{ "currentVersion": 11.3, "cimVersion": "3.3.0", "id": 242, "name": "2016-2017 woody vegetation clearing", "type": "Feature Layer", "description": "The classes are identified by the [code] attribute as follows: 1- Pasture; 2- Crop; 3- Settlement; 4- Mine; 5- Infrastructure; 6- Timber plantation; 7- Thinning; 8- Missed clearing in previous period; 10- Natural disaster damage; 11- Natural tree death. Due to the range of overpass dates, the SLATS mapping period is not a precise 365-day period, and this also varies from scene to scene. This means that the area of clearing mapped in a given period is not necessarily comparable to the area mapped in another period; variations in the satellite overpass dates mean that reporting periods can be longer or shorter than a year. Therefore, for reporting, the total area of mapped clearing (hectares) is converted to an annual clearing rate (hectares/year) based on a 1st August\u20131st August period. This conversion makes the results comparable by re-weighting shorter or longer periods, based on the assumption that clearing occurs at a uniform rate throughout the year. Refer to section 2 of the 2015\u201316 report for more information: \u2018Land cover change in Queensland 2015\u201316: Statewide Landcover and Trees Study. (2017) Department of Environment and Science available online at http://www.qld.gov.au/environment/land/vegetation/mapping/slats-reports/. Refer to the \u2018Land cover change in Queensland' report relevant to the 2015-2016 data period for lineage information. Reports are available online at http://www.qld.gov.au/environment/land/vegetation/mapping/slats-reports/. The final raster mosaic was vectorised and attributed to a uniform set of attributes, consistent across all SLATS periods. Geometrically corrected Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) or Landsat 8 Operational Land Imager (OLI) L1T images are acquired from the USGS (http://earthexplorer.usgs.gov/), and radiometric standardisation, and topographic correction applied. Cloud, smoke and shadow contamination were masked, using automatic masks generated using the methods of Zhu & Woodcock (2012), combined with manual editing to ensure accuracy. All the data described here has been generated from the analysis of Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 OLI data acquired as ortho-rectified L1T images from USGS. Imagery has a spatial resolution of 30m. Analyses by the USGS suggest that the locational error is below a single pixel (Storey et al, 2014). Reference: Storey J, Choate M, and Lee K, (2014) \u2018Landsat 8 Operational Land Imagery On-Orbit Geometric Calibration and Performance\u2019 Remote Sensing, 6(11), pp. 11127-11152.", "geometryType": "esriGeometryPolygon", "sourceSpatialReference": { "wkid": 4283, "latestWkid": 4283, "xyTolerance": 8.98315284119521E-9, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -400, "falseY": -400, "xyUnits": 9.999999999999999E8, "falseZ": -100000, "zUnits": 10000, "falseM": -100000, "mUnits": 10000 }, "copyrightText": "© State of Queensland (Department of Environment and Science) 2020. 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