Next Article in Journal
Previous Article in Journal
Remote Sens. 2013, 5(10), 5265-5284; doi:10.3390/rs5105265
Article

Empirical and Physical Estimation of Canopy Water Content from CHRIS/PROBA Data

1
, 2,3
 and 1,*
Received: 31 July 2013; in revised form: 11 October 2013 / Accepted: 14 October 2013 / Published: 21 October 2013
View Full-Text   |   Download PDF [803 KB, uploaded 19 June 2014]   |   Browse Figures
Abstract: Efficient monitoring of Canopy Water Content (CWC) is a central feature in vegetation studies. The potential of hyperspectral high spatial resolution CHRIS/PROBA satellite data for the retrieval of CWC was here investigated using empirical and physical based approaches. Special attention was paid to the spectral band selection, inversion technique and training process. Performances were evaluated with ground measurements from the SEN3EXP field campaign over a range of crops. Results showed that the optimal band selection includes four spectral bands: one centered about 970 nm absorption feature which is sensible to Cw, and three bands in green, red and near infrared to estimate LAI and compensate from leaf- and canopy-level effects. A simple neural network with a single hidden layer of five tangent sigmoid transfer functions trained over PROSAIL radiative transfer simulations showed benefits in the retrieval performances compared with a look up table inversion approach (root mean square error of 0.16 kg/m2 vs. 0.22 kg/m2). The neural network inversion approach showed a good agreement and performances similar to an empirical up-scaling approach based on a multivariate iteratively re-weighted least squares algorithm, demonstrating the applicability of radiative transfer model inversion methods to CHRIS/PROBA for high spatial resolution monitoring of CWC.
Keywords: canopy water content; model inversion; neural networks; look up tables; empirical up-scaling; CHRIS/PROBA canopy water content; model inversion; neural networks; look up tables; empirical up-scaling; CHRIS/PROBA
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Cernicharo, J.; Verger, A.; Camacho, F. Empirical and Physical Estimation of Canopy Water Content from CHRIS/PROBA Data. Remote Sens. 2013, 5, 5265-5284.

AMA Style

Cernicharo J, Verger A, Camacho F. Empirical and Physical Estimation of Canopy Water Content from CHRIS/PROBA Data. Remote Sensing. 2013; 5(10):5265-5284.

Chicago/Turabian Style

Cernicharo, Jesus; Verger, Aleixandre; Camacho, Fernando. 2013. "Empirical and Physical Estimation of Canopy Water Content from CHRIS/PROBA Data." Remote Sens. 5, no. 10: 5265-5284.


Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert