GIS analysis for the marine environmental data off Karnataka coast

ETL refers to the process of data extracting, transformation and loading and is deemed as a critical step in ensuring the quality, data specification and standardization of marine environmental data. Marine data, due to their complication, field diversity and huge volume, still remain decentralized, polyphyletic and isomerous with different semantics and hence far from being able to provide effective data sources for decision making. ETL enables the construction of marine environmental data warehouse in the form of cleaning, transformation, integration, loading and periodic updating of basic marine data warehouse. The paper presents a research on rules for cleaning, transformation and integration of marine data, based on which original ETL system of marine environmental data warehouse is so designed and developed. The system further guarantees data quality and correctness in analysis and decision-making based on marine environmental data in the future.

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Research on the Incremental Updating Mechanism of Marine Environmental Data Warehouse

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.668-669.1378 ◽

2014 ◽

Vol 668-669 ◽

pp. 1378-1381 ◽

Cited By ~ 1

Author(s):

Wei Jun Wen

Keyword(s):

Data Warehouse ◽

Marine Environment ◽

Historical Data ◽

Environmental Data ◽

Operating Efficiency ◽

Massive Data ◽

Complete Set ◽

Incremental Update ◽

Update Frequency ◽

Marine Environmental

Marine environment data warehouse can store massive data. After the full amount of historical data has been initially loaded, the incremental update mode must be applied to ensure timely updates of data. In this paper, in view of the marine environment data warehouse’s characteristics, such as massive data amount, large number of historical data and low update frequency, a complete set of mechanisms for incremental update of marine environment data warehouse was proposed to greatly improve the operating efficiency of marine environment data warehouse.

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Assmilation model of marine environmental data measured by different organizations in Osaka Bay

Oceans '04 MTS/IEEE Techno-Ocean '04 (IEEE Cat. No.04CH37600) ◽

10.1109/oceans.2004.1405519 ◽

2005 ◽

Author(s):

T. Yamada ◽

R. Hosoda

Keyword(s):

Environmental Data ◽

Osaka Bay ◽

Marine Environmental

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Forecasting Weed Distributions using Climate Data: A GIS Early Warning Tool

Invasive Plant Science and Management ◽

10.1614/ipsm-08-073.1 ◽

2010 ◽

Vol 3 (4) ◽

pp. 365-375 ◽

Cited By ~ 14

Author(s):

Catherine S. Jarnevich ◽

Tracy R. Holcombe ◽

David T. Barnett ◽

Thomas J. Stohlgren ◽

John T. Kartesz

Keyword(s):

Time Series ◽

Early Detection ◽

Exotic Species ◽

Early Warning ◽

Local Level ◽

The United States ◽

Environmental Data ◽

Analysis Tool ◽

Gis Analysis ◽

Invasive Exotic

AbstractThe number of invasive exotic plant species establishing in the United States is continuing to rise. When prevention of exotic species from entering into a country fails at the national level and the species establishes, reproduces, spreads, and becomes invasive, the most successful action at a local level is early detection followed by eradication. We have developed a simple geographic information system (GIS) analysis for developing watch lists for early detection of invasive exotic plants that relies upon currently available species distribution data coupled with environmental data to aid in describing coarse-scale potential distributions. This GIS analysis tool develops environmental envelopes for species based upon the known distribution of a species thought to be invasive and represents the first approximation of its potential habitat while the necessary data are collected to perform more in-depth analyses. To validate this method we looked at a time series of species distributions for 66 species in Pacific Northwest and northern Rocky Mountain counties. The time series analysis presented here did select counties that the invasive exotic weeds invaded in subsequent years, showing that this technique could be useful in developing watch lists for the spread of particular exotic species. We applied this same habitat-matching model based upon bioclimatic envelopes to 100 invasive exotics with various levels of known distributions within continental U.S. counties. For species with climatically limited distributions, county watch lists describe county-specific vulnerability to invasion. Species with matching habitats in a county would be added to that county's list. These watch lists can influence management decisions for early warning, control prioritization, and targeted research to determine specific locations within vulnerable counties. This tool provides useful information for rapid assessment of the potential distribution based upon climate envelopes of current distributions for new invasive exotic species.

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