Mapping of hydrothermally altered rocks by the EO‐1 Hyperion sensor, Northern Danakil Depression, Eritrea

Gersman, Ronen; Ben‐Dor, Eyal; Beyth, M.; Avigad, Dov; Abraha, Michael; Kibreab, Alem

doi:10.1080/01431160701874587

Cited by 72 publications

(25 citation statements)

References 40 publications

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“…Hyperion's data were found of greater utility than data from the broad bands Landsat TM to create surface cover abundance maps [107,108]. Some Hyperion studies were able to distinguish green vegetation from talc, dolomite, chlorite and white micas [109], while others differentiated calcite from dolomite [7], detected differences in solid solution of micas [7] or spotted ammonium-bearing minerals with the 1558-nm band characterized by a relatively high SNR [110]. On the other hand, Leverington [107,108] obtained poor to moderate results when using Hyperion to separate several important sedimentary lithological end-members in Texas and Canada.…”

Section: Geology Applicationsmentioning

confidence: 99%

“…A few months after the launch of Hyperion, Pearlman et al [193] reported SNRs values from 140:1-190:1 in the VNIR, 96:1 in the SWIR around 1225 nm and 38:1 in the SWIR around 2125 nm. Based on Hyperion imagery and three specific targets when mapping hydrothermally-altered rocks, Gersman et al [110] estimated an SNR of 90:1 for the VIS range, 60:1 for the 1000-1600-nm bands and 35:1 for the 2000-2400-nm bands. Kruse et al [7] reported SNR values of about 25:1 for the 2000-2400-nm bands for less-than-optimum acquisition conditions (i.e., winter season, dark targets).…”

Section: Revisit Timementioning

confidence: 99%

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Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context

et al. 2018

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In the last few decades, researchers have developed a plethora of hyperspectral Earth Observation (EO) remote sensing techniques, analysis and applications. While hyperspectral exploratory sensors are demonstrating their potential, Sentinel-2 multispectral satellite remote sensing is now providing free, open, global and systematic high resolution visible and infrared imagery at a short revisit time. Its recent launch suggests potential synergies between multi-and hyper-spectral data. This study, therefore, reviews 20 years of research and applications in satellite hyperspectral remote sensing through the analysis of Earth observation hyperspectral sensors' publications that cover the Sentinel-2 spectrum range: Hyperion, TianGong-1, PRISMA, HISUI, EnMAP, Shalom, HyspIRI and HypXIM. More specifically, this study (i) brings face to face past and future hyperspectral sensors' applications with Sentinel-2's and (ii) analyzes the applications' requirements in terms of spatial and temporal resolutions. Eight main application topics were analyzed including vegetation, agriculture, soil, geology, urban, land use, water resources and disaster. Medium spatial resolution, long revisit time and low signal-to-noise ratio in the short-wave infrared of some hyperspectral sensors were highlighted as major limitations for some applications compared to the Sentinel-2 system. However, these constraints mainly concerned past hyperspectral sensors, while they will probably be overcome by forthcoming instruments. Therefore, this study is putting forward the compatibility of hyperspectral sensors and Sentinel-2 systems for resolution enhancement techniques in order to increase the panel of hyperspectral uses.

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Section: Geology Applicationsmentioning

confidence: 99%

Section: Revisit Timementioning

confidence: 99%

Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context

et al. 2018

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“…Though Hyperion images are characterized by relatively high levels of noise [59,[62][63][64][65][66][67][68], they represent important alternatives to datasets generated by orbiting multispectral systems. In numerous case studies, Hyperion images have proven useful in the mapping of lithological and mineralogical classes [63,64,67,[69][70][71][72][73][74][75][76]. In the Sudbury region, Hyperion images have previously been used in the study of vegetation growth related to land reclamation near smelters [20,77].…”

Section: Hyperion Imagesmentioning

confidence: 99%

Detection and Mapping of Black Rock Coatings Using Hyperion Images: Sudbury, Ontario, Canada

Leverington

Schindler

2016

Remote Sensing

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Base metal smelting activities can produce acidic rain that promotes vegetation loss and the development of black coatings on bedrock. Such coatings can form over large areas and are among the most prominent long-term vestiges of past smelting activities. In this study, multispectral images derived from Hyperion reflectance data were evaluated with regard to their utility in the discrimination and mapping of black rock coatings near Sudbury. Spectral angle mapper (SAM) classifications generated on the basis of image-derived endmember spectra could not be used to properly identify major exposures of coated bedrock without also producing substantial confusion with uncoated classes. Neural network and maximum likelihood classifications produced improved representations of the spatial distribution of coated bedrock, though confusion between coated and uncoated classes is problematic in most outputs. Maximum likelihood results generated using a null class are noteworthy for their effectiveness in highlighting exposures of coated bedrock without substantial confusion with uncoated classes. Although challenges remain, classification results confirm the potential of remote sensing techniques for use in the worldwide detection, mapping, and monitoring of coating-related environmental degradation in the vicinities of base metal smelters.

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“…Furthermore, we applied the forward-inverse Minimum Noise Fraction Transformation (MNFT) in the EO-1 Hyperion image, in order to reduce noise of the images for both the VNIR and SWIR bands of the image, for reducing the residual noise of the imagery [55]. The MNF components that resulted from the forward transformation were analyzed for their spectral information content based on their eigenvalues which represent the SNR.…”

Section: Image Pre-processingmentioning

confidence: 99%

A Comparative Analysis of EO-1 Hyperion, Quickbird and Landsat TM Imagery for Fuel Type Mapping of a Typical Mediterranean Landscape

2014

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Forest fires constitute a natural disturbance factor and an agent of environmental change with local to global impacts on Earth's processes and functions. Accurate knowledge of forest fuel extent and properties can be an effective component for assessing the impacts of possible future wildfires on ecosystem services. Our study aims to evaluate and compare the spectral and spatial information inherent in the EO-1 Hyperion, Quickbird and Landsat TM imagery. The analysis was based on a support vector machine classification approach in order to discriminate and map Mediterranean fuel types. The fuel classification scheme followed a site-specific fuel model within the study area, which is suitable for fire behavior prediction and spatial simulation. The overall accuracy of the Quickbird-based fuel type mapping was higher than 74% with a quantity disagreement of 9% and an allocation disagreement of 17%. Both classifications from the Hyperion and Landsat TM fuel type maps presented approximately 70% overall accuracy and 16% allocation disagreement. The McNemar's test indicated that the overall accuracy differences between the three produced fuel type maps were not significant (p < 0.05). Based on both overall and individual higher accuracies obtained with the use of the Quickbird image, this study suggests that the high spatial resolution might be more decisive than the high spectral resolution in Mediterranean fuel type mapping.

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Mapping of hydrothermally altered rocks by the EO‐1 Hyperion sensor, Northern Danakil Depression, Eritrea

Cited by 72 publications

References 40 publications

Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context

Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context

Detection and Mapping of Black Rock Coatings Using Hyperion Images: Sudbury, Ontario, Canada

A Comparative Analysis of EO-1 Hyperion, Quickbird and Landsat TM Imagery for Fuel Type Mapping of a Typical Mediterranean Landscape

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