scholarly journals CONCEPTUAL MODEL OF AGROECOLOGICAL PROPERTIES OF LAND. SEQUENCES

2021 ◽  
pp. 80-87
Author(s):  
В.К. Каличкин ◽  
Р.А. Корякин ◽  
К.Ю. Максимович ◽  
Р.Р. Галимов ◽  
Н.А. Чернецкая
Keyword(s):  
Spatial Data ◽  
Digital Terrain Model ◽  
Knowledge Bases ◽  
Sequence Diagrams ◽  
Land Area ◽  
Modeling Tools ◽  
Intelligence System ◽  
Terrain Model ◽  
Logical Language ◽  
In The Beginning

Рассмотрен процесс создания последовательностей при описании предметных областей на формально-логическом языке UML. Использование последовательностей основано на понятии «источник данных», введённом авторами на основе предыдущего этапа концептуализации предметной области «агроэкологические свойства земель» – диаграммы классов. В классе начала связи выбирается один из комплектов атрибутов, в классе конца связи – один из методов (запрос), соответствующий этому комплекту. Многократно применяя этот подход при различных значениях атрибутов центрального класса, получается массив данных (в том числе пространственных). Атрибуты являются связующим звеном между создаваемой моделью, методами, потоками данных и запросов системы, так как, с одной стороны, они входят в состав классов, участвующих в сценариях диаграмм последовательностей, а с другой – принадлежат к внешней оболочке модели. На примерах движения информации, необходимой для расчетов гидротермического коэффициента Селянинова и степени проявления эрозии для рабочего участка, построены диаграммы последовательностей «ГидротермическийКоэффициент» и «СтепеньПроявленияЭрозии». Данные для диаграмм последовательностей формируются с помощью геоинформационных систем (географические координаты рабочего участка, цифровая модель рельефа) и справочно-информационного портала «Погода и климат». Предлагаемый подход даёт возможность автоматического построения баз знаний на основе двух концептуальных понятий: «источники данных» и «последовательности». Структурирование и формализация знаний позволяет осуществить переход от набора информации к знаниям и последующему их графическому отображению. Визуализация помогает наглядно отобразить связи между классами, которые могут быть не очевидны. Становится доступной возможность последующей оценки жизнеспособности модели, ее проектирования в симбиозе с использованием инструментов для имитационного моделирования, а также математических методов анализа и обработки информации. Данные диаграммы используются для построения и верификации созданных подсистем в процессе прямого и обратного проектирования аграрной интеллектуальной системы. The process of creating sequences while describing subdicipline in the formal-logical language UML is considered. The sequences usage is based on the concept of a "data source". It was deduced by the authors on the basis of the previous step of subdicipline conceptualization «agroecological lands properties» - class diagrams. In the beginning link's class, one of the attribute set is selected, in the ending class - one of the adequate to this set methods (query). The result of repeated application this approach, with different values of the attributes of the central class, is a database (including spatial data). Attributes mediate the created model, methods, data streams and system requests, as, on the one hand, they are among the classes involved in sequence diagrams scripting, and on the other - belong to the outer shell of the model. Sequences diagrams were constructed by the examples of the information flow necessary for calculating the Selyaninov hydrothermal index and the degree of erosion for the working land area. These diagrams are "HydrothermalIndexQuery" and "ErosionDegreeQuery". Data for sequence diagrams is generated by Geological Information System (geographic coordinates of the working land area, digital terrain model) and the reference-information gateway “Weather and Climate". The proposed approach makes it possible to build knowledge bases with the scope of two concepts: "data sources" and "sequence" automatically. Knowledge structuralizasion and formalization allows produce a shift from collecting information to knowledge and its subsequent graphical image. Visualization helps to demonstrably provide insight into classes' connections that may occur not to be obvious. The possibility of subsequent estimate of model consistency, its creation process using simulation modeling tools, as well as mathematical analysis methods and processing of data becomes more accessible. Diagrams' data is used for sybsystem construction and verification. These parts of a whole system were created in the process of forward and reverse engineering agricultural intelligence system.

scholarly journals INTEGRATING GEO-SPATIAL DATA FOR REGIONAL LANDSLIDE SUSCEPTIBILITY MODELING IN CONSIDERATION OF RUN-OUT SIGNATURE

