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Using Remote Sensing to Estimate Cro...

Reyes-Gonzalez, Arturo.

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Using Remote Sensing to Estimate Crop Water Use to Improve Irrigation Water Management.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Using Remote Sensing to Estimate Crop Water Use to Improve Irrigation Water Management./
Author:	Reyes-Gonzalez, Arturo.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	196 p.
Notes:	Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
Contained By:	Dissertation Abstracts International79-02B(E).
Subject:	Agriculture. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10619810
ISBN:	9780355225037

Using Remote Sensing to Estimate Crop Water Use to Improve Irrigation Water Management.
Reyes-Gonzalez, Arturo.

Using Remote Sensing to Estimate Crop Water Use to Improve Irrigation Water Management. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 196 p.

Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.

Thesis (Ph.D.)--South Dakota State University, 2017.

Irrigation water is scarce. Hence, accurate estimation of crop water use is necessary for proper irrigation managements and water conservation. Satellite-based remote sensing is a tool that can estimate crop water use efficiently.

ISBN: 9780355225037Subjects--Topical Terms:

518588
Agriculture.

Using Remote Sensing to Estimate Crop Water Use to Improve Irrigation Water Management.
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020 $a 9780355225037
035 $a (MiAaPQ)AAI10619810
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035 $a AAI10619810
040 $a MiAaPQ $c MiAaPQ
100 1 $a Reyes-Gonzalez, Arturo. $3 3426655
245 1 0 $a Using Remote Sensing to Estimate Crop Water Use to Improve Irrigation Water Management.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 196 p.
500 $a Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
500 $a Advisers: Todd Trooien; Jeppe Kjaersgaard.
502 $a Thesis (Ph.D.)--South Dakota State University, 2017.
520 $a Irrigation water is scarce. Hence, accurate estimation of crop water use is necessary for proper irrigation managements and water conservation. Satellite-based remote sensing is a tool that can estimate crop water use efficiently.
520 $a Several models have been developed to estimate crop water requirement or actual evapotranspiration (ETa) using remote sensing. One of them is the Mapping EvapoTranspiration at High Resolution using Internalized Calibration (METRIC) model. This model has been compared with other methods for ET estimations including weighing lysimeters, pan evaporation, Bowen Ratio Energy Balance System (BREBS), Eddy Covariance (EC), and sap flow. However, comparison of METRIC model outputs to an atmometer for ETa estimation has not yet been attempted in eastern South Dakota. The results showed a good relationship between ETa estimated by the METRIC model and estimated with atmometer (r2 = 0.87 and RMSE = 0.65 mm day-1). However, ETa values from atmometer were consistently lower than ET a values from METRIC.
520 $a The verification of remotely sensed estimates of surface variables is essential for any remote-sensing study. The relationships between LAI, Ts, and ETa estimated using the remote sensing-based METRIC model and in-situ measurements were established. The results showed good agreement between the variables measured in situ and estimated by the METRIC model. LAI showed r2 = 0.76, and RMSE = 0.59 m2 m -2, Ts had r2 = 0.87 and RMSE 1.24 °C and ETa presented r2= 0.89 and RMSE = 0.71 mm day -1.
520 $a Estimation of ETa using energy balance method can be challenging and time consuming. Thus, there is a need to develop a simple and fast method to estimate ETa using minimum input parameters. Two methods were used, namely 1) an energy balance method (EB method) that used input parameters of the Landsat image, weather data, a digital elevation map, and a land cover map and 2) a Kc-NDVI method that use two input parameters: the Landsat image and weather data. A strong relationship was found between the two methods with r2 of 0.97 and RMSE of 0.37 mm day -1. Hence, the Kc-NDVI method performed well for ET a estimations, indicating that Kc-NDVI method can be a robust and reliable method to estimate ETa in a short period of time.
520 $a Estimation of crop evapotranspiration (ETc) using satellite remote sensing-based vegetation index such as the Normalized Difference Vegetation Index (NDVI). The NDVI was calculated using near-infrared and red wavebands. The relationship between NDVI and tabulated Kc's was used to generate Kc maps. ETc maps were developed as an output of Kc maps multiplied by reference evapotranspiration (ETr). Daily ETc maps helped to explain the variability of crop water use during the growing season. Based on the results we can conclude that ETc maps developed from remotely sensed multispectral vegetation indices are a useful tool for quantifying crop water use at regional and field scales.
590 $a School code: 0205.
650 4 $a Agriculture. $3 518588
650 4 $a Remote sensing. $3 535394
650 4 $a Water resources management. $3 794747
690 $a 0473
690 $a 0799
690 $a 0595
710 2 $a South Dakota State University. $b Agricultural & Biosystems Engineering. $3 3282880
773 0 $t Dissertation Abstracts International $g 79-02B(E).
790 $a 0205
791 $a Ph.D.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10619810