bluuebunny/crossref_metadata_2025 huggingface dataset:
DATA PROCESSING AND RECORDING USING A VERSATILE MULTI-SENSOR VEHICLE
Authors: Borgmann B. , Schatz V. , Kieritz H. , Scherer-Klöckling C. , Hebel M. , Arens M.
Published: September 2018

Abstract. In this paper we present a versatile multi-sensor vehicle which is used in several research projects. The vehicle is equipped with various sensors in order to cover the needs of different research projects in the area of object detection and tracking, mobile mapping and change detection. We show an example for the capabilities of this vehicle by presenting camera- and LiDAR-based pedestrian detection methods. Besides this specific use case, we provide a more general in-depth description of the vehicle’s hard- and software design and its data-processing capabilities. The vehicle can be used as a sensor carrier for mobile mapping, but it also offers hardware and software components to allow for an adaptable onboard processing. This enables the development and testing of methods related to real-time applications or high-level driver assistance functions. The vehicle’s hardware and software layout result from several years of experience, and our lessons learned can help other researchers set up their own experimental platform.
EXTRACTION OF SOLAR CELLS FROM UAV-BASED THERMAL IMAGE SEQUENCES
Authors: Hoegner L. , Pfaffenzeller N. , Wagner L. , Stilla U.
Published: September 2018

Abstract. This paper discusses the automatic generation of thermal infrared ortho image mosaics and the extraction of solar cells from these ortho image mosaics. Image sequences are recorded by a thermal infrared (TIR) camera mounted on a remotely piloted aerial system (RPAS). The image block is relatively oriented doing a bundle block adjustment and transferred to a local coordinate system using ground control points. The resulting ortho image mosaic is searched for solar cells. A library of templates of solar cells from thermal images is used to learn an implicit shape model. The extraction of the single solar cells is done by estimating corners and centre points of cells using these shape models in a Markov-Chain-Monte-Carlo algorithm by combining four corners and a centre point. As for the limited geometric resolution and radiometric contrast, most of the cells are not directly detected. An iterative process based on the knowledge of the regular grid structure of a solar cell installation is used to predict further cells and verify their existence by repeating the corner extraction and grammar combination. Results show that this work flow is able to detect most of the solar cells under the condition that the cells have a more or less common radiometric behaviour and no reflections i.e. from the sun occur. The cells need a rectangular shape and have the same orientation so that the model of the grammar is applicable to the solar cells.
DISPARITY REFINEMENT OF BUILDING EDGES USING ROBUSTLY MATCHED STRAIGHT LINES FOR STEREO MATCHING
Authors: Huang X. , Qin R. , Chen M.
Published: September 2018

Abstract. Stereo dense matching has already been one of the dominant tools in 3D reconstruction of urban regions, due to its low cost and high flexibility in generating 3D points. However, the image-derived 3D points are often inaccurate around building edges, which limit its use in several vision tasks (e.g. building modelling). To generate 3D point clouds or digital surface models (DSM) with sharp boundaries, this paper integrates robustly matched lines for improving dense matching, and proposes a non-local disparity refinement of building edges through an iterative least squares plane adjustment approach. In our method, we first extract and match straight lines in images using epipolar constraints, then detect building edges from these straight lines by comparing matching results on both sides of straight lines, and finally we develop a non-local disparity refinement method through an iterative least squares plane adjustment constrained by matched straight lines to yield sharper and more accurate edges. Experiments conducted on both satellite and aerial data demonstrate that our proposed method is able to generate more accurate DSM with sharper object boundaries.
PILOT STUDY ON THE RETRIEVAL OF DBH AND DIAMETER DISTRIBUTION OF DECIDUOUS FOREST STANDS USING CAST SHADOWS IN UAV-BASED ORTHOMOSAICS
Authors: Kattenborn T. , Hernández J. , Lopatin J. , Kattenborn G. , Fassnacht F. E.
Published: September 2018

Abstract. One fundamental metric to characterize trees and forest stands is the diameter at breast height (DBH). However, the vertical geometry of tree stems hampers a direct measurement by means of orthographic aerial imagery. Nevertheless, the DBH in deciduous forest stands could be measured from UAV-based imagery using the width of a stem´s cast shadow projected on the ground. Here, we compare in-situ measured DBH of 100 trees with the DBH visually interpreted from cast-shadows derived in UAV-based aerial imagery. Then, based on simulated datasets, we determine suitable DBH sampling sizes for a robust and efficient retrieval of stand diameter distributions. The UAV-based DBH estimation resulted in an r2 of 0.74, RMSE of 7.61 cm, NRMSE of 12.8 % and approximately unbiased results. According to our simulations it can be assumed that a sample size of 25–50 individual DBH measurements per forest stand allows estimating reliable diameter distributions. The presented pilot study gives a first insight on the potential of such an approach for operational assessments of diameter distribution in deciduous forest stands and might be particularly interesting for stands in difficult terrain situations. The presented approach can be extended to estimate the basal area, timber stock or biomass.
UAV-LiCAM SYSTEM DEVELOPMENT: CALIBRATION AND GEO-REFERENCING
Authors: Cortes C. , Shahbazi M. , Ménard P.
Published: September 2018

Abstract. In the last decade, applications of unmanned aerial vehicles (UAVs), as remote-sensing platforms, have extensively been investigated for fine-scale mapping, modeling and monitoring of the environment. In few recent years, integration of 3D laser scanners and cameras onboard UAVs has also received considerable attention as these two sensors provide complementary spatial/spectral information of the environment. Since lidar performs range and bearing measurements in its body-frame, precise GNSS/INS data are required to directly geo-reference the lidar measurements in an object-fixed coordinate system. However, such data comes at the price of tactical-grade inertial navigation sensors enabled with dual-frequency RTK-GNSS receivers, which also necessitates having access to a base station and proper post-processing software. Therefore, such UAV systems equipped with lidar and camera (UAV-LiCam Systems) are too expensive to be accessible to a wide range of users. Hence, new solutions must be developed to eliminate the need for costly navigation sensors. In this paper, a two-fold solution is proposed based on an in-house developed, low-cost system: 1) a multi-sensor self-calibration approach for calibrating the Li-Cam system based on planar and cylindrical multi-directional features; 2) an integrated sensor orientation method for georeferencing based on unscented particle filtering which compensates for time-variant IMU errors and eliminates the need for GNSS measurements.
DEVELOP A GIS-BASED CONTEXT-AWARE SENSOR NETWORK DEPLOYMENT ALGORITHM TO OPTIMIZE SENSOR COVERAGE IN AN URBAN AREA
Authors: Argany M. , Mostafavi M.-A.
Published: September 2018

Abstract. Adequate coverage is an important issue in geosensor networks in order to fulfill the sensing applications in urban areas. GIS as well as Optimization methods are widely used to distribute geosensors in the network to achieve the desired level of coverage. Most of the algorithms applied in urban domain suffer from the lack of considering real environmental information. In this paper, the problem of placing sensors to get optimum coverage is studied by investigating the concept of urban contextual information in sensor network. Then, a local GIS-based context-aware framework of sensor network deployment optimization method is introduced. Obtained results of our algorithm under different working conditions and applications show the effectiveness of our approach.
AN AUTOMATIC PROCEDURE FOR MOBILE LASER SCANNING PLATFORM 6DOF TRAJECTORY ADJUSTMENT
Authors: Hussnain Z. , Oude Elberink S. , Vosselman G.
Published: September 2018

Abstract. In this paper, a method is presented to improve the MLS platform’s trajectory for GNSS denied areas. The method comprises two major steps. The first step is based on a 2D image registration technique described in our previous publication. Internally, this registration technique first performs aerial to aerial image matching, this issues correspondences which enable to compute the 3D tie points by multiview triangulation. Similarly, it registers the rasterized Mobile Laser Scanning Point Cloud (MLSPC) patches with the multiple related aerial image patches. The later registration provides the correspondence between the aerial to aerial tie points and the MLSPC’s 3D points. In the second step, which is described in this paper, a procedure utilizes three kinds of observations to improve the MLS platform’s trajectory. The first type of observation is the set of 3D tie points computed automatically in the previous step (and are already available), the second type of observation is based on IMU readings and the third type of observation is soft-constraint over related pose parameters. In this situation, the 3D tie points are considered accurate and precise observations, since they provide both locally and globally strict constraints, whereas the IMU observations and soft-constraints only provide locally precise constraints. For 6DOF trajectory representation, first, the pose [R, t] parameters are converted to 6 B-spline functions over time. Then for the trajectory adjustment, the coefficients of B-splines are updated from the established observations. We tested our method on an MLS data set acquired at a test area in Rotterdam, and verified the trajectory improvement by evaluation with independently and manually measured GCPs. After the adjustment, the trajectory has achieved the accuracy of RMSE X = 9 cm, Y = 14 cm and Z = 14 cm. Analysing the error in the updated trajectory suggests that our procedure is effective at adjusting the 6DOF trajectory and to regenerate a reliable MLSPC product.
MOSAICKING VERY-HIGH-RESOLUTION HELICOPTER-BORNE IMAGES ACQUIRED OVER DRIFTING ARCTIC SEA ICE USING COTS SENSORS
Authors: Hyun C. U. , Kim H. C.
Published: September 2018

Abstract. In order to observe and record conditions of the sea ice efficiently and specifically during in-situ investigation with the support of icebreaker research vessel (IBRV), the very-high-resolution (VHR) imaging systems have been used in recent past. The VHR images are generally acquired lower altitude than cloud height, therefore, the images can be acquired even in unfavourable weather conditions for optical satellite image acquisition, and can be applied to comparison with various kinds of remote sensing datasets. However, producing mosaicked image using the VHR images have suffered from drift of sea ice. The sea ice drift interrupts simultaneous geotagging in overall study area as geographic locations of sea ice moves continuously; therefore, the mosaicked image generated from improperly geotagged individual image depicts a scene of ambiguous time. In this study, we present a case study of VHR sea ice image acquisition using a helicopter equipped with commercial off-the-shelf (COTS) geotagging and imaging sensors with a support of IBRV Araon in East Siberian Sea, Arctic Ocean. We also propose an image mosaicking strategy using the improperly geotagged VHR images acquired over drifting sea ice to decrease temporal and spatial ambiguity.
SYSTEMATIC GEOMETRIC IMAGE ERRORS OF VERY HIGH RESOLUTION OPTICAL SATELLITES
Authors: Jacobsen K.
Published: September 2018

