scholarly journals A SVR Learning Based Sensor Placement Approach for Nonlinear Spatially Distributed Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-12
Author(s):  
Xian-xia Zhang ◽  
Zhi-qiang Fu ◽  
Wei-lu Shan ◽  
Bing Wang ◽  
Tao Zou
Keyword(s):  
Spatial Distribution ◽  
Distributed Systems ◽  
Spatial Data ◽  
Sensor Placement ◽  
Spatiotemporal Data ◽  
Industrial Processes ◽  
Crucial Issue ◽  
Data Set ◽  
Spatially Distributed ◽  
Optimal Sensor Location

Many industrial processes are inherently distributed in space and time and are called spatially distributed dynamical systems (SDDSs). Sensor placement affects capturing the spatial distribution and then becomes crucial issue to model or control an SDDS. In this study, a new data-driven based sensor placement method is developed. SVR algorithm is innovatively used to extract the characteristics of spatial distribution from a spatiotemporal data set. The support vectors learned by SVR represent the crucial spatial data structure in the spatiotemporal data set, which can be employed to determine optimal sensor location and sensor number. A systematic sensor placement design scheme in three steps (data collection, SVR learning, and sensor locating) is developed for an easy implementation. Finally, effectiveness of the proposed sensor placement scheme is validated on two spatiotemporal 3D fuzzy controlled spatially distributed systems.

scholarly journals Location Matters: A Framework to Investigate the Spatial Characteristics of Distributed Flood Attenuation

Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2706
Author(s):  
Federico Antolini ◽  
Eric Tate
Keyword(s):  
Spatial Distribution ◽  
Distributed Systems ◽  
Green Infrastructure ◽  
Multiple Scales ◽  
Flood Management ◽  
Ability To Work ◽  
Catchment Scale ◽  
Flood Magnitude ◽  
Spatially Distributed ◽  
Flood Attenuation

Distributed attenuation in flood management relies on small and low-impact runoff attenuating features variously distributed within a catchment. Distributed systems of reservoirs, natural flood management, and green infrastructure are practical examples of distributed attenuation. The effectiveness of attenuating features lies in their ability to work in concert, by reducing and slowing runoff in strategic parts of the catchment, and desynchronizing flows. The spatial distribution of attenuating features plays an essential role in the process. This article proposes a framework to place features in a hydrologic network, group them into spatially distributed systems, and analyze their flood attenuation effects. The framework is applied to study distributed systems of reservoirs in a rural watershed in Iowa, USA. The results show that distributed attenuation can be an effective alternative to a single centralized flood mitigation approach. The different flow peak attenuation of considered distributed systems suggest that the spatial distribution of features significantly influences flood magnitude at the catchment scale. The proposed framework can be applied to examine the effectiveness of distributed attenuation, and its viability as a widespread flood attenuation strategy in different landscapes and at multiple scales.

scholarly journals The analysis of relationships between annual precipitation and relief and landscape characteristics in the Carpathian region of Ukraine

2015 ◽  
pp. 224-229
Author(s):  
Oleksandr Mkrtchian ◽  
Pavlo Shuber
Keyword(s):  
Spatial Distribution ◽  
Multiple Regression ◽  
Spatial Data ◽  
Annual Precipitation ◽  
P Value ◽  
Landscape Characteristics ◽  
Carpathian Region ◽  
Spatially Distributed ◽  
Terrain Roughness ◽  
The Impact

