bluuebunny/crossref_metadata_2025 huggingface dataset:
RELATIONSHIP BETWEEN LANDCOVER PATTERN AND SURFACE NET RADIATION IN AN COASTAL CITY
Authors: Zhao X. , Liu L. , Liu X. , Zhao Y.
Published: June 2016

Abstract. Taking Xiamen city as the study area this research first retrieved surface net radiation using meteorological data and Landsat 5 TM images of the four seasons in the year 2009. Meanwhile the 65 different landscape metrics of each analysis unit were acquired using landscape analysis method. Then the most effective landscape metrics affecting surface net radiation were determined by correlation analysis, partial correlation analysis, stepwise regression method, etc. At both class and landscape levels, this paper comprehensively analyzed the temporal and spatial variations of the surface net radiation as well as the effects of land cover pattern on it in Xiamen from a multi-seasonal perspective. The results showed that the spatial composition of land cover pattern shows significant influence on surface net radiation while the spatial allocation of land cover pattern does not. The proportions of bare land and forest land are effective and important factors which affect the changes of surface net radiation all the year round. Moreover, the proportion of forest land is more capable for explaining surface net radiation than the proportion of bare land. So the proportion of forest land is the most important and continuously effective factor which affects and explains the cross-seasonal differences of surface net radiation. This study is helpful in exploring the formation and evolution mechanism of urban heat island. It also gave theoretical hints and realistic guidance for urban planning and sustainable development.
CHANGES IN SCATTERED GREENERY IN SELECTED AREA IN THE CZECH REPUBLIC FROM 1953 TO 2014
Authors: Ždímal V.
Published: June 2016

Abstract. The Land Cover of the Czech landscape could change several times. Reconstructing Land Cover and especially greenery in the past is important for today’s use of the landscape. Two periods were chosen to track changes in scattered greenery, the years 1953 and 2014. The source of information was an historical orthophotomap supplemented with a Military Topographic Map and an orthophotomap supplemented by terrain mapping. The software ArcMap and GuidosToolbox were used. The greenery was highlighted and manually converted to a vector format. The total area of the monitored territory is 2,190 hectares. In 1953, greenery took up 102 ha and 90 individual green areas were identified here. In 2014, greenery took up 222 ha and it was divided into 113 individual areas. In 1953 the perimeter of all green areas was 41,537 meters; in 2014 the perimeter of all green areas was 89,974 meters. There are two apparent trends here. The first is the simplification of shapes as a result of large-scale management; the second is the formation of a large length of linear greenery and small width with a large perimeter. The shape of the surface is linked to the area and perimeter. In 1953 this parameter was on average 1.87, and in 2014 the average value was 2.58. Comparing the results of the distance analysis of Label Objects using the GuidosToolbox software found that virtually all green areas were classified differently in 1953 and 2014. The results are completely different and further analysis makes no sense.
MAPPING OF CORAL REEF ENVIRONMENT IN THE ARABIAN GULF USING MULTISPECTRAL REMOTE SENSING
Authors: Ben-Romdhane H. , Marpu P. R. , Ghedira H. , Ouarda T. B. M. J.
Published: June 2016

Abstract. Coral reefs of the Arabian Gulf are subject to several pressures, thus requiring conservation actions. Well-designed conservation plans involve efficient mapping and monitoring systems. Satellite remote sensing is a cost-effective tool for seafloor mapping at large scales. Multispectral remote sensing of coastal habitats, like those of the Arabian Gulf, presents a special challenge due to their complexity and heterogeneity. The present study evaluates the potential of multispectral sensor DubaiSat-2 in mapping benthic communities of United Arab Emirates. We propose to use a spectral-spatial method that includes multilevel segmentation, nonlinear feature analysis and ensemble learning methods. Support Vector Machine (SVM) is used for comparison of classification performances. Comparative data were derived from the habitat maps published by the Environment Agency-Abu Dhabi. The spectral-spatial method produced 96.41% mapping accuracy. SVM classification is assessed to be 94.17% accurate. The adaptation of these methods can help achieving well-designed coastal management plans in the region.
MONITORING HIGH-FREQUENCY OCEAN SIGNALS USING LOW-COST GNSS/IMU BUOYS
Authors: Huang Yu-Lun , Kuo Chung-Yen , Shih Chiao-Hui , Lin Li-Ching , Chiang Kai-wei , Cheng Kai-Chien
Published: June 2016

Abstract. In oceans there are different ocean signals covering the multi-frequencies including tsunami, meteotsunami, storm surge, as sea level change, and currents. These signals have the direct and significant impact on the economy and life of human-beings. Therefore, measuring ocean signals accurately becomes more and more important and necessary. Nowadays, there are many techniques and methods commonly used for monitoring oceans, but each has its limitation. For example, tide gauges only measure sea level relative to benchmarks and are disturbed unevenly, and satellite altimeter measurements are not continuous and inaccurate near coastal oceans. In addition, high-frequency ocean signals such as tsunami and meteotsunami cannot be sufficiently detected by 6-minutes tide gauge measurements or 10-day sampled altimetry data. Moreover, traditional accelerometer buoy is heavy, expensive and the low-frequency noise caused by the instrument is unavoidable. In this study, a small, low-cost and self-assembly autonomous Inertial Measurement Unit (IMU) that independently collects continuous acceleration and angular velocity data is mounted on a GNSS buoy to provide the positions and tilts of the moving buoy. The main idea is to integrate the Differential GNSS (DGNSS) or Precise Point Positioning (PPP) solutions with IMU data, and then evaluate the performance by comparing with in situ tide gauges. The validation experiments conducted in the NCKU Tainan Hydraulics Laboratory showed that GNSS and IMU both can detect the simulated regular wave frequency and height, and the field experiments in the Anping Harbor, Tainan, Taiwan showed that the low-cost GNSS buoy has an excellent ability to observe significant wave heights in amplitude and frequency.
LARGE OIL SPILL CLASSIFICATION USING SAR IMAGES BASED ON SPATIAL HISTOGRAM
Authors: Schvartzman I. , Havivi S. , Maman S. , Rotman S. R. , Blumberg D. G.
Published: June 2016

Abstract. Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR) is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010). The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA) data.
CONTRIBUTION OF SATELLITE ALTIMETRY DATA IN GEOLOGICAL STRUCTURE RESEARCH IN THE SOUTH CHINA SEA
Authors: Tran Tuan Dung , Ho Thi Huong Mai
Published: June 2016

Abstract. The study area is bordered on the East China Sea, the Philippine Sea, and the Australian-Indo plate in the Northeast, in the East and in the South, respectively. It is a large area with the diversely complicated conditions of geological structure. In spite of over the past many years of investigation, marine geological structure in many places have remained poorly understood because of a thick seawater layer as well as of the sensitive conflicts among the countries in the region. In recent years, the satellite altimeter technology allows of enhancement the marine investigation in any area. The ocean surface height is measured by a very accurate radar altimeter mounted on a satellite. Then, that surface can be converted into marine gravity anomaly or bathymetry by using the mathematical model. It is the only way to achieve the data with a uniform resolution in acceptable time and cost. The satellite altimetry data and its variants are essential for understanding marine geological structure. They provide a reliable opportunity to geologists and geophysicists for studying the geological features beneath the ocean floor. Also satellite altimeter data is perfect for planning the more detailed shipboard surveys. Especially, it is more meaningful in the remote or sparsely surveyed regions. In this paper, the authors have effectively used the satellite altimetry and shipboard data in combination. Many geological features, such as seafloor spreading ridges, fault systems, volcanic chains as well as distribution of sedimentary basins are revealed through the 2D, 3D model methods of interpretation of satellite-shipboard-derived data and the others. These results are improved by existing boreholes and seismic data in the study area.
RANDOM FOREST CLASSIFICATION OF SEDIMENTS ON EXPOSED INTERTIDAL FLATS USING ALOS-2 QUAD-POLARIMETRIC SAR DATA
Authors: Wang W. , Yang X. , Liu G. , Zhou H. , Ma W. , Yu Y. , Li Z.
Published: June 2016

Abstract. Coastal zones are one of the world’s most densely populated areas and it is necessary to propose an accurate, cost effective, frequent, and synoptic method of monitoring these complex ecosystems. However, misclassification of sediments on exposed intertidal flats restricts the development of coastal zones surveillance. With the advent of SAR (Synthetic Aperture Radar) satellites, polarimetric SAR satellite imagery plays an increasingly important role in monitoring changes in coastal wetland. This research investigated the necessity of combining SAR polarimetric features with optical data, and their contribution in accurately sediment classification. Three experimental groups were set to make assessment of the most appropriate descriptors. (i) Several SAR polarimetric descriptors were extracted from scattering matrix using Cloude-Pottier, Freeman-Durden and Yamaguchi methods; (ii) Optical remote sensing (RS) data with R, G and B channels formed the second feature combinations; (iii) The chosen SAR and optical RS indicators were both added into classifier. Classification was carried out using Random Forest (RF) classifiers and a general result mapping of intertidal flats was generated. Experiments were implemented using ALOS-2 L-band satellite imagery and GF-1 optical multi-spectral data acquired in the same period. The weights of descriptors were evaluated by VI (RF Variable Importance). Results suggested that optical data source has few advantages on sediment classification, and even reduce the effect of SAR indicators. Polarimetric SAR feature sets show great potentials in intertidal flats classification and are promising in classifying mud flats, sand flats, bare farmland and tidal water.
A STUDY ON PRODUCING HIGHLY RELIABILE REFERENCE DATA SETS FOR GLOBAL LAND COVER VALIDATION
Authors: Soyama N. , Muramatsu K. , Daigo M. , Ochiai F. , Fujiwara N.
Published: June 2016

Abstract. Validating the accuracy of land cover products using a reliable reference dataset is an important task. A reliable reference dataset is produced with information derived from ground truth data. Recently, the amount of ground truth data derived from information collected by volunteers has been increasing globally. The acquisition of volunteer-based reference data demonstrates great potential. However information given by volunteers is limited useful vegetation information to produce a complete reference dataset based on the plant functional type (PFT) with five specialized forest classes. In this study, we examined the availability and applicability of FLUXNET information to produce reference data with higher levels of reliability. FLUXNET information was useful especially for forest classes for interpretation in comparison with the reference dataset using information given by volunteers.
AN APPLICATION OF CLOSE-UP PHOTOGRAMMETRY IN VITICULTURE
Authors: D'Urso Maria Grazia , Marino Costantino Luis
Published: June 2016

Abstract. Within the context of Geomatic-based Agriculture an application of close-up photogrammetry is illustrated with reference to precision farming. The application has been carried out in a particularly attractive archaeological site and concerns some viticulture species produced in situ by following a farming technique dated about two thousand years. Specifically we illustrate and comment the photogrammetric close-range acquisitions, carried out both outdoor and indoor, aimed at producing a digital botanic atlas that can adequately replace the traditional ones drawn by hand. High precision geometric measurements of vineyard leaves and grapes, are suitable indices of their growth rate and an objective estimate of the relevant repening degree.
ASSESSING THE IMPACTS OF FLOODING CAUSED BY EXTREME RAINFALL EVENTS THROUGH A COMBINED GEOSPATIAL AND NUMERICAL MODELING APPROACH
Authors: Santillan J. R. , Amora A. M. , Makinano-Santillan M. , Marqueso J. T. , Cutamora L. C. , Serviano J. L. , Makinano R. M.
Published: June 2016

Abstract. In this paper, we present a combined geospatial and two dimensional (2D) flood modeling approach to assess the impacts of flooding due to extreme rainfall events. We developed and implemented this approach to the Tago River Basin in the province of Surigao del Sur in Mindanao, Philippines, an area which suffered great damage due to flooding caused by Tropical Storms Lingling and Jangmi in the year 2014. The geospatial component of the approach involves extraction of several layers of information such as detailed topography/terrain, man-made features (buildings, roads, bridges) from 1-m spatial resolution LiDAR Digital Surface and Terrain Models (DTM/DSMs), and recent land-cover from Landsat 7 ETM+ and Landsat 8 OLI images. We then used these layers as inputs in developing a Hydrologic Engineering Center Hydrologic Modeling System (HEC HMS)-based hydrologic model, and a hydraulic model based on the 2D module of the latest version of HEC River Analysis System (RAS) to dynamically simulate and map the depth and extent of flooding due to extreme rainfall events. The extreme rainfall events used in the simulation represent 6 hypothetical rainfall events with return periods of 2, 5, 10, 25, 50, and 100 years. For each event, maximum flood depth maps were generated from the simulations, and these maps were further transformed into hazard maps by categorizing the flood depth into low, medium and high hazard levels. Using both the flood hazard maps and the layers of information extracted from remotely-sensed datasets in spatial overlay analysis, we were then able to estimate and assess the impacts of these flooding events to buildings, roads, bridges and landcover. Results of the assessments revealed increase in number of buildings, roads and bridges; and increase in areas of land-cover exposed to various flood hazards as rainfall events become more extreme. The wealth of information generated from the flood impact assessment using the approach can be very useful to the local government units and the concerned communities within Tago River Basin as an aid in determining in an advance manner all those infrastructures (buildings, roads and bridges) and land-cover that can be affected by different extreme rainfall event flood scenarios.
NEW APPROACH FOR SEGMENTATION AND EXTRACTION OF SINGLE TREE FROM POINT CLOUDS DATA AND AERIAL IMAGES
Authors: Homainejad A. S.
Published: June 2016

Abstract. This paper addresses a new approach for reconstructing a 3D model from single trees via Airborne Laser Scanners (ALS) data and aerial images. The approach detects and extracts single tree from ALS data and aerial images. The existing approaches are able to provide bulk segmentation from a group of trees; however, some methods focused on detection and extraction of a particular tree from ALS and images. Segmentation of a single tree within a group of trees is mostly a mission impossible since the detection of boundary lines between the trees is a tedious job and basically it is not feasible. In this approach an experimental formula based on the height of the trees was developed and applied in order to define the boundary lines between the trees. As a result, each single tree was segmented and extracted and later a 3D model was created. Extracted trees from this approach have a unique identification and attribute. The output has application in various fields of science and engineering such as forestry, urban planning, and agriculture. For example in forestry, the result can be used for study in ecologically diverse, biodiversity and ecosystem.
BIODIVERSITY MAPPING VIA NATURA 2000 CONSERVATION STATUS AND EBV ASSESSMENT USING AIRBORNE LASER SCANNING IN ALKALI GRASSLANDS
Authors: Zlinszky A. , Deák B. , Kania A. , Schroiff A. , Pfeifer N.
Published: June 2016

Abstract. Biodiversity is an ecological concept, which essentially involves a complex sum of several indicators. One widely accepted such set of indicators is prescribed for habitat conservation status assessment within Natura 2000, a continental-scale conservation programme of the European Union. Essential Biodiversity Variables are a set of indicators designed to be relevant for biodiversity and suitable for global-scale operational monitoring. Here we revisit a study of Natura 2000 conservation status mapping via airbone LIDAR that develops individual remote sensing-derived proxies for every parameter required by the Natura 2000 manual, from the perspective of developing regional-scale Essential Biodiversity Variables. Based on leaf-on and leaf-off point clouds (10 pt/m2) collected in an alkali grassland area, a set of data products were calculated at 0.5 ×0.5 m resolution. These represent various aspects of radiometric and geometric texture. A Random Forest machine learning classifier was developed to create fuzzy vegetation maps of classes of interest based on these data products. In the next step, either classification results or LIDAR data products were selected as proxies for individual Natura 2000 conservation status variables, and fine-tuned based on field references. These proxies showed adequate performance and were summarized to deliver Natura 2000 conservation status with 80% overall accuracy compared to field references. This study draws attention to the potential of LIDAR for regional-scale Essential Biodiversity variables, and also holds implications for global-scale mapping. These are (i) the use of sensor data products together with habitat-level classification, (ii) the utility of seasonal data, including for non-seasonal variables such as grassland canopy structure, and (iii) the potential of fuzzy mapping-derived class probabilities as proxies for species presence and absence.
IMPROVING GLOBALlAND30 ARTIFICIAL TYPE EXTRACTION ACCURACY IN LOW-DENSITY RESIDENTS
Authors: Hou Lili , Zhu Ling , Peng Shu , Xie Zhenlei , Chen Xu
Published: June 2016

Abstract. GlobalLand 30 is the first 30m resolution land cover product in the world. It covers the area within 80°N and 80°S. There are ten classes including artificial cover, water bodies, woodland, lawn, bare land, cultivated land, wetland, sea area, shrub and snow,. The TM imagery from Landsat is the main data source of GlobalLand 30. In the artificial surface type, one of the omission error happened on low-density residents’ part. In TM images, hash distribution is one of the typical characteristics of the low-density residents, and another one is there are a lot of cultivated lands surrounded the low-density residents. Thus made the low-density residents part being blurred with cultivated land. In order to solve this problem, nighttime light remote sensing image is used as a referenced data, and on the basis of NDBI, we add TM6 to calculate the amount of surface thermal radiation index TR-NDBI (Thermal Radiation Normalized Difference Building Index) to achieve the purpose of extracting low-density residents. The result shows that using TR-NDBI and the nighttime light remote sensing image are a feasible and effective method for extracting low-density residents’ areas.
MODELING THE DISTRIBUTION OF AFRICAN SAVANNA ELEPHANTS IN KRUGER NATIONAL PARK: AN APPLICATION OF MULTI-SCALE GLOBELAND30 DATA
Authors: Xu W. , Hays B. , Fayrer-Hosken R. , Presotto A.
Published: June 2016

Abstract. The ability of remote sensing to represent ecologically relevant features at multiple spatial scales makes it a powerful tool for studying wildlife distributions. Species of varying sizes perceive and interact with their environment at differing scales; therefore, it is important to consider the role of spatial resolution of remotely sensed data in the creation of distribution models. The release of the Globeland30 land cover classification in 2014, with its 30 m resolution, presents the opportunity to do precisely that. We created a series of Maximum Entropy distribution models for African savanna elephants (Loxodonta africana) using Globeland30 data analyzed at varying resolutions. We compared these with similarly re-sampled models created from the European Space Agency’s Global Land Cover Map (Globcover). These data, in combination with GIS layers of topography and distance to roads, human activity, and water, as well as elephant GPS collar data, were used with MaxEnt software to produce the final distribution models. The AUC (Area Under the Curve) scores indicated that the models created from 600 m data performed better than other spatial resolutions and that the Globeland30 models generally performed better than the Globcover models. Additionally, elevation and distance to rivers seemed to be the most important variables in our models. Our results demonstrate that Globeland30 is a valid alternative to the well-established Globcover for creating wildlife distribution models. It may even be superior for applications which require higher spatial resolution and less nuanced classifications.
A KNOWLEDGE-BASED APPROACH ON GLOBELAND30 INCREMENTAL UPDATING: A CASE STUDY OF BUILT-UP AREA
Authors: Zhang Jun , Wu Hao , Peng Shu
Published: June 2016

Abstract. Global land cover/land use product in multiple periods is pivotal to understand the complex drivers and mechanisms in global climate change, and to forecast future land use trends in sustainable development. GlobeLand30, as the world’s first high spatial resolution land cover product (83% accuracy), needs to be continually updated to meet various needs. However, many challenges - such as removing pseudo change to keep consistency of updating - remain unsolved. To deal with high temporal and spatial variability happened within built-up area class and between it and other classes, this paper presents an alternative approach that exploits domain knowledge and object-based change detection technique. The central premise of the approach is that one-class segmentation is first proceeded on both former image and current image. Then, segments of former image are labeled by using corresponding Globeland30 product. Segments of built-up area in current image are finally recognized through correlation which is established based on domain knowledge. Knowledge used in this study mainly includes area index, shape index, perimeter index, spectral similarity, 'from to' types and spatial relation. The proposed method and classification method were tested for their ability for built-up area updating in Shandong area. Results showed that the proposed method proved particularly effective for maintaining consistency of unchanged areas from former product to current one, and more than 80% changes could be identified correctly. The proposed method also provided a practical way for an economic and accurate updating of Globeland30 product.
USING AIRBORNE REMOTE SENSING TO INCREASE SITUATIONAL AWARENESS IN CIVIL PROTECTION AND HUMANITARIAN RELIEF – THE IMPORTANCE OF USER INVOLVEMENT
Authors: Römer H. , Kiefl R. , Henkel F. , Wenxi C. , Nippold R. , Kurz F. , Kippnich U.
Published: June 2016

Abstract. Enhancing situational awareness in real-time (RT) civil protection and emergency response scenarios requires the development of comprehensive monitoring concepts combining classical remote sensing disciplines with geospatial information science. In the VABENE++ project of the German Aerospace Center (DLR) monitoring tools are being developed by which innovative data acquisition approaches are combined with information extraction as well as the generation and dissemination of information products to a specific user. DLR’s 3K and 4k camera system which allow for a RT acquisition and pre-processing of high resolution aerial imagery are applied in two application examples conducted with end users: a civil protection exercise with humanitarian relief organisations and a large open-air music festival in cooperation with a festival organising company. This study discusses how airborne remote sensing can significantly contribute to both, situational assessment and awareness, focussing on the downstream processes required for extracting information from imagery and for visualising and disseminating imagery in combination with other geospatial information. Valuable user feedback and impetus for further developments has been obtained from both applications, referring to innovations in thematic image analysis (supporting festival site management) and product dissemination (editable web services). Thus, this study emphasises the important role of user involvement in application-related research, i.e. by aligning it closer to user’s requirements.
DEVELOPMENT OF TIME-SERIES HUMAN SETTLEMENT MAPPING SYSTEM USING HISTORICAL LANDSAT ARCHIVE
Authors: Miyazaki H. , Nagai M. , Shibasaki R.
Published: June 2016

Abstract. Methodology of automated human settlement mapping is highly needed for utilization of historical satellite data archives for urgent issues of urban growth in global scale, such as disaster risk management, public health, food security, and urban management. As development of global data with spatial resolution of 10-100 m was achieved by some initiatives using ASTER, Landsat, and TerraSAR-X, next goal has targeted to development of time-series data which can contribute to studies urban development with background context of socioeconomy, disaster risk management, public health, transport and other development issues. We developed an automated algorithm to detect human settlement by classification of built-up and non-built-up in time-series Landsat images. A machine learning algorithm, Local and Global Consistency (LLGC), was applied with improvements for remote sensing data. The algorithm enables to use MCD12Q1, a MODIS-based global land cover map with 500-m resolution, as training data so that any manual process is not required for preparation of training data. In addition, we designed the method to composite multiple results of LLGC into a single output to reduce uncertainty. The LLGC results has a confidence value ranging 0.0 to 1.0 representing probability of built-up and non-built-up. The median value of the confidence for a certain period around a target time was expected to be a robust output of confidence to identify built-up or non-built-up areas against uncertainties in satellite data quality, such as cloud and haze contamination. Four scenes of Landsat data for each target years, 1990, 2000, 2005, and 2010, were chosen among the Landsat archive data with cloud contamination less than 20%.We developed a system with the algorithms on the Data Integration and Analysis System (DIAS) in the University of Tokyo and processed 5200 scenes of Landsat data for cities with more than one million people worldwide.
DYNAMIC MONITORING OF SOIL AND WATER LOSSES USING REMOTE SENSING AND GIS TECHNIQUES: A CASE STUDY OF JIALING RIVER, YANGTZE RIVER, CHINA
Authors: Li C. , Zhu Y. J. , Li G. E. , Zhu Y. Q. , Li R. H. , Wang L. , Wu Y. J.
Published: June 2016

Abstract. Water and soil loss problems are serious in China, especially in the upper and middle reaches of big rivers. This paper dynamically observed water and soil loss in key control regions in Jialing River Basin. Based on remotely sensed images, the method used in this paper is a combination of field investigation and indoor artificial interpretation under the technologies of RS and GIS. The method was proven to be effective of improving the accuracy of interpreting. The result shows the land use types of the researched regions and how they changed among the previous years. Evaluation of water and soil conservation was made. This result can provide references for further policy-making and water and soil loss controlling.
EXAMINING URBAN EXPANSION USING MULTI-TEMPORAL LANDSAT IMAGERY: A CASE STUDY OF THE MONTREAL CENSUS METROPOLITAN AREA FROM 1975 TO 2015, CANADA
Authors: Ma Lingfei , Zhao He , Li Jonathan
Published: June 2016

Abstract. Urban expansion, particularly the movement of residential and commercial land use to sub-urban areas in metropolitan areas, has been considered as a significant signal of regional economic development. In 1970s, the economic centre of Canada moved from Montreal to Toronto. Since some previous research have been focused on the urbanization process in Greater Toronto Area (GTA), it is significant to conduct research in its counterpart. This study evaluates urban expansion process in Montréal census metropolitan area (CMA), Canada, between 1975 and 2015 using satellite images and socio-economic data. Spatial and temporal dynamic information of urbanization process was quantified using Landsat imagery, supervised classification algorithms and the post-classification change detection technique. Accuracy of the Landsat-derived land use classification map ranged from 80% to 97%. The results indicated that continuous growth of built-up areas in the CMA over the study period resulted in a decrease in the area of cultivated land and vegetation. The results showed that urban areas expanded 442 km2 both along major river systems and lakeshores, as well as expanded from urban centres to surrounded areas. The analysis revealed that urban expansion has been largely driven by population growth and economic development. Consequently, the urban expansion maps produced in this research can assist decision-makers to promote sustainable urban development, and forecast potential changes in urbanization growth patterns.
GEOSPATIAL INFORMATION FROM SATELLITE IMAGERY FOR GEOVISUALISATION OF SMART CITIES IN INDIA
Authors: Mohan M.
Published: June 2016

Abstract. In the recent past, there have been large emphasis on extraction of geospatial information from satellite imagery. The Geospatial information are being processed through geospatial technologies which are playing important roles in developing of smart cities, particularly in developing countries of the world like India. The study is based on the latest geospatial satellite imagery available for the multi-date, multi-stage, multi-sensor, and multi-resolution. In addition to this, the latest geospatial technologies have been used for digital image processing of remote sensing satellite imagery and the latest geographic information systems as 3-D GeoVisualisation, geospatial digital mapping and geospatial analysis for developing of smart cities in India. The Geospatial information obtained from RS and GPS systems have complex structure involving space, time and presentation. Such information helps in 3-Dimensional digital modelling for smart cities which involves of spatial and non-spatial information integration for geographic visualisation of smart cites in context to the real world. In other words, the geospatial database provides platform for the information visualisation which is also known as geovisualisation. So, as a result there have been an increasing research interest which are being directed to geospatial analysis, digital mapping, geovisualisation, monitoring and developing of smart cities using geospatial technologies. However, the present research has made an attempt for development of cities in real world scenario particulary to help local, regional and state level planners and policy makers to better understand and address issues attributed to cities using the geospatial information from satellite imagery for geovisualisation of Smart Cities in emerging and developing country, India.
Design, characterization, and modeling of microcirculation systems with integrated oxygenators
Authors: Busek Mathias , Gruenzner Stefan , Steege Tobias , Schmieder Florian , Klotzbach Udo , Sonntag Frank
Published: June 2016

Abstract. Here, we describe a microfluidic system for hypoxia assays on human cell culture models. These systems are developed to replace or reduce animal testing in biomedical basic research. The presented system uses a gas-permeable membrane as a gas–liquid interface and a micropump for media actuation to influence the oxygen content in two cell culture chambers. To apply well-defined hypoxic conditions to the cells, a good understanding of the mass transport phenomena is necessary. Therefore, a complete network model of the microfluidic system is presented. This model is validated by means of micro-particle image velocimetry (µPIV) and optical oxygen measurement with fluorescence lifetime detection. Finally, the impact of several process parameters, e.g., the gas permeability of the pump, is discussed using the developed model.
Charitable Trusts and Political Purposes: Sowing the Seeds of Change? Lessons from Australia.
Authors: Chevalier-Watts Juliet
Published: June 2016

This article examines the current absence of legal regulation of gendered hate speech in Australia. Drawing on contemporary examples, the article compares hate speech directed towards women as women with other forms of hate speech, in particular racial hate speech, which is currently the subject of legal regulation in all Australian jurisdictions. The various laws regulating hate speech in Australia, civil and criminal, are discussed. Possible reasons for the failure to recognise gendered hate speech are canvassed and recommendations made for legislative change to recognise the harm it causes.
The Challenges of Autonomous Motor Vehicles for Queensland Road and Criminal Laws
Authors: Tranter Kieran Mark
Published: June 2016

This article examines the challenges of autonomous motor vehicles for Queensland road and criminal laws. Autonomous vehicles refer to motor vehicles where driver decision making has been augmented or replaced by intelligent systems. Proponents of autonomous vehicles argue that they will virtually eliminate road accidents, boost productivity and provide significant environmental benefits. The key issue is that autonomous vehicles challenge the notion of human responsibility which lies at the core of Queensland’s road and criminal laws. The road rules are predicated on a driver in control of the vehicle, the intoxication regime is concerned with the person in charge of the vehicle and the dangerous driving offences require a person who operates a vehicle. Notwithstanding this challenge, it can be seen that much of Queensland’s law is adaptable to autonomous vehicles. However, there are some identifiable anomalies that require reform.
An Alternative Approach to the Treatment of Penalties and Fines in Bankruptcy
Authors: Sise Peter
Published: June 2016

Currently, penalties and fines are not provable in bankruptcy.  This article examines the policy behind this approach and its consequences.  It then suggests an alternative approach where penalties and fines are provable, but are subordinated to other unsecured debts and are not released upon the discharge of the bankrupt.  Although this approach is not perfect, it addresses some of the difficulties of the current approach and balances the goals of protecting the bankrupt from pressure by creditors during the term of their bankruptcy, deterring and punishing misconduct, and giving the bankrupt a ‘fresh start’ upon their discharge.
The Legal Assault on Australian Democracy
Authors: Williams George
Published: June 2016

Recent years have seen fierce public debate on whether Australia’s parliaments are passing laws that undermine fundamental democratic values, such as freedom of speech and freedom of association. Such debate has tended to focus on a few contentious laws, including s 18C of the Racial Discrimination Act 1975 (Cth), s 35P of the Australian Security Intelligence Organisation Act 1979 (Cth) and Queensland’s anti-bikie legislation. This article conducts a survey of the federal, state and territory statute books in order to determine whether such examples are isolated, or indicative of a broader trend. It identifies 350 instances of laws that arguably encroach upon rights and freedoms essential to the maintenance of a healthy democracy. Most of these laws have entered onto the statute book since September 2001. The article finds that the terrorist attacks of that month marked a watershed moment in the making of Australian laws, and that since that time parliamentarians have been less willing to exercise self-restraint by not passing laws that undermine Australia’s democratic system.
Reports from the 2015 American College of Rheumatology Congress
Authors: Avouac Jérôme , Tomcik Michal , Beyer Christian
Published: June 2016

Systemic sclerosis (SSc) was one of the major topics covered during the 2015 American College of Rheumatology meeting.

Selected abstracts related to basic research reported the identification of new relevant targets including interferon regulatory factor 7 (IRF7), long coding RNAs, C-terminal domain of endostatin, M2 macrophages and keratinocytes. Several new compounds, including abatacept, nintedanib and soluble guanylate cyclase stimulators, displayed potent antifibrotic effects in complementary animal models of experimental dermal fibrosis.

Clinical aspects of the disease were also largely covered, with a specific focus on cardiac biomarkers and the relationship between cancer and SSc. The results of several clinical trials were also presented, including the comparison between cyclophosphamide and mycophenolate mofetil in the scleroderma lung study-2 and the effects of riociguat in patients with pulmonary arterial hypertension associated with connective tissue diseases.
Achieving Sex-Representative International Court Benches
Authors: Grossman Nienke
Published: June 2016

Twenty-five years ago, in this Journal, Hilary Charlesworth, Christine Chinkin, and Shelley Wright argued that the structures of international law “privilege men.” As shown in Table 1, which summarizes data from a forthcoming article, on nine of twelve international courts of varied size, subject-matter jurisdiction, and global and regional membership, women made up 20 percent or less of the bench in mid 2015. On many of these courts, the percentage of women on the bench has stayed constant, vacillated, or even declined over time. Women made up a lower percentage of the bench in mid 2015 than in previous years on two-thirds of the courts surveyed.
The Ethics Inside the Monetary Circuit: How Bank’s Social Responsibility Affects Money Creation
Authors: Oliva Nadia , Pacella Andrea
Published: June 2016

The paper aims to introduce ethical remarks into the monetary circuit (or monetary theory of production)
approach in order to study the mechanism of money creation when banks discriminate production on an ethical
plane. By the micro-foundation of the banks’ and firms’ behaviour, it will be shown that the ethical
discrimination of firms by banks is implemented by the differentiation of the mark-ups on the loan rate and how
this discrimination leads the system to create different credit markets according to the capacity (or willingness)
of firms to satisfy (or not) the ethical claims of the banks.
The Experience and Practice of Social Support during Major Organizational Changes: The Case of the Bank Collapse in Iceland in 2008
Authors: Snorradóttir Asta , Rafnsdottir Gudbjorg Linda , Aust Birgit
Published: June 2016

This study explored how Icelandic bank employees perceived and practiced social support in the wake of the
economic crisis when the banks suddenly collapsed in 2008. Drawing on 20 interviews with bank employees, it
was found that during stressful situations, employees referred to social support as one of the most important
factors in overcoming the changes. The study points toward a complex picture of social support practices during organizational changes and underlines the importance of distinguishing between both nature and source of the social support in practice and in research.
A Comparative Study on Job Satisfaction between Registered Nurses and Other Qualified Healthcare Professionals
Authors: Parveen Musrrat , Maimani Khalid , Kassim Norizan M.
Published: June 2016

Introduction The concept of overall job satisfaction has recently received a lot of attention in the healthcare human resource management, particularly in Saudi Arabia. Saudi Arabia faces the biggest challenges in providing qualified healthcare workers and also local health care professionals, such as physicians, nurses and pharmacists. Job satisfaction/dissatisfaction in terms of salary package, personal growth and professional support may have resulted in high healthcare workers turnover rate within the healthcare system in Saudi Arabia.

Method For this study, a total of 400 self-administered questionnaires were conveniently distributed among the RNs and QHPs in both public and private hospitals in Jeddah, one of the major cities of Saudi Arabia.

Analysis Quantitative analysis was carried out on the data, which related to 400 healthcare professionals. This study used a-two way multivariate analysis of variance (MANOVA) to test the differences by using SPSS version 16.

Results Results suggested that QHPs were more contented and satisfied with their salary package as compared to RNs. However, both professions were dissatisfied with the personal growth, and professional support they received from their employers. Some implications of the findings for managers/administrators to practice are discussed.
Conclusion This study sheds some lights on the issues pertaining to the overall job satisfaction among the healthcare professionals in Saudi Arabia.
Understanding the Role of Consumer Factors and Store Factors in Private Label Purchase
Authors: S. Jayakrishnan , Chikhalkar Rekha D. , Chaudhuri Ranjan
Published: June 2016

Purpose: Indian retail sector is witnessing a steady growth of private labels or store brands in food category. The study primarily looks into understanding the consumer preference for private labels or store brands in food category and the role of consumer and store factors in store brand purchase in this category. Consumer responses are collected from the city of Trivandrum (India) using structured questionnaire. Five point Likert scale is used to measure the factors. Responses are collected from consumers at organized retail outlets and households. Structural equation model is used to understand the role of consumer and store factors in private label purchase. Factors like perceived quality, product familiarity, shelf space allocation and private label quality belief are found to have a significant role in determining the private label purchase in food category. n relationship among regions is very important. Finally, some policies about fiscal exnpenditure and economic development are proposed.
A Study on the Leadership Style and the Organizational Performance in Korea and USA
Authors: Lee Young Kwan , Deok Hee Cheon
Published: June 2016

This study aimed to suggest ways Korea’s top-class hotels can improve their global competitiveness, using as a model the developmental process of hotel leadership in the US. We conducted an expert opinion survey on hotel leaders in Korea and the US and explored the differences between their perceptions of emotional leadership and servant leadership and ways to improve organizational performance. We also conducted a quantitative study involving employees of Korea's top-class hotels to investigate the effect of emotional and servant leadership styles on job satisfaction, innovative behavior, and customer orientation. The results suggest that, to improve job satisfaction, respect for values and support for growth under servant leadership should be focused on and that innovative behavior is encouraged by respect for values and the formation of community under servant leadership. To enhance customer orientation, respect for values and support for growth should be focused on. Finally, job satisfaction and innovative behavior contribute directly to improving customer orientation.
Customer Clustering Using a Combination of Fuzzy C-Means and Genetic Algorithms
Authors: Ansari Azarnoush , Riasi Arash
Published: June 2016

This study intends to combine the fuzzy c-means clustering and genetic algorithms to cluster the customers of steel industry. The customers were divided into two clusters by using the variables of the LRFM (length, recency, frequency, monetary value) model. Results indicated that customers belonging to the first cluster had a higher length of the relationship, recency of trade, and frequency of trade but lower monetary value compared to the average values of these criteria for all customers. The results also showed that customers belonging to the second
cluster had a higher recency of trade and monetary value but lower length of the relationship and frequency of trade compared to the average values of these criteria for all customers. It was also found that the combined algorithm (i.e., fuzzy c-means clustering and genetic algorithm) used in this study had a lower mean squared error (MSE) compared to fuzzy c-means clustering.