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Remote Sens. 2019, 11(8), 898;

Impact of Soil Reflectance Variation Correction on Woody Cover Estimation in Kruger National Park Using MODIS Data

1,2,*, 1,3, Kevin Tansey 1,, 4,5 and 6
Centre for Landscape and Climate Research, School of Geography, Geology and the Environment, University of Leicester, Leicester LE1 7RH, UK
Department of Geography, Adamu Augie College of Education, PMB 1012, Argungu, Kebbi State, Nigeria
National Centre for Earth Observation, University of Leicester, Leicester LE1 7RH, UK
Ecosystems Earth Observation, Natural Resources and the Environment, Council for Scientific and Industrial Research, PO Box 395, Pretoria 0001, South Africa
Department of Geography, Geomatics and Meteorology, Private BagX20, Hatfield 0028, University of Pretoria, Pretoria 0001, South Africa
Graduate School of Global Environmental Studies, Kyoto University, Kyoto 606-8501, Japan
Author to whom correspondence should be addressed.
Received: 7 March 2019 / Revised: 3 April 2019 / Accepted: 10 April 2019 / Published: 12 April 2019
(This article belongs to the Special Issue Forest Health Monitoring)
PDF [923 KB, uploaded 12 April 2019]


Time-series of imagery acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) has previously been used to estimate woody and herbaceous vegetation cover in savannas. However, this is challenging due to the mixture of woody and herbaceous plant functional types with specific contributions to the phenological signal and variations in soil background reflectance signatures observed from satellite. These factors cause variations in the accuracy and precision of woody cover estimates from different modelling approaches and datasets. Here, woody cover is estimated over Kruger National Park (KNP) from the MODIS 16-day composite time-series data using dry season NDVI/SAVI images and applying NDVIsoil determination methods. The woody cover estimates when NDVIsoil was ignored had R² = 0.40, p < 0.01, slope = 1.01, RMSE (root mean square error) = 15.26% and R² = 0.32, p < 0.03, slope = 0.79, RMSE = 16.39% for NDVIpixel and SAVIpixel, respectively, when compared to field plot data of plant functional type fractional cover. The woody cover estimated from the soil determination methods had a slope closer to 1 for both NDVI and SAVI but also a slightly higher RMSE. For a soil-invariant method, RMSE = 19.04% and RMSE = 17.34% were observed for NDVI and SAVI respectively, while for a soil-variant method, RMSE = 18.28% and RMSE = 19.17% were found for NDVI and SAVI. The woody cover estimated from all models had a high correlation and significant relationship with LiDAR/SAR based estimates and a woody cover map produced by Bucini. Woody cover maps are required for vegetation succession monitoring, grazing impact assessment, climate change mitigation and adaptation research and dynamic vegetation model validation.
Keywords: Keywords soil reflectance; woody cover; phenology; MODIS; NDVI; SAVI Keywords soil reflectance; woody cover; phenology; MODIS; NDVI; SAVI

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Ibrahim, S.; Balzter, H.; Mathieu, R.; Tsutsumida, N. Impact of Soil Reflectance Variation Correction on Woody Cover Estimation in Kruger National Park Using MODIS Data. Remote Sens. 2019, 11, 898.

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