Oil Spill Detection Using Otical Sensors: A Multi-Temporal Approach

Oil pollution is one of the most destructive consequences due to human activities in the marine environment. Oil wastes come from many sources and take decades to be disposed of. Satellite based remote sensing systems can be implemented into a surveillance and monitoring network. In this study, a multi-temporal approach to the oil spill detection problem is investigated. Change Detection (CD) analysis was applied to MODIS/Terra and Aqua and OLI/Landsat 8 images of several reported oil spill events, characterized by different geographic location, sea conditions, source and extension of the spill. Toward the development of an automatic detection algorithm, a Change Vector Analysis (CVA) technique was implemented to carry out the comparison between the current image of the area of interest and a dataset of reference image, statistically analyzed to reduce the sea spectral variability between different dates. The proposed approach highlights the optical sensors’ capabilities in detecting oil spills at sea. The effectiveness of different sensors’ resolution towards the detection of spills of different size, and the relevance of the sensors’ revisiting time to track and monitor the evolution of the event is also investigated.

Fusion of Satellite Images in Transform Domain

Unique—Image fusion in light of the wavelet and fourier trans-form comes about rich multispectral points of interest yet gives less spatial subtle elements from source images. Wavelet transform performs well at straight highlights yet not at non-direct discontinuities since Wavelets don't utilize the geometric properties of structures. Curvelet transforms defeat such troubles in include rep-resentation. A novel Image fusion rule by means of high pass balance utilizing Local Magnitude Ratio (LMR) in Fast Discrete Curvelet Transforms domain (FDCT) and Discrete wavelet transform (DWT) is characterized. Indian Remote Sensing Geo satellite images are utilized for MS and Pan images. This fusion rule creates HR multispectral image with high spatial resolution. This technique is contrasted and wavelet, Principal Component Analysis (PCA), Fast Discrete Curvelet Transforms domain fusion strategies. Master postured technique spatially performs alternate strategies and results rich multispectral information.

RECOGNITION OF CHARACTER FROM VIDEO SUBTITLES

An important task in content based video indexing is to extract text information from videos. The challenges involved in text extraction and recognition are variation of illumination on each video frame with text, the text present on the complex background and different font size of the text. Using various image processing algorithms like morphological operations, blob detection and histogram of oriented gradients the character recognition of video subtitles is implemented. Segmentation, feature extraction and classification are the major steps of character recognition. Several experimental results are shown to demonstrate the performance of the proposed algorithm.

Influence of DEM resolution on topographic correction models using spot satellite image

Topographic correction models (TCMs) are valid on satellite image data preprocessing steps. The illumination angle may be sensitive to different terrain slope and aspect conditions base on sun-terrain-sensor geometry. Although the topographic correction is influenced by the sun azimuth and zenith angle, the correction result can be equally in the same image status. By contrast, the terrain factors change with different digital elevation model (DEM) resolution in the topographic correction equations and cause a significant effect. Slope is sensitive in rugged terrain, and aspect is impressionable at flat surface at a coarse DEM resolution data. As the DEM resolution lead a distinct result on TCMs, this research is aimed to examine the impact of DEM resolution on the accuracy of terrain representation and of the gradient determined. In this study, five TCMs, including cosine correction, C correction, SCS correction, SCS+C correction and Minnaert correction models are compared by different resolutions using SPOT image data. The 5 meter DEM obtained from Ministry of the interior will be resampled to 10 to 500 meters to test those topographic models sustainability on Lienhuachih Research Center. The accuracy of five topographic correction models base on different DEM resolution will be evaluated by root-mean-square error (RMSE).

Co-occurrence of extreme ozone and heat waves in two cities from Morocco

Temperature is the first meteorological factor to be directly involved in leading ozone (O3) extreme events. Generally, upward temperatures increase the probability of having exceedance in ozone adopted thresholds. In the global climate change context more frequent and/or persistent heat waves and extreme ozone (O3) episodes are likely to occur during in coming decades and a key question is about the coincidence and co-occurrence of these extremes. In this paper, using 7 years of surface temperature and air quality observations over two cities from Morocco (Casablanca and Marrakech) and implementing a percentile thresholding approach, we show that the extremes in temperature and ozone (O3) cluster together in many cases and that the outbreak of ozone events generally match the first or second days of heat waves. This co-occurrence of extreme episodes is highly impacted by humidity and may be overlapping large-scale episodes.

Applying high-resolution visible imagery to satellite melt pond fraction retrieval: A neural network approach

During summer, melt ponds have a significant influence on Arctic sea-ice albedo. The melt pond fraction (MPF) also has the ability to forecast the Arctic sea-ice in a certain period. It is important to retrieve accurate melt pond fraction (MPF) from satellite data for Arctic research. This paper proposes a satellite MPF retrieval model based on the multi-layer neural network, named MPF-NN. Our model uses multi-spectral satellite data as model input and MPF information from multi-site and multi-period visible imagery as prior knowledge for modeling. It can effectively model melt ponds evolution of different regions and periods over the Arctic. Evaluation results show that the MPF retrieved from MODIS data using the proposed model has an RMSE of 3.91% and a correlation coefficient of 0.73. The seasonal distribution of MPF is also consistent with previous results.

