Spectral characterization of bacterial leaf blight of rice through spectroscopy and remotely sensed multi-spectral imagery
Ronaldo Alberto: Central Luzon State University
<div>Bacterial Leaf Blight is one of the most destructive diseases of rice. Detection at early growth stage may prevent substantial damage and yield loss. Since all objects on earth’s surface has its own spectral reflectance, spectral reflectance curves of both bacterial leaf blight infected and uninfected rice leaves were compared and assessed the possibility of using remote sensing imagery to determine which spectral bands are most responsive to the presence of BLB.</p> <p>Spectroscopy and multi-spectral imaging were applied to rapidly and non-destructively characterized BLB-infected rice fields. Spectral signatures of rice leaves at different severity levels were collected, namely: normal (healthy), slight, moderate to severe. The data were processed using spectral calculator to obtain the ratio between reflectance and wavelength within the electromagnetic spectrum. Multi-spectral Landsat 8 Operational Land Imager imagery was also downloaded in Geotiff format and pre-processed in ENVI software using radiometric calibration.</p> <p>Leaf spectroscopy showed greater variation between healthy and BLB infected rice plant with wavelengths between 650 to 680 nanometer (red region) and 749 to 769 (Near-Infrared region). In Landsat 8 image, wavelengths from 630 - 670 nm (red region) were statistically separable indicating BLB infection, suggesting that both leaf spectroscopy and multi-spectral images can discriminate healthy and BLB-infected rice, thus, the possibility of using multi-spectral images to estimate BLB infection in a larger scale, estimating potential losses and allowing precision disease management. Moreover, using high resolution images could further characterize diseases of different severity levels to avoid spectral mixing caused by medium resolution multispectral image.</div>
View Presentation |
