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<gmd:statement><gco:CharacterString>Created from (1) CGDL layers (DPI corporate geospatial data library) Topographic and cadastral data layers LINEBREAK
 STARTUNORDEREDLIST STARTDOTPOINTDigital cadastre 1:25,000 - VicMap Property (July 2003)ENDDOTPOINT STARTDOTPOINTTransport - Roads and Rail 1:25,000 - VicMap TransportENDDOTPOINT STARTDOTPOINTHydrologic features; line and point 1:25,000 - VicMap Hydrology (Sep. 2003) State-wide/Regional land data and mapping layersENDDOTPOINT STARTDOTPOINTPublic Land Management - current legal status of land 1:100,000 - plmmt100 (Sep. 2003)ENDDOTPOINT STARTDOTPOINTTree Cover - 1:25,000 - tree25 (June 2003)ENDDOTPOINT ENDUNORDEREDLIST (2) Valuer-General of Victoria (VGV) Shire Valuation Datasets (Dec. 2002).LINEBREAK
 (3) Fieldwork carried out in September 2004, Janurary 2005, August 2005, Janurary 2006LINEBREAK
 (5) Aerial Photography: Dryland Photography - 1:15,000 and 1:25,000 flown in February and March 2001 LINEBREAK
 (6) Satellite Imagery:LINEBREAK
 STARTUNORDEREDLIST STARTDOTPOINTSpot5 - 30m Captured 1/11/2001ENDDOTPOINT STARTDOTPOINTLandsat 5 ETM - 30m Captured 20/09/2004ENDDOTPOINT STARTDOTPOINTLandsat 5 ETM - 30m Captured 27/08/2004ENDDOTPOINT ENDUNORDEREDLIST Inputs and Processes - Draft Landuse Layer LINEBREAK
 1. Classification by Shire: The draft classification was first performed on each of the shires that made up the catchment. The VicMap digital cadastre of each shire was first clipped to the catchment boundary before the classification was undertaken. These clipped shires would eventually be merged to form the one whole dataset. LINEBREAK
 2. VGV Shire Valuation Dataset: The first step in the draft classification process was to use the Land Classification Codes (LCC) that were surveyed by the Valuers for each Shire. The Valuers assign an LCC code to each Property Number (PROPNUM) of a Shire's Vicmap Property cadastre. Using these Property Numbers, the Valuer's Landuse Dataset could then be linked to the corresponding shire's Vicmap Digital Property Cadastre. A Lookup Table was created that assigned an ALUM Classification Code to each of the 265 LCC codes. This Lookup table was then linked to the digital cadastre to provide a base landuse dataset for each shire. As the Valuer's dataset also contained other relevant information pertaining to landuse, this helped with the classification of the anomalies that were present within the LCC Codes (Eg. LCC Code 666 = Mixed Use Farming). Information regarding landuse such as the amount of land that is dryland, irrigated, horticulture, cropping or grazing may also be provided within the dataset, which could then be used to assign an ALUM code to the property. It must be noted that the quality of this information varied from shire to shire. The product of this Valuer's information made up the base of the draft landuse dataset for each shire.LINEBREAK
 3. Public Land Management Layer: The next step in the process was to classify the public land (i.e. Conservation and natural environments) within each shire. The latest 1:100,000 Public Land Management Layer from the CGDL (September 2003) was overlayed on the digital cadastre and an appropriate ALUM code was then assigned to each corresponding polygon.LINEBREAK
 Inputs and Processes - Final Landuse Layer LINEBREAK
 1. Refinement of Draft Landuse Layer: Building upon the Draft Landuse layer, cadastre parcels that remained unclassified or incorrectly classified in the intensive used areas of towns and irrigated horticulture were classified based upon aerial photography and satellite imagery. LINEBREAK
 2. Merging Datasets: The completed landuse datasets of each shire were then merged together to produce the overall coverage of the catchment extent. Positional accuracy is 25-100m. The accuracy of the land use attributes has been determined through a validation procedure. Validation was carried out for each shire, shortly after the completion of the land use data layer. 50 random sample sites were generated for every 245,000Ha. The number of sample sites allocated to each land use was proportional to the area of each land use class in each validation area. Land uses at sample sites were recorded by independent observers. An error matrix was constructed for each validation area, comparing mapped land use to independently observed land use classes. The validation results produce an attribute accuracy of 92.5%LINEBREAK
 Data Collation Integration of existing datasets containing information relating to landuse including remotely sensed Landsat 5 ETM, SPOT, aerial photography, DPI/DSE Corporate datasets including cadastre, public land, infrastructure and tree cover, and VGV Shire Valuation Datasets.LINEBREAK
 Interpretation This stage involved interpreting landuse, by assigning appropriate landuse codes to the source datasets and preparing draft landuse maps for verification and field checking.LINEBREAK
 Verification Field verification of draft landuse maps included the annotation of field maps on the basis of expert advice and field checking. The primary focus of this activity was to capture agricultural landuse and incorporated extensive windscreen surveys, utilising mobile mapping technology and local knowledge of DPI/DSE staff.LINEBREAK
 Final Editing Final editing was carried out using ArcGIS 9.1, ArcView 3.3 and ArcInfo Workstation.</gco:CharacterString></gmd:statement>
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