Data Integration Issues in Research Supporting Sustainable Natural Resource Management

Dados Bibliográficos

ID5877399
AutoresAlexander Herr (0000-0001-6081-3597, Commonwealth Scientific and Industrial Research Organisation, autor correspondente)
Ano2007
Volume45
Fascículo4
Páginas376-386
Data de publicação2007-12-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoGeographical Research (JOURNAL)
Identificadores do periódicoISSN: 1745-5863 • E-ISSN: 1745-5871
EditoraWiley (PUBLISHER • GB)
DOI10.1111/j.1745-5871.2007.00476.x
OpenAlexW2074617993
IdiomaEN
Citações recebidas3
Referências citadas16

Current decision-making in natural resource use and management aims at delivering ecologically-sustainable development to achieve conservation and economic benefits. The process of guiding natural resource use requires the integration of social, economic and biophysical information on which to base management decisions. This paper discusses the integration of socio-economic information for natural resource management (NRM) planning and decision-making in the Australian context. A comprehensive resource of socio-economic data is the Census, which is undertaken every five years by the Australian Bureau of Statistics (ABS) for the whole of Australia. Unfortunately there are qualitative and quantitative issues stemming from the use of ABS census data maps for NRM decision-making, as they are at a different scale to and the boundaries do not coincide with biophysical information. These issues include the variable shape of collection districts, the use of enumerated data for population-based statistics, the large size of collection districts in low populated areas, and the averaging of socio-economic information over the collection districts. Examples highlight these issues and show a way forwards in improving data integration, which includes simple spatial overlay methods and regression modelling

Cartography · Census · Data collection · Data science · Economics · Environmental resource management · Geography · Natural resource · Natural resource management · Population · Statistics · Computer Science · Conservation, Biodiversity, and Resource Management · Economic and Environmental Valuation · Land Use and Ecosystem Services · Ecology