Three decades of hyperspectral remote sensing of the Earth: A personal view

Goetz, Alexander

doi:10.1016/j.rse.2007.12.014

Cited by 649 publications

(354 citation statements)

References 47 publications

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“…Gillespie et al (2007) presented an overview of recent satellites with passive sensors that provide panchromatic, visible, near-infrared, shortwave infrared, and thermal infrared (TIR) information suitable for the remote sensing of hazards. Goetz (2009) discussed the development of airborne and spaceborne hyperspectral sensors and data analysis techniques during the last 30 years and pointed out current limitations and future needs. CubeSats have been addressed by Sandau (2010) and Cracknell (2010), amongst others.…”

Section: Spaceborne Remote Sensing Of Vegetation Biodiversitymentioning

confidence: 99%

“…Distributing badly calibrated or distorted sensor data would hold the potential of 'face loss' or professional criticism, and countries may not be able to have the infrastructure and administrative capacity in place to deal with global data requests. A good example has been given by the consortium around Gong et al (2013) enabling access to global Landsatderived land-cover data. Nevertheless, we consider the following appeal (Figure 12) worth making to data provider and remote-sensing community globally.…”

Section: Data Access and Availabilitymentioning

confidence: 99%

“…areal cover densities (Cracknell et al 2013;Gong et al 2013). Furthermore, most biologists, ecologists, and conservationists have a relatively local focus area or habitat of interest, and local studies based on a few Landsat scenes are often sufficient.…”

Section: Data Access and Availabilitymentioning

confidence: 99%

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Earth observation satellite sensors for biodiversity monitoring: potentials and bottlenecks

Kuenzer

Ottinger²,

Wegmann³

et al. 2014

International Journal of Remote Sensing

154

112

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Many biologists, ecologists, and conservationists are interested in the possibilities that remote sensing offers for their daily work and study site analyses as well as for the assessment of biodiversity. However, due to differing technical backgrounds and languages, cross-sectorial communication between this group and remote-sensing scientists is often hampered. Hardly any really comprehensive studies exist that are directed towards the conservation community and provide a solid overview of available Earth observation sensors and their different characteristics. This article presents, categorizes, and discusses what spaceborne remote sensing has contributed to the study of animal and vegetation biodiversity, which different types of variables of value for the biodiversity community can be derived from remote-sensing data, and which types of spaceborne sensor data are available for which time spans, and at which spatial and temporal resolution. We categorize all current and important past sensors with respect to application fields relevant for biologists, ecologists, and conservationists. Furthermore, sensor gaps and current challenges for Earth observation with respect to data access and provision are presented.

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Section: Spaceborne Remote Sensing Of Vegetation Biodiversitymentioning

confidence: 99%

Section: Data Access and Availabilitymentioning

confidence: 99%

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Earth observation satellite sensors for biodiversity monitoring: potentials and bottlenecks

Kuenzer

Ottinger²,

Wegmann³

et al. 2014

International Journal of Remote Sensing

154

112

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“…Hyper-spectral imaging has been employed in various scientific disciplines to provide valuable data for fields such as astronomy [1], earth sciences and remote sensing [2,3], food safety [4], criminal investigation, and computer vision [5]. With the advances in technology and cost reductions, the hyperspectral imaging of historical art and murals is now accessible for use at mural protection and research institutes.…”

