کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4459219 | 1621281 | 2012 | 14 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Evaluation of the information content of Medium Resolution Imaging Spectrometer (MERIS) data for regional leaf area index assessment Evaluation of the information content of Medium Resolution Imaging Spectrometer (MERIS) data for regional leaf area index assessment](/preview/png/4459219.png)
Substantial research has been conducted to derive Leaf Area Index (LAI), an essential climate variable, from satellite imageries acquired by moderate resolution optical sensors. The Medium Resolution Imaging Spectrometer (MERIS) is unique among such sensors in that it provides relatively high spectral (15 bands) and spatial (~ 300 m resolution) sampling within visible and near infrared wavelengths. A recent evaluation of four operational MERIS LAI algorithms found that they did not consistently meet accuracy targets typical of operational requirements. One explanation for the mixed performance of these algorithms may be that they do not suitably exploit the enhanced spectral sampling of MERIS. We exploit this enhanced spectral sampling to estimate several (80) narrow-band vegetation indices (VIs) by interpolating MERIS surface reflectance. The interpolation accuracy was evaluated using Hyperion imagery. Regressions were then calibrated between estimated VIs and in-situ LAI over a range of land cover types. The strongest performance (root mean squared error < 0.92 and relative root mean squared error < 0.38) was observed for two selected VIs (the NDVI8 and the CTR) based on both training and validation data. This study demonstrates that MERIS has the information content to meet typical operational performance specifications for LAI retrieval within the 1 unit error margin for the given atmospheric, environmental, soil and plant cover conditions on the day of the overpass and using locally derived relationships. Therefore the development of robust algorithms for retrieving LAI using these VIs is recommended.
► The study exploits MERIS enhanced spectral sampling for LAI assessment.
► Several narrow-band VIs were calculated by interpolating MERIS surface reflectance.
► The interpolation accuracy was evaluated using Hyperion imagery.
► The strongest performances for LAI retrieval were observed for the VIs NDVI8 and CTR.
► MERIS has the information content for operational LAI retrieval.
Journal: Remote Sensing of Environment - Volume 119, 16 April 2012, Pages 301–314