Data mining techniques for land use catchment planning

Neil Dunstan

Data mining techniques for land use catchment planning

Neil Dunstan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Computer-based tools to facilitate catchment planning use predictive modeling and analytical procedures applied to large volumes of multidimensional data. Their purpose is to discover sustainable land and water management scenarios with regard to human activities and the environment. Data mining techniques can be usefully applied in this process. This paper describes the use of modeling, On-line Analytical Processing, clustering, sequence analysis and visualization in catchment planning.

Original language	English
Title of host publication	Proceedings of the Knowledge Discovery for Rural Systems Workshop 2010
Editors	L J Armstrong, J Clayden
Place of Publication	Mt Lawley, Australia
Publisher	Edith Cowan University
ISBN (Print)	9780646547909, 0646547909
Publication status	Published - 2010
Event	KDRS 2010: eWorkshop on Knowledge Discovery for Rural Systems - Hyderabad, India Duration: 21 Jun 2010 → …

Conference

Conference	KDRS 2010: eWorkshop on Knowledge Discovery for Rural Systems
City	Hyderabad, India
Period	21/06/10 → …

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 15 Life on Land

Keywords

Decision Support and Group Support Systems

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https://hdl.handle.net/1959.11/10345

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@inproceedings{6c85e0e40b594fba9869e5e3e5317668,

title = "Data mining techniques for land use catchment planning",

abstract = "Computer-based tools to facilitate catchment planning use predictive modeling and analytical procedures applied to large volumes of multidimensional data. Their purpose is to discover sustainable land and water management scenarios with regard to human activities and the environment. Data mining techniques can be usefully applied in this process. This paper describes the use of modeling, On-line Analytical Processing, clustering, sequence analysis and visualization in catchment planning.",

keywords = "Decision Support and Group Support Systems",

author = "Neil Dunstan",

year = "2010",

language = "English",

isbn = "9780646547909",

editor = "\{J Armstrong\}, L and J Clayden",

booktitle = "Proceedings of the Knowledge Discovery for Rural Systems Workshop 2010",

publisher = "Edith Cowan University",

note = "KDRS 2010: eWorkshop on Knowledge Discovery for Rural Systems ; Conference date: 21-06-2010",

}

TY - GEN

T1 - Data mining techniques for land use catchment planning

AU - Dunstan, Neil

PY - 2010

Y1 - 2010

N2 - Computer-based tools to facilitate catchment planning use predictive modeling and analytical procedures applied to large volumes of multidimensional data. Their purpose is to discover sustainable land and water management scenarios with regard to human activities and the environment. Data mining techniques can be usefully applied in this process. This paper describes the use of modeling, On-line Analytical Processing, clustering, sequence analysis and visualization in catchment planning.

AB - Computer-based tools to facilitate catchment planning use predictive modeling and analytical procedures applied to large volumes of multidimensional data. Their purpose is to discover sustainable land and water management scenarios with regard to human activities and the environment. Data mining techniques can be usefully applied in this process. This paper describes the use of modeling, On-line Analytical Processing, clustering, sequence analysis and visualization in catchment planning.

KW - Decision Support and Group Support Systems

M3 - Conference contribution

SN - 9780646547909

SN - 0646547909

BT - Proceedings of the Knowledge Discovery for Rural Systems Workshop 2010

A2 - J Armstrong, L

A2 - Clayden, J

PB - Edith Cowan University

CY - Mt Lawley, Australia

T2 - KDRS 2010: eWorkshop on Knowledge Discovery for Rural Systems

Y2 - 21 June 2010

ER -

Data mining techniques for land use catchment planning

Abstract

Conference

UN SDGs

Keywords

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