Application of Imaging Spectroscopy to Quantify Fractional Cover Over Agricultural Lands

In this study, we demonstrate the implementation of an automated unmixing algorithm for the estimation of cover fractions in photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and bare soil (BS). To develop and test the algorithm, a series of field campaigns were conducted across various locations in the United States, utilizing the Global Airborne Observatory (GAO) equipped with visible-to-shortwave infrared (VSWIR) spectrometer technology. This imaging capability facilitates the quantification of diverse land and ocean ecosystem properties. Here, the Automated Monte-Carlo Unmixing (AutoMCU) algorithm was applied to an example dataset collected from a research farm in Iowa, US, yielding consistent results across different spatial scales, atmospheric corrections, and iterations.

• Publication year

  2023

• Venue

  IEEE International Geoscience and Remote Sensing Symposium

• Publication date

  2023-07-16

• Fields of study

  Agricultural and Food Sciences, Computer Science, Environmental Science

• Identifiers
  DOI 10.1109/IGARSS52108.2023.10283149
• 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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