Correction of Remotely Sensed Imagery

Dear Colleagues,

The development of highly efficient correction methods for the fast and accurate retrieval of bio- and geo-physical key variables for a wide variety of atmospheric conditions and land or ocean surface types remains a challenging task for providing the end-users with methods suitable for operational processing flow.

Producing high precision standard surface reflectance products both in terms of recovering quality and implementation efficiency is even more challenging for the multisensor exploitation of remotely sensed scenes possibly captured in different inclement conditions.

These methods should adapt to a wide variety of operational conditions, involving a wide range of spatial and spectral resolutions, including coarse, medium and high resolution cases, different temporal scales (frequent or long-term surveys) as well as to different sensor suites (multi-, hyper- spectral, radar). In every case, the ultimate goal is to provide high quality sensor data that meet the users' requirements and expectations for interdisciplinary applications.

This Special Issue is thus intended to cover the last advances (but not limited to) related to the accurate correction of data remotely sensed from emerging technologies and platforms (spaceborne, airborne and from Unmanned Aerial Vehicles). This typically includes the conventional stages of atmospheric, radiometric, and geometric corrections as well as all methods for internal calibration, external re-calibration and post-processing methods developed to mitigate or properly compensate for a strong variation of disturbances or correct attenuation, artefacts, measurement and residual errors from any error source (calibration anomaly, geolocation, misalignment, topographic relief effect, shadow area, data inconsistencies between sensor(s),...). Validation methods for comparing retrieved parameters to either forward bio- or geo- physical or in situ measurements are also focused.

A wide spectrum of recent and latest emerging applications highlighting remotely sensed data corrections are obviously targeted including biodiversity assessment, vegetation and environmental monitoring (identification of diversity in grassland species, invasive plants, biomass estimation, wetlands), precision agriculture in agricultural ecosystems and crop management, water resource and quality management in nearshore coastal (mapping near-surface water constituents, benthic habitats) and inland waters (analysis and surveying of rivers and lakes), sustainable forestry and agroforestry (forest preservation and mapping of forest species, wildfire detection), mapping archaeological areas, urban development and management, land data assimilation system over mountainous terrain and hazard monitoring.

Dr. Benoit Vozel
Dr. Adrianos Retalis
Guest Editors

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