Abstract. Very high resolution optical satellites are imaging the object space by a combination of CCD-lines in one direction and by time, speed and satellite rotation in the other direction. The combination of the CCD-lines usually is known by pre-calibration. Remaining errors of the pre-calibration, also slightly depending upon the satellite movement and rotation, with few exceptions are usually small up to negligible. This may not be the case for the image component in the scan direction and the alignment of the line combinations - they are controlled by giros and stellar cameras. Stellar cameras are compensating giro drifts, but their recording frequency is limited as well as in general the accuracy of the satellite view direction. In addition the satellites may show a jitter caused by the fast rotation from one pointed area to another. Not all giros are able to record the jitter frequency. A limited accuracy of the view direction is causing systematic image errors in relation to the used mathematical model of geometric reconstruction. The systematic image errors can be determined theoretically by image orientation based on ground control points (GCPs), but usually not a satisfying number and distribution of GCPs is available. Another possibility is the analysis of the intersection of corresponding rays in a stereo model and an analysis of generated height models against reference height models. Here also free of charge available height models as the SRTM Digital Surface Model (DSM) or AW3D30 can be used. Several very high resolution satellite cameras have been analyzed; this includes images from WorldView-2, WorldView-4, Kompsat-3, Kompsat-1, Pleiades, Cartosat-1, ZY3, OrbView-3, QuickBird, IKONOS, ASTER, IRS-1C, SPOT, SPOT-5 HRS, EROS-B, IKONOS, QuickBird, OrbView and GeoEye but only results of the today more important satellites are shown in detail. For few satellites the systematic image errors can be ignored, but others require a correction which may be just a levelling of the DSM but also a higher degree of deformation up to a compensation of the satellite jitter effect. The used method cannot be named as calibration due to variation from image to image, only the character and size of deformation is typical for the used special optical satellite, but it depends also upon the operating conditions as fast satellite rotation. Due to the very high number of reference points in a DSM the determination of systematic image errors is independent upon random errors and also high frequent jitter can be determined with a standard deviation down to 0.1 ground sampling distance (GSD) or even better.
SMILE CORRECTION IN THE ENMAP GROUND SEGMENT PROCESSOR: A QUALITATIVE ANALYSIS
Authors: Langheinrich M. , Richter R. , de los Reyes R. , Palubinskas G. , Storch T.
Published: September 2018

Abstract. The Environmental Mapping and Analysis Program (EnMAP) is an upcoming German hyperspectral satellite mission aiming to observe and characterize the Earth’s environment on a global scale. In course of a the development of the EnMAP ground segment processing chain, measures were taken to deal with probable spectral and spatial distortion effects of the sensor, that can only be addressed by post-processing once the satellite platform is launched into orbit. One of these effects is a pixel- and band-wise spectral distortion, the so called sensor smile effect. This paper describes the methods and performance of the smile correction process as implemented for the EnMAP ground segment processing chain, explaining design choices and difficulties currently encountered with the proposed approach and evaluating the results of the smile correction on basis of simulated EnMAP hyperspectral data.
NETWORK ADJUSTMENT OF AUTOMATIC RELATIVE ORIENTATION FROM IMAGE SEQUENCES
Authors: Lin C. C. , Tseng Y. H. , Lin K. Y. , Chiang K. W.
Published: September 2018

Abstract. Recently, Visual Odometry (VO) using cameras for navigation is known as an alternative solution in GNSS-hostile environments. VO is a process of estimating the egomotion based on consecutive frames captured by the camera. 3D Motion including the attitude and position can be described as the exterior orientation parameters (EOPs) in photogrammetry. The advantage of VO compared with wheel odometry is that VO is not affected by wheel slip in uneven terrain or other adverse conditions. Since VO computes the camera path incrementally, the errors are accumulated as well according to the motion of each new frame-to-frame over time. That would cause the drift in the estimated trajectory compared to the real path. To solve this issue, this research proposes the network adjustment model based on relative orientation parameters (ROPs) for monocular VO. The fundamental idea originates from the traverse in the field of surveying. A traverse is a series of consecutive lines whose ends have been marked in the field and whose lengths and angles have been determined from observations. Consequently, ROPs are adopted as observations in the model that would update the states of image sequence furthermore. In this research, it is worth mentioning that the coordinates of object points are not necessary to be calculated, and more accurate ROPs are improved automatically during the process. In the future, VO with this proposed method could be integrated with GNSS/INS to a navigation system.
INVESTIGATING THE USE OF COASTAL BLUE IMAGERY FOR BATHYMETRIC MAPPING OF INLAND WATER BODIES
Authors: Mandlburger G. , Kremer J. , Steinbacher F. , Baran R.
Published: September 2018

