynski, J., Tsegai, D., and Walz, Y., 2019. Chapter 9 - Assessment, monitoring, and early warning of droughts: the potential for satellite remote sensing and beyond, in Mapedza, E., Tsegai, D., Bruntrup, M., and McLeman, R. (Eds.), Current Directions in Water Scarcity Research. Elsevier, pp. 115-131
- Dubovyk, O., 2018. Spatiotemporal Assessment of Vegetation Trends in Post-Soviet Central Asia. in: Egamberdieva, D., Öztürk, M. (Eds), Vegetation of Central Asia and Environs. Springer International Publishing, pp. 1-13.
- Mirzabaev, A., Goedecke, J., Dubovyk, O., Djanibekov, U., Le, Q., Aw-Hassan, A. (2016). Economics of Land Degradation in Central Asia, in: Nkonya, E., Mirzabaev, A., von Braun, J. (Eds.), Economics of Land Degradation and Improvement – A Global Assessment for Sustainable Development. Springer International Publishing, pp. 261-290.
- Aw-Hassan, A., Korol, V., Nishanov, N., Djanibekov, U., Dubovyk, O., Mirzabaev, A., 2016. Economics of Land Degradation and Improvement in Uzbekistan, in: Nkonya, E., Mirzabaev, A., von Braun, J. (Eds.), Economics of Land Degradation and Improvement – A Global Assessment for Sustainable Development. Springer International Publishing, pp. 651-682.
- Dubovyk, O., 2017. Remote Sensing of land degradation. Habilitation thesis. Bonn, University of Bonn.
- Dubovyk, O., 2013. Multi-scale targeting of land degradation in northern Uzbekistan using satellite remote sensing. PhD thesis. Bonn, University of Bonn.
- Dubovyk, O., 2010. Spatio-temporal analysis of informal settlements development. A case study of Istanbul, Turkey. MSc thesis. Enschede, University of Twente.
Sensing Biodiversity Across Scales (SEBAS)
The project "SEnsing Biodiversity Across Scales (SEBAS)" in DFG Priority Programme 1374 – "Biodiversity Exploratories" was raised by Olena Dubovyk (PI) and Anja Linstädter (co-PI) (University of Postdam, Germany).
In the past decades, most grassland ecosystems in Central Europe were transformed by higher fertilization rates in combination with increased frequencies of mowing or grazing. While this land-use intensification improved the delivery of the Ecosystem Service (ES) of forage, it has in many cases decreased biodiversity and the delivery of other ESs. In this context, there is an urgent need for a more mechanistic understanding of land-use effects on the biodiversity-ecosystem functioning (BEF) and the biodiversity-ecosystem service (BES) relationship. Due to inherent spatial mismatches between ecological processes and management units in coupled social-ecological systems, though, this is a challenging task. In our proposed project SEBAS, we aim at improving this mechanistic understanding by integrating site-based ecological research on land-use intensity and six ‘essential biodiversity variables (EBVs) with satellite Remote Sensing of these proxies. We will specifically explore linkages between functional and structural diversity and the ecosystem service of forage production, focusing on observation units relevant for decision-making, i.e. meadows/pastures, farms, and landscapes. We hypothesize that (i) the five EBVs as affected by different land-use intensities could be derived at multiple spatial scales using multi-modal satellite image time series data calibrated and validated with existing and newly collected data on land-use intensity and EBVs; and that (ii) land-use effects on BEF/BES relationships will vary across spatial scales, with functional and structural diversity playing a key role for the supply and temporal stability of forage production. The output of the project will be a set of spatially explicit satellite and unmanned aerial vehicle based EBVs products, as well as novel methodologies relying on a number of multi-scale and multi-modal Remote Sensing datasets (PlanetScope, RapidEye, Sentinel 1/2, Landsat and MODIS) and novel machine learning and hybrid models. Via space-for-time substitutions for climate change and land-use change, we will also address interactive effects of these two main drivers of global change on the BEF/BES relationship. We will formalize drivers’ direct and indirect (biodiversity-mediated) effects on forage production through a social-ecological systems approach, and quantify them via structural equation models to foster a deeper understanding of ecosystem functioning and ES supply in Central European grasslands.
For further information, please contact: Olena Dubovyk
The project website is here.