bluuebunny/crossref_metadata_2025 huggingface dataset:
COSEISMIC DEFORMATION FIELD AND FAULT SLIP DISTRIBUTION OF THE 2015 CHILE Mw8.3 EARTHQUAKE
Authors: Qu Chunyan , Zuo Ronghu , Shan Xin Jian , Zhang Guohong , Zhang Yingfeng , Song Xiaogang
Published: August 2016

On September 16, 2015, a magnitude 8.3 earthquake struck west of Illapel, Chile. We analyzed Sentinel-1A/IW InSAR data on the descending track acquired before and after the Chile Mw8.3 earthquake of 16 September 2015. We found that the coseismic deformation field of this event consists of many semi circular fringes protruding to east in an approximately 300km long and 190km wide region. The maximum coseismic displacement is about 1.33m in LOS direction corresponding to subsidence or westward shift of the ground. We inverted the coseismic fault slip based on a small-dip single plane fault model in a homogeneous elastic half space. The inverted coseismic slip mainly concentrates at shallow depth above the hypocenter with a symmetry shape. The rupture length along strike is about 340 km with maximum slip of about 8.16m near the trench. The estimated moment is 3.126×1021 N.m (Mw8.27)，the maximum depth of coseismic slip near zero appears to 50km. We also analyzed the postseismic deformation fields using four interferograms with different time intervals. The results show that postseismic deformation occurred in a narrow area of approximately 65km wide with maximum slip 11cm, and its predominant motion changes from uplift to subsidence with time. that is to say, at first, the postseismic deformation direction is opposite to that of coseismic deformation, then it tends to be consistent with coseismic deformation.It maybe indicates the differences and changes in the velocity between the Nazca oceanic plate and the South American continental plate.
POLARIMETRIC SIGNATURES IDENTIFICATION FOR DIFFERENT FEATURES IN RADARSAT-2 POLSAR IMAGE: A CASE STUDY OF HALAYIB AREA, EGYPT
Authors: Nasr Ayman H. , Abdelhamid Hind Z.
Published: August 2016

In fully polarized SAR (PolSAR) data the returned signal from a target contains all polarizations. More information about this target may be inferred with respect to single-polarization. Distinct polarization separates targets due to its different backscattering responses. A Radarsat-2 PolSAR image acquired on December 2013 of part of Halayib area (Egypt) was used in this study. Polarimetric signatures for various features (Wadi deposits, Tonalite, Chlorite schist, and Radar penetrated areas) were derived and identified. Their Co-polarized and Cross-polarized signatures were generated, based on the calculation of the backscattered power at various ellipticity and orientation angles. Graphical 3D-representation of these features was provided and more details of their physical information are depicted according to their different polarization bases. The results illustrate that polarimetric signatures, obtained due to factors like surface roughness, dielectric constant and feature orientation, can be an effective representation for analyzing various features. The shape of the signature is significant and can also indicate the scattering mechanisms dominating the features response.
EVALUATION OF RELATIVE GEOMETRIC ACCURACY OF TERRASAR-X BY PIXEL MATCHING METHODOLOGY
Authors: Nonaka T. , Asaka T. , Iwashita K.
Published: August 2016

Recently, high-resolution commercial SAR satellites with several meters of resolutions are widely utilized for various applications and disaster monitoring is one of the commonly applied areas. The information about the flooding situation and ground displacement was rapidly announced to the public after the Great East Japan Earthquake 2011. One of the studies reported the displacement in Tohoku region by the pixel matching methodology using both pre- and post- event TerraSAR-X data, and the validated accuracy was about 30 cm at the GEONET reference points. In order to discuss the spatial distribution of the displacement, we need to evaluate the relative accuracy of the displacement in addition to the absolute accuracy. In the previous studies, our study team evaluated the absolute 2D geo-location accuracy of the TerraSAR-X ortho-rectified EEC product for both flat and mountain areas. Therefore, the purpose of the current study was to evaluate the spatial and temporal relative geo-location accuracies of the product by considering the displacement of the fixed point as the relative geo-location accuracy. Firstly, by utilizing TerraSAR-X StripMap dataset, the pixel matching method for estimating the displacement with sub-pixel level was developed. Secondly, the validity of the method was confirmed by comparing with GEONET data. We confirmed that the accuracy of the displacement for X and Y direction was in agreement with the previous studies. Subsequently, the methodology was applied to 20 pairs of data set for areas of Tokyo Ota-ku and Kawasaki-shi, and the displacement of each pair was evaluated. It was revealed that the time series displacement rate had the seasonal trend and seemed to be related to atmospheric delay.
DOES THE DATA RESOLUTION/ORIGIN MATTER? SATELLITE, AIRBORNE AND UAV IMAGERY TO TACKLE PLANT INVASIONS
Authors: Müllerová Jana , Brůna Josef , Dvořák Petr , Bartaloš Tomáš , Vítková Michaela
Published: August 2016

Invasive plant species represent a serious threat to biodiversity and landscape as well as human health and socio-economy. To successfully fight plant invasions, new methods enabling fast and efficient monitoring, such as remote sensing, are needed. In an ongoing project, optical remote sensing (RS) data of different origin (satellite, aerial and UAV), spectral (panchromatic, multispectral and color), spatial (very high to medium) and temporal resolution, and various technical approaches (object-, pixelbased and combined) are tested to choose the best strategies for monitoring of four invasive plant species (giant hogweed, black locust, tree of heaven and exotic knotweeds). In our study, we address trade-offs between spectral, spatial and temporal resolutions required for balance between the precision of detection and economic feasibility. For the best results, it is necessary to choose best combination of spatial and spectral resolution and phenological stage of the plant in focus. For species forming distinct inflorescences such as giant hogweed iterative semi-automated object-oriented approach was successfully applied even for low spectral resolution data (if pixel size was sufficient) whereas for lower spatial resolution satellite imagery or less distinct species with complicated architecture such as knotweed, combination of pixel and object based approaches was used. High accuracies achieved for very high resolution data indicate the possible application of described methodology for monitoring invasions and their long-term dynamics elsewhere, making management measures comparably precise, fast and efficient. This knowledge serves as a basis for prediction, monitoring and prioritization of management targets.
HARVESTING, INTEGRATING AND DISTRIBUTING LARGE OPEN GEOSPATIAL DATASETS USING FREE AND OPEN-SOURCE SOFTWARE
Authors: Oliveira Ricardo , Moreno Rafael
Published: August 2016

Federal, State and Local government agencies in the USA are investing heavily on the dissemination of Open Data sets produced by each of them. The main driver behind this thrust is to increase agencies’ transparency and accountability, as well as to improve citizens’ awareness. However, not all Open Data sets are easy to access and integrate with other Open Data sets available even from the same agency. The City and County of Denver Open Data Portal distributes several types of geospatial datasets, one of them is the city parcels information containing 224,256 records. Although this data layer contains many pieces of information it is incomplete for some custom purposes. Open-Source Software were used to first collect data from diverse City of Denver Open Data sets, then upload them to a repository in the Cloud where they were processed using a PostgreSQL installation on the Cloud and Python scripts. Our method was able to extract non-spatial information from a ‘not-ready-to-download’ source that could then be combined with the initial data set to enhance its potential use.
Development of Open source-based automatic shooting and processing UAV imagery for Orthoimage Using Smart Camera UAV
Authors: Park J. W. , Jeong H. H. , Kim J. S. , Choi C. U.
Published: August 2016

Recently, aerial photography with unmanned aerial vehicle (UAV) system uses UAV and remote controls through connections of ground control system using bandwidth of about 430 MHz radio Frequency (RF) modem. However, as mentioned earlier, existing method of using RF modem has limitations in long distance communication. The Smart Camera equipments’s LTE (long-term evolution), Bluetooth, and Wi-Fi to implement UAV that uses developed UAV communication module system carried out the close aerial photogrammetry with the automatic shooting. Automatic shooting system is an image capturing device for the drones in the area’s that needs image capturing and software for loading a smart camera and managing it. This system is composed of automatic shooting using the sensor of smart camera and shooting catalog management which manages filmed images and information. Processing UAV imagery module used Open Drone Map. This study examined the feasibility of using the Smart Camera as the payload for a photogrammetric UAV system. The open soure tools used for generating Android, OpenCV (Open Computer Vision), RTKLIB, Open Drone Map.
SUPPORTING MANAGEMENT OF EUROPEAN REFUGEE STREAMS BY EARTH OBSERVATION AND GEOINFORMATION
Authors: Komp K.-U. , Müterthies A.
Published: August 2016

The sharp increase in refugee numbers arriving in the European Union has recently caused major and manifold challenges for the member states and their administrative services. Location based situation reports and maps may support the refugee management from local to European level. The first support is mapping of the geographical distribution of migrating people which needs more or less real time data. The actual data sources are location related observations along the routes of refugees, actual satellite observations and data mining results. These tools and data are used to monitor spatial distributions as well as extrapolate the arrival of refugees for the subsequent weeks. The second support is the short term update of the location of initial registration facilities and first reception facilities, their capacities, and their occupancy. The third management level is the systematic inquiry for unoccupied housing facilities and for empty places within build-up areas. Geo-coded data sets of house numbers have to be cross-referenced with city maps and communal inhabitants address data. The legal aspects of data mining and secured access to personal data are strictly controlled by the administration allowing only limited access and distribution of data and results. However, the paper will not disclose scientific progress in Earth Observation and GIS, but will actually demonstrate an urgently needed new combination of existing methods to support actual needs. The societal benefits of EO/GIS are no longer just potential possibilities, but actual results in real political, administrative and humanitarian day to day reality.
MONITORING OF IN-FIELD VARIABILITY FOR SITE SPECIFIC CROP MANAGEMENT THROUGH OPEN GEOSPATIAL INFORMATION
Authors: Řezník T. , Lukas V. , Charvát K. , Charvát Jr. K. , Horáková Š. , Křivánek Z. , Herman L.
Published: August 2016

