Crop Monitoring of Paddy Field Using Landsat 8 OLI

Abstract

There are times where paddy farmers faced crop yield production that does not meet their expectations although the crop has been well-tended. Especially when the growing and harvest seasons, farmers will be able estimate on cutting some production costs while increasing crop yields with crop yield monitoring and mapping if they could measure the different vegetitation indices of crop field. Therefore, to test the efficiency of this study, the crop health was monitored using vegetation index values obtained from multispectral remote sensing images, such as the Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI). The objectives were to estimate the NDVI and SAVI values of a paddy field in Sabak Bernam, Selangor and create a crop health map using the calculated NDVI and SAVI during its resting period (January, February, July, August) and growing up period (April) in 2020. This study used Landsat 8 OLI images at a resolution of 30 meters. The data was then processed using Erdas Imagine and ArcGIS Pro to estimate the NDVI and SAVI values, as well as produce crop health maps. As a result, the estimated NDVI and SAVI crop health maps were displayed. In comparison to NDVI, SAVI estimates a greater vegetation index as the value of adjustment factor (L) applied in the SAVI can reduce the soil noise compared to the NDVI. Furthermore, the computation of planted areas revealed that some changes had occurred. The planted area decreased in a specific month, indicating the harvesting season.