Section: Introductionmentioning

confidence: 99%

Extracting graphite sketch of the mural using Hyper-Spectral Imaging method

et al. 2015

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Original scientific paper Many contaminants appear in murals as time passes, which make the original mural blurred and difficult to recognize; therefore, extracting a clear graphite sketch of the mural is significant. In this study, we used invisible spectra, particularly near-infrared (NIR) bands, to detect the graphite information and strengthen the features of the mural information to obtain a graphite sketch. This is the first study to extract the contour line from the draft of the mural using hyper-spectral imaging (HSI) technology. First, spectral matching methods were used to identify the pigment of the contour line and graphite was determined as the main pigment of the draft. Then, the characteristic bands were selected by analysing the spectra of the pigments. After that, the information extraction method was used to extract the graphite information. The results showed that the method could improve the efficiency of graphite information extraction significantly. The key steps of the current method involved extracting the graphite contour line end-member spectrum, followed by mapping the grey image of the graphite contour line spectrum. Finally, the visually enhanced image was reconstructed using the alpha blending fusion method with the original visible image and the graphite information image. The efficiency of results is evaluated by quantitative methods. The study also explained and discussed the two key points of election thresholds in obtaining the graphite sketch. These results demonstrate that the method is efficient for extracting graphite sketch based on hyper-spectral data of mural, and that it could provide useful information to explore cultural relics and to support some other protection researches. Keywords: graphite contour line; Hyper-Spectral Imaging; information extraction; murals; visual enhancement Dobivanje grafitne skice murala primjenom metode Hyper-Spectral ImagingIzvorni znanstveni rad Kako vrijeme prolazi murali postaju sve zagađeniji te originalni mural postaje nejasan i teško prepoznatljiv; stoga je važno dobivanje jasne grafitne skice murala. U ovom smo radu primijenili nevidljive spektre, posebice skoro-infracrvene pojaseve (near-infrared (NIR) bands), kako bismo otkrili podatke o grafitu i učvrstili karakteristične informacije o muralu za dobivanje grafitne skice. Ovo je prvo istraživanje u svrhu dobivanja osnovne linije konture iz skice murala primjenom tehnologije hiper-spektralnog slikovnog prikaza (hyper-spectral imaging (HSI). Najprije se metodama spektralne kompatibilnosti identificirao pigment osnovne konture te se grafit odredio kao osnovni pigment skice. Tada su se odabrali karakteristični pojasevi analizom spektra pigmenata. Nakon toga, metodom izvlačenja informacija dobivena su saznanja o grafitu. Rezultati su pokazali da se tom metodom mogla značajno povećati učinkovitost dobivanja novih spoznaja o grafitu. Ključni postupci ove metode obuhvatili su dobivanje spektra završnog elementa osnovne konture grafita, te mapiranje sive slike spektra osnovne konture grafit...

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“…Hyperspectral imaging (HSI) is a spin-off from remote sensing technology developed by NASA for space exploration and earth observation [1]. Hyperspectral imaging can extend human vision to infrared and near-infrared wavelength regions.…”

Section: Introductionmentioning

confidence: 99%

Hyperspectral imaging and spectral-spatial classification for cancer detection

Fei

Akbari

Halig

2012

2012 5th International Conference on BioMedical Engineering and Informatics

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Abstract-Hyperspectral imaging is an emerging modality for medical applications. Its spectroscopic data can be utilized to noninvasively detect cancer. In this study, an advanced image processing and classification method is proposed to analyze hyperspectral image data for prostate cancer detection. Least squares support vector machines (LS-SVMs) were developed and evaluated for classifying hyperspectral data in order to enhance the detection of cancer tissue. The method was used to detect prostate cancer in tumor-bearing mice. Spatially resolved images were created to highlight the differences of the reflectance properties of cancer versus those of normal tissue. Preliminary results with 11 mice show that the hyperspectral imaging and classification method was able to reliably detect prostate tumors in the animal model. This study may lead to advances in the optical diagnosis of cancer using hyperspectral imaging.

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Three decades of hyperspectral remote sensing of the Earth: A personal view

Cited by 649 publications

References 47 publications

Earth observation satellite sensors for biodiversity monitoring: potentials and bottlenecks

Earth observation satellite sensors for biodiversity monitoring: potentials and bottlenecks

Extracting graphite sketch of the mural using Hyper-Spectral Imaging method

Hyperspectral imaging and spectral-spatial classification for cancer detection

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