Remote sensing technologies have been successfully used for deforestation monitoring, and with the wide availability of satellite products from different platforms, forest monitoring applications have grown in recent years. The observed potential in these technologies motivates the development of forest mapping and monitoring tools that could also be used for neighboring applications like agriculture or land-use mapping. A literature review confirmed the research areas of interest in deforestation monitoring using synthetic aperture radar (SAR) and data fusion techniques, which guided the formulation of the method developed in this article consisting of a data preprocessing workflow for SAR (Sentinel-1) and multispectral (Sentinel-2) data and a procedure for the selection of a machine learning model for forest/nonforest segmentation evaluated in different combinations of Sentinel-1 and Sentinel-2 bands. The selected model is a random forest algorithm that uses C-band SAR dual-polarimetric bands, intensity features, and vegetation indices derived from optical/multispectral data. The selected random forest classifier’s balanced accuracies were 79–81%, and the f1-scores were 0.72–0.76 for the validation set. The results allow the obtention of yearly forest/nonforest and forest loss maps in the study area of Bajo Cauca in Colombia, a region with a documented high deforestation rate.

Ultrashort bunch length measurements are crucial for characterizing electron beams in short-pulse accelerators, including novel accelerators like EuPRAXIA and those used for free-electron lasers (FELs). This work provides an overview of the design process and the current status of a single-shot bunch length monitor prototype based on a broadband spatial imaging system for coherent transition radiation (CTR), which was recently installed at the MAX IV short-pulse facility (SPF). The THz-based imaging system was designed using optical system simulation software for full bunch simulation. CTR images were captured experimentally, followed by image analysis for comparison with reference bunch length data from the transverse deflecting cavity (TDC). This paper presents the conceptualization and design choices for the optical system of the bunch length monitor, the current experimental set-up, the installation details, and preliminary positive observations confirming the potential of this method as a novel approach to bunch length monitoring using spatial CTR images and a scalar technique, with potential for future bunch profile measurements.