Regularization strategies for agricultural monitoring: The EnMAP vegetation analyzer (AVA)

In the frame of the German hyperspectral satellite mission “Environmental Mapping and Analysis Program” (EnMAP) a software interface is under development to facilitate the processing of the future hyperspectral data used by a range of environmental applications. For agricultural studies, the software will include the Agricultural Vegetation Analyzer (AVA) module, which is based on a look-up table (LUT) inversion of a radiative transfer model (RTM). Moreover, a statistical evaluator box (MapStat) will be implemented to validate, amongst others, the estimation of vegetation biophysical variables. Results from a hyperspectral field campaign with the Airborne Prism Experiment (APEX) instrument in Bavaria (Germany) showed that AVA can be regarded as robust and sound technique obtaining moderate to good results without the need of crop- or site specific calibration. MapStat will guarantee comparability between numerous modeling studies expected in the upcoming years within the context of the future EnMAP sensor.

[1]  C. Atzberger,et al.  Spatially constrained inversion of radiative transfer models for improved LAI mapping from future Sentinel-2 imagery , 2012 .

[2]  Clement Atzberger,et al.  Evaluation of Sentinel-2 Spectral Sampling for Radiative Transfer Model Based LAI Estimation of Wheat, Sugar Beet, and Maize , 2011, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[3]  Roberta E. Martin,et al.  PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments , 2008 .

[4]  W. Verhoef.  Light scattering by leaf layers with application to canopy reflectance modeling: The Scattering by Arbitrarily Inclined Leaves (SAIL) model , 1984 .

[5]  W. Verhoef,et al.  PROSPECT+SAIL models: A review of use for vegetation characterization , 2009 .

[6]  R. Myneni,et al.  Investigation of a model inversion technique to estimate canopy biophysical variables from spectral and directional reflectance data , 2000 .

[7]  Timo Stuffler,et al.  EnMAP A Hyperspectral Sensor for Environmental Mapping and Analysis , 2006, 2006 IEEE International Symposium on Geoscience and Remote Sensing.

[8]  F. Baret,et al.  Estimating Canopy Characteristics from Remote Sensing Observations: Review of Methods and Associated Problems , 2008 .

[9]  Jens Nieke,et al.  APEX - the Hyperspectral ESA Airborne Prism Experiment , 2008, Sensors.

[10]  Wolfram Mauser,et al.  Preparatory analyses and development of algorithms for agricultural applications in the context of the EnMAP hyperspectral mission , 2010, Remote Sensing.

[11]  W. Verhoef.  Light scattering by leaf layers with application to canopy reflectance modelling: The SAIL model , 1984 .

[12]  G. D’Urso,et al.  Experimental assessment of the Sentinel-2 band setting for RTM-based LAI retrieval of sugar beet and maize , 2009 .

[13]  Clement Atzberger,et al.  Derivation of biophysical variables from Earth observation data: validation and statistical measures , 2012 .

[14]  J. Norman,et al.  Instrument for Indirect Measurement of Canopy Architecture , 1991 .

[15]  F. L. Dimet,et al.  Multitemporal-patch ensemble inversion of coupled surface-atmosphere radiative transfer models for land surface characterization , 2008 .