Reflection-coefficient experimental extraction from S21- parameter for radar oil-spill detection application

Oil spill in sea water is one of the main accidents that affect significantly the maritime environment over a long period of time. Knowing the severe influence of oil spills on the ecosystem, it is crucial to have oil spill detecting and monitoring systems for quick intervention and danger containment. In our project, we propose the usage of drones as an oil spill detection system. The drones will be implementing different previously developed multi-frequency approaches for the detection. The effectiveness of such techniques is based on the accuracy of the data collected and their match to the theory. This journal presents a method for the remote extraction of reflection coefficients from multilayer structure modeling an oil spill in sea water. The experimental results for the reflectivity extraction validate the theoretical calculations and allow the implementation of different algorithms based on the statistical information taken directly from the site.

Test and evaluation of a simple parameterization to enhance air-sea coupling in a global coupled model

A simple temperature-dependent wind stress scheme is implemented in National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM), aiming to enhance positive wind stress and sea surface temperature (SST) correlation in SST-frontal regions. A series of three-year coupled experiments are conducted to determine a proper coupling coefficient for the scheme based on the agreement of surface wind stress and SST at oceanic mesoscale between model simulations and observations. Afterwards, 80-year simulations with/without the scheme are conducted to explore its effects on simulated ocean states and variability. The results show that the new scheme indeed improves the positive correlation between SST and wind stress magnitude near the large oceanic fronts. With more realistic surface heat flux and wind stress, the global SST biases are reduced. The global ocean circulation represented by barotropic stream function exhibits a weakened gyre circulation close to the western boundary separation, in agreement with previous studies. The simulation of equatorial Pacific current system is improved as well. The overestimated El Niño Southern Oscillation (ENSO) magnitude in original CESM is reduced by ~30% after using the new scheme with an improved period.

A study of temperature profiles and trends as revealed by COSMIC RO technique and balloon –borne radiosonde instrument

This research presents atmospheric temperature profiles and trends retrieved using COSMIC RO technique and balloon-borne radiosonde instrument in 2007 and a few cases during 2017. By effectively using ‘wet’ temperature product available at COSMIC Data Analysis and Archive Center (CDAAC) website, an analysis has been made to present temperature profiles and trends at various regions including, Indian, Taiwan and Japan. A one-to-one correspondence is, clearly, seen between temperature profiles retrieved with COSMIC RO and radiosonde instrument. But, few and dominant differences in temperature profiles are found below at an altitude of ~5 km and above around tropopause (~16-17 km). The dominant differences found at below ~5km could be due to the inhomogeneous distribution of humidity present, generally, at the tropical regions, whereas above the tropopause altitudes, differences might be due to the ionospheric residual correction as reported by other researchers. Further, temperature monthly trends at various regions show distinct characteristics including, a sharp temperature inversion up to tropopause altitude. In addition, it is also observed maximum temperatures (peaks) during the northern summer seasons (May, June, July, and August) and minimum temperatures (troughs) during the northern winter seasons (November, December, January, and February) near to the surface of the Earth. Interestingly, although it is generally observed that the tropopause altitude is located at ~ 16-17 km at various regions, a keen observation reveals that distinct seasonal and latitudinal variations can be witnessed. With this case study, it may be concluded that the COSMIC RO technique is able to provide very accurate measurement, which reiterates its importance as a powerful tool to explore the Earth’s atmosphere on the local and global scale.

Satellite-based study of physico-optical properties of aerosols over a westernmost location of Brahmaputra valley

This study examines the long term trend of the radiatively active atmospheric aerosols which can influence the Earth’s energy budget directly by scattering and absorbing radiation and indirectly by acting as cloud condensation nuclei. MODIS sensor on board the NASA Earth Observing System Terra and Aqua satellite based Aerosol Optical Depth (AOD) data are used for long term analysis of aerosols over Bongaigaon, Assam for the period August, 2002 to March, 2017. Highest AOD values are observed in pre-monsoon (March-May) season due to long range transportation as well as intense biomass burning activities especially as a part of Jhum cultivation. In general, AOD values are low in post-monsoon (October-November) season which may be due to wash out of aerosols by rain in the preceding months without enough replacement. The monthly AOD values vary from its highest value 0.949 in April, 2016 to its lowest value 0.107 in November, 2002 for the study period. From the comparison of MODIS Terra and Aqua AOD at 550 nm, it is clearly seen that generally Terra AOD at 10:30 hr is higher than the Aqua AOD at 13:30hr. A slowly increasing trend of both Aqua and Terra AOD at 550 nm is observed over the study location. The observed Ångström exponent value varies from its minimum value in monsoon season to its maximum value in winter season. With increasing AOD values, horizontal visibility decreases over Bongaigaon.