Abstract. In this contribution, we report on an experimental airborne data acquisition with two medium format cameras (Coastal Blue, RGB) and a topo-bathymetric laser scanner for capturing the bathymetry of a dozen of groundwater supplied lakes located near Augsburg, Germany. The specific research question was to investigate whether the use of high-resolution Coastal Blue imagery (λ = 400–460 nm) provides added value for mapping bathymetry and characterization of water bottom features. While data processing is still in progress, preliminary results indicate that the blue (λ = 420–500 nm) and green (λ = 490–570 nm) color channels of the RGB camera are better suited for estimating bathymetry, but the Coastal Blue channel adds an additional water penetrating band increasing the number of useful band combinations with a positive effect on the water bottom classification capabilities. Whereas Coastal Blue channels are rather used from satellite platforms (Landsat 8, WorldView-2) with spatial resolutions in the meter range, our experiment aims at using higher resolution Coastal Blue imagery with a ground sampling distance of around 5 cm enabling not only spectrally based shallow water depth mapping but also the application of multi-media photogrammetry in high spatial resolution. To the best of our knowledge the use of high-resolution Coastal Blue captured from airborne platforms is novel in the context of mapping shallow water bathymetry.
IMPACT OF REDUCTION OF RADIOMETRIC RESOLUTION IN HYPERSPECTRAL IMAGES ACQUIRED OVER FOREST FIELD
Authors: Miyoshi G. T. , Imai N. N. , Tommaselli A. M. G. , Honkavaara E.
Published: September 2018

Abstract. The objective of this study was to evaluate the impact of reducing the radiometric information of hyperspectral images. The image data was collected originally with 32 bits and rescaled to 8 and 16 bit/pixel. The images were acquired with a Rikola Hyperspectral Camera attached to an Unmanned Aerial Vehicle (UAV). After the geometric and radiometric processing of the images, a mosaic was obtained with pixels representing reflectance factor coded in 32 bits. Using the minimum and maximum values of each spectral band, a linear equation was thus applied to reduce the radiometric resolution of the original mosaic, from 32 bits to 8 bits and from 32 bits to 16 bits. Following, the Normalized Root Mean Square Error (NRMSE %) and the Mean Absolute Percentage Error (MAPE %) were used to evaluate the results, showing that for the 8 bits mosaic, the loss of information was higher. For this radiometric resolution rescaling, the MAPE % achieved values until 22.486 % and the highest NRMSE % value was 0.455 % while, for the 16 bits mosaics, the highest MAPE % and NRMSE % values were 0.069 % and 0.002 %, respectively. Finally, it can be inferred that the impact of radiometric transformation can be considered as negligible for the hyperspectral mosaic with 16 bits of radiometric resolution, which presented lower values of NRMSE % and MAE % and could not affect the mosaic analysis.
FEATURE MATCHING ENHANCEMENT OF UAV IMAGES USING GEOMETRIC CONSTRAINTS
Authors: Mohammed H. M. , El-Sheimy N.
Published: September 2018

Abstract. Preliminary matching of image features is based on the distance between their descriptors. Matches are further filtered using RANSAC, or a similar method that fits the matches to a model; usually the fundamental matrix and rejects matches not belonging to that model. There are a few issues with this scheme. First, mismatches are no longer considered after RANSAC rejection. Second, RANSAC might fail to detect an accurate model if the number of outliers is significant. Third, a fundamental matrix model could be degenerate even if the matches are all inliers. To address these issues, a new method is proposed that relies on the prior knowledge of the images’ geometry, which can be obtained from the orientation sensors or a set of initial matches. Using a set of initial matches, a fundamental matrix and a global homography can be estimated. These two entities are then used with a detect-and-match strategy to gain more accurate matches. Features are detected in one image, then the locations of their correspondences in the other image are predicted using the epipolar constraints and the global homography. The feature correspondences are then corrected with template matching. Since global homography is only valid with a plane-to-plane mapping, discrepancy vectors are introduced to represent an alternative to local homographies. The method was tested on Unmanned Aerial Vehicle (UAV) images, where the images are usually taken successively, and differences in scale and orientation are not an issue. The method promises to find a well-distributed set of matches over the scene structure, especially with scenes of multiple depths. Furthermore; the number of outliers is reduced, encouraging to use a least square adjustment instead of RANSAC, to fit a non-degenerate model.
HYPERSPECTRAL PANORAMIC IMAGING
Authors: Müller-Rowold M. , Reulke R.
Published: September 2018

