Estimation of Crop Coefficient and Evapotranspiration of Wheat (Triticum aestivum) in an Irrigation Command Using Remote Sensing and GIS

Gontia, Narendra Kumar; Tiwari, K. N.

doi:10.1007/s11269-009-9505-3

Cited by 70 publications

(38 citation statements)

References 9 publications

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“…These two seasons were characterized because in the initial stage crop needs smaller water requirements, whereas in the mid-season crop needs higher water requirements, as we can see in the next section. The ET c maps created in this study are in agreement with other researchers; for example, in [2,4,58,59], they generated ET c maps using c derived from remote sensing-based vegetation indices. Other researchers reported that c derived from canopy reflectance based vegetation index had the potential to estimate crop evapotranspiration at regional and field scales, for example, in [17,18,29,55,60,61].…”

Section: 3supporting

confidence: 89%

“…High values of NDVI are related to healthy and dense vegetation, which presents high reflectance values in the NIR waveband and low reflectance values in the red waveband [17]. Crop coefficients generated from VIs determine ET c better than a tabulated c because it represents the actual crop growth conditions and capture the spatial variability among different fields [2,18,19].…”

Section: Advances In Meteorologymentioning

confidence: 99%

“…Crop coefficients derived from remotely sensed vegetation index also have used to generate local and regional ET c maps [2,[32][33][34]; however, in northern Mexico, ET c maps using satellite remote sensing-based vegetation index remain unexplored.…”

Section: Advances In Meteorologymentioning

confidence: 99%

“…Agriculture is the major consumer of fresh water [1,2], but it is not necessarily used efficiently due to farmers supplying more water than is consumed by the crop. Thus, better estimation of irrigation water requirements is essential to use water efficiently so water is available for use in the future.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index

Reyes-González

Kjaersgaard

Trooien

et al. 2018

Advances in Meteorology

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Irrigation water is limited and scarce in many areas of the world, including Comarca Lagunera, Mexico. Thus better estimations of irrigation water requirements are essential to conserve water. The general objective was to estimate crop water demands or crop evapotranspiration (ET c ) at different scales using satellite remote sensing-based vegetation index. The study was carried out in northern Mexico (Comarca Lagunera) during four growing seasons. Six, eleven, three, and seven clear Landsat images were acquired for 2013, 2014, 2015, and 2016, respectively, for the analysis. The results showed that ET c was low at initial and early development stages, while ET c was high during mid-season and harvest stages. These results are not new but give us confidence in the rest of our ET c results. Daily ET c maps helped to explain the variability of crop water use during the growing season. Based on the results we can conclude that ET c maps developed from remotely sensed multispectral vegetation indices are a useful tool for quantifying crop water consumption at regional and field scales. Using ET c maps at the field scale, farmers can supply appropriate amounts of irrigation water corresponding to each growth stage, leading to water conservation.

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Section: 3supporting

confidence: 89%

Section: Advances In Meteorologymentioning

confidence: 99%

Section: Advances In Meteorologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index

Reyes-González

Kjaersgaard

Trooien

et al. 2018

Advances in Meteorology

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“…Several research studies have successfully developed ET prediction models using VIs for different vegetation covers [19] including shrub lands [20,21], riparian sites [22][23][24][25], and over regional scales with a variety of land covers/land uses of grasslands to forests [26,27]. NDVI, the most widely used VI, quantifies the vegetation's photosynthetic response to red radiation absorption and near infrared reflectance [28][29][30][31][32][33]. For most satellites, NDVI is computed from Equation 1:…”

Section: Study Areamentioning

confidence: 99%

High Spatial Resolution WorldView-2 Imagery for Mapping NDVI and Its Relationship to Temporal Urban Landscape Evapotranspiration Factors

et al. 2014

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Evapotranspiration estimation has benefitted from recent advances in remote sensing and GIS techniques particularly in agricultural applications rather than urban environments. This paper explores the relationship between urban vegetation evapotranspiration (ET) and vegetation indices derived from newly-developed high spatial resolution WorldView-2 imagery. The study site was Veale Gardens in Adelaide, Australia. Image processing was applied on five images captured from February 2012 to February 2013 using ERDAS Imagine. From 64 possible two band combinations of WorldView-2, the most reliable one (with the maximum median differences) was selected. Normalized Difference Vegetation Index (NDVI) values were derived for each category of landscape cover, namely trees, shrubs, turf grasses, impervious pavements, and water bodies. Urban landscape evapotranspiration rates for Veale Gardens were estimated through field monitoring using observational-based landscape coefficients. The relationships between remotely sensed NDVIs for the entire Veale Gardens and for individual NDVIs of different vegetation covers were compared with field measured urban landscape evapotranspiration rates. The water stress conditions experienced in January

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Vegetation index‐based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems

Glenn

Neale

Hunsaker

et al. 2011

Hydrological Processes

211

136

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Abstract:Crop coefficients were developed to determine crop water needs based on the evapotranspiration (ET) of a reference crop under a given set of meteorological conditions. Starting in the 1980s, crop coefficients developed through lysimeter studies or set by expert opinion began to be supplemented by remotely sensed vegetation indices (VI) that measured the actual status of the crop on a field-by-field basis. VIs measure the density of green foliage based on the reflectance of visible and near infrared (NIR) light from the canopy, and are highly correlated with plant physiological processes that depend on light absorption by a canopy such as ET and photosynthesis. Reflectance-based crop coefficients have now been developed for numerous individual crops, including corn, wheat, alfalfa, cotton, potato, sugar beet, vegetables, grapes and orchard crops. Other research has shown that VIs can be used to predict ET over fields of mixed crops, allowing them to be used to monitor ET over entire irrigation districts. VI-based crop coefficients can help reduce agricultural water use by matching irrigation rates to the actual water needs of a crop as it grows instead of to a modeled crop growing under optimal conditions. Recently, the concept has been applied to natural ecosystems at the local, regional and continental scales of measurement, using time-series satellite data from the MODIS sensors on the Terra satellite. VIs or other visible-NIR band algorithms are combined with meteorological data to predict ET in numerous biome types, from deserts, to arctic tundra, to tropical rainforests. These methods often closely match ET measured on the ground at the global FluxNet array of eddy covariance moisture and carbon flux towers. The primary advantage of VI methods for estimating ET is that transpiration is closely related to radiation absorbed by the plant canopy, which is closely related to VIs. The primary disadvantage is that they cannot capture stress effects or soil evaporation.

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Estimation of Crop Coefficient and Evapotranspiration of Wheat (Triticum aestivum) in an Irrigation Command Using Remote Sensing and GIS

Cited by 70 publications

References 9 publications

Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index

Estimation of Crop Evapotranspiration Using Satellite Remote Sensing-Based Vegetation Index

High Spatial Resolution WorldView-2 Imagery for Mapping NDVI and Its Relationship to Temporal Urban Landscape Evapotranspiration Factors

Vegetation index‐based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems

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