Abstract
Vegetation biophysical parameter retrieval is an important earth remote sensing system application. In this paper, we studied the potential impact of the addition of new spectral bands in the red edge region in future Landsat satellites on agroecosystem canopy green leaf area index (LAI) retrieval. The test data were simulated from SPARC ‘03 field campaign HyMap hyperspectral data. Three retrieval approaches were tested: empirical regression based on vegetation index, physical model-based look-up-table (LUT) inversion, and machine learning. The results of all three approaches showed that a potential new spectral band located between the Landsat-8 Operational Land Imager (OLI) red and NIR bands slightly improved the agroecosystem green LAI retrieval accuracy (R2 of 0.787 vs. 0.810 for vegetation index approach, 0.806 vs. 0.828 for LUT inversion approach, and 0.925 vs. 0.933 for machine learning approach). The results of this work are consistent with the conclusions from previous research on the value of Sentinel-2 red edge bands for agricultural green LAI retrieval.
Highlights
IntroductionSeveral remote sensing satellites such as MODIS [1] and MERIS [2] provide vegetation monitoring products using their multi-temporal and multi-angular observations
Vegetation monitoring is a key application of earth observing systems
The results from all three approaches suggested that a limited retrieval accuracy increase can be achieved after the addition of at most three new spectral bands located between the Operational Land Imager (OLI) red and NIR bands
Summary
Several remote sensing satellites such as MODIS [1] and MERIS [2] provide vegetation monitoring products using their multi-temporal and multi-angular observations. These products have relatively coarse spatial resolution, which makes them less useful for precise crop yield prediction or local scale forest monitoring. The Sentinel-2 missions have a revisit date of five days and high spatial resolution vegetation monitoring related bands: 10 m for blue/green/red/NIR bands and 20 m for red-edge bands/SWIR1/SWIR2 bands. These characteristics of a moderate revisit interval and high spatial resolution make the Sentinel-2 mission a good data source for vegetation monitoring studies
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