Decision Support System for Managing Oil Spill Events

The Mediterranean environment is exposed to various hazards, including oil spills, forest fires, and floods, making the development of a decision support system (DSS) for emergency management an objective of utmost importance. The present work presents a complete DSS for managing marine pollution events caused by oil spills. The system provides all the necessary tools for early detection of oil-spills from satellite images, monitoring of their evolution, estimation of the accident consequences and provision of support to responsible Public Authorities during clean-up operations. The heart of the system is an image processing–geographic information system and other assistant individual software tools that perform oil spill evolution simulation and all other necessary numerical calculations as well as cartographic and reporting tasks related to a specific management of the oil spill event. The cartographic information is derived from the extant general maps representing detailed information concerning several regional environmental and land-cover characteristics as well as financial activities of the application area. Early notification of the authorities with up-to-date accurate information on the position and evolution of the oil spill, combined with the detailed coastal maps, is of paramount importance for emergency assessment and effective clean-up operations that would prevent environmental hazard. An application was developed for the Region of Crete, an area particularly vulnerable to oil spills due to its location, ecological characteristics, and local economic activities.     

SAR图像的小波阈值去噪研究

研究了如何有效抑制合成孔径雷达图像中的斑点噪声并尽量保留图像的细节信息.选用具有较好紧支性和正交性的Daubechies小波,对图像进行2D小波变换,并在对各层小波系数阈值处理时采用了软硬阈值方法以及改进的软硬阈值折衷方法.实验表明,小波阈值去噪较许多常用的斑点去噪方法具有很大优势,而软硬阈值折衷方法可以一定程度上结合软、硬阈值处理的优点,既能较好地滤除SAR图像中的斑点噪声,又具有较好的边缘保持能力,从而改善了图像的解译能力.     

Using NOAA AVHRR data to assess flood damage in China

The article used two NOAA-14 Advanced Very High ResolutionRadiometer (AVHRR) datasets to assess flood damage in the middleand lower reaches of China's Changjiang River (Yangtze River) in 1998. As the AVHRR is an optical sensor, it cannot penetratethe clouds that frequently cover the land during the flood season, and this technology is greatly limited in flood monitoring. However the widely used normalized difference vegetation index (NDVI) can be used to monitor flooding, sincewater has a much lower NDVI value than other surface features.Though many factors other than flooding (e.g. atmospheric conditions, different sun-target-satellite angles, and cloud) can change NDVI values, inundated areas can be distinguished fromother types of ground cover by changes in the NDVI value beforeand after the flood after eliminating the effects of other factors on NDVI. AVHRR data from 26 May and 22 August, 1998 wereselected to represent the ground conditions before and after flooding. After accurate geometric correction by collecting GCPs,and atmospheric and angular corrections by using the 6S code, NDVI values for both days and their differences were calculatedfor cloud-free pixels. The difference in the NDVI values betweenthese two times, together with the NDVI values and a land-use map, were used to identify inundated areas and to assess the arealost to the flood. The results show a total of 358 867 ha, with 207 556 ha of cultivated fields (paddy and non-irrigated field) inundated during the flood of 1998 in the middle and lower reaches of the Changjiang River Catchment; comparing with the reported total of 321 000 and 197 000 ha, respectively. The discrimination accuracy of this method was tested by comparing the results from two nearly simultaneous sets of remote-sensingdata (NOAA's AVHRR data from 10 September, 1998, and JERS-1 synthetic aperture radar (SAR) data from 11 September, 1998, with a lag of about 18.5 hr) over a representative flooded regionin the study area. The results showed that 67.26% of the total area identified as inundated using the NOAA data was also identified as inundated using the SAR data.     

监测浒苔灾害的微波遥感数据选取

2008年奥帆赛举办地青岛海域出现了大面积的浒苔自然灾害,利用卫星遥感监测浒苔能够达到快速准确的效果.本文使用RADARSAT-1、ENVISAT-ASAR、ALOS-PALSAR三种星载雷达传感器的数据,首先进行了影像预处理,并且针对浒苔的影像特征提出了一种基于灰度值的影像分析方法,该方法能够快速的对监测浒苔灾害的星...     

