Semi-automatic Extraction Research Articles

Definition frames as language-dependent models of knowledge transfer

Definitions are an important means of structuring knowledge in a domain. We explore definitions in the domain of karstology from a cross-language perspective with the aim of comparing the cognitive frames underlying defining strategies in Croatian and English. The experiment involved the semi-automatic extraction of definition candidates from our corpora, manual selection of valid examples, identification of functional units and semantic annotation with conceptual categories and relations. Our results comply with related frame-based approaches in that they clearly demonstrate the multidimensionality of concepts and the key factors affecting the choice of defining strategy, e. g. concept category, its place in the conceptual system of the domain and the communicative setting. Our approach extends related work by applying the framebased view on a new language pair and a new domain, and by performing a more detailed semantic analysis. The most interesting finding, however, regards the cross-language comparison; it seems that definition frames are language- and/or culture-specific in that certain conceptual structures may exist in one language but not the other. These results imply that a cross-linguistic analysis of conceptual structures is an essential step in the construction of knowledge bases, ontologies and other domain representations.

Extraction of Geological Structural Lineaments in Northern Kuwait Using High Resolution Landsat 8 ETM+ Satellite Images and Edge Enhancement Techniques

Earth consists of hard rock layers where water is restricted to secondary permeability, and thus to fractures and the weather zones. Satellite images, aerial photographs and digital elevation models will give lineament information. Recent advances in digital image processing allow such lineament extraction to be accomplished in semi-automatic to fully automatic approaches. Precise delineation and mapping of geological structural lineaments is very much needed in Northern Kuwait in view of their close spatial association with subsurface tectonic fractures in oil fields at deep levels and groundwater fields (aquifers) at shallow depths. As such, high spatial resolution remote sensing multispectral image data (Landsat 8 ETM+ satellite) will be used delineate and map the lineaments. Lineaments are linear features which provide information about the underlying geological structure. Their analysis are widely considered in the location or sitting of suitable groundwater exploration sites since the water will tend to flow along the fracture zones. The major objective was to extract the lineaments in Northern Kuwait, with a view of using the analysis for groundwater exploration in the future to mitigate the requirement of groundwater in the area. The analysis was carried out using Band 5, 6 and 7 of Landsat 8 (OLI), which was processed using the edge enhancement filters available to extract the lineaments in the study area. These were then verified using manually digitized lineaments from a geological map partly covering the region and false color composites of the study area. The results showed that the semi-automatic extraction of lineaments can yield tangible results using optical imagery. However, the lineaments still require verification through comparison with known lineaments. Filters which are Sobel, Laplacian and Directional filtering of Band 5, 6 and 7 of Landsat 8 proved to be useful in visual identification and verification of lineaments.

EtG/EtS in Serum by UHPLC-MS-MS in Suspected Sexual Assault Cases.

A method including semi-automated extraction of ethyl glucuronide (EtG) and ethyl sulfate (EtS) from serum followed by ultra-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS-MS) has been developed and validated. Sample preparation prior to UHPLC-MS-MS analysis consisted of protein precipitation and filtration through a phospholipid removal plate. Chromatography was achieved using an HSS T3 column and gradient elution with formic acid in water in combination with methanol. The mass spectrometer was monitored in the negative mode with multiple reaction monitoring. Two transitions were monitored for the analytes and one for the deuterated internal standards (ISs). The limits of quantification were 0.025 mg/L for EtG and 0.009 mg/L for EtS. The between-assay relative standard deviations were in the range of 3.8-9.1%, the recovery was 66-102% and matrix effects ranged from 88 to 97% (corrected with IS). Compared to previously published studies, the method presented is semi-automated, uses a simple method for phospholipid removal and has short run times and low limit of quantifications. We analyzed serum samples from 49 female patients presenting to the Sexual Assault Centre at St. Olav University Hospital in Trondheim, Norway, for ethanol, EtG and EtS. EtG and EtS were detected longer than ethanol itself after intake of ethanol, with estimated maximum detection times of >24 h. The ethanol, EtG and EtS concentrations were highly correlated (P < 0.001), but with large inter-individual variations. This study suggests that analysis of EtG and EtS in serum or blood may complement ethanol analysis and shed light on the patient's recent ethanol intake after ethanol itself is no longer detectable.

Analysis of Urban Green Spaces Based on Sentinel-2A: Case Studies from Slovakia

Urban expansion and its ecological footprint increases globally at an unprecedented scale and consequently, the importance of urban greenery assessment grows. The diversity and quality of urban green spaces (UGS) and human well-being are tightly linked, and UGS provide a wide range of ecosystem services (e.g., urban heat mitigation, stormwater infiltration, food security, physical recreation). Analyses and inter-city comparison of UGS patterns and their functions requires not only detailed information on their relative quantity but also a closer examination of UGS in terms of quality and land use, which can be derived from the land cover composition and spatial structure. In this study, we present an approach to UGS extraction from newly available Sentinel-2A satellite imagery, provided in the frame of the European Copernicus program. We investigate and map the spatial distribution of UGS in three cities in Slovakia: Bratislava, Žilina and Trnava. Supervised maximum likelihood classification was used to identify UGS polygons. Based on their function and physiognomy, each UGS polygon was assigned to one of the fifteen classes, and each class was further described by the proportion of tree canopy and its ecosystem services. Our results document that the substantial part of UGS is covered by the class Urban greenery in family housing areas (mainly including privately-owned gardens) with the class abundance between 17.7% and 42.2% of the total UGS area. The presented case studies showed the possibilities of semi-automatic extraction of UGS classes from Sentinel-2A data that may improve the transfer of scientific knowledge to local urban environmental monitoring and management.

Terrestrial laser scanner for the analysis of airport pavement geometry

The knowledge of the geometric features of an airport’s pavement surface is essential to ensuring the safety and comfort of the driving users. For this purpose, it is important to find the most suitable survey methods and computation procedures for determining these geometric features and their evolution over time. In this study, we used a terrestrial laser scanner (TLS) to survey a stretch of a taxiway of an international airport. We designed the survey with the goal of defining the optimal parameters for the scans and the spacing between the TLS station points, combining high efficiency with data quality and accuracy. An algorithm for the semi-automatic extraction of the longitudinal and transversal profiles of the track from the digital elevation model (DEM) has been implemented. Longitudinal and cross slopes have been computed from the profiles using a linear fit, assessing the conformity of the values to the standards. The algorithm allows the verification of irregularities and the assessment of the severity of deviations from a linear trend. Our approach is suitable for obtaining an accurate reconstruction of the road surface that can be measured in post-processing and that is geo-referenced in a way that allows monitoring over time. We believe that the surveying technique that we analysed and assessed could improves the effectiveness of the measurements, and it could be used wherever pavement geometry control cannot be performed on discrete elements but rather a continuous approach is needed.

Semi-automated extraction of longitudinal subglacial bedforms from digital terrain models – Two new methods

Relict drumlin and mega-scale glacial lineation (positive relief, longitudinal subglacial bedforms – LSBs) morphometry has been used as a proxy for paleo ice-sheet dynamics. LSB morphometric inventories have relied on manual mapping, which is slow and subjective and thus potentially difficult to reproduce. Automated methods are faster and reproducible, but previous methods for LSB semi-automated mapping have not been highly successful. Here, two new object-based methods for the semi-automated extraction of LSBs (footprints) from digital terrain models are compared in a test area in the Puget Lowland, Washington, USA. As segmentation procedures to create LSB-candidate objects, the normalized closed contour method relies on the contouring of a normalized local relief model addressing LSBs on slopes, and the landform elements mask method relies on the classification of landform elements derived from the digital terrain model. For identifying which LSB-candidate objects correspond to LSBs, both methods use the same LSB operational definition: a ruleset encapsulating expert knowledge, published morphometric data, and the morphometric range of LSBs in the study area. The normalized closed contour method was separately applied to four different local relief models, two computed in moving windows and two hydrology-based. Overall, the normalized closed contour method outperformed the landform elements mask method. The normalized closed contour method performed on a hydrological relief model from a multiple direction flow routing algorithm performed best. For an assessment of its transferability, the normalized closed contour method was evaluated on a second area, the Chautauqua drumlin field, Pennsylvania and New York, USA where it performed better than in the Puget Lowland. A broad comparison to previous methods suggests that the normalized relief closed contour method may be the most capable method to date, but more development is required.

