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Journal of Applied Remote Sensing

Effect of spatial resolution on remote sensing estimation of total evaporation in the uMngeni catchment, South Africa
Author(s): Cletah Shoko; David Clark; Michael Mengistu; Timothy Dube; Hartley Bulcock
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Paper Abstract

This study evaluated the effect of two readily available multispectral sensors: the newly launched 30 m spatial resolution Landsat 8 and the long-serving 1000 m moderate resolution imaging spectroradiometer (MODIS) datasets in the spatial representation of total evaporation in the heterogeneous uMngeni catchment, South Africa, using the surface energy balance system model. The results showed that sensor spatial resolution plays a critical role in the accurate estimation of energy fluxes and total evaporation across a heterogeneous catchment. Landsat 8 estimates showed better spatial representation of the biophysical parameters and total evaporation for different land cover types, due to the relatively higher spatial resolution compared to the coarse spatial resolution MODIS sensor. Moreover, MODIS failed to capture the spatial variations of total evaporation estimates across the catchment. Analysis of variance (ANOVA) results showed that MODIS-based total evaporation estimates did not show any significant differences across different land cover types (one-way ANOVA; F1.924=1.412, p=0.186). However, Landsat 8 images yielded significantly different estimates between different land cover types (one-way ANOVA; F1.993=5.185, p<0.001). The validation results showed that Landsat 8 estimates were more comparable to eddy covariance (EC) measurements than the MODIS-based total evaporation estimates. EC measurement on May 23, 2013, was 3.8  mm/day, whereas the Landsat 8 estimate on the same day was 3.6  mm/day, with MODIS showing significantly lower estimates of 2.3  mm/day. The findings of this study underscore the importance of spatial resolution in estimating spatial variations of total evaporation at the catchment scale, thus, they provide critical information on the relevance of the readily available remote sensing products in water resources management in data-scarce environments.

Paper Details

Date Published: 14 October 2015
PDF: 21 pages
J. Appl. Remote Sens. 9(1) 095997 doi: 10.1117/1.JRS.9.095997
Published in: Journal of Applied Remote Sensing Volume 9, Issue 1
Show Author Affiliations
Cletah Shoko, Univ. of KwaZulu-Natal (South Africa)
David Clark, Univ. of KwaZulu-Natal (South Africa)
Michael Mengistu, Univ. of KwaZulu-Natal (South Africa)
Timothy Dube, Univ. of KwaZulu-Natal (South Africa)
Hartley Bulcock, Univ. of KwaZulu-Natal (South Africa)

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