Abstract. Hyperspectral instruments are designed for the characterisation of planetary surfaces, oceans and the atmosphere. At the moment there are a number of aircraft systems and planned space missions. Examples for this are the hyperspectral missions for Earth remote sensing (EnMAP) and also for deep space and planetary missions (Mercury mission Bepi Colombo).There are basically two options for a hyperspectral system: Snapshot systems and scanning systems. This paper investigates a scanning hyperspectral push-broom systems. In most systems the input aperture is a long slit whose image is dispersed across a 2-D detector array, so that all points along a line in the scene are sampled simultaneously. To fill out the spatial dimension orthogonal to the slit, the scene is scanned across the entrance aperture. An ideal low cost hyperspectral scanning device analogue to push broom scanner is a 2D-detector with variable spectral filters, each filter being arranged perpendicular to the direction of flight.The biggest challenge is the mapping of the images of the individual spectral channels to each other (co-registration). The solution of the problem is the prerequisite for the use of this kind of hyperspectral cameras e.g. on board of an aircraft. Therefore, an investigation should focus on the procedure of data acquisition, correction and registration. In addition, an example showing the advantages of a possible application is explained.
MULTI-CAMERA SYSTEM CALIBRATION OF A LOW-COST REMOTELY OPERATED VEHICLE FOR UNDERWATER CAVE EXPLORATION
Authors: Nocerino E. , Nawaf M. M. , Saccone M. , Ellefi M. B. , Pasquet J. , Royer J.-P. , Drap P.
Published: September 2018

Abstract. Exploration, documentation and mapping of underwater environment is one of the biggest open challenges for science and engineering. Humankind is not naturally designed to operate in water and, despite the enormous technological advancement that offers nowadays unprecedented opportunities, diving and working underwater is still very dangerous, especially in confined spaces such as underwater caves. Great research efforts are currently devoted to underwater autonomous navigation, but available solutions still mainly rely on complex and expensive systems, due to the difficulty of adapting localization and mapping sensors and algorithms suited for terrestrial or aerial applications. However, small and affordable underwater remotely operated vehicles (ROVs) are available, which offer good opportunities for underwater exploration and mapping. This paper focuses on the development of a small, low-cost ROV designed for 3D mapping of underwater environments, like caves. The system is based on a commercially available vehicle, the BluRov2, and relies on the use of up to 12 action cameras (GoPro) mounted on it. A trifocal camera system for underwater real-time visual odometry can also be included. The work describes the photogrammetric procedure developed for the synchronization and calibration of the GoPro cameras and provides a thorough analysis on the achievable results.
MULTI-DATE SENTINEL1 SAR IMAGE TEXTURES DISCRIMINATE PERENNIAL AGROFORESTS IN A TROPICAL FOREST-SAVANNAH TRANSITION LANDSCAPE
Authors: Numbisi F. N. , Van Coillie F. , De Wulf R.
Published: September 2018

Abstract. Synthetic Aperture Radar (SAR) provides consistent information on target land features; especially in tropical conditions that restrain penetration of optical imaging sensors. Because radar response signal is influenced by geometric and di-electrical properties of surface features’, the different land cover may appear similar in radar images. For discriminating perennial cocoa agroforestry land cover, we compare a multi-spectral optical image from RapidEye, acquired in the dry season, and multi-seasonal C-band SAR of Sentinel 1: A final set of 10 (out of 50) images that represent six dry and four wet seasons from 2015 to 2017. We ran eight RF models for different input band combinations; multi-spectral reflectance, vegetation indices, co-(VV) and cross-(VH) polarised SAR intensity and Grey Level Co-occurrence Matrix (GLCM) texture measures. Following a pixel-based image analysis, we evaluated accuracy metrics and uncertainty Shannon entropy. The model comprising co- and cross-polarised texture bands had the highest accuracy of 88.07 % (95 % CI: 85.52–90.31) and kappa of 85.37; and the low class uncertainty for perennial agroforests and transition forests. The optical image had low classification uncertainty for the entire image; but, it performed better in discriminating non-vegetated areas. The measured uncertainty provides reliable validation for comparing class discrimination from different image resolution. The GLCM texture measures that are crucial in delineating vegetation cover differed for the season and polarization of SAR image. Given the high accuracies of mapping, our approach has value for landscape monitoring; and, an improved valuation of agroforestry contribution to REDD+ strategies in the Congo basin sub-region.
LEM BENCHMARK DATABASE FOR TROPICAL AGRICULTURAL REMOTE SENSING APPLICATION
Authors: Sanches I. D. , Feitosa R. Q. , Achanccaray P. , Montibeller B. , Luiz A. J. B. , Soares M. D. , Prudente V. H. R. , Vieira D. C. , Maurano L. E. P.
Published: September 2018