Método semiautomático para extração e regularização de talhões de cana-de-açúcar utilizando imagens Landsat-5, classificador paralelepípedo e algoritmo de Douglas-Peuker

This paper proposes a semi-automatic method for the extraction and regularization of sugarcane crops from Landsat-5 image. The method uses a enhancement function for increase contrast between objects in the image, the quadtree structure used for subdividing the image into homogeneous regions, parallelepiped classifier used for extract pixels that belongs to the desired pattern, edge detection from binary image with segmented regions, polygonization and regularization of contours by Douglas-Peuker algorithm. Experiments carried out with test area show that the proposed method is appropriate for applications involving semi-automatic sugarcane areas extraction, as it provided contour information with approximately 94.95% of pixel correctly classified, 1.64% of false positive and 3.4% of false negatives. Keywords: sugarcane, remote sensing, contours regularization.

Stratified Template Matching to Support Refugee Camp Analysis in OBIA Workflows

Accurate and reliable information about the situation in refugee or internally displaced person camps is very important for planning any kind of help like health care, infrastructure, or vaccination campaigns. The number and spatial distribution of single dwellings extracted semi-automatically from very high-resolution (VHR) satellite imagery as an indicator for population estimations can provide such important information. The accuracy of the extracted dwellings can vary quite a lot depending on various factors. To enhance established single dwelling extraction approaches, we have tested the integration of stratified template matching methods in object-based image analysis (OBIA) workflows. A template library for various dwelling types (template samples are taken from ten different sites using 16 satellite images), incorporating the shadow effect of dwellings, was established. Altogether, 18 template classes were created covering typically occurring dwellings and their cast shadows. The created template library aims to be generally applicable in similar conditions. Compared to pre-existing OBIA classifications, the approach could increase the producer’s accuracy by 11.7 percentage points on average and slightly increase the user’s accuracy. These results show that the stratified integration of template matching approaches in OBIA workflows is a possibility to further improve the results of semi-automated dwelling extraction, especially in complex situations.

Semi automatic road extraction from digital images

Road extraction from digital images is of fundamental importance in the context of automatic mapping, effective urban planning and updating GIS databases. Very high spatial resolution (VHR) imagery acquired by airborne and space borne sensors is the main source for accurate road extraction. Manual techniques are fading away as they are time consuming and costly. Hence, road extraction method that is significantly more automated has become a research hotspot in remote sensing information processing. This paper proposes a semi-automatic approach to extract different road types from high-resolution remote sensing images. The approach is based on edge detection and SVM and mathematical morphology method. First the outline of the road is detected based on Canny operator. Then, Full Lambda Schedule merging method combines adjacent segments. Then the entire image was classified using Support Vector Machine (SVM) and various spatial, spectral, and texture attributes to form a road image. Finally, the quality of detected roads is improved using morphological operators. The algorithm was systematically evaluated on a variety of satellite images from Worldview, QuickBird and UltraCam airborne Images. The results of the accuracy evaluation demonstrate that the proposed road extraction approach can provide high accuracy for extraction of different road types.

