bluuebunny/crossref_metadata_2025 huggingface dataset:
Building the COllaborative Carbon Column Observing Network
(COCCON): Long term stability and ensemble performance of the
EM27/SUN Fourier transform spectrometer
Authors: Frey Matthias , Sha Mahesh Kumar , Hase Frank , Kiel Matthäus , Blumenstock Thomas , Harig Roland , Surawicz Gregor , Deutscher Nicholas M. , Shiomi Kei , Franklin Jonathan , Bösch Hartmut , Chen Jia , Grutter Michel , Ohyama Hirofumi , Sun Youwen , Butz André , Mengistu Tsidu Gizaw , Ene Dragos , Wunch Debra , Cao Zhensong , Garcia Omaira , Ramonet Michel , Vogel Felix , Orphal Johannes
Published: June 2018

Abstract. In a 3.5 year long study, the long term performance of a mobile Bruker EM27/SUN spectrometer, used for greenhouse gases observations, is checked with respect to a co-located reference Bruker IFS 125HR spectrometer, which is part of the Total Carbon Column Observing Network (TCCON). We find that the EM27/SUN is stable on timescales of several years, qualifying it as an useful supplement for the existing TCCON network in remote areas. For achieving consistent performance, such an extension requires careful testing of any spectrometers involved by application of common quality assurance measures. One major aim of the COllaborative Carbon Column Observing Network (COCCON) infrastructure is to provide these services to all EM27/SUN operators. In the framework of COCCON development, the performance of an ensemble of 30 EM27/SUN spectrometers was tested and found to be very uniform, enhanced by the centralized inspection performed at the Karlsruhe Institute of Technology prior to deployment. Taking into account measured instrumental line shape parameters for each spectrometer, the resulting average bias across the ensemble in XCO2 is 0.20 ppm, while it is 0.8 ppb for XCH4. As indicated by the executed long-term study on one device presented here, the remaining empirical calibration factor deduced for each individual instrument can be assumed constant over time. Therefore the application of these empirical factors is expected to further improve the EM27/SUN network conformity beyond the raw residual bias reported above.
Reduced Carbon Cycle Resilience across the Palaeocene-Eocene Thermal Maximum
Authors: Armstrong McKay David I. , Lenton Timothy M.
Published: June 2018

Abstract. Several past episodes of rapid carbon cycle and climate change are hypothesised to be the result of the Earth system reaching a tipping point beyond which an abrupt transition to a new state occurs. At the Palaeocene-Eocene Thermal Maximum (PETM) ~ 56 Ma, and at subsequent hyperthermal events, hypothesised tipping points involve the abrupt transfer of carbon from surface reservoirs to the atmosphere. Theory suggests that tipping points in complex dynamical systems should be preceded by critical slowing down of their dynamics, including increasing temporal autocorrelation and variability. However, reliably detecting these indicators in palaeorecords is challenging, with issues of data quality, false positives, and parameter selection potentially affecting reliability. Here we show that in a sufficiently long, high-resolution palaeorecord there is consistent evidence of destabilisation of the carbon cycle in the ~ 1.5 My prior to the PETM, elevated carbon cycle and climate instability following both the PETM and Eocene Thermal Maximum 2 (ETM2), and differing carbon cycle dynamics preceding the PETM and ETM2. Our results indicate a loss of resilience (weakened stabilising negative feedbacks and greater sensitivity to small shocks) in the carbon cycle before the PETM, and in the carbon-climate system following it. This pre-PETM carbon cycle destabilisation may reflect gradual forcing by the contemporaneous North Atlantic Volcanic Province eruptions. Our results are consistent with but cannot prove the existence of a tipping point for abrupt carbon release, e.g. from methane hydrate or terrestrial organic carbon reservoirs, whereas we find no support for a tipping point in deep ocean temperature.
Cluster-based analysis of multi-model climate ensembles
Authors: Hyde Richard , Hossaini Ryan , Leeson Amber A.
Published: June 2018

Abstract. Clustering – the automated grouping of similar data – can
provide powerful and unique insight into large and complex data sets, in a
fast and computationally efficient manner. While clustering has been used in
a variety of fields (from medical image processing to economics), its
application within atmospheric science has been fairly limited to date, and
the potential benefits of the application of advanced clustering techniques
to climate data (both model output and observations) has yet to be fully
realised. In this paper, we explore the specific application of clustering to
a multi-model climate ensemble. We hypothesise that clustering techniques can
provide (a) a flexible, data-driven method of testing model–observation
agreement and (b) a mechanism with which to identify model development
priorities. We focus our analysis on chemistry–climate model (CCM) output of
tropospheric ozone – an important greenhouse gas – from the recent
Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP).
Tropospheric column ozone from the ACCMIP ensemble was clustered using the
Data Density based Clustering (DDC) algorithm. We find that a multi-model
mean (MMM) calculated using members of the most-populous cluster identified
at each location offers a reduction of up to ∼ 20 % in the global
absolute mean bias between the MMM and an observed satellite-based
tropospheric ozone climatology, with respect to a simple, all-model MMM. On a
spatial basis, the bias is reduced at ∼ 62 % of all locations, with
the largest bias reductions occurring in the Northern Hemisphere – where
ozone concentrations are relatively large. However, the bias is unchanged at
9 % of all locations and increases at 29 %, particularly in the
Southern Hemisphere. The latter demonstrates that although cluster-based
subsampling acts to remove outlier model data, such data may in fact be
closer to observed values in some locations. We further demonstrate that
clustering can provide a viable and useful framework in which to assess and
visualise model spread, offering insight into geographical areas of agreement
among models and a measure of diversity across an ensemble. Finally, we
discuss caveats of the clustering techniques and note that while we have
focused on tropospheric ozone, the principles underlying the cluster-based
MMMs are applicable to other prognostic variables from climate models.
INTEGRATED IMAGING APPROACHES SUPPORTING THE EXCAVATION ACTIVITIES. MULTI-SCALE GEOSPATIAL DOCUMENTATION IN HIERAPOLIS (TK)
Authors: Spanò A. , Chiabrando F. , Sammartano G. , Teppati Losè L.
Published: May 2018

