Predicting soil nutrients with PRISMA hyperspectral data at the field scale: the Handan (south of Hebei Province) test cases-Reference-Cited by-同舟云学术

Predicting soil nutrients with PRISMA hyperspectral data at the field scale: the Handan (south of Hebei Province) test cases

Published:2024-05-03 Issue:3 Volume:27 Page:870-891
ISSN:1009-5020
Container-title:Geo-spatial Information Science
language:en
Short-container-title:Geo-spatial Information Science

Author:

Rossi Francesco¹²^ORCID,Casa Raffaele³^ORCID,Huang Wenjiang⁴^ORCID,Laneve Giovanni¹^ORCID,Linyi Liu⁴^ORCID,Mirzaei Saham²^ORCID,Pascucci Simone²^ORCID,Pignatti Stefano²^ORCID,Yu Ren⁴

Affiliation:

1. School of Aerospace Engineering, Sapienza University of Rome, Rome, Italy

2. National Research Council, Institute of Methodologies for Environmental Analysis, Tito Scalo, Italy

3. University of Tuscia-DAFNE, Viterbo, Italy

4. State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

Funder

European Space Agency

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10095020.2024.2343021

Reference71 articles.

1. Evaluation of Airborne HySpex and Spaceborne PRISMA Hyperspectral Remote Sensing Data for Soil Organic Matter and Carbonates Estimation

2. Remote Sensing Techniques for Soil Organic Carbon Estimation: A Review

3. ASI. 2020. “PRISMA Products Specification Document Issue 2.3.”

4. ASI. n.d. “PRISMA 2G.” Accessed August 23 2023. https://www.asi.it/2022/02/prisma2g-siglato-il-contratto-tra-agenzia-spaziale-italiana-e-thales-alenia-space-per-lavvio-della-fase-di-studio/destinata-allo-sviluppo-del-satellite-di-seconda-generazione/.

5. Vis-SWIR spectral prediction model for soil organic matter with different grouping strategies

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