bluuebunny/crossref_metadata_2025 huggingface dataset:
MULTISCALE SEGMENTATION OF POLARIMETRIC SAR IMAGE BASED ON SRM SUPERPIXELS
Authors: Lang F. , Yang J. , Wu L. , Li D.
Published: June 2016

Abstract. Multi-scale segmentation of remote sensing image is more systematic and more convenient for the object-oriented image analysis compared to single-scale segmentation. However, the existing pixel-based polarimetric SAR (PolSAR) image multi-scale segmentation algorithms are usually inefficient and impractical. In this paper, we proposed a superpixel-based binary partition tree (BPT) segmentation algorithm by combining the generalized statistical region merging (GSRM) algorithm and the BPT algorithm. First, superpixels are obtained by setting a maximum region number threshold to GSRM. Then, the region merging process of the BPT algorithm is implemented based on superpixels but not pixels. The proposed algorithm inherits the advantages of both GSRM and BPT. The operation efficiency is obviously improved compared to the pixel-based BPT segmentation. Experiments using the Lband ESAR image over the Oberpfaffenhofen test site proved the effectiveness of the proposed method.
MAPPING TROPICAL FOREST FOR SUSTAINABLE MANAGEMENT USING SPOT 5 SATELLITE IMAGE
Authors: Nguyen Huong Thi Thanh
Published: June 2016

Abstract. This paper describes the combination of multi-data in stratifying the natural evergreen broadleaved tropical forest of the Central Highlands of Vietnam. The forests were stratified using both unsupervised and supervised classification methods based on SPOT5 and field data. The forests were classified into 3 and 4 strata separably. Correlation between stratified forest classes and forest variables was analyzed in order to find out 1) how many classes is suitable to stratify for the forest in this area and 2) how closely the forest variables are related with forest classes. The correlation coefficient shows although all forest variables did have a significant correlation with the forest classes, stand volume appeared to have the strongest correlation with forest classes. These are 0.64 and 0.59 for four and three strata respectively. The results of supervised classification also show the four strata of heavily degraded forest, moderate disturbance, insignificant disturbance, and dense forest were discriminated more clearly comparing to the forest stratified into three classes. The proof is that overall accuracy of supervised classification was 86% with Kappa of 0.8 for four classes, meanwhile, these are 77% and 0.62 respectively for forest area classified into 3 classes.
POLARIMETRIC SAR DATA GMM CLASSIFICATION BASED ON IMPROVED FREEMAN INCOHERENT DECOMPOSITION
Authors: Rouabah S. , Ouarzeddine M. , Azmedroub B.
Published: June 2016

Abstract. Due to the increasing volume of available SAR Data, powerful classification processings are needed to interpret the images. GMM (Gaussian Mixture Model) is widely used to model distributions. In most applications, GMM algorithm is directly applied on raw SAR data, its disadvantage is that forest and urban areas are classified with the same label and gives problems in interpretation. In this paper, a combination between the improved Freeman decomposition and GMM classification is proposed. The improved Freeman decomposition powers are used as feature vectors for GMM classification. The E-SAR polarimetric image acquired over Oberpfaffenhofen in Germany is used as data set. The result shows that the proposed combination can solve the standard GMM classification problem.
PRELIMINARY RESULTS OF EARTHQUAKE-INDUCED BUILDING DAMAGE DETECTION WITH OBJECT-BASED IMAGE CLASSIFICATION
Authors: Sabuncu A. , Uca Avci Z. D. , Sunar F.
Published: June 2016

Abstract. Earthquakes are the most destructive natural disasters, which result in massive loss of life, infrastructure damages and financial losses. Earthquake-induced building damage detection is a very important step after earthquakes since earthquake-induced building damage is one of the most critical threats to cities and countries in terms of the area of damage, rate of collapsed buildings, the damage grade near the epicenters and also building damage types for all constructions. Van-Ercis (Turkey) earthquake (Mw= 7.1) was occurred on October 23th, 2011; at 10:41 UTC (13:41 local time) centered at 38.75 N 43.36 E that places the epicenter about 30 kilometers northern part of the city of Van. It is recorded that, 604 people died and approximately 4000 buildings collapsed or seriously damaged by the earthquake. In this study, high-resolution satellite images of Van-Ercis, acquired by Quickbird-2 (© Digital Globe Inc.) after the earthquake, were used to detect the debris areas using an object-based image classification. Two different land surfaces, having homogeneous and heterogeneous land covers, were selected as case study areas. As a first step of the object-based image processing, segmentation was applied with a convenient scale parameter and homogeneity criterion parameters. As a next step, condition based classification was used. In the final step of this preliminary study, outputs were compared with streetview/ortophotos for the verification and evaluation of the classification accuracy.
TOPIC MODELLING FOR OBJECT-BASED CLASSIFICATION OF VHR SATELLITE IMAGES BASED ON MULTISCALE SEGMENTATIONS
Authors: Shen Li , Wu Linmei , Li Zhipeng
Published: June 2016

Abstract. Multiscale segmentation is a key prerequisite step for object-based classification methods. However, it is often not possible to determine a sole optimal scale for the image to be classified because in many cases different geo-objects and even an identical geo-object may appear at different scales in one image. In this paper, an object-based classification method based on mutliscale segmentation results in the framework of topic modelling is proposed to classify VHR satellite images in an entirely unsupervised fashion. In the stage of topic modelling, grayscale histogram distributions for each geo-object class and each segment are learned in an unsupervised manner from multiscale segments. In the stage of classification, each segment is allocated a geo-object class label by the similarity comparison between the grayscale histogram distributions of each segment and each geo-object class. Experimental results show that the proposed method can perform better than the traditional methods based on topic modelling.
A FUZZY LOGIC-BASED APPROACH FOR THE DETECTION OF FLOODED VEGETATION BY MEANS OF SYNTHETIC APERTURE RADAR DATA
Authors: Tsyganskaya V. , Martinis S. , Twele A. , Cao W. , Schmitt A. , Marzahn P. , Ludwig R.
Published: June 2016

Abstract. In this paper an algorithm designed to map flooded vegetation from synthetic aperture radar (SAR) imagery is introduced. The approach is based on fuzzy logic which enables to deal with the ambiguity of SAR data and to integrate multiple ancillary data containing topographical information, simple hydraulic considerations and land cover information. This allows the exclusion of image elements with a backscatter value similar to flooded vegetation, to significantly reduce misclassification errors. The flooded vegetation mapping procedure is tested on a flood event that occurred in Germany over parts of the Saale catchment on January 2011 using a time series of high resolution TerraSAR-X data covering the time interval from 2009 to 2015. The results show that the analysis of multi-temporal X-band data combined with ancillary data using a fuzzy logic-based approach permits the detection of flooded vegetation areas.
BALANCED VS IMBALANCED TRAINING DATA: CLASSIFYING RAPIDEYE DATA WITH SUPPORT VECTOR MACHINES
Authors: Ustuner M. , Sanli F. B. , Abdikan S.
Published: June 2016

Abstract. The accuracy of supervised image classification is highly dependent upon several factors such as the design of training set (sample selection, composition, purity and size), resolution of input imagery and landscape heterogeneity. The design of training set is still a challenging issue since the sensitivity of classifier algorithm at learning stage is different for the same dataset. In this paper, the classification of RapidEye imagery with balanced and imbalanced training data for mapping the crop types was addressed. Classification with imbalanced training data may result in low accuracy in some scenarios. Support Vector Machines (SVM), Maximum Likelihood (ML) and Artificial Neural Network (ANN) classifications were implemented here to classify the data. For evaluating the influence of the balanced and imbalanced training data on image classification algorithms, three different training datasets were created. Two different balanced datasets which have 70 and 100 pixels for each class of interest and one imbalanced dataset in which each class has different number of pixels were used in classification stage. Results demonstrate that ML and NN classifications are affected by imbalanced training data in resulting a reduction in accuracy (from 90.94% to 85.94% for ML and from 91.56% to 88.44% for NN) while SVM is not affected significantly (from 94.38% to 94.69%) and slightly improved. Our results highlighted that SVM is proven to be a very robust, consistent and effective classifier as it can perform very well under balanced and imbalanced training data situations. Furthermore, the training stage should be precisely and carefully designed for the need of adopted classifier.
EXTRACTING URBAN GROUND OBJECT INFORMATION FROM IMAGES AND LiDAR DATA
Authors: Yi Lina , Zhao Xuesheng , Li Luan , Zhang Guifeng
Published: June 2016

Abstract. To deal with the problem of urban ground object information extraction, the paper proposes an object-oriented classification method using aerial image and LiDAR data. Firstly, we select the optimal segmentation scales of different ground objects and synthesize them to get accurate object boundaries. Then, this paper uses ReliefF algorithm to select the optimal feature combination and eliminate the Hughes phenomenon. Eventually, the multiple classifier combination method is applied to get the outcome of the classification. In order to validate the feasible of this method, this paper selects two experimental regions in Stuttgart and Germany (Region A and B, covers 0.21 km2 and 1.1 km2 respectively). The aim of the first experiment on the Region A is to get the optimal segmentation scales and classification features. The overall accuracy of the classification reaches to 93.3 %. The purpose of the experiment on region B is to validate the application-ability of this method for a large area, which is turned out to be reaches 88.4 % overall accuracy. In the end of this paper, the conclusion shows that the proposed method can be performed accurately and efficiently in terms of urban ground information extraction and be of high application value.
A NEW IDL IMPLEMENTATION OF THE JUPP METHOD FOR BATHYMETRY EXTRACTION IN SHALLOW WATERS
Authors: Deidda M. , Pala A. , Sanna G.
Published: June 2016

Abstract. There is an ongoing effort in using imagery from remote sensing platforms to obtain information about the sea depth; this allows to monitor the dynamics of coastal erosion without the need for costly and repeated local surveys. We worked on a new implementation of the Jupp method to extract depth information from satellite images. Our software is based on previous implementations of the algorithm in the IDL language, but we made our current implementation more modular in order to make possible experimentations with different approaches. We used this implementation on a series of six images (three from the Landsat TM sensor and three from the Landsat OLI sensor) in order to improve the available tools. We established an iterative workflow for working on the Landat-8 images widely exposed in this paper.
OBJECT-ORIENTED CHANGE DETECTION FOR REMOTE SENSING IMAGES BASED ON MULTI-SCALE FUSION
Authors: Feng Wenqing , Sui Haigang , Tu Jihui
Published: June 2016

Abstract. In the process of object-oriented change detection, the determination of the optimal segmentation scale is directly related to the subsequent change information extraction and analysis. Aiming at this problem, this paper presents a novel object-level change detection method based on multi-scale segmentation and fusion. First of all, the fine to coarse segmentation is used to obtain initial objects of different sizes; then, according to the features of the objects, Change Vector Analysis is used to obtain the change detection results of various scales. Furthermore, in order to improve the accuracy of change detection, this paper introduces fuzzy fusion and two kinds of decision level fusion methods to get the results of multi-scale fusion. Based on these methods, experiments are done with SPOT5 multi-spectral remote sensing imagery. Compared with pixel-level change detection methods, the overall accuracy of our method has been improved by nearly 10%, and the experimental results prove the feasibility and effectiveness of the fusion strategies.
UTILIZING SAR AND MULTISPECTRAL INTEGRATED DATA FOR EMERGENCY RESPONSE
Authors: Havivi S. , Schvartzman I. , Maman S. , Marinoni A. , Gamba P. , Rotman S. R. , Blumberg D. G.
Published: June 2016

Abstract. Satellite images are used widely in the risk cycle to understand the exposure, refine hazard maps and quickly provide an assessment after a natural or man-made disaster. Though there are different types of satellite images (e.g. optical, radar) these have not been combined for risk assessments. The characteristics of different remote sensing data type may be extremely valuable for monitoring and evaluating the impacts of disaster events, to extract additional information thus making it available for emergency situations. To base this approach, two different change detection methods, for two different sensor's data were used: Coherence Change Detection (CCD) for SAR data and Covariance Equalization (CE) for multispectral imagery. The CCD provides an identification of the stability of an area, and shows where changes have occurred. CCD shows subtle changes with an accuracy of several millimetres to centimetres. The CE method overcomes the atmospheric effects differences between two multispectral images, taken at different times. Therefore, areas that had undergone a major change can be detected. To achieve our goals, we focused on the urban areas affected by the tsunami event in Sendai, Japan that occurred on March 11, 2011 which affected the surrounding area, coastline and inland. High resolution TerraSAR-X (TSX) and Landsat 7 images, covering the research area, were acquired for the period before and after the event. All pre-processed and processed according to each sensor. Both results, of the optical and SAR algorithms, were combined by resampling the spatial resolution of the Multispectral data to the SAR resolution. This was applied by spatial linear interpolation. A score representing the damage level in both products was assigned. The results of both algorithms, high level of damage is shown in the areas closer to the sea and shoreline. Our approach, combining SAR and multispectral images, leads to more reliable information and provides a complete scene for the emergency response following an event.
OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH
Authors: Jia Yonghong , Zhou Mingting , Jinshan Ye
Published: June 2016

Abstract. The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.
ANALYSIS OF LANDSLIDES BASED ON DISPLACEMENTS OF LINES
Authors: Mozas-Calvache A. T. , Pérez-García J. L. , Fernández-del Castillo T. , Gómez-López J. M. , Colomo-Jiménez C.
Published: June 2016

Abstract. Nowadays, the development of UAS has allowed the obtaining of high resolution and accurate cartographic products, such as DSMs and orthoimages. These products can be used in studies of the evolution of landslides. The stability of slopes is a main issue because, among others, it can suppose a serious risk to infrastructures. Until this moment, some studies for analysing slope movements have been carried out using the comparison of positions of well-defined points or comparing two surfaces obtained from two DSMs. In this paper we present a methodology for analysing landslides based on some linear elements located on the terrain. More specifically, we analyse some lines of road sections which are located on an unstable slope, checking the movements of the landslide and their effect on the infrastructure. The methodology includes the obtaining of high resolution orthoimages and DSMs which correspond to two or more epochs of the same landslide, the 3D digitizing of common linear elements, and the computing of the displacements of matched lines (from two epochs) using positional control methods based on lines. The proposed methodology has been tested using two DSMs and two orthoimages (corresponding to two epochs) obtained from two photogrammetric projects developed with an UAS. This real case was applied to an unstable slope with landslides which affected several sections of a road. The results have demonstrated the viability of the proposed methodology in analysing the behaviour of the landslide and more specifically, the effects on these infrastructures.
CHANGE DETECTION IN UAV VIDEO MOSAICS COMBINING A FEATURE BASED APPROACH AND EXTENDED IMAGE DIFFERENCING
Authors: Saur Günter , Krüger Wolfgang
Published: June 2016

