
March, 2017 Int J Agric & Biol Eng Open Access at https://www.ijabe.org Vol. 10 No.2 103 Sub-pixel analysis to enhance the accuracy of evapotranspiration determined using MODIS images Abdalhaleem A. Hassaballa1*, Abdul-Nasir Matori2, Khalid A. Al-Gaadi1,3, Elkamil H. Tola1, Rangaswamy Madugundu1 (1. Precision Agriculture Research Chair (PARC), King Saud University, Riyadh 11451, Saudi Arabia; 2. Geoinformatics Cluster, Department of Civil Engineering, Universiti Tecknologi PETRONAS, Tronoh 31750, Malaysia; 3. Department of Agricultural Engineering, College of Food and Agriculture Sciences, King Saud University, Riyadh 11451, Saudi Arabia) 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 land surface cover (urban, agriculture and multi-surface areas) reflections. The weighting 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. Keywords: evapotranspiration, sub-pixel analysis, MODIS image, MODIS sensor, remote sensing, land surface cover DOI: 10.3965/j.ijabe.20171002.2890 Citation: Hassaballa A A, Matori A, Al-Gaadi K A, Tola E H, Madugundu R. Sub-pixel analysis to enhance the accuracy of evapotranspiration determined using MODIS images. Int J Agric & Biol Eng, 2017; 10(2): 103–113. based on the solar radiation fraction that hits the soil 1 Introduction surface. This fraction is decreasing as the crop evolves Evaporation and transpiration are two processes that and grows, where the crop canopy increasingly shades the concurrently take place and cannot be differentiated. ground surface beneath the plant. Water is mainly lost The amount of evaporation from croplands is principally through soil evaporation at germination and early stages of plant growth. When the crop is well toned and totally Received date: 2016-10-02 Accepted date: 2017-02-14 Biographies: Abdul-Nasir Matori, PhD, Associate Professor, covers the soil surface, the transpiration, which acts at the research interests: geomatics, Email: [email protected]; plants’ leaves and stomata, becomes the dominant water Khalid Ali Al-Gaadi, PhD, Professor, research interests: precision losses process from croplands[1]. agriculture, Email: [email protected]; Elkamil Hamed Tola, Investigating ET at regional scale becomes an PhD, Associate Professor, research interests: precision agriculture, Email: [email protected]; Rangaswamy Madugundu, important matter as it helps in understanding the global PhD, Assistant Professor, research interests: precision agriculture, changes in the environment as well as when planning to Email: [email protected] develop water supplies for agricultural schemes or/and *Corresponding author: Abdalhaleem Abdalla Hassaballa, PhD, Assistant Professor, research interests: precision agriculture. other related activities. In addition, ET analysis is Mailing address: P.O.Box 2460, Riyadh 11451, Saudi Arabia. Tel: always required to develop a hydrological model at any +966-114691943/542053994(M), Email: [email protected]. scale for a specific region[2-7]. 104 March, 2017 Int J Agric & Biol Eng Open Access at https://www.ijabe.org Vol. 10 No.2 Since the fundamental of satellite remote sensing is climatic conditions. The third one is the deterministic based on knowledge of the spectral response of surface method, which usually depends on more complicated entities, reflectance form vegetation cover and surface models such as Soil-Vegetation-Atmosphere Transfer temperature (Ts) are considered as the most important two models (SVAT). This model has been designed to parameters obtained from the optical and the thermal simulate the interaction between plant canopy processes spectral portions of the spectrum, respectively. and the environment, and to calculate different elements However, no intensive work has been devoted to study of energy budget[17]. The fourth method is the energy the relationship between vegetation and Ts with respect to balance equation, which is used for ET estimation land use/cover. This is because these two parameters (equivalent to the latent heat flux LE) using various are tightly correlated to both the moisture availability and surface properties such as albedo, leaf area index, [8] [18] the vegetation condition. Price pointed out that there vegetation indices and TS . would be no advantage of using sophisticated simulation The most issue hindering the measurement of ET at model for the estimation of ET, if the required surface ground stations is its dependency on some surface parameters are not available for the region. parameters that are so difficult to measure