bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Uncertainties in Classical and Component (Blocked Force) Transfer Path Analysis (TPA)
Authors: Moorhouse Andy , Meggitt Joshua , Elliott Andrew
Published: June 2019

Transfer path analysis (TPA) has become a widely used diagnostic technique in the automotive and other sectors. In classic TPA, a two-stage measurement is conducted including operational and frequency response function (FRF) phases from which the contribution of various excitations to a target quantity, typically cabin sound pressure, are determined. Blocked force TPA (also called in situ Source Path Contribution Analysis, in-situ TPA and component TPA) is a development of the classic TPA approach and has been attracting considerable recent attention. Blocked force TPA is based on very similar two stage measurements to classic TPA but has two major advantages: there is no need to dismantle the vehicle and the blocked forces obtained are an independent property of the source component and are therefore transferrable to different assemblies. However, despite the now widespread reliance on classic TPA, and the increasing use of blocked force TPA in the automotive sector, it is rare to see any evaluation of the associated uncertainties. This paper therefore aims to summarize recent work and provide a guide to the evaluation of uncertainties in both forms of TPA. The various types of uncertainty are first categorized as, ‘model’, ‘source’ and ‘experimental’ uncertainties. Model uncertainties arise due to incomplete or inconsistent representation of the physical assembly by the measurements. Criteria are provided for evaluation of completeness in terms of measured quantities. Experimental and source uncertainties are evaluated through a first order propagation approach. Expressions are provided allowing the uncertainty in the target quantity to be estimated from measured quantities. Additional data storage and analysis is required but no additional measurements are needed over and above the usual TPA measurements. An illustrative example is provided.
Optimal Pressure Relief Groove Geometry for Improved NVH Performance of Variable Displacement Oil Pumps
Authors: Zouani Abdelkrim , Marri Vidya
Published: June 2019

Variable Displacement Oil Pump (VDOP) is becoming the design of choice for engine friction reduction and fuel economy improvement. Unfortunately, this pump creates excessive pressure ripples, at the outlet port during oil pump shaft rotation, causing oscillating forces within the lubrication system and leading to the generation of objectionable tonal noises and vibrations. In order to minimize the level of noise, different vanes spacing and porting geometries are used. Moreover, an oil pressure relief groove can be added, at the onset of the high pressure port, to achieve this goal.

This paper presents an optimization method to identify the best geometry of the oil pressure relief groove. This method integrates adaptive meshing, 3D CFD simulation, Matlab routine and Genetic Algorithm based optimization. The genetic algorithm is used to create the required design space in order to perform a multi-objective optimization using a large number of parameterized groove geometries. Results of this optimization method are discussed and a design guideline for the oil pressure relief groove is disclosed.
Machine Learning Algorithm for the Prediction of Idle Combustion Uniformity
Authors: Li Xiaoqi , Zouani Abdelkrim
Published: June 2019

Combustion stability is a key contributor to engine shake at idle speed and can impact the overall perception of vehicle quality. The sub-firing harmonics of the combustion torque are used as a metric to assess idle shake and are, typically, measured at different levels of engine break mean effective pressure (BMEP). Due to the nature of the combustion phenomena at idle, it is clear that predicting the cycle-to-cycle and cylinder-to-cylinder combustion pressure variations, required to assess the combustion uniformity, cannot be achieved with the state of the art simulation technology.

Inspired by the advancement in the field of machine learning and artificial intelligence and by the availability of a large amount of measured combustion test data, this paper explores the performance of various machine learning algorithms in predicting the idle combustion uniformity. The algorithms that are explored include Neural Network (NN), Support Vector Machine (SVM), Ensembles of Trees (EOT) and Gaussian Process (GP). The variables selected as inputs to these algorithms include BMEP, indicated mean effective pressure (IMEP), pumping mean effective pressure (PMEP), spark timing, crank angle at 10% fuel burn (Burn0010), crank angle at 90% fuel burn (Burn1090), and crankshaft timing at 50% fuel burn (CA50). The algorithms output the amplitude of 0.5 order, 1.0 order and the 1.5 order harmonics of the combustion torque.

The results presented in this paper show the superiority of the Gaussian Process algorithm in predicting the combustion torque harmonics. Using this algorithm, this paper further investigates the sensitivity of the engine torque harmonics to the parameters, used as inputs to the algorithm, in order to establish potential design guidelines for upfront combustion system development.
Multi-Physics and CFD Analysis of an Enclosed Coaxial Carbon Nanotube Speaker for Automotive Exhaust Noise Cancellation
Authors: Prabhu Suraj Madhav , Barnard Andrew , Senczyszyn Steven
Published: June 2019

Automotive exhaust noise is one of the major sources of noise pollution and it is controlled by passive control system (mufflers) and active control system (loudspeakers and active control algorithm). Mufflers are heavy, bulky and large in size while loudspeakers have a working temperature limitation. Carbon nanotube (CNT) speakers generate sound due to the thermoacoustic effect. CNT speakers are also lightweight, flexible, have acoustic and light transparency as well as high operating temperature. These properties make them ideal to overcome the limitations of the current exhaust noise control systems. An enclosed, coaxial CNT speaker is designed for exhaust noise cancellation application. The development of a 3D multi-physics (coupling of electrical, thermal and acoustical domains) model, for the coaxial speaker is discussed in this paper. The model is used to simulate the sound pressure level, input power versus ambient temperature and efficiency. The 3D model provides accurate results of the temperature profile and heat flow as compared to a 2D model. Also, the flow of exhaust gases can be efficiently modeled using a 3D model. The flow analysis would help understand any flow penetration into the speaker as well as the effect of heat transfer due to the flow. The model is validated by comparing the experimental results with the simulation results. Along with multi-physics simulation, CFD analysis of the coaxial speaker is also studied in this paper. The CFD analysis is focused on the backpressure generated by the speaker and the flow path of the exhaust gases inside the CNT speaker.
Ensino de Sociologia: a constituição de um sub-campo de pesquisa
Authors: Handfas Anita , Carvalho Izabella
Published: June 2019

O objetivo do artigo é refletir sobre a identidade da área de pesquisa sobre o ensino de sociologia na educação básica, tendo em vista o debate já iniciado por alguns autores que sustentam a hipótese desta área ser um sub-campo de pesquisa no interior do campo científico das ciências sociais. Dialogando com o conceito de campo, de Pierre Bourdieu, o artigo dialoga com alguns desses trabalhos e ao mesmo tempo apresenta resultados da pesquisa de perfil dos pesquisadores de mestrado que desenvolveram pesquisas sobre o tema. Os dados levantados pelo perfil corroboram com a hipótese de que o ensino de sociologia se constitui como um sub-campo de pesquisa.
Reflexões sobre o papel dos partidos no sistema político brasileiro: atividade parlamentar no contexto de preponderância do executivo
Authors: Alves Vinícius Silva
Published: June 2019

O presente trabalho oferece uma reflexão sobre as possibilidades de atuação de deputados federais no sistema político brasileiro, marcado pela preponderância do Poder Executivo. Admite-se que a preocupação com a continuidade de suas carreiras políticas condiciona o comportamento e atuação dos parlamentares. O texto apresenta, após uma breve introdução, que ilustra as bases sobre as quais se desenvolvem as relações entre Executivo e Legislativo no Brasil, a literatura que nos auxilia a compreender as decisões que os atores políticos tomam ao longo de suas carreiras. Em seguida, são discutidas as interpretações e achados sobre a atuação dos deputados brasileiros, assim como as críticas que podem nos ajudar a compreender a atividade parlamentar sob uma perspectiva mais dinâmica. Ao final, sugerimos que os partidos políticos condicionariam as possibilidades de atuação de seus membros, oferecendo vantagens e obstáculos às atividades dos aliados e dos oposicionistas em relação ao governo federal.
A política macroeconômica brasileira no período 2003-2017: uma análise institucionalista
Authors: Silva Leonardo
Published: June 2019

Com base em um levantamento bibliográfico, neste artigo analiso a trajetória assumida pela política macroeconômica brasileira entre 2003 e 2017. Argumento que no final do primeiro governo Lula ocorreu uma hibridização do paradigma macroeconômico neoliberal então dominante. Apesar de conservar o tripé neoliberal instituído por FHC, esse paradigma “liberal-desenvolvimentista” apresentava medidas distributivas e redistributivas e medidas de incentivo aos setores produtivos. Esse paradigma híbrido manteve-se até 2016 quando Temer ascendeu à presidência. Orientando-se pelas diretrizes neoliberais, Temer tem eliminado os componentes desenvolvimentistas do paradigma macroeconômico fato que tem, por sua vez, conduzido o país de volta ao “fundamentalismo de mercado” dominante nos governos Collor e FHC.
A sociologia católica de Francisca Peeters na constituição do campo educacional brasileiro na década de 1930
Authors: Cigales Marcelo Pinheiro
Published: June 2019

Este artigo analisa o manual "Noções de Sociologia" de Francisca Peeters escrito na década de 1930. Trata-se de um manual destinado ao ensino da sociologia na escola normal, caracterizado pela concepção católica da sociologia. O estudo investiga o projeto civilizacional do manual, a partir de uma proposta de análise baseada na manualística escolar e na perspectiva relacional de Pierre Bourdieu, com vista a compreender as configurações do campo educacional brasileiro nesse período. Os resultados evidenciam a disputa entre intelectuais católicos e renovadores e os distintos projetos de ensino para a sociologia, visível no manual a partir da sua dinâmica explicativa de mundo, combativa das teorias sociais em voga, e, prescritiva de instituição da verdade baseada no cristianismo católico.
A frágil democracia: Simone Weil e o fim dos partidos políticos
Authors: Barros Eduardo Portanova
Published: June 2019

Esta resenha crítica trata do livro “Sobre a supressão geral dos partidos políticos”, de Simone Weil, no qual a filósofa francesa desacredita, totalmente, na figura da democracia representativa e, mais especificamente, em partido político. Consideramos um texto atual e propositivo diante da exacerbação das múltiplas guerras culturais e políticas, em todas as latitudes, que promovem antes o dissenso do que um consenso democrático. Buscamos no referencial nietzschiano do embate apolíneo-dionisíaco-metafísico-anarquista uma justificativa para ancorar a crítica de Simone Weil à democracia e sua posição de referencial niilista. Weil conclui que o partido político está morto.
Gênero e Educação: o feminino santificado no Cariri cearense
Authors: Barreto Polliana de Luna Nunes , Holanda Patrícia Helena Carvalho
Published: June 2019

Trata das representações sobre o feminino santificado no Cariri cearense, observando que esse feminino atua como elemento de amoldamento dos sujeitos, na medida em que é também amoldado por meio de um fenômeno educativo lato sensu. Aborda a escrita em estilo hagiográfico sobre Luzia Coelho, de Barbalha – CE (1923 – 1952), enquanto elemento de propagação de modelos para o feminino, considerando o recuo temporal. Considera que a observação da história de vida das santas em período anterior à atualidade é importante para compreendermos como esses contextos históricos interferem nos valores constituídos no Brasil para a idealização da Santidade e dos papéis femininos. Ressalta, como síntese, a vinculação do discurso relacionado ao código moral católico-cristão, os aspectos também relativos à manutenção da família nuclear e os elementos educacionais que propagam funções para o feminino e constroem a santidade.
Fatigue in heart failure outpatients: levels, associated factors, and the impact on quality of life
Authors: Polikandrioti Maria , Kalafatakis Fotios , Koutelekos Ioannis , Kokoularis Dimitrios
Published: June 2019

Introduction

Heart failure (HF) patients experience various psychosocial issues and physical symptoms such as fatigue, which adversely affect their quality of life (QoL). The aim of the study was to assess levels of fatigue in HF outpatients and the associated factors, as well as to explore the correlation between fatigue and QoL.

Material and methods

One hundred and thirty patients were enrolled in the study. Data collection was performed by the completion of “Minnesota Living With Heart Failure” questionnaire (MLHFQ) and the Greek version of the Modified Fatigue Impact Scale (MFIS-Greek). Data also included self-reported patients’ characteristics.

Results

Of the 130 HF outpatients, 50% scored above 69 (median) in total fatigue and above 41 and 29 (median) in physical and mental fatigue, respectively. Furthermore, 50% scored above 66 (median) in total QoL and above 32.5 and 13 (median) in the physical and mental state, respectively. These values indicate moderate to high impact of HF on fatigue and on patients’ QoL. Total fatigue was statistically significantly associated with NYHA stage (p = 0.001), confidence to acknowledge health deteriorations (p = 0.004), decrease in appetite (p = 0.001), dyspnoea at night (p = 0.001), oedema in lower limbs (p = 0.023), relation with health professionals (p = 0.031), and whether patients had limited daily activities (p = 0.002), social contacts (p = 0.014), and if they had financial worries (p = 0.003). Finally, as the score of fatigue increased, so the QoL score also increased.

Conclusions

A broader understanding of this distressing symptom in HF may contribute to the development of suitable interventions with the ultimate goal of improving QoL.
The effect of different types of honey on the lipid profile of streptozotocin-induced diabetic rats
Authors: Mohammadimanesh Ali , Vahidiniya Ali Asghar , Doaei Saeid , Gholamalizadeh Maryam , Shahvegharasl Zahra , Salehi Iraj , Fayyaz Nasrin , Khosravi Hassan Mozzaffari
Published: June 2019

Introduction

The effect of honey consumption in diabetic patients has been contradictory. The aim of the present animal study was to compare the effect of different types of honey on the lipid profile in diabetic rats.

Material and methods

Sixty-four male Wistar rats were divided into two main groups: a streptozotocin-induced diabetes mellitus (DM) group (including four subgroups) and a healthy group (including four subgroups), based on random allocation. Three subgroups of each main group were given 1 mg/kg of three different types of honey (acacia, astragalus, and artificial honey) by oral gavage for 10 weeks. The control groups were given distilled water. Blood samples were collected, and the lipid profile was measured and compared between the eight groups after the intervention.

Results

The levels of LDL, triglycerides (TG), and total cholesterol (Tchol) in DM rats treated with astragalus honey were significantly lower and the HDL level was significantly higher compared to the other DM and healthy groups (all p-values < 0.05). LDL, TG, and Tchol levels in DM rats treated with artificial honey were significantly higher, and HDL levels were significantly lower than for other types of honey and for the control groups (all p-values < 0.05). LDL, HDL, TG, and Tchol levels in healthy rats were not significantly different between the groups (p-value > 0.05).

Conclusions

Different types of honey (acacia, astragalus, and artificial honey) had various effects on serum lipid profiles in diabetic rats. The results of this study indicated that the effect of honey on diabetic patients can vary widely based on its source.
Changes in histone H3 lysine 4 trimethylation in Hashimoto’s thyroiditis
Authors: Lu Xixuan , Sun Jing , Liu Tingting , Zhang Hao , Shan Zhongyan , Teng Weiping
Published: June 2019

Introduction

The precise pathogenesis of Hashimoto’s thyroiditis (HT) is yet to be fully elucidated. The role of epigenetics in the pathogenesis of HT has scarcely been addressed. Tri-methylated histone H3 lysine 4 (H3K4me3) is generally regarded as a marker of gene activation. The aim of this study was to explore genome-wide H3K4me3 patterns and global protein levels in primary thyrocytes and thyroids from HT patients.

Material and methods

Chromatin immunoprecipitation sequencing (ChIP-seq) was used to analyze genome-wide H3K4me3 patterns in primary cultured thyrocytes from three HT females and three age-matched female control subjects. Western blotting was used to analyze global H3K4me3 levels in thyrocytes and thyroid tissues. Gene expression was determined using RT-PCR. Mixed-lineage leukemia 1 (MLL1) protein levels were measured by western blotting and immunohistochemistry.

Results

Nine genes – TG, CXCL8, CCL2, CXCL10, FASLG, ICAM1, ITGA4, IL18 and TRAIL – showed increased H3K4me3 enrichment in promoter regions around the transcriptional start sites, and gene expression of ICAM1, CCL2 and CXCL8 was consistently increased (p < 0.05). KEGG pathway analysis suggested that differential peak-related genes were markedly associated with autoimmune thyroid disease< 0.05).

Conclusions

This first investigation of genome-wide H3K4me3 distribution in thyroid follicular cells suggested that genes associated with autoimmune thyroiditis showed differential H3K4me3 enrichment, which was partly related to gene expression. Global H3K4me3 changes and increased MLL1 expression were found in thyroid tissues from HT patients.
Regulation strategies and their impact on subsequent response inhibition: the moderating role of the self-control trait
Authors: Wójcik Natalia , Nęcka Edward
Published: June 2019

Background

Much research has shown that effortful acts of self-control temporarily impair its subsequent exertion. The aim of our experi-ment was to examine whether this effect, called ego depletion, is influenced by application of certain strategies that help people to overcome impulses. Another purpose of our research was to investigate the role of self-control as a trait in this area. We fo-cused on amusement regulation because of its importance in everyday life.

Participants and procedure

Participants (N = 90) completed the Self-Control Scale (NAS-50) and were then asked to rate humorous cartoons (Task 1) while inducing the following self-regulatory strategies suggested by the instructions: cognitive change, response inhibition, or none (between-subjects manipulation). Subsequently, participants performed the Stop Signal Task (Task 2).

Results

The results indicate that the depletion effect is absent unless trait self-control is included in the analysis. We observed the interac-tion between the self-control trait and the effectiveness of the adopted self-regulatory strategy. Participants with poor self-control did not differ in their performance in Task 2, regardless of the adopted strategy. With the increase in the self-control trait, we observed differences in Task 2 that indicated that the cognitive change strategy guarded against depletion in participants with a medium level of self-control. Participants with a high self-control trait level obtained better scores in both regulatory groups, compared to the condition without any strategy.

Conclusions

We discuss these findings in terms of the competing explanations of the ‘ego depletion’ effect, as well as in terms of the trait versus state approach to self-control.
A NEW THINKING OF LULC CLASSIFICATION ACCURACY ASSESSMENT
Authors: Cheng K. S. , Ling J. Y. , Lin T. W. , Liu Y. T. , Shen Y. C. , Kono Y.
Published: June 2019

Abstract. A majority of studies involving remote sensing LULC classification conducted classification accuracy assessment without consideration of the training data uncertainty. In this study we present new concepts of LULC classification accuracies, namely the training-sample-based global accuracy and the classifier global accuracy, and a general expression of different measures of classification accuracy in terms of the sample dataset for classifier training and the sample dataset for evaluation of classification results. Through stochastic simulation of a two-feature and two-class case, we demonstrate that the training-sample confusion matrix should replace the commonly adopted reference-sample confusion matrix for evaluation of LULC classification results. We then propose a bootstrap-simulation approach for establishing 95% confidence intervals of classifier global accuracies.
A PRELIMINARY QUALITY ANALYSIS OF THE CLIMATE CHANGE INITIATIVE LAND COVER PRODUCTS FOR CONTINENTAL PORTUGAL
Authors: Fonte C. C. , See L. , Lesiv M. , Fritz S.
Published: June 2019

Abstract. The aim of this paper is to perform a preliminary analysis of the compatibility and quality of the available time series of land cover data available for continental Portugal, in particular, Climate Change Initiative Land Cover maps, which are available annually from 1992 to 2015; CORINE Land Cover and the Urban Atlas for 2006 and 2012; and the Portuguese Carta de Ocupação do Solo for 2007 and 2010. Changes were first identified per product between the different data sets for consecutive dates and then a comparison was made between products. This was followed by validation of two study areas using the COS and UA as reference products. The results show that increases in urbanization are visible in all pairs of products but that the amount of change varies. Moreover, some changes are not in the same direction but may be attributable to classes with small areas and the coarser resolution of the CCI LC maps compared to the other products. The CCI LC maps also overestimate the forest/natural vegetation class by 11–13%, which is also the largest class in Portugal.
HIERARCHICAL DATA MODEL FOR STORAGE AND INDEXING OF MASSIVE STREET VIEW
Authors: Du M. , Wang J. , Jing C. , Jiang J. , Chen Q.
Published: June 2019

Abstract. Maintaining an up-to-date inventory of urban infrastructure such as fire hydrant is critical to urban management. Street view database such as Google Street View and Baidu Street View contain street-level images, their potential for urban management has not been fully explored. For the massive image, data model for storage and indexing is an important research issue. Considering multiple cameras and GPS device in the image capturing platform, a hierarchical data model named 3D-Grid is proposed. Massive street view images were stored according to grid ID, GPS time and camera ID. An efficient time indexing algorithm is brought forth to replace the spatial indexing. Real test experiments are conducted in a project, and the validation and feasibility of 3D-Grid including time indexing algorithm were validated.
RANKING NODES IN COMPLEX NETWORKS: A CASE STUDY OF THE GAUBUS
Authors: Moyo T. , Musakwa W.
Published: June 2019

Abstract. Connecting points of interest through a well-planned, inter-connected network provides manifold benefits to commuters and service providers. In the South African context, traffic congestion has become of great concern. Given how the South Africa community is slowly developing towards the use of multi-modes of mobility, the Gautrain network can be used to promote the use of multi-modes of mobility, as the Gautrain has been identified as the backbone of mobility within the Gauteng province. Currently commuters have the option to board the Gaubus (a form of Bus Rapid Transit) at their origin points which will take them to the Gautrain station to board the Gautrain. The problem to be solved arises when a commuter wishes to traverse from any bus stop to the Gautrain station, currently he/she only has one option and if the bus network has a shutdown at any point in the network the commuter’s journey will not be possible. In solving this problem, we consider the problem of graph robustness (that is creating new alternative routes to increase node/bus stop connectivity). We initial use Strava data, to identify locations were cyclist prefer to cycle and at what time of day. In graph theory, the nodes with most spreading ability are called influential nodes. Identification of most influential nodes and ranking them based on their spreading ability is of vital importance. Closeness centrality and betweenness are one of the most commonly used methods to identify influential nodes in complex networks. Using the Gaubus network we identify the influential nodes/ bus stops, using the betweenness centrality measure. The results reveal the influential nodes with the highest connectivity as these have cross-connections in the network. Identification of the influential nodes presents an important implication for future planning, accessibility, and, more generally, quality of life.
LUNAR SURFACE SAMPLING FEASIBILITY EVALUATION METHOD FOR CHANG’E-5 MISSION
Authors: Wang J. , Ma C. , Zhang Z. , Wang Y. , Peng M. , Wan W. , Feng X. , Wang X. , He X. , You Y.
Published: June 2019

Abstract. As China’s first unmanned spacecraft to collect lunar surface samples and return them to Earth, the Chang’E-5 detector is a crucial probe that will complete lunar surface sampling in China’s lunar exploration project. This lunar sampling will be the first successful lunar surface sampling return mission in China. Sampling decisions needs to be made based on topographical analysis results and characteristics of the area to be explored. Due to the unknown extraterrestrial terrain and uncertainty of sampled objects, we propose a sampling feasibility estimation for safely implementing lunar surface sampling.Our strategy took into account the influence of factors that may interfere with the sampling process, and provided quantitative assessment of the sampling feasibility for the area to be explored. We combined the three-dimensional topography of the lunar surface with five parameters of the sampling area, flatness, slope, slope aspect, accessibility of the mechanical arm distal end, and safety of sampling conditions. The first three values were calculated based on a digital elevation model (DEM) of the landing area generated using stereo images. The other values were computed based on the mechanical properties of the arm and kinematic analysis of its articulated joints. Based on the above-mentioned quantitative parameters, they were weighed to obtain an evaluation value for the sampling feasibility of each DEM pixel. Meanwhile, a multichannel sampling area analysis graph was generated that combined all the above indicators as well as the sampling feasibility values, which provides a visualization for determining detection targets in the Chang’E-5 sampling mission.
FLOATING CAR DATA (FCD) FOR MOBILITY APPLICATIONS
Authors: Ajmar A. , Arco E. , Boccardo P. , Perez F.
Published: June 2019

Abstract. Floating car data (FCD) is becoming more and more relevant for mobility domain applications, overcoming issues derived by the use of physical sensors (e.g. inductive loops, video observation, infrared and laser vehicle detection etc.), such as limited geographical distribution, measure inhomogeneities, limited or null coverage of minor roads. An increasing number of vehicles are equipped with devices capable of acquiring GPS positions and other data, transmitted in almost real-time to traffic control centres. Based on FCD data, several traffic analysis in support to mobility services can be performed: vehicle density, speed, origin-destination matrices, different patterns in function of vehicle type. If currently the representativeness of FCD can be considered an issue, current growing trend in FCD penetration should naturally overcome this issue. FCD are also higher sensitive to traffic events (e.g. traffic jams) than model-based approaches.
DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONS
Authors: Fissore E. , Pirotti F.
Published: June 2019

Abstract. Using multiple sources of 3D information over buildings to go from building footprints (LOD0) to higher LODs in CityGML models is a widely investigated topic. In this investigation we propose to use a very common 2.5D product, i.e. digital terrain and surface models (DTMs and DSMs), to test how much they can contribute to improve a CityGML model. The minimal information required to represents a 3 dimensional space in an urban environment is the combination of a DTM, the footprints of buildings and their heights; in this way a representation of urban environment to define LOD1 CityGML is guaranteed. In this paper we discuss the following research questions: can DTMs and DSMs provide significant information for modelling buildings at higher LODs? What characteristics can be extracted depending on the ground sampling distance (GSD) of the DTM/DSM? Results show that the used DTM/DSM at 1 m GSD provides potential significant information for higher LODs and that the conversion of the unstructured point cloud to a regular grid helps in defining single buildings using connected component analysis. Regularization of the original point cloud does loose accuracy of the source information due to smoothing or interpolation, but has the advantage of providing a predictable distance between points, thus allowing to join points belonging to the same building and provide initial primitives for further modelling.
V-RSIR: A WEB-BASED TOOL AND BENCHMARK DATASET FOR REMOTE SENSING IMAGE RETRIEVAL
Authors: Hou D. , Xing H.
Published: June 2019

Abstract. Benchmark datasets play an important role in evaluating remote sensing image retrieval methods. Current benchmark datasets are mostly collected through the Google Map API or other desktop tools. However, the Google Map API requires the users to have programming skills and other collection tools are not publicly available, which may hinder the development of new benchmark datasets. This paper develops an open access web-based tool V-RSIR to help users generating new benchmark datasets with volunteers for remote sensing image retrieval. Using this tool, a new benchmark dataset V-RSIR that contains 38 classes with at least 1500 images per class is created by 32 volunteers. A handcrafted low-level feature method and a deep learning high-level feature method are used to test the dataset. The evaluation results are consistent with our perception. This shows that the tool can help users effectively creating benchmark datasets for RSIR.
MONITORING SDG 9 WITH GLOBAL OPEN DATA AND OPEN SOFTWARE – A CASE STUDY FROM RURAL TANZANIA
Authors: Ilie C. M. , Brovelli M. A. , Coetzee S.
Published: June 2019

Abstract. The 17 goals adopted by the United Nations (UN) are aimed at achieving a better and more sustainable future for all. For each goal, a set of indicators has been defined. The indicators measure progress towards achieving the respective SDG. For the majority of these indicators, geospatial information is needed to evaluate the current state of the indicator. While geospatial information is largely available in developed countries, this is not the case in many developing countries of the world. Furthermore, skills and capacity for calculating indicator values are also limited in many developing countries. To address these shortcomings, the third challenge of the 2018 UN OSGeo Committee Educational Challenges called for the development of training material for using open source software together with freely available high resolution global geospatial datasets in support of monitoring SDG progress. The resulting training material provides a step-by-step guide for calculating the state of SDG indicator 9.1.1, Proportion of the rural population who live within 2km of an all-season road, using open software and open data with global coverage. Through the development of this training material, we showed that anyone can monitor progress towards achieving SDG indicator 9.1.1 for their specific part of the world. Because open source software and open data were used, the indicator calculation is cost effective and completely sustainable.
GROUND POINT FILTERING FROM AIRBORNE LIDAR POINT CLOUDS USING DEEP LEARNING: A PRELIMINARY STUDY
Authors: Janssens-Coron E. , Guilbert E.
Published: June 2019

Abstract. Airborne lidar data is commonly used to generate point clouds over large areas. These points can be classified into different categories such as ground, building, vegetation, etc. The first step for this is to separate ground points from non-ground points. Existing methods rely mainly on TIN densification but there performance varies with the type of terrain and relies on the user’s experience who adjusts parameters accordingly. An alternative may be on the use of a deep learning approach that would limit user’s intervention. Hence, in this paper, we assess a deep learning architecture, PointNet, that applies directly to point clouds. Our preliminary results show mitigating classification rates and further investigation is required to properly train the system and improve the robustness, showing issues with the choices we made in the preprocessing. Nonetheless, our analysis suggests that it is necessary to enrich the architecture of the network to integrate the notion of neighbourhood at different scales in order to increase the accuracy and the robustness of the treatment as well as its capacity to treat data from different geographical contexts.
A METHOD OF URBAN ROAD NETWORK EXTRACTION BASED ON FLOATING CAR TRAJECTORY DATA
Authors: Mi C. , Lu F.
Published: June 2019

Abstract. With the gradual opening of floating car trajectory data, it is possible to extract road network information from it. Currently, most road network extraction algorithms use unified thresholds to ignore the density difference of trajectory data, and only consider the trajectory shape without considering the direction of the trajectory, which seriously affects the geometric precision and topological accuracy of their results. Therefore, an adaptive radius centroid drift clustering method is proposed in this paper, which can automatically adjust clustering parameters according to the track density and the road width, using trajectory direction to complete the topological connection of roads. The algorithm is verified by the floating car trajectory data of a day in Futian District, Shenzhen. The experimental results are qualitatively and quantitatively analyzed with ones of the other two methods. It indicates that the road network data extracted by this algorithm has a significant improvement in geometric precision and topological accuracy, and which is suitable for big data processing.
EXPLORING THE POTENTIAL OF CROWD SOURCED DATA TO MAP COMMUTER POINTS OF INTEREST: A CASE STUDY OF JOHANNESBURG
Authors: Moyo T. , Musakwa W.
Published: June 2019

Abstract. Modern African cities are faced with various mobility and transportation challenges. In developing smart sustainable cities, city planners need to create a balance between supply and demand for public transportation. Development of multi-mobility mode models has contemporarily received a special interest in smart cities development. Globally, the use of bike sharing services to complete the first kilometre or last kilometre of the trip has been highly received, with commuters using either rail or road mobility modes for the middle section of their trip. Within the developing world context, the use of multi-mobility modes in daily commuting is still new, and little research has been done to guide this. Notwithstanding the influence of uncertainties and fragmentation over demand and supply in public transportation provision. In the South Africa context, various modes of public transportation have been developed which seek to be smart, sustainable and efficient such as the fast train (Gautrain), Bus rapid transport (Rea Vaya and Gaubus) and Bikes sharing platforms (Upcycles), however most of these modes are currently not spatially connected. Hence the researcher sought to develop a stepping stone in planning for future mobility demand. Using an explorative methodology, the authors collected quantitative and spatial data in the form of land-use data and crowd sourced data (from twitter) to map commuter points of interest in and around the city of Johannesburg. The results reveal hot and cold spots in the city. The hot spots reveal areas where commuters frequently travel to, and when overlaid with transportation data, we are able to identify potential locations to develop new transportation hubs as these will overtime become key points of interest.
AUTOMATIC DETECTION AND LABELLING OF PHOTOGRAMMETRIC CONTROL POINTS IN A CALIBRATION TEST FIELD
Authors: Jarron D. , Shahbazi M. , Lichti D. , Radovanovic R.
Published: June 2019

Abstract. In this work, a new method is developed for the automatic and accurate detection and labelling of signalized, un-coded circular targets for the purpose of automated camera calibration in a test field. The only requirements of this method are the approximate height of the camera, an approximate range of orientations of the camera, and the object-space coordinates of the targets. In each image, circular targets are detected using adaptive thresholding and robust ellipse fitting. Labelling of those targets is performed next. First, the exterior orientation parameters of the image are estimated using a one-point pose-estimation approach, where a list of possible orientation and target labels are used, along with height, to calculate the camera position. The estimated position and orientation of the camera combined with the interior orientation parameters (IOPs) are then used to back-project the known object-space coordinates of the targets into the image space. These targets are then matched against the targets detected in the image, and the list entry with the best fit is chosen as the solution. This resolves both the detection and labelling of the targets, without the need for any coded targets or their associated software packages, and each image is solved independently allowing for parallel processing. This process accurately labels 92–97% of images, with average accuracy rates of 97% or better, and average completeness rates of 70–95% in imagery from the three cameras tested. The cameras were calibrated using observations from the detection and labelling process, which resulted in sub-pixel root mean square (RMS) values determined for the pixel space residuals.
RELIABILITY OF THE GEOMETRIC CALIBRATION OF AN HYPERSPECTRAL FRAME CAMERA
Authors: Musci M. A. , Aicardi I. , Dabove P. , Lingua A. M.
Published: June 2019

Abstract. One of the main tools for high resolution remote sensing and photogrammetry is the lightweight hyperspectral frame camera, that is used in several application areas such as precision agriculture, forestry, and environmental monitoring. Among these types of sensors, the Rikola (which is based on a Fabry–Perot interferometer (FPI) and produced by Senop) is one of the latest innovations. Due to its internal geometry, there are several issues to be addressed for the appropriate definition and estimation of the inner orientation parameters (IOPs). The main problems concern the possibility to change every time the sequence of the bands and to assess the reliability of the IOPs. This work focuses the attention on the assessment of the IOPs definition for each sensor, considering the impact of environmental conditions (e.g., different time, exposure, brightness) and different configurations of the FPI camera, in order to rebuild an undistorted hypercube for image processing and object estimation. The aim of this work is to understand if the IOPs are stable over the time and if and which bands can be used as reference for the calculation of the inner parameters for each sensor, considering different environmental configurations and surveys, from terrestrial to aerial applications. Preliminary performed tests showed that the focal length percentage variation among the bands of different experiments is around 1%.
ICE SHEET ELEVATION MAPPING AND CHANGE DETECTION WITH THE ICE, CLOUD AND LAND ELEVATION SATELLITE-2
Authors: Csatho B. M. , Schenk A. F. , Neumann T.
Published: June 2019

Abstract. On September 15, 2018, ICESat-2 (Ice, Cloud, and land Elevation satellite) was successfully launched to measure ice sheet and glacier elevation change, sea ice freeboard, and vegetation. This paper describes the computation of surface elevation change rates obtained with SERAC (Surface Elevation Reconstruction And Change detection) from ICESat-2 observations. After summarizing some relevant aspects of ICESat-2 and its sole instrument ATLAS (Advanced Topographic Laser Altimetry System) the paper focuses on how we calculate time series of elevation change rates from ICESat-2’s data product ATL03. Since real ICESat-2 data suitable for generating time series of several time epochs are not yet available, we used simulated data for this study. We will start generating time series from real ICESat-2 data after the conclusion of the ongoing calibration and validation phase and we expect to present real-world examples at the WG III/9 meeting in June, 2019 in Enschede, The Netherlands.
PRELIMINARY RESULTS OF SEA ICE FREEBOARD MEASUREMENTS OF BEAUFORT SEA FROM CRYOSAT-2 ALTIMETRY
Authors: Zhang S. , Zuo Y. , Xiao F. , Yuan L. , Geng T. , Xuan Y.
Published: June 2019

