Mapping Evapotranspiration Coefficients in a Temperate Maritime Climate Using the METRIC Model and Landsat TM

Spiliotopoulos, Marios; Holden, Nicholas M.; Λουκάς, Αθανάσιος

doi:10.3390/w9010023

Cited by 15 publications

(11 citation statements)

References 59 publications

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“…It is imperative to perform independent validation of the methodology. For this reason, a new satellite image of Landsat ETM+, taken in 2015, was used to compare the ET r F values calculated by the proposed method and the respective values acquired using the METRIC methodology, which is considered as benchmark [58]. This is also supported by the fact that Earth Engine Evapotranspiration Flux (EEFlux), which is a web-based tool operating on the Google Earth Engine and computational cloud, uses the METRIC model as foundation [58,71].…”

Section: Validation Of the Methodologymentioning

confidence: 99%

“…EVI2 is a very convenient variation of Enhanced Vegetation Index (EVI) as explained in [49,56,57]. Those indices use only two spectral bands for their formulation, resulting in relatively easy processing, which is a very important parameter in choosing them for processing, along with previous experience [33,36,58]. The related formulas used for the computations of the above indices are:…”

Section: Landsat 7 Etm+ and In-situ Ger1500 Data Availabilitymentioning

confidence: 99%

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Hybrid Methodology for the Estimation of Crop Coefficients Based on Satellite Imagery and Ground-Based Measurements

Spiliotopoulos

Λουκάς

2019

Water

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The objective of the current study was the investigation of specific relationships between crop coefficients and vegetation indices (VI) computed at the water-limited environment of Lake Karla Watershed, Thessaly, in central Greece. A Mapping ET (evapotranspiration) at high Resolution and with Internalized Calibration (METRIC) model was used to derive crop coefficient values during the growing season of 2012. The proposed methodology was developed using medium resolution Landsat 7 ETM+ images and meteorological data from a local weather station. Cotton, sugar beets, and corn fields were utilized. During the same period, spectral signatures were obtained for each crop using the field spectroradiometer GER1500 (Spectra Vista Corporation, NY, U.S.A.). Relative spectral responses (RSR) were used for the filtering of the specific reflectance values giving the opportunity to match the spectral measurements with Landsat ETM+ bands. Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and Enhanced Vegetation Index 2 (EVI2) were then computed, and empirical relationships were derived using linear regression analysis. NDVI, SAVI, and EVI2 were tested separately for each crop. The resulting equations explained those relationships with a very high R2 value (>0.86). These relationships have been validated against independent data. Validation using a new image file after the experimental period gives promising results, since the modeled image file is similar in appearance to the initial one, especially when a crop mask is applied. The CROPWAT model supports those results when using the new crop coefficients to estimate the related crop water requirements. The main benefit of the new approach is that the derived relationships are better adjusted to the crops. The described approach is also less time-consuming because there is no need for atmospheric correction when working with ground spectral measurements.

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Section: Validation Of the Methodologymentioning

confidence: 99%

Section: Landsat 7 Etm+ and In-situ Ger1500 Data Availabilitymentioning

confidence: 99%

Hybrid Methodology for the Estimation of Crop Coefficients Based on Satellite Imagery and Ground-Based Measurements

Spiliotopoulos

Λουκάς

2019

Water

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“…(2011a, 2011b), Spiliotopoulos et al . (2017) and Mokhtari et al . (2019) state that a single cloud‐free satellite image is decent enough in the estimation of seasonal ET.…”

Section: Methodsmentioning

confidence: 97%

“…Since the study region is coastal buffered, due to high cloud cover and comparatively less temporal resolution, the number of Landsat image matches with the Sentinel overpass is relatively less. For each study year, we identified two Landsat that imbricated Sentinel considerably with little cloud cover except 2016 (Spiliotopoulos et al, 2017; Mokhtari et al ., 2019; Niu et al ., 2019; Runge and Grosse, 2019). There were hardly any changes observed on the site among the Landsat 8 and Sentinel 2 same‐day observations.…”

Section: Site Description and Data Usedmentioning

confidence: 99%

Satellite‐based regional‐scale evapotranspiration estimation mapping of the rice bowl of Tamil Nadu: A little water to spare^*