The paper deals with the statistical analysis of relationships between the spatial distribution of precipitation values in the Carpathian region of Ukraine and the spatially distributed relief and landscape parameters. Processed data of 20 weather stations have been a data source of annual precipitation data for 1961–1991 period, while SRTM elevation dataset has been used as a source of spatial data on relief parameters. Step-wise multiple regression has revealed the set of parameters manifesting the strongest relationship with the precipitation distribution. This set includes following parameters: terrain roughness, local and focal elevation, and aspect factor for NW/SE direction; the overall relationship is highly statistically significant. The terrain roughness has appeared to be the single parameter with the strongest effect on precipitation values, followed by the local and focal elevation and the aspect factor. ANOVA results were much more modest in comparison with the multiple regression, suggesting that the quantitative spatial modeling, which uses relief parameters as predictors, produces much more reliable predictions of the precipitation spatial distribution than just averaging the precipitation values round the delineated natural regions. ANCOVA results show that the interaction between the quantitative and numerical predictors is statistically significant with the p-value of less than 0.01, suggesting that belonging to natural regions can moderate the impact of quantitative relief parameters. Thus considering the belonging to natural regions significantly improves the final prediction, when used in addition to numerical relief parameters. Key words: annual precipitation, climatic mapping, multiple regression, ANOVA, AVCOVA.

scholarly journals Do galactic bars depend on environment?: an information theoretic analysis of Galaxy Zoo 2

2020 ◽  
Vol 501 (1) ◽  
pp. 994-1001
Author(s):  
Suman Sarkar ◽  
Biswajit Pandey ◽  
Snehasish Bhattacharjee
Keyword(s):  
Spatial Distribution ◽  
Mutual Information ◽  
Local Density ◽  
Statistical Significance ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Host Galaxy ◽  
Data Sets ◽  
Data Set ◽  
Information Theoretic

ABSTRACT We use an information theoretic framework to analyse data from the Galaxy Zoo 2 project and study if there are any statistically significant correlations between the presence of bars in spiral galaxies and their environment. We measure the mutual information between the barredness of galaxies and their environments in a volume limited sample (Mr ≤ −21) and compare it with the same in data sets where (i) the bar/unbar classifications are randomized and (ii) the spatial distribution of galaxies are shuffled on different length scales. We assess the statistical significance of the differences in the mutual information using a t-test and find that both randomization of morphological classifications and shuffling of spatial distribution do not alter the mutual information in a statistically significant way. The non-zero mutual information between the barredness and environment arises due to the finite and discrete nature of the data set that can be entirely explained by mock Poisson distributions. We also separately compare the cumulative distribution functions of the barred and unbarred galaxies as a function of their local density. Using a Kolmogorov–Smirnov test, we find that the null hypothesis cannot be rejected even at $75{{\ \rm per\ cent}}$ confidence level. Our analysis indicates that environments do not play a significant role in the formation of a bar, which is largely determined by the internal processes of the host galaxy.

scholarly journals Spatial Agglomeration of China’s Forest Products Manufacturing Industry: Measurement, Characteristics and Determinants

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1006
Author(s):  
Zhenhuan Chen ◽  
Hongge Zhu ◽  
Wencheng Zhao ◽  
Menghan Zhao ◽  
Yutong Zhang
Keyword(s):  
Spatial Distribution ◽  
Spatial Data ◽  
Large Scale ◽  
Manufacturing Industry ◽  
Economies Of Scale ◽  
Forest Products ◽  
Spatial Data Analysis ◽  
Forest Protection ◽  
Spatial Agglomeration ◽  
Continuous Space

China’s forest products manufacturing industry is experiencing the dual pressure of forest protection policies and wood scarcity and, therefore, it is of great significance to reveal the spatial agglomeration characteristics and evolution drivers of this industry to enhance its sustainable development. Based on the perspective of large-scale agglomeration in a continuous space, in this study, we used the spatial Gini coefficient and standard deviation ellipse method to investigate the spatial agglomeration degree and location distribution characteristics of China’s forest products manufacturing industry, and we used exploratory spatial data analysis to investigate its spatial agglomeration pattern. The results show that: (1) From 1988 to 2018, the degree of spatial agglomeration of China’s forest products manufacturing industry was relatively low, and the industry was characterized by a very pronounced imbalance in its spatial distribution. (2) The industry has a very clear core–periphery structure, the spatial distribution exhibits a “northeast-southwest” pattern, and the barycenter of the industrial distribution has tended to move south. (3) The industry mainly has a high–high and low–low spatial agglomeration pattern. The provinces with high–high agglomeration are few and concentrated in the southeast coastal area. (4) The spatial agglomeration and evolution characteristics of China’s forest products manufacturing industry may be simultaneously affected by forest protection policies, sources of raw materials, international trade and the degree of marketization. In the future, China’s forest products manufacturing industry should further increase the level of spatial agglomeration to fully realize the economies of scale.

