Small satellite's role in future hyperspectral Earth observation missions

Guelman, M.; Ortenberg, Fred

doi:10.1016/j.actaastro.2009.01.013

Cited by 26 publications

(3 citation statements)

References 7 publications

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“…Several satellite hyperspectral missions, with open access policy for scientific use, are under preparation: the EnMAP (Environmental Mapping and Analysis Program) by the Space Agency of the German Aerospace Centre, the HyspIRI mission of the National Aeronautics and Space Administration of the United States, the continuity of PRISMA (Hyperspectral Precursor of the Application Mission) led by the Italian Space Agency, and the HISUI HIS sensor for launch on ALOS-3 satellite by the Japanese Space Agency. Furthermore, micro-and mini-satellites will certainly have a role in future hyperspectral EO missions (Guelman & Ortenberg, 2009). Thus, it is clear that in the coming decade our way to observe and study forests might be radically changed by the availability of these new data.…”

Section: Functional Composition (Guilds)mentioning

confidence: 99%

Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data

Laurin

Puletti

Hawthorne

et al. 2016

Remote Sensing of Environment

157

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a b s t r a c tTo answer new scientific and ecological questions and monitor multiple forest changes, a fine scale characterization of these ecosystems is needed, and could imply the mapping of specific species, of detailed forest types, and of functional composition. This characterization can be now provided by the novel Earth Observation tools. This study aims to contribute to understanding the innovation in forest and ecological research that can be brought in by advanced remote sensing instruments, and proposes the guild mapping approach as a tool to efficiently monitor the varied tropical forest resources. We evaluated, in tropical Ghanaian forests, the ability of airborne hyperspectral and simulated multispectral Sentinel-2 data, and derived vegetation indices and textures, to: distinguish between two different forest types; to discriminate among selected dominant species; and to separate trees species grouped according to their functional guilds: Pioneer, Non Pioneer Light Demanding, and Shade Bearer. We then produced guild classification maps for each area using hyperspectral data. Our results showed that with both hyperspectral and simulated Sentinel-2 data these discrimination tasks can be successfully accomplished. Results also stressed the importance of texture features, especially if using the lower spectral and spatial Sentinel-2 resolution data, and highlighted the important role of the new Sentinel-2 data for ecological monitoring. Classification results showed a statistically significant improvement in overall accuracy using Support Vector Machine, over Maximum Likelihood approach. We proposed the functional guilds mapping as an innovative approach to: (i) monitor compositional changes, especially with respect to the effects of global climate change on forests, and particularly in the tropical biome where the occurrence of hundreds of species prevents mapping activities at species level; (ii) support large-scale forest inventories. The imminent Sentinel-2 data could serve to open the road for the development of new concepts and methods in forestry and ecological research..

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Section: Functional Composition (Guilds)mentioning

confidence: 99%

Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data

Laurin

Puletti

Hawthorne

et al. 2016

Remote Sensing of Environment

157

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“…This section reviews all past, present, and planned future hyperspectral missions that were known at the time of writing this article. Hyperspectral missions were reviewed in several previous studies including airborne platforms (Buckingham et al 2002;Shippert 2003;Buckingham and Staenz 2008;Guelman and Ortenberg 2009), the history of remote sensing, and instruments and data analysis (Schaepman 2007;Schaepman et al 2009). To the best of the authors' knowledge, none of the existing literature sources discusses image compression techniques from such missions.…”

Section: Review Of Hyperspectral Spaceborne Missionsmentioning

confidence: 99%

Investigation into lossless hyperspectral image compression for satellite remote sensing

Noor

Vladimirova

2013

International Journal of Remote Sensing

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Hyperspectral sensors acquire images in many, very narrow, contiguous spectral bands throughout the visible, near-infrared (IR), mid-IR and thermal IR portions of the spectrum, thus requiring large data storage on board the satellite and high bandwidth of the downlink transmission channel to ground stations. Image compression techniques are required to compensate for the limitations in terms of on-board storage and communication link bandwidth. In most remote-sensing applications, preservation of the original information is important and urges studies on lossless compression techniques for on-board implementation. This article first reviews hyperspectral spaceborne missions and compression techniques for hyperspectral images used on board satellites. The rest of the article investigates the suitability of the integer Karhunen-Loève transform (KLT) for lossless inter-band compression in spaceborne hyperspectral imaging payloads. Clustering and tiling strategies are employed to reduce the computational complexity of the algorithm. The integer KLT performance is evaluated through a comprehensive numerical experimentation using four airborne and four spaceborne hyperspectral datasets. In addition, an implementation of the integer KLT algorithm is ported to an embedded platform including a digital signal processor (DSP). The DSP performance results are reported and compared with the desktop implementation. The effects of clustering and tiling techniques on the compression ratio and latency are assessed for both desktop and the DSP implementation.

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“…This restricts the number of devices that can affordably be fielded at any one time. An additional drawback of current systems is the large data sets generated, since grating-based HSI systems have thousands of spectral channels, whereas typical hyperspectral data products require only a fraction of these spectral channels to generate atmospheric profiles with high scientific value [1][2][3][4] . The metamaterial spectral filter (MMS) described in this work allows the use of a compact optical system to produce a tailored spectral channel dataset.…”

Section: Introductionmentioning

confidence: 99%

Metamaterial spectrometer on a chip for hyperspectral imaging and atmospheric sounding

Crouse

Bendoym

Lepak

et al. 2023

High Contrast Metastructures XII

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The monitoring of Earth’s atmosphere requires routine measurements of many gasses and aerosols. The most common technique to perform this task is hyperspectral imaging (HSI). However, with the push to integrate HSI sensing capabilities on small platforms, e.g. cubesats and UAVs, the development of smaller, cheaper, higher performing, and low power HSI systems is necessary. Current HSI systems are composed of a large and complex assortment of lenses, filters and cameras that are large, heavy, expensive, and intolerant to physical shocks—all things that make them challenging for use in space-based sensing and imaging applications. The metamaterial filter described in this work eliminates the need for many of the previously necessary optics because it can spectrally filter light independent of the lights angle of incidence—this allows for a focused beam of light to be filtered by the metamaterial. This is in distinct contrast to grating-based HSI systems where the spectrometer requires collimated light. Additionally, the metamaterial filter is designed to filter light only at the desired spectral bands; this is a great benefit for small-platform systems because of the substantially reduced data rate and required computational resources.

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Small satellite's role in future hyperspectral Earth observation missions

Cited by 26 publications

References 7 publications

Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data

Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data

Investigation into lossless hyperspectral image compression for satellite remote sensing

Metamaterial spectrometer on a chip for hyperspectral imaging and atmospheric sounding

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