Abstract. The paper focuses on the exploration of the suitability and the discretization of applicability issues about advanced surveying integrated techniques, mainly based on image-based approaches compared and integrated to range-based ones that have been developed with the use of the cutting-edge solutions tested on field. The investigated techniques integrate both technological devices for 3D data acquisition and thus editing and management systems to handle metric models and multi-dimensional data in a geospatial perspective, in order to innovate and speed up the extraction of information during the archaeological excavation activities. These factors, have been experienced in the outstanding site of the Hierapolis of Phrygia ancient city (Turkey), downstream the 2017 surveying missions, in order to produce high-scale metric deliverables in terms of high-detailed Digital Surface Models (DSM), 3D continuous surface models and high-resolution orthoimages products. In particular, the potentialities in the use of UAV platforms for low altitude acquisitions in aerial photogrammetric approach, together with terrestrial panoramic acquisitions (Trimble V10 imaging rover), have been investigated with a comparison toward consolidated Terrestrial Laser Scanning (TLS) measurements. One of the main purposes of the paper is to evaluate the results offered by the technologies used independently and using integrated approaches. A section of the study in fact, is specifically dedicated to experimenting the union of different sensor dense clouds: both dense clouds derived from UAV have been integrated with terrestrial Lidar clouds, to evaluate their fusion. Different test cases have been considered, representing typical situations that can be encountered in archaeological sites.
FOREST COVER CLASSIFICATION USING GEOSPATIAL MULTIMODAL DATA
Authors: Suzuki K. , Rin U. , Maeda Y. , Takeda H.
Published: May 2018

Abstract. To address climate change, accurate and automated forest cover monitoring is crucial. In this study, we propose a Convolutional Neural Network (CNN) which mimics professional interpreters’ manual techniques. Using simultaneously acquired airborne images and LiDAR data, we attempt to reproduce the 3D knowledge of tree shape, which interpreters potentially make use of. Geospatial features which support interpretation are also used as inputs to the CNN. Inspired by the interpreters’ techniques, we propose a unified approach that integrates these datasets in a shallow layer in the CNN network. With the proposed CNN, we show that the multi-modal CNN works robustly, which gets more than 80 % user’s accuracy. We also show that the 3D multi-modal approach is especially suited for deciduous trees thanks to the ability of capturing 3D shapes.
SPECTRAL AND 3D CULTURAL HERITAGE DOCUMENTATION USING A MODIFIED CAMERA
Authors: Webb E. K. , Robson S. , MacDonald L. , Garside D. , Evans R.
Published: May 2018

Abstract. Spectral and 3D imaging techniques are used for museum imaging and cultural heritage documentation providing complementary information to aid in documenting the condition, informing the care, and increasing our understanding of objects. Specialised devices for spectral and 3D imaging may not be accessible for many heritage institutions, due to cost and complexity, and the modification of a consumer digital camera presents the potential of an accessible scientific tool for 2D and 3D spectral imaging. Consumer digital cameras are optimised for visible light, colour photography, but the underlying sensor is inherently sensitive to near ultraviolet, visible, and near infrared radiation. This research presents the characterisation of a modified camera to investigate the impact of the modification on the spectroradiometric and geometric image quality with the intention of the device being used as a scientific tool for cultural heritage documentation. The characterisation includes the assessment of 2D image quality looking at visual noise, sharpness, and sampling efficiency using the target and software associated with the Federal Agencies Digitization Guidelines Initiative. Results suggest that these modifications give rise to discrepancies in computed surface geometries of the order of ± 0.1 mm for small to medium sized objects used in the study and recorded in the round (maximum dimension 20 cm). Measuring the spectral response quantifies the modified camera as a scientific device for more accurate measurements and provides indications of wavelengths that could improve documentation based on sensitivity. The modification of a consumer digital camera provides a less expensive, high-resolution option for 2D and 3D spectral imaging.
EXTRACTION OF BUILDING ROOF EDGES FROM LIDAR DATA TO OPTIMIZE THE DIGITAL SURFACE MODEL FOR TRUE ORTHOPHOTO GENERATION
Authors: Widyaningrum E. , Lindenbergh R. C. , Gorte B. G. H. , Zhou K.
Published: May 2018

Abstract. Various kinds of urban applications require true orthophotos. True orthophoto generation requires a DSM (Digital Surface Model) to project the photo orthogonally and minimize geometric distortion due to topographic variance. DSMs are often generated from airborne laser scan data. In urban scenes, DSM data may fail to deliver sharp and straight building roof edges. This will affect the quality of the resulting orthophotos. Therefore, it is necessary to incorporate good quality building outlines as breaklines during DSM interpolation. This study proposes a data-driven approach to construct building roof outlines from LiDAR point clouds by a workflow consisting of the following steps: given roof segments, roof boundary points are extracted using a concave hull algorithm. Straight edges may be difficult to find in complex roof configurations. Therefore, two ingredients are combined. First, RanSAC corner point preselection, and second, DBSCAN-based clustering of edge points. The method is demonstrated on an area of ±1.2 km2 containing 42 buildings of different characteristics. A quality assessment shows that the proposed method is able to deliver 92 % of building lines with acceptable geometric accuracy in comparison to a building line in the base map.
A FRAMEWORK FOR ARCHITECTURAL HERITAGE HBIM SEMANTIZATION AND DEVELOPMENT
Authors: Brusaporci S. , Maiezza P. , Tata A.
Published: May 2018

Abstract. Despite the recognized advantages of the use of BIM in the field of architecture and engineering, the extension of this procedure to the architectural heritage is neither immediate nor critical. The uniqueness and irregularity of historical architecture, on the one hand, and the great quantity of information necessary for the knowledge of architectural heritage, on the other, require appropriate reflections. The aim of this paper is to define a general framework for the use of BIM procedures for architectural heritage. The proposed methodology consists of three different Level of Development (LoD), depending on the characteristics of the building and the objectives of the study: a simplified model with a low geometric accuracy and a minimum quantity of information (LoD 200); a model nearer to the reality but, however, with a high deviation between virtual and real model (LoD 300); a detailed BIM model that reproduce as much as possible the geometric irregularities of the building and is enriched by the maximum quantity of information available (LoD 400).
EVALUATION OF PHOTOGRAMMETRIC BLOCK ORIENTATION USING QUALITY DESCRIPTORS FROM STATISTICALLY FILTERED TIE POINTS
Authors: Calantropio A. , Deseilligny M. P. , Rinaudo F. , Rupnik E.
Published: May 2018

Abstract. Due to the increasing number of low-cost sensors, widely accessible on the market, and because of the supposed granted correctness of the semi-automatic workflow for 3D reconstruction, highly implemented in the recent commercial software, more and more users operate nowadays without following the rigorousness of classical photogrammetric methods. This behaviour often naively leads to 3D products that lacks metric quality assessment. This paper proposes and analyses an approach that gives the users the possibility to preserve the trustworthiness of the metric information inherent in the 3D model, without sacrificing the automation offered by modern photogrammetry software. At the beginning, the importance of Data Quality Assessment is outlined, together with some recall of photogrammetry best practices. With the purpose of guiding the user through a correct pipeline for a certified 3D model reconstruction, an operative workflow is proposed, focusing on the first part of the object reconstruction steps (tie-points extraction, camera calibration, and relative orientation). A new GUI (Graphical User Interface) developed for the open source MicMac suite is then presented, and a sample dataset is used for the evaluation of the photogrammetric block orientation using statistically obtained quality descriptors. The results and the future directions are then presented and discussed.
POINT CLOUD AND DIGITAL SURFACE MODEL GENERATION FROM HIGH RESOLUTION MULTIPLE VIEW STEREO SATELLITE IMAGERY
Authors: Gong K. , Fritsch D.
Published: May 2018

Abstract. Nowadays, multiple-view stereo satellite imagery has become a valuable data source for digital surface model generation and 3D reconstruction. In 2016, a well-organized multiple view stereo publicly benchmark for commercial satellite imagery has been released by the John Hopkins University Applied Physics Laboratory, USA. This benchmark motivates us to explore the method that can generate accurate digital surface models from a large number of high resolution satellite images. In this paper, we propose a pipeline for processing the benchmark data to digital surface models. As a pre-procedure, we filter all the possible image pairs according to the incidence angle and capture date. With the selected image pairs, the relative bias-compensated model is applied for relative orientation. After the epipolar image pairs’ generation, dense image matching and triangulation, the 3D point clouds and DSMs are acquired. The DSMs are aligned to a quasi-ground plane by the relative bias-compensated model. We apply the median filter to generate the fused point cloud and DSM. By comparing with the reference LiDAR DSM, the accuracy, the completeness and the robustness are evaluated. The results show, that the point cloud reconstructs the surface with small structures and the fused DSM generated by our pipeline is accurate and robust.
SPHERICAL IMAGES FOR CULTURAL HERITAGE: SURVEY AND DOCUMENTATION WITH THE NIKON KM360
Authors: Gottardi C. , Guerra F.
Published: May 2018

Abstract. The work presented here focuses on the analysis of the potential of spherical images acquired with specific cameras for documentation and three-dimensional reconstruction of Cultural Heritage. Nowadays, thanks to the introduction of cameras able to generate panoramic images automatically, without the requirement of a stitching software to join together different photos, spherical images allow the documentation of spaces in an extremely fast and efficient way. In this particular case, the Nikon Key Mission 360 spherical camera was tested on the Tolentini’s cloister, which used to be part of the convent of the close church and now location of the Iuav University of Venice. The aim of the research is based on testing the acquisition of spherical images with the KM360 and comparing the obtained photogrammetric models with data acquired from a laser scanning survey in order to test the metric accuracy and the level of detail achievable with this particular camera. This work is part of a wider research project that the Photogrammetry Laboratory of the Iuav University of Venice has been dealing with in the last few months; the final aim of this research project will be not only the comparison between 3D models obtained from spherical images and laser scanning survey’s techniques, but also the examination of their reliability and accuracy with respect to the previous methods of generating spherical panoramas. At the end of the research work, we would like to obtain an operational procedure for spherical cameras applied to metric survey and documentation of Cultural Heritage.
RAPID OBJECT DETECTION SYSTEMS, UTILISING DEEP LEARNING AND UNMANNED AERIAL SYSTEMS (UAS) FOR CIVIL ENGINEERING APPLICATIONS
Authors: Griffiths D. , Boehm J.
Published: May 2018

Abstract. With deep learning approaches now out-performing traditional image processing techniques for image understanding, this paper accesses the potential of rapid generation of Convolutional Neural Networks (CNNs) for applied engineering purposes. Three CNNs are trained on 275 UAS-derived and freely available online images for object detection of 3m2 segments of railway track. These includes two models based on the Faster RCNN object detection algorithm (Resnet and Incpetion-Resnet) as well as the novel onestage Focal Loss network architecture (Retinanet). Model performance was assessed with respect to three accuracy metrics. The first two consisted of Intersection over Union (IoU) with thresholds 0.5 and 0.1. The last assesses accuracy based on the proportion of track covered by object detection proposals against total track length. In under six hours of training (and two hours of manual labelling) the models detected 91.3 %, 83.1 % and 75.6 % of track in the 500 test images acquired from the UAS survey Retinanet, Resnet and Inception-Resnet respectively. We then discuss the potential for such applications of such systems within the engineering field for a range of scenarios.
DETERMINING GEOMETRIC PARAMETERS OF AGRICULTURAL TREES FROM LASER SCANNING DATA OBTAINED WITH UNMANNED AERIAL VEHICLE
Authors: Hadas E. , Jozkow G. , Walicka A. , Borkowski A.
Published: May 2018

Abstract. The estimation of dendrometric parameters has become an important issue for agriculture planning and for the efficient management of orchards. Airborne Laser Scanning (ALS) data is widely used in forestry and many algorithms for automatic estimation of dendrometric parameters of individual forest trees were developed. Unfortunately, due to significant differences between forest and fruit trees, some contradictions exist against adopting the achievements of forestry science to agricultural studies indiscriminately. In this study we present the methodology to identify individual trees in apple orchard and estimate heights of individual trees, using high-density LiDAR data (3200 points/m2) obtained with Unmanned Aerial Vehicle (UAV) equipped with Velodyne HDL32-E sensor. The processing strategy combines the alpha-shape algorithm, principal component analysis (PCA) and detection of local minima. The alpha-shape algorithm is used to separate tree rows. In order to separate trees in a single row, we detect local minima on the canopy profile and slice polygons from alpha-shape results. We successfully separated 92 % of trees in the test area. 6 % of trees in orchard were not separated from each other and 2 % were sliced into two polygons. The RMSE of tree heights determined from the point clouds compared to field measurements was equal to 0.09 m, and the correlation coefficient was equal to 0.96. The results confirm the usefulness of LiDAR data from UAV platform in orchard inventory.
WATCHING GRASS GROW- A PILOT STUDY ON THE SUITABILITY OF PHOTOGRAMMETRIC TECHNIQUES FOR QUANTIFYING CHANGE IN ABOVEGROUND BIOMASS IN GRASSLAND EXPERIMENTS
Authors: Kröhnert M. , Anderson R. , Bumberger J. , Dietrich P. , Harpole W. S. , Maas H.-G.
Published: May 2018

Abstract. Grassland ecology experiments in remote locations requiring quantitative analysis of the biomass in defined plots are becoming increasingly widespread, but are still limited by manual sampling methodologies. To provide a cost-effective automated solution for biomass determination, several photogrammetric techniques are examined to generate 3D point cloud representations of plots as a basis, to estimate aboveground biomass on grassland plots, which is a key ecosystem variable used in many experiments. Methods investigated include Structure from Motion (SfM) techniques for camera pose estimation with posterior dense matching as well as the usage of a Time of Flight (TOF) 3D camera, a laser light sheet triangulation system and a coded light projection system. In this context, plants of small scales (herbage) and medium scales are observed. In the first pilot study presented here, the best results are obtained by applying dense matching after SfM, ideal for integration into distributed experiment networks.
EVALUATION OF DEEP LEARNING BASED STEREO MATCHING METHODS: FROM GROUND TO AERIAL IMAGES
Authors: Liu J. , Ji S. , Zhang C. , Qin Z.
Published: May 2018

Abstract. Dense stereo matching has been extensively studied in photogrammetry and computer vision. In this paper we evaluate the application of deep learning based stereo methods, which were raised from 2016 and rapidly spread, on aerial stereos other than ground images that are commonly used in computer vision community. Two popular methods are evaluated. One learns matching cost with a convolutional neural network (known as MC-CNN); the other produces a disparity map in an end-to-end manner by utilizing both geometry and context (known as GC-net). First, we evaluate the performance of the deep learning based methods for aerial stereo images by a direct model reuse. The models pre-trained on KITTI 2012, KITTI 2015 and Driving datasets separately, are directly applied to three aerial datasets. We also give the results of direct training on target aerial datasets. Second, the deep learning based methods are compared to the classic stereo matching method, Semi-Global Matching(SGM), and a photogrammetric software, SURE, on the same aerial datasets. Third, transfer learning strategy is introduced to aerial image matching based on the assumption of a few target samples available for model fine tuning. It experimentally proved that the conventional methods and the deep learning based methods performed similarly, and the latter had greater potential to be explored.
AUTOMATIC RAIL EXTRACTION AND CELARANCE CHECK WITH A POINT CLOUD CAPTURED BY MLS IN A RAILWAY
Authors: Niina Y. , Honma R. , Honma Y. , Kondo K. , Tsuji K. , Hiramatsu T. , Oketani E.
Published: May 2018

Abstract. Recently, MLS (Mobile Laser Scanning) has been successfully used in a road maintenance. In this paper, we present the application of MLS for the inspection of clearance along railway tracks of West Japan Railway Company. Point clouds around the track are captured by MLS mounted on a bogie and rail position can be determined by matching the shape of the ideal rail head with respect to the point cloud by ICP algorithm. A clearance check is executed automatically with virtual clearance model laid along the extracted rail. As a result of evaluation, the accuracy of extracting rail positions is less than 3 mm. With respect to the automatic clearance check, the objects inside the clearance and the ones related to a contact line is successfully detected by visual confirmation.
USE OF FISHEYE PARROT BEBOP 2 IMAGES FOR 3D MODELLING USING COMMERCIAL PHOTOGRAMMETRIC SOFTWARE
Authors: Pagliari D. , Pinto L.
Published: May 2018

Abstract. Fisheye camera installed on-board mass market UAS are becoming very popular and it is more and more frequent the use of such platforms for photogrammetric purposes. The interest of wide-angles images for 3D modelling is confirmed by the introduction of fisheye models in several commercial software packages. The paper exploits the different mathematical models implemented in the most famous commercial photogrammetric software packages, highlighting the different processing pipelines and analysing the achievable results in terms of checkpoint residuals, as well as the quality of the delivered 3D point clouds. A two-step approach based on the creation of undistorted images has been tested too. An experimental test has been carried out using a Parrot Bebop 2 UAS by performing a flight over an historical complex located near Piacenza (Northern Italy), which is characterized by the simultaneous presence of horizontal, vertical and oblique surfaces. Different flight configurations have been tested to evaluate the potentiality and possible drawbacks of the previously mentioned UAS platform. Results confirmed that the fisheye images acquired with the Parrot Bebop 2 are suitable for 3D modelling, ensuring accuracies of the photogrammetric blocks of the order of the GSD (about 0.05 m normal to the optic axis in case of a flight height equal to 35 m). The generated point clouds have been compared to a reference scan, acquired by means of a MS60 MultiStation, resulting in differences below 0.05 in all directions.
DEEP LEARNING AND IMAGE PROCESSING FOR AUTOMATED CRACK DETECTION AND DEFECT MEASUREMENT IN UNDERGROUND STRUCTURES
Authors: Panella F. , Boehm J. , Loo Y. , Kaushik A. , Gonzalez D.
Published: May 2018

Abstract. This work presents the combination of Deep-Learning (DL) and image processing to produce an automated cracks recognition and defect measurement tool for civil structures. The authors focus on tunnel civil structures and survey and have developed an end to end tool for asset management of underground structures. In order to maintain the serviceability of tunnels, regular inspection is needed to assess their structural status. The traditional method of carrying out the survey is the visual inspection: simple, but slow and relatively expensive and the quality of the output depends on the ability and experience of the engineer as well as on the total workload (stress and tiredness may influence the ability to observe and record information). As a result of these issues, in the last decade there is the desire to automate the monitoring using new methods of inspection. The present paper has the goal of combining DL with traditional image processing to create a tool able to detect, locate and measure the structural defect.
EFFECT OF THE TRAINING SET CONFIGURATION ON SENTINEL-2-BASED URBAN LOCAL CLIMATE ZONE CLASSIFICATION
Authors: Qiu C. P. , Schmitt M. , Ghamisi P. , Zhu X. X.
Published: May 2018

Abstract. As any supervised classification procedure, also Local Climate Zone (LCZ) mapping requires reliable reference data. These are usually created manually and inevitably include label noise, caused by the complexity of the LCZ class scheme as well as variations in cultural and physical environmental factors. This study aims at evaluating the impact of the training set configuration, i.e. training sample number and imbalance, on the performance of Canonical Correlation Forests (CCFs) for a classification of the 11 urban LCZ classes. Experiments are carried out based on globally available Sentinel-2 imagery. Besides multi-spectral observations, different index measures extracted from the images as well as the Global Urban Footprint (GUF) and Open Street Map (OSM) layers are fed into the CCFs classifier. The results show that different LCZs favor different configurations in terms of training sample number and balance. Based on the findings, majority voting of different predictions from different configurations is proposed and performed. This way, a significant accuracy improvement can be achieved.
DTM GENERATION THROUGH UAV SURVEY WITH A FISHEYE CAMERA ON A VINEYARD
Authors: Ronchetti G. , Pagliari D. , Sona G.
Published: May 2018

Abstract. Precision agriculture recommends a sustainable employment of nutrients and water, according to the site-specific crop requirements. In this context, the knowledge of soil characteristics allows to appropriately manage resources. Even the topography can influence the spatial distribution of the water on a field. This work focuses on the production of high-resolution Digital Terrain Model (DTM) in agriculture by photogrammetric processing fisheye images, acquired with very light Unmanned Aerial Vehicle (UAV). Particular attention is given to the data processing procedures and to the assessment of the quality of the results, considering the peculiarity of the acquired images. An experimental test has been carried out on a vineyard located in Monzambano, Northern Italy, through photogrammetric survey with Parrot Bebop 2 UAV. It has been realized at the end of the vegetation season, to investigate the ground without any impediment due to the presence of leaves or branches. In addition, the survey has been used for evaluating the performance of Bebop fisheye camera in viticulture. Different flight strategies have been tested, together with different Ground Control Points (GCPs) and Check Points (CPs) configurations and software packages. The computed DTMs have been compared with a reference model obtained through Kriging interpolation of GNSS-RTK measurements. Residuals on CPs are of the order of 0.06 m, for all the considered scenarios, that for agricultural applications is by far sufficient. The photogrammetric DTMs show a good agreement with the reference one.
Modelling study of transformations of the exchange flows along the Strait of Gibraltar
Authors: Sanchez-Roman Antonio , Jorda Gabriel , Sannino Gianmaria , Gomis Damia
Published: June 2018

Abstract. Vertical transfers of heat, salt and mass between the inflowing and outflowing layers at the Strait of Gibraltar are explored basing on the outputs of a three-dimensional, fully non-linear numerical model. The model covers the entire Mediterranean basin and has a very high spatial resolution around the Strait (1/200°). Another distinctive feature of the model is that it includes a realistic barotropic tidal forcing (diurnal and semidiurnal), in addition to atmospheric pressure and heat and water surface fluxes. The results show a significant transformation of the properties of the inflowing and outflowing water masses along their path through the Strait. This transformation is mainly induced by the recirculation of water, and therefore of heat and salt, between the inflowing and outflowing layers. The underlying process seems to be the hydraulic control acting at the Espartel section, Camarinal Sill and Tarifa Narrows, which limits the amount of water than can cross the sections and forces a vertical recirculation. This results in a complex spatio-temporal pattern of vertical transfers, with the sign of the net vertical transfer being opposite in each side of Camarinal Sill. Conversely, the mixing seems to have little influence on the heat and salt exchanged between layers (∼ 2–10 % of advected heat/salt). Therefore, the main point of our work is that most of the transformation of water properties along the Strait is induced by the vertical advection of heat and salt and not by vertical mixing. A simple relationship between the net flux and the vertical transfers of water, heat and salt is also proposed. This relationship could be used for the fine tuning of coarse resolution model parameterizations in the Strait.
Phosphorus transport in lateral subsurface flow at forested hillslopes
Authors: Sohrt Jakob , Puhlmann Heike , Weiler Markus
Published: June 2018

Abstract. This study is concerned with the transport of Phosphorus (P) with lateral subsurface flow in the organic layer and topsoil of three forested headwater sites in Germany. Sampling frequency was set proportional to the incident flow rate in high temporal resolution. With this approach we want to investigate intra-event dynamics of P transport in lateral subsurface flow to establish initial process understanding about this potentially relevant pathway of P loss in forested hillslopes. With the organic layer being an important transfer site in the P cycle of temperate forests, availability and transportability of P in short timescales may reveal details about the overall balance of P in theses ecosystems. Our results demonstrate that P concentrations in lateral flow are highly variable within and in between distinct flow events as well as among our study sites. To determine possible controls of the P transport we constructed multiple linear models of the P concentration in lateral flow as a function of site specific environmental datasets. Site affiliation was responsible for more than half of total explained variability regarding P concentration in lateral flow, followed by flow rate, electric conductivity of subsurface lateral flow
"Dactylopius opuntiae" vs. "Opuntia Ficus-indica" en España: análisis espacio-temporal y repercusiones paisajísticas a través de los medios de comunicación on-line
Authors: Serrano-Montes José Luis , Olmedo-Cobo José Antonio , Gómez-Zotano José , Martínez-Ibarra Emilio
Published: May 2018