over large and Studies of remote sensing in estimating ET usually heterogeneous areas[2,19-22]. Thus, the effectiveness of include four basic common methods. The first one is such methods will not exceed the areas where parameters known as the simplified energy balance method, which is are measured. In addition, the ground-based estimation the basic formula initially extracted at field scale by of ET is considered as a vegetation-type-specific, and the Jackson[9], and later employed successfully by Pinker[10] estimation accuracy is affected by surface resistance, for mapping daily ET over large areas via surface which introduces more difficulties in applying the temperature measurements. This method was also found ground-based ET on a regional scale. to be very successful in estimating crop water use in On the other hand, the estimation of ET from the irrigated areas[11]. However, the estimation of energy multi-temporal resolution sensors such as MODIS balance components from the remotely sensed data (Moderate Resolution Imaging Spectroradiometer) and requires series of computations and site-specific NOAA (National Oceanic & Atmospheric Administration) meteorological data such as reference ET (ET0), vapor does not represent the real signature of surface features, pressure deficit, wind speed, relative humidity, net because of the coarse spatial resolution. As a result, the radiation, etc.[12] The second one is the empirical value of ET is always produced from a holistic land method, which is an empirical relationship between the surface cover within the image pixel, what leads to spectral variables measured from satellites and the ET. over/under estimations of ET. As examples, Idso[13] developed a linear relationship This study aimed particularly at providing an between evaporation and the net thermal radiation. In enhanced and cost-effective qualitative estimation of ET another study, Menenti[14] determined ET as a linear through the sub-pixel analysis. The study employed the function of the remote sensing estimated Ts and the weighting approach on ET maps of three different land surface albedo. Seguin and Itier[15] demonstrated that, at covers generated through the Surface Energy Balance a specific location, there is a strong relationship between Algorithm for Land (SEBAL). The three land cover [16] the midday TS and the daily ET. Also, Kerr identified classes included cultivated area (agriculture) represented a detailed relationship between the Normalized difference by Seberang Perak’s paddy field (SP), urban area vegetation index (NDVI) extracted from the NOAA High represented by Sitiawan (SITI) city and multi-cover area Resolution Picture Transmission (HRPT) data and the represented by a weather station allocated at the field of actual ET. Although the empirical methods are widely Universiti Teknologi PETRONAS (UTP). The study and successfully applied for ET estimation, most of them also intended to enhance the value of the MODIS satellite are site-specific and can’t be used for areas with different extracted TS through a correlation process against the soil March, 2017 Abdalhaleem H, et al. Sub-pixel analysis to enhance accuracy of evapotranspiration determination Vol. 10 No.2 105 temperature measured in-situ at the time of satellite and surrounded Manjung district from the southern side overpass. to the coast downstream. Perak Tengah district encompassed an area of 2 Materials and methods 1282.05 km2 comprised 11 localities. This district was 2.1 Study area located in the center of the state of Perak, in an elongated The study area covered two distinctive districts of shape from north to south, where the Sungai Perak River Perak state (Malaysia), which were Perak Tengah and spited it into two halves on the left and right. Manjung Manjung. The two neighbor districts lie between was surrounded by only two districts Kerian from the latitudes 4º00'-4º30'N and longitudes 100º30'-101º00'E north and Perak Tengah from the east, while the coastline (Figure 1) and separated by Sungai Perak (Perak River) occupied the remaining directions. The total area under which ran along the study area from the north to the south the study was about 1074 km2[23]. Figure 1 The study area with classified land use land cover map for surface representation 2.2 Topography, climate & Land use/land cover fields of paddy, oil palm and coconut managed by some The study area was occupied mainly by four types of agricultural companies.
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