Data underlying the PhD thesis of Stefanie Steinbach: Sustainable Use of African Wetlands for Food Security: A Spatial Evaluation Approach

This dataset includes data and codes underlying the PhD thesis of Stefanie Steinbach: Sustainable Use of African Wetlands for Food Security: A Spatial Evaluation Approach. The dataset uses and complements the data published in the four articles constituting the core part of the thesis. Chapter 2: Dataset containing four wetland data layers that were created and analyzed in the study - https://doi.org/10.5281/zenodo.4326702 Steinbach, S., Cornish, N., Franke, J., Hentze, K., Strauch, A., Thonfeld, F., Zwart, S.J., Nelson, A., 2021. A New Conceptual Framework for Integrating Earth Observation in Large-scale Wetland Management in East Africa. Wetlands 41, 93. https://doi.org/10.1007/s13157-021-01468-9 Chapter 3: Dataset with the layer that was created and analyzed in the study - https://doi.org/10.5281/zenodo.14247305 Steinbach, S., Hentschel, E., Hentze, K., Rienow, A., Umulisa, V., Zwart, S.J., Nelson, A., 2023. Automatization and evaluation of a remote sensing-based indicator for wetland health assessment in East Africa on national and local scales. Ecol. Inform. 75, 102032. https://doi.org/10.1016/j.ecoinf.2023.102032 Chapter 4: Dataset with measurement locations and in-situ turbidity measurement values - https://doi.org/10.5281/zenodo.14275713 Steinbach, S., Rienow, A., Chege, M.W., Dedring, N., Kipkemboi, W., Thiong’o, B.K., Zwart, S.J., Nelson, A., 2024. Low-Cost Sensors and Multitemporal Remote Sensing for Operational Turbidity Monitoring in an East African Wetland Environment. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 17, 8490–8508. https://doi.org/10.1109/JSTARS.2024.3381756 Chapter 5: Scripts and workflow applied to retrieve and analyze remote sensing-based small reservoir turbidity - https://doi.org/10.5281/zenodo.14245504 Steinbach, S., Bartels, A., Rienow, A., Thiong’o, B.K., Zwart, S.J., Nelson, A. Predicting Turbidity Dynamics in Small Reservoirs in Central Kenya Using Remote Sensing and Machine Learning. International Journal of Applied Earth Observation and Geoinformation - Under review