La creciente introducción de especies exóticas invasoras representa un importante factor de transformación ecológica, paisajística y social, siendo especialmente significativo el efecto de ciertos invertebrados fitófagos sobre la vegetación. En esta investigación se realiza un análisis de la distribución geográfica y de las repercusiones paisajísticas de la cochinilla silvestre (Dactylopius opuntiae) que está afectando a las chumberas (Opuntia ficus-indica) en España. Se utilizan los medios de comunicación online como fuente de información. Los resultados muestran, por primera vez, el alcance socio-espacial de este insecto y ponen de manifiesto la disociación existente entre la gestión efectuada por las administraciones públicas y las demandas ciudadanas.
TERRA VERSUS TERRITÓRIO: PENSAR CONFLITOS SOBRE TERRITORIALIDADES QUILOMBOLAS A PARTIR DA REALIDADE KALUNGA - DOI: http://dx.doi.org/10.5216/rfd.v41i2.47611
Authors: Oliveira Daniel Gonçalves de , Tárrega Maria Cristina Vidotte Blanco
Published: June 2018

Resumo: No contexto de uma agrariedade ampliada, em que se busca superar os limites do direito e do estado fundados no capitalismo, com reflexões socioambientais includentes de comunidades tradicionais, propõe-se no presente artigo, a análise jurídica dos direitos territoriais quilombolas e da questão terra propriedade individual versus espaço comunal, tendo por referência a Comunidade Kalunga. A questão centra-se em manter territorialidades pelo preservar da propriedade comum em desfavor da propriedade privada com titulação individual, problema que aparece no debate em várias comunidades quilombolas. O texto traz uma reflexão crítica do direito como instrumento de dominação e está estruturado em três partes: síntese histórica da Comunidade Kalunga e da gênese do conflito interno para organizar as posses e estabelecimentos territoriais; legislação acerca dos direitos territoriais quilombolas; análise a partir de categorias teóricas bourdieusianas da reprodução social, da violência simbólica e do direito, e de recortes teóricos de autores brasileiros. A ordem jurídica brasileira, tanto da perspectiva constitucional como da legislação infraconstitucional mostram-se ineficientes para dar conta das questões territoriais quilombolas.Abstract: In the context of an expanded agrarian system, which seeks to overcome the limits of the right and the state based on capitalism, with social-environmental reflections that include traditional communities, it is proposed in this article, the legal analysis of territorial rights quilombolas and land ownership individual versus communal space, with reference to the Kalunga Community. The issue focuses on maintaining territoriality by preserving common property in detriment of private ownership with individual titling, a problem that appears in the debate in several quilombola communities. The text brings a critical reflection of law as an instrument of domination and is structured in three parts: historical synthesis of the Kalunga Community and the genesis of the internal conflict to organize the territorial possessions and establishments; quilombola territorial rights legislation; analysis based on theoretical and bourdieusian categories of social reproduction, symbolic violence and law, and theoretical cut-outs of Brazilian authors. The Brazilian legal order, both from the constitutional perspective and from the infraconstitutional legislation, are inefficient to deal with quilombola territorial issues.
PRELÚDIOS DE UM CONSTITUCIONALISMO POPULAR E LATINO-AMERICANO NO BRASIL? PARTICIPAÇÃO DEMOCRÁTICA PÓS-88 E QUEDA DO DECRETO LEI 8.243/2014 - DOI: http://dx.doi.org/10.5216/rfd.v41i2.47930
Authors: Fonseca Faller Maria Helena , Kozicki Katya
Published: June 2018

Resumo: Este artigo pretende avaliar a proposta do constitucionalismo latino-americano e do constitucionalismo popular como possibilidade de se repensar as democracias constitucionais contemporâneas, fundamentadas na presença da cidadania na definição da política e da Constituição. A partir disso, analisa em que medida a democracia brasileira pós- 88 obteve resultados positivos no que se refere a participação popular na vida política e na construção dos direitos constitucionais, verificando qual contexto permitiu a derrubada do Decreto-Lei 8.243/2014. Identifica, por fim, os limites institucionais existentes à participação do cidadão na política, sem deixar de perceber prelúdios de uma potencialidade democrática ainda a ser experimentada.  Abstract: This article intends to evaluate the Latin-American and Popular constitutionalism proposals as possible ways to rethink contemporary forms of constitutional democracy based on the fundamental principle of citizen participation in the construction of Politics and Constitutional laws.  From this, it analyses the extent to which the Brazilian democracy pos-1988 generated positive outcomes in terms of popular participation in its political life and in the establishment of constitutional rights, considering the context that led to the overturn of the Executive order n. 8,243/2014. At last, it identifies existing institutional limitations to citizen participation in politics, while considering the preludes of a democratic potential yet to be experienced.
High-Performance Human Resource Practices and Team Job Satisfaction: Moderating Role of Team Citizenship Behaviors
Authors: Misra Kaumudi
Published: June 2018

