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Annual Grass Biomass Mapping with Landsat-8 and Sentinel-2 Data over Kruger National Park, South Africa

Berger, Christian and Lux, Harald and Urban, Marcel and Baade, Jussi and Schmullius, Christiane and Thiel, Christian and Wigley-Coetsee, Corli and Smit, Izak (2020) Annual Grass Biomass Mapping with Landsat-8 and Sentinel-2 Data over Kruger National Park, South Africa. Proceedings of International Geoscience and Remote Sensing Symposium IGARSS. IEEE.

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Abstract

This study explores the potential of Landsat-8 and Sentinel-2 imagery for annual grass biomass mapping in savannas. To this end, three wet season image mosaics based on Landsat-8 and Sentinel-2 were created for 2016, 2017 and 2018 over Kruger National Park (KNP), South Africa. For the purpose of calibration and validation, use was made of in situ fuel biomass values measured as part of the yearly veld condition assessment (VCA) in KNP. The satellite and reference data were fed into a random forests machine learning approach to make park-wide predictions of grass biomass and to assess the performance of Landsat-8 and Sentinel-2 predictors (i.e., surface reflectance and the normalized difference vegetation index, NDVI). Examples of the data sets used and biomass maps produced are provided together with the obtained error statistics. The latter suggest that wet season NDVI mosaics from Landsat-8 and Sentinel-2 data enable the creation of fairly reliable, annual maps of fuel biomass for KNP. These new biomass estimates represent a slight improvement over recent mapping efforts based on Sentinel-1 data.

Item URL in elib:https://elib.dlr.de/139902/
Document Type:Editorship of Proceedings
Title:Annual Grass Biomass Mapping with Landsat-8 and Sentinel-2 Data over Kruger National Park, South Africa
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Berger, ChristianUniversität JenaUNSPECIFIED
Lux, HaraldUniversität JenaUNSPECIFIED
Urban, MarcelUniversität JenaUNSPECIFIED
Baade, JussiFriedrich-Schiller-Universität JenaUNSPECIFIED
Schmullius, ChristianeFriedrich-Schiller-Universität JenaUNSPECIFIED
Thiel, ChristianChristian.Thiel (at) dlr.dehttps://orcid.org/0000-0001-5144-8145
Wigley-Coetsee, CorliSANParksUNSPECIFIED
Smit, IzakSANParksUNSPECIFIED
Date:26 September 2020
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Publisher:IEEE
Series Name:Proceedings of International Geoscience and Remote Sensing Symposium IGARSS
Status:Published
Keywords:Grass, biomass, mapping, national park, Sentinel, Landsat, machine learning, savanna, South Africa
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:04 Jan 2021 12:27
Last Modified:04 Jan 2021 12:27

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