Drought Monitoring in Sugarcane Based on Water Stress Model Using Remote Sensing


Student:
Restu Triadi

Department:
Computer science

Supervisor:
- Dr Yeni Herdiyeni, SSi, MKomp
- Dr Ir Suria Darma Tarigan, MSc

Description:
Drought is one of the main factors causing the decline in sugarcane production. This study aims to apply remote sensing technology to estimate the water stress level in PTPN X's sugarcane plantations. The water stress level on land is measured using the crop water stress index (CWSI) parameter. The land surface temperature (LST) was calculated using a split-window algorithm (SWA) to obtain CWSI.

CWSI estimation using a remote sensing approach can be done more easily and cheaply compared to field measurements. Furthermore, drought monitoring is carried out by looking at the prediction of water stress conditions for the next few months. The random forest regression algorithm can be used to predict CWSI quite well. In general, the addition of normalized difference vegetation index (NDVI) data to the model formation can improve the model's performance in predicting CWSI values.

Uses:
Applying remote sensing technology to determine water stress levels. Then, do drought monitoring by predicting water stress conditions for the next one, two, and three months.

Advantages:
This research is expected to be used as an early warning system in dealing with drought. Irrigation scheduling techniques can be applied by farmers based on predictions to increase sugarcane production and increase the efficiency of water resource management.



Published Date : 19-Nov-2020