20240311 19115600 1.0 FALSE qld_landsat_fire_scars_2010_x 137.994863 153.545706 -29.177647 -10.059912 1 002 Geographic GDA2020 Angular Unit: Degree (0.017453) <GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.0.0'><WKT>GEOGCS[&quot;GDA2020&quot;,DATUM[&quot;GDA2020&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433],AUTHORITY[&quot;EPSG&quot;,7844]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>999999999.99999988</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>8.983152841195215e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>7844</WKID><LatestWKID>7844</LatestWKID></GeographicCoordinateSystem> 20240311 17394400 20240311 17394400 ISO19139 /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCACFAMgDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD3+iii gAooooAKKKKACiiigAooooAKKO1Iucc469qAFooooAKKKKACiiigAooooAKKKKACiiigAooooAKK KKACiiigAooooAKKKKACiiigBrNg4Gfwpx46mot485s7MKODnnn/ACKWKUSmQBSNjbee/AOf1qU9 RtElFFFUIKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKazBSBnqcY9aAