Geospatial Database

2021 ◽  
pp. 279-325
Author(s):  
Tiejun Cui ◽  
Jianzhong Guo
Keyword(s):  
Geospatial Database

Geographic information database for the analysis of spatial distribution of the Baikal endemic amphipods in Yenisei river

2018 ◽  
Author(s):  
А.В. Андрианова ◽  
О.Э. Якубайлик
Keyword(s):  
Information Exchange ◽  
Field Research ◽  
Field Studies ◽  
Hydroelectric Power Station ◽  
Hydroelectric Power ◽  
Yenisei River ◽  
Web System ◽  
Geospatial Database ◽  
Software Interfaces ◽  
The Yenisei River

Рассматривается состояние эндемичных байкальских амфипод в р. Енисей, приводятся результаты экспедиционных исследований. Отмечается факт многоразового увеличения количества амфипод в Енисее после зарегулирования плотиной Красноярской ГЭС. Данные гидробиологического мониторинга оформлены в виде геопространственной базы данных на геопортале, который предоставляет возможности визуализации результатов исследований в виде интерактивных тематических карт, прямого доступа к данным через картографические веб-сервисы из современных ГИС. The purpose. The purpose of the work is the theoretical and practical studies of the possibilities for using the geoinformation web-system modern technologies for improving the efficiency of hydrobiological monitoring, and design of software tools of data presentation and analysis for field research. Methods. The technologies for development of distributed information systems in multi-tier architecture, along with software interfaces and protocols, information exchange standards are considered. The possibilities for using of geoinformation and cartographic modelling methods for searching the relationship between the spatial distributions of Baikal amphipods in the Yenisei river with different environmental factors are investigated. Results. The technologies and related software are developed for the considered problem. The geospatial database is generated and filled with the results of own longterm hydrobiological field studies, it has become an integral part of the geoportal of ICM SB RAS, which was formed by the separate thematic section. The focus is on the results of extensive field studies of the Yenisei implemented in 2015 and 2016. As to database content, the information about the quantitative distribution of zoobenthos (animals inhabiting the ponds bottom), in particular endemic Baikal amphipods, in the area from Yenisei river headwaters to its delta was used. It was revealed that the amphipods — the endemics of the Baikal lake — spread far beyond its limits not only downward, but also upstream the Yenisei river. After the commissioning of the Krasnoyarsk hydroelectric power station, their share in the total zoobenthos biomass is increased by 10 times. Gmelinoides fasciatus crustacean is especially active; it has massively populated the area of the Upper Yenisei river below the Sayano-Shushensky reservoir. The density and the fraction of crustaceans in the zoobenthos in the area of the Angara — Podkamennaya Tunguska has increased over the last 15 years. Conclusions. Creation of a geospatial database alongside with the results of expeditionary research and the introduction of a GIS web-system for information-analytical support of hydrobiological monitoring significantly expands opportunities for the analysis and presentation of geodata, forms the basis for interdisciplinary research.

Identifying the main physical and socioeconomic drivers of illegal landfills in the Canary Islands

2018 ◽  
Vol 36 (11) ◽  
pp. 1049-1060 ◽  
Author(s):  
L Quesada-Ruiz ◽  
V Rodriguez-Galiano ◽  
R Jordá-Borrell
Keyword(s):  
Multivariable Analysis ◽  
Principal Component ◽  
Binary Logistic Regression ◽  
Gran Canaria ◽  
Analysis Techniques ◽  
La Palma ◽  
Socioeconomic Drivers ◽  
Geospatial Database ◽  
Total Data ◽  
Degree Of Association

The management of disposed waste in illegal landfills (ILs) is a significant problem in contemporary societies due to respective hazards for the environment and human health. This paper presents a characterisation of ILs on the islands of La Palma (LP) and Gran Canaria (GC) based on multivariable statistical analysis. Inspection of numerous sites on both islands revealed a total of 153 and 286 ILs on LP and GC, respectively. A geospatial database was created composed of different potentially explanatory features of different typology (177): waste type, control and vigilance, socioeconomic, accessibility, distance to elements of interest, visibility and physical. The degree of association between the explanatory features and the occurrence of ILs was analysed with the support of exploratory statistics and the multivariable analysis techniques of principal component analysis (PCA) and binary logistic regression (LR). PCA explained 82.34% and 81.83% of total data variance in LP and GC, respectively, considering 7 and 6 components (Kaiser–Mayer–Olkin; LP: 0.715; GC: 0.711). The LR models for LP and GC had an overall accuracy of 93.5% and 92.5%. In LP and GC, 6 of 23 features and 9 of 21 features were, respectively, selected. The features most associated with the occurrence of ILs were: in LP, building density, distance to agricultural spaces and distance to green zones; in GC, the industrial activity indicator, density of ground use transition to artificial covers, density of greenhouses and distance to communication routes.

scholarly journals APPLICATION OF 3D SPATIO-TEMPORAL DATA MODELING, MANAGEMENT, AND ANALYSIS IN DB4GEO

2016 ◽  
Vol IV-2/W1 ◽  
pp. 163-170
Author(s):  
P. V. Kuper ◽  
M. Breunig ◽  
M. Al-Doori ◽  
A. Thomsen
Keyword(s):  
Water Supply ◽  
United Arab Emirates ◽  
Transport Systems ◽  
Reservoir Modeling ◽  
Future Research ◽  
Temporal Data ◽  
Temporal Dimension ◽  
Geospatial Database ◽  
Spatio Temporal ◽  
Temporal Objects