Abstract. The monitoring of agricultural activities at a regular basis is crucial to assure that the food production meets the world population demands, which is increasing yearly. Such information can be derived from remote sensing data. In spite of topic’s relevance, not enough efforts have been invested to exploit modern pattern recognition and machine learning methods for agricultural land-cover mapping from multi-temporal, multi-sensor earth observation data. Furthermore, only a small proportion of the works published on this topic relates to tropical/subtropical regions, where crop dynamics is more complicated and difficult to model than in temperate regions. A major hindrance has been the lack of accurate public databases for the comparison of different classification methods. In this context, the aim of the present paper is to share a multi-temporal and multi-sensor benchmark database that can be used by the remote sensing community for agricultural land-cover mapping. Information about crops in situ was collected in Luís Eduardo Magalhães (LEM) municipality, which is an important Brazilian agricultural area, to create field reference data including information about first and second crop harvests. Moreover, a series of remote sensing images was acquired and pre-processed, from both active and passive orbital sensors (Sentinel-1, Sentinel-2/MSI, Landsat-8/OLI), correspondent to the LEM area, along the development of the main annual crops. In this paper, we describe the LEM database (crop field boundaries, land use reference data and pre-processed images) and present the results of an experiment conducted using the Sentinel-1 and Sentinel-2 data.
EFFECT OF DIFFERENT SEGMENTATION METHODS USING OPTICAL SATELLITE IMAGERY TO ESTIMATE FUZZY CLUSTERING PARAMETERS FOR SENTINEL-1A SAR IMAGES
Authors: Bayram B. , Demir N. , Akpinar B. , Oy S. , Erdem F. , Vögtle T. , Seker D. Z.
Published: September 2018

Abstract. Optical and SAR data are efficient data sources for shoreline monitoring. The processing of SAR data such as feature extraction is not an easy task since the images have totally different structure than optical imagery. Determination of threshold value is a challenging task for SAR data. In this study, SENTINEL-2A optical data was used as ancillary data to predict fuzzy membership parameters for segmentation of SENTINEL-1A SAR data to extract shoreline. SENTINEL-2A and SENTINEL-1A satellite images used were taken in September 9, 2016 and September 13, 2016 respectively. Three different segmentation algorithms which are selected from object, learning and pixel-based methods. They have been exploited to obtain land and water classes which have been used as an input data for parameter estimation. Thus, the performance of different segmentation algorithm has been investigated and analysed. In the first step of the study, Mean-Shift, Random Forest and Whale Optimization algorithms have been employed to obtain water and land classes from the SENTINEL-2A image. Water and land classes derived from each algorithm – are used as input data, and then the required parameters for the fuzzy clustering of SENTINEL-1A SAR image, were calculated. Lake Constance, Germany has been chosen as the study area. In this study, additionally an interface plugin has been developed and integrated into the open source Quantum GIS software platform. The developed interface allows non-experts to process and extract the shorelines without using any parameters. But, this system requires pre-segmented data as input. Thus, the batch process calculates the required parameters.
TANDEM-X MISSION STATUS, PRODUCTS AND PERSPECTIVES
Authors: Böer J. , Wecklich C. , Bachmann M. , Buckreuss S. , Rizzoli P. , Zink M.
Published: September 2018

Abstract. TanDEM-X is an innovative single-pass interferometric radar mission, which is comprised of two formation flying satellites. The TerraSAR-X (TSX) satellite was launched on June 15th 2007, and its almost identically constructed twin satellite TanDEM-X (TDX) was launched on 21st of June 2010. Together they supply high-quality radar data in order to serve two main mission goals: Scientific observation of the Earth and provision of remote sensing data for the commercial market (TerraSAR-X mission), and the generation of a global digital elevation model (DEM) of the Earth’s surface (TanDEM-X mission). Between December 2010 and early 2015, radar data of all land surfaces has been acquired and as of September 2016 the final TanDEM-X DEM dataset has been available. This paper provides a final quality assessment of the TanDEM-X global DEM products with respect to the relative and absolute height accuracy and data coverage both at the global and geocell level. In addition, an overview on current mission status is given and new DEM products, which are currently in the scope of the TanDEM-X mission, are described.
MOBILE LASER SCANNING SYSTEMS FOR GPS/GNSS-DENIED ENVIRONMENT MAPPING
Authors: Wen C. , Xia Y. , Lian Y. , Dai Y. , Tan J. , Wang C. , Li J.
Published: September 2018

Abstract. Indoor 3D mapping provides a useful three-dimensional structure via an indoor map for many applications. To acquire highly efficient and relatively accurate mapping for large-scale GPS/GNSS-denied scene, we present an upgraded backpacked laser scanning system and a car-mounted indoor mobile laser scanning system. The systems provide both 3D laser scanning point cloud and camera images. In this paper, a simultaneous extrinsic calibration approach for multiple multi-beam LIDAR and multiple cameras is also proposed using the Simultaneous Localization and Mapping (SLAM)-based algorithm. The proposed approach uses the SLAM-based algorithm to achieve a large calibration scene using mobile platforms, registers an acquired multi-beam LIDAR point cloud to the terrestrial LIDAR point cloud to acquire denser points for corner feature extraction, and finally achieves simultaneous calibration. With the proposed mapping and calibration algorithms, we can provide centimetre-lever coloured point cloud with relatively high efficiency and accuracy.
MICRO-RADAR AND UWB AIDED UAV NAVIGATION IN GNSS DENIED ENVIRONMENT
Authors: Zahran S. , Mostafa M. M. , Masiero A. , Moussa A. M. , Vettore A. , El-Sheimy N.
Published: September 2018

