JOM KITA KE POLITEKNIK

Hybrid retrieval of crop traits from multi-temporal PRISMA hyperspectral imagery (Record no. 1640)

MARC details
042 ## - AUTHENTICATION CODE
Authentication code dc
100 10 - MAIN ENTRY--PERSONAL NAME
Personal name Tagliabue, Giulia
Relator term author
9 (RLIN) 1306
245 00 - TITLE STATEMENT
Title Hybrid retrieval of crop traits from multi-temporal PRISMA hyperspectral imagery
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Date of publication, distribution, etc. 2022-05.
500 ## - GENERAL NOTE
General note /pmc/articles/PMC7613384/
500 ## - GENERAL NOTE
General note /pubmed/36093126
520 ## - SUMMARY, ETC.
Summary, etc. The recently launched and upcoming hyperspectral satellite missions, featuring contiguous visible-to-shortwave infrared spectral information, are opening unprecedented opportunities for the retrieval of a broad set of vegetation traits with enhanced accuracy through novel retrieval schemes. In this framework, we exploited hyperspectral data cubes collected by the new-generation PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite of the Italian Space Agency to develop and test a hybrid retrieval workflow for crop trait mapping. Crop traits were mapped over an agricultural area in north-east Italy (Jolanda di Savoia, FE) using PRISMA images collected during the 2020 and 2021 vegetative seasons. Leaf chlorophyll content, leaf nitrogen content, leaf water content and the corresponding canopy level traits scaled through leaf area index were estimated using a hybrid retrieval scheme based on PROSAIL-PRO radiative transfer simulations coupled with a Gaussian processes regression algorithm. Active learning algorithms were used to optimise the initial set of simulated data by extracting only the most informative samples. The accuracy of the proposed retrieval scheme was evaluated against a broad ground dataset collected in 2020 in correspondence of three PRISMA overpasses. The results obtained were positive for all the investigated variables. At the leaf level, the highest accuracy was obtained for leaf nitrogen content (LNC: r(2)=0.87, nRMSE=7.5%), while slightly worse results were achieved for leaf chlorophyll content (LCC: r(2)=0.67, nRMSE=11.7%) and leaf water content (LWC: r(2)=0.63, nRMSE=17.1%). At the canopy level, a significantly higher accuracy was observed for nitrogen content (CNC: r(2)=0.92, nRMSE=5.5%) and chlorophyll content (CCC: r(2)=0.82, nRMSE=10.2%), whereas comparable results were obtained for water content (CWC: r(2)=0.61, nRMSE=16%). The developed models were additionally tested against an independent dataset collected in 2021 to evaluate their robustness and exportability. The results obtained (i. e., LCC: r(2)=0.62, nRMSE=27.9%; LNC: r(2)=0.35, nRMSE=28.4%; LWC: r(2)=0.74, nRMSE=20.4%; LAI: r(2)=0.84, nRMSE=14.5%; CCC: r(2)=0.79, nRMSE=18.5%; CNC: r(2)=0.62, nRMSE=23.7%; CWC: r(2)=0.92, nRMSE=16.6%) evidence the transferability of the hybrid approach optimised through active learning for most of the investigated traits. The developed models were then used to map the spatial and temporal variability of the crop traits from the PRISMA images. The high accuracy and consistency of the results demonstrates the potential of spaceborne imaging spectroscopy for crop monitoring, paving the path towards routine retrievals of multiple crop traits over large areas that could drive more effective and sustainable agricultural practices worldwide.
540 ## - TERMS GOVERNING USE AND REPRODUCTION NOTE
Terms governing use and reproduction
546 ## - LANGUAGE NOTE
Language note en
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element Article
655 7# - INDEX TERM--GENRE/FORM
Genre/form data or focus term Text
Source of term local
700 10 - ADDED ENTRY--PERSONAL NAME
Personal name Boschetti, Mirco
Relator term author
9 (RLIN) 1307
700 10 - ADDED ENTRY--PERSONAL NAME
Personal name Bramati, Gabriele
Relator term author
9 (RLIN) 1308
700 10 - ADDED ENTRY--PERSONAL NAME
Personal name Candiani, Gabriele
Relator term author
9 (RLIN) 1309
700 10 - ADDED ENTRY--PERSONAL NAME
Personal name Colombo, Roberto
Relator term author
9 (RLIN) 1310
700 10 - ADDED ENTRY--PERSONAL NAME
Personal name Nutini, Francesco
Relator term author
9 (RLIN) 1311
700 10 - ADDED ENTRY--PERSONAL NAME
Personal name Pompilio, Loredana
Relator term author
9 (RLIN) 1312
700 10 - ADDED ENTRY--PERSONAL NAME
Personal name Rivera-Caicedo, Juan Pablo
Relator term author
9 (RLIN) 1313
700 10 - ADDED ENTRY--PERSONAL NAME
Personal name Rossi, Marta
Relator term author
9 (RLIN) 1314
700 10 - ADDED ENTRY--PERSONAL NAME
Personal name Rossini, Micol
Relator term author
9 (RLIN) 1315
700 10 - ADDED ENTRY--PERSONAL NAME
Personal name Verrelst, Jochem
Relator term author
700 10 - ADDED ENTRY--PERSONAL NAME
Personal name Panigada, Cinzia
Relator term author
9 (RLIN) 1317
786 0# - DATA SOURCE ENTRY
Note ISPRS J Photogramm Remote Sens
856 41 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://dx.doi.org/10.1016/j.isprsjprs.2022.03.014">http://dx.doi.org/10.1016/j.isprsjprs.2022.03.014</a>
Public note Connect to this object online.

No items available.