Satellite Remote Sensing Phenological Libraries

Dear Colleagues,

Satellite remote sensing can provide the necessary data to estimate phenology, an important element of landscape that can be useful, especially for climate and land use change assessments, at the global, continental, regional or even local scales. Phenology data can be used for the assessment of vegetation types distribution, carbon budget quantification, evaluation of year-to-year spatial and temporal variations of vegetation seasonality, and the dependence of these variations on environmental factors. Phenology data sets are also important for estimation of primary productivity, ecosystem healthiness and they also serve as input to land surface models. Given the plethora of free satellite missions and the available products, either those coming from medium-to-high spatial resolution sensors, e.g. Landsat and Sentinel, or from moderate resolution sensors, e.g. MODIS, time series methods are becoming very popular approaches. Moreover, the advent of hyperspectral missions, like PRISMA and Venµs, is opening new possibilities to estimate phenological parameters, allowing more precise spectral diagnostic and quantitative monitoring of vegetation phenology status over larger areas.

Remote sensing phenology captures broad scale phenological patterns with high degree of homogeneity and standardization offered by the nature of remote sensing data. Remotely sensed phenological data can be useful for numerous applications covering fields like forestry, agriculture, climate, hazards, oceanography and inland waters, drought severity, and wildfire risk. Under this perspective, in this special issue we expect and welcome high quality manuscripts on the assessment and use of satellite remote sensing time series data and satellite remote sensing phenological libraries that can be used in any scientific domain and field.

Assoc. Prof. Dr. Nikos Koutsias
Assoc. Prof. Dr. Alexandra Gemitzi
Dr. Sofia Bajocco
Guest Editors

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