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This requirement discusses the need for a long-term time series data set for Earth observation, focusing on AVHRR, MODIS, VIIRS, and SGLI. It emphasizes the importance of storing original and corrected data for future analysis and the inclusion of reference information in higher-level products.
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Requirements on long term Earth observation time series data set - for successive process of AVHRR/MODIS/VIIRS data - Koji Kajiwara Center for Environmental Remote Sensing, Chiba University Also SGLI
Long Term Earth Observation • In order to understand the global change from satellite observed data, at least 50 years time series data is required. • Past and feature obtained satellite data must be stored for sophisticated data analysis in future.
Item to be considered for time series data set • Geometric / radiometric correction of each sensor data is important but most important thing is to keep original data and correction parameter for future analysis • One of reason is to prevent miss-understand of the meaning of data representing for end user.
NOAAAVHRRNDVIimage Jan. Mar. May Jul.
Land Cover Classification Mapcreated form AVHRR-NDVI product
Problem • Higher level product which processed with uncertain parameters cannot be verified in future analysis.
Requirements • While geometric correction is needed for time series analysis, each pixel must be able to refer the original observed data. • The data structure of stored data which can be used for re-processing should be considered.
Requirements • Higher products also must be contain reference information stored in original data.
Schematic diagram of long term time series data set Long term time series data set Original Images Higher product
Discussions between each organization related to store the Earth observation data is needed. • In Japan, discussions of storage structure for AVHRR L1b and higher product data is started between remote sensing community of universities.