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With the ability of multibeam echo sounders (MBES) to measure backscatter strength (BS) as a function of true angle of insonification across the seafloor, came a new recognition of the potential of backscatter measurements to remotely characterize the properties of the seafloor. Advances in transducer design, digital electronics, signal processing capabilities, navigation, and graphic display devices, have improved the resolution and particularly the dynamic range available to sonar and processing software manufacturers. Alongside these improvements the expectations of what the data can deliver has also grown. In this paper, we identify these user-expectations and explore how MBES backscatter is utilized by different communities involved in marine seabed research at present, and the aspirations that these communities have for the data in the future. The results presented here are based on a user survey conducted by the GeoHab (Marine Geological and Biological Habitat Mapping) association. This paper summarises the different processing procedures employed to extract useful information from MBES backscatter data and the various intentions for which the user community collect the data. We show how a range of backscatter output products are generated from the different processing procedures, and how these results are taken up by different scientific disciplines, and also identify common constraints in handling MBES BS data. Finally, we outline our expectations for the future of this unique and important data source for seafloor mapping and characterisation.  相似文献   
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Historical changes in the level of Lake Bosumtwi, Ghana, have been simulated using a catchment‐scale hydrological model in order to assess the importance of changes in climate and land use on lake water balance on a monthly basis for the period 1939–2004. Several commonly used models for computing evaporation in data‐sparse regions are compared, including the Penman, the energy budget, and the Priestley–Taylor methods. Based on a comparison with recorded lake level variations, the model with the energy‐budget evaporation model subcomponent is most effective at reproducing observed lake level variations using regional climate records. A sensitivity analysis using this model indicates that Lake Bosumtwi is highly sensitive to changes in precipitation, cloudiness and temperature. However, the model is also sensitive to changes in runoff related to vegetation, and this factor needs to be considered in simulating lake level variations. Both interannual and longer‐term changes in lake level over the last 65 years appear to have been caused primarily by changes in precipitation, though the model also suggests that the drop in lake level over the last few decades has been moderated by changes in cloudiness and temperature over that time. Based on its effectiveness at simulating the magnitude and rate of lake level response to changing climate over the historical record, this model offers a potential future opportunity to examine the palaeoclimatic factors causing past lake level fluctuations preserved in the geological record at Lake Bosumtwi. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   
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The existence of uncertainty in classified remotely sensed data necessitates the application of enhanced techniques for identifying and visualizing the various degrees of uncertainty. This paper, therefore, applies the multidimensional graphical data analysis technique of parallel coordinate plots (PCP) to visualize the uncertainty in Landsat Thematic Mapper (TM) data classified by the Maximum Likelihood Classifier (MLC) and Fuzzy C-Means (FCM). The Landsat TM data are from the Yellow River Delta, Shandong Province, China. Image classification with MLC and FCM provides the probability vector and fuzzy membership vector of each pixel. Based on these vectors, the Shannon's entropy (S.E.) of each pixel is calculated. PCPs are then produced for each classification output. The PCP axes denote the posterior probability vector and fuzzy membership vector and two additional axes represent S.E. and the associated degree of uncertainty. The PCPs highlight the distribution of probability values of different land cover types for each pixel, and also reflect the status of pixels with different degrees of uncertainty. Brushing functionality is then added to PCP visualization in order to highlight selected pixels of interest. This not only reduces the visualization uncertainty, but also provides invaluable information on the positional and spectral characteristics of targeted pixels.  相似文献   
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A growing need to manage marine biodiversity sustainably at local, regional and global scales cannot be met by applying existing biological data. Abiotic surrogates of biodiversity are thus increasingly valuable in filling the gaps in our knowledge of biodiversity patterns, especially identification of hotspots, habitats needed by endangered or commercially valuable species and systems or processes important to the sustained provision of ecosystem services. This review examines the use of abiotic variables as surrogates for patterns in benthic biodiversity with particular regard to how variables are tied to processes affecting species richness and how easily those variables can be measured at scales relevant to resource management decisions.  相似文献   
