Spectral vegetation indices for benchmarking water productivity of irrigated cotton and sugarbeet crops

González‐Dugo, M. P.; Mateos, Luciano

doi:10.1016/j.agwat.2007.09.001

Cited by 131 publications

(79 citation statements)

References 41 publications

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“…The local calibration performed in [12] was also retained here, the only difference being the source of the NDVI data (satellite or hand-held radiometer). Thus there is no contradiction to state that local calibration is necessary and to find that the same method driven by satellite data is accurate: [15,16]. An empirical function between K cb and NDVI, consisting of two regressions, has been found by [9] for cotton crops.…”

Section: Model Descriptionmentioning

confidence: 99%

“…However, there is no agreement on the nature and generality of these relationships [16]. Some studies [6][7][8]11,14,17] have shown that these relationships are linear, but others have found non linearity relationships [9,10,12,16]. Therefore, establishing a unique relationship between crop coefficient and spectral vegetation indices is an ongoing research topic.…”

Section: Introductionmentioning

confidence: 99%

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Combining Satellite Remote Sensing Data with the FAO-56 Dual Approach for Water Use Mapping In Irrigated Wheat Fields of a Semi-Arid Region

2010

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Abstract:The aim of this study was to combine the FAO-56 dual approach and remotely-sensed data for mapping water use (ET c ) in irrigated wheat crops of a semi-arid region. The method is based on the relationships established between Normalized Difference Vegetation Index (NDVI) and crop biophysical variables such as basal crop coefficient, cover fraction and soil evaporation. A time series of high spatial resolution SPOT and Landsat images acquired during the 2002/2003 agricultural season has been used to generate the profiles of NDVI in each pixel that have been related to crop biophysical parameters which were used in conjunction with FAO-56 dual source approach. The obtained results showed that the spatial distribution of seasonal ET c varied between 200 and 450 mm depending to sowing date and the development of the vegetation. The validation of spatial results showed that the ET c estimated by FAO-56 corresponded well with actual ET measured by eddy covariance system over test sites of wheat, especially when soil evaporation and plant water stress are not encountered. OPEN ACCESSRemote Sens. 2010, 2 376

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Section: Model Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Combining Satellite Remote Sensing Data with the FAO-56 Dual Approach for Water Use Mapping In Irrigated Wheat Fields of a Semi-Arid Region

2010

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“…The general approach is consistent with Allen et al [48,55], who also proposed separating the Kc of crops that have a significant period of minimal canopy cover into dual components consisting of a basal crop coefficient (Kcb) that represents water loss by transpiration and an evaporation coefficient (Ke), representing loss from soil evaporation. Direct relationships between Fc and Kcb have been reported for several crops such as broccoli [56], wheat [57], cotton [58], sugar beets [58], and grapes [59].…”

Section: Et-based Approaches To Scheduling Irrigations In Vegetablesmentioning

confidence: 99%

New Approaches to Irrigation Scheduling of Vegetables

Cahn

Johnson

2017

Horticulturae

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Using evapotranspiration (ET) data for scheduling irrigations on vegetable farms is challenging due to imprecise crop coefficients, time consuming computations, and the need to simultaneously manage many fields. Meanwhile, the adoption of soil moisture monitoring in vegetables has historically been limited by sensor accuracy and cost, as well as labor required for installation, removal, and collection of readings. With recent improvements in sensor technology, public weather-station networks, satellite and aerial imaging, wireless communications, and cloud computing, many of the difficulties in using ET data and soil moisture sensors for irrigation scheduling of vegetables can now be addressed. Web and smartphone applications have been developed that automate many of the calculations involved in ET-based irrigation scheduling. Soil moisture sensor data can be collected through wireless networks and accessed using web browser or smartphone apps. Energy balance methods of crop ET estimation, such as eddy covariance and Bowen ratio, provide research options for further developing and evaluating crop coefficient guidelines of vegetables, while recent advancements in surface renewal instrumentation have led to a relatively low-cost tool for monitoring crop water requirement in commercial farms. Remote sensing of crops using satellite, manned aircraft, and UAV platforms may also provide useful tools for vegetable growers to evaluate crop development, plant stress, water consumption, and irrigation system performance.

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“…The parameter β2 corresponds to an adjustment coefficient associated with crop senescence and leaves yellowing. Both NDVI and SAVI are sensitive to leaf senescence thus yielding smaller values at the end of the growing cycle than before peak development was reached [51]. Therefore, the β2 adjustment is considered to compensate the decrease in VI due to the senescence and/or yellowing of plants, which is independent from fc.…”

Section: Basal Crop Coefficients Derived From Reflectance Vegetation mentioning

confidence: 99%

Estimation of Actual Crop Coefficients Using Remotely Sensed Vegetation Indices and Soil Water Balance Modelled Data

et al. 2015

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Abstract:A new procedure is proposed for estimating actual basal crop coefficients from vegetation indices (Kcb VI) considering a density coefficient (Kd) and a crop coefficient for bare soil. Kd is computed using the fraction of ground cover by vegetation (fc VI), which is also estimated from vegetation indices derived from remote sensing. A combined approach for estimating actual crop coefficients from vegetation indices (Kc VI) is also proposed by integrating the Kcb VI with the soil evaporation coefficient (Ke) derived from the soil water balance model SIMDualKc. Results for maize, barley and an olive orchard have shown that the approaches for estimating both fc VI and Kcb VI compared well with results obtained using the SIMDualKc model after calibration with ground observation data. For the crops studied, the correlation coefficients relative to comparing the actual Kcb VI and Kc VI with actual Kcb and Kc obtained with SIMDualKc were larger than 0.73 and 0.71, respectively. The corresponding regression coefficients were close to 1.0. The methodology herein presented and discussed allowed for obtaining information for the whole crop season, including periods when vegetation cover is incomplete, as the initial and development stages. Results show that the proposed methods are adequate for supporting irrigation management. OPEN ACCESSRemote Sens. 2015, 7 2374

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Spectral vegetation indices for benchmarking water productivity of irrigated cotton and sugarbeet crops

Cited by 131 publications

References 41 publications

Combining Satellite Remote Sensing Data with the FAO-56 Dual Approach for Water Use Mapping In Irrigated Wheat Fields of a Semi-Arid Region

Combining Satellite Remote Sensing Data with the FAO-56 Dual Approach for Water Use Mapping In Irrigated Wheat Fields of a Semi-Arid Region

New Approaches to Irrigation Scheduling of Vegetables

Estimation of Actual Crop Coefficients Using Remotely Sensed Vegetation Indices and Soil Water Balance Modelled Data

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