International Journal on Advanced Science, Engineering and Information Technology, Vol. 13 (2023) No. 2, pages: 399-407, DOI:10.18517/ijaseit.13.2.15531

Estimation of Single Crop Coefficient and Crop Evapotranspiration Using Remote Sensing for Irrigation Management

- Suhardi, Bambang Marhaenanto, Joni Murti Mulyo Aji


Indonesia has rainy and dry seasons sequentially from April to October and October to March. In the dry season, water availability in the soil gradually decreases, especially from June to October, when the peak of drought occurs, causing many agricultural lands to be left uncultivated. However, a small portion of agricultural land can still be planted for crops such as maize and groundnut. However, limited water availability causes crop growth to be disrupted because the amount of water absorbed by crop roots is less than the amount of evapotranspiration water. Therefore, an accurate evapotranspiration estimation technique is needed to make the water supply efficient. This study aims to evaluate the reliability of the technique of estimating crop coefficient (Kc) of maize and groundnut and temperature at the research location. A linear relationship between the Normalized Difference Vegetation Index (NDVI) from sentinel two imagery and Kc-FAO was used to estimate Kc. Meanwhile, a linear relationship between LST from Landsat 8 imagery and the results of interpolating temperature data from 4 climatological stations were used to estimate the temperature at the research site. The results of estimation showed that Kc of maize and groundnut were very accurate with the determinant coefficients (R2) respectively 0.8791 and 0.9352. This is similar to the results of the temperature estimation of the research location, showing a very accurate R2 is 0.9073. The results of this study are expected to be used for future research to improve water crop management.


Sentinel 2; Landsat 8; crop coefficient; evapotranspiration; remote sensing.

Viewed: 417 times (since abstract online)

cite this paper     download