scholarly journals POSSIBILITIES OF UPDATING SMALL-SCALE BASIC SPATIAL DATA IN LITHUANIA USING GENERALIZATION METHODS / LIETUVOS SMULKIOJO MASTELIO BAZINIŲ ERDVINIŲ DUOMENŲ ATNAUJINIMO GALIMYBĖS TAIKANT APIBENDRINAMUOSIUS METODUS / ВОЗМОЖНОСТИ ОБНОВЛЕНИЯ МЕЛКОМАСШТАБНЫХ ЛИТОВСКИХ БАЗОВЫХ ПРОСТРАНСТВЕННЫХ ДАННЫХ С ИСПОЛЬЗОВАНИЕМ МЕТОДОВ ГЕНЕРАЛИЗАЦИИ

2012 ◽  
Vol 37 (4) ◽  
pp. 143-148 ◽  
Author(s):  
Lina Papšienė ◽  
Kęstutis Papšys
Keyword(s):  
Spatial Data ◽  
Spatial Information ◽  
Professional Preparation ◽  
Small Scale ◽  
Minimum Length ◽  
Data Sets ◽  
Object A ◽  
Topological Characteristics ◽  
Transfer Of Information ◽  
Scale Data

Small-scale spatial data are widely used at regional and national levels not only for mapping but also for the purposes of planning, forecasting, etc. Therefore, a professional preparation of such data is necessary. The generalization of large or medium scale spatial data is the most efficient process to produce and update smaller-scale data. Certainly, a simple transfer of information is almost never suitable to satisfy requirements for small-scale maps. Additional transformations (generalization) are necessary. Spatial information complexity may be significantly reduced in terms of the number of objects, geometry, etc. However, the main spatial, non-spatial and topological characteristics of the objects have to be preserved. The process of reduction is irreversible, and therefore it is necessary at first to clearly define requirements for spatial data (for example, the density of spatial objects, the minimal allowed area, the width and length of an object, a minimum length of the edge of an object, spatial links between the objects). The above imposed requirements provide a possibility of defining procedures for generalization and a conceptual model between particular data sets. Santrauka Regioniniu ir valstybiniu lygmeniu smulkiojo mastelio erdvinai duomenys plačiai naudojami ne tik rengiant žemelapius, bet ir vertinant aplinkos sąlygas atliekant planavimą, prognozavimą ir kt. Taigi šie erdviniai duomenys turi būti parengti profesionaliai. Stambiojo ir vidutinio mastelio erdvinių duomenų kartografinis apibendrinimas yra efektyviausias procesas kuriant ir atnaujinant smulkesnio mastelio erdvinius duomenis. Kadangi atliekant elementarųjį informacijos perkelimą gaunami erdviniai duomenys dažnai neatitinka smulkiojo mastelio žemelapiams keliamų reikalavimų, būtinos papildomos transformacijos. Erdvinė informacija kartografinio apibendrinimo procese gali būti žymiai supaprastinta mažinant objektų, supaprastinant jų geometriją ir pan., tačiau vis dėlto išlaikant pagrindines objektų erdvines, neerdvines ir topologines charakteristikas. Kadangi toks apibendrinimo procesas negrįžtamas, pirmiausia būtina aiškiai nustatyti, kokius reikalavimus turi atitikti smulkiojo mastelio erdviniai duomenys (pavyzdžiui, erdvinių objektų tankumas, mažiausias leidžiamasis objekto plotas, plotis ir ilgis, mažiausias objekto kraštines ilgis, erdviniai objektų ryšiai). Numačius šiuos reikalavimus, galima aprašyti procedūras ir sudaryti koncepcinį modelį konkrečiam erdviniam duomenų rinkiniui apibendrinti. Резюме Мелкомасштабные пространственные данные широко используются на региональном и национальном уровне не только для отображения, но и для оценки состояния окружающей среды в целях планирования, прогнозирования и т. д. Поэтому такие данные должны быть подготовлены профессионально. Генерализация пространственных данных крупного или среднего масштаба является наиболее эффективным процессом для получения и обновления данных меньшего масштаба. Безусловно, элементарная передача информации зачастую не удовлетворяет требований мелкомасштабных карт. Необходимы дополнительные трансформации (генерализация). В процессе генерализации сложность пространственной информации может быть значительно уменьшена благодаря уменьшению количества объектов, упрощению геометрии и т. д. Однако основные пространственные, непространственные и топологические характеристики объекта должны быть сохранены. Процесс генерализации необратим, поэтому вначале необходимо четко определить требования, предъявляемые к пространственным данным (например, плотность объектов, минимально допустимая площадь, ширина и длина объекта, минимальная длина стороны объекта, пространственные связи между объектами). С учетом этих требований можно определить процедуры генерализации и концептуальную модель для конкретного набора данных.