2016 ◽  
Vol XLI-B8 ◽  
pp. 89-93
Author(s):  
J.-S. Lai ◽  
F. Tsai ◽  
S.-H. Chiang
Keyword(s):  
Random Forests ◽  
Spatial Data ◽  
Landslide Susceptibility ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Digital Terrain Model ◽  
Landslide Inventory ◽  
Terrain Model ◽  
Susceptibility Modeling ◽  
Causative Factors

This study implements a data mining-based algorithm, the random forests classifier, with geo-spatial data to construct a regional and rainfall-induced landslide susceptibility model. The developed model also takes account of landslide regions (source, non-occurrence and run-out signatures) from the original landslide inventory in order to increase the reliability of the susceptibility modelling. A total of ten causative factors were collected and used in this study, including aspect, curvature, elevation, slope, faults, geology, NDVI (Normalized Difference Vegetation Index), rivers, roads and soil data. Consequently, this study transforms the landslide inventory and vector-based causative factors into the pixel-based format in order to overlay with other raster data for constructing the random forests based model. This study also uses original and edited topographic data in the analysis to understand their impacts to the susceptibility modeling. Experimental results demonstrate that after identifying the run-out signatures, the overall accuracy and Kappa coefficient have been reached to be become more than 85 % and 0.8, respectively. In addition, correcting unreasonable topographic feature of the digital terrain model also produces more reliable modelling results.

scholarly journals Changes in a hydrographic network of the Słowiński National Park in terms of photogrammetric analyses

2017 ◽  
Vol 21 (4) ◽  
pp. 197-204
Author(s):  
Maciej Góraj ◽  
Marcin Kucharski ◽  
Krzysztof Karsznia ◽  
Izabela Karsznia ◽  
Jarosław Chormański
Keyword(s):  
Spatial Data ◽  
National Park ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Aerial Photographs ◽  
Terrain Model ◽  
Digital Terrain ◽  
Protected Natural Area ◽  
Water Courses ◽  
Hydrographic Network

AbstractThe main objective of this study is to evaluate the changes in the hydrographic network of Słowiński National Park. The authors analysed the changes occurring in the drainage network due to limited maintenance in this legally protected natural area. To accomplish this task, elaborations prepared on the basis of aerial photographs were used: an orthophoto map from 1996, hyperspectral imaging from June 2015, and a digital terrain model based on airborne laser scanning (ALS) from June 2015. These spatial data resources enabled the digitisation of the water courses for which selected hydro-morphological features had been defined. As a result of analysing the differences of these features, a quality map was elaborated which was then subjected to interpretation, and the identified changes were quantified in detail.

scholarly journals Kriging Method Optimization for the Process of DTM Creation Based on Huge Data Sets Obtained from MBESs

Geosciences ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. 433 ◽  
Author(s):  
Maleika Wojciech
Keyword(s):  
Spatial Data ◽  
Moving Average ◽  
Digital Terrain Model ◽  
Computation Time ◽  
Fixed Number ◽  
Kriging Interpolation ◽  
Computational Time ◽  
Kriging Method ◽  
Terrain Model ◽  
Digital Terrain

The paper presents an optimized method of digital terrain model (DTM) estimation based on modified kriging interpolation. Many methods are used for digital terrain model creation; the most popular methods are: inverse distance weighing, nearest neighbour, moving average, and kriging. The latter is often considered to be one of the best methods for interpolation of non-uniform spatial data, but the good results with respect to model’s accuracy come at the price of very long computational time. In this study, the optimization of the kriging method was performed for the purpose of seabed DTM creation based on millions of measurement points obtained from a multibeam echosounder device (MBES). The purpose of the optimization was to significantly decrease computation time, while maintaining the highest possible accuracy of created model. Several variants of kriging method were analysed (depending on search radius, minimum of required points, fixed number of points, and used smoothing method). The analysis resulted in a proposed optimization of the kriging method, utilizing a new technique of neighbouring points selection throughout the interpolation process (named “growing radius”). Experimental results proved the new kriging method to have significant advantages when applied to DTM estimation.

Topographic Map Update of Esan Central LGA, Edo State, Nigeria, Using SPOT-5 and ASTER LiDAR Data

2014 ◽  
Vol 1 (1) ◽  
pp. 52-69
Author(s):  
S.O. Ogedegbe
Keyword(s):  
Spatial Data ◽  
Digital Terrain Model ◽  
Topographic Maps ◽  
Lidar Data ◽  
Topographic Map ◽  
Terrain Model ◽  
Digital Elevation ◽  
Système D’Information ◽  
Elevation Model ◽  
Spot 5

This study examines the effectiveness and accuracy of SPOT-5 and ASTER LiDAR data satellite images, Global Pos1t1on1ng System (GPS), Digital Terrain Model (DTM), and Geographic Information System (GIS) in carrying out a revision of Nigerian topographic maps at the scale of 1:50,000. The data for the study were collected by extraction of relevant spatial data from the 1964 topographic map, delineation and interpretation of 2009 SPOT-5 data, and field surveys. The landscape changes extracted from SPOT- 5 were used to update the topographic base map and to determine the nature and direction of changes that have taken place in the study area. The findings revealed that changes have occurred in both cultural and relief features over time. The coefficient of correlation and t-test was calculated to show that changes in point, linear and areal features are significant. Also significant were the planh11etric and height accuracies of the revised map. The study shows that satellite data especially SPOT-5 is useful for the revision of topographic maps at scales of 1:50,000 and even larger. And, high-resolution remote sensing at Sm and ASTER data (30m) with GPS (±1.9m) can be used to c.reate a digital elevation model (DEM) on the map which is an essential dataset for complete revision. Cette étude examine l'efficacité et la précision des images satellites de données SPOT-5 et ASTER LiDAR, du système de positionnement global (GPS), du modèle numérique de terrain (MNT) et du système d'information géographique (SIG) pour effectuer une révision des cartes topographiques nigérianes au échelle de 1:50 000. Les données de l'étude ont été recueillies par extraction de données spatiales pertinentes à partir de la carte topographique de 1964, délimitation et interprétation des données SPOT-5 de 2009 et relevés de terrain. Les changements de paysage extraits de SPOT-5 ont été utilisés pour mettre à jour le fond de carte topographique et pour déterminer la nature et la direction des changements qui ont eu lieu dans la zone d'étude. Les résultats ont révélé que des changements se sont produits dans les caractéristiques culturelles et du relief au fil du temps. Le coefficient de corrélation et le test t ont été calculés pour montrer que les changements dans les caractéristiques ponctuelles, linéaires et aréales sont significatifs. Les précisions planimétriques et altimétriques de la carte révisée étaient également importantes. L'étude montre que les données satellitaires, en particulier SPOT-5, sont utiles pour la révision des cartes topographiques à des échelles de 1:50 000 et même plus. De plus, la télédétection haute résolution aux données Sm et ASTER (30 m) avec GPS (± 1,9 m) peut être utilisée pour créer un modèle d'élévation numérique (DEM) sur la carte qui est un ensemble de données essentiel pour une révision complète.

scholarly journals Assessment of Landscape Character and Absorptivity Based on Digital Terrain Model Analysis—Case Study of Jelenia Góra City in Poland

2021 ◽  
Vol 13 (14) ◽  
pp. 7969
Author(s):  
Grzegorz Budzik ◽  
Piotr Krajewski
Keyword(s):  
Spatial Distribution ◽  
Spatial Data ◽  
Digital Terrain Model ◽  
Terrain Model ◽  
Landscape Studies ◽  
Digital Terrain ◽  
Research Problems ◽  
Position Index ◽  
Landscape Character ◽  
Landscape Units

In an era of significant growth in the availability of spatial data and continued advances in computing technologies, opportunities for new interpretations and solutions to the landscape research problems posed worldwide are emerging. This paper presents different possibilities of applying digital terrain model (DTM) data in research of various aspects of landscape. For this purpose, two different methods were proposed. The first was to identify a set of components of the Jelenia Góra city landscape character on the basis of the topographic position index and spatial distribution of land cover, while the second was to assess the landscape of Jelenia Góra city in terms of the possibility of adopting new elements, using the author’s scenic absorptivity method. The results indicate the structure of the components of the landscape character of Jelenia Góra city together with its spatial distribution, which also allowed for the delineation of landscape units. The scenic absorptivity analysis showed that there are isolated areas within Jelenia Góra city that are capable of accommodating significant size elements that would not adversely affect the city landscape. In conclusion, DTM data are able to significantly improve research methods in landscape studies.

scholarly journals Drone technology for identification of healing forest spot at Kampung Cisamaya Mount Ciremai National Park

2021 ◽  
Vol 918 (1) ◽  
pp. 012040
Author(s):  
H Ramdan
Keyword(s):  
Forest Ecosystem ◽  
Psychological Health ◽  
Spatial Data ◽  
National Park ◽  
Vegetation Index ◽  
Digital Terrain Model ◽  
Physical Parameters ◽  
Vegetation Density ◽  
Terrain Model ◽  
Research Activities

Abstract Reconnecting people to nature through healing activities in the forest ecosystem is important. Various studies have shown that forest ecosystems dominated by tree vegetation have positive impacts on physical and psychological health. Not all locations in the forest ecosystem are suitable for healing forests (HF), but their suitability should be identified. Land slope, vegetation density, and easiness access to the site are some physical parameters of the land which are indicators for the development of HF site. Identification of suitable HF spots can be identified using drone technology and GIS. The research objective was the use of drones equipment in identifying potential sites for HF activities. The research site was Kampung Cisamaya in Mount Ciremai National Park. The type of drone used was the Phantom 4 Pro Obsidian equipped with a 20-megapixel RGB camera. The stages of research activities were data acquisition, processing, and analyzing from drone spatial data. Vegetation density was determined through GRVI (Green-Red Vegetation Index), while drone data analyzed the slope classification by DTM (Digital Terrain Model). The accessibility to the location was analyzed through data from the spatial map of the Kuningan Regency. The results found that the use of drones was effective in evaluating the suitability spots for HF activities. From this study can be concluded that the Cisamaya area was suitable for the development of HF activities due to physical parameters of flat to gentle slopes (0-15%), having dense vegetation, as well as the easiness access by people.

scholarly journals INTEGRATING GEO-SPATIAL DATA FOR REGIONAL LANDSLIDE SUSCEPTIBILITY MODELING IN CONSIDERATION OF RUN-OUT SIGNATURE

2016 ◽  
Vol XLI-B8 ◽  
pp. 89-93
Author(s):  
J.-S. Lai ◽  
F. Tsai ◽  
S.-H. Chiang
Keyword(s):  
Random Forests ◽  
Spatial Data ◽  
Landslide Susceptibility ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Digital Terrain Model ◽  
Landslide Inventory ◽  
Terrain Model ◽  
Susceptibility Modeling ◽  
Causative Factors

This study implements a data mining-based algorithm, the random forests classifier, with geo-spatial data to construct a regional and rainfall-induced landslide susceptibility model. The developed model also takes account of landslide regions (source, non-occurrence and run-out signatures) from the original landslide inventory in order to increase the reliability of the susceptibility modelling. A total of ten causative factors were collected and used in this study, including aspect, curvature, elevation, slope, faults, geology, NDVI (Normalized Difference Vegetation Index), rivers, roads and soil data. Consequently, this study transforms the landslide inventory and vector-based causative factors into the pixel-based format in order to overlay with other raster data for constructing the random forests based model. This study also uses original and edited topographic data in the analysis to understand their impacts to the susceptibility modeling. Experimental results demonstrate that after identifying the run-out signatures, the overall accuracy and Kappa coefficient have been reached to be become more than 85 % and 0.8, respectively. In addition, correcting unreasonable topographic feature of the digital terrain model also produces more reliable modelling results.

scholarly journals ANALYSIS OF GOOGLE EARTH ALTITUDE ERRORS FOR USE IN GEODESIC WORKS

2021 ◽  
Vol 3 (163) ◽  
pp. 47-51
Author(s):  
I. Musiienko ◽  
L. Kazachenko ◽  
E. Zaharova
Keyword(s):  
Spatial Data ◽  
Spatial Information ◽  
Digital Terrain Model ◽  
Original Data ◽  
Google Earth ◽  
Longitudinal Profile ◽  
Reference Object ◽  
Terrain Model ◽  
Desktop Computers ◽  
Longitudinal Profiles