Abstract. Change detection is an important task when using unmanned aerial vehicles (UAV) for video surveillance. We address changes of short time scale using observations in time distances of a few hours. Each observation (previous and current) is a short video sequence acquired by UAV in near-Nadir view. Relevant changes are, e.g., recently parked or moved vehicles. Examples for non-relevant changes are parallaxes caused by 3D structures of the scene, shadow and illumination changes, and compression or transmission artifacts. In this paper we present (1) a new feature based approach to change detection, (2) a combination with extended image differencing (Saur et al., 2014), and (3) the application to video sequences using temporal filtering. In the feature based approach, information about local image features, e.g., corners, is extracted in both images. The label “new object” is generated at image points, where features occur in the current image and no or weaker features are present in the previous image. The label “vanished object” corresponds to missing or weaker features in the current image and present features in the previous image. This leads to two “directed” change masks and differs from image differencing where only one “undirected” change mask is extracted which combines both label types to the single label “changed object”. The combination of both algorithms is performed by merging the change masks of both approaches. A color mask showing the different contributions is used for visual inspection by a human image interpreter.
MONITORING PHENOLOGY OF FLOODPLAIN GRASSLAND AND HERBACEOUS VEGETATION WITH UAV IMAGERY
Authors: van Iersel W. K. , Straatsma M. W. , Addink E. A. , Middelkoop H.
Published: June 2016

Abstract. River restoration projects, which aim at improved flood safety and increased ecological value, have resulted in more heterogeneous vegetation. However, they also resulted in increasing hydraulic roughness, which leads to higher flood water levels during peak discharges. Due to allowance of vegetation development and succession, both ecological and hydraulic characteristics of the floodplain change more rapidly over time. Monitoring of floodplain vegetation has become essential to document and evaluate the changing floodplain characteristics and associated functioning. Extraction of characteristics of low vegetation using single-epoch remote sensing data, however, remains challenging. The aim of this study was to (1) evaluate the performance of multi-temporal, high-spatial-resolution UAV imagery for extracting temporal vegetation height profiles of grassland and herbaceous vegetation in floodplains and (2) to assess the relation between height development and NDVI changes. Vegetation height was measured six times during one year in 28 field plots within a single floodplain. UAV true-colour and false-colour imagery of the floodplain were recorded coincidently with each field survey. We found that: (1) the vertical accuracy of UAV normalized digital surface models (nDSMs) is sufficiently high to obtain temporal height profiles of low vegetation over a growing season, (2) vegetation height can be estimated from the time series of nDSMs, with the highest accuracy found for combined imagery from February and November (RMSE = 29-42 cm), (3) temporal relations between NDVI and observed vegetation height show different hysteresis behaviour for grassland and herbaceous vegetation. These results show the high potential of using UAV imagery for increasing grassland and herbaceous vegetation classification accuracy.
CALIBRATION/VALIDATION OF LANDSAT-DERIVED OCEAN COLOUR PRODUCTS IN BOSTON HARBOUR
Authors: Pahlevan Nima , Sheldon Patrick , Peri Francesco , Wei Jianwei , Shang Zhehai , Sun Qingsong , Chen Robert F. , Lee Zhongping , Schaaf Crystal B. , Schott John R. , Loveland Thomas
Published: June 2016

Abstract. The Landsat data archive provides a unique opportunity to investigate the long-term evolution of coastal ecosystems at fine spatial scales that cannot be resolved by ocean colour (OC) satellite sensors. Recognizing Landsat’s limitations in applications over coastal waters, we have launched a series of field campaigns in Boston Harbor and Massachusetts Bay (MA, USA) to validate OC products derived from Landsat-8. We will provide a preliminary demonstration on the calibration/validation of the existing OC algorithms (atmospheric correction and in-water optical properties) to enhance monitoring efforts in Boston Harbor. To do so, Landsat optical images were first compared against ocean colour products over high-latitude regions. The in situ cruise data, including optical data (remote sensing reflectance) and water samples were analyzed to obtain insights into the optical and biogeochemical properties of near-surface waters. Along with the cruise data, three buoys were deployed in three locations across the Harbor to complement our database of concentrations of chlorophyll a, total suspended solids (TSS), and absorption of colour dissolved organic matter (CDOM). The data collected during the first year of the project are used to develop and/or tune OC algorithms. The data will be combined with historic field data to map in-water constituents back to the early 1990’s. This paper presents preliminary analysis of some of the data collected under Landsat-8 overpasses.
USING MULTI-DIMENSIONAL MICROWAVE REMOTE SENSING INFORMATION FOR THE RETRIEVAL OF SOIL SURFACE ROUGHNESS
Authors: Marzahn P. , Ludwig R.
Published: June 2016

Abstract. In this Paper the potential of multi parametric polarimetric SAR (PolSAR) data for soil surface roughness estimation is investigated and its potential for hydrological modeling is evaluated. The study utilizes microwave backscatter collected from the Demmin testsite in the North-East Germany during AgriSAR 2006 campaign using fully polarimetric L-Band airborne SAR data. For ground truthing extensive soil surface roughness in addition to various other soil physical properties measurements were carried out using photogrammetric image matching techniques. The correlation between ground truth roughness indices and three well established polarimetric roughness estimators showed only good results for Re[ρRRLL] and the RMS Height s. Results in form of multitemporal roughness maps showed only satisfying results due to the fact that the presence and development of particular plants affected the derivation. However roughness derivation for bare soil surfaces showed promising results.
VISUAL TOOLS FOR CROWDSOURCING DATA VALIDATION WITHIN THE GLOBELAND30 GEOPORTAL
Authors: Chuprikova E. , Wu H. , Murphy C. E. , Meng L.
Published: June 2016

Abstract. This research aims to investigate the role of visualization of the user generated data that can empower the geoportal of GlobeLand30 produced by NGCC (National Geomatics Center of China). The focus is set on the development of a concept of tools that can extend the Geo-tagging functionality and make use of it for different target groups. The anticipated tools should improve the continuous data validation, updating and efficient use of the remotely-sensed data distributed within GlobeLand30.
PRAGMATICS DRIVEN LAND COVER SERVICE COMPOSITION UTILIZING BEHAVIOR-INTENTION MODEL
Authors: Wu Hao , Chen Jun , Xing Huaqiao , Li Songnian , Hu Juju
Published: June 2016

Abstract. Web service composition is one of the key issues to develop a global land cover (GLC) information service portal. Aiming at the defect that traditional syntax and semantic service compositionare difficult to take pragmatic information into account, the paper firstly analyses three tiers of web service language and their succession relations, discusses the conceptual model of pragmatic web service, and proposes the idea of pragmatics-oriented adaptive composition method based on the analysis of some examples. On this basis it puts forward the pragmatic web service model based on Behavior-Intention through presetting and expression of service usability, users' intention, and other pragmatic information, develops the on-demand assembly method based on the agent theory and matching and reconstruction method on heterogeneous message, solves the key technological issue of algorithm applicability and heterogeneous message transformation in the process of covering web service composition on the ground, applies these methods into service combination, puts forward the pragmatic driven service composition method based on behavior-intention model, and effectively settles the issue of coordination and interaction of composite service invocation.
ERA-PLANET THE EUROPEAN NETWORK FOR OBSERVING OUR CHANGING PLANET
Authors: Pirrone N. , Cinnirella S. , Nativi S. , Sprovieri F. , Hedgecock I. M.
Published: June 2016

Abstract. In the last decade a significant number of projects and programmes in different domains of Earth Observation and environmental monitoring have generated a substantial amount of data and knowledge on different aspects related to environmental quality and sustainability. Big data generated by in-situ or satellite platforms are being collected and archived with a plethora of systems and instruments making difficult the sharing of data and transfer of knowledge to stakeholders and policy makers to support key economic and societal sectors. The overarching goal of ERAPLANET is to strengthen the European Research Area in the domain of Earth Observation in coherence with the European participation in the Group on Earth Observation (GEO) and Copernicus. The expected impact is to strengthen European leadership within the forthcoming GEO 2015-2025 Work Plan. ERA-PLANET is designed to reinforce the interface with user communities, whose needs the Global Earth Observation System of Systems (GEOSS) intends to address. It will provide more accurate, comprehensive and authoritative information to policy and decision-makers in key societal benefit areas, such as Smart Cities and Resilient Societies; Resource efficiency and Environmental management; Global changes and Environmental treaties; Polar areas and Natural resources. ERA-PLANET will provide advanced decision-support tools and technologies aimed to better monitor our global environment and share the information and knowledge available in the different domains of Earth Observation.
Development and analysis of a continuous record of global near-surface soil freeze/thaw patterns from AMSR-E and AMSR2 data
Authors: Hu Tongxi , Zhao Tianjie , Shi Jiancheng , Wang Tianxing , Ji Dabin , Bitar Ahmad Al , Peng Bin , Cui Yurong
Published: June 2016