The agricultural sector is in a unique position due to its strategic importance around the world. It is crucial for both citizens (consumers) and the economy (both regional and global), which, ideally, should ensure that the whole sector is a network of interacting organisations. It is important to develop new tools, management methods, and applications to improve the management and logistic operations of agricultural producers (farms) and agricultural service providers. From a geospatial perspective, this involves identifying cost optimization pathways, reducing transport, reducing environmental loads, and improving the energy balance, while maintaining production levels, etc.

 This paper describes the benefits of, and open issues arising from, the development of the Open Farm Management Information System. Emphasis is placed on descriptions of available remote sensing and other geospatial data, and their harmonization, processing, and presentation to users. At the same time, the FOODIE platform also offers a novel approach of yield potential estimations. Validation for one farm demonstrated 70% successful rate when comparing yield results at a farm counting 1’284 hectares on one hand and results of a theoretical model of yield potential on the other hand. The presented Open Farm Management Information System has already been successfully registered under Phase 8 of the Global Earth Observation System of Systems (GEOSS) Architecture Implementation Pilot in order to support the wide variety of demands that are primarily aimed at agriculture and water pollution monitoring by means of remote sensing.
THE FRAMEWORK ON MULTI-SCALE LANDSLIDE HAZARD EVALUATION IN CHINA
Authors: Li W. Y. , Liu C. , Gao J.
Published: August 2016

Nowadays, Landslide has been one of the most frequent and seriously widespread natural hazards all over the world. How landslides can be monitored and predicted is an urgent research topic of the international landslide research community. Particularly, there is a lack of high quality and updated landslide risk maps and guidelines that can be employed to better mitigate and prevent landslide disasters in many emerging regions, including China. This paper considers national and regional scale, and introduces the framework on combining the empirical and physical models for landslide evaluation. Firstly, landslide susceptibility in national scale is mapped based on empirical model, and indicates the hot-spot areas. Secondly, the physically based model can indicate the process of slope instability in the hot-spot areas. The result proves that the framework is a systematic method on landslide hazard monitoring and early warning.
ASSESSMENT OF CLASSIFICATION ACCURACIES OF SENTINEL-2 AND LANDSAT-8 DATA FOR LAND COVER / USE MAPPING
Authors: Topaloğlu Raziye Hale , Sertel Elif , Musaoğlu Nebiye
Published: August 2016

This study aims to compare classification accuracies of land cover/use maps created from Sentinel-2 and Landsat-8 data. Istanbul metropolitan city of Turkey, with a population of around 14 million, having different landscape characteristics was selected as study area. Water, forest, agricultural areas, grasslands, transport network, urban, airport- industrial units and barren land- mine land cover/use classes adapted from CORINE nomenclature were used as main land cover/use classes to identify. To fulfil the aims of this research, recently acquired dated 08/02/2016 Sentinel-2 and dated 22/02/2016 Landsat-8 images of Istanbul were obtained and image pre-processing steps like atmospheric and geometric correction were employed. Both Sentinel-2 and Landsat-8 images were resampled to 30m pixel size after geometric correction and similar spectral bands for both satellites were selected to create a similar base for these multi-sensor data. Maximum Likelihood (MLC) and Support Vector Machine (SVM) supervised classification methods were applied to both data sets to accurately identify eight different land cover/ use classes. Error matrix was created using same reference points for Sentinel-2 and Landsat-8 classifications. After the classification accuracy, results were compared to find out the best approach to create current land cover/use map of the region. The results of MLC and SVM classification methods were compared for both images.
COSTAL BATHYMETRY ESTIMATION FROM MULTISPECTRAL IMAGE WITH BACK PROPAGATION NEURAL NETWORK
Authors: Huang S. Y. , Liu C. L. , Ren H.
Published: August 2016

Bathymetric data in coastal area are important for marine sciences, hydrological applications and even for transportation and military purposes. Compare to traditional sonar and recent airborne bathymetry LIDAR systems, optical satellite images can provide information to survey a large area with single or multiple satellite images efficiently and economically. And it is especially suitable for coastal area because the penetration of visible light in water merely reaches 30 meters. In this study, a three-layer back propagation neural network is proposed to estimate bathymetry. In the learning stage, some training samples with known depth are adopted to train the weights of the neural network until the stopping criterion is satisfied. The spectral information is sent to the input layer and fits the true water depth with the output. The depths of training samples are manually measured from stereo images of the submerged reefs after water refraction correction. In the testing stage, all non-land pixels are processed. The experiments show the mean square errors are less than 3 meters.
ASSESSING FLOOD IMPACTS IN RURAL COASTAL COMMUNITIES USING LIDAR
Authors: Johnson E. S.
Published: August 2016

Coastal communities are vulnerable to floods from storm events which are further exacerbated by storm surges. Additionally, coastal towns provide specific challenges during flood events as many coastal communities are peninsular and vulnerable to inundation of road access points. Publicly available lidar data has been used to model areas of inundation and resulting flood impacts on road networks. However, these models may overestimate areas that are inaccessible as they rely on publicly available Digital Terrain Models. Through incorporation of Digital Surface Models to estimate bridge height, a more accurate model of flood impacts on rural coastal residents can be estimated.
SHANGHAI SHORELINE EVOLUTION INTERPRETED FROM HISTORICAL ATLAS AND REMOTE SENSING IMAGERY OVER THE PAST 2,200 YEARS
Authors: Mi H. , Wang W. , Qiao G.
Published: August 2016

Shanghai, the axis of economic development in China and holding the most prosperous metropolis in the world, is located at Yangtze Estuary which is susceptible to shoreline changes affected by different factors, such as sediment supply and sea level changes, making it very important to study the shoreline changes over long time period. This paper presents the Shanghai shoreline evolution process from BC 221 up to 2015, by employing both the cartographic data (historical atlas) and the remote sensing images. A series of image processing techniques were applied to seamlessly register the historical atlas and satellite images to the same orthophoto base map, followed by the semi-automatic extraction of shoreline from images. Results show that since BC 221, the Shanghai shoreline has been witnessing distinct progradation, and the rate of shoreline advance varied in different areas. The average shoreline change in southern Yangtze Estuary was about 2,573 km2 (accretion) between BC 221 and 1948 with a 40 km progradation, while the shoreline in northern Hangzhou Bay kept relatively steady after 1671. Overall, 3,119 km2 of Shanghai area was added between BC 221 and 1948 with an average rate of 75 km2/50yr, and the addition went to 4,372 km2 in 2015. In this paper, the possible drives of the shoreline evolution was discussed. This study is important for understanding the coastal dynamics in Shanghai over a long time period for the management and development of coastal environments.
NEAR REAL-TIME DETERMINATION OF EARTHQUAKE SOURCE PARAMETERS FOR TSUNAMI EARLY WARNING FROM GEODETIC OBSERVATIONS
Authors: Manneela Sunanda , Srinivasa Kumar T. , Nayak Shailesh R.
Published: August 2016

Exemplifying the tsunami source immediately after an earthquake is the most critical component of tsunami early warning, as not every earthquake generates a tsunami. After a major under sea earthquake, it is very important to determine whether or not it has actually triggered the deadly wave. The near real-time observations from near field networks such as strong motion and Global Positioning System (GPS) allows rapid determination of fault geometry. Here we present a complete processing chain of Indian Tsunami Early Warning System (ITEWS), starting from acquisition of geodetic raw data, processing, inversion and simulating the situation as it would be at warning center during any major earthquake. We determine the earthquake moment magnitude and generate the centroid moment tensor solution using a novel approach which are the key elements for tsunami early warning. Though the well established seismic monitoring network, numerical modeling and dissemination system are currently capable to provide tsunami warnings to most of the countries in and around the Indian Ocean, the study highlights the critical role of geodetic observations in determination of tsunami source for high-quality forecasting.
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: August 2016

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.
WHIRL WIND DETECTION AND IDENTIFICATION IN INDONESIA UTILIZING SINGLE POLARIZATION DOPPLER WEATHER RADAR VOLUMETRIC DATA
Authors: Ali Abdullah , Hidayati Sabitul
Published: August 2016

Whirl wind occurrence frequency in Indonesia tends increasing in the last five years. Geospatial data from National Agency for Disaster Management (BNPB) recorded 72 cases with the impact of the two victims died, ten injured, 485 people were evacuated, and 1285 buildings were destroyed at period of January-June 2015. Based on the impact, early warning through remote sensing by using single polarization Doppler weather radar is need to be efforted. Whirl wind detection is done by identifying the characteristic pattern of the rotating convective cloud system by hook echo, analyzing the exsistance of vortex and rotation, and the strength of turbulence. The results show horizontal wind profile with a rotational pattern at CAPPI (V) and HWIND (V) by the altitude of 0.5 km, strong turbulence through product CAPPI (W) 0.5 km ranged of 1.75-2.05 ms-1, the vertical wind profile by product VVP (V) with a maximum value updraft reaches more than 20 knots at a 100-200 meters height, strong horizontal wind shear through HSHEAR (V) and CAPPI (HSHEAR) altitude of 0.5 km with a range of 6.23 to 10.12 ms-1/km. SWI and SSA show that the cloud base height is very low ranged from 200-600 meters with a maximum reflectivity reached 61.5 dBZ by top cloud height reached 14 km, while the product CAPPI (Z) 0.5 km and CMAX (Z) is very difficult to identify patterns hook echo. The results of remote sensing are very representative with the physical properties of whirl wind even whirl wind in a smaller scale.
STUDY OF AUTOMATIC IMAGE RECTIFICATION AND REGISTRATION OF SCANNED HISTORICAL AERIAL PHOTOGRAPHS
Authors: Chen H. R. , Tseng Y. H.
Published: August 2016

Historical aerial photographs directly provide good evidences of past times. The Research Center for Humanities and Social Sciences (RCHSS) of Taiwan Academia Sinica has collected and scanned numerous historical maps and aerial images of Taiwan and China. Some maps or images have been geo-referenced manually, but most of historical aerial images have not been registered since there are no GPS or IMU data for orientation assisting in the past. In our research, we developed an automatic process of matching historical aerial images by SIFT (Scale Invariant Feature Transform) for handling the great quantity of images by computer vision. SIFT is one of the most popular method of image feature extracting and matching. This algorithm extracts extreme values in scale space into invariant image features, which are robust to changing in rotation scale, noise, and illumination. We also use RANSAC (Random sample consensus) to remove outliers, and obtain good conjugated points between photographs. Finally, we manually add control points for registration through least square adjustment based on collinear equation. In the future, we can use image feature points of more photographs to build control image database. Every new image will be treated as query image. If feature points of query image match the features in database, it means that the query image probably is overlapped with control images.With the updating of database, more and more query image can be matched and aligned automatically. Other research about multi-time period environmental changes can be investigated with those geo-referenced temporal spatial data.
IMPROVING GLOBALlAND30 ARTIFICIAL TYPE EXTRACTION ACCURACY IN LOW-DENSITY RESIDENTS
Authors: Hou Lili , Zhu Ling , Peng Shu , Xie Zhenlei , Chen Xu
Published: August 2016

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.
HIGH RESOLUTION AEROSOL OPTICAL DEPTH MAPPING OF BEIJING USING LANSAT8 IMAGERY
Authors: Li Yan , Liu Yuanliang , Wu Jianliang
Published: August 2016

Aerosol Optical Depth (AOD) is one of the most important parameters in the atmospheric correction of remote sensing images. We present a new method of per pixel AOD retrieval using the imagery of Landsat8. It is based on Second Simulation of the Satellite Signal in the Solar Spectrum (6S). General dark target method takes dense vegetation pixels as dark targets and derives their 550nm AODs directly from the LUT, and interpolates the AODs of other pixels according to spatial neighbourhood using those of dark target pixels. This method will down estimate the AOD levels for urban areas. We propose an innovative method to retrieval the AODs using multiple temporal data. For a pixel which has nothing change between the associated time, there must exists an intersection of surface albedo. When there are enough data to find the intersection it ought to be a value that meet the error tolerance. In this paper, we present an example of using three temporal Landsat ETM+ image to retrieve AOD taking Beijing as the testing area. The result is compared to the commonly employed dark target algorithm to show the effectiveness of the methods.
PRAGMATICS DRIVEN LAND COVER SERVICE COMPOSITION UTILIZING BEHAVIOR-INTENTION MODEL
Authors: Wu Hao , Chen Jun , Xing Huaqiao , Li Songnian , Hu Juju
Published: August 2016

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.
Evaluating the Human Damage of Tsunami at Each Time Frame in Aggregate Units Based on GPS data
Authors: Ogawa Y. , Akiyama Y. , Kanasugi H. , Shibasaki R. , Kaneda H.
Published: August 2016

Assessments of the human damage caused by the tsunami are required in order to consider disaster prevention at such a regional level. Hence, there is an increasing need for the assessments of human damage caused by earthquakes. However, damage assessments in japan currently usually rely on static population distribution data, such as statistical night time population data obtained from national census surveys. Therefore, human damage estimation that take into consideration time frames have not been assessed yet. With these backgrounds, the objectives of this study are: to develop a method for estimating the population distribution of the for each time frame, based on location positioning data observed with mass GPS loggers of mobile phones, to use a evacuation and casualties models for evaluating human damage due to the tsunami, and evaluate each time frame by using the data developed in the first objective, and 3) to discuss the factors which cause the differences in human damage for each time frame. By visualizing the results, we clarified the differences in damage depending on time frame, day and area. As this study enables us to assess damage for any time frame in and high resolution, it will be useful to consider provision for various situations when an earthquake may hit, such as during commuting hours or working hours and week day or holiday.
THE BENEFITS AND CHALLENGES OF HAVING AN OPEN AND FREE BASIS SATELLITE DATA SHARING PLATFORM IN TURKEY: GEZGİN
Authors: Deveci Hüsne Seda , Koru Aziz , Sakarya Ufuk , Tevrizoğlu İsmail , Teke Mustafa , Küpçü Ramazan , Avenoğlu Bülent , Demirkesen Can , Gürbüz Sevgi Zübeyde , Öztoprak A. Feray , Açıkgöz İbrahim Serdar , Demirhan İsmail Hakkı , Kozal Ali Ömer , Efendioğlu Mehmet , Berke Erdinç , Şimşek F. Fehmi , Atıl İlkay , Kaya Derya , Uçmak Pınar , Ersöz Eda , Özen Hilal
Published: August 2016

Turkey is a county that experiences rapid socioeconomic development, which, in turn, leads to high urbanization rates due to migration of people from rural to urban areas, many large-scale development projects (e.g. highways, dams, housing and infrastructure), and environmental problems that adversely affect agriculture, such as soil erosion and deforestation. Furthermore, Turkey lies in a region prone to natural disasters, especially earthquakes, landslides, flooding and forest fires. Successfully overcoming these challenges requires continuous monitoring to enable rapid response as well as the development of effective socioeconomic policies. In this regard, space-based earth observation (EO) systems play a critical role in the rapid acquisiton and extraction of crucial information. The first launch of the first Turkish-designed satellite, RASAT, in 2011 led to the wide-spread exploitation of space-based resources by Turkish institutions through the dissemination of EO data on an open and free basis via the GEZGIN internet portal (http://www.gezgin.gov.tr). The push for data sharing was further instigated by the nationally funded project GEOPORTAL (“Satellite Image Processing and Geoportal Development Project”) and European Union FP7 project EOPOWER (“Earth Observation for Economic Empowerment”), which strove to create conditions for sustainable economic development through the increased use of Earth observation products and services for environmental applications. In this work, the technical challenges involving processing and preparing raw satellite data for dissemination as well as software design of the GEZGIN Portal will be presented.
EARTH OBSERVATION-SUPPORTED SERVICE PLATFORM FOR THE DEVELOPMENT AND PROVISION OF THEMATIC INFORMATION ON THE BUILT ENVIRONMENT – THE TEP-URBAN PROJECT
Authors: Esch T. , Asamer H. , Boettcher M. , Brito F. , Hirner A. , Marconcini M. , Mathot E. , Metz A. , Permana H. , Soukop T. , Stanek F. , Kuchar S. , Zeidler J. , Balhar J.
Published: August 2016

The Sentinel fleet will provide a so-far unique coverage with Earth observation data and therewith new opportunities for the implementation of methodologies to generate innovative geo-information products and services. It is here where the TEP Urban project is supposed to initiate a step change by providing an open and participatory platform based on modern ICT technologies and services that enables any interested user to easily exploit Earth observation data pools, in particular those of the Sentinel missions, and derive thematic information on the status and development of the built environment from these data. Key component of TEP Urban project is the implementation of a web-based platform employing distributed high-level computing infrastructures and providing key functionalities for i) high-performance access to satellite imagery and derived thematic data, ii) modular and generic state-of-the art pre-processing, analysis, and visualization techniques, iii) customized development and dissemination of algorithms, products and services, and iv) networking and communication. This contribution introduces the main facts about the TEP Urban project, including a description of the general objectives, the platform systems design and functionalities, and the preliminary portfolio products and services available at the TEP Urban platform.
RUNNING TO SAFETY: ANALYSIS OF DISASTER SUSCEPTIBILITY OF NEIGHBORHOODS AND PROXIMITY OF SAFETY FACILITIES IN SILAY CITY, PHILIPPINES
Authors: Patiño C. L. , Saripada N. A. , Olavides R. D. , Sinogaya J.
Published: August 2016

Going on foot is the most viable option when emergency responders fail to show up in disaster zones at the quickest and most reasonable time. In the Philippines, the efficacy of disaster management offices is hampered by factors such as, but not limited to, lack of equipment and personnel, distance, and/or poor road networks and traffic systems. In several instances, emergency response times exceed acceptable norms. This study explores the hazard susceptibility, particularly to fire, flood, and landslides, of neighborhoods vis-à-vis their proximity to safety facilities in Silay City, Philippines. Imbang River exposes communities in the city to flooding while the mountainous terrain makes the city landslide prone. Building extraction was done to get the possible human settlements in the city. The building structures were extracted through image processing using a ruleset-based approach in the process of segmentation and classification of LiDAR derivatives and ortho-photos. Neighborhoods were then identified whether they have low to high susceptibility to disaster risks in terms of floods and landslides based on the hazards maps obtained from the Philippines' Mines and Geosciences Bureau (MGB). Service area analyses were performed to determine the safety facilities available to different neighborhoods at varying running times. Locations which are inaccessible or are difficult to run to because of distance and corresponding hazards were determined. Recommendations are given in the form of infrastructure installation, relocation of facilities, safety equipment and vehicle procurement, and policy changes for specific areas in Silay City.
LANDSLIDES IDENTIFICATION USING AIRBORNE LASER SCANNING DATA DERIVED TOPOGRAPHIC TERRAIN ATTRIBUTES AND SUPPORT VECTOR MACHINE CLASSIFICATION
Authors: Pawłuszek Kamila , Borkowski Andrzej
Published: August 2016

Since the availability of high-resolution Airborne Laser Scanning (ALS) data, substantial progress in geomorphological research, especially in landslide analysis, has been carried out. First and second order derivatives of Digital Terrain Model (DTM) have become a popular and powerful tool in landslide inventory mapping. Nevertheless, an automatic landslide mapping based on sophisticated classifiers including Support Vector Machine (SVM), Artificial Neural Network or Random Forests is often computationally time consuming. The objective of this research is to deeply explore topographic information provided by ALS data and overcome computational time limitation. For this reason, an extended set of topographic features and the Principal Component Analysis (PCA) were used to reduce redundant information. The proposed novel approach was tested on a susceptible area affected by more than 50 landslides located on Rożnów Lake in Carpathian Mountains, Poland. The initial seven PCA components with 90% of the total variability in the original topographic attributes were used for SVM classification. Comparing results with landslide inventory map, the average user’s accuracy (UA), producer’s accuracy (PA), and overall accuracy (OA) were calculated for two models according to the classification results. Thereby, for the PCA-feature-reduced model UA, PA, and OA were found to be 72%, 76%, and 72%, respectively. Similarly, UA, PA, and OA in the non-reduced original topographic model, was 74%, 77% and 74%, respectively. Using the initial seven PCA components instead of the twenty original topographic attributes does not significantly change identification accuracy but reduce computational time.
EXTRACTION OF FLOODED AREAS DUE THE 2015 KANTO-TOHOKU HEAVY RAINFALL IN JAPAN USING PALSAR-2 IMAGES
Authors: Yamazaki F. , Liu W.
Published: August 2016

Triggered by two typhoons, heavy rainfall hit Kanto and Tohoku regions of Japan from September 9 to 11, 2015. Increased river water by the continuous rainfall overflowed and destroyed several river banks and caused damaging floods in wide areas. PALSAR-2 onboard ALOS-2 satellite carried out emergency observation for the impacted areas during and after the heavy rainfall. In this study, two pre-event and four co- and post-event PALSAR-2 images were used to extract the inundation area in Joso city, Ibaraki prefecture. First, using the pre-event SAR intensity image and a detailed topographic map, the backscattering coefficient of river water was investigated. Then the flooded areas were extracted by a common threshold value of backscatter for water bodies in the six temporal images. The colour composite of the sigma naught values was also made to visualize pixels that had been converted from ground to water. Finally, the extracted results were compared with those from the visual interpretation of aerial photographs and field survey reports. This comparison revealed that the accuracy of the flood extraction was fairly good for agricultural lands and non-urban land uses. But for built-up urban areas, it was not easy to extract water body since radar illumination did to reach the ground (water) surface.
3D VISUALIZATION OF VOLCANIC ASH DISPERSION PREDICTION WITH SPATIAL INFORMATION OPEN PLATFORM IN KOREA
Authors: Youn J. , Kim T.
Published: August 2016

Visualization of disaster dispersion prediction enables decision makers and civilian to prepare disaster and to reduce the damage by showing the realistic simulation results. With advances of GIS technology and the theory of volcanic disaster prediction algorithm, the predicted disaster dispersions are displayed in spatial information. However, most of volcanic ash dispersion predictions are displayed in 2D. 2D visualization has a limitation to understand the realistic dispersion prediction since its height could be presented only by colour. Especially for volcanic ash, 3D visualization of dispersion prediction is essential since it could bring out big aircraft accident. In this paper, we deals with 3D visualization techniques of volcanic ash dispersion prediction with spatial information open platform in Korea. First, time-series volcanic ash 3D position and concentrations are calculated with WRF (Weather Research and Forecasting) model and Modified Fall3D algorithm. For 3D visualization, we propose three techniques; those are 'Cube in the air', 'Cube in the cube', and 'Semi-transparent plane in the air' methods. In the 'Cube in the Air', which locates the semitransparent cubes having different color depends on its particle concentration. Big cube is not realistic when it is zoomed. Therefore, cube is divided into small cube with Octree algorithm. That is 'Cube in the Cube' algorithm. For more realistic visualization, we apply 'Semi-transparent Volcanic Ash Plane' which shows the ash as fog. The results are displayed in the 'V-world' which is a spatial information open platform implemented by Korean government. Proposed techniques were adopted in Volcanic Disaster Response System implemented by Korean Ministry of Public Safety and Security.
EXTENDING LKN CLIMATE REGIONALIZATION WITH SPATIAL REGULARIZATION: AN APPLICATION TO EPIDEMIOLOGICAL RESEARCH
Authors: Liss Alexander , Gel Yulia R. , Kulinkina Alexandra , Naumova Elena N.
Published: August 2016

Regional climate is a critical factor in public health research, adaptation studies, climate change burden analysis, and decision support frameworks. Existing climate regionalization schemes are not well suited for these tasks as they rarely take population density into account. In this work, we are extending our recently developed method for automated climate regionalization (LKN-method) to incorporate the spatial features of target population. The LKN method consists of the data limiting step (L-step) to reduce dimensionality by applying principal component analysis, a classification step (K-step) to produce hierarchical candidate regions using k-means unsupervised classification algorithm, and a nomination step (N-step) to determine the number of candidate climate regions using cluster validity indexes. LKN method uses a comprehensive set of multiple satellite data streams, arranged as time series, and allows us to define homogeneous climate regions. The proposed approach extends the LKN method to include regularization terms reflecting the spatial distribution of target population. Such tailoring allows us to determine the optimal number and spatial distribution of climate regions and thus, to ensure more uniform population coverage across selected climate categories. We demonstrate how the extended LKN method produces climate regionalization can be better tailored to epidemiological research in the context of decision support framework.
LINKING SATELLITE REMOTE SENSING BASED ENVIRONMENTAL PREDICTORS TO DISEASE: AN APPLICATION TO THE SPATIOTEMPORAL MODELLING OF SCHISTOSOMIASIS IN GHANA
Authors: Wrable M. , Liss A. , Kulinkina A. , Koch M. , Biritwum N. K. , Ofosu A. , Kosinski K. C. , Gute D. M. , Naumova E. N.
Published: August 2016

90% of the worldwide schistosomiasis burden falls on sub-Saharan Africa. Control efforts are often based on infrequent, small-scale health surveys, which are expensive and logistically difficult to conduct. Use of satellite imagery to predictively model infectious disease transmission has great potential for public health applications. Transmission of schistosomiasis requires specific environmental conditions to sustain freshwater snails, however has unknown seasonality, and is difficult to study due to a long lag between infection and clinical symptoms. To overcome this, we employed a comprehensive 8-year time-series built from remote sensing feeds. The purely environmental predictor variables: accumulated precipitation, land surface temperature, vegetative growth indices, and climate zones created from a novel climate regionalization technique, were regressed against 8 years of national surveillance data in Ghana. All data were aggregated temporally into monthly observations, and spatially at the level of administrative districts. The result of an initial mixed effects model had 41% explained variance overall. Stratification by climate zone brought the R2 as high as 50% for major zones and as high as 59% for minor zones. This can lead to a predictive risk model used to develop a decision support framework to design treatment schemes and direct scarce resources to areas with the highest risk of infection. This framework can be applied to diseases sensitive to climate or to locations where remote sensing would be better suited than health surveys.
STOCHASTIC COLOURED PETRINET BASED HEALTHCARE INFRASTRUCTURE INTERDEPENDENCY MODEL
Authors: Nukavarapu Nivedita , Durbha Surya
Published: August 2016

The Healthcare Critical Infrastructure (HCI) protects all sectors of the society from hazards such as terrorism, infectious disease outbreaks, and natural disasters. HCI plays a significant role in response and recovery across all other sectors in the event of a natural or manmade disaster. However, for its continuity of operations and service delivery HCI is dependent on other interdependent Critical Infrastructures (CI) such as Communications, Electric Supply, Emergency Services, Transportation Systems, and Water Supply System. During a mass casualty due to disasters such as floods, a major challenge that arises for the HCI is to respond to the crisis in a timely manner in an uncertain and variable environment. To address this issue the HCI should be disaster prepared, by fully understanding the complexities and interdependencies that exist in a hospital, emergency department or emergency response event. Modelling and simulation of a disaster scenario with these complexities would help in training and providing an opportunity for all the stakeholders to work together in a coordinated response to a disaster. The paper would present interdependencies related to HCI based on Stochastic Coloured Petri Nets (SCPN) modelling and simulation approach, given a flood scenario as the disaster which would disrupt the infrastructure nodes. The entire model would be integrated with Geographic information based decision support system to visualize the dynamic behaviour of the interdependency of the Healthcare and related CI network in a geographically based environment.