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RSS FeedsRemote Sensing, Vol. 11, Pages 2616: Validation of Earth Observation Time-Series: A Review for Large-Area and Temporally Dense Land Surface Products (Remote Sensing)

 
 

8 november 2019 23:03:31

 
Remote Sensing, Vol. 11, Pages 2616: Validation of Earth Observation Time-Series: A Review for Large-Area and Temporally Dense Land Surface Products (Remote Sensing)
 


Large-area remote sensing time-series offer unique features for the extensive investigation of our environment. Since various error sources in the acquisition chain of datasets exist, only properly validated results can be of value for research and downstream decision processes. This review presents an overview of validation approaches concerning temporally dense time-series of land surface geo-information products that cover the continental to global scale. Categorization according to utilized validation data revealed that product intercomparisons and comparison to reference data are the conventional validation methods. The reviewed studies are mainly based on optical sensors and orientated towards global coverage, with vegetation-related variables as the focus. Trends indicate an increase in remote sensing-based studies that feature long-term datasets of land surface variables. The hereby corresponding validation efforts show only minor methodological diversification in the past two decades. To sustain comprehensive and standardized validation efforts, the provision of spatiotemporally dense validation data in order to estimate actual differences between measurement and the true state has to be maintained. The promotion of novel approaches can, on the other hand, prove beneficial for various downstream applications, although typically only theoretical uncertainties are provided.


 
215 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 11, Pages 2617: A Method of Fast and Simultaneous Calibration of Many Mobile FMCW Radars Operating in a Network Anti-Drone System (Remote Sensing)
Remote Sensing, Vol. 11, Pages 2622: Evaluation of Incident Light Sensors on Unmanned Aircraft for Calculation of Spectral Reflectance (Remote Sensing)
 
 
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