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For mapping, quantifying and monitoring regional and global forest health, satellite remote sensing provides fundamental data for the observation of spatial and temporal forest patterns and processes. While new remote-sensing technologies are able to detect forest data in high quality and large quantity, operational applications are still limited by deficits of in situ verification. In situ sampling data as input is required in order to add value to physical imaging remote sensing observations and possibilities to interlink the forest health assessment with biotic and abiotic factors. Numerous methods on how to link remote sensing and in situ data have been presented in the scientific literature using e.g. empirical and physical-based models. In situ data differs in type, quality and quantity between case studies. The irregular subsets of in situ data availability limit the exploitation of available satellite remote sensing data. To achieve a broad implementation of satellite remote sensing data in forest monitoring and management, a standardization of in situ data, workflows and products is essential and necessary for user acceptance. The key focus of the review is a discussion of concept and is designed to bridge gaps of understanding between forestry and remote sensing science community. Methodological approaches for in situ/remote-sensing implementation are organized and evaluated with respect to qualifying for forest monitoring. Research gaps and recommendations for standardization of remote-sensing based products are discussed. Concluding the importance of outstanding organizational work to provide a legally accepted framework for new information products in forestry are highlighted. [ABSTRACT FROM AUTHOR]

For mapping, quantifying and monitoring regional and global forest health, satellite remote sensing provides fundamental data for the observation of spatial and temporal forest patterns and processes. While new remote-sensing technologies are able to detect forest data in high quality and large quantity, operational applications are still limited by deficits of in situ verification. In situ sampling data as input is required in order to add value to physical imaging remote sensing observations and possibilities to interlink the forest health assessment with biotic and abiotic factors. Numerous methods on how to link remote sensing and in situ data have been presented in the scientific literature using e.g. empirical and physical-based models. In situ data differs in type, quality and quantity between case studies. The irregular subsets of in situ data availability limit the exploitation of available satellite remote sensing data. To achieve a broad implementation of satellite remote sensing data in forest monitoring and management, a standardization of in situ data, workflows and products is essential and necessary for user acceptance. The key focus of the review is a discussion of concept and is designed to bridge gaps of understanding between forestry and remote sensing science community. Methodological approaches for in situ/remote-sensing implementation are organized and evaluated with respect to qualifying for forest monitoring. Research gaps and recommendations for standardization of remote-sensing based products are discussed. Concluding the importance of outstanding organizational work to provide a legally accepted framework for new information products in forestry are highlighted.

A widE-Ranging investigation of the first COVID-19 LOCkdown effects on the atmospheric composition in five Italian Urban Sites (AER–LOCUS) has been carried out and is presented in this study. The analysis uses particle and gas concentrations from surface in situ sampling, column aerosol and gas properties from photometer/spectrometers, and satellite NO 2 determinations at five sites distributed over the whole Italian territory: Aosta, Milan, Bologna, Rome, and Taranto. These data are related to meteorological conditions to identify the numerous events of long-range transport and separate local from remote influences. Four different types of long-range transport over Italy are identified during the lockdown period, affecting PM 10 , PM 2.5 , and NO 2 concentrations, and aerosol optical depths: fires plumes from Eastern Europe and Montenegro, dust from the Caspian area and from the Sahara, and pollution from the Po Valley. Once the long-range transport events are identified and excluded, the variation of gas and particle concentrations occurring during the containment period is calculated with respect to the period 2015–2019. A general decrease of PM 10 (ranging from a maximum of −52% in Aosta to a minimum of −4% in Taranto), PM 2.5 (from −46% in Aosta and Milan to −0.6% in Bologna), BC (from −77% in Aosta to −25% in Milan), NO 2 (from −72% in Rome to −4% in Taranto), and benzene (about −50%) concentration is found. A positive variation of PM 2.5 is conversely found during March in the southern sites due to some stagnation events, and a strong increase of benzene (up to +104%) in the industrial area of Taranto. Ozone is found to increase by an average of about 30% in all sites. The removal of the long-range transport contributions affects the variations with respect to the reference period reducing the concentrations by up to 22% for PM 10 and 29% for PM 2.5 in the northern sites, and 18% for PM 10 and 16% for PM 2.5 in the southern sites. For NO 2 the reduction due to the removal is up to 14% in Milan and 6% in the southern sites, while for the aerosol optical depth it is up to 70% in Aosta and 50% in Rome. [Display omitted] • Pollutant concentrations during the lockdown are affected by long-range transports of air masses from outside. • The long-range transports are spotted by ground/space remote sensing, in situ sampling and meteorological analysis. • The effects on the local emissions due only to the restrictions are identified. • The relative variation of gas and particle concentrations with respect to the period 2015–2019 is calculated. • The removal of the long-range transports leads to a greater reduction of the concentrations. [ABSTRACT FROM AUTHOR]