The Google Earth service is an information system with extensive functionality used in the Internet, for mobile devices and for desktop computers. The system is a "virtual globe" built on pooled photographs with the addition of spatial information provided by Alphabet Inc in the coordinate system - WGS 84 and the universal cross-section of Mercator. In the system there is an opportunity to lay a line of a route, to receive a longitudinal profile of this line with marks and a slope. However, the question of the accuracy of spatial information remains. The answer to this question will highlight a range of engineering, geodetic and design tasks that can be solved with this service. The article considers this problem from the analysis of height errors. The accuracy of Google Earth's spatial information can be assessed by comparing it to a geodetic reference object. As such object in this work the data of adjustment of the design documentation for construction of the highway bypassing Novy Bug (the second turn) in the Nikolaev area are taken. In the first stage, a "reference" object has been considered, for which there are spatial data obtained by geodetic methods of a given accuracy. In the second stage, the Google Earth system built a road route and a longitudinal profile. At the third stage the received information was systematized and analyzed. In this work, the accuracy of construction of the longitudinal profile by geodetic methods was reduced due to the construction of a black line of the longitudinal profile through a digital terrain model, and hence due to the standard errors of Delaunay triangulation. When using geometric leveling data, the compatibility of the two longitudinal profiles will increase. With careful preparation of the original data, you can achieve meter accuracy in height. Representation of the Earth's surface with such accuracy can be used in solving many engineering problems: variant design of linear structures, preliminary feasibility study of design solutions and more. In the future, we must to assess the horizontal errors.

scholarly journals VISUALISATION WITH G.I.S OF AGIA EIRINI GORGE AT THE SOUTHERN MARGINS OF THE WHITE MOUNTAINS, SW CRETE

2018 ◽  
Vol 36 (2) ◽  
pp. 1018
Author(s):  
Κ. Μπιζούρα ◽  
Ε. Μανούτσογλου ◽  
Ε. Σπυρίδωνος
Keyword(s):  
Spatial Data ◽  
Digital Terrain Model ◽  
Field Work ◽  
Digital Information ◽  
White Mountains ◽  
Natural Systems ◽  
Terrain Model ◽  
Digital Terrain ◽  
The Creation ◽  
Available Information

Sustainable management of protected areas requires good knowledge of the entire system. Complicated natural systems require for their management the use of digital information systems, that would allow the integration of all the available information on the studied natural system as well as the elements of new researches. Among the natural systems the gorges constitute mainly geological structrures. The aim of the present study is the development of a 3D digital morphotectonic model for the Agia Eirini Gorge, crossing the southern limbs of mountain Lefka Ori in South-Western Crete. The work is divided in two parts, on one side in the creation of suitable backgrounds that is reqi ired for the creation of a 3D model and on the other hand the placement of the spatial data into the model. For the creation of the digital terrain model (DTM) of the gorge area, maps at a 1:5.000 scale, obtained from the Army Geographic Service were digitised using CAD Overlay 2000i software. The data obtained were transferred into SURPAC 2000 supplemented with orthophotomaps of the region with the method of superimposition. The initial data drawn from the existing geological map of the region were evaluated by data obtained from field work. This methodology allows integration of all available information for the system under study, including newly acquired data

scholarly journals CREATING AND ANALYSING THE DIGITAL TERRAIN MODEL OF THE SLIVOVO AREA USING QGIS SOFTWARE

2017 ◽  
Vol 43 (3) ◽  
pp. 111-117 ◽  
Author(s):  
Edon MALIQI ◽  
Petar PENEV ◽  
Faik KELMENDI
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Spatial Data ◽  
Digital Terrain Model ◽  
Terrain Model ◽  
Digital Terrain ◽  
Methods And Techniques

The aim of the paper is developing the Digital Terrain Model (DTM in the further text) through QGIS software. In order to accomplish intention of the paper will test some of the methods and techniques that are widely known in nowadays and those are supported by QGIS software – an open source software. And those methods named TIN and GRID. For showing complexity on the study area will analyse some features or characteristics of terrain in the created DTM. All of these methods and techniques will be applied in QGIS. In general, the QGIS software has rich methodology for creation, intepretation, visualization and analysing the geo-spatial data and the DTM in particular.

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