Influence of Atmospheric Water Vapour on IRS NIR Measurements for Detecting Vegetation Signal. Part II: Validation of Si
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RESEARCH ARTICLE
Influence of Atmospheric Water Vapour on IRS NIR Measurements for Detecting Vegetation Signal. Part II: Validation of Simulation Results using Hyperion Data Mehul R. Pandya & Raghavendra Pratap Singh & Sushma Panigrahy & Jai Singh Parihar
Received: 24 June 2010 / Accepted: 15 August 2011 / Published online: 14 September 2011 # Indian Society of Remote Sensing 2011
Abstract This is the second paper of the series on the influence of the atmospheric water vapour (WV) on IRS NIR measurements. In the first paper (Pandya et al. 2011) a simulation study was presented where through the radiative transfer calculations it was shown that the variation of 0 to 6 g/cm2 in the WV hampered the IRS NIR reflectance up to 14%. In that study splitting of IRS NIR (0.770–0.860 μm) into two bands, such as NIR1 (0.775–0.805 μm) and NIR2 (0.845–0.875 μm) was also proposed, which facilitated a considerable improvement in NIR reflectance as well as in NDVI. Objective of the present paper is to validate the findings of simulation study with the use of EO1-Hyperion data. An improvement of the order of 7% in the top-ofatmosphere reflectance over vegetation target was obtained from the satellite data analysis, which is in good agreement to that of simulation results (3.7 to 7.9%) for the continental WV conditions of 1 to 3 g/cm2. This is also true for NDVI values, which illustrated a good agreement between the satellite observations (2.5%) and simulation results (2 to 4.6%) for the magnitude of improvement. Findings of the present study are preliminary in the nature but it provides a basis for enhanced NIR observations for future IRS sensors. Keywords Atmospheric water vapour . Hyperion . Near infrared . NDVI . Validation . Vegetation M. R. Pandya (*) : R. P. Singh : S. Panigrahy : J. S. Parihar Space Applications Centre ISRO, Ambawadi, Ahmedabad 380015, India e-mail: [email protected]
Introduction Remote sensing of vegetation greatly relies on the measurements of the near infrared (NIR) channel because of a unique response of plants to this wavelength region. It is this distinctive interaction of light and leaf most of the earth observations sensors embrace NIR channel in their systems. The scientific rationale behind the placement of the NIR channel for vegetation monitoring has been discussed in the previous study (Pandya et al. 2011). Indian Remote Sensing (IRS) satellite series is one of these (Navalgund, 2006) systems providing multispectral channel data including NIR region (0.770–0.860 μm) since 1988. Accurate NIR observations are used to generate the vegetation indices (VI’s), which are then employed in various applications. In order to derive precise VI’s from NIR observations to be utilized in diverse applications and for generating long-term data series to answer some of the science questions (e.g. Myneni et al. (1997) provided the findings of increase in the plant growth in the northern latitude from NDVI time-series data from the NOAA-AVHRR observations), signal in the IRS NIR wavelength region should hav
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