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A Special Issue titled ’New Insights in Crop Monitoring and Management Using Remote Sensing Data’ was launched in November 2022. It invited scientific contributions focused on the quantitative assessment of crop growth, management, and yield using innovative and integrated remote sensing techniques. To date, it has published 11 peer-reviewed research articles covering topics such as crop growth trajectory reconstruction, the retrieval of biophysical traits of leaves and crop canopies, crop aboveground biomass and yield prediction, and field irrigation amount estimation. The contributors come from research institutes and universities distributed in Russia, Canada, Brazil, Turkey, Germany, and the USA. Scholars from Xinjiang University proposed new algorithms to reconstruct Landsat EVI time series of crop growth seasons that are strongly polluted by clouds. Dr. Konstantin Muzalevskiy effectively estimated wheat height and aboveground biomass jointly using the MHz- and GHz-frequency band impulses when employing contactless ground penetration radar (GPR). A paper published in May of 2024 explored the use of VIS-NIR-SWIR hyperspectral and chlorophyll a fluorescence sensors to predict leaf structures and compounds and has received nine citations. An article estimating the aboveground biomass of winter wheat using a three-dimensional conceptual model with the help of UAV remote sensing images has 20 citations. This issue has garnered significant attention from agronomists, ecologists, and remote sensing scientists, as evidenced by its 30,569 web views.