Abstract. During the last decade, the number of applications of UAVs has continuously increased, making the global UAV market one of those with the highest rate of growth. The worldwide increasing usage of UAVs is causing an ever-growing demand for efficient solutions in order to make them usable in every kind of working condition. In fact, nowadays the main restriction to the usage of UAVs is probably the need of reliable position estimates provided by using the Global Navigation Satellite System (GNSS): since UAVs mostly rely on the integration of GNSS/Inertial Navigation System (INS) to properly fulfil their tasks, they face a major challenge while navigating in GNSS denied environments. The goal of this paper is that of investigating possible strategies to reduce such main restriction to UAV usage, i.e. enabling flights in GNSS denied environment by providing position estimates with accuracy quite comparable to that of standard GNSS receivers currently mounted on commercialized drones. To be more specific, this paper proposes the combined use of a novel Frequency Modulated Continuous Wave (FMCW) Radar, a set of Ultra-Wideband (UWB) devices, and Inertial Measurement Unit (IMU) measurements in order to compensate for the unavailability of the GNSS signal units. A 24-GHz micro FMCW radar and a UWB device have been attached to a quadcopter during the flight. The radar receives the reflections from ground scatterers, whereas the UWB system provides range measurements between a UWB rover mounted on the UAV and a set of UWB anchors distributed along the flying area.
Dual-satellite (Sentinel-2 and Landsat 8) remote sensing of supraglacial lakes in Greenland
Authors: Williamson Andrew G. , Banwell Alison F. , Willis Ian C. , Arnold Neil S.
Published: September 2018

Abstract. Remote sensing is commonly used to monitor supraglacial lakes on
the Greenland Ice Sheet (GrIS); however, most satellite records must trade off
higher spatial resolution for higher temporal resolution (e.g. MODIS) or vice
versa (e.g. Landsat). Here, we overcome this issue by developing and applying
a dual-sensor method that can monitor changes to lake areas and volumes at
high spatial resolution (10–30 m) with a frequent revisit time (∼3 days). We achieve this by mosaicking imagery from the Landsat 8 Operational Land Imager (OLI) with
imagery from the recently launched Sentinel-2 Multispectral Instrument (MSI) for a ∼12 000 km2 area of West Greenland in the 2016 melt season. First, we
validate a physically based method for calculating lake depths with
Sentinel-2 by comparing measurements against those derived from the available
contemporaneous Landsat 8 imagery; we find close correspondence between the
two sets of values (R2=0.841; RMSE = 0.555 m). This provides us
with the methodological basis for automatically calculating lake areas,
depths, and volumes from all available Landsat 8 and Sentinel-2 images. These
automatic methods are incorporated into an algorithm for Fully Automated
Supraglacial lake Tracking at Enhanced Resolution (FASTER). The FASTER
algorithm produces time series showing lake evolution during the 2016 melt
season, including automated rapid (≤4 day) lake-drainage identification.
With the dual Sentinel-2–Landsat 8 record, we identify 184 rapidly draining
lakes, many more than identified with either imagery collection alone (93
with Sentinel-2; 66 with Landsat 8), due to their inferior temporal
resolution, or would be possible with MODIS, due to its omission of small
lakes <0.125 km2. Finally, we estimate the water volumes drained
into the GrIS during rapid-lake-drainage events and, by analysing downscaled
regional climate-model (RACMO2.3p2) run-off data, the water quantity that
enters the GrIS via the moulins opened by such events. We find that during
the lake-drainage events alone, the water drained by small lakes (<0.125 km2) is only 5.1 % of the total water volume drained by all
lakes. However, considering the total water volume entering the GrIS after
lake drainage, the moulins opened by small lakes deliver 61.5 % of the
total water volume delivered via the moulins opened by large and small lakes;
this is because there are more small lakes, allowing more moulins to open,
and because small lakes are found at lower elevations than large lakes, where
run-off is higher. These findings suggest that small lakes should be included
in future remote-sensing and modelling work.
“The Greatest Agricultural Colony on Earth”: Landscape and Community Development of the Estelle Colony, Atlantic County, New Jersey, 1895–1910
Authors: Avery-Quinn Samuel
Published: September 2018

In 1901 the Chancery Court of New Jersey heard arguments in one of the largest property lawsuits ever held in Atlantic County. The suit, filed by the Estell Family, alleged that Philadelphia businessman Daniel Risley had failed to repay mortgages held by the Estells on thousands of acres of pinelands along the Tuckahoe River. Risley had developed the lands as the Estelle Colony. The lawsuit opened a window onto the economic decline, real estate speculation, and demographic changes transforming the landscape of the southern New Jersey Pine Barrens. As the colony's mostly immigrant residents struggled with building homes, farming the sandy pinelands soils, and filling a vacuum of governance with a unique example of a village improvement association, they transformed their landscape and crafted community identity out of hardship. The first years of their settlement present a significant story of placemaking in Philadelphia's nearest wilderness.
Interdisciplinary Connections Across the Curriculum: Fostering Collaborations between Freshman and Capstone Students Through Peer-Review Assignments
Authors: Boumlik Habiba , Jaafar Reem , Alberts Ian
Published: September 2018

