A viable method to implement oil spill detection and monitoring based on marine radar is proposed. The primary data of this study are obtained from the X-band marine radar of the teaching–training ship, YUKUN, of the Dalian Maritime University on July 21, 2010, when a pipeline burst and an oil spill accident occurred at the Xingang Port in Dalian. Aiming at the working characteristics of marine radar, the adaptive median filter algorithm is improved to eliminate the radar shared-frequency interference by adding the identification of noise points and resetting the neighborhood window. A power attenuation correction method is proposed to solve the uneven distribution in resolution and echo intensity by acquiring the average power distribution of radar images simultaneously. Oil spill will be easily detected from different sea backgrounds after morphological processing, gray segmentation, and image smoothing. Comparison with the images extracted from a thermal infrared sensor on the same monitoring point demonstrates the validity of the extraction method for oil spill based on X-band marine radar.
The harm of oil spills has caused extensive public concern. Remote sensing technology has become one of the most effective means of monitoring oil spill. However, how to evaluate the information extraction capabilities of various sensors and choose the most effective one has become an important issue. The current evaluation of sensors to detect oil films was mainly using in-situ measured spectra as a reference to determine the favorable band, but ignoring the effects of environmental noise and spectral response function. To understand the precision and accuracy of environment variables acquired from remote sensing, it is important to evaluate the target detection sensitivity of the entire sensor-air-target system corresponding to the change of reflectivity. The measurement data associated with the evaluation is environmental noise equivalent reflectance difference (NEΔRE ), which depends on the instrument signal to noise ratio(SNR) and other image data noise (such as atmospheric variables, scattered sky light scattering and direct sunlight, etc.). Hyperion remote sensing data is taken as an example for evaluation of its oil spill detection capabilities with the prerequisite that the impact of the spatial resolution is ignored. In order to evaluate the sensor’s sensitivity of the film of water, the reflectance spectral data of light diesel and crude oil film were used. To obtain Hyperion reflectance data, we used FLAASH to do the atmospheric correction. The spectral response functions of Hyperion sensor was used for filtering the measured reflectance of the oil films to the theoretic spectral response. Then, these spectral response spectra were normalized to NEΔRE, according to which, the sensitivity of the sensor in oil film detecting could be evaluated. For crude oil, the range for Hyperion sensor to identify the film is within the wavelength from 518nm to 610nm (Band 17 to Band 26 of Hyperion sensors), within which the thin film and thick film can also be distinguished. For light diesel oil film, the range for Hyperion sensor to identify the film is within the wavelength from 468nm to 752nm (Band 12 to Band 40 of Hyperion sensors).
Crop breeding and variety analysis play the important role in the national economy. A lot of sample data and typical
probability distribution are needed in the conventional methods to evaluate the high-yield crop cultivars such as
correlation analysis, regression analysis and grey relational grade analysis etc, which are difficult to be realized. Delayed
fluorescence (DF) can be used to evaluate plant photosynthesis. The current investigation has revealed that there is a
good linear correlation between DF and photosynthesis capacity. More importantly, the slopes of linear fit of the
correlationship for different yield varieties are different. Four known yield crop cultivars from each of the two different
species (Maize and Soybean) are selected as samples to be analyzed. The statistical results show that the slope of
high-yield variety is smaller than that of low-yield. We thus conclude that the slope of linear fit of correlation between
DF and photosynthesis capacity is an excellent marker for high-yield crop cultivars identification. Compared with the
conventional methods, the presented method needs less samples and it's fast and easy to be measured.
Remote sensing is an effective tool to monitor oil spills. The theory of oil spill remote sensing is based on the differences
between oil slick and other environmental objects. For optical sensor, the ability of different bands to find oil film at sea
is different. Oil spill object could be intensified by composing appropriate bands. In addition, image enhancements could
also strengthen oil spill features. For SAR, image characteristics of oil spill are crucial to oil detection. Applications
show that sensors loaded on satellite can find oil slick at sea. Optical sensor and SAR have their own advantages, and
play different roles in oil spill remote sensing. It is necessary to integrate them to establish an all-weather,
omnidirectional 3-D monitoring network for monitoring oil spills and illicit vessel discharges.
Oil spills are seriously affecting marine ecosystem and cause political and scientific concern. In order to implement an emergency in case of oil spills, it is necessary to monitor oil spill using remote sensing. Techniques for monitoring oil spills includes optical, microwave, and radar approaches using aircraft or satellites. However, Satellites have wider coverage and lower price. Recent years, with more sensors launching, correctness and real time of oil spills monitoring using satellites are improved. Based on many successful experiences in oil spills monitoring, sensitivities of different bands to different oil types are analyzed using AVHRR and TM data, and methodologies to extract oil spills information, especial oil thickness, are presented. In addition, with regard to requirements of customers, position, area, drifting trajectory and velocity can be calculated, which supports marine oil spill fast emergency response effectively. It is believed that it is possible to establish an oil spill monitoring network using satellite covering main sea area in China.
Oil spills are seriously affecting the marine ecosystem. In order to implement an emergency in case of oil spills, it is
necessary to monitor oil spill using remote sensing. Spectral measurements are undertaken for several oil types in 1998
and 1999. Based on the oil spectral characteristics, this study demonstrates how MODIS (Moderate Resolution Imaging
Spectroradiometer) can monitor oil spills in an oil spill event occurred near Dalian in North China Sea. The study shows
that MODIS has possessed some hyperspectral characteristics, which improve the capability of oil spill monitoring.