Editorial Board Members’ Collection Series: From Data to Field — towards the Standardization of Processes, Products, and Services in Remote Sensing

Dear Colleagues,

A huge amount of remotely sensed data, products, and services are entering many application fields, used toward a technology transfer that could somehow be commercially exploitable. Nevertheless, a high degree of variability is proving to affect the processing chain, creating paradoxical situations where different results can be obtained from the same native data. The present availability of free data from global scientific programs (Copernicus, Landsat, etc.) and the easiness of self-managed acquisitions from remotely piloted aerial systems (RPAS) bring remote sensing closer to the user than ever before. Unfortunately, this easiness of data access coupled with a very high degree of automation that software (e.g., drone data processing) provides also attract users who are not properly skilled and, therefore, unable to properly  read and understand the generated results. The way data are processed strictly depends on algorithms, users’ scientific background, and, in many cases, expected/desired (not actual) results. This makes any final product from remote sensing unreliable, even if scientifically sounding and robust, forbidding a true transfer of this technology. Consequently, the need arises to define, certify, and validate procedures of data processing.

Especially in those fields where quantitative information from remotely sensed data is used to address management practices whose properness can highly impact the final outcome (e.g., agriculture), adequateness of data processing is crucial. A situation where the same, differently processed data generate inconsistent results cannot be allowed any more, especially when a service is provided to support final users. Standardization and certification are therefore mandatory to make results comparable. This need is even higher considering that the time domain is playing a crucial role today, requiring that maps or estimates obtained at different times are consistent.

In this framework, this Special Issue is intended to collect all those research experiences based on remotely sensed data referring to:

• Data validation;
• Comparison of processes;
• Significance of measures;
• Operating services and procedures;
• Standard definition of data, processing, and results formats;
• Guidelines for standard definition.

Dr. Enrico Borgogno-Mondino
Dr. Baskaran Stephen Inbaraj
Guest Editors

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• data validation
• comparison of processes
• significance of measures
• operating services and procedures
• standard definition of data, processing, and results formats
• guidelines for standard definition