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This paper describes a process that has been developed to produce a map of agricultural profit for Australia for the year 2005/2006.
A map of agricultural profit on a large scale and regular updates thereof will help understand profit trends in time and across space.
There is however currently no flexible system in operation which allows for a consistent update of a map of agricultural profits in Australia or elsewhere.
Given the upcoming challenges and their associated uncertainties, it is important to ensure that a map of agricultural profit can be reproduced in a scenario and simulation setting which will allow exploring uncertainties around the impacts on agricultural profits as well.
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Remotely sensed data provide reliable, cost and time effective information for monitoring, analyzing and mapping of agricultural land areas.
Maps of agricultural activities or water demand can then be superimposed on maps of water resources and hydraulic facilities to check if they are consistent.
Therefore, the most important improvement to this method would be more accurate and more frequently updated maps of agricultural land use.
Agricultural soil (Ap-horizon, 0 20 cm) samples were collected in Europe (33 countries, 5.6 million km2) as part of the GEMAS (GEochemical Mapping of Agricultural and grazing land Soil) soil-mapping project.
Agricultural soil (Ap-horizon, 0 20 cm) samples were collected from a large part of Europe (33 countries, 5.6 million km2) as part of the GEMAS (GEochemical Mapping of Agricultural and grazing land Soil) soil mapping project.
2108 agricultural soil samples (Ap-horizon, 0 20 cm) were collected in Europe (33 countries, area 5.6 million km2) as part of the recently completed GEMAS (GEochemical Mapping of Agricultural and grazing land Soil) soil mapping project.
Both methods were applied to a case study involving Fe, V and Y datasets originating from two European geochemical mapping projects: the Geochemical Mapping of Agricultural Soils of Europe (GEMAS) and the Baltic Soil Survey (BSS).
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