Extraction and Classification of Road Markings Using Mobile Laser Scanning Point Clouds

This study aims at building a robust method for semiautomated information extraction of pavement markings detected from mobile laser scanning (MLS) point clouds. The proposed workflow consists of three components: 1) preprocessing, 2) extraction, and 3) classification. In preprocessing, the three-dimensional (3-D) MLS point clouds are converted into radiometrically corrected and enhanced two-dimensional (2-D) intensity imagery of the road surface. Then, the pavement markings are automatically extracted with the intensity using a set of algorithms, including Otsu's thresholding, neighbor-counting filtering, and region growing. Finally, the extracted pavement markings are classified with the geometric parameters by using a manually defined decision tree. A study was conducted by using the MLS dataset acquired in Xiamen, Fujian, China. The results demonstrated that the proposed workflow and method can achieve 92% in completeness, 95% in correctness, and 94% in F -score.

WATERSHED SPATIAL DISCRETIZATION FOR THE ANALYSIS OF LAND USE CHANGE IN COASTAL REGIONS

In this study, we present a methodology to discretize a non-assessed basin based on terrain analysis using the SRTM digital elevation model (DEM) and a high resolution surface model (DSM) with a drainage network semi-automatic extraction process. The Juqueriquerê River Basin was used for the case study, which has the most representative non-urbanized plains of the northern coastline of São Paulo State, Brazil. The low-lying region is featured by elevations close to the sea level, mild slopes, and shallow water tables. It is also influenced by tidal variation and orographic rains. Therefore, frequent flooding occurs, even in vegetated areas. Two conflicting land use scenarios, proposed by the City Master Plan (CMP) of Caraguatatuba and the Ecological-Economical Zoning (EEZ), were compared to analyze the flood vulnerability increase and geotechnical risk caused by the urbanization process. The drainage extraction techniques showed better results on high resolution DSM for low-lying regions than the SRTM DEM and determined with accuracy the locations of flood potentiality in the plains. The watershed spatial discretization allowed us to show the effects of the two different land use approaches, considering the flood vulnerability and geotechnical risk of each sub-basin

Gut Microbiota Analysis Results Are Highly Dependent on the 16S rRNA Gene Target Region, Whereas the Impact of DNA Extraction Is Minor.

Next-generation sequencing (NGS) is currently the method of choice for analyzing gut microbiota composition. As gut microbiota composition is a potential future target for clinical diagnostics, it is of utmost importance to enhance and optimize the NGS analysis procedures. Here, we have analyzed the impact of DNA extraction and selected 16S rDNA primers on the gut microbiota NGS results. Bacterial DNA from frozen stool specimens was extracted with 5 commercially available DNA extraction kits. Special attention was paid to the semiautomated DNA extraction methods that could expedite the analysis procedure, thus being especially suitable for clinical settings. The microbial composition was analyzed with 2 distinct protocols: 1 targeting the V3-V4 and the other targeting the V4-V5 area of the bacterial 16S rRNA gene. The overall effect of DNA extraction on the gut microbiota 16S rDNA profile was relatively small, whereas the 16S rRNA gene target region had an immense impact on the results. Furthermore, semiautomated DNA extraction methods clearly appeared suitable for NGS procedures, proposing that application of these methods could importantly reduce hands-on time and human errors without compromising the validity of results.

3D SPECT/CT fusion using image data projection of bone SPECT onto 3D volume-rendered CT images: feasibility and clinical impact in the diagnosis of bone metastasis