Cultivating interdisciplinary connections between freshman and capstone students epitomizes a novel pedagogical approach to deepen student understanding of the learning process in a Community College environment. Within such a context, this article focuses on the outcomes of a two-semester collaborative effort that aims to establish and strengthen interactions between students at opposite ends of the academic spectrum. The work discussed focuses on an initiative in which capstone students in their culminating college class are supported in using their educational experiences to guide their first-year peers as they make the transition to college life. After discussing the creation and implementation of scaffolded collaborative assignments in which capstone students peer-reviewed freshman students work, the paper analyzes the impact of the research on student understanding of the learning process, the outcomes of self-reflection activities, student integration of knowledge and skills from diverse sources and the quality of their work in the peer-review endeavor.
A study of HIV positive undocumented African migrants’ access to health services in the UK
Authors: Whyte IV James , Whyte Maria D. , Dickey Sabrina
Published: September 2018

Newly immigrated persons, whatever their origin, tend to fall in the lower socioeconomic levels.  In fact, failure of an asylum application renders one destitute in a large proportion of cases, often resulting in a profound lack of access to basic necessities. With over a third of HIV positive failed asylum seekers reporting no income, and the remainder reporting highly limited resources, poverty is a reality for the vast majority. The purpose of the study was to determine the basic social processes that guide HIV positive undocumented migrant’s efforts to gain health services in the UK. The study used the Grounded Theory Approach. Theoretical saturation occurred after 16 participants were included in the study. The data included reflections of the prominent factors related to the establishment of a safe and productive life and the ability of individuals to remain within the UK. The data reflected heavily upon the ability of migrants to enter the medical care system during their asylum period, and on an emerging pattern of service denial after loss on immigration appeal, which often resulted in a discontinuation of medical therapies. This inevitably was associated with a pattern of decline and inability to fundamental needs. The findings of this study are notable in that they have demonstrated sequence of events along a timeline related to the interaction between the asylum process and access to health related services. The results reflect that African migrants maintain a degree of formal access to health services during the period that they possess legal access to services and informal access after the failure of their asylum claim.
Nursing students’ attitudes towards older people and future career choices in Macao-A pilot study
Authors: Hsu Mei Hua Kerry , Ling Man Ho
Published: September 2018

Background: As global ageing, Macao also faces challenges with regards to an aging population. Not many nursing students are willing to choose gerontological nursing (GN) as a career choice. This pilot study was conducted on a small sample of Macao nursing students to assess nursing students’ attitudes towards older people and their future career choices. Moreover, this pilot study is aimed to validate the survey questionnaire for the further study.Methods: A cross-sectional survey to explore 30 Macao nursing students’ attitudes towards older people and future career choices. Kogan’s attitudes towards older people scale (KAOP) was adopted in this study.Results: About 33.3% nursing students agreed to work in GN after graduation. Only 6.7% participants chose “aged care institute” as their first choice for future career. Participants have higher mean scores of KAOP that indicate more positive attitudes towards older people. “GN practice experience” and “personal preference” are confirmed as contributors for nursing students towards GN in this study.Conclusions: Macao nursing students have positive attitudes towards older people but not many of them would choose GN as future career. This pilot study provided knowledge to current nursing educators and government for the situation among nursing students in Macao.
Comparison of Short-term Complication Rates Between Cephalomedullary Hip Screw Devices and Sliding Hip Screws: An Analysis of the National Surgical Quality Improvement Program Database
Authors: Pandarinath Rajeev , Amdur Richard , DeBritz James N. , Rao Raj D.
Published: September 2018

Background:

The literature pertaining to the management of intertrochanteric hip fractures using cephalomedullary hip screws (CMHSs) and sliding hip screws (SHSs) has shown varying results. CMHS use has increased over time without validation of its superiority in the literature.

Methods:

We conducted a retrospective cohort study using the American College of Surgeons National Quality Improvement Program database. Patients who had sustained a peritrochanteric hip fracture were identified. Short-term (<30 day) complications were identified with adjustments made for preoperative comorbidities. We also examined the relative percentages of CMHS and SHS surgeries over time.

Results:

A total of 14,415 subjects met the inclusion criteria. Patients undergoing SHS surgery were generally healthier, having a lower American College of Surgeon class, preoperative bleeding, hypertension, pulmonary risk factors, congestive heart failure, and higher preoperative hematocrit. After adjusting for demographics and comorbidities, we noted a higher rate of 30-day mortality (odds ratio [OR] = 1.19; P = 0.024), bleeding (OR = 1.10; P = 0.007), pulmonary complications (OR = 1.19; P = 0.049), and clotting events (OR = 1.35; P = 0.035) in the CMHS group. We observed a higher rate of urinary tract infection (OR = 0.81; P = 0.023) and length of stay (1.0 days; P < 0.0001) in the SHS group. The overall percentage of SHS cases was 33% and trended lower over time.

Conclusions:

Although differences in complication subtypes and the overall complication rate were found, further multicenter, randomized controlled trials would be helpful in elucidating differences between the treatment groups. The popularity of the CMHS continues to increase over time.