The Experts below are selected from a list of 9567 Experts worldwide ranked by ideXlab platform
Bernhard Riegl - One of the best experts on this subject based on the ideXlab platform.
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detection of shallow subtidal corals from IKONOS satellite and qtc view 50 200 khz single beam sonar data arabian gulf dubai uae
Remote Sensing of Environment, 2005Co-Authors: Bernhard Riegl, Samuel J PurkisAbstract:We compared the results of seafloor classifications with special emphasis on detecting coral versus non-coral areas that were obtained from a 4×4-m pixel-resolution multispectral IKONOS satellite image and two acoustic surveys using a QTC View Series 5 system on 50 and 200 kHz signal frequency. A detailed radiative transfer model was obtained by in situ measurement of optical parameters that then allowed calibration of the IKONOS image against in situ optical measurements and a series of ground-truthing points. Eight benthic classes were distinguished optically with an overall accuracy of 69% and a Tau index T of 65. The classification of the IKONOS image allowed discrimination of three different coral assemblages (dense live, dense dead, sparse), which were confirmed by ground-truthing. Data evaluation of the acoustic surveys involved culling of datapoints with 90% accuracy and >30% probability) were used, and 60% accurate (T=53) when less processed data (selcted classes only, all data) were used. Accuracy against ground-truthing points of the most highly processed dataset was 56% (T=46). These results indicate that results from optical and acoustic surveys have some degree of commonality. Therefore, there is a potential to produce maps outlining coral areas from optical remote-sensing in shallow areas and acoustic methods in adjacent deeper areas beyond optical resolution with the limitation that acoustic maps will resolve fewer habitat classes and have lower accuracy.
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spatial and temporal dynamics of arabian gulf coral assemblages quantified from remote sensing and in situ monitoring data
Marine Ecology Progress Series, 2005Co-Authors: Samuel J Purkis, Bernhard RieglAbstract:We analysed spatial patterns of coral communities mapped from IKONOS satellite imagery in combination with 8 yr of traditional ecological monitoring data and archived sea-surface temperature data to explain why coral assemblages in the SE Arabian Gulf (Jebel Ali, Dubai) are impoverished and most do not build reefal frameworks. Analysis of archive sea-surface temperature (SST) data confirmed that the area is subject to recurrent and cyclic temperature anomalies at a frequency which suggests at least a partial link to the El Nino Southern Oscillation via the Indian Ocean Zonal Mode. Classification of high-resolution (4 m pixel-size) IKONOS satellite data gave a large-scale synoptic overview of substrate zonation which, in tandem with a long-term ecological time-series study, allowed us to determine the spatial and temporal dynamics of the coral community. We show that the spatial expression of 4 coral assemblages, as mapped using the IKONOS imagery, is consistent with what would be predicted if reef development was repeatedly 'reset' on a decadal time-scale following recurring episodes of coral mass mortality induced by severe SST anomalies. Furthermore, merging the remotely sensed map of substrate distribution with a detailed bathymetric digital elevation model, revealed no evidence of any significant framework development in the past, suggesting that the cycle of temperature-induced mortality has been operating for some considerable time.
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multi site evaluation of IKONOS data for classification of tropical coral reef environments
Remote Sensing of Environment, 2003Co-Authors: Serge Andrefouet, Philip Kramer, Damaris Torrespulliza, Karen E Joyce, Eric J Hochberg, Rodrigo Garzaperez, Peter J Mumby, Bernhard Riegl, Hiroya Yamano, William H WhiteAbstract:Ten IKONOS images of different coral reef sites distributed around the world were processed to assess the potential of 4-m resolution multispectral data for coral reef habitat mapping. Complexity of reef environments, established by field observation, ranged from 3 to 15 classes of benthic habitats containing various combinations of sediments, carbonate pavement, seagrass, algae, and corals in different geomorphologic zones (forereef, lagoon, patch reef, reef flats). Processing included corrections for sea surface roughness and bathymetry, unsupervised or supervised classification, and accuracy assessment based on ground-truth data. IKONOS classification results were compared with classified Landsat 7 imagery for simple to moderate complexity of reef habitats (5–11 classes). For both sensors, overall accuracies of the classifications show a general linear trend of decreasing accuracy with increasing habitat complexity. The IKONOS sensor performed better, with a 15–20% improvement in accuracy compared to Landsat. For IKONOS, overall accuracy was 77% for 4–5 classes, 71% for 7–8 classes, 65% in 9–11 classes, and 53% for more than 13 classes. The Landsat classification accuracy was systematically lower, with an average of 56% for 5–10 classes. Within this general trend, inter-site comparisons and specificities demonstrate the benefits of different approaches. Pre-segmentation of the different geomorphologic zones and depth correction provided different advantages in different environments. Our results help guide scientists and managers in applying IKONOS-class data for coral reef mapping applications.
Pete Reinartz - One of the best experts on this subject based on the ideXlab platform.
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mutual information based registration of terrasar x and IKONOS imagery in urban areas
IEEE Transactions on Geoscience and Remote Sensing, 2010Co-Authors: Sahil Suri, Pete ReinartzAbstract:The launch of high-resolution remote sensing satellites like TerraSAR-X, WorldView, and IKONOS has benefited the combined application of synthetic aperture radar (SAR) and optical imageries tremendously. Specifically, in case of natural calamities or disasters, decision makers can now easily use an old archived optical with a newly acquired (postdisaster) SAR image. Although the latest satellites provide the end user already georeferenced and orthorectified data products, still, registration differences exist between different data sets. These differences need to be taken care of through quick automated registration techniques before using the images in different applications. Specifically, mutual information (MI) has been utilized for the intricate SAR-optical registration problem. The computation of this metric involves estimating the joint histogram directly from image intensity values, which might have been generated from different sensor geometries and/or modalities (e.g., SAR and optical). Satellites carrying high-resolution remote sensing sensors like TerraSAR-X and IKONOS generate enormous data volume along with fine Earth observation details that might lead to failure of MI to detect correct registration parameters. In this paper, a solely histogram-based method to achieve automatic registration within TerraSAR-X and IKONOS images acquired specifically over urban areas is analyzed. Taking future sensors into a perspective, techniques like compression and segmentation for handling the enormous data volume and incompatible radiometry generated due to different SAR-optical image acquisition characteristics have been rightfully analyzed. The findings indicate that the proposed method is successful in estimating large global shifts followed by a fine refinement of registration parameters for high-resolution images acquired over dense urban areas.
Jue Wang - One of the best experts on this subject based on the ideXlab platform.
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evaluation and improvement of geopositioning accuracy of IKONOS stereo imagery
Journal of Surveying Engineering-asce, 2005Co-Authors: Jue WangAbstract:IKONOS imagery has been used in many commercial, government, and research applications ranging from environment monitoring, to coastal change detection, and to national security. The high costs of IKONOS high end products (Pro and Precision products) make it extremely attractive to find practical methods that use lower-cost IKONOS Geo products to produce highly accurate mapping products. This paper presents four different models defined in both object space and image space to refine the rational function derived ground coordinates. The models are the translation, scale and translation, affine, and second-order polynomial models. Different configurations of ground control points (GCPs) are carefully examined to evaluate the impact on accuracy improvement. The models are tested based on two IKONOS stereo pairs acquired in the Lake Erie coastal area. It is demonstrated that if an appropriate model and GCPs are used, ground point errors can be reduced from 5-6 to 1.5 m in horizontal and from 7 to 2 m in vertical directions.
