Crop Monitoring of Paddy Field Using Landsat 8 OLI

Abstract

Rice production of paddy fields is the main source of food for the Malaysian and thus the stability of the production is important for the food security program. Therefore, monitoring of its availability become the main agenda of Malaysia. In this study, the vegetation index parameters of Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) were derived from multispectral remote sensing images and used to produce health crop maps. The Landsat 8 images with 30 m resolution were acquired in the study area of the paddy field in Sabak Bernam. The data was then processed using Erdas Imagine and ArcGIS Pro to estimate NDVI and SAVI values and generate the health crop maps, respectively. The results show that the standard deviation of the difference between NDVI and SAVI was highest in October at 0.07, while the lowest in February of 0.02. It indicates that the capabilities of NDVI and SAVI were different in extracting the values of vegetation indices in high vegetation areas. The values of NDVI and SAVI range from -1 to +1 which the value of -1 indicates the dead vegetation; meanwhile, the value of 1 shows the healthiest vegetation.