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The Special Issue on “Remote Sensing in Agriculture: State-of-the-Art” gives an exhaustive overview of the ongoing remote sensing technology transfer into the agricultural sector. It consists of 10 high-quality papers focusing on a wide range of remote sensing models and techniques to forecast crop production and yield, to map agricultural landscape and to evaluate plant and soil biophysical features. Satellite, RPAS, and SAR data were involved. This preface describes shortly each contribution published in such Special Issue.

Technology: general issues --- History of engineering & technology --- Environmental science, engineering & technology --- feature selection --- spectral angle mapper --- support vector machine --- support vector regression --- hyperspectral imaging --- UAV --- cross-scale --- yellow rust --- spatial resolution --- winter wheat --- MODIS --- northern Mongolia --- remote sensing indices --- spring wheat --- yield estimation --- UAV-based LiDAR --- biomass --- crop height --- field phenotyping --- oasis crop type mapping --- Sentinel-1 and 2 integration --- statistically homogeneous pixels (SHPs) --- red-edge spectral bands and indices --- recursive feature increment (RFI) --- random forest (RF) --- unmanned aerial vehicles (UAVs) --- remote sensing (RS) --- thermal UAV RS --- thermal infrared (TIR) --- precision agriculture (PA) --- crop water stress monitoring --- plant disease detection --- vegetation status monitoring --- Landsat --- data blending --- crop yield prediction --- gap-filling --- volumetric soil moisture --- synthetic aperture radar (SAR) --- Sentinel-1 --- soil moisture semi-empirical model --- soil moisture Karnataka India --- reflectance --- digital number (DN) --- vegetation index (VI) --- Parrot Sequoia (Sequoia) --- DJI Phantom 4 Multispectral (P4M) --- Synthetic Aperture Radar --- SAR --- lodging --- Hidden Markov Random Field --- HMRF --- CDL --- corn --- soybean --- crop Monitoring --- crop management --- apple orchard damage --- polarimetric decomposition --- entropy --- anisotropy --- alpha angle --- storm damage mapping --- economic loss --- insurance support

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“Smart Sensing Technologies for Agriculture” is a Special Issue of Sensors that includes 14 research papers on diverse topics about the measurement of physical, chemical, and biological characteristics of soil, plants, and animals related to modern farming practices.

History of engineering & technology --- moisture measurement --- Kalman filter --- model predictive control --- germination paper --- convolutional neural networks --- livestock --- lying posture --- standing posture --- Three-dimensional mapping --- quasi-3D inversion algorithm --- cation exchange capacity --- clay content --- sandy infertile soil --- optical micro-sensors --- crop protection --- precision agriculture --- infrared spectroscopy --- principal component analysis (PCA) --- partial least squares (PLS) --- droplet characterization --- apparent electrical conductivity (ECa) --- pH --- UAV --- boundary-line --- quantile regression --- law of minimum --- on-site detection --- ion-selective electrode (ISE) --- soil nitrate nitrogen (NO3−-N) --- soil moisture --- sensor fusion --- transfer learning --- deep learning --- body dimensions --- point cloud --- Kd-network --- feature recognition --- FFPH --- non-contact measurement --- X-ray fluorescence --- spectroscopy --- soil nutrients --- proximal soil sensing --- soil testing --- laser-induced breakdown spectroscopy --- LIBS --- elemental composition --- broiler surface temperature extraction --- thermal image processing --- head region locating --- adaptive K-means --- ellipse fitting --- harvesting robot --- gripper --- segmentation --- cutting point detection --- soil --- soil electrical resistivity --- autonomous robot --- real-time measurement --- precision farming --- mapping --- precision weeding --- multispectral imaging --- kinetic stereo imaging --- plant detection --- yield estimation --- machine vision --- willow tree