Hyperion: The first global orbital spectrometer, earth observing-1 (EO-1) satellite (2000–2017)

Middleton, Elizabeth M.; Campbell, P. K. E.; Ong, Lawrence; Landis, D.R.; Zhang, Qingyuan; Neigh, C. S. R.; Huemmrich, K. F.; Ungar, Stephen; Mandl, Daniel; Frye, Stuart; Ly, Vuong; Cappelaere, P. G.; Chien, Steve; Franks, Shannon; Pollack, N.

doi:10.1109/igarss.2017.8127639

Cited by 9 publications

(5 citation statements)

References 9 publications

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“…The availability of HS datasets collected from space dates back to almost a quarter of century ago, with the pioneering push-broom Hyperion spectrometer on the Earth Observation-1 (EO-1) satellite, launched by NASA. EO-1 was also equipped with a 10-band MS scanner, including a 10 m Pan image [15]. Unfortunately, Hyperion featured a narrow swath (7.7 km) because of technological limitations and experienced serious miscalibration problems just a few years after its launch, a problem that new-generation spaceborne imaging spectrometers have brilliantly solved through an onboard calibration system based on fixed stars.…”

Section: Hyperspectral and Multispectral Scanners From Spacementioning

confidence: 99%

Spatial Resolution Enhancement of Vegetation Indexes via Fusion of Hyperspectral and Multispectral Satellite Data

Alparone,

Arienzo,

Garzelli

2024

Remote Sensing

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The definition and calculation of a spectral index suitable for characterizing vegetated landscapes depend on the number and widths of the bands of the imaging instrument. Here, we point out the advantages of performing the fusion of hyperspectral (HS) satellite data with the multispectral (MS) bands of Sentinel-2 to calculate such vegetation indexes as the normalized area over reflectance curve (NAOC) and the red-edge inflection point (REIP), which benefit from the availability of quasi-continuous pixel spectra. Unfortunately, MS data may be acquired from satellite platforms with very high spatial resolution; HS data may not. Despite their excellent spectral resolution, satellite imaging spectrometers currently resolve areas not greater than 30 × 30 m2, where different thematic classes of landscape may be mixed together to form a unique pixel spectrum. A way to resolve mixed pixels is to perform the fusion of the HS dataset with the same dataset produced by an MS scanner that images the same scene with a finer spatial resolution. The HS dataset is sharpened from 30 m to 10 m by means of the Sentinel-2 bands that have all been previously brought to 10 m. To do so, the hyper-sharpening protocol, that is, m:n fusion, is exploited in two nested steps: the first one to bring the 20 m bands of Sentinel-2 all to 10 m, the second one to sharpen all the 30 m HS bands to 10 m by using the Sentinel-2 bands previously hyper-sharpened to 10 m. Results are presented on an agricultural test site in The Netherlands imaged by Sentinel-2 and by the satellite imaging spectrometer recently launched as a part of the environmental mapping and analysis program (EnMAP). Firstly, the excellent match of statistical consistency of the fused HS data to the original MS and HS data is evaluated by means of analysis tools, existing and developed ad hoc for this specific case. Then, the spatial and radiometric accuracy of REIP and NAOC calculated from fused HS data are analyzed on the classes of pure and mixed pixels. On pure pixels, the values of REIP and NAOC calculated from fused data are consistent with those calculated from the original HS data. Conversely, mixed pixels are spectrally unmixed by the fusion process to resolve the 10 m scale of the MS data. How the proposed method can be used to check the temporal evolution of vegetation indexes when a unique HS image and many MS images are available is the object of a final discussion.

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Section: Hyperspectral and Multispectral Scanners From Spacementioning

confidence: 99%

Spatial Resolution Enhancement of Vegetation Indexes via Fusion of Hyperspectral and Multispectral Satellite Data

Alparone,

Arienzo,

Garzelli

2024

Remote Sensing

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“…T HE availability of hyperspectral (HS) datasets taken from space, dates back to almost a quarter of century ago, with the pioneering push-broom Hyperion spectrometer on the Earth Observation-1 (EO-1) satellite, launched by NASA. EO-1 was also equipped with a 10-band multispectral (MS) scanner, including a 10 m panchromatic (PAN) band [1].…”

Section: Scenario and Motivationsmentioning

confidence: 99%

Spatial Resolution Enhancement of Satellite Hyperspectral Data via Nested Hypersharpening With Sentinel-2 Multispectral Data

Alparone,

Arienzo,

Garzelli

2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The paper presents an original method for the spatial resolution enhancement of satellite hyperspectral (HS) data by means of the Sentinel-2 visible-near infrared (VNIR) and shortwave infrared (SWIR) bands at 10 and 20 m spatial resolution. Presently, HS data are available from PRISMA (Italian acronym for hyperspectral precursor of the application mission) and EnMAP (environmental mapping and analysis program): both map the spectral interval of the solar radiation onto 240 and 224 bands, respectively, with 10 nm and 6.5/10 nm widths. A 5 m×5 m panchromatic (PAN) band is also acquired by PRISMA.

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“…However, due to its limited duty cycle, EO-1 only collected specific images as requested by users for science and application studies. Since these study sites were distributed globally, they have provided a unique archive of VSWIR measurements of various surface types sampled around the globe, based on both multispectral data (ALI) and Hyperion spectra [ 75 , 76 , 77 , 78 , 79 ] (EO-1 served as a key pathfinder that led to technological advances in instruments flown in space today (e.g., Landsat-8 and 9, EMAP, Prisma, and EMIT, all discussed in later sections) and those expected to fly over the next several years.…”

Section: Pioneering Nasa Missions Eos-1 and The Eos Flagship Satellit...mentioning

confidence: 99%

Current and Near-Term Earth-Observing Environmental Satellites, Their Missions, Characteristics, Instruments, and Applications

Ustin,

Middleton

2024

Sensors

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Among the essential tools to address global environmental information requirements are the Earth-Observing (EO) satellites with free and open data access. This paper reviews those EO satellites from international space programs that already, or will in the next decade or so, provide essential data of importance to the environmental sciences that describe Earth’s status. We summarize factors distinguishing those pioneering satellites placed in space over the past half century, and their links to modern ones, and the changing priorities for spaceborne instruments and platforms. We illustrate the broad sweep of instrument technologies useful for observing different aspects of the physio-biological aspects of the Earth’s surface, spanning wavelengths from the UV-A at 380 nanometers to microwave and radar out to 1 m. We provide a background on the technical specifications of each mission and its primary instrument(s), the types of data collected, and examples of applications that illustrate these observations. We provide websites for additional mission details of each instrument, the history or context behind their measurements, and additional details about their instrument design, specifications, and measurements.

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Hyperion: The first global orbital spectrometer, earth observing-1 (EO-1) satellite (2000–2017)

Cited by 9 publications

References 9 publications

Spatial Resolution Enhancement of Vegetation Indexes via Fusion of Hyperspectral and Multispectral Satellite Data

Spatial Resolution Enhancement of Vegetation Indexes via Fusion of Hyperspectral and Multispectral Satellite Data

Spatial Resolution Enhancement of Satellite Hyperspectral Data via Nested Hypersharpening With Sentinel-2 Multispectral Data

Current and Near-Term Earth-Observing Environmental Satellites, Their Missions, Characteristics, Instruments, and Applications

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