Sar And Modis Data Oil Spill Monitoring Methods

Oil spill detection has important significance for the oceanic environmental protection. With the rapid development of the satellite remote sensing, remote sensing technique has become one of the important and effective tools in oil spill detection. This dissertation discussed the methods of the sea surface oil spill detection using Synthetic Aperture Radar (SAR) and MODIS data sets. The main researches focus on the oil spill phenomena recognition in the SAR images, oil film thickness estimation with MODIS data, oil spill detection system based on satellite data and GIS and oil spill distribution in the China Sea. The main results and conclusions of this dissertation are summarized as follows:1. The procedures are introduced to distinguish oil spill from the look-like phenomena in the SAR images, which include image preprocessing (radiation correction and speckle noise filtering), image segmentation, feature extraction, feature filtering and oil spill recognition based on Artificial Neural Network (ANN).After analyzing 10 different noise filtering methods, we chose the enhanced Lee filter with the window of size 3×3 pixels to reduce speckle noise. Oil spill region is segmented effectively by combining the Level Set and multi-level wavelet method, and the new segmented method improves the computation efficiency and decreases the computation complexity.To distinguish oil spills from the look-like phenomena, texture features of SAR images were extracted, in addition to the grey features, to be used as the inputs of ANN. The analysis of variance (ANOVA) was used to evaluate the importance of the features in distinguishing oil spills from the look-likes phenomena. The selected 16 features were used as the input of ANN. We found that 83% of the total test data were classified correctly, and it seems that the second-order statistic features based on co-occurrence matrix and features filtering with ANOVA improve the result of oil spills identification compared with the other methods.2. The fuzzy C-means (FCM) cluster algorithm with a texture feature analysis was developed to detect oil spill using.MODIS images in 250m resolution. Use of entropy based on the GLCM improved the efficacity of classification significantly, and the oil spills in the coastal region of Dalian port was clearly identified. The movement of oil spill estimated from two consecutive MODIS images was consistent with the ocean current estimated from the prevailing wind field and tidal data. Then we proposed a simple radiative transfer model of surface oil spill and analyzed the corresponding optical property in the visible band. The contrast between surface oil and background water depends on the absorption of upwelling radiance within the oil film. The upwelling radiance contrast owns a greatest value near the sea water reflectance peak and decreases as the oil film thickness increase. For the radiance received at the top of atmosphere (TOA) by the satellite sensor, the contrast between oil film and surrounding water depends on the balance between specular reflectance and the sub-surface upwelling radiance. The contrast of TOA radiance is positive when the contrast of specular reflectance is higher. Based on the above result and the MODIS data, the film thickness distribution of two oil spill accidents was analyzed qualitatively.3. An oil spill detection system is constructed by integrating Apache web server, Oracle database management system, Mapserver, PHP and satellite remote sensing data into the Web Geographic Information System(WebGIS). The system included the environmental information collecting model, oil spill information extracting model and oil spill drift forecasting model. Based on collecting SAR images from 2002 to 2005 and the WebGIS as a reference system, the oil spill distribution map for the East China Sea is presented. Four heavily polluted areas in the region have been delineated; they include the central part of the East China Sea, the eastern area of Bohai Strait, the marine area in the vicinity of the mouth of the Yangtze River and surrounding waters, and the southern part of the East China Sea including Taiwan Strait. A main source of oil pollution in the China Seas is the illegal discharges from passing ships, which are roughly distributed along main regional/international ship routes. Other sources include fish & oil waste caused by fishing operations and surface active materials with river runoff produced by onshore industrial enterprises.4. Combining the above WebGIS framework and FCM method, a system is constructed to help farmers to create management zones for variable rate applications of fertilizer. Based on the system, the further research is to examine how to use routine satellites data, such as Landsat,to create management zones. By comparing results with the management zones created with yield maps or soil survey, we will determine the optimal satellite images both temporally and spectrally that can be used to delineate appropriate management zones. NIR data from Landsat of the vegetation canopy flourishing season present the promising potential to replace yield data as the input of model to create the zone map of nitrogen fertilizer application.