Next Article in Journal
Retrieval of Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) from VIIRS Time-Series Data
Previous Article in Journal
Advancements for Snowmelt Monitoring by Means of Sentinel-1 SAR
Open AccessArticle

A Combined Satellite-Derived Drought Indicator to Support Humanitarian Aid Organizations

1
Department of Geodesy and Geoinformation (GEO), Vienna University of Technology (TU Wien), Vienna 1040, Austria
2
International Institute for Applied Systems Analysis (IIASA), Ecosystems Services and Management (ESM) Group, Laxenburg 2361, Austria
3
Institute of Surveying, Remote Sensing and Land Information, University of Natural Resources and Life Sciences (BOKU), Vienna 1180, Austria
4
ZAMG, Vienna 1190, Austria
5
Doctors without Borders, Médecins Sans Frontières (MSF), Austrian Section, Vienna 1020, Austria
*
Author to whom correspondence should be addressed.
Academic Editors: Yoshio Inoue and Prasad S. Thenkabail
Remote Sens. 2016, 8(4), 340; https://doi.org/10.3390/rs8040340
Received: 14 October 2015 / Revised: 29 March 2016 / Accepted: 6 April 2016 / Published: 20 April 2016
Governments, aid organizations and researchers are struggling with the complexity of detecting and monitoring drought events, which leads to weaknesses regarding the translation of early warnings into action. Embedded in an advanced decision-support framework for Doctors without Borders (Médecins sans Frontières), this study focuses on identifying the added-value of combining different satellite-derived datasets for drought monitoring and forecasting in Ethiopia. The core of the study is the improvement of an existing drought index via methodical adaptations and the integration of various satellite-derived datasets. The resulting Enhanced Combined Drought Index (ECDI) links four input datasets (rainfall, soil moisture, land surface temperature and vegetation status). The respective weight of each input dataset is calculated for every grid point at a spatial resolution of 0.25 degrees (roughly 28 kilometers). In the case of data gaps in one input dataset, the weights are automatically redistributed to other available variables. Ranking the years 1992 to 2014 according to the ECDI-based warning levels allows for the identification of all large-scale drought events in Ethiopia. Our results also indicate a good match between the ECDI-based drought warning levels and reported drought impacts for both the start and the end of the season. View Full-Text
Keywords: remote sensing; drought monitoring; drought index; food security remote sensing; drought monitoring; drought index; food security
Show Figures

Graphical abstract

MDPI and ACS Style

Enenkel, M.; Steiner, C.; Mistelbauer, T.; Dorigo, W.; Wagner, W.; See, L.; Atzberger, C.; Schneider, S.; Rogenhofer, E. A Combined Satellite-Derived Drought Indicator to Support Humanitarian Aid Organizations. Remote Sens. 2016, 8, 340. https://doi.org/10.3390/rs8040340

AMA Style

Enenkel M, Steiner C, Mistelbauer T, Dorigo W, Wagner W, See L, Atzberger C, Schneider S, Rogenhofer E. A Combined Satellite-Derived Drought Indicator to Support Humanitarian Aid Organizations. Remote Sensing. 2016; 8(4):340. https://doi.org/10.3390/rs8040340

Chicago/Turabian Style

Enenkel, Markus; Steiner, Caroline; Mistelbauer, Thomas; Dorigo, Wouter; Wagner, Wolfgang; See, Linda; Atzberger, Clement; Schneider, Stefan; Rogenhofer, Edith. 2016. "A Combined Satellite-Derived Drought Indicator to Support Humanitarian Aid Organizations" Remote Sens. 8, no. 4: 340. https://doi.org/10.3390/rs8040340

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop