bluuebunny/crossref_metadata_2025 huggingface dataset:
Posttranscriptional Regulation of HLA-A Protein Expression by Alternative Polyadenylation Signals Involving the RNA-Binding Protein Syncrip
Authors: Kulkarni Smita , Ramsuran Veron , Rucevic Marijana , Singh Sukhvinder , Lied Alexandra , Kulkarni Viraj , O’hUigin Colm , Le Gall Sylvie , Carrington Mary
Published: October 2017

Genomic variation in the untranslated region (UTR) has been shown to influence HLA class I expression level and associate with disease outcomes. Sequencing of the 3′UTR of common HLA-A alleles indicated the presence of two polyadenylation signals (PAS). The proximal PAS is conserved, whereas the distal PAS is disrupted within certain alleles by sequence variants. Using 3′RACE, we confirmed expression of two distinct forms of the HLA-A 3′UTR based on use of either the proximal or the distal PAS, which differ in length by 100 bp. Specific HLA-A alleles varied in the usage of the proximal versus distal PAS, with some alleles using only the proximal PAS, and others using both the proximal and distal PAS to differing degrees. We show that the short and the long 3′UTR produced similar mRNA expression levels. However, the long 3′UTR conferred lower luciferase activity as compared with the short form, indicating translation inhibition of the long 3′UTR. RNA affinity pull-down followed by mass spectrometry analysis as well as RNA coimmunoprecipitation indicated differential binding of Syncrip to the long versus short 3′UTR. Depletion of Syncrip by small interfering RNA increased surface expression of an HLA-A allotype that uses primarily the long 3′UTR, whereas an allotype expressing only the short form was unaffected. Furthermore, specific blocking of the proximal 3′UTR reduced surface expression without decreasing mRNA expression. These data demonstrate HLA-A allele-specific variation in PAS usage, which modulates their cell surface expression posttranscriptionally.
Recurrent pelvic organ prolapse: a case report
Authors: Drusany Starič Kristina , Bukovec Petra , Zore Andrej , Lukanović Adolf
Published: October 2017

Pelvic organ prolapse (POP) is a common female condition, which is seen as protrusion of pelvic organs into or beyond the vagina. Its incidence is increasing and every woman has an 11% lifetime risk of needing surgical treatment because of this condition. POP that is recurrent several times is a rare condition; however it can have major negative impact on quality of life. We present the case of a 77-year old Caucasian woman with repeated POP. She underwent six gynecologic operations for correction of recurrent POP. Presentation of this case clearly demonstrates dramatic recurrences of POP and how difficult its treatment and prevention can be. We do not know what the reason for multiple reoccurrence of this condition might be. We need to emphasize that there are no researches on specific risk for an individual patient, which may potentiate occurrence of POP and may affect decisions about surgical procedure.
Outcome of using a modified surgical technique for the repair of complex vesicovaginal fistulas in Nigeria
Authors: Umoiyoho Aniefiok J. , Inyang-Etoh Emmanuel C.
Published: October 2017

The relatively low effectiveness of available surgical repair techniques for complex obstetric fistula has justified the need for continued exploration of more effective repair techniques. Subjects who presented at a vesicovaginal fistula referral centre in Nigeria were randomized into the study group (modified technique) and the control group (conventional technique). Success rates between the two groups were compared. The study comprised 29 patients in each arm of the study. The mean age of patients in the study group was 23.9 ± 9.6 years and 24.4 ± 2.1 years among patients in the control group with the vast majority of the patients in the both groups being married, 75.9% and 86.2% respectively. In both groups, the majority were secundipara, 55.2% in the study group and 44.8% in the control group. The majority (41.4% in the study group and 44.8% in the control group) of the patients in both groups had attained primary level of education. The mean duration of the fistulas among patients in the study population was 1.1 ± 0.3 years with over half (50.0% among patients in the study group and 53.5% of patients in the control group) of the patients had their fistula for less than one year. A highly statistically significant difference in success rate between patients in the study group and patients in the control group was obtained (p=0.0004). The modified repair technique presented by this study has proved to produce superior results when compared to the conventional repair technique in the management of complex obstetric fistulas in Nigeria.
The Black Swans of Agricultural Education: A Glimpse into theLived Experiencesthat Shapte Urban Agricultural Educators' Meaning in Work
Authors: Roberts Richie , Ramsey Jon W.
Published: October 2017

Urban agricultural educators face a number of unique challenges in performing their job duties. Therefore, the purpose of this study was to understand the essence of urban agricultural educators’ meaning in their work by exploring their lived experiences. In this study, the essence emerged in the form of a metaphor: A Black Swan. The black swan represents a distinctiveness that urban agricultural educators possess in the agricultural education discipline. The black swans are guided by fusing (a) individualization, (b) self-connection, (c) contribution, (d) unification, and (e) coping abilities into a powerful construct identified as transcendence. By transcending ordinary levels of meaning, urban agricultural educators appeared to cope with their challenges in unique ways. Perhaps, the reason underlying the use of this coping strategy is the distinct population that urban agricultural educators serve since participants reported their programs were largely comprised of ethnic minority students living in low socioeconomic households. Urban agricultural educators might, therefore, continuously be faced with issues that remind them of the important role they play in their students’ lives. Moving forward, the study’s findings could be used as a foundation to explore and refine the discipline’s current understandings of urban agricultural educators’ meaning in work.
Concerns of Female Preservice Teachers in Teaching and Supervising the Agricultural Mechanics Laboratory
Authors: Tummons John D. , Langley G. Curtis , Reed Jeff J. , Paul Emily E.
Published: October 2017

Agricultural mechanics is a top career choice among secondary students enrolled in agricultural programs. Secondary agricultural mechanics teachers provide hands-on skill instruction with shielded metal arc welders, oxyfuel torches, and various hand tools in their agricultural mechanics laboratories. Preservice agriculture teachers have reported lack of preparation to adequately teach in this potentially dangerous environment. This qualitative case study explored the concerns of preservice teachers about teaching secondary students in the agricultural mechanics laboratory and how those concerns evolved over time. Researchers used a constructivist epistemology and open coding to identify and explore emergent themes. Three themes emerged from the data: 1) issues of trust and control in supervising laboratory students manifest themselves as a professional threat, 2) mechanics skill and supervisory skill development coincided with a change in focus toward student safety and learning, and 3) the agricultural mechanics laboratory provides unique instructional challenges and opportunities. Although each preservice teacher differed in their development, the authors identified persistent issues with agricultural mechanics skill knowledge and student trust.
Using Home Irrigation Users' Perceptions to Inform Water Conservation Programs
Authors: Warner Laura A. , Chaudhary Anil Kumar , Lamm Alexa J. , Rumble Joy N. , Momol Esen
Published: October 2017

Targeted agricultural education programs can play a role in solving complex water issues. This article applies importance-performance analysis to examine dimensions of water resources that may inform local water conservation campaigns in the United States. The purpose of this study was to generate a deep understanding of home irrigation users’ preferences and perceptions about water to inform landscape irrigation water best practices campaigns among this audience nationwide. Importance-performance analysis was conducted using quantitative survey research. Responses were drawn from 2,675 people who use home landscape irrigation in all states nationwide and from three areas experiencing serious water issues: Florida, California, and the Chesapeake Bay Watershed. There were differences among respondents as a function of geographical location, which revealed people are likely influenced by their exposure to and experience with water issues. There were significant differences between respondents’ perceived importance with clean water for different purposes and plentiful water for different purposes. We identified gaps between importance of and satisfaction with clean and plentiful water for different purposes which demonstrate dissatisfaction around important water topics, such as clean water for local and large water bodies. The findings provide insight for targeted programs surrounding local needs and issues. Agricultural education professionals who work on water issues should emphasize home irrigation users’ influence on water quality issues over water quantity issues, and should incorporate locally specific findings into programs.
Using the Theory of Planned Behavior to Encourage Water Conservation among Extensin Clients
Authors: Chaudhary Anil Kumar , Warner Laura A. , Lamm Alexa J. , Israel Glenn D. , Rumble Joy N. , Cantrell Randall A.
Published: October 2017

Extension professionals can play a role in addressing water scarcity issues by helping home landscape irrigation users to conserve water. This study used survey research to examine the relationship between several variables, including attitudes, subjective norms, perceived behavioral control, personal norms, demographic factors, and past behaviors, on intention to use good irrigation practices among Florida home landscape irrigation users (N = 1,063). Following subsequent hierarchical linear regression models, the final model explained 39% of the variance in intentions to engage in good landscape irrigation practices. Subjective norms had a strong influence on intention to engage in landscape water conservation, and past behaviors and personal norms improved the prediction. Extension professionals should incorporate subjective norms into water conservation programs by emphasizing somewhat invisible conservation behaviors to improve perceptions of peers’ practices. When personal norms are strong, the subjective norms are slightly less important. Residents who feel a personal obligation to conserve water may be more open to information related to water conservation, and they may be more likely to act, even in the absence of social support. Finally, Extension professionals should consider the audience’s past behaviors to design programs that are compatible with actions that Extension clients are likely to take.
The Role of Teachers in Facilitating Mathematics Learning Opprtunities in Agriculture, Food, and Natural Resources
Authors: McKim Aaron J. , Velez Jonathan J. , Everett Michel W. , Sorenson Tyson J.
Published: October 2017

Strengthening knowledge and skills in mathematics is critically important to preparing the next generation of innovators, problem solvers, and interdisciplinary thinkers. School-based agricultural education offers a valuable context to co-develop mathematics knowledge and skills alongside knowledge and skills in agriculture, food, and natural resources. The current study explored the role of school-based agricultural education teachers in facilitating interdisciplinary agriculture, food, natural resources, and mathematics learning experiences. Findings suggest teachers possessed positive attitudes, supportive subjective norms, high levels of perceived behavioral control, and moderate to high perceptions of mathematics knowledge. Additionally, teachers intended to teach mathematics content in an average of 24.51% of agriculture, food, and natural resources curriculum. However, in modeling the intentions of school-based agricultural education teachers to teach math, the combination of attitude toward the behavior, subjective norms, perceived behavioral control, and mathematics knowledge explained only 9% of the variance. Within the model, perceived behavioral control was a statistically significant, positive predictor of intentions to teach math. Findings are discussed in terms of statistical and practical significance, with specific recommendations for follow-up research exploring a wider breadth of variables potentially influencing intentions to teach math.
Students' Perceptions of School-Based Agricultural Education Through an Initial Early Field Experience
Authors: Rank Bryan D. , Smalley Scott W.
Published: October 2017

The purpose of this study was to identify the perception of students enrolled in an initial early field experience (EFE) in relation to the components of the agricultural education model. The students enrolled in the initial field experience were freshmen and sophomore students. The initial field experience course consisted of four face-to-face class meetings and a 12-hour initial field experience observation. Students’ photographed their perceptions of each component in the agricultural education model (classroom, SAE, FFA). The coding of reflective captions led to themes in three areas of the agricultural education model: (a) classroom themes were active learning, collaboration and facilities, (b) FFA themes were activities and opportunities, and (c) SAE themes were school based projects, awards/degrees, and the smallest circle. Overall, the EFE students used their photographs and descriptions to describe the learner-centered nature of the program. The EFE students described how the three components of the agricultural education model worked together to help school-based agricultural education (SBAE) students gain knowledge and experience. It is recommended that teacher educators incorporate photovoice in EFE programs to facilitate discussion of the initial perceptions of students.
Using Critical Thinking Styles of Opinion Leaders to Drive Extension Communication
Authors: Putnam Brianne B. , Lamm Alexa J. , Lundy Lisa K.
Published: October 2017

In order to address the complex challenges facing the agricultural and natural resource industry, extension educators must collaborate with opinion leaders. Extension educators can use the assistance of opinion leaders in program design and implementation in order to best meet the needs of stakeholders and the public. Collaboration between extension educators and opinion leaders is more easily conducted when each party understands one another’s cognitive style and communication channel preference. This study explored the relationship between opinion leader critical thinking style among three contextual issue groups in agriculture and natural resources and preferred communication preferences used by extension educators. The three contextual issue groups included opinion leaders from the areas of water, food safety, and genetic modification (GM). Researchers used the University of Florida Critical Thinking Inventory (UFCTI) to measure critical thinking style of 300 respondents in Florida. Each of the contextual issue groups preferred engagement with information as their preferred critical thinking style. Among the contextual issue groups, significant differences were identified between the water and food safety groups in the information seeking UFCTI score and the GM and food safety groups in the information engagement score. The preferred method of receiving information overall was visiting a website.
Merged SAGE II, Ozone_cci and OMPS ozone profile dataset and evaluation of ozone trends in the stratosphere
Authors: Sofieva Viktoria F. , Kyrölä Erkki , Laine Marko , Tamminen Johanna , Degenstein Doug , Bourassa Adam , Roth Chris , Zawada Daniel , Weber Mark , Rozanov Alexei , Rahpoe Nabiz , Stiller Gabriele , Laeng Alexandra , von Clarmann Thomas , Walker Kaley A. , Sheese Patrick , Hubert Daan , van Roozendael Michel , Zehner Claus , Damadeo Robert , Zawodny Joseph , Kramarova Natalya , Bhartia Pawan K.
Published: October 2017

Abstract. In this paper, we present a merged dataset of ozone profiles from several satellite instruments: SAGE II on ERBS, GOMOS, SCIAMACHY and MIPAS on Envisat, OSIRIS on Odin, ACE-FTS on SCISAT, and OMPS on Suomi-NPP. The merged dataset is created in the framework of the European Space Agency Climate Change Initiative (Ozone_cci) with the aim of analyzing stratospheric ozone trends. For the merged dataset, we used the latest versions of the original ozone datasets. The datasets from the individual instruments have been extensively validated and intercompared; only those datasets which are in good agreement, and do not exhibit significant drifts with respect to collocated ground-based observations and with respect to each other, are used for merging. The long-term SAGE–CCI–OMPS dataset is created by computation and merging of deseasonalized anomalies from individual instruments. The merged SAGE–CCI–OMPS dataset consists of deseasonalized anomalies of ozone in 10° latitude bands from 90° S to 90° N and from 10 to 50 km in steps of 1 km covering the period from October 1984 to July 2016. This newly created dataset is used for evaluating ozone trends in the stratosphere through multiple linear regression. Negative ozone trends in the upper stratosphere are observed before 1997 and positive trends are found after 1997. The upper stratospheric trends are statistically significant at midlatitudes and indicate ozone recovery, as expected from the decrease of stratospheric halogens that started in the middle of the 1990s and stratospheric cooling.
Simulation of fine organic aerosols in the western Mediterranean
area during the ChArMEx 2013 summer campaign
Authors: Cholakian Arineh , Beekmann Matthias , Colette Augustin , Coll Isabelle , Siour Guillaume , Sciare Jean , Marchand Nicolas , Couvidat Florian , Pey Jorge , Gros Valérie , Sauvage Stéphane , Michoud Vincent , Sellegri Karine , Colomb Aurélie , Sartelet Karine , Langley DeWitt Helen , Elser Miriam , Prévot André S. H. , Szidat Sonke , Dulac François
Published: October 2017

Abstract. The simulation of fine organic aerosols with CTMs (Chemistry Transport Models) in the western Mediterranean basin has not been studied until recently. The ChArMEx (the Chemistry-Aerosol Mediterranean Experiment) SOP 2 (Special Observation Period 2) intensive field campaign in summer of 2013 gathered a large and comprehensive dataset of observations allowing the study of different aspects of the Mediterranean atmosphere including the formation of organic aerosols (OA) in 3D models. In this study, we used the CHIMERE CTM to perform simulations for the duration of the SAFMED (Secondary Aerosol Formation in the MEDiterranean) period (July to August 2013) of this campaign. In particular, we evaluated four schemes for the simulation of OA, including the CHIMERE standard scheme, the VBS (Volatility Basis Set) standard scheme with two parameterizations including aging of biogenic secondary OA, and a modified version of the VBS scheme which includes fragmentation and formation of non-volatile OA. The results for these four schemes are compared to observations at two stations in the western Mediterranean basin, located in Cap Corse (Corsica) and Cap Es Pinar (Mallorca). These observations include OA mass concentration, PMF (positive matrix factorization) results of different OA fractions, and 14C observations showing the fossil or non-fossil origins of carbonaceous particles. It is concluded that the modified VBS scheme is close to observations in all three aspects mentioned above; the standard VBS scheme without BSOA (Biogenic Secondary Organic Aerosol) aging also has a satisfactory performance in simulating the mass concentration of OA, but not for the source origin analysis comparisons. In addition, the OA sources over the western Mediterranean basin are explored. OA shows a major biogenic origin, especially at several hundred meters height from the surface; however over the Gulf of Genoa near the surface, the anthropogenic origin is of similar importance. A general assessment of other species was performed to evaluate the robustness of the simulations for this particular domain before evaluating OA simulation schemes. It is also shown that the Cap Corse site presents important orographic complexity which makes comparison between model simulations and observations difficult. A method was designed to estimate an orographic representativeness error for a list of species and yields an uncertainty of between 50–85 % for primary pollutants, and around 2–10 % for secondary species, for these species model to observations comparisons are only little impacted by orography.
Consistency assessment of rating curve data in various locations using Bidirectional Reach (BReach)
Authors: Van Eerdenbrugh Katrien , Van Hoey Stijn , Coxon Gemma , Freer Jim , Verhoest Niko E. C.
Published: October 2017

Abstract. When estimating discharges through rating curves, temporal data consistency is a critical issue. In this research, consistency in stage–discharge data is investigated using a methodology called Bidirectional Reach (BReach), which departs from a (in operational hydrology) commonly used definition of consistency. A period is considered to be consistent if no consecutive and systematic deviations from a current situation occur that exceed observational uncertainty. Therefore, the capability of a rating curve model to describe a subset of the (chronologically sorted) data is assessed in each observation by indicating the outermost data points for which the rating curve model behaves satisfactorily. These points are called the maximum left or right reach, depending on the direction of the investigation. This temporal reach should not be confused with a spatial reach (indicating a part of a river). Changes in these reaches throughout the data series indicate possible changes in data consistency and if not resolved could introduce additional errors and biases. In this research, various measurement stations in the UK, New Zealand and Belgium are selected based on their significant historical ratings information and their specific characteristics related to data consistency. For each country, regional information is maximally used to estimate observational uncertainty. Based on this uncertainty, a BReach analysis is performed and, subsequently, results are validated against available knowledge about the history and behavior of the site. For all investigated cases, the methodology provides results that appear to be consistent with this knowledge of historical changes and thus facilitates a reliable assessment of (in)consistent periods in stage–discharge measurements. This assessment is not only useful for the analysis and determination of discharge time series, but also to enhance applications based on these data (e.g., by informing hydrological and hydraulic model evaluation design about consistent time periods to analyze).
TOWARDS AN INTEGRATION OF GIS AND BIM DATA: WHAT ARE THE GEOMETRIC
AND TOPOLOGICAL ISSUES?
Authors: Arroyo Ohori K. , Biljecki F. , Diakité A. , Krijnen T. , Ledoux H. , Stoter J.
Published: October 2017

Abstract. Geographic information and building information modelling both model buildings and infrastructure, but the way in which they are modelled is usually complimentary and BIM-GIS integration is widely considered as a way forward for both domains. For one, more detailed BIM data can feed more general GIS data and GIS data can provide the context that is necessary to BIM data. While previous studies have focused on the theoretical aspects of such an integration at a schema level, in this paper we focus on explaining the geometric and topological issues we have found while trying to develop software to realise such an integration in practice and at a data level. In our preliminary results, which are presented here, we have found that many issues for such an integration remain: handling the geometric and topological problems in BIM models, dealing with bad georeferencing and figuring out the best way to convert data between IFC and CityGML are all open issues.
SOLAR POTENTIAL ANALYSIS AND INTEGRATION OF THE TIME-DEPENDENT
SIMULATION RESULTS FOR SEMANTIC 3D CITY MODELS USING DYNAMIZERS
Authors: Chaturvedi K. , Willenborg B. , Sindram M. , Kolbe T. H.
Published: October 2017

Abstract. Semantic 3D city models play an important role in solving complex real-world problems and are being adopted by many cities around the world. A wide range of application and simulation scenarios directly benefit from the adoption of international standards such as CityGML. However, most of the simulations involve properties, whose values vary with respect to time, and the current generation semantic 3D city models do not support time-dependent properties explicitly. In this paper, the details of solar potential simulations are provided operating on the CityGML standard, assessing and estimating solar energy production for the roofs and facades of the 3D building objects in different ways. Furthermore, the paper demonstrates how the time-dependent simulation results are better-represented inline within 3D city models utilizing the so-called Dynamizer concept. This concept not only allows representing the simulation results in standardized ways, but also delivers a method to enhance static city models by such dynamic property values making the city models truly dynamic. The dynamizer concept has been implemented as an Application Domain Extension of the CityGML standard within the OGC Future City Pilot Phase 1. The results are given in this paper.
STOCHASTIC AND GEOMETRIC REASONING FOR INDOOR BUILDING MODELS
WITH ELECTRIC INSTALLATIONS – BRIDGING THE GAP BETWEEN GIS AND BIM
Authors: Dehbi Y. , Haunert J.-H. , Plümer L.
Published: October 2017

Abstract. 3D city and building models according to CityGML encode the geometry, represent the structure and model semantically relevant building parts such as doors, windows and balconies. Building information models support the building design, construction and the facility management. In contrast to CityGML, they include also objects which cannot be observed from the outside. The three dimensional indoor models characterize a missing link between both worlds. Their derivation, however, is expensive. The semantic automatic interpretation of 3D point clouds of indoor environments is a methodically demanding task. The data acquisition is costly and difficult. The laser scanners and image-based methods require the access to every room. Based on an approach which does not require an additional geometry acquisition of building indoors, we propose an attempt for filling the gaps between 3D building models and building information models. Based on sparse observations such as the building footprint and room areas, 3D indoor models are generated using combinatorial and stochastic reasoning. The derived models are expanded by a-priori not observable structures such as electric installation. Gaussian mixtures, linear and bi-linear constraints are used to represent the background knowledge and structural regularities. The derivation of hypothesised models is performed by stochastic reasoning using graphical models, Gauss-Markov models and MAP-estimators.
ABOUT THE SUBDIVISION OF INDOOR SPACES IN INDOORGML
Authors: Diakité A. A. , Zlatanova S. , Li K.-J.
Published: October 2017

Abstract. Boosted by the dynamic urbanization of cities, indoor environments are getting more and more complex in order to be able to host people properly. While most of our time is spent inside buildings, the need of GIS tools to assist our daily activities that can become tedious, such as indoor navigation or facility management, became more and more urgent. In that perspective, the IndoorGML standard is aiming to address the gaps left by other standards regarding the spatial modelling for indoor navigation. It includes several concepts such as the organization of the spaces into cells along with their network representation and the possibility to represent multiple connected layers. However, being at its first stage, several concepts of the standard could be improved. One of these is the cell subspacing that is not enough discussed in the current version of the standard. In this paper, we explore all the aspects involved in the subdivision process, from the identification of the navigable and non-navigable space cells to the generation of a navigation graph. We propose several criteria on which the indoor sub-spacing can rely to be automatically performed and and illustrate them on a 3D indoor model.
CITYBEM: AN OPEN SOURCE IMPLEMENTATION AND VALIDATION OF MONTHLY HEATING AND COOLING ENERGY NEEDS FOR 3D BUILDINGS IN CITIES
Authors: Murshed S. M. , Picard S. , Koch A.
Published: October 2017

Abstract. Cities play an important role in reaching local and global targets on energy efficiency and the reduction of greenhouse gas emissions. In order to determine the potential of energy efficiency in the building sector new planning instruments are required that allow depicting the complete building stock on the one hand and investigate detailed measures on the other hand. To pursue this objective, the ISO 13970:2008 monthly heating and cooling energy model is implemented using an open source based software architecture (CityBEM), in connection with data from 3D city models in the CityGML standard (LOD2). Input parameters such as the building geometry, typology and energy characteristics have been associated with the 3D data. The model has been applied to several urban districts with different numbers of buildings in the city of Karlsruhe. In order to test the accuracy of the implemented model and its robustness, a 3-step validation has been conducted. The comparison of simulation results with results based on a TRNSYS simulation showed acceptable results for the studied application cases. The proposed approach can help urban decision makers to perform a city or district wide analysis of the building energy need which can be further used to prepare future scenarios or renovation plans to support decision making.
TOWARDS A DECISION SUPPORT TOOL FOR 3D VISUALISATION:
APPLICATION TO SELECTIVITY PURPOSE OF SINGLE OBJECT IN A 3D CITY SCENE
Authors: Neuville R. , Pouliot J. , Poux F. , Hallot P. , De Rudder L. , Billen R.
Published: October 2017

Abstract. This paper deals with the establishment of a comprehensive methodological framework that defines 3D visualisation rules and its application in a decision support tool. Whilst the use of 3D models grows in many application fields, their visualisation remains challenging from the point of view of mapping and rendering aspects to be applied to suitability support the decision making process. Indeed, there exists a great number of 3D visualisation techniques but as far as we know, a decision support tool that facilitates the production of an efficient 3D visualisation is still missing. This is why a comprehensive methodological framework is proposed in order to build decision tables for specific data, tasks and contexts. Based on the second-order logic formalism, we define a set of functions and propositions among and between two collections of entities: on one hand static retinal variables (hue, size, shape…) and 3D environment parameters (directional lighting, shadow, haze…) and on the other hand their effect(s) regarding specific visual tasks. It enables to define 3D visualisation rules according to four categories: consequence, compatibility, potential incompatibility and incompatibility. In this paper, the application of the methodological framework is demonstrated for an urban visualisation at high density considering a specific set of entities. On the basis of our analysis and the results of many studies conducted in the 3D semiotics, which refers to the study of symbols and how they relay information, the truth values of propositions are determined. 3D visualisation rules are then extracted for the considered context and set of entities and are presented into a decision table with a colour coding. Finally, the decision table is implemented into a plugin developed with three.js, a cross-browser JavaScript library. The plugin consists of a sidebar and warning windows that help the designer in the use of a set of static retinal variables and 3D environment parameters.
SPATIO-SEMANTIC COMPARISON OF LARGE 3D CITY MODELS IN CITYGML
USING A GRAPH DATABASE
Authors: Nguyen S. H. , Yao Z. , Kolbe T. H.
Published: October 2017

Abstract. A city may have multiple CityGML documents recorded at different times or surveyed by different users. To analyse the city’s evolution over a given period of time, as well as to update or edit the city model without negating modifications made by other users, it is of utmost importance to first compare, detect and locate spatio-semantic changes between CityGML datasets. This is however difficult due to the fact that CityGML elements belong to a complex hierarchical structure containing multi-level deep associations, which can basically be considered as a graph. Moreover, CityGML allows multiple syntactic ways to define an object leading to syntactic ambiguities in the exchange format. Furthermore, CityGML is capable of including not only 3D urban objects’ graphical appearances but also their semantic properties. Since to date, no known algorithm is capable of detecting spatio-semantic changes in CityGML documents, a frequent approach is to replace the older models completely with the newer ones, which not only costs computational resources, but also loses track of collaborative and chronological changes. Thus, this research proposes an approach capable of comparing two arbitrarily large-sized CityGML documents on both semantic and geometric level. Detected deviations are then attached to their respective sources and can easily be retrieved on demand. As a result, updating a 3D city model using this approach is much more efficient as only real changes are committed. To achieve this, the research employs a graph database as the main data structure for storing and processing CityGML datasets in three major steps: mapping, matching and updating. The mapping process transforms input CityGML documents into respective graph representations. The matching process compares these graphs and attaches edit operations on the fly. Found changes can then be executed using the Web Feature Service (WFS), the standard interface for updating geographical features across the web.
UPSCALING OF SOLAR INDUCED CHLOROPHYLL FLUORESCENCE FROM LEAF TO CANOPY USING THE DART MODEL AND A REALISTIC 3D FOREST SCENE
Authors: Liu W. , Atherton J. , Mõttus M. , MacArthur A. , Teemu H. , Maseyk K. , Robinson I. , Honkavaara E. , Porcar-Castell A.
Published: October 2017

Abstract. Solar induced chlorophyll a fluorescence (SIF) has been shown to be an excellent proxy of photosynthesis at multiple scales. However, the mechanical linkages between fluorescence and photosynthesis at the leaf level cannot be directly applied at canopy or field scales, as the larger scale SIF emission depends on canopy structure. This is especially true for the forest canopies characterized by high horizontal and vertical heterogeneity. While most of the current studies on SIF radiative transfer in plant canopies are based on the assumption of a homogeneous canopy, recently codes have been developed capable of simulation of fluorescence signal in explicit 3-D forest canopies. Here we present a canopy SIF upscaling method consisting of the integration of the 3-D radiative transfer model DART and a 3-D object model BLENDER. Our aim was to better understand the effect of boreal forest canopy structure on SIF for a spatially explicit forest canopy.
RADIOMETRIC CORRECTION OF MULTITEMPORAL HYPERSPECTRAL UAS IMAGE MOSAICS OF SEEDLING STANDS
Authors: Markelin L. , Honkavaara E. , Näsi R. , Viljanen N. , Rosnell T. , Hakala T. , Vastaranta M. , Koivisto T. , Holopainen M.
Published: October 2017

Abstract. Novel miniaturized multi- and hyperspectral imaging sensors on board of unmanned aerial vehicles have recently shown great potential in various environmental monitoring and measuring tasks such as precision agriculture and forest management. These systems can be used to collect dense 3D point clouds and spectral information over small areas such as single forest stands or sample plots. Accurate radiometric processing and atmospheric correction is required when data sets from different dates and sensors, collected in varying illumination conditions, are combined. Performance of novel radiometric block adjustment method, developed at Finnish Geospatial Research Institute, is evaluated with multitemporal hyperspectral data set of seedling stands collected during spring and summer 2016. Illumination conditions during campaigns varied from bright to overcast. We use two different methods to produce homogenous image mosaics and hyperspectral point clouds: image-wise relative correction and image-wise relative correction with BRDF. Radiometric datasets are converted to reflectance using reference panels and changes in reflectance spectra is analysed. Tested methods improved image mosaic homogeneity by 5 % to 25 %. Results show that the evaluated method can produce consistent reflectance mosaics and reflectance spectra shape between different areas and dates.
CLUSTERING INCOMPLETE SPECTRAL DATA WITH ROBUST METHODS
Authors: Äyrämö S. , Pölönen I. , Eskelinen M. A.
Published: October 2017

Abstract. Missing value imputation is a common approach for preprocessing incomplete data sets. In case of data clustering, imputation methods may cause unexpected bias because they may change the underlying structure of the data. In order to avoid prior imputation of missing values the computational operations must be projected on the available data values. In this paper, we apply a robust nan-K-spatmed algorithm to the clustering problem on hyperspectral image data. Robust statistics, such as multivariate medians, are more insensitive to outliers than classical statistics relying on the Gaussian assumptions. They are, however, computationally more intractable due to the lack of closed-form solutions. We will compare robust clustering methods on the bands incomplete data cubes to standard K-means with full data cubes.
ASSESSMENT OF VARIOUS REMOTE SENSING TECHNOLOGIES IN BIOMASS AND NITROGEN CONTENT ESTIMATION USING AN AGRICULTURAL TEST FIELD
Authors: Näsi R. , Viljanen N. , Kaivosoja J. , Hakala T. , Pandžić M. , Markelin L. , Honkavaara E.
Published: October 2017

Abstract. Multispectral and hyperspectral imaging is usually acquired by satellite and aircraft platforms. Recently, miniaturized hyperspectral 2D frame cameras have showed great potential to precise agriculture estimations and they are feasible to combine with lightweight platforms, such as drones. Drone platform is a flexible tool for remote sensing applications with environment and agriculture. The assessment and comparison of different platforms such as satellite, aircraft and drones with different sensors, such as hyperspectral and RGB cameras is an important task in order to understand the potential of the data provided by these equipment and to select the most appropriate according to the user applications and requirements. In this context, open and permanent test fields are very significant and helpful experimental environment, since they provide a comparative data for different platforms, sensors and users, allowing multi-temporal analyses as well. Objective of this work was to investigate the feasibility of an open permanent test field in context of precision agriculture. Satellite (Sentinel-2), aircraft and drones with hyperspectral and RGB cameras were assessed in this study to estimate biomass, using linear regression models and in-situ samples. Spectral data and 3D information were used and compared in different combinations to investigate the quality of the models. The biomass estimation accuracies using linear regression models were better than 90 % for the drone based datasets. The results showed that the use of spectral and 3D features together improved the estimation model. However, estimation of nitrogen content was less accurate with the evaluated remote sensing sensors. The open and permanent test field showed to be suitable to provide an accurate and reliable reference data for the commercial users and farmers.
TREE STEM AND CANOPY BIOMASS ESTIMATES FROM TERRESTRIAL LASER SCANNING DATA
Authors: Olofsson K. , Holmgren J.
Published: October 2017

Abstract. In this study an automatic method for estimating both the tree stem and the tree canopy biomass is presented. The point cloud tree extraction techniques operate on TLS data and models the biomass using the estimated stem and canopy volume as independent variables. The regression model fit error is of the order of less than 5 kg, which gives a relative model error of about 5 % for the stem estimate and 10–15 % for the spruce and pine canopy biomass estimates. The canopy biomass estimate was improved by separating the models by tree species which indicates that the method is allometry dependent and that the regression models need to be recomputed for different areas with different climate and different vegetation.
PROCESSING CHAINS FOR DESIS AND ENMAP IMAGING SPECTROSCOPY DATA: SIMILARITIES AND DIFFERENCES
Authors: Storch T. , Müller R.
Published: October 2017

Abstract. The Earth Observation Center (EOC) of the German Aerospace Center (DLR) realizes operational processors for DESIS (DLR Earth Sensing Imaging Spectrometer) and EnMAP (Environmental Mapping and Analysis Program) high-resolution imaging spectroscopy remote sensing satellite missions. DESIS is planned to be launched in 2018 and EnMAP in 2020. The developmental (namely schedule, deployment, and team) and functional (namely processing levels, algorithms in processors, and archiving approaches) similarities and differences of the fully-automatic processors are analyzed. The processing chains generate high-quality standardized image products for users at different levels taking characterization and calibration data into account. EOC has long lasting experiences with the airborne and spaceborne acquisition, processing, and analysis of hyperspectral image data. It turns out that both activities strongly benefit from each other.
CHOOSING OF OPTIMAL REFERENCE SAMPLES FOR BOREAL LAKE CHLOROPHYLL A CONCENTRATION MODELING USING AERIAL HYPERSPECTRAL DATA
Authors: Erkkilä A.-L. , Pölönen I. , Lindfors A. , Honkavaara E. , Nurminen K. , Näsi R.
Published: October 2017

Abstract. Optical remote sensing has potential to overcome the limitations of point estimations of lake water quality by providing spatial and temporal information. In open ocean waters the optical properties are dominated by phytoplankton density, while the relationship between color and the constituents is more complicated in inland waters varying regionally and seasonally. Concerning the difficulties relating to comprehensive modeling of complex inland and coastal waters, the alternative approach is considered in this paper: the raw digital numbers (DN) recorded using aerial remote hyperspectral sensing are used without corrections and derived by means of regression modeling to predict Chlorophyll a (Chl-a) concentrations using in situ reference measurements. The target of this study is to estimate which number of local reference measurements is adequate for producing reliable statistical model to predict Chl-a concentration in complex lake water ecosystem. Based on the data collected from boreal lake Lohjanjärvi, the effect of standard deviation of Chl-a concentration of reference samples and their local clustering on predictability of model increases when number of reference samples or bands used as model variables decreases. However, the 2 or 3 band models are beneficial and more cost efficient when compared to 5 or 7 band models when the standard deviation of Chl-a concentration of reference samples is over certain level. The simple empirical approach combining remote sensing and traditional sampling may be feasible for regional and seasonal retrieval of Chl-a concentration distributions in complex ecosystems, where the comprehensive models are difficult or even impossible to derive.
REVISITING EXISTING CLASSIFICATION APPROACHES FOR BUILDING MATERIALS BASED ON HYPERSPECTRAL DATA
Authors: Ilehag R. , Weinmann M. , Schenk A. , Keller S. , Jutzi B. , Hinz S.
Published: October 2017

Abstract. Classification of materials found in urban areas using remote sensing, in particular with hyperspectral data, has in recent times increased in importance. This study is conducting classification of materials found on building using hyperspectral data, by using an existing spectral library and collected data acquired with a spectrometer. Two commonly used classification algorithms, Support Vector Machine and Random Forest, were used to classify the materials. In addition, dimensionality reduction and band selection were performed to determine if selected parts of the full spectral domain, such as the Short Wave Infra-Red domain, are sufficient to classify the different materials. We achieved the best classification results for the two datasets using dimensionality reduction based on a Principal Component Analysis in combination with a Random Forest classification. Classification using the full domain achieved the best results, followed by the Short Wave Infra-Red domain.
MEASURING LEAF WATER CONTENT USING MULTISPECTRAL TERRESTRIAL LASER SCANNING
Authors: Junttila S. , Vastaranta M. , Linnakoski R. , Sugano J. , Kaartinen H. , Kukko A. , Holopainen M. , Hyyppä H. , Hyyppä J.
Published: October 2017

Abstract. Climate change is increasing the amount and intensity of disturbance events, i.e. drought, pest insect outbreaks and fungal pathogens, in forests worldwide. Leaf water content (LWC) is an early indicator of tree stress that can be measured remotely using multispectral terrestrial laser scanning (MS-TLS). LWC affects leaf reflectance in the shortwave infrared spectrum which can be used to predict LWC from spatially explicit MS-TLS intensity data. Here, we investigated the relationship between LWC and MS-TLS intensity features at 690 nm, 905 nm and 1550 nm wavelengths with Norway spruce seedlings in greenhouse conditions. We found that a simple ratio of 905 nm and 1550 nm wavelengths was able to explain 84 % of the variation (R2) in LWC with a respective prediction accuracy of 0.0041 g/cm2. Our results showed that MS-TLS can be used to estimate LWC with a reasonable accuracy in environmentally stable conditions.
ACQUISITION AND PROCESSING OF HIGH RESOLUTION HYPERSPECTRAL
IMAGERIES FOR THE 3D MAPPING OF URBAN HEAT ISLANDS AND
MICROPARTICLES OF MONTREAL
Authors: Mongeau R. , Baudouin Y. , Cavayas F.
Published: October 2017

Abstract. Ville de Montreal wanted to develop a system to identify heat islands and microparticles at the urban scale and to study their formation. UQAM and UdeM universities have joined their expertise under the framework "Observatoire Spatial Urbain" to create a representative geospatial database of thermal and atmospheric parameters collected during the summer months. They innovated in the development of a methodology for processing high resolution hyperspectral images (1–2 m). In partnership with Ville de Montreal, they integrated 3D geospatial data (topography, transportation and meteorology) in the process. The 3D mapping of intraurban heat islands as well as air micro-particles makes it possible, initially, to identify the problematic situations for future civil protection interventions during extreme heat. Moreover, it will be used as a reference for the Ville de Montreal to establish a strategy for public domain tree planting and in the analysis of urban development projects.