REMOTE SENSING TECHNIQUES FOR DETECTING OIL SLICKS AT SEA—A REVIEW OF WORK CARRIED OUT IN THE UNITED KINGDOM

1987 ◽  
Vol 1987 (1) ◽  
pp. 95-100
Author(s):  
Douglas Cormack ◽  
Neil Hurford ◽  
David Tookey

ABSTRACT The U.K. Department of Transport has equipped a light aircraft with a remote sensing system. The capabilities of the sensors for detecting oil slicks have been evaluated and the aircraft is now being used to carry out surveillance patrols. A detailed evaluation has been carried out into the feasibility of using microwave radiometry to supply more detailed information about oil slick thickness. The results showed that such a detector should only be used in conjunction with existing IR and UV sensors.

1978 ◽  
Vol 9 (9) ◽  
pp. 234-238 ◽  
Author(s):  
R.A.A. Blackman ◽  
F.L. Franklin ◽  
M.G. Norton ◽  
K.W. Wilson

2019 ◽  
Vol 11 (1) ◽  
pp. 219-235 ◽  
Author(s):  
Elżbieta Bielecka ◽  
Elżbieta Burek

Abstract Using the literature review and quantitative analysis, the research on the quality and uncertainty of spatial data have been compared and analysed according to years of publication, authors, document types, WoS categories, and countries. The paper portrayed the development in the field, studied the state and evolution of the most productive and influential journals, conferences, and research institutions. The results showed that remote sensing, computer science, and geography relate mostly to data imperfection and assessment of its uncertainty. This relation is clearly translated into the most productive journals, and conferences proceedings. The top-ranked countries in this field are United States, China, and the United Kingdom.


2019 ◽  
Vol 14 (5) ◽  
pp. 728-743
Author(s):  
Tetsuya Jitsufuchi ◽  

In 2016, we launched the “Promotion Project for Next Generation Volcano Research B2 (Theme B: Development of Cutting-edge Volcano Observation Technology, subtheme 2: Development of Remote Sensing Techniques for Volcano Observation), subtopic 2-2 (Development of Remote Sensing Techniques for Surface Phenomena of Volcano)” under the “Integrated Program for Next Generation Volcano Research and Human Resources Development” [1], aiming at the development of an optical multispectral remote sensing system for measuring volcanic surface phenomena. With subtopic 2-2, we are planning to develop a new observation device called a surface phenomena imaging camera (SPIC), which is technically superior to current remote sensing techniques, i.e., optical remote observation techniques used to observe volcanic surface phenomena from aircrafts or ground. We are also aiming at applying the developed observation system to quantify volcanic activities and determine volcanic eruption potentials (degrees of urgency) or branching of event trees for volcanic crises with high accuracy, contributing to better predictions of volcanic eruption transitions. To achieve the above-mentioned aims, we started the development of the SPIC by equipping it with camera-type sensors, based on preliminary analyses of the experimental observations made with the airborne spectral imaging system ARTS-SE, which consists of a pushbroom scanner and a camera system, developed by the National Research Institute for Earth Science and Disaster Resilience in FY 2015. We have already developed its components, such as the prototype filter-type multiband cameras SPIC-UC, a prototype uncooled infrared camera, SPIC-C, a cooled camera, and SPIC-SS, a visible-light camera. The SPIC-UC is a two-band camera with the function of visualizing temperature and SO2 gas concentration distributions. The SPIC-C has the function of measuring temperatures between 2 and 1075◦C with high accuracy (noise equivalent temperature difference, NETD: 16 mK); it is equipped with a sensor and a filter wheel that work in the middle wave infrared region (MWIR). The SPIC-SS is a six-lens multiband camera system that estimates the measured images from multiband spectra (6 bands) to hyper spectra (300 bands). Further, we studied a method to estimate digital surface model with a ∼30-m error. As our plan has progressed as scheduled, we intend to complete the prototype SPIC by 2020.


2009 ◽  
pp. 1-6 ◽  
Author(s):  
Nishan Fernando ◽  
Gordon Prescott ◽  
Jennifer Cleland ◽  
Kathryn Greaves ◽  
Hamish McKenzie

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