Four planes of social being: more connections

2021 ◽  
pp. 127-144
Author(s):  
Priscilla Alderson
Keyword(s):  
Social Relations ◽  
Interdisciplinary Research ◽  
Policy Making ◽  
Interpersonal Relations ◽  
Oil Spills ◽  
Small Scale ◽  
Data Sets ◽  
Mortality And Morbidity ◽  
Critical Realist ◽  
Scale Data

Adverse mortality and morbidity effects of the huge oil spills in Bayelsa State, Niger Delta, illustrate the value of critical realism’s four planes of social being for organising complex findings and for combining large- and small-scale data sets. These planes cover every aspect of being human: bodies in relation to nature; interpersonal relations; larger social relations and structures; and inner human being in the mental-social-embodied personality. Chapter 5 also considers critical realist approaches to managing data-analysis: laminated systems analysis; interdisciplinary research and policy-making; critical realist theories about interdisciplinarity; overcoming barriers to interdisciplinarity, and interdisciplinary commitments. The detailed examples are about improving the physical health of people with a diagnosis of serious mental illness, and feminist-informed counselling after sexual assault.

From CAD to GIS to the Geoweb: A Natural Evolution

2010 ◽  
Author(s):  
Steve Adam
Keyword(s):  
Decision Making ◽  
Spatial Data ◽  
Oil And Gas ◽  
Spatial Information ◽  
Digital Data ◽  
Computer Hardware ◽  
Disruptive Technology ◽  
Data Sets ◽  
Spatial Data Sets ◽  
Pipeline Design

Computer hardware and software have played a significant role in supporting the design and maintenance of pipeline systems. CAD systems allowed designers and drafters to compile drawings and make edits at a pace unmatched by manual pen drawings. Although CAD continues to provide the environment for a lot of pipeline design, Geographic Information Systems (GIS) are also innovating pipeline design through routines such as automated alignment sheet generation. What we have seen over the past two or three decades is an evolution in how we manage the data and information required for decision making in pipeline design and system operation. CAD provided designers and engineers a rapid electronic method for capturing information in a drawing, editing it, and sharing it. As the amount of digital data available to users grows rapidly, CAD has been unable to adequately exploit data’s abundance and managing change in a CAD environment is cumbersome. GIS and spatial data management have proven to be the next evolution in situations where engineering, integrity, environmental, and other spatial data sets dominate the information required for design and operational decision making. It is conceivable that GIS too will crumble under the weight of its own data usage as centralized databases become larger and larger. The Geoweb is likely to emerge as the geospatial world’s evolution. The Geoweb implies the merging of spatial information with the abstract information that currently dominates the Internet. This paper and presentation will discuss this fascinating innovation, it’s force as a disruptive technology, and oil and gas applications.

IMPACT ANALYSIS OF THE INSPIRE DIRECTIVE ON LAND-USE PLANNING PUBLICATION AND DEVELOPMENT

2017 ◽  
Vol 165 (45) ◽  
pp. 76-85
Author(s):  
WALDEMAR IZDEBSKI ◽  
ZBIGNIEW MALINOWSKI
Keyword(s):  
Land Use ◽  
Land Use Planning ◽  
Spatial Data ◽  
Local Governments ◽  
Impact Analysis ◽  
Spatial Information ◽  
Technological Development ◽  
Data Sets ◽  
Gis Technology ◽  
Spatial Data Sets

The INSPIRE Directive went into force in May 2007 and it resulted in changing the way of thinking about spatial data in local government. Transposition of the Directive on Polish legislation is the Law on spatial information infrastructure from 4 March 2010., which indicates the need for computerization of spatial data sets (including land-use planning). This act resulted in an intensification of thinking about the computerization of spatial data, but, according to the authors, the needs and aspirations of the digital land-use planning crystallized already before the INSPIRE Directive and were the result of technological development and increasing the awareness of users. The authors analyze the current state of land-use planning data computerization in local governments. The analysis was conducted on a group of more than 1,700 local governments, which are users of spatial data management (GIS) technology eGmina.

Apple Disease Recognition Based on Small-scale Data Sets

2021 ◽  
Vol 37 (3) ◽  
pp. 481-490
Author(s):  
Chenyong Song ◽  
Dongwei Wang ◽  
Haoran Bai ◽  
Weihao Sun
Keyword(s):  
Identification Accuracy ◽  
Model Complexity ◽  
Geometric Transformation ◽  
Small Scale ◽  
Model Parameters ◽  
Data Sets ◽  
List Type ◽  
Data Set ◽  
Disease Identification ◽  
Scale Data

HighlightsThe proposed data enhancement method can be used for small-scale data sets with rich sample image features.The accuracy of the new model reaches 98.5%, which is better than the traditional CNN method.Abstract: GoogLeNet offers far better performance in identifying apple disease compared to traditional methods. However, the complexity of GoogLeNet is relatively high. For small volumes of data, GoogLeNet does not achieve the same performance as it does with large-scale data. We propose a new apple disease identification model using GoogLeNet’s inception module. The model adopts a variety of methods to optimize its generalization ability. First, geometric transformation and image modification of data enhancement methods (including rotation, scaling, noise interference, random elimination, color space enhancement) and random probability and appropriate combination of strategies are used to amplify the data set. Second, we employ a deep convolution generative adversarial network (DCGAN) to enhance the richness of generated images by increasing the diversity of the noise distribution of the generator. Finally, we optimize the GoogLeNet model structure to reduce model complexity and model parameters, making it more suitable for identifying apple tree diseases. The experimental results show that our approach quickly detects and classifies apple diseases including rust, spotted leaf disease, and anthrax. It outperforms the original GoogLeNet in recognition accuracy and model size, with identification accuracy reaching 98.5%, making it a feasible method for apple disease classification. Keywords: Apple disease identification, Data enhancement, DCGAN, GoogLeNet.

5. Calibrating Measures of Family Activities between Large- and Small-Scale Data Sets

2007 ◽  
Vol 37 (1) ◽  
pp. 119-149 ◽  
Author(s):  
Nora Broege ◽  
Ann Owens ◽  
Anthony P. Graesch ◽  
Jeanne E. Arnold ◽  
Barbara Schneider
Keyword(s):  
Leisure Activities ◽  
National Sample ◽  
Small Scale ◽  
Data Sets ◽  
Large N ◽  
Combining Data ◽  
Working Families ◽  
Collection Methods ◽  
Scale Data ◽  
Combined Data

Two studies of working families are combined to demonstrate a strategy for producing reliable estimates from the combination of self-reported (large N) and observational (small N) data. Both studies examine where and how dual-career families spend time at home. The 500 Family Study is sociological and uses self-reported time diary data from a national sample; the CELF study is anthropological and uses observational scan sampling data from a regional sample of 32 families. The data are combined as if they constitute one sample, and an analytic solution for establishing the reliability of the resulting composite estimates of time use is provided. Merging the data sets provides validation for each study, neither of which is without potential methodological weaknesses. The advantages of combining data from the independent data collection methods are discussed, and selected substantive findings on families' activities are highlighted, illustrating similarities and differences between findings in the independent and combined data sets. Results show that working families spend significant time in a small spectrum of home spaces, particularly kitchens and living rooms, with leisure activities prevailing, but mothers, fathers, and children differ in where and how they spend their time. Overall, a template for merging data from different disciplines and methods is provided.

scholarly journals Multiscale Feature Model for Terrain Data Based on Adaptive Spatial Neighborhood

2013 ◽  
Vol 2013 ◽  
pp. 1-12
Author(s):  
Huijie Zhang ◽  
Yun Ma ◽  
Zhiqiang Ma ◽  
Xinting He ◽  
Yaxin Liu ◽  
...  
Keyword(s):  
Spatial Data ◽  
Large Scale ◽  
Feature Model ◽  
Data Sets ◽  
Scheduling Problems ◽  
Hilbert Curve ◽  
Data Scheduling ◽  
Large Scale Data ◽  
Schedule Time ◽  
Scale Data

Multiresolution hierarchy based on features (FMRH) has been applied in the field of terrain modeling and obtained significant results in real engineering. However, it is difficult to schedule multiresolution data in FMRH from external memory. This paper proposed new multiscale feature model and related strategies to cluster spatial data blocks and solve the scheduling problems of FMRH using spatial neighborhood. In the model, the nodes with similar error in the different layers should be in one cluster. On this basis, a space index algorithm for each cluster guided by Hilbert curve is proposed. It ensures that multi-resolution terrain data can be loaded without traversing the whole FMRH; therefore, the efficiency of data scheduling is improved. Moreover, a spatial closeness theorem of cluster is put forward and is also proved. It guarantees that the union of data blocks composites a whole terrain without any data loss. Finally, experiments have been carried out on many different large scale data sets, and the results demonstrate that the schedule time is shortened and the efficiency of I/O operation is apparently improved, which is important in real engineering.

Online teaching quality evaluation model based on support vector machine and decision tree

2020 ◽  
pp. 1-11
Author(s):  
Jingwen Hou
Keyword(s):  
Online Teaching ◽  
Large Scale ◽  
Quality Evaluation ◽  
Dimensional Space ◽  
Teaching Quality ◽  
Support Vector ◽  
Small Scale ◽  
Data Sets ◽  
Large Scale Data ◽  
Scale Data

At present, online education evaluation models are insufficient when dealing with small-scale evaluation data sets. In order to discriminate the learner’s learning state, this paper further studies online teaching machine learning methods, and introduces adaptive learning rate and momentum terms to improve the gradient descent method of BP neural network to improve the convergence rate of the model. Moreover, this study proposes a deep neural network model to deal with complex high-dimensional large-scale data set problems. In the process of supervised prediction, this study uses support vector regression as a predictor for supervised prediction, and this study maps complex non-linear relationships into high-dimensional space to achieve a linear relationship similar to low-dimensional space. In addition, in this study, small-scale teaching quality evaluation data sets and large-scale data sets are input into the model to perform experiments. Finally, the model proposed in this study is compared with other shallow models. The results show that the model proposed in this research is effective and advantageous in evaluating teaching quality in universities and processing large-scale data sets.

Research on the Location of Fire Station Based on GIS and GA

2011 ◽  
Vol 130-134 ◽  
pp. 377-380
Author(s):  
Wei Zhang ◽  
Jun Cheng Jiang
Keyword(s):  
Spatial Data ◽  
Site Selection ◽  
Small Scale ◽  
Data Set ◽  
C Language ◽  
Urban Fire ◽  
Fire Station ◽  
Fire Planning ◽  
Massive Spatial Data ◽  
Scale Data

To locate the fire station under a prescribed period is of strategic significance in the urban fire planning. On the .Net platform, integrate the Genetic Algorithm and Geographic Information System (GIS) via the C# language to resolve the complicated issue of the spatial site selection. The GIS spatial data will be imported to the module first. Then on the basis of both the spatial analysis feature and the network analysis feature of GIS, calculate the individual’s fitness in the process of the genetic evolution. The Conventional coding approach is generally utilized to optimize the small-scale data set. However, to meet the search requirements in the massive spatial data of GIS, the object oriented coding approach is designed in the module. It is indicated that the entire module is able to resolve the site selection issue of the urban fire station properly, which meets the quick response’s requirements.

scholarly journals Analysis of the availability of spatial datasets defined by the 3rd annex of the INSPIRE directive in Poland

2020 ◽  
Vol 19 ◽  
pp. 49-58
Author(s):  
Artur Krawczyk
Keyword(s):  
Environmental Policy ◽  
Public Administration ◽  
Service Provider ◽  
Spatial Data ◽  
Spatial Information ◽  
Open Data ◽  
Environmental Engineering ◽  
Data Sets ◽  
Digital Maps ◽  
Eu Directive

The article describes changes in the usage of spatial information taking place in the field of environmental engineering and protection over the last 20 years when the analogue maps have been phased out in favour of digital maps. The importance of EU INSPIRE Directive for the popularization of the services for sharing spatial data in order to adopt an environmental policy implemented under the “environmental” EU Directive is discussed. The article describes the main ways of using spatial information in environmental engineering and protection. Then it discusses the problem of the openness of public administration data in the context of the “Open Data” EU Directive. Based on the four criteria defined by the author, the accessibility of data sets for all 21 subjects of 3rd Annex to the INSPIRE Directive in Poland has been analyzed. The key evaluation parameter has been the accessibility of data downloadable without the requirement to log in to the system of the service provider. The summary presents the research results, and the conclusions contain the proposed methods of solving them.

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