PurposeWe developed a method of image data projection of bone SPECT into 3D volume-rendered CT images for 3D SPECT/CT fusion. The aims of our study were to evaluate its feasibility and clinical usefulness.MethodsWhole-body bone scintigraphy (WB) and SPECT/CT scans were performed in 318 cancer patients using a dedicated SPECT/CT systems. Volume data of bone SPECT and CT were fused to obtain 2D SPECT/CT images. To generate our 3D SPECT/CT images, colored voxel data of bone SPECT were projected onto the corresponding location of the volume-rendered CT data after a semi-automatic bone extraction. Then, the resultant 3D images were blended with conventional volume-rendered CT images, allowing to grasp the three-dimensional relationship between bone metabolism and anatomy. WB and SPECT (WB + SPECT), 2D SPECT/CT fusion, and 3D SPECT/CT fusion were evaluated by two independent reviewers in the diagnosis of bone metastasis. The inter-observer variability and diagnostic accuracy in these three image sets were investigated using a four-point diagnostic scale.ResultsIncreased bone metabolism was found in 744 metastatic sites and 1002 benign changes. On a per-lesion basis, inter-observer agreements in the diagnosis of bone metastasis were 0.72 for WB + SPECT, 0.90 for 2D SPECT/CT, and 0.89 for 3D SPECT/CT. Receiver operating characteristic analyses for the diagnostic accuracy of bone metastasis showed that WB + SPECT, 2D SPECT/CT, and 3D SPECT/CT had an area under the curve of 0.800, 0.983, and 0.983 for reader 1, 0.865, 0.992, and 0.993 for reader 2, respectively (WB + SPECT vs. 2D or 3D SPECT/CT, p < 0.001; 2D vs. 3D SPECT/CT, n.s.). The durations of interpretation of WB + SPECT, 2D SPECT/CT, and 3D SPECT/CT images were 241 ± 75, 225 ± 73, and 182 ± 71 s for reader 1 and 207 ± 72, 190 ± 73, and 179 ± 73 s for reader 2, respectively. As a result, it took shorter time to read 3D SPECT/CT images than 2D SPECT/CT (p < 0.0001) or WB + SPECT images (p < 0.0001).Conclusions3D SPECT/CT fusion offers comparable diagnostic accuracy to 2D SPECT/CT fusion. The visual effect of 3D SPECT/CT fusion facilitates reduction of reading time compared to 2D SPECT/CT fusion.

Semi-automated extraction and characterization of Stromal Vascular Fraction using a new medical device.

The stem cell rich Stromal Vascular Fraction (SVF) can be harvested by processing lipo-aspirate or fat tissue with an enzymatic digestion followed by centrifugation. To date neither a standardised extraction method for SVF nor a generally admitted protocol for cell application in patients exists. A novel commercially available semi-automated device for the extraction of SVF promises sterility, consistent results and usability in the clinical routine. The aim of this work was to compare the quantity and quality of the SVF between the new system and an established manual laboratory method. SVF was extracted from lipo-aspirate both by a prototype of the semi-automated UNiStation™ (NeoGenesis, Seoul, Korea) and by hand preparation with common laboratory equipment. Cell composition of the SVF was characterized by multi-parametric flow-cytometry (FACSCanto-II, BD Biosciences). The total cell number (quantity) of the SVF was determined as well the percentage of cells expressing the stem cell marker CD34, the leucocyte marker CD45 and the marker CD271 for highly proliferative stem cells (quality). Lipo-aspirate obtained from six patients was processed with both the novel device (d) and the hand preparation (h) which always resulted in a macroscopically visible SVF. However, there was a tendency of a fewer cell yield per gram of used lipo-aspirate with the device (d: 1.1×105±1.1×105 vs. h: 2.0×105±1.7×105; p = 0.06). Noteworthy, the percentage of CD34+ cells was significantly lower when using the device (d: 57.3% ±23.8% vs. h: 74.1% ±13.4%; p = 0.02) and CD45+ leukocyte counts tend to be higher when compared to the hand preparation (d: 20.7% ±15.8% vs. h: 9.8% ±7.1%; p = 0.07). The percentage of highly proliferative CD271+ cells was similar for both methods (d:12.9% ±9.6% vs. h: 13.4% ±11.6%; p = 0.74) and no differences were found for double positive cells of CD34+/CD45+ (d: 5.9% ±1.7% vs. h: 1.7% ±1.1%; p = 0.13), CD34+/CD271+ (d: 24.1% ±12.0% vs. h: 14.2% ±8.5%; p = 0.07). The semi-automated closed system provides a considerable amount of sterile SVF with high reproducibility. Furthermore, the SVF extracted by both methods showed a similar cell composition which is in accordance with the data from literature. This semi-automated device offers an opportunity to take research and application of the SVF one step further to the clinic.

