The Land Potentially Suitable for the Agriculture Zone mapping layer was produced as part of the agricultural land mapping project commissioned by the Department of Justice, Planning Policy Unit on behalf of the Minister for Planning and Local Government to assist local government in applying the Agriculture Zone as part of the Local Provisions Schedules in the Tasmanian Planning Scheme. The agricultural land mapping project aims to provide support for the recalibrated rural zones in the State Planning Provisions, the Rural Zone and Agriculture Zone, specifically to provide guidance to local government in spatially applying the Agriculture Zone. This layer represents the refined mapping of land that has been subject to a series of filters to determine potential constraints as outlined in the Agricultural Land Mapping Project â Background Report: http://planningreform.tas.gov.au/__data/assets/pdf_file/0004/390874/Agricultural_Land_Mapping_Project_-Background_Report-_May_2017.pdf. The filters cover issues such as: suitability of the title to sustainably support agriculture, including potential access to irrigation water; consideration of existing forestry land; and potential constraints for agricultural use, including potential economic or physical barriers, and potential land use conflicts. The mapping has also been aligned to cadastre boundaries. This layer should be viewed in conjunction with the Potential Agricultural Land Initial Analysis mapping layer, which provides an additional analysis tool for determining the suitability of the land for the Agriculture Zone. The mapping should also be used in conjunction with Guideline No. 1 â Local Provisions Schedule (LPS): zone and code application: http://www.planning.tas.gov.au/news/news_items/guidance_for_drafting_lps.

The potentially arable areas dataset is derived from a number of source datasets to provide an approximation of the area of land in Western Australia which is potentially available for agricultural purposes.

A predictive model has been established and tested to account for variations in the landscape to reflect changes in agricultural land capability class (on a progressive rating of 1: good - 7: poor). This dataset (and map) provides a prediction of the most likely land capability class to be expected in a particular location based on several layers of readily available information. These layers included geology, rainfall, slope, elevation, forest cover and surface drainage status. These data layers were input into a Geographic Information System modelling framework. Using previous experience and limited visits in the field, the output has been produced as a digital dataset and 1: 100,000 map. It was found to provide a relatively good impression of the landscapes potential for agricultural persuits (ie cropping and grazing). It was found to represent changes in capability class very well where geology, climate or slope control capability. In those areas where subsurface drainage controlled land capability it was found to be less reliable. Overall however as these areas of the State were previously devoid of any broadscale land resource information for this purpose - this map provides a valuable fist step in discerning land capability.

A predictive model has been established and tested to account for variations in the landscape to reflect changes in agricultural land capability class (on a progressive rating of 1: good - 7: poor). This dataset (and map) provides a prediction of the most likely land capability class to be expected in a particular location based on several layers of readily available information. These layers included geology, rainfall, slope, elevation, forest cover and surface drainage status. These data layers were input into a Geographic Information System modelling framework. Using previous experience and limited visits in the field, the output has been produced as a digital dataset and 1: 100,000 map. It was found to provide a relatively good impression of the landscapes potential for agricultural persuits (ie cropping and grazing). It was found to represent changes in capability class very well where geology, climate or slope control capability. In those areas where subsurface drainage controlled land capability it was found to be less reliable. Overall however as these areas of the State were previously devoid of any broadscale land resource information for this purpose - this map provides a valuable fist step in discerning land capability.