Strategic human resource management literature has highlighted the role of high performance work systems as a set of workplace practices that enhance employee productivity and organizational performance. While the high performance literature has been around for over two decades now, research in this area has been staggered, and inconclusive about the organizational variables that comprise high performance work practices, as well as the effects of these practices on organizational outcomes - especially attitudinal employee outcomes such as job satisfaction and commitment. By creating an environment of empowerment and teamwork, high performance work practices motivate employees to perform better.  One of the ways in which these workplace practices achieve higher performance is by eliciting discretionary, or extra-role behaviors, from employees. Using foundational research from the high performance paradigm, this paper examines the effects of team-level strategic HR practices on job satisfaction. Analyses of data collected from 138 frontline teams in US Midwestern hospitals, show that while self-managed work teams and team communication result in higher job satisfaction for members, this effect is mitigated when team members display organizational citizenship behaviors. Theoretical and practical implications of finds are discussed.
Diversified Network Effects on Innovation Performance in Tanzania: Innovation Strategy in Service Firms
Authors: Pacho Frida Thomas
Published: May 2018

The study examined the issue of innovation with a focus on innovative diversified network in Tanzania service firms. The study aim was to assess the effect of diversified network which regarded as innovation strategy in firm’s innovation performance. By empirically tested network variables named collaboration, information exploration and exploitation and technology acquisition. The regression results indicated information exploration and exploitation to be highly significant network over collaboration and technical acquisition in service firms in Tanzania. This imply that the service firms in Tanzania are tend to rely on information exploitation and exploration network compared to other networks such as collaboration and technology acquisition. The study made contribution to the literature regarding innovation in developing countries in service firms, non-patentable innovative firms in particular.
Socio-economic Factors as Predictors of Undergraduate Students’ Attitude towards Entrepreneurship in Botswana
Authors: Baliyan Som Pal , Baliyan Pritika Singh
Published: May 2018

Attitudes and values related to entrepreneurship imbibed by graduates may serve as impediments to future economic growth and development of entrepreneurship. Factors behind the nonchalant attitude towards entrepreneurship by the potential entrepreneur youth need to be identified and their influence remedied. This descriptive and co-relational study analyzed the socio-economic factors determining attitude towards entrepreneurship among graduates in Botswana. A valid and reliable questionnaire was used for data collection through a survey of 149 (n=149) randomly sampled graduates in Botswana. Data was analyzed through descriptive and inferential statistical tools of mean, frequency, independent t-test, one way analysis of variance and multiple regression analysis. Descriptive statistics indicated that the students would like to pursue their future career as entrepreneurs but opposite to the student career ambition, the parents want their children to become future professionals. Findings revealed that eight socio-economic factors namely; gender, program of study, year of study, mothers’ education level, mothers’ profession, family income level and students career ambition after completion of degree program and parents career ambition after completion of degree program have significant influence on the students’ attitude towards entrepreneurship. Multiple regression analysis indicated that the socio-economic factors are significant predictors of students’ attitude towards entrepreneurship. Furthermore, mothers’ education level was the top significant socio-economic factor predicting the students’ attitude followed by students’ career ambition after completion of the program, the year of study and the program of study. Further research can be conducted to investigate the reasons for gender difference in students’ attitude towards entrepreneurship and, reasons for contradicting career ambitions of the students and their parents.
1990: ¿hacia la pacificación y la democracia?
Authors: Editor El
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 13, 1990: 3-8
Panegírico al Dr. Segundo Montes
Authors: Brand Salvador Osvaldo
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 13, 1990: 79-83
Crecimiento demográfico y dinámica social en El Salvador
Authors: Morales Velado Oscar
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 14, 1990: 91-133
Centroamérica: paz, desarrollo y democracia versus guerra y militarismo. El reto de los años noventa
Authors: Benítez Manaut Raúl
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 14, 1990: 165-182
Política de tasas de interés reforma tributaria (Resumen del acuerdo sobre una nueva política de tasa de interés adoptada en la Junta Monetaria No. JM 19/89, de 18 de julio de 1989)
Authors: Editor El
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 15, 1990: 303-328
Presentación No. 16
Authors: Editor El
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 16, 1990: 331-332
La ley de privatización bancaria: ¿de la privatización a la privatización?
Authors: Ibisate Francisco Javier
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 16, 1990: 333-354
Política macroeconómica y sus efectos en la agricultura y la seguridad alimentaria. Crisis de la agricultura, política agraria y ajuste estructural. Caso: El Salvador
Authors: Goitia Alfonso , Abrego Lisandro
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 17, 1990: 533-588
Los cambios en la estructura tributaria de El Salvador: implicaciones para el desarrollo
Authors: McGuire J. Michael
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 18, 1990: 641-676
1991. Cambios en el escenario mundial y nacional
Authors: Editor El
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 19-20, 1991: 3-10
Los problemas de concertación económico-social que presentan los PAE
Authors: Pleitez Rafael A.
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 19-20, 1991: 65-82
El concepto de praxis en Marx: la unidad de ética y ciencia
Authors: González Luis Armando
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 19, 1991: 195-226
Liberalización financiera y sistema de ahorro y préstamo en El Salvador
Authors: Fontg Marta G. , Barrientos Miriam N. , Figueroa Angélica M.
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 21, 1991: 299-325
Cuadro básico, principios y criterios para protección y asistencia aplicable a los proyectos de repatriación voluntaria de los refugiados salvadoreños
Authors: Racicott Denis
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 21, 1991: 375-400
Plan de investigación del IIES-UCA
Authors: Editor El
Published: May 2018

No abstract availableRealidad: Revista de Ciencias Sociales y Humanidades No. 21, 1991: 403-431