ALBERT

Description: Respiratory and heart rates are among the most important physiological parameters used to monitor patients’ health. It is important to design devices that can measure these parameters without risking or altering the subject’s health. In this context, a novel sensing method to monitor simultaneously the heartbeat and respiratory rate signals of patients within an electrically safety environment was developed and tested. An optical fiber-based sensor was used in order to detect two optical phenomena. Photo-plethysmography and the relation between bending radius and attenuation of optical fiber were coupled through a single beam light traveling along this fiber.

Description: Forests, Vol. 8, Pages 392: Estimation of Vegetation Cover Using Digital Photography in a Regional Survey of Central Mexico Forests doi: 10.3390/f8100392 Authors: Víctor Salas-Aguilar Cristóbal Sánchez-Sánchez Fabiola Rojas-García Fernando Paz-Pellat J. Valdez-Lazalde Carmelo Pinedo-Alvarez The methods for measuring vegetation cover in Mexican forest surveys are subjective and imprecise. The objectives of this research were to compare the sampling designs used to measure the vegetation cover and estimate the over and understory cover in different land uses, using digital photography. The study was carried out in 754 circular sampling sites in central Mexico. Four spatial sampling designs were evaluated in three spatial distribution patterns of the trees. The sampling designs with photographic captures in diagonal form had lower values of mean absolute error (MAE < 0.12) and less variation in random and grouped patterns. The Carbon and Biomass Sampling Plot (CBSP) design was chosen due to its smaller error in the different spatial tree patterns. The image processing was performed using threshold segmentation techniques and was automated through an application developed in the Python language. The two proposed methods to estimate vegetation cover through digital photographs were robust and replicable in all sampling plots with different land uses and different illumination conditions. The automation of the process avoided human estimation errors and ensured the reproducibility of the results. This method is working for regional surveys and could be used in national surveys due to its functionality.

Description: Sensors, Vol. 18, Pages 826: Mapping Wildfire Ignition Probability Using Sentinel 2 and LiDAR (Jerte Valley, Cáceres, Spain) Sensors doi: 10.3390/s18030826 Authors: Yolanda Sánchez Sánchez Antonio Martínez-Graña Fernando Santos Francés Marina Mateos Picado Wildfire is a major threat to the environment, and this threat is aggravated by different climatic and socioeconomic factors. The availability of detailed, reliable mapping and periodic and immediate updates makes wildfire prevention and extinction work more effective. An analyst protocol has been generated that allows the precise updating of high-resolution thematic maps. For this protocol, images obtained through the Sentinel 2A satellite, with a return time of five days, have been merged with Light Detection and Ranging (LiDAR) data with a density of 0.5 points/m2 in order to obtain vegetation mapping with an accuracy of 88% (kappa = 0.86), which is then extrapolated to fuel model mapping through a decision tree. This process, which is fast and reliable, serves as a cartographic base for the later calculation of ignition-probability mapping. The generated cartography is a fundamental tool to be used in the decision making involved in the planning of preventive silvicultural treatments, extinguishing media distribution, infrastructure construction, etc.