TAILIEUCHUNG - Estimation of rice vegetation coverage from DVI of Landsat 7 and 8 data

The field observations of the reflectance and the VC were carried out in two paddy rice varieties in 2013. Paddy field reflectance was observed by spectrometer Ocean Optics SD2000. The photos of paddies were taken from the height of 1 m by a digital camera in order to calculate the VC. The reflectances of paddy field corresponding to red and near-infrared bands of Landsat 7 and 8 were calculated from the field observation data. | SCIENCE & TECHNOLOGY DEVELOPMENT, Vol. 19, No. K4-2016 Estimation of rice vegetation coverage from DVI of Landsat 7 and 8 data Phan Thi Anh Thư Rikimaru Atsushi Kenta Sakata Kazuyoshi Takahashi Junki Abe Nagaoka university of Technology, Japan (Manuscript Received on June 28th, 2016, Manuscript Revised August 18rd, 2016) ABSTRACT Monitoring of rice growth is a requirement for high quality rice production. In addtion to plant height, number stem and rice leaf color, vegetation coverage (VC) which represents for percentage of ground covered by rice plant is also considered as an important index to validate rice growth. Thus, the study is to estimate rice vegetation coverage from difference vegetation index (DVI) calculated from reflectance of near-infrared and red band of Landsat 7 and 8 images. The field observations of the reflectance and the VC were carried out in two paddy rice varieties in 2013. Paddy field reflectance was observed by spectrometer Ocean Optics SD2000. The photos of paddies were taken from the height of 1 m by a digital camera in order to calculate the VC. The reflectances of paddy field corresponding to red and near-infrared bands of Landsat 7 and 8 were calculated from the field observation data. Satellite reflectance was also converted from pixel value of Landsat images. According to the data analysis, VC rapidly increased in two fields and got saturation status (VC>90%) at 65 days after transplanting (DAT) in the early July. DVI was approximately 25% when VC saturated. Additionally, DVI had strong correlation with VC with high determination coefficient (r2 =) when VC was less than 90%. Thus, VC were computed from DVI, calculated from reflectances of Landsat images, using a regression model of VC and DVI. From the result of comparison between the estimated and computed VC, the possibility of estimating VC from DVI calculated from Landsat reflectance is confirmed. Keywords: DVI, vegetation coverage, Landsat data, reflectance 1.

• Địa Lý
• Estimation of rice vegetation coverage
• Rice vegetation coverage
• DVI of Landsat 7 and 8 data
• Difference vegetation index
• Calculate the VC