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In this study, the Langelier saturation index and the Ryznar stability index of the groundwater of the east of Ergene Basin were evaluated to assess the corrosivity or scale-forming tendencies. Corrosion is one of the most complicated and costly problems facing drinking water utilities. Corrosion can affect public health, public acceptance of a water supply, and the cost of providing safe drinking water. For this purpose, total of 17 representative groundwater samples were collected. Except for well nos. 1, 2, and 3 with corrosive characteristics, all the groundwater samples were stable or had a slight tendency for dissolving of scale. Results showed that the amount of precipitation and irrigation caused seasonal variation in corrosive characteristics. Increased ionic concentration of SO4 ?2 contributes to the corrosivity of groundwater.  相似文献   
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A comprehensive 32 kHz multibeam bathymetry and backscatter survey of Cook Strait, New Zealand (∼8500 km2), is used to generate a regional substrate classification map over a wide range of water depths, seafloor substrates and geological landforms using an automated mapping method based on the textural image analysis of backscatter data. Full processing of the backscatter is required in order to obtain an image with a strongly attenuated specular reflection. Image segmentation of the merged backscatter and bathymetry layers is constrained using shape, compactness, and texture measures. The number of classes and their spatial distribution are statistically identified by employing an unsupervised fuzzy-c-means (FCM) clustering algorithm to sediment samples, independent of the backscatter data. Classification is achieved from the overlay of the FCM result onto a segmented image and attributing segments with the FCM class. Four classes are identified and uncertainty in class attribution is quantified by a confusion index layer. Validation of the classification map is done by comparing the results with the sediment and structural maps. Backscatter (BS) strength angular profiles are used to show acoustic class separation. The method takes us one step further in combining multibeam data with physical seabed data in a complementary analysis to seek correlations between datasets using object-based image analysis and unsupervised classification. Texture within these identified classes is then examined for correlation with typical backscatter angular responses for mud, sand and gravel. The results show a first order correlation between each of the classes and both the sedimentary properties and the geomorphological map.  相似文献   
8.
In this study, we propose, describe, and demonstrate a new geovisualization tool to demonstrate the use of exploratory and interactive visualization techniques for a visual fuzzy classification of remotely sensed imagery. The proposed tool uses dynamically linked views, consisting of an image display, a parallel coordinate plot, a 3D feature space plot, and a classified map with an uncertainty map. It allows a geoscientist to interact with the parameters of a fuzzy classification algorithm by visually adjusting fuzzy membership functions and fuzzy transition zones of land-cover classes. The purpose of this tool is to improve insight into fuzzy classification of remotely sensed imagery and related uncertainty. We tested our tool with a visual fuzzy land-cover classification of a Landsat 7 ETM+ image of an area in southern France characterized by objects with indeterminate boundaries. Good results were obtained with the visual classifier. Additionally, a focus-group user test of the tool showed that insight into a fuzzy classification algorithm and classification uncertainty improved considerably.  相似文献   
9.
Multibeam bathymetric data provide critical information for the modeling of seabed geology and benthic biodiversity. The accuracy of these models depends on the accuracy of the bathymetric data, which contain uncertainties that are stochastic at individual soundings but exhibit a distinct spatial distribution with increasing magnitude from nadir to the outer beams. A restricted spatial randomness method that simulates both the stochastic and spatial characteristics of the data uncertainty performed better than a complete spatial randomness method in analyzing the impact of bathymetric data uncertainty on derived seafloor attributes.  相似文献   
10.
This study was the first to use high-resolution IKONOS imagery to classify vegetation communities on sub-Antarctic Heard Island. We focused on the use of texture measures, in addition to standard multispectral information, to improve the classification of sub-Antarctic vegetation communities. Heard Island’s pristine and rapidly changing environment makes it a relevant and exciting location to study the regional effects of climate change. This study uses IKONOS imagery to provide automated, up-to-date, and non-invasive means to map vegetation as an important indicator for environmental change. Three classification techniques were compared: multispectral classification, texture based classification, and a combination of both. Texture features were calculated using the Grey Level Co-occurrence Matrix (GLCM). We investigated the effect of the texture window size on classification accuracy. The combined approach produced a higher accuracy than using multispectral bands alone. It was also found that the selection of GLCM texture features is critical. The highest accuracy (85%) was produced using all original spectral bands and three uncorrelated texture features. Incorporating texture improved classification accuracy by 6%.  相似文献   
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