Assessing Rice Phenological Features with Hyperspectral Imaging Insights from Earth Surface Mineral Dust Source Investigation (EMIT)

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 (R2 = 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.

• Publication year

  2024

• Venue

  IEEE International Geoscience and Remote Sensing Symposium

• Publication date

  2024-07-07

• Fields of study

  Agricultural and Food Sciences, Computer Science, Environmental Science

• Identifiers
  DOI 10.1109/IGARSS53475.2024.10640540
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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