合成孔径雷达在湿地资源研究中的应用

合成孔径雷达(SAR)因为其独特的优势,成为遥感研究的热点问题。湿地作为复杂水陆交汇系统,传统的遥感手段不能全面获取湿地信息。将SAR引入到湿地遥感研究中具有重要意义。论文系统、全面介绍了这一方面研究的最新成果,主要包括SAR在湿地制图、湿地水位及湿地生物量估算方面的应用。     

Application of Remote Sensing in Detection of Ocean Oil Pollution

It is well known that the increase of surface tension due to the presence of oil slicks causes the surface wave motion is depressed or even disappeared, thus making the surface electromagnetically smoother. Therefore, the radar backscattered energy is correspondingly decreased. These damping effects is now well understood and such effects enables the oil slicks to be discernible from the radar image. in this paper, we are concerned with the digital technique that effectively delineates the oil slicks pattern from the SAR image. the detected pattern allows us to estimate the coverage of oil spillage. the technique is based on the fact that the oil slicks make a gray value surface in the image which is a concave area with a certain size. in order to identify correctly these oil slicks and suppress the speckle noise and other natural phenomena, an image pyramid with multi-resolution layers is generated sequentially from the original image. Then a top-down approach, which applies both first and second order derivative operators, the Difference of Gaussian (DoG) and the Laplace of Gaussian (LoG), to the image pyramid, is used to detect oil patches. Two ERS-1 SAR images acquired on August 5, 1994 and September 5, 1994, around Taiwan, were used for testing. Results indicate that the proposed method depresses the speckle noise and other sea noise signals, and enhances the oil slicks pattern clearly. the robustness to the empirical parameters introduced in this scheme was also demonstrated.     

Synthesis and pharmacological properties of certain analogs of pilocarpine

The synthesis of 4‐(4'‐pyrimidinylmethyl)oxacyclohexan‐2‐one (2a) and 4‐(4'‐pyrimidinylmethyl)oxacycloheptan‐2‐one (3a) were achieved through the Michael addition of the anion derived from 4‐methylpyrimidine with oxacyclyo‐3‐hexen‐2‐one and oxacyclo‐3‐hepten‐2‐one respectively. These compounds 2a and 3a and their quaternary methiodide salts lack cholinomimetic activity.     

酸雨对鼎湖山土壤的累积效应及荷木的反应

运用盆栽实验研究了酸雨对鼎湖山季风常绿阔叶林土壤危害的累积效应和优势树种荷木的一些生理反应.结果表明,在酸雨直接淋洗土壤的条件下,与对照相比,土壤酸度,土壤淋洗液酸度增加;土壤交换性K⁺、Na⁺上升,Ca²⁺、Mg²⁺和有效Mn、Zn下降;土壤淋洗液中K、Na含量下降,Ca、Mg、Cu、Fe、Mn和Al在pH3.05的酸雨处理下含量显著上升;但生长于模拟酸雨土壤中的荷木在土壤化学性质发生变化后仍能健康生长.     

基于DEM的SAR图像洪水水体的提取

星载雷达遥感已广泛应用于洪水灾害的监测和评估中。但是由于其阴影与水体严重混淆 ,使得从雷达图像中提取洪水水体较为困难。为此 ,本文探讨了在地形数据的支持下 ,实现星载SAR图像洪水水体半自动提取的方法。主要包括以下几步 :首先 ,对雷达图像进行滤波处理 ,并将其与地形数据匹配 ,从雷达图像中提取出初步的洪水水体范围 ;其次 ,利用地形数据生成DEM ,并根据雷达图像的成像参数和DEM生成相应的模拟雷达图像 ;最后 ,利用模拟雷达图像上的阴影 ,剔除被误提为洪水水体的阴影 ,从而实现洪水水体的准确提取。研究表明 ,该方法能有效地、半自动地将星载雷达图像上的洪水水体提取出来 ;同时 ,该方法可以用于多种星载多模式的雷达图像的洪水水体的识别提取 ,尤其对含山区的大范围洪水水体的半自动提取 ,更为适用。     

地震灾区河谷滑坡检测的遥感分析——以北川县滑坡为例

震区滑坡易堵塞河道形成高危型堰塞湖,一旦坝堤溃决,将释放巨大能量,造成严重的地震次生水灾。本文利用多源遥感数据,旨在研究一种检测河道滑坡的快速有效的方法,迅速判断出滑坡位置,为救援减灾提供重要信息。首先,对于灾前CBERS-02B星CCD数据,通过归一化水体指数(NDWI)来提取灾前水体信息主要为河道;由于灾后震区天气状况恶劣,故采用Radarsat-1SAR数据。利用水体在SAR影像上的特性,经过多次试验后使用阈值法来提取河道范围。再对两幅影像提取结果中的河道区域进行交集运算,检测出河道范围内的变化部分。通过上述方法提取的河道信息较为模糊、零散,这些模糊、零散并非都由滑坡堵塞河道造成,而是受噪声影响,在此对河道交集影像做膨胀处理,达到突出滑坡信息的目的,进而得以提取河道真实堵塞范围。最后进行人机交互判读,提取滑坡区域。实验以四川省北川县滑坡灾害为例,证明了本文方法的高效性与可靠性。