Document Type

Conference Proceeding

Publication Date

7-2024

Abstract

In California's Central Valley, water management and crop health, particularly in rice cultivation, are critical. This paper details the application of Earth surface Mineral dust source InvesTigation (EMIT) hyperspectral imaging, specifically employing Spectral Correlation Mapper (SCM) and Spectral Information Divergence (SID), for precise phenological analysis. By aligning EMIT data with Hyperion satellite references, we address spectral and geographical discrepancies. Our methodology includes seasonal sampling of spectral curves to capture the phenological stages of rice. Results show a strong correlation (R 2 = 0.86) between August EMIT and Reference dataset, emphasizing EMIT's utility in enhancing agricultural practices and water efficiency in the region, and highlighting the importance of understanding rice phenology for sustainable farming.

Comments

This is a pre-copy-editing, author-produced PDF of an article accepted for publication in the proceedings of the IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium in 2024 following peer review. This article may not exactly replicate the final published version. The definitive publisher-authenticated version is available online at https://doi.org/10.1109/IGARSS53475.2024.10640540.

Peer Reviewed

1

Copyright

© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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