New generation hyperspectral sensors DESIS and PRISMA provide improved agricultural crop classifications
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Abstract
Using new remote sensing technology to study agricultural crops will support advances in food and water security. The recently launched, new generation spaceborne hyperspectral sensors, German DLR Earth Sensing Imaging Spectrometer (DESIS) and Italian PRecursore IperSpettrale della Missione Applicativa (PRISMA), provide unprecedented data in hundreds of narrow spectral bands for the study of the Earth. Therefore, our overarching goal in this study was to use these data to explore advances that can be made in agricultural research. We selected PRISMA and DESIS images during the 2020 growing season in California's Central Valley to study seven major crops. PRISMA and DESIS images were highly correlated (R 2of 0.9–0.95). Out of the 235 DESIS bands (400–1000 nm) and 238 PRISMA bands (400–2500 nm), 26 (11%) and 45 (19%) bands, respectively, were optimal to study agricultural crops. These optimal bands provided crop type classification accuracies of 83–90%. Hyperspectral vegetation indices to estimate plant pigment content, stress, biomass, moisture, and cellulose/lignin content were also identified.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | New generation hyperspectral sensors DESIS and PRISMA provide improved agricultural crop classifications |
| Series title | Photogrammetric Engineering & Remote Sensing |
| DOI | 10.14358/PERS.22-00039R2 |
| Volume | 88 |
| Issue | 11 |
| Year Published | 2022 |
| Language | English |
| Publisher | American Society for Photogrammetry and Remote Sensing |
| Contributing office(s) | Western Geographic Science Center |
| Description | 15 p. |
| First page | 715 |
| Last page | 729 |
| Country | United States |
| State | California |
| Google Analytic Metrics | Metrics page |