scholarly journals THE CULTURAL HERITAGE SPATIAL DATA SET OF KLAIPĖDA OLD TOWN / SAUGOMŲ KLAIPĖDOS SENAMIESČIO OBJEKTŲ ERDVINIŲ DUOMENŲ RINKINYS / НАБОР ПРОСТРАНСТВЕННЫХ ДАННЫХ ОХРАНЯЕМЫХ ОБЪЕКТОВ СТАРОГО ГОРОДА КЛАЙПЕДЫ

2012 ◽  
Vol 37 (4) ◽  
pp. 172-176
Author(s):  
Lina Kuklienė ◽  
Dainora Jankauskienė ◽  
Indrius Kuklys
Keyword(s):  
Cultural Heritage ◽  
Spatial Data ◽  
Road Construction ◽  
Heritage Management ◽  
Data Set ◽  
Management Planning ◽  
Cultural Heritage Management ◽  
Input Devices ◽  
Relevant Point ◽  
Cultural Heritage Objects

The purpose of the thesis is to analyze the main geodetic databases of Lithuania and to create a geodetic database of cultural heritage objects in Klaipėda using program ArcGIS 9.3. The problem is that the geodetic database storing graphical and attributive information about cultural heritage in Klaipeda city has not been created yet. Thus, in order to incorporate GIS technologies into the management of cultural heritage, starting the creation of such a database seems to be a relevant point. The fully completed and regularly updated geodetic database can be used for cultural heritage management, planning, design, road construction, etc. Therefore, the following objectives have been set: 1) describing geo-data collection and input devices; 2) stimulating the geodetic database that introduces information about buildings, building complexes, cemeteries, locations of archaeological and cultural heritage; 3) giving a detailed description of the database creation process; 4) analyzing the need for establishing a geodetic database of cultural heritage objects in Klaipėda. Santrauka Lietuvoje GIS pagrindu sukurta daug įvairiems tikslams skirtų georeferencinių bei teminių erdvinių duomenų rinkinių. Viena iš šių rinkinių panaudojimo sričių – valstybės registruose esančių duomenų kaupimas. Tokiu principu yra sukurta Kultūros vertybių registro duomenų bazė, kurios pagrindiniai duomenys buvo panaudoti kuriant Klaipėdos miesto kultūros paveldo objektų erdvinių duomenų rinkinį. Siekiant kuo operatyviau įtraukti GIS technologijas į kultūros paveldo objektų tvarkybą, aktualu Klaipėdoje pradėti kurti kultūros paveldo objektų erdvinių duomenų rinkinį. Nuolat atnaujinamas erdvinių duomenų rinkinys palengvins įvairių sričių specialistų atliekamus kultūros paveldo objektų administravimo, teritorijų planavimo, projektavimo, kelių tiesimo ir kitus darbus. Резюме В Литве на основе ГИС для различных целей создано множество гео-ссылок, а также тематических наборов пространственных данных. Область использования одного из множеств – сбор данных, имеющихся в государственном учете. По такому принципу создана регистрационная база культурных ценностей, основные данные которой были использованы при создании набора пространственных данных объектов культурного наследия города Клайпеды. С целью оперативно обеспечить управление объектами культурного наследия технологиями ГИС следует начать создание набора пространственных данных объектов культурного наследия в Клайпеде. Полностью заполненный и постоянно обновляемый набор пространственных данных облегчит работу специалистов в различных областях: администрировании объектов культурного наследия, планировании территорий, проектировании, строительстве дорог и других.

scholarly journals Leveraging Road Characteristics and Contributor Behaviour for Assessing Road Type Quality in OSM

