Surface moisture and vegetation cover analysis for drought monitoring in the southern Kruger National Park using Sentinel-1, Sentinel-2, and Landsat-8

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dc.contributor.author Urban, M.
dc.contributor.author Berger, C.
dc.contributor.author Mudau, T.E.
dc.contributor.author Heckel, K.
dc.contributor.author Truckenbrodt, J.
dc.contributor.author Odipo, V.O.
dc.contributor.author Smit, I.P.J.
dc.date.accessioned 2020-01-15T14:30:43Z
dc.date.available 2020-01-15T14:30:43Z
dc.date.issued 2018-09
dc.identifier.citation Urban, M. et al. 2018. Surface moisture and vegetation cover analysis for drought monitoring in the southern Kruger National Park using Sentinel-1, Sentinel-2, and Landsat-8.Remote Sensing 10(9), Article number 1482 en_ZA
dc.identifier.issn 2072-4292(PRINT)
dc.identifier.issn 2072-4292(ONLINE)
dc.identifier.uri https://hdl.handle.net/10539/28748
dc.description.abstract During the southern summer season of 2015 and 2016, South Africa experienced one of the most severe meteorological droughts since the start of climate recording, due to an exceptionally strong El Niño event. To investigate spatiotemporal dynamics of surface moisture and vegetation structure, data from ESA's Copernicus Sentinel-1/-2 and NASA's Landsat-8 for the period between March 2015 and November 2017were utilized. In combination, these radar and optical satellite systems provide promising data with high spatial and temporal resolution. Sentinel-1 C-band data was exploited to derive surface moisture based on a hyper-temporal co-polarized (vertical-vertical-VV) radar backscatter change detection approach, describing dynamics between dry and wet seasons. Vegetation information from a TLS (Terrestrial Laser Scanner)-derived canopy height model (CHM), as well as the normalized difference vegetation index (NDVI) from Sentinel-2 and Landsat-8, were utilized to analyze vegetation structure types and dynamics with respect to the surface moisture index (SurfMI). Our results indicate that our combined radar-optical approach allows for a separation and retrieval of surface moisture conditions suitable for drought monitoring. Moreover, we conclude that it is crucial for the development of a drought monitoring system for savanna ecosystems to integrate land cover and vegetation information for analyzing surface moisture dynamics derived from Earth observation time series. en_ZA
dc.language.iso en en_ZA
dc.publisher MDPI en_ZA
dc.rights © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). en_ZA
dc.subject Space-based radar en_ZA
dc.subject Drought en_ZA
dc.subject Drought monitoring en_ZA
dc.subject Dynamics en_ZA
dc.subject LANDSAT en_ZA
dc.subject Ecosystems en_ZA
dc.subject Savanna ecosystems en_ZA
dc.subject NASA en_ZA
dc.subject Surface moistures en_ZA
dc.subject Vegetation en_ZA
dc.title Surface moisture and vegetation cover analysis for drought monitoring in the southern Kruger National Park using Sentinel-1, Sentinel-2, and Landsat-8 en_ZA
dc.type Article en_ZA
dc.journal.volume 10 en_ZA
dc.journal.title Remote Sensing en_ZA
dc.description.librarian NLB2020 en_ZA
dc.citation.doi 10.3390/rs10091482 en_ZA
dc.funder European Union (EU) Horizon 2020 Research and Innovation Program, Deutscher Akademischer Austauschdienst (DAAD) etc. en_ZA
dc.journal.issue 9 en_ZA
dc.faculty Faculty of Science en_ZA


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