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Wildfires are one of the most destructive disasters on the planet. They also significantly impact the land surface. Satellite data have been widely used to detect the outbreak and monitor the expansion of fire incidents for damage assessment and disaster management. Polar-orbiting satellite data have been used for several decades but data from geostationary satellites, which can provide observations with a high temporal resolution, have received much less attention. This paper utilizes data from FengYun-2G, a Chinese geostationary satellite, to detect wildfires in two selected research regions in January 2016. The detection algorithm systemizes image-based analysis to filter out obvious nonfire pixels and temporal analysis to confirm the true detections. Fire detection is based on comparisons between predicted and observed values. The results show that the proposed method has some advantages compared with the use of polar-orbiting satellite data, including early detection and continuous observation. The validation work is conducted based on the collection 6.1 Global Monthly Fire Location Product generated from fire detections by Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. The average accuracy within the target time is 56%, while the omission error rate is over 78%. In detail, the algorithm has a lower omission error rate in Australia while it fails in detecting most of the fire pixels in India. The dominance of small fire incidents, as well as low spatial resolution greatly limit the detection ability. Many small fires were beyond the ability of Stretched Visible and Infrared Spin Scan Radiometer (S-VISSR) data when no significant fire characteristics could be captured. Future development of the algorithm will focus on improving the results by enhancing the adaption to different regions, as well as, including multisource data sets. [ABSTRACT FROM AUTHOR]

Recent growth in seaborne trade has increased the tugboat operation cycle to maneuver incoming marine vessels at port. To meet the tugboat load demand for maneuvering, multiple power sources are being employed on-board. This necessitates a coordinated control strategy for the effective operation of these multiple power sources. To design an effective coordinated control strategy, this article initially estimates multiple power sources capacities (doubly fed induction machine (DFIM) and battery storage system) for a diesel-electric tugboat system based on a real-time tugboat operation cycle obtained from Visakhapatnam port, India. With respect to these multiple power sources, a coordinated control strategy for a better fuel efficiency is proposed based on a state machine control algorithm. The proposed control strategy operates a variable speed diesel-electric generator (diesel engine coupled DFIM) at a minimum specific fuel consumption value and battery based on its state of charge. To show the efficacy of the proposed variable speed diesel-electric system, fuel consumption is computed, which resulted in 26.42% of saving in comparison with a traditionally used diesel-mechanical tugboat. To evaluate the real-time system (2 MW DFIM + 150 kWh battery), MATLAB/Simulink tool is used and an experimental demonstration is performed on a laboratory prototype. [ABSTRACT FROM AUTHOR]