Comparative study of AVHRR ratio vegetation index and normalized difference vegetation index in district level agricultural monitoring

Abstract With the temporal profiles of mean values of ratio vegetation index (RVI) and normalized difference vegetation index (NDVI) and their standard deviations over the crop growth cycle for two districts displaying more than 90 per cent of the area sown under wheat, this article indicates the better sensitivity aspect of RVI as compared to NDVI during emergence-crown root initiation-late tillering-jointing-near flowering stages of the crop growth cycle; and suggests a combined use of RVI and NDVI for crop growth oriented studies. The relative narrowness of the standard deviation of RVI in these early crop growth stages as compared to that for the NDVI suggests that the RVI possesses better information content integration capabilities.

[1]  G. Asrar,et al.  Estimating Absorbed Photosynthetic Radiation and Leaf Area Index from Spectral Reflectance in Wheat1 , 1984 .

[2]  Ray Jackson,et al.  Development of Agrometeorological Crop Model Inputs from Remotely Sensed Information , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[3]  A. Huete.  A soil-adjusted vegetation index (SAVI) , 1988 .

[4]  V. Whitehead,et al.  Vegetation Assessment Using a Combination of Visible, Near-IR, and Thermal-Jr AVHRR Data , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[5]  J. U. Hielkema,et al.  Rainfall and vegetation monitoring in the Savanna Zone of the Democratic Republic of Sudan using the NOAA Advanced Very High Resolution Radiometer , 1986 .

[6]  R. Crippen.  Calculating the vegetation index faster , 1990 .

[7]  K. Gallo,et al.  Large-area crop monitoring with the NOAA AVHRR: Estimating the silking stage of corn development , 1989 .

[8]  Rajendra Kumar Gupta.  Processing error reduction factors in the generation of geometrically corrected NOAA/AVHRR vegetation index images , 1992 .

[9]  Glenn Biatwright,et al.  Early Warning and Crop Condition Assessment Research , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[10]  A. J. Richardsons,et al.  DISTINGUISHING VEGETATION FROM SOIL BACKGROUND INFORMATION , 1977 .

[11]  Philip N. Slater,et al.  Discrimination of growth and water stress in wheat by various vegetation indices through clear and turbid atmospheres , 1983 .

[12]  T. Phulpin,et al.  AVHRR data processing to study the surface canopies in temperate regions First results of HAPEX-MOBELHY , 1989 .

[13]  C. Justice,et al.  Analysis of the phenology of global vegetation using meteorological satellite data , 1985 .

[14]  Application of Remotely Sensed Data in Wheat Growth Modelling , 1985 .

[15]  J. A. Schell,et al.  Monitoring vegetation systems in the great plains with ERTS , 1973 .

[16]  P. Ashburn,et al.  The vegetative index number and crop identification , 1979 .

[17]  J. Townshend,et al.  African Land-Cover Classification Using Satellite Data , 1985, Science.

[18]  Directionality in emitted infrared radiation from grassy surfaces , 1985 .

[19]  Samuel N. Goward,et al.  Comparison of North and South American biomes from AVHRR observations , 1987 .

[20]  R. Gupta.  District level NOAA/AVHRR vegetation indices and scan angle effects , 1992 .

[21]  R. Kauth,et al.  The tasselled cap - A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat , 1976 .

[22]  John E. Estes,et al.  Studying the Earth's Vegetation from Space , 1984 .

[23]  G. Suits.  The calculation of the directional reflectance of a vegetative canopy , 1971 .

[24]  C. Perry,et al.  Functional equivalence of spectral vegetation indices , 1984 .