Many of today´s world wide challenges such as climate change, water supply and transport systems in cities or movements of crowds need spatio-temporal data to be examined in detail. Thus the number of examinations in 3D space dealing with geospatial objects moving in space and time or even changing their shapes in time will rapidly increase in the future. Prominent spatio-temporal applications are subsurface reservoir modeling, water supply after seawater desalination and the development of transport systems in mega cities. All of these applications generate large spatio-temporal data sets. However, the modeling, management and analysis of 3D geo-objects with changing shape and attributes in time still is a challenge for geospatial database architectures. In this article we describe the application of concepts for the modeling, management and analysis of 2.5D and 3D spatial plus 1D temporal objects implemented in DB4GeO, our service-oriented geospatial database architecture. An example application with spatio-temporal data of a landfill, near the city of Osnabrück in Germany demonstrates the usage of the concepts. Finally, an outlook on our future research focusing on new applications with big data analysis in three spatial plus one temporal dimension in the United Arab Emirates, especially the Dubai area, is given.

scholarly journals GEOSPATIAL DATABASE FOR STRATA OBJECTS BASED ON LAND ADMINISTRATION DOMAIN MODEL (LADM)

2016 ◽  
Vol XLII-4/W1 ◽  
pp. 329-334
Author(s):  
N. N. Nasorudin ◽  
M. I. Hassan ◽  
N. A. Zulkifli ◽  
A. Abdul Rahman
Keyword(s):  
Standard Model ◽  
Real World ◽  
Data Model ◽  
Database Design ◽  
Domain Model ◽  
Standard Data ◽  
Land Administration ◽  
Physical Database Design ◽  
Geospatial Database ◽  
2D And 3D

Recently in our country, the construction of buildings become more complex and it seems that strata objects database becomes more important in registering the real world as people now own and use multilevel of spaces. Furthermore, strata title was increasingly important and need to be well-managed. LADM is a standard model for land administration and it allows integrated 2D and 3D representation of spatial units. LADM also known as ISO 19152. The aim of this paper is to develop a strata objects database using LADM. This paper discusses the current 2D geospatial database and needs for 3D geospatial database in future. This paper also attempts to develop a strata objects database using a standard data model (LADM) and to analyze the developed strata objects database using LADM data model. The current cadastre system in Malaysia includes the strata title is discussed in this paper. The problems in the 2D geospatial database were listed and the needs for 3D geospatial database in future also is discussed. The processes to design a strata objects database are conceptual, logical and physical database design. The strata objects database will allow us to find the information on both non-spatial and spatial strata title information thus shows the location of the strata unit. This development of strata objects database may help to handle the strata title and information.

scholarly journals A lake-centric geospatial database to guide research and inform management decisions in an Arctic watershed in northern Alaska experiencing climate and land-use changes

AMBIO ◽  
2017 ◽  
Vol 46 (7) ◽  
pp. 769-786 ◽  
Author(s):  
Benjamin M. Jones ◽  
Christopher D. Arp ◽  
Matthew S. Whitman ◽  
Debora Nigro ◽  
Ingmar Nitze ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Changes ◽  
Management Decisions ◽  
Geospatial Database ◽  
Northern Alaska

FogLearn

2019 ◽  
pp. 1225-1241 ◽  
Author(s):  
Rabindra K. Barik ◽  
Rojalina Priyadarshini ◽  
Harishchandra Dubey ◽  
Vinay Kumar ◽  
Kunal Mankodiya
Keyword(s):  
Big Data ◽  
Fog Computing ◽  
Big Data Analytics ◽  
River Basin Management ◽  
Pathological Feature ◽  
Ganga Basin ◽  
Learning Framework ◽  
Geospatial Database ◽  
Patients With Diabetes ◽  
River Ganga

Big data analytics with the cloud computing are one of the emerging area for processing and analytics. Fog computing is the paradigm where fog devices help to reduce latency and increase throughput for assisting at the edge of the client. This article discusses the emergence of fog computing for mining analytics in big data from geospatial and medical health applications. This article proposes and develops a fog computing-based framework, i.e. FogLearn. This is for the application of K-means clustering in Ganga River Basin Management and real-world feature data for detecting diabetes patients suffering from diabetes mellitus. The proposed architecture employs machine learning on a deep learning framework for the analysis of pathological feature data that obtained from smart watches worn by the patients with diabetes and geographical parameters of River Ganga basin geospatial database. The results show that fog computing holds an immense promise for the analysis of medical and geospatial big data.

Assessing the Existing Vegetation Around Abandoned Mining Areas With Potentially Toxic Heavy Metals

2021 ◽  
pp. 14-31
Author(s):  
José Manuel Naranjo Gómez ◽  
José Cabezas Fernández ◽  
Rui Alexandre Castanho ◽  
Carlos José Pinto Gomes
Keyword(s):  
Heavy Metals ◽  
Geographic Information Systems ◽  
Geographic Information ◽  
Geospatial Analysis ◽  
Abandoned Mines ◽  
Toxic Heavy Metals ◽  
Mining Areas ◽  
Geospatial Database ◽  
Thematic Cartography ◽  
Physical Consequences

In abandoned mining areas, heavy metals may exist. Those heavy metals can cause physical consequences and death. Through the use of geographic information systems (GIS), the environmental diagnosis of vegetation potentially affected by the presence of very toxic heavy metals in abandoned mining areas in Extremadura was conducted. Initially, graphic and alphanumeric information was obtained from numerous sources, and the geospatial database generated was analyzed, allowing the location of abandoned mines. Subsequently, the mines were classified according to the degree of toxicity of the heavy metals that had been exploited. Then, taking into account the mines whose heavy metals were considered very toxic, a geospatial analysis was performed using concentric buffers at 1, 5, 10, 20, 40, and 60 kilometres. The results obtained made it possible to obtain thematic cartography representative of the areas potentially affected. The proportion of vegetation potentially affected, has been classified according to the existing vegetation series and climatic belts.

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