2021 ◽  
Vol 10 (7) ◽  
pp. 436
Author(s):  
Amerah Alghanim ◽  
Musfira Jilani ◽  
Michela Bertolotto ◽  
Gavin McArdle
Keyword(s):  
Machine Learning ◽  
Spatial Data ◽  
Classification Accuracy ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Data Set ◽  
Semantic Inference ◽  
Road Type ◽  
The Impact

Volunteered Geographic Information (VGI) is often collected by non-expert users. This raises concerns about the quality and veracity of such data. There has been much effort to understand and quantify the quality of VGI. Extrinsic measures which compare VGI to authoritative data sources such as National Mapping Agencies are common but the cost and slow update frequency of such data hinder the task. On the other hand, intrinsic measures which compare the data to heuristics or models built from the VGI data are becoming increasingly popular. Supervised machine learning techniques are particularly suitable for intrinsic measures of quality where they can infer and predict the properties of spatial data. In this article we are interested in assessing the quality of semantic information, such as the road type, associated with data in OpenStreetMap (OSM). We have developed a machine learning approach which utilises new intrinsic input features collected from the VGI dataset. Specifically, using our proposed novel approach we obtained an average classification accuracy of 84.12%. This result outperforms existing techniques on the same semantic inference task. The trustworthiness of the data used for developing and training machine learning models is important. To address this issue we have also developed a new measure for this using direct and indirect characteristics of OSM data such as its edit history along with an assessment of the users who contributed the data. An evaluation of the impact of data determined to be trustworthy within the machine learning model shows that the trusted data collected with the new approach improves the prediction accuracy of our machine learning technique. Specifically, our results demonstrate that the classification accuracy of our developed model is 87.75% when applied to a trusted dataset and 57.98% when applied to an untrusted dataset. Consequently, such results can be used to assess the quality of OSM and suggest improvements to the data set.

scholarly journals TNO-MACC_II emission inventory; a multi-year (2003–2009) consistent high-resolution European emission inventory for air quality modelling

2014 ◽  
Vol 14 (20) ◽  
pp. 10963-10976 ◽  
Author(s):  
J. J. P. Kuenen ◽  
A. J. H. Visschedijk ◽  
M. Jozwicka ◽  
H. A. C. Denier van der Gon
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
High Resolution ◽  
Emission Inventory ◽  
Point Sources ◽  
Air Quality Modelling ◽  
Emission Data ◽  
Data Set ◽  
Spatially Distributed ◽  
Reported Data

Abstract. Emissions to air are reported by countries to EMEP. The emissions data are used for country compliance checking with EU emission ceilings and associated emission reductions. The emissions data are also necessary as input for air quality modelling. The quality of these "official" emissions varies across Europe. As alternative to these official emissions, a spatially explicit high-resolution emission inventory (7 × 7 km) for UNECE-Europe for all years between 2003 and 2009 for the main air pollutants was made. The primary goal was to supply air quality modellers with the input they need. The inventory was constructed by using the reported emission national totals by sector where the quality is sufficient. The reported data were analysed by sector in detail, and completed with alternative emission estimates as needed. This resulted in a complete emission inventory for all countries. For particulate matter, for each source emissions have been split in coarse and fine particulate matter, and further disaggregated to EC, OC, SO4, Na and other minerals using fractions based on the literature. Doing this at the most detailed sectoral level in the database implies that a consistent set was obtained across Europe. This allows better comparisons with observational data which can, through feedback, help to further identify uncertain sources and/or support emission inventory improvements for this highly uncertain pollutant. The resulting emission data set was spatially distributed consistently across all countries by using proxy parameters. Point sources were spatially distributed using the specific location of the point source. The spatial distribution for the point sources was made year-specific. The TNO-MACC_II is an update of the TNO-MACC emission data set. Major updates included the time extension towards 2009, use of the latest available reported data (including updates and corrections made until early 2012) and updates in distribution maps.

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