Monitoring of Rice Leaf Folder Damage Based on Remote Sensing Methods

Abstract

Rice leaf folder (Cnaphalocrocis medinalis Guenee) is one of the most important pests that endanger rice development and yield, which has characteristics of large outbreak areas, high occurrence frequencies and heavy damages. At present, the monitoring methods of rice leaf folder damage is based on artificial investigation, which has the advantages of objective truth and high reliability, while there is a drawback of time-consuming, and it cannot used for a wide range of rice damage monitoring. An ASD (Analytical Spectral Devices, Inc.) Hand-held Spectroradiometer was used at jointing stage of rice. The results showed that, reflectance from rice canopy significantly decreased in the green (530–570 nm) and near infrared (700–1000 nm) regions, and significantly increased in the blue (450–520 nm) and red (580–700 nm) regions as the rice leaf folder population increased. Reflectance from rice canopy significantly decreased in the spectral regions from 737 to 1000 nm as the infestation scale of pest population increased, and the most correlation appeared at 941 nm. The more the numbers of rice leaf folder, the higher the changes of such characteristic parameters. The positive correlations were found between the damage of rice leaf folder and the discrepancy of characteristic parameters in these experimental fields. With China Remote Sensing career advancement, a large number of independent researches and development satellites have launched. Among a new generation of high-resolution satellites, GaoFen-1 (GF-1) stands out. It sets high spatial resolution (2 m-16 m), multi-spectral and high temporal resolution (4-day) with 60 km-800 km swath in a fusion technology with strategic significance. In order to explore the adaptability of Chinese GF-1 images in monitoring rice damage from rice leaf folder, nine rice fields were selected by damage severity in Xinghua City, Jiangsu Province at full heading stage in 2015, and the Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), 2-band Enhanced Vegetation Index (EVI2), Soil Adjusted Vegetation Index (SAVI), Optimized Soil Adjusted Vegetation Index (OSAVI) were used to characterize the occurrence of rice leaf folder damages, which were calculated from the satellite GF-1 retrieval data. A series of analyses were performed to disclose the relationship among these six indices and the severity of rice leaf folder. Quantitative correlation analyses showed that NDVI, EVI, EVI2, SAVI, OSAVI and leaf folding population had a highly significant correlation (P<0.01), and SAVI had a highest correlation of 0.94. While there was no significant correlation between RVI and leaf folding population. Therefore, it was feasible to using hyperspectral data and GF-1 satellite images to monitor and warn the outbreak and development of rice leaf folder, which provided a new possible method to monitor dynamically the damage of rice leaf folder.