MULTISPECTRAL IMAGING FOR RICE HEALTH IN FERTILE ALLUVIAL PLAIN OF SOUTHEASTERN FLANK MERAPI VOLCANO

Aditya SAPUTRA , Danardono DANARDONO , Afif Ari WIBOWO , Christopher GOMEZ , Dedi SURACHMAN, Said Willya PUTRA, Ridwan HAFIDZIN

DOI: 10.21163/GT_2026.211.06

ABSTRACT: Food security is a pressing issue in Indonesia, where challenges in land suitability and crop productivity are exacerbated by rice diseases and pests. This study aims to detect and analyze rice diseases and pests in southeastern Mount Merapi, Klaten Regency, using UAV technology to support sustainable agriculture. The research establishes an integrated framework for precision agriculture by combining a region Land Potency Index (LPI) with UAV-based multispectral monitoring to address these challenges. The LPI, assessing slope, lithology, soil, water, and hazard exposure, strategically identified the central zone of Klaten Regency as the area with the highest agricultural potential, thereby optimizing the focus for subsequent detailed analysis. Within these high-potential zones, UAV-derived vegetation indices (NDVI and NDCI) served as effective early-warning indicators. The analysis revealed a clear distinction where healthy rice plants consistently exhibited NDVI > 0.6 and NDCI > 0.5, while significant clusters fell below these thresholds. Crucially, field validation confirmed that these low-value clusters were predominantly associated with leaf blast disease, demonstrating the method's efficacy in pinpointing specific physiological stress. The widespread prevalence of blast in high-potential areas underscores a direct and significant threat to regional yield. Therefore, this study demonstrates that the integration of LPI for targeting and UAVs for diagnosis provides a scalable, data-driven workflow. The findings highlight the critical need for management strategies that leverage this early detection capability to implement timely interventions, such as the use of resistant varieties and balanced fertilization, thereby enhancing the sustainability and resilience of rice production systems in Indonesia and similar agro-ecological contexts.

Keywords: Multispectral drone; LPI; NDVI; NDCI; Leaf blast

Full article here