Estimation of rice area in KWD region using geospatial tools

Abstract

The estimation of crop areas was recognized as crucial for assessing agricultural production, supporting food security, and guiding policy decisions. In India, rice cultivation was particularly significant, especially in Andhra Pradesh, where remote sensing technologies like Landsat 9 improved the accuracy of mapping and monitoring crop areas compared to traditional field survey methods. These advancements helped optimize resource allocation, enhance market forecasting, and detect shifts in cropping patterns. The study aimed to estimate rice area in the KWD region during the kharif season of 2023 using geospatial tools. A combination of satellite imagery and ground truth data was employed. Landsat 9 data were utilized to estimate rice areas during the kharif season, and this data was processed using ENVI software. The Random Forest classification method was applied to distinguish rice areas, achieving an overall accuracy of 94.3% with a Kappa coefficient of 0.81, indicating almost perfect agreement. The total rice area in the study region was estimated at 127,565 ha, with the largest area recorded in Bapatla (12,299 ha) and the smallest in Pedanandipadu (3 ha). A 4.4% underestimation was observed when compared to the Department of Agriculture (DoA) statistics, which reported 133,402 ha.