Title
Optimal Exploitation of the Sentinel-2 Spectral Capabilities for Crop Leaf Area Index Mapping
Abstract
The continuously increasing demand of accurate quantitative high quality information on land surface properties will be faced by a new generation of environmental Earth observation (EO) missions. One current example, associated with a high potential to contribute to those demands, is the multi-spectral ESA Sentinel-2 (S2) system. The present study focuses on the evaluation of spectral information content needed for crop leaf area index (LAI) mapping in view of the future sensors. Data from a field campaign were used to determine the optimal spectral sampling from available S2 bands applying inversion of a radiative transfer model (PROSAIL) with look-up table (LUT) and artificial neural network (ANN) approaches. Overall LAI estimation performance of the proposed LUT approach (LUTN50) was comparable in terms of retrieval performances with a tested and approved ANN method. Employing seven- and eight-band combinations, the LUTN50 approach obtained LAI RMSE of 0.53 and normalized LAI RMSE of 0.12, which was comparable to the results of the ANN. However, the LUTN50 method showed a higher robustness and insensitivity to different band settings. Most frequently selected wavebands were located in near infrared and red edge spectral regions. In conclusion, our results emphasize the potential benefits of the Sentinel-2 mission for agricultural applications.
Year
DOI
Venue
2012
10.3390/rs4030561
REMOTE SENSING
Keywords
Field
DocType
Sentinel-2,leaf area index,model inversion,look-up table,artificial neural networks,optimal spectral sampling,PROSAIL model
Leaf area index,Normalization (statistics),Remote sensing,Mean squared error,Robustness (computer science),Atmospheric radiative transfer codes,Sampling (statistics),Earth observation,Geology,Red edge
Journal
Volume
Issue
Citations 
4
3
19
PageRank 
References 
Authors
1.62
8
5
Name
Order
Citations
PageRank
Katja Richter1677.40
Tobias Hank25411.02
francesco vuolo313217.93
wolfram mauser4191.62
Guido D'Urso59413.12