Special Issue "Monitoring Land Surface Dynamic with AVHRR Data"
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (7 December 2018)
Dr. Stefan Wunderle
Head of Remote Sensing Research Group, Oeschger Centre for Climate Change Research, Institute of Geography, University of Bern, Hallerstrasse 12, CH-3012 Bern, Switzerland
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Phone: +41 31 631 8553
Interests: Essential Climate Variables (ECV) time series; AVHRR; snow extent; lake surface water temperature; fire; albedo; mountains
The Global Climate Observing System (GCOS) has defined many essential climate variables (ECV) to be monitored to understand changes of land systems (biosphere, cryosphere, and hydrosphere). The World Meteorological Organization (WMO) reported that a time series of at least 30 years is needed to retrieve statistically significant changes of ECVs. Considering that these are extended periods of time, only a limited selection of satellites and sensors can be used for global monitoring—one of these is the Advanced Very High Resolution Sensor (AVHRR) onboard of NOAA satellites (since 1981) and on the EUMETSAT platform MetOp (since 2006). The objective of the NOAA series was to deliver images on a regular basis, but not to use the data for quantitative investigations. The intended data application defines the AVHRR’s sensor design. For instance, onboard calibration for the VIS and NIR channels were not included, the orbit of the NOAA satellites was not stable, which results in an orbit drift with changing overpass times over the equator, and leads to variable solar illumination over area of interests throughout the lifetime of the satellite. Nevertheless, the four (five) spectral channels in VIS, NIR, and TIR, in addition to a spatial resolution of 1.1 km in nadir and high radiometric resolution of 10-bit, provides a very detailed view of clouds and the Earth surface—a milestone in satellite remote sensing.
The aim of this Special Issue of remote sensing is to compile the latest developments in AVHRR pre-processing (calibration, geo-coding) and ECV retrieval. This considers regional time series based on Local Area Coverage (LAC) data in 1.1 km in nadir but also global applications using Global Area Coverage (GAC) data in 4 km spatial resolution. The main focus is on the retrieval and validation of time series related to the following ECVs: Lakes, snow cover, glaciers and ice caps, ice sheets, permafrost, albedo, land cover (including vegetation type), fraction of absorbed photosynthetically active radiation (FAPAR), leaf area index (LAI), above-ground biomass, soil carbon, and fire disturbance. Additionally, papers describing new retrieval methods for the above-mentioned ECVs resulting in improved accuracy, which has to be documented with sound validation procedure are welcome. Furthermore, authors of methodological papers focusing on novel approaches to determine the uncertainty of the retrieved products are encouraged to submit their work, too.
Dr. Stefan Wunderle
Manuscript Submission Information
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- Essential Climate Variables (lakes, snow, glaciers, ice sheets, albedo, land cover, vegetation, fire)
- Long time series to fulfill the requirements of WMO
- New retrieval methods for the above mentioned ECVs
- Methodological papers focusing on uncertainty