Logo

Sub-pixel analysis to enhance the accuracy of evapotranspiration determined using MODIS images

Hassaballa, A.A. and Matori, A.-N. and Al-Gaadi, K.A. and Tola, E.H. and Madugundu, R. (2017) Sub-pixel analysis to enhance the accuracy of evapotranspiration determined using MODIS images. International Journal of Agricultural and Biological Engineering, 10 (2). pp. 103-113.

Full text not available from this repository.

Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

A study was carried out to estimate the actual evapotranspiration (ET) over a 1074 km2 of the humid area of Perak State (Malaysia), where water and evaporation cycle deeply influences the climate, natural resources and human living aspects. Images from both Terra and Aqua platforms of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor were used for ET estimation by employing the Surface Energy Balance Algorithm for Land (SEBAL) model. As a part of the accuracy assessment process, in-situ measurements on soil temperature and reference ET (ET0) were recorded at the time of satellite overpass. In order to enhance the accuracy of the generated ET maps, MODIS images were subjected to sub-pixel analysis by assigning weights for different surface cover (urban, agriculture and multi-surface areas) reflections. The weightage process was achieved by integrating ET from pure pixels with the respective site-specific ET0 of each land cover. The enhanced SEBAL model estimated ET exhibited a good correlation with the in-situ measured Penman-Montieth ET0, with R2 values for the Aqua and the Terra platforms of 0.67 and 0.73, respectively. However, the correlation of the non-enhanced ET maps resulted in R2 values of 0.61 and 0.68 for the Aqua and the Terra platforms, respectively. Hence, the results of this study revealed the feasibility of employing the sub-pixel analysis method for an accurate estimation of ET over large areas. © 2017, Chinese Society of Agricultural Engineering. All rights reserved.

Item Type:Article
Impact Factor:cited By 0
Departments / MOR / COE:Division > Academic > Faculty of Engineering > Civil Engineering
ID Code:19776
Deposited By: Ahmad Suhairi
Deposited On:20 Apr 2018 07:43
Last Modified:20 Apr 2018 07:43

Repository Staff Only: item control page