Detection of Paddy Rice Drought Stress with Sentinel Image Vegetation Index and the Relation with Productivity
Gusryani Marfuah(*1), Dr. Ir. Daniel, M.Eng.Sc (2) and Dr. Suhardi S.TP, M.P (2)

1*) Student of Agriculture Engineering Study Program, Universitas Hasanuddin, Makassar, 90245, Indonesia
2) Lecturer of Agriculture Engineering Study Program, Universitas Hasanuddin, Makassar, 90245, Indonesia

Abstract

Maros Regency is one of the rice storage areas in South Sulawesi. According to the Central Bureau of Statistics for Maros Regency in 2020, the harvested area of rice decreased by 10.11% or 4,849.55 Ha compared to 2018 and rice production decreased by 16.96% or 37,719.68 tons. This causes the productivity of rice also decreased. One of the factors causing the decline in rice production in Maros Regency is drought. Sentinel 2 imagery is one of the remote sensing data that can be used to detect rice drought using the drought index method. This study aims to detect dryness of paddy rice in Allatengae Village using Sentinel-2A satellite imagery based on NDDI index analysis and determine the relationship between drought index and rice productivity. The method used is the Normalized Difference Drought Index (NDDI) method to determine the dryness level of paddy fields based on NDVI and NDWI parameters and the regression analysis method. From the results of this study, dry rice in Allatengae Village was detected in August and November. In September (42 HST), the average NDDI value was 0.0254 and it was in a mild class of drought conditions while in October (62 HST), the average NDDI value was 0.2425 and it was in a moderate class of drought conditions. and a correlation coefficient of -0.8636 was obtained, which means that there is a strong (negative) relationship between NDDI and rice productivity, where the higher the NDDI index value, the lower the rice productivity value.

Keywords: Sentinel Imagery, Drought, NDDI, and Productivity.

Topic: Digital farming