Development of Reflectance-Based Crop Coefficients for Corn

Neale, Christopher M. U.; Bausch, Walter C.; Heermann, Dale F.

doi:10.13031/2013.31240

Cited by 158 publications

(31 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Some of these authors already postulated the possible use of these relationships for the estimation of crop transpiration and the desirable use of these approaches for irrigation assessment in operative scenarios [22]. Following the development of the “two-step” procedure, some pioneers provided empirical evidence about the direct relationship between the Kcb values with the VI derived from multispectral satellite images [23,24,25] (see Figure 2). …”

Section: Remote Sensing-based Estimates Of Evapotranspirationmentioning

confidence: 99%

Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users

Calera

Campos

Osann

et al. 2017

Sensors

196

120

View full text Add to dashboard Cite

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.

show abstract

Section: Remote Sensing-based Estimates Of Evapotranspirationmentioning

confidence: 99%

Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users

Calera

Campos

Osann

et al. 2017

Sensors

196

120

View full text Add to dashboard Cite

show abstract

“…The greater advantage of the use of remote sensing data is the possibility to have spatially distributed information. In particular, methods that combine vegetation index and crop coefficients have been developed in agricultural crops from 30 years ago [31]. …”

Section: Introductionmentioning

confidence: 99%

Assessing Crop Coefficients for Natural Vegetated Areas Using Satellite Data and Eddy Covariance Stations

Corbari

Ravazzani

Galvagno

et al. 2017

Sensors

View full text Add to dashboard Cite

The Food and Agricultural Organization (FAO) method for potential evapotranspiration assessment is based on the crop coefficient, which allows one to relate the reference evapotranspiration of well irrigated grass to the potential evapotranspiration of specific crops. The method was originally developed for cultivated species based on lysimeter measurements of potential evapotranspiration. Not many applications to natural vegetated areas exist due to the lack of available data for these species. In this paper we investigate the potential of using evapotranspiration measurements acquired by micrometeorological stations for the definition of crop coefficient functions of natural vegetated areas and extrapolation to ungauged sites through remotely sensed data. Pastures, deciduous and evergreen forests have been considered and lower crop coefficient values are found with respect to FAO data.

show abstract

“…The Spatial EvapoTranspiration Modeling Interface (SETMI) described by Geli and Neale (2012) has been modified and implemented in VRI research in maize and soybean (common commodity crops in the High Plains) by Barker et al (2018a) and Barker et al (2018b). This model includes a reflectancebased crop coefficient evapotranspiration (ET) model, wherein the basal crop coefficient is related to a multispectral vegetation index (Neale et al, 1989). SETMI uses relationships developed for maize and soybean in Nebraska by Campos et al (2017).…”

Section: Introductionmentioning

confidence: 99%

Variable Rate Irrigation of Maize and Soybean in West-Central Nebraska Under Full and Deficit Irrigation

Barker¹,

Bhatti

Heeren

et al. 2019

Front. Big Data

View full text Add to dashboard Cite

Variable rate irrigation (VRI) may improve center pivot irrigation management, including deficit irrigation. A remote-sensing-based evapotranspiration model was implemented with Landsat imagery to manage irrigations for a VRI equipped center pivot irrigated field located in West-Central Nebraska planted to maize in 2017 and soybean in 2018. In 2017, the study included VRI using the model, and uniform irrigation using neutron attenuation for full irrigation with no intended water stress (VRI-Full and Uniform-Full treatments, respectively). In 2018, two deficit irrigation treatments were added (VRI-Deficit and Uniform-Deficit, respectively) and the model was modified in an attempt to reduce water balance drift; model performance was promising, as it was executed unaided by measurements of soil water content throughout the season. VRI prescriptions did not correlate well with available water capacity (R 2 < 0.4); however, they correlated better with modeled ET in 2018 (R 2 = 0. 69, VRI-Full; R 2 = 0.55, VRI-Deficit). No significant differences were observed in total intended gross irrigation depth in 2017 (VRI-Full = 351 mm, Uniform Full = 344). However, in 2018, VRI resulted in lower mean prescribed gross irrigation than the corresponding uniform treatments (VRI-Full = 265 mm, Uniform Full = 282 mm, VRI-Deficit = 234 mm, and Uniform Deficit = 267 mm). Notwithstanding the differences in prescribed irrigation (in 2018), VRI did not affect dry grain yield, with no statistically significant differences being found between any treatments in either year (F = 0.03, p = 0.87 in 2017; F = 0.00, p = 0.96 for VRI/Uniform and F = 0.01, p = 0.93 for Full/Deficit in 2018). Likewise, any reduction in irrigation application apparently did not result in detectable reductions in deep percolation potential or actual evapotranspiration. Additional research is needed to further vet the model as a deficit irrigation management tool. Suggested model improvements include a continuous function for water stress and an optimization routine in computing the basal crop coefficient.

show abstract

Development of Reflectance-Based Crop Coefficients for Corn

Cited by 158 publications

References 0 publications

Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users

Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users

Assessing Crop Coefficients for Natural Vegetated Areas Using Satellite Data and Eddy Covariance Stations

Variable Rate Irrigation of Maize and Soybean in West-Central Nebraska Under Full and Deficit Irrigation

Contact Info

Product

Resources

About