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automatic shoreline extraction from high resolution IKONOS satellite imagery
2003Co-Authors: Kaichang Di, Jue Wang, Ron LiAbstract:ABSTRACT Shoreline mapping and shoreline change detection are critical for safe navigation, coastal resource management, coastal environmental protection, and sustainable coastal development and planning. This paper reports the results of IKONOS geopositioning accuracy improvement, showing that a 1-2 meter accuracy can be achieved from 1m-resolution IKONOS Geo stereo images. The experiment indicated that a simple adjustment model, e.g., either the Affine or the Scale &Offset model, is effective both to eliminate the systematic errors found in the vendor-provided Rational Function (RF) coefficients and to significantly improve the accuracy of 3D geopositioning. Aiming to automate shoreline mapping, we investigated a novel approach for automatic extraction of shorelines from high-resolution IKONOS imagery. In the first step of the proposed approach, the image is segmented into homogeneous regions by mean shift segmentation. Then, the major water body is identified and an initial shoreline is generated. The final shoreline is obtained by local refinement within the boundaries of the candidate regions adjacent to the initial shoreline. We test the approach using 4m- and 1m-resolution IKONOS images in a pilot project area along the Lake Erie shore. Test results show that the proposed approach is capable of extracting shorelines from IKONOS images with little human interaction. A method for 3D-shoreline generation is also discussed. The accuracies of the extracted shorelines from 4m XS and 1m Pan stereo images are estimated to be 8.5m and 2-3m respectively.
Samuel J Purkis - One of the best experts on this subject based on the ideXlab platform.
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detection of shallow subtidal corals from IKONOS satellite and qtc view 50 200 khz single beam sonar data arabian gulf dubai uae
Remote Sensing of Environment, 2005Co-Authors: Bernhard Riegl, Samuel J PurkisAbstract:We compared the results of seafloor classifications with special emphasis on detecting coral versus non-coral areas that were obtained from a 4×4-m pixel-resolution multispectral IKONOS satellite image and two acoustic surveys using a QTC View Series 5 system on 50 and 200 kHz signal frequency. A detailed radiative transfer model was obtained by in situ measurement of optical parameters that then allowed calibration of the IKONOS image against in situ optical measurements and a series of ground-truthing points. Eight benthic classes were distinguished optically with an overall accuracy of 69% and a Tau index T of 65. The classification of the IKONOS image allowed discrimination of three different coral assemblages (dense live, dense dead, sparse), which were confirmed by ground-truthing. Data evaluation of the acoustic surveys involved culling of datapoints with 90% accuracy and >30% probability) were used, and 60% accurate (T=53) when less processed data (selcted classes only, all data) were used. Accuracy against ground-truthing points of the most highly processed dataset was 56% (T=46). These results indicate that results from optical and acoustic surveys have some degree of commonality. Therefore, there is a potential to produce maps outlining coral areas from optical remote-sensing in shallow areas and acoustic methods in adjacent deeper areas beyond optical resolution with the limitation that acoustic maps will resolve fewer habitat classes and have lower accuracy.
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spatial and temporal dynamics of arabian gulf coral assemblages quantified from remote sensing and in situ monitoring data
Marine Ecology Progress Series, 2005Co-Authors: Samuel J Purkis, Bernhard RieglAbstract:We analysed spatial patterns of coral communities mapped from IKONOS satellite imagery in combination with 8 yr of traditional ecological monitoring data and archived sea-surface temperature data to explain why coral assemblages in the SE Arabian Gulf (Jebel Ali, Dubai) are impoverished and most do not build reefal frameworks. Analysis of archive sea-surface temperature (SST) data confirmed that the area is subject to recurrent and cyclic temperature anomalies at a frequency which suggests at least a partial link to the El Nino Southern Oscillation via the Indian Ocean Zonal Mode. Classification of high-resolution (4 m pixel-size) IKONOS satellite data gave a large-scale synoptic overview of substrate zonation which, in tandem with a long-term ecological time-series study, allowed us to determine the spatial and temporal dynamics of the coral community. We show that the spatial expression of 4 coral assemblages, as mapped using the IKONOS imagery, is consistent with what would be predicted if reef development was repeatedly 'reset' on a decadal time-scale following recurring episodes of coral mass mortality induced by severe SST anomalies. Furthermore, merging the remotely sensed map of substrate distribution with a detailed bathymetric digital elevation model, revealed no evidence of any significant framework development in the past, suggesting that the cycle of temperature-induced mortality has been operating for some considerable time.
Serge Andrefouet - One of the best experts on this subject based on the ideXlab platform.
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multi site evaluation of IKONOS data for classification of tropical coral reef environments
Remote Sensing of Environment, 2003Co-Authors: Serge Andrefouet, Philip Kramer, Damaris Torrespulliza, Karen E Joyce, Eric J Hochberg, Rodrigo Garzaperez, Peter J Mumby, Bernhard Riegl, Hiroya Yamano, William H WhiteAbstract:Ten IKONOS images of different coral reef sites distributed around the world were processed to assess the potential of 4-m resolution multispectral data for coral reef habitat mapping. Complexity of reef environments, established by field observation, ranged from 3 to 15 classes of benthic habitats containing various combinations of sediments, carbonate pavement, seagrass, algae, and corals in different geomorphologic zones (forereef, lagoon, patch reef, reef flats). Processing included corrections for sea surface roughness and bathymetry, unsupervised or supervised classification, and accuracy assessment based on ground-truth data. IKONOS classification results were compared with classified Landsat 7 imagery for simple to moderate complexity of reef habitats (5–11 classes). For both sensors, overall accuracies of the classifications show a general linear trend of decreasing accuracy with increasing habitat complexity. The IKONOS sensor performed better, with a 15–20% improvement in accuracy compared to Landsat. For IKONOS, overall accuracy was 77% for 4–5 classes, 71% for 7–8 classes, 65% in 9–11 classes, and 53% for more than 13 classes. The Landsat classification accuracy was systematically lower, with an average of 56% for 5–10 classes. Within this general trend, inter-site comparisons and specificities demonstrate the benefits of different approaches. Pre-segmentation of the different geomorphologic zones and depth correction provided different advantages in different environments. Our results help guide scientists and managers in applying IKONOS-class data for coral reef mapping applications.
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sea surface correction of high spatial resolution IKONOS images to improve bottom mapping in near shore environments
IEEE Transactions on Geoscience and Remote Sensing, 2003Co-Authors: Eric J Hochberg, Serge Andrefouet, M R TylerAbstract:A significant number of high spatial resolution (4 m) IKONOS images acquired over shallow coastal environments present quasi-stochastic sea surface effects that seriously compromise reconnaissance of bottom features. This problem is common in wide field-of-view images where there is limited control on acquisition conditions other than cloud cover. To eliminate most of these wave and glint patterns, we use the near-infrared band, which exhibits maximum absorption and minimal water leaving radiance over clear waters, to characterize the spatial distribution of relative glint intensity, which is then scaled by absolute glint intensities in each of the visible bands. The result is subtracted from the visible bands, thus filtering out glint effects. Corrected visible bands clearly reveal seabed structural features obscured in the original data. Before- and after-correction classifications of an IKONOS image of Lee Stocking Island (Bahamas) reveal an improvement of user's accuracies for critical benthic habitat classes such as coral-dominated habitat (46.8% versus 60.5%) or dense seagrass beds (31.7% versus 52.1%). This technique offers potential to use previously discarded sections of high spatial resolution airborne or satellite images of optically shallow water for mapping substrate features.
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a comparison of landsat etm spot hrv IKONOS aster and airborne master data for coral reef habitat mapping in south pacific islands
Canadian Journal of Remote Sensing, 2003Co-Authors: Patrick Capolsini, Serge Andrefouet, Cedric Rion, Claude PayriAbstract:The performances of the Landsat-7 ETM+, ASTER, SPOT HRV, and IKONOS satellite sensors and the airborne MASTER (MODIS‐ASTER simulator) were compared for coral reef habitat mapping in South Pacific reefs. This unique image data set provided different spatial resolution (4 m for IKONOS to 30 m for Landsat-7 ETM+), spectral resolution (two visible bands for SPOT-HRV to five visible bands for MASTER) and digitization (8‐16 bits). We focused on two islands (Tahiti and Moorea, French Polynesia) with barrier and fringing structures representative of reefs of South Pacific volcanic islands. Five levels of benthic habitat complexity were defined (with three, four, five, seven, and nine classes). Using a supervised maximum likelihood algorithm, the comparisons suggested several trends in sensor performances. Overall accuracies of Landsat-7 ETM+ compared well with sensors with higher spatial (IKONOS) or spectral (MASTER) resolution for low or moderate habitat complexity mapping. For high-complexity mapping (nine clas...
