Integration Remote Sensing and Meteorological Data to Monitoring Plant Phenology and Estimation Crop Coefficient and Evapotranspiration

被引：4

作者：

Hassan, Diaa Fliah ^{[1
]}

Abdalkadhum, Aysar Jameel ^{[1
]}

Mohammed, Rafal J. ^{[2
]}

Shaban, Amin ^{[3
]}

机构：

[1] Al Qasim Green Univ, Coll Engn, Al Qasim 8, Iraq

[2] Al Qasim Green Univ, Coll Agr, Al Qasim 8, Iraq

[3] Natl Council Sci Res, Beirut, Lebanon

来源：

JOURNAL OF ECOLOGICAL ENGINEERING | 2022年 / 23卷 / 04期

关键词：

actual evapotranspiration; crop coefficient; remote sensing; vegetation index; WATER-BUDGET; VEGETATION; CALIBRATION; STRESS; MODEL;

D O I：

10.12911/22998993/146267

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The water requirements of the wheat crop are represented by the actual evapotranspiration, which depends on the meteorological data of the study area and the amount of water consumed during the season. Estimation of crop coefficients (Kc) and evapotranspiration (ETc) using remote sensing data is essential for decision-making regarding water management in irrigated areas in arid and semi-arid large-scale areas. This research aims to estimate the crop coefficient calculated from remote sensing data and the actual evapotranspiration values for the crop. The FAO Penman-Monteith equation has been used to estimate the reference evapotranspiration from meteorological data. Linear regression analysis was applied by developing prediction equations for the crop coefficient for different growth stages of comparing with the vegetation cover index (NDVI). The results showed that (R-2 = 0.98) between field crop coefficient and crop coefficient predicted from (Kc = 2.0114 NDVI-0.147) in addition to (RMSE = 0.92 and (d = 0.97).

引用

页码：325 / 335

页数：11

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