Hari

Tyagi

Huddar

et al. 2020

Irrigation and Drainage

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Improved regular and rapid monitoring techniques are needed to quantify evapotranspiration (ET) precisely on agricultural fields to enhance the efficient usage of water resources and protect water quality and the environment. This study proposes estimating and mapping ET using a vegetation index coupled with a crop coefficient estimation method over the famous rice bowl region of Tamil Nadu, India. The study utilized a very high‐resolution satellite—Sentinel—of resolution 10 m. The study is based on a crop coefficient—Normalized Difference Vegetation Index (NDVI)—based ET estimation, which is one of the most adaptable practical approaches in quantifying crop water usage in multiple phases of crop growth on a regional scale. The results have been further calibrated using the surface energy‐based Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) model to assess estimation correctness. The estimations analysed for the 2016–2019 kharif cropping season show good overall correlation with the coefficient of determination (R2) of ≥0.72, with mean bias error (MBE) of ≤0.0009 mm day−1 and root mean square error (RMSE) of ≤0.67 mm day−1, indicating a positive assessment of ET for the delta region of Tamil Nadu for reaching vindicable intendance of crop water in this region.

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“…Finally, it is important to indicate that the number of days with a complete data set (satellite images and EC fluxes) was limited by cloudiness when the satellite overpassed the experimental site and persistent noise of the EC system (instrumental problems and flow distortion through the tower). For these reasons, several researchers have used a limited number of images to evaluate the satellite-based remote sensing (SBRS) models [6,[45][46][47][48][49].…”

Section: Image Processingmentioning

confidence: 99%

Implementation of a Two-Source Model for Estimating the Spatial Variability of Olive Evapotranspiration Using Satellite Images and Ground-Based Climate Data

Fuentes-Peñailillo

Ortega-Farías

Acevedo-Opazo

et al. 2018

Water

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A study was carried out to evaluate the potential use of the two-source Shuttleworth and Wallace (SW) model to compute the intra-orchard spatial variability of actual evapotranspiration (ET) of olive trees using satellite images and ground-based climate data. The study was conducted in a drip-irrigated olive orchard using satellite images (Landsat 7 ETM+), which were acquired on clear sky days during the main phenological stages (2009/10 growing season). The performance of the SW model was evaluated using instantaneous latent heat flux (LE) measurements that were obtained from an eddy correlation system. At the time of satellite overpass, the estimated values of net radiation (Rn i) and soil heat flux (G i) were compared with ground measurements from a four-way net radiometer and soil heat flux plates, respectively. The results indicated that the SW model subestimated instantaneous LE (W m −2) and daily ET (mm d −1), with errors of 12% and 10% of observed values, respectively. The root mean square error (RMSE) and mean absolute error (MAE) values for instantaneous LE were 26 and 20 W m −2 , while those for daily values of ET were 0.31 and 0.28 mm d −1 , respectively. Finally, the submodels computed Rn i and G i with errors of between 4.0% and 8.0% of measured values and with RMSE and MAE between 25 and 39 W m −2 .

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Mapping Evapotranspiration Coefficients in a Temperate Maritime Climate Using the METRIC Model and Landsat TM

Cited by 15 publications

References 59 publications

Hybrid Methodology for the Estimation of Crop Coefficients Based on Satellite Imagery and Ground-Based Measurements

Hybrid Methodology for the Estimation of Crop Coefficients Based on Satellite Imagery and Ground-Based Measurements

Satellite‐based regional‐scale evapotranspiration estimation mapping of the rice bowl of Tamil Nadu: A little water to spare^*

Implementation of a Two-Source Model for Estimating the Spatial Variability of Olive Evapotranspiration Using Satellite Images and Ground-Based Climate Data

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Mapping Evapotranspiration Coefficients in a Temperate Maritime Climate Using the METRIC Model and Landsat TM

Cited by 15 publications

References 59 publications

Hybrid Methodology for the Estimation of Crop Coefficients Based on Satellite Imagery and Ground-Based Measurements

Hybrid Methodology for the Estimation of Crop Coefficients Based on Satellite Imagery and Ground-Based Measurements

Satellite‐based regional‐scale evapotranspiration estimation mapping of the rice bowl of Tamil Nadu: A little water to spare*

Implementation of a Two-Source Model for Estimating the Spatial Variability of Olive Evapotranspiration Using Satellite Images and Ground-Based Climate Data

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Product

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Satellite‐based regional‐scale evapotranspiration estimation mapping of the rice bowl of Tamil Nadu: A little water to spare^*