Abstract. Satellite altimetry has been used to observe the Arctic sea ice in long term and large scale, and the records show a continued decline for Arctic sea ice thickness over decades. In this study, the sea ice freeboard in Beaufort Sea of Arctic have been estimated using CryoSat-2 data, and validated with Upward Looking Sonar (ULS) data of Beaufort Gyre Exploration Project (BGEP). The results show an obvious seasonal variation of the Beaufort Sea with a high reliability estimation of the sea ice freeboard. The average height of the sea ice freeboard increase from January to March and achieve the maximum value 0.38 m in March. The sea ice melts after March and the average height of the sea ice freeboard reduces to the minimum 0.12 m in August. In the next few months the sea water begins to freeze and the average height of the sea ice freeboard will increase to the maximum value.
COMPARISON OF PIXEL AND REGION-BASED APPROACHES FOR TREE SPECIES MAPPING IN ATLANTIC FOREST USING HYPERSPECTRAL IMAGES ACQUIRED BY UAV
Authors: Miyoshi G. T. , Imai N. N. , Tommaselli A. M. G. , Honkavaara E.
Published: June 2019

Abstract. The objective of this work was the comparison of two different classification approaches to detect four different tree species of a highly diverse tropical Atlantic Forest area. In order to achieve the objective, images were acquired with the Rikola hyperspectral camera onboard the UX4 UAV. The study area is in the Western part of São Paulo State, a tropical Atlantic Forest area protected by governmental laws, which contains areas already deforested in the past and which are currently in regeneration. The tested approaches were one based only in the pixel values and other one based in regions. After the image acquisition, the images were radiometrically and geometrically processed. In addition, an airborne laser scanning point cloud was used to calculate the canopy height model of the area, which was used to detect the individual tree crowns with the superpixels method. Those superpixels were used to the region-based classification and to feature extraction. A total of 28 features were extracted where 25 correspond to the spectral bands acquired with the Rikola camera and three correspond to the three first principal components of the images. The features were extracted from the 91 samples recognized during a field work. From the total of samples, 19 were separated to validate the classification results. The chosen classifier was the Random Forests and the results presented a kappa coefficient of 18.20% and 36.57% for the pixel-based and region-based classifications showing that the second one had a better performance.
POLINSAR BASED SCATTERING INFORMATION RETRIEVAL FOR FOREST ABOVEGROUND BIOMASS ESTIMATION
Authors: Agrawal N. , Kumar S. , Tolpekin V. A.
Published: June 2019

Abstract. Forests play a crucial role in storing carbon and are of paramount importance in maintaining global carbon cycle. Assessment of forest biomass at regional and global level is vital for understanding and monitoring health of both tree species and entire cover. Changes in forest biomass are caused by human activities, natural factors and variations in climate. Forest biomass measurement is necessary for gauging the changes in forest ecosystems. Remote sensing is indispensable for mapping forest biophysical parameters. Microwaves are capable of collecting data even in case of cloud cover as the microwaves are of long wavelength. Microwaves help in retrieving scattering information of target. The goal of this research was to map aboveground biomass (AGB) over Barkot forest range in Dehradun, India. The current work focuses on the retrieval of PolInSAR based scattering information for the estimation of aboveground biomass. Radarsat-2 fully Polarimetric C-band data was used for the estimation of AGB in Barkot forest area. A semi-empirical model, which is Extended Water Cloud Model (EWCM) was utilized for AGB estimation. EWCM considers ground-stem interactions. Due to overestimation of volume scattering, polarization orientation angle shift correction was implemented on the PolInSAR pair. Field biomass data was utilized for accuracy assessment. The results show that coefficient of determination (R2) value of 0.47, Root Mean Square Error (RMSE) of 56.18 (t ha−1) and accuracy of 72% was obtained between modelled biomass against field measured biomass. Hence, it can be inferred from the obtained results that PolInSAR technique, in combination with semi-empirical modelling approach, can be implemented for estimating forest biomass.
APPLICATIONS OF SENTINEL-1 SYNTHETIC APERTURE RADAR IMAGERY FOR FLOODS DAMAGE ASSESSMENT: A CASE STUDY OF NAKHON SI THAMMARAT, THAILAND
Authors: Dadhich G. , Miyazaki H. , Babel M.
Published: June 2019

Abstract. Flooding is one of the major disasters occurring in various parts of the world. Estimation of economic loss due to flood often becomes necessary for flood damage mitigation. This present practice to carry out post flood survey to estimate damage, which is a laborious and time-consuming task. This paper presents a framework of rapid estimation of flood damage using SAR earth observation satellite data.In Nakhon Si Thammarat, a southern province in Thailand, flooding is a recurrent event affecting the entire province, especially the urban area. Every year, it causes lives and damages to infrastructure, agricultural production and severely affects local economic development. In order to monitor and estimate flood damages in near-real time, numerous techniques can be used, from a simply digitizing on maps, to using detailed surveys or remote sensing techniques. However, when using the last-mentioned technique, the results are conditioned by the time of data acquisition (day or night) as well as by weather conditions. Although, these impediments can be surpassed by using RADAR satellite imagery. The aim of this study is to delineate the land surface of Chian Yai, Pak Phanang and Hua Sai districts of that was affected by floods in December 2018 and January 2019. For this case study, Sentinel-1 C-Band SAR data provided by ESA (European Space Agency) were used. The data sets were taken before and after the flood took place, all within 1 days and were processed using Sentinel Toolbox. Cropland mapping has been carried out to assess the agricultural loss in study area using Sentinel-1 SAR data. The thematic accuracy has been assessed for cropland classification for test site shows encouraging overall accuracy as 82.63 % and kappa coefficients (κ) as 0.78.