Abstract. Monitoring near-surface soil freeze/thaw patterns is becoming essential under the context of global changes as it is more sensitive to climatic fluctuation compared with subsurface thermal characteristics and its evolution could be an early warning of changes in near-surface permafrost. It requires continuous long term and stable data record for understanding hydrological, ecological and biogeochemical responses of permafrost to global climate change. AMSR2 (Advanced Microwave Scanning Radiometer 2) is designed as a successor of AMSR-E (Advanced Microwave Scanning Radiometer – Earth Observing System) to ensure continuity of such observation. In this study, a linear regression is used to inter-calibrate the AMSR-E and AMSR2 brightness temperatures. Then discriminant function algorithm is adopted to produce a long term freeze/thaw data record. It is compared with in situ air temperature measurements from both the temporal and spatial aspects. The results show that the accuracy is consistent between AMSR-E and AMSR2 with a value above 85 %, according to the result of spatial distribution accuracy. Analysis is conducted with this data record to explore the spatial distribution of frost days, its changing trend and the frost probability of each pixel on a specific date. The mean annual frost days of high northern latitude (HNL, > 45° N) zone is 214.2 ± 69.5 days and the trend of frost days indicates that the frost period is decreasing at a rate of −0.0065 day/month in 27 % of the domain which is defined by significance level of the F-test, and most of which are concentrated in the high latitude area specifically over the Northeast of Canada, Central and Eastern Russia and most part of Eastern Europe. The significant changes in frost days mostly occur in regions of discontinuous permafrost and transient permafrost. The spatial distribution of the frost days and its trend variations are found to be consistent with the minimum temperature anomalies trend. It indicates that the global warming is not constant at different regions over the globe. Further analysis over the Qinghai-Tibetan Plateau where discontinuous permafrost, island permafrost, seasonally frozen ground exist demonstrated that the frost period is shortening slightly over the past decade, and the last frost date is advanced over more than half of the region. It is considered to be a remarkable indication for permafrost degradation in this area.
Operational algorithm for ice/water classification on dual-polarized RADARSAT-2 images
Authors: Zakhvatkina Natalia , Korosov Anton , Muckenhuber Stefan , Sandven Stein , Babiker Mohamed
Published: June 2016

Abstract. Synthetic aperture radar (SAR) data from RADARSAT-2 (RS2) taken in dual-polarization mode provide additional information for discriminating sea ice and open water compared to single-polarization data. We have developed a fully automatic algorithm to distinguish between open water (rough/calm) and sea ice based on dual-polarized RS2 SAR images. Several technical problems inherent in RS2 data were solved on the pre-processing stage including thermal noise reduction in HV-polarization channel and correction of angular backscatter dependency on HH-polarization. Texture features are used as additional information for supervised image classification based on Support Vector Machines (SVM) approach. The main regions of interest are the ice-covered seas between Greenland and Franz Josef Land. The algorithm has been trained using 24 RS2 scenes acquired during winter months in 2011 and 2012, and validated against the manually derived ice chart product from the Norwegian Meteorological Institute. Between 2013 and 2015, 2705 RS2 scenes have been utilised for validation and the average classification accuracy has been found to be 91 ± 4 %.
Polifemo en Yucatán. Variaciones sobre un episodio de la Eneida en la épica cortesiana del Quinientos
Authors: Río Torres-Murciano Antón
Published: June 2016

Entre los modelos literarios que, en las epopeyas quinientistas acerca de la conquista de México, sirven para dar forma épica a la materia histórica tomada de las crónicas, la Eneida de Virgilio desempeña un papel fundamental. En el presente artículo se pretende mostrar cómo la identificación de Jerónimo de Aguilar con el Aqueménides virgiliano, que se encuentra por primera vez en el Carlo famoso de Luis Zapata, reaparece en Francisco de Terrazas, en Gabriel Lobo Lasso de la Vega y en Antonio de Saavedra Guzmán, así como proponer algunas consideraciones acerca de las relaciones que se hayan podido dar entre las obras de estos poetas.
De la letra a la tela (I): Jan Steen y La visita del médico en la pintura holandesa del Siglo de Oro a la luz de la tradición clásica
Authors: Díaz Gito Manuel Antonio
Published: June 2016

Primera parte de las dos que componen un trabajo que se ocupa de analizar la influencia de la tradición clásica en un tema pictórico de gran predicamento entre los grandes maestros del Siglo de Oro de la pintura holandesa, La visita del médico o La enferma de amor, con especial atención a su tratamiento en la obra de uno de sus más conspicuos representantes, el pintor de Leiden Jan Steen (1626-1679).
A Cloud-Based Home Management System for Patients with a left Ventricular Assist Device: A Case Report
Authors: Nomoto Shinichi , Utsumi Momoe , Minakata Kenji
Published: June 2016

Since implantable left ventricular assist devices (LVAD) with smaller configurations became available for bridge-to-transplant or even destination therapy in patients with end-stage heart failure, an increasing number of patients with these devices are receiving home medical management. However, these patients may be anxious about potential complications such as pump failure, thromboembolism, and infections that may occur during home management. To provide a sense of security during home management of patients with LVAD and to establish an ideal shared-care system, we developed a patient-centered cloud-based home management system for patients with LVAD. In this case report, we describe this system and report a trial of it in a 64-year-old patient with an LVAD.
An Analysis of the Influencing Factors of the End of City Logistics Distribution on the Base of Interpretive Structural Model
Authors: Dong Xinyi , Ju Hongmei , Yin Sifan
Published: June 2016

E-commerce has a rapid development with the advent of the Internet era, the era of “Internet +” also let many industries to find new opportunities. Now online shopping has become a mainstream to meet the needs of people’s life, especially in the developed cities, more and more people are willing to buy all sorts of goods in e - Bay, Amazon, Sunning, JD and other large e-commerce enterprises. Business enterprise needs to deliver intact goods quickly to customers to improve customers’ intention of purchasing. So the development of e-commerce and express industry is closely linked. The end of the city logistics needs to contact with consumers directly as the last part of the whole process in normal logistics distribution, which may occur some problems about the damage of goods, slow information feedback, service quality and other issues will reduce the satisfaction of consumers and affect reputation of companies. This article use ISM technology to analyze the influencing factors of the logistics of the ecommerce enterprise from the perspective of consumers, and divide all of the factors into three levels, each level contains different meanings which make a reference for the trend of development of the end of city logistics distribution. 
Blended E-Learning Constraints from the Viewpoint of Faculty Members
Authors: Abed Alabaddi Zaid Ahmad , Hisham Rahahleh Arwa , Al-Omoush Majd Mohammad
Published: June 2016

This research aims to identify obstacles ‎ to the use of blended e-learning in Al-Balqa Applied University through the viewpoint of faculty members. This research also aims at finding out the constraints that this type of e-learning and finding appropriate solutions for these constraints in the future. The results of this research will also offer proposals and recommendations that will increase the effectiveness of this type of e-learning. Furthermore, the research also aims to find out the best method of training faculty members on how to use blended e-learning.

The study used a descriptive analytical through the review of the literature on the subject of the study to determine the factors influencing the phenomenon of study. A questioner was then developed to collect the necessary data. After analysis, the results showed that the constraints relating to the University support cited the most relating to faculty members. This was followed by constraints involving students and finally constraints related to infrastructure were ranked last. Training and workshops were shown to be the best methods to develop skills for e-learning systems for faculty members.
One of the main recommendations of this study was there needs to be attractive incentives for faculty members to be motivated and provide introductory course in e-learning for students. and provide adequate support for content development and the involvement of faculty members in designing the content and Exchange of experience between faculty members in the University with the support of the Ministry of higher education, and Increase the number of laboratories dedicated to blended e-learning that is available to students outside lecture times.
Industrial Ingredient Co-branding: A Brand Relationship Approach
Authors: Andreini Daniela , Bergamaschi Mara , Pedeliento Giuseppe , Salo Jari
Published: June 2016

Existing research on industrial ingredient co-branding alliances has largely focused on the functional and
transactional value that ingredient brands provide to ingredient buyers and sellers. The current research draws on the brand relationship perspective to investigate how the relational assets of ingredient brands generate value for both ingredient buyers and for the ingredient supplier itself. For the former, such value manifests in ingredient co-branding value, and for the latter, the value lies in brand equity. The results are derived from a survey of 107 ingredient buyers from a multinational ingredient manufacturer aiming to initiate ingredient co-branding agreements in the energy component industry. The results of the structural equation model reveal that ingredient brand trust directly affects both ingredient brand loyalty and ingredient co-branding value, but indicate no significant effect between brand loyalty and ingredient co-branding value. Moreover, ingredient co-branding value proved to be a driver of ingredient supplier brand equity.
The Process of Staff Promotion in Relation to Salary or Wages Upgrade in the Public Sector Institutions: Local Government Service VS Ghana Education Service Policy Statements
Authors: Adam Abdul-Kahar , Boakye Kwame Owusu , Ashie Augustina Adei , Bawah Alhassan Salifu , Pobbi Mavis
Published: June 2016

Two sets of questionnaires were designed for experts and working staff of the case study totaling 100 elements as the target. In this study, 81 questionnaires in all were answered and returned, which were used for analysis and conclusions. Out of this, 35 elements were targeted from experts group whereas 65 elements were targeted from the non-random sampling of employees. The questionnaires were sorted as 26 answered questionnaires from the experts whereas 55 questionnaires were obtained by quota sampling (non-random) from employees as the actual responds received. As the main objective of this paper was to gather and point out the best staff promotion policy statements and procedures to enhance employers, professionals, and practitioners for future adoption. First of all, the research findings shows that the number of years that a staff will work before being promoted is not significant in the promotion process because of other factors that may be considered within such period of work.

Also, the findings showed that the number of times that a person can be or should be promoted in an organization is not significant as it depends on other factors and activities that may play a part in determining how often a person is promoted. The results obtained from the cases indicated in the hypothesis that if a staff obtains a high qualification during employment is not a guarantee for promotion.

The study also showed that staff promotion as a policy does not mean that staff will climb the organizational ladder or hierarchy automatically. It means that a lot more work is taken into account once an employee is employed by helping to solve the organizational challenges for the achievement of organizational goals and objectives. Therefore, staff promotion is the advancement of an employees’ rank or position in an organizational hierarchical system (Goblar et al., 2002; Tuwei et al., 2013). The following are the attributes or factors to be considered in staff promotion – experience and knowledge gained on-the-job, qualification, leadership skills, can do ability, good interpersonal relations, commitment to deliver/hard work, and punctuality but not job enrichment, job enlargement, whom you know, who knows you, and friendship, etc. This is what the research findings showed.
Since this paper used several research methodologies, its findings concludes that staff promotion of an organization must be in line with the general long term budgets estimates and allocations in order to apply promotion processes and procedures appropriately, efficiently, and effectively. From the research as seen in the hypothesis indicates that, if a member of staff obtained further qualification in the course of employment does not serve as a guarantee for promotion.
Comparing Executive Function of Normal Children with ADHD Children
Authors: Heydari Fereshteh , Farahani Shohreh
Published: June 2016

This study was conducted to compare with the executive function of ADHD versus normal male and female children. To obtain this objective, 30 ADHD children referring a private psychological center for the first time who had taken no medication for this disorder, and 30 normal children from one of the schools of District 14 in Tehran were selected randomly who were of the same age and gender of ADHD children. Wisconsin test was used as a measurement tool. Results showed that there is a significant difference between the average scores of the executive function of normal and ADHD children as well as average scores of the executive function of normal boys and ADHD children at the 0.01 level. In addition, there was a significant difference between the average scores of the executive function of normal girls and ADHD girls at the 0.05 level according to which null hypothesis is rejected. Therefore, ADHD children are of lower executive and cognitive function compared to normal children and have extensive cognitive deficits. Therefore, they require medications along with special training and rehabilitation.
The Acquaintance Level of Turkish Prospective Teachers with Qualified Works of Children’s Literature
Authors: Çer Erkan , Sahin Ertugrul
Published: June 2016

The aim of this cross-sectional study is investigate to what extent acquainted prospective Turkish teachers are with qualified works of children’s literature. A convenience sample of 146 university students studying at the Turkish teaching department at a university in the Central Black Sea Region completed a questionnaire to determine the qualified works of children’s literature about which the students knew. Firstly, books which were assessed as quality by students for primary and secondary school pupils were classified using frequencies and percentages. In the second stage of the analysis, appropriate books suiting the definition of quality books for children were selected according to Çer’s (2016a, 2016b) suggestions, and the foreknowledge levels of each student for quality books were determined. The Mann-Whitney U test and the Kruskal-Wallis H test were performed to examine gender and grade level differences in foreknowledge levels. Results of this study showed that the level of foreknowledge of Turkish prospective teachers about quality books for children for primary and secondary school students was quite low. Additionally, being female and grade level is associated with qualified works of children’s literature which the students knew. Such that, female prospective teachers significantly more acquainted with quality books for secondary school than males and the junior and senior students were significantly more acquainted with books for primary school than the freshmen and sophomore students. Senior students were also significantly more acquainted with books for secondary school than the freshmen, sophomore and junior students.
New and interesting lichen records from northeastern Poland
Authors: Kubiak Dariusz , Sucharzewska Ewa
Published: June 2016

Details are given of the occurrence of three rarely reported and poorly known lichen species from Poland area. Brief taxonomic, distributional, and ecological notes of Agonimia flabelliformis, Bacidia pycnidiata, and Vezdaea aestivalis have been provided. Agonimia flabelliformis have been reported for the first time from the northeastern part of Poland and B. pycnidiata from the northern part of the country. Vezdaea aestivalis has been rediscovered in northeastern Poland, nearly 150 years after its first and only recording in the region.
Miniestaquia de Grevillea robusta A. Cunn. a partir de propágulos juvenis.
Authors: Souza Junior Levi de , Quoirin Marguerite , Wendling Ivar
Published: June 2016

O presente estudo teve como objetivo avaliar a sobrevivência e a produtividade de minicepas no sistema de tubetes e o efeito do ácido indolbutírico (AIB) no enraizamento de miniestacas de Grevillea robusta. O experimento foi conduzido em Colombo, PR, com minicepas formadas partindo de mudas obtidas de sementes, as quais foram cultivadas no sistema de tubetes, durante o período de um ano. A sobrevivência das minicepas, após 15 coletas, foi de 100% com produtividade média de 1,7 miniestacas por minicepa e 4030 miniestacas por metro quadrado ao ano. As taxas médias de enraizamento foram 83, 79, 75 e 72% para os tratamentos com 0, 1000, 2000 e 4000 mg L-1 de AIB respectivamente, sendo os melhores níveis obtidos sem aplicação exógena de AIB. Com base nesses resultados, conclui-se que a miniestaquia de propágulos juvenis é uma opção para produção de mudas de Grevillea robusta durante o ano inteiro, sem a necessidade de aplicações de reguladores de crescimento, além de ser uma importante ferramenta para adaptação dos protocolos de propagação vegetativa em materiais adultos selecionados.