Peripheral inflammatory markers indicate microstructural damage within periventricular white matter hyperintensities in Alzheimer's disease: A preliminary report

IntroductionWhite matter hyperintensities (WMH) presumed to reflect cerebral small vessel disease and increased peripheral inflammatory markers are found commonly in Alzheimer's disease (AD), but their interrelationships remain unclear. MethodsInflammatory markers were assayed in 54 elderly participants (n = 16 with AD). Periventricular WMH were delineated from T1, T2/proton density, and fluid-attenuated magnetic resonance imaging using semiautomated fuzzy lesion extraction and coregistered with maps of fractional anisotropy (FA), a measure of microstructural integrity assessed using diffusion tensor imaging. ResultsMean FA within periventricular WMH was associated with an inflammatory factor consisting of interleukin (IL)-1β, tumor necrosis factor, IL-10, IL-21, and IL-23 in patients with AD (ρ = −0.703, P = .002) but not in healthy elderly (ρ = 0.217, P = .190). Inflammation was associated with greater FA in deep WMH in healthy elderly (ρ = 0.425, P = .008) but not in patients with AD (ρ = 0.174, P = .520). DiscussionPeripheral inflammatory markers may be differentially related to microstructural characteristics within the white matter affected by cerebral small vessel disease in elders with and without AD.

An Improved Method for Mapping Tidal Flats Based on Remote Sensing Waterlines: A Case Study in the Bohai Rim, China

Tidal flats form boundaries between marine and terrestrial environments, and reported rapid decreases in their extent require improved measures of their status. Current methods for delineating tidal flats have low accuracy because of the limited precision of available imagery, and they cannot identify zones within tidal flats. Three zones within tidal flats are ecologically distinct due to their varied inundation. These include the supratidal, intertidal, and subtidal zones. In this study, we present a more precise method for mapping tidal flats. We used Chinese HJ-1A/B satellite images with a semiautomatic extraction method to generate a sufficient number of waterline estimates taken at various tide heights to delineate the full extent of tidal flats. Then, the full set of waterline estimates is analyzed with the Digital Shoreline Analysis System (DSAS) using Jenks Natural Breaks to identify three zones within tidal flats. We demonstrated the utility of this approach by mapping tidal flats of the Bohai Rim, China. In 2014, the estimate of available tidal flats in the region was 3093 km2, among which the area of supratidal, intertidal, and subtidal zones accounted for 5.0%, 84.3%, and 10.7%, respectively. A confusion matrix for accuracy assessment revealed a 93.8% overall accuracy for the resulting tidal flat map. Our method enables tidal flats to be mapped and monitored precisely and comprehensively, providing baseline data on the extent of this disappearing ecosystem that can be used to inform coastal planning and sustainable development.

Semi-Automatic Extraction of Training Examples From Sensor Readings for Fall Detection and Posture Monitoring

While inexpensive wearable motion-sensing devices have shown great promise for fall detection and posture monitoring, two major problems still exist and have to be solved: 1) a framework for the development of firmware and 2) software to make intelligent decisions. We address both the problems. We propose a generic framework for developing the firmware. We also demonstrate that the k-means clustering algorithm can semi-automatically extract training examples from motion data. Moreover, we trained and evaluated several one- and two-level classification networks to monitor non-fall activities and to detect fall events. The proposed classification networks are the combinations of neural networks and softmax regression. These networks are trained offline with examples extracted by our proposed method. The cross-validation of trained two-level networks shows 100% accuracy for non-fall activities and fall events. The data sets for training and testing have been collected using the devices we assembled with four off-the-shelf components. We have programmed them using a prototype of our proposed framework. The data sets include seven types of non-fall activities and four types of fall events. This paper advances the state of the art for the development and training of wearable devices for monitoring non-fall activities and detecting fall events.

SHANGHAI SHORELINE EVOLUTION INTERPRETED FROM HISTORICAL ATLAS AND REMOTE SENSING IMAGERY OVER THE PAST 2,200 YEARS

Shanghai, the axis of economic development in China and holding the most prosperous metropolis in the world, is located at Yangtze Estuary which is susceptible to shoreline changes affected by different factors, such as sediment supply and sea level changes, making it very important to study the shoreline changes over long time period. This paper presents the Shanghai shoreline evolution process from BC 221 up to 2015, by employing both the cartographic data (historical atlas) and the remote sensing images. A series of image processing techniques were applied to seamlessly register the historical atlas and satellite images to the same orthophoto base map, followed by the semi-automatic extraction of shoreline from images. Results show that since BC 221, the Shanghai shoreline has been witnessing distinct progradation, and the rate of shoreline advance varied in different areas. The average shoreline change in southern Yangtze Estuary was about 2,573 km&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt; (accretion) between BC 221 and 1948 with a 40 km progradation, while the shoreline in northern Hangzhou Bay kept relatively steady after 1671. Overall, 3,119 km&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt; of Shanghai area was added between BC 221 and 1948 with an average rate of 75 km&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt;/50yr, and the addition went to 4,372 km&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt; in 2015. In this paper, the possible drives of the shoreline evolution was discussed. This study is important for understanding the coastal dynamics in Shanghai over a long time period for the management and development of coastal environments.

SHANGHAI SHORELINE EVOLUTION INTERPRETED FROM HISTORICAL ATLAS AND REMOTE SENSING IMAGERY OVER THE PAST 2,200 YEARS

Abstract. Shanghai, the axis of economic development in China and holding the most prosperous metropolis in the world, is located at Yangtze Estuary which is susceptible to shoreline changes affected by different factors, such as sediment supply and sea level changes, making it very important to study the shoreline changes over long time period. This paper presents the Shanghai shoreline evolution process from BC 221 up to 2015, by employing both the cartographic data (historical atlas) and the remote sensing images. A series of image processing techniques were applied to seamlessly register the historical atlas and satellite images to the same orthophoto base map, followed by the semi-automatic extraction of shoreline from images. Results show that since BC 221, the Shanghai shoreline has been witnessing distinct progradation, and the rate of shoreline advance varied in different areas. The average shoreline change in southern Yangtze Estuary was about 2,573 km2 (accretion) between BC 221 and 1948 with a 40 km progradation, while the shoreline in northern Hangzhou Bay kept relatively steady after 1671. Overall, 3,119 km2 of Shanghai area was added between BC 221 and 1948 with an average rate of 75 km2/50yr, and the addition went to 4,372 km2 in 2015. In this paper, the possible drives of the shoreline evolution was discussed. This study is important for understanding the coastal dynamics in Shanghai over a long time period for the management and development of coastal environments.

RAPID INSPECTION OF PAVEMENT MARKINGS USING MOBILE LIDAR POINT CLOUDS

Abstract. This study aims at building a robust semi-automated pavement marking extraction workflow based on the use of mobile LiDAR point clouds. The proposed workflow consists of three components: preprocessing, extraction, and classification. In preprocessing, the mobile LiDAR point clouds are converted into the radiometrically corrected intensity imagery of the road surface. Then the pavement markings are automatically extracted with the intensity using a set of algorithms, including Otsu’s thresholding, neighbor-counting filtering, and region growing. Finally, the extracted pavement markings are classified with the geometric parameters using a manually defined decision tree. Case studies are conducted using the mobile LiDAR dataset acquired in Xiamen (Fujian, China) with different road environments by the RIEGL VMX-450 system. The results demonstrated that the proposed workflow and our software tool can achieve 93% in completeness, 95% in correctness, and 94% in F-score when using Xiamen dataset.