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Comparing the dry season in-situ leaf area index (lai) derived from high-resolution rapideye imagery with MODIS LAI in a Namibian savanna

DOI zum Zitieren dieses Dokuments: https://doi.org/10.3390/rs70404834

Title data

Mayr, Manuel J. ; Samimi, Cyrus:
Comparing the dry season in-situ leaf area index (lai) derived from high-resolution rapideye imagery with MODIS LAI in a Namibian savanna.
In: Remote Sensing. Vol. 7 (2015) Issue 4 . - pp. 4834-4857.
ISSN 2072-4292
DOI: https://doi.org/10.3390/rs70404834

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Abstract

The Leaf Area Index (LAI) is one of the most frequently applied measures to characterize vegetation and its dynamics and functions with remote sensing. Satellite missions, such as NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) operationally produce global datasets of LAI. Due to their role as an input to large-scale modeling activities, evaluation and verification of such datasets are of high importance. In this context, savannas appear to be underrepresented with regards to their heterogeneous appearance (e.g., tree/grass-ratio, seasonality). Here, we aim to examine the LAI in a heterogeneous savanna ecosystem located in Namibia's Owamboland during the dry season. Ground measurements of LAI are used to derive a high-resolution LAI model with RapidEye satellite data. This model is related to the corresponding MODIS LAI/FPAR (Fraction of Absorbed Photosynthetically Active Radiation) scene (MOD15A2) in order to evaluate its performance at the intended annual minimum during the dry season. Based on a field survey we first assessed vegetation patterns from species composition and elevation for 109 sites. Secondly, we measured in situ LAI to quantitatively estimate the available vegetation (mean = 0.28). Green LAI samples were then empirically modeled (LAI<inf>model</inf>) with high resolution RapidEye imagery derived Difference Vegetation Index (DVI) using a linear regression (R2 = 0.71). As indicated by several measures of model performance, the comparison with MOD15A2 revealed moderate consistency mostly due to overestimation by the aggregated LAI<inf>model</inf>. Model constraints aside, this study may point to important issues for MOD15A2 in savannas concerning the underlying MODIS Land Cover product (MCD12Q1) and a potential adjustment by means of the MODIS Burned Area product (MCD45A1). © 2015 by the authors; licensee MDPI, Basel, Switzerland.

Further data

Item Type: Article in a journal
Keywords: dry season; savanna; Leaf Area Index; vegetation pattern; RapidEye; MOD15A2; empirical modeling; Namibia
DDC Subjects: 500 Science > 500 Natural sciences
500 Science > 550 Earth sciences, geology
Institutions of the University: Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Professorship Climatology
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Professorship Climatology > Professorship Climatology - Univ.-Prof. Dr. Cyrus Samimi
Profile Fields > Advanced Fields > African Studies
Profile Fields > Advanced Fields > Ecology and the Environmental Sciences
Faculties
Faculties > Faculty of Biology, Chemistry and Earth Sciences
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences
Profile Fields
Profile Fields > Advanced Fields
Language: English
Originates at UBT: Yes
Date Deposited: 30 May 2016 07:44
Last Modified: 08 Feb 2017 10:44
URI: https://epub.uni-bayreuth.de/id/eprint/3123

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