{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T19:04:46Z","timestamp":1774638286135,"version":"3.50.1"},"reference-count":78,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2018,9,17]],"date-time":"2018-09-17T00:00:00Z","timestamp":1537142400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010661","name":"Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["640176"],"award-info":[{"award-number":["640176"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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 Ni\u00f1o event. To investigate spatiotemporal dynamics of surface moisture and vegetation structure, data from ESA\u2019s Copernicus Sentinel-1\/-2 and NASA\u2019s Landsat-8 for the period between March 2015 and November 2017 were 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\u2014VV) 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\u2013optical 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.<\/jats:p>","DOI":"10.3390\/rs10091482","type":"journal-article","created":{"date-parts":[[2018,9,17]],"date-time":"2018-09-17T10:42:20Z","timestamp":1537180940000},"page":"1482","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":78,"title":["Surface Moisture and Vegetation Cover Analysis for Drought Monitoring in the Southern Kruger National Park Using Sentinel-1, Sentinel-2, and Landsat-8"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0127-2804","authenticated-orcid":false,"given":"Marcel","family":"Urban","sequence":"first","affiliation":[{"name":"Department for Earth Observation, Institute of Geography, Friedrich-Schiller-University Jena, Loebdergraben 32, 07743 Jena, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6793-4073","authenticated-orcid":false,"given":"Christian","family":"Berger","sequence":"additional","affiliation":[{"name":"Department for Earth Observation, Institute of Geography, Friedrich-Schiller-University Jena, Loebdergraben 32, 07743 Jena, Germany"}]},{"given":"Tami E.","family":"Mudau","sequence":"additional","affiliation":[{"name":"CSIR (Council for Scientific and Industrial Research), Meiring Naud\u00e9 Road, Brummeria, Pretoria 0184, South Africa"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5789-2615","authenticated-orcid":false,"given":"Kai","family":"Heckel","sequence":"additional","affiliation":[{"name":"Department for Earth Observation, Institute of Geography, Friedrich-Schiller-University Jena, Loebdergraben 32, 07743 Jena, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7259-101X","authenticated-orcid":false,"given":"John","family":"Truckenbrodt","sequence":"additional","affiliation":[{"name":"Department for Earth Observation, Institute of Geography, Friedrich-Schiller-University Jena, Loebdergraben 32, 07743 Jena, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1213-4095","authenticated-orcid":false,"given":"Victor","family":"Onyango Odipo","sequence":"additional","affiliation":[{"name":"Department for Earth Observation, Institute of Geography, Friedrich-Schiller-University Jena, Loebdergraben 32, 07743 Jena, Germany"}]},{"given":"Izak P. J.","family":"Smit","sequence":"additional","affiliation":[{"name":"Scientific Services, South African National Parks, Private Bag X402, Skukuza 1350, South Africa"},{"name":"Centre for African Ecology, School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Private Bag 3, Wits 2050, South Africa"}]},{"given":"Christiane","family":"Schmullius","sequence":"additional","affiliation":[{"name":"Department for Earth Observation, Institute of Geography, Friedrich-Schiller-University Jena, Loebdergraben 32, 07743 Jena, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2018,9,17]]},"reference":[{"key":"ref_1","unstructured":"RIASCO (Regional Interagency Standing Committee) (2018, September 14). Response Plan for the El Ni\u00f1o-Induced Drought in Southern Africa. Available online: https:\/\/reliefweb.int\/report\/world\/riasco-action-plan-southern-africa-response-plan-el-ni-o-induced-drought-southern."},{"key":"ref_2","unstructured":"Liberto, T. 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