Agricultural commodity mapping for land use change assessment and environmental management: an application in the Murray–Darling Basin, Australia

In this study we map the distribution and dynamics of commodity-level agricultural land use in the Murray–Darling Basin, Australia for two snapshot years 1996/1997 and 2000/2001. In the process, we integrate a diverse set of information including time-series remote sensing, agricultural statistics, field data from control sites and geographic information system data. A Bayesian Monte Carlo Markov chain technique is combined with areal interpolation to map the spatial distribution and dynamics of 48 agricultural commodities at 1.1 km resolution. We use the maps to assess land use change in the Murray–Darling Basin including a 22% increase in the area of irrigated agriculture and discuss the impacts for the management of land and water resources. The high-resolution outputs are suitable for other applications including spatially explicit economic modelling, assessments of natural resource use, and for informing agricultural, water and natural resource management planning and policy.

[1]  Stefan Hajkowicz,et al.  Mapping Economic Returns to Agriculture for Informing Environmental Policy in the Murray–Darling Basin, Australia , 2009 .

[2]  M. Ejaz Qureshi,et al.  Integrated hydrologic–economic modelling for analyzing water acquisition strategies in the Murray River Basin , 2007 .

[3]  Helmut Haberl,et al.  A comprehensive global 5 min resolution land-use data set for the year 2000 consistent with national census data , 2007 .

[4]  M. Mainuddin,et al.  Economic Assessment of Acquiring Water for Environmental Flows in the Murray Basin , 2007 .

[5]  Patrick Bogaert,et al.  A statistical method to downscale aggregated land use data and scenarios , 2006 .

[6]  M. Mainuddin,et al.  CATCHMENT BEHAVIOR AND COUNTER‐CYCLICAL WATER TRADE: AN INTEGRATED MODEL , 2006 .

[7]  Armin Gemperli,et al.  Mapping malaria transmission in West and Central Africa , 2006, Tropical medicine & international health : TM & IH.

[8]  Rob Lesslie,et al.  Land use information for integrated natural resources management—a coordinated national mapping program for Australia , 2006 .

[9]  Petra Döll,et al.  Development and validation of the global map of irrigation areas , 2005 .

[10]  M. Simon,et al.  The expansion of agriculture in the Brazilian Amazon , 2005, Environmental Conservation.

[11]  GLEN A. SARGEANT,et al.  MARKOV CHAIN MONTE CARLO ESTIMATION OF SPECIES DISTRIBUTIONS: A CASE STUDY OF THE SWIFT FOX IN WESTERN KANSAS , 2005 .

[12]  D. Saunders,et al.  Land use and ecosystems. , 2005 .

[13]  S. Fritz,et al.  A land cover map of South America , 2004 .

[14]  John R. Nuckols,et al.  An automated approach to mapping corn from Landsat imagery , 2004 .

[15]  Tim R. McVicar,et al.  Current and potential uses of optical remote sensing in rice-based irrigation systems: a review , 2004 .

[16]  Sunil Nautiyal,et al.  Patterns and ecological implications of agricultural land-use changes: a case study from central Himalaya, India , 2004 .

[17]  R. Latifovic,et al.  Land cover mapping of North and Central America—Global Land Cover 2000 , 2004 .

[18]  Jeffrey A. Cardille,et al.  Agricultural land-use change in Brazilian Amazônia between 1980 and 1995: Evidence from integrated satellite and census data , 2003 .

[19]  H. Alphan Land‐use change and urbanization of Adana, Turkey , 2003 .

[20]  Anthony J. Jakeman,et al.  Integrated assessment and modelling: features, principles and examples for catchment management , 2003, Environ. Model. Softw..

[21]  P. Defourny,et al.  Land cover characterization and mapping of continental Southeast Asia using multi-resolution satellite sensor data , 2003 .

[22]  Pawan Kumar Joshi,et al.  SPOT vegetation multi temporal data for classifying vegetation in south central Asia , 2003 .

[23]  Changsheng Li,et al.  Combining remote sensing and ground census data to develop new maps of the distribution of rice agriculture in China , 2002 .

[24]  Daniel Müller,et al.  Land use dynamics in the central highlands of Vietnam: a spatial model combining village survey data with satellite imagery interpretation , 2002 .

[25]  J. Foley,et al.  Characterizing patterns of agricultural land use in Amazonia by merging satellite classifications and census data , 2002 .

[26]  G. Senay,et al.  Capability of AVHRR data in discriminating rangeland cover mixtures , 2002 .

[27]  Trevor Hastie,et al.  The Elements of Statistical Learning , 2001 .

[28]  J. C. Taylor,et al.  Monitoring land use change in the Badia transition zone in Jordan using aerial photography and satellite imagery , 2001 .

[29]  E. Lambin,et al.  Quantifying processes of land-cover change by remote sensing: Resettlement and rapid land-cover changes in south-eastern Zambia , 2001 .

[30]  J. Townshend,et al.  Global land cover classi(cid:142) cation at 1 km spatial resolution using a classi(cid:142) cation tree approach , 2004 .

[31]  Xiangming Xiao,et al.  Agricultural land‐use in China: a comparison of area estimates from ground‐based census and satellite‐borne remote sensing , 1999 .

[32]  Yoram J. Kaufman,et al.  MODIS NDVI Optimization To Fit the AVHRR Data Series—Spectral Considerations , 1998 .

[33]  M. A. Tanner,et al.  Tools for Statistical Inference: Methods for the Exploration of Posterior Distributions and Likelihood Functions, 3rd Edition , 1998 .

[34]  P. Walker,et al.  Disaggregating Agricultural Statistics Using NOAA-AVHRR NDVI , 1998 .

[35]  Russell G. Congalton,et al.  Mapping and Monitoring Agricultural Crops and Other Land Cover in the Lower Colorado River Basin , 1998 .

[36]  Paul A. Walker,et al.  Using Integrated Economic and Ecological Information to Improve Government Policy , 1997, Int. J. Geogr. Inf. Sci..

[37]  J. Walker,et al.  Indicators of catchment health: a technical perspective. , 1996 .

[38]  Andrew Moxey,et al.  Areal Interpolation of Spatially Extensive Variables: A Comparison of Alternative Techniques , 1994, Int. J. Geogr. Inf. Sci..

[39]  M. Tanner Tools for statistical inference: methods for the exploration of posterior distributions and likeliho , 1994 .

[40]  Michael F. Goodchild,et al.  A Framework for the Areal Interpolation of Socioeconomic Data , 1993 .

[41]  Alexander Rule,et al.  Forests of Australia , 1968 .