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A multi-scale remote sensing approach to understanding vegetation dynamics in the Nama Karoo-Grassland ecotone of South Africa

Ndyamboti, Khule and de Toit, J. and Baade, Jussi and Kaiser, Andreas and Urban, Marcel and Schmullius, Christiane and Thiel, Christian and Berger, Christian (2020) A multi-scale remote sensing approach to understanding vegetation dynamics in the Nama Karoo-Grassland ecotone of South Africa. In: 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020. IEEE. 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020-09-26 - 2020-10-02, Weikoloa, USA. doi: 10.1109/IGARSS39084.2020.9323460. ISBN 978-172816374-1. ISSN 2153-6996.

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Abstract

In this paper, we propose a methodology for upscaling fractional vegetation cover (FVC) estimates derived from unmanned aerial vehicles (UAVs) to a larger area using freely available Sentinel-1/2 and Landsat-8 satellite data in the semi-arid Nama-Karoo biome of South Africa. To the best of our knowledge, such an approach is still lacking yet critical for understanding human-environment interactions, degradation, and the impacts of climate change in this vulnerable dryland ecosystem. The proposed approach utilizes ultra-high spatial resolution UAV imagery (i.e. < 5 cm) to develop a high quality FVC product. The resulting product is then used to upscale and validate satellite-based estimates of FVC. The rationale for upscaling UAV estimates to the satellite-scale is not only to cover larger areas but also to exploit historical satellite times series data, in an attempt to understand past trends and vegetation dynamics in the Nama Karoo-Grassland ecotone. The proposed method is expected to produce the first-ever high-resolution continuous maps of FVC and its changes in the above-mentioned ecosystem. Such information is of vital importance as it could help decision makers to gain a better understanding of the extent at which mechanisms such as bush encroachment, grassland expansion, or degradation are occurring in dryland ecosystems.

Item URL in elib:https://elib.dlr.de/139898/
Document Type:Conference or Workshop Item (Speech)
Title:A multi-scale remote sensing approach to understanding vegetation dynamics in the Nama Karoo-Grassland ecotone of South Africa
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Ndyamboti, KhuleFriedrich-Schiller-Universität JenaUNSPECIFIEDUNSPECIFIED
de Toit, J.Grootfontein Agriculture Development Institute, MiddelburgUNSPECIFIEDUNSPECIFIED
Baade, JussiFriedrich-Schiller-Universität JenaUNSPECIFIEDUNSPECIFIED
Kaiser, AndreasFriedrich-Schiller-Universität JenaUNSPECIFIEDUNSPECIFIED
Urban, MarcelFriedrich-Schiller-Universität JenaUNSPECIFIEDUNSPECIFIED
Schmullius, ChristianeFriedrich-Schiller-Universität JenaUNSPECIFIEDUNSPECIFIED
Thiel, ChristianUNSPECIFIEDhttps://orcid.org/0000-0001-5144-8145UNSPECIFIED
Berger, ChristianUniversität JenaUNSPECIFIEDUNSPECIFIED
Date:26 September 2020
Journal or Publication Title:2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI:10.1109/IGARSS39084.2020.9323460
Publisher:IEEE
Series Name:Proceedings of International Geoscience and Remote Sensing Symposium IGARSS
ISSN:2153-6996
ISBN:978-172816374-1
Status:Published
Keywords:Upscaling, fractional cover, vegetation dynamics, monitoring, Karoo, UAV, TLS, Sentinel, Landsat
Event Title:2020 IEEE International Geoscience and Remote Sensing Symposium
Event Location:Weikoloa, USA
Event Type:international Conference
Event Start Date:26 September 2020
Event End Date:2 October 2020
Organizer:IEEE
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:other
DLR - Research area:Raumfahrt
DLR - Program:R - no assignment
DLR - Research theme (Project):R - no assignment
Location: Jena
Institutes and Institutions:Institute of Data Science > Citizen Science
Deposited By: Thiel, Christian
Deposited On:08 Sep 2025 13:15
Last Modified:09 Sep 2025 10:58

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