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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Manual digitizing on aerial photographs is still commonly used for characterizing gully erosion over large areas. Even when automated detection procedures are implemented, manual digitizing is frequently being resorted to in order to constitute reference datasets used for training and validation. In both cases, manual digitizing entails some subjective decisions on behalf of the operator, which introduces uncertainty into the resulting datasets. To assess the magnitude of this uncertainty, 11 experienced operators were asked to digitize and classify ephemeral gullies (EGs) on cropland following a standardized methodology. The resulting 11 datasets were compared in terms of number, type and location of EGs. Furthermore, for EGs located on a well‐defined runoff flow concentration axis, the slope versus contributing area topographic thresholds required for initiating gully channels were assessed using four thresholding methods, and compared across the 11 datasets. The operators identified 259 different EGs. However, the number (52–139) and sum total length (8.9–23.7 km) of EGs varied widely across operators. Only 34% of the EGs were digitized by more than half of the operators, and 7% were identified by all. Identification of EGs located on a well‐defined flow concentration axis proved least subjective. The longer the EG and the more fields the EG crossed, the larger the number of operators that were able to identify it. EGs were also most easily identified when located in sugar beet fields as compared to other crops. EG classification and topographic threshold lines were also found to be strongly operator‐dependent. Quantile regression appeared to be one of the most robust thresholding methods. Operator subjectivity when digitizing EGs on orthophotographs introduces uncertainty that should be taken into account in future remote sensing‐based studies of EG erosion whenever they rely, in part or in full, on manual photograph interpretation. Copyright © 2014 John Wiley & Sons, Ltd.

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