1,720,985 research outputs found
Detection of Tree Crowns Based on Reclassification Using Aerial Images and Lidar Data
No full textTree detection using aerial sensors in early decades was focused by many researchers in different fields including Remote Sensing and Photogrammetry. This paper is intended to detect trees in complex city areas using aerial imagery and laser scanning data. Our methodology is a hierarchal unsupervised method consists of some primitive operations. This method could be divided into three sections, in which, first section uses aerial imagery and both second and third sections use laser scanners data. In the first section a vegetation cover mask is created in both sunny and shadowed areas. In the second section Rate of Slope Change (RSC) is used to eliminate grasses. In the third section a Digital Terrain Model (DTM) is obtained from LiDAR data. By using DTM and Digital Surface Model (DSM) we would get to Normalized Digital Surface Model (nDSM). Then objects which are lower than a specific height are eliminated. Now there are three result layers from three sections. At the end multiplication operation is used to get final result layer. This layer will be smoothed by morphological operations. The result layer is sent to WG III/4 to evaluate. The evaluation result shows that our method has a good rank in comparing to other participants’ methods in ISPRS WG III/4, when assessed in terms of 5 indices including area base completeness, area base correctness, object base completeness, object base correctness and boundary RMS. With regarding of being unsupervised and automatic, this method is improvable and could be integrate with other methods to get best results
Automatic Model Selection for 3D Reconstruction of Buildings from Satellite Imagary
No full textThrough the improvements of satellite sensor and matching technology, the derivation of 3D models from space borne stereo data obtained a lot of interest for various applications such as mobile navigation, urban planning, telecommunication, and tourism. The automatic reconstruction of 3D building models from space borne point cloud data is still an active research topic. The challenging
problem in this field is the relatively low quality of the Digital Surface Model (DSM) generated by stereo matching of satellite data comparing to airborne LiDAR data. In order to establish an efficient method to achieve high quality models and complete automation from the mentioned DSM, in this paper a new method based on a model-driven strategy is proposed. For improving the results, refined orthorectified panchromatic images are introduced into the process as additional data. The idea of this method is based on ridge line extraction and analysing height values in direction of and perpendicular to the ridgeline direction. After applying
pre-processing to the orthorectified data, some feature descriptors are extracted from the DSM, to improve the automatic ridge line detection. Applying RANSAC a line is fitted to each group of ridge points. Finally these ridge lines are refined by matching them or closing gaps. In order to select the type of roof model the heights of point in extension of the ridge line and height differences perpendicular to the ridge line are analysed. After roof model selection, building edge information is extracted from canny edge detection and parameters derived from the roof parts. Then the best model is fitted to extracted façade roofs based on detected type
of model. Each roof is modelled independently and final 3D buildings are reconstructed by merging the roof models with the corresponding walls
Fusion of ALS Point Cloud and Optical Imagery for 3D Reconstruction of Building's Roof
No full textThree-dimensional building models are important in various applications such as disaster management and urban planning. In this paper a method based on fusion of LiDAR point cloud and aerial image data sources has been proposed. Firstly using 2D map, the point set relevant to each building separated from the overall LiDAR point cloud. In the next step, the mean shift clustering algorithm applied to the points of different buildings in the feature space. Finally the segmentation stage ended with the separation of parallel and coplanar segments. Then using the adjacency matrix, adjacent segments are intersected and inner vertices are determined. In the other space, the area of any building cropped in the image space and the mean shift algorithm applied to it. Then, the lines of roof’s outline edge extracted by the Hough transform algorithm and the points obtained from the intersection of these lines transformed to the ground space. Finally, by integration of structural points of intersected adjacent facets and the transformed points from image space, reconstruction performed. In order to evaluate the efficiency of proposed method, buildings with different shapes and different level of complexity selected and the results of the 3D model reconstruction evaluated. The results showed credible efficiency of method for different buildings
Exploring the Potentials of UAV Based Geo-Spatial Data Acquisition in Urban Environment:A Case study in Dhaka City, Bangladesh
No full textThe usage of Unmanned Arial Vehicle (UAV) is undoubtedly very potential as well as very rapidly growing geospatial data acquisition method with disruptive role in the domain. The main focus of this research is to utilize an indigenous Quad-Copter to acquire spatial data in complex urban environment with a view toillustrating the potential using UAV data in urban planning and management activities including utility services. The study was conducted in a dense area of Dhaka city, the capital of Bangladesh. The process started with using an indigenous quad-copter; in this case, Mission-planner has been utilized to prepare a flight path for the UAV. After conducting the flight, extensive image processing has been operated, through synchronization of images, registration of the images, bundle block adjustment. For image processing and further extraction of data, Pix4DMapper and Correlator3D have been utilized. Moving forward, the processed images are used to prepare DTM, DSM, Orthographic images, and 3D point clouds. The process provided the data that are essential for several urban planning operations; such as Land Use planning, extracting urban volumetric data, extraction of vegetation structure, and common uses of DTM and DSM. The unique features of the UAV data for Dhaka is highly accurate, as Dhaka is mostly built us unplanned city, the urban fabric is very complex to extract data from medium or semi-high resolution optical satellite images. The UAV data used in this case study has provided 5cm resolution for orthophoto, planimetric accuracy of 2 cm and height accuracy of 5 cm. This studyseems to be very effective with special regards to time and cost saving with a significant improvement in data quality. This effort also helps us to overcome the limitations of cloud cover, spatial and temporal resolution of optical satellite images.<br/
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Exploring the Potentials of UAV Based Geo-Spatial Data Acquisition in Urban Environment:A Case study in Dhaka City, Bangladesh
No full textThe usage of Unmanned Arial Vehicle (UAV) is undoubtedly very potential as well as very rapidly growing geospatial data acquisition method with disruptive role in the domain. The main focus of this research is to utilize an indigenous Quad-Copter to acquire spatial data in complex urban environment with a view toillustrating the potential using UAV data in urban planning and management activities including utility services. The study was conducted in a dense area of Dhaka city, the capital of Bangladesh. The process started with using an indigenous quad-copter; in this case, Mission-planner has been utilized to prepare a flight path for the UAV. After conducting the flight, extensive image processing has been operated, through synchronization of images, registration of the images, bundle block adjustment. For image processing and further extraction of data, Pix4DMapper and Correlator3D have been utilized. Moving forward, the processed images are used to prepare DTM, DSM, Orthographic images, and 3D point clouds. The process provided the data that are essential for several urban planning operations; such as Land Use planning, extracting urban volumetric data, extraction of vegetation structure, and common uses of DTM and DSM. The unique features of the UAV data for Dhaka is highly accurate, as Dhaka is mostly built us unplanned city, the urban fabric is very complex to extract data from medium or semi-high resolution optical satellite images. The UAV data used in this case study has provided 5cm resolution for orthophoto, planimetric accuracy of 2 cm and height accuracy of 5 cm. This studyseems to be very effective with special regards to time and cost saving with a significant improvement in data quality. This effort also helps us to overcome the limitations of cloud cover, spatial and temporal resolution of optical satellite images.<br/
Exploring the Potentials of UAV Based Geo-Spatial Data Acquisition in Urban Environment:A Case study in Dhaka City, Bangladesh
No full textThe usage of Unmanned Arial Vehicle (UAV) is undoubtedly very potential as well as very rapidly growing geospatial data acquisition method with disruptive role in the domain. The main focus of this research is to utilize an indigenous Quad-Copter to acquire spatial data in complex urban environment with a view toillustrating the potential using UAV data in urban planning and management activities including utility services. The study was conducted in a dense area of Dhaka city, the capital of Bangladesh. The process started with using an indigenous quad-copter; in this case, Mission-planner has been utilized to prepare a flight path for the UAV. After conducting the flight, extensive image processing has been operated, through synchronization of images, registration of the images, bundle block adjustment. For image processing and further extraction of data, Pix4DMapper and Correlator3D have been utilized. Moving forward, the processed images are used to prepare DTM, DSM, Orthographic images, and 3D point clouds. The process provided the data that are essential for several urban planning operations; such as Land Use planning, extracting urban volumetric data, extraction of vegetation structure, and common uses of DTM and DSM. The unique features of the UAV data for Dhaka is highly accurate, as Dhaka is mostly built us unplanned city, the urban fabric is very complex to extract data from medium or semi-high resolution optical satellite images. The UAV data used in this case study has provided 5cm resolution for orthophoto, planimetric accuracy of 2 cm and height accuracy of 5 cm. This studyseems to be very effective with special regards to time and cost saving with a significant improvement in data quality. This effort also helps us to overcome the limitations of cloud cover, spatial and temporal resolution of optical satellite images.<br/
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
- …
