The Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) is in preparation to carry a unique visible to shortwave infrared spectrometer. CHIME will globally provide routine hyperspectral observations to support new and enhanced services for, among others, sustainable agricultural and biodiversity management. The mission shall provide Level 1B, 1C and 2A products, as well a set of downstream products related to the different environmental applications, such as the quantification of vegetation traits. In this context, this work presents the first hybrid retrieval models for the operational delivery of vegetation properties products. Within ESA’s CHIME end-to-end (E2E) simulator study, 13 leaf and canopy trait models were developed as part of the L2B vegetation (L2BV) module. The E2E framework functions as a simulated reality that enabled to test and improve the algorithms. The models were further tuned and validated against campaign data using active learning methods. As a proof of concept, the prototype retrieval models were applied to both hyperspectral airborne (HyPlant) and spaceborne (PRISMA) imagery that were first resampled to CHIME band settings. Among the provided vegetation products, it led to a first space-based canopy nitrogen content map over a heterogeneous landscape. The obtained CHIME-like L2BV traits maps demonstrate the feasibility to routinely deliver a collection of next-generation vegetation products across the globe.

Verrelst, J., De Grave, C., Amin, E., Reyes, P., Morata, M., Portales, E., et al. (2021). Prototyping Vegetation Traits Models in the Context of the Hyperspectral Chime Mission Preparation. In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (pp.7678-7681). New York : IEEE [10.1109/IGARSS47720.2021.9554407].

Prototyping Vegetation Traits Models in the Context of the Hyperspectral Chime Mission Preparation

Tagliabue, G.;Panigada, C.;
2021

Abstract

The Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) is in preparation to carry a unique visible to shortwave infrared spectrometer. CHIME will globally provide routine hyperspectral observations to support new and enhanced services for, among others, sustainable agricultural and biodiversity management. The mission shall provide Level 1B, 1C and 2A products, as well a set of downstream products related to the different environmental applications, such as the quantification of vegetation traits. In this context, this work presents the first hybrid retrieval models for the operational delivery of vegetation properties products. Within ESA’s CHIME end-to-end (E2E) simulator study, 13 leaf and canopy trait models were developed as part of the L2B vegetation (L2BV) module. The E2E framework functions as a simulated reality that enabled to test and improve the algorithms. The models were further tuned and validated against campaign data using active learning methods. As a proof of concept, the prototype retrieval models were applied to both hyperspectral airborne (HyPlant) and spaceborne (PRISMA) imagery that were first resampled to CHIME band settings. Among the provided vegetation products, it led to a first space-based canopy nitrogen content map over a heterogeneous landscape. The obtained CHIME-like L2BV traits maps demonstrate the feasibility to routinely deliver a collection of next-generation vegetation products across the globe.
paper
CHIME; Hybrid models; Imaging spectroscopy; Operational processing; Traits; Vegetation;
English
2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 - 12 July 2021 through 16 July 2021
2021
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
978-1-6654-0369-6
2021
7678
7681
none
Verrelst, J., De Grave, C., Amin, E., Reyes, P., Morata, M., Portales, E., et al. (2021). Prototyping Vegetation Traits Models in the Context of the Hyperspectral Chime Mission Preparation. In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (pp.7678-7681). New York : IEEE [10.1109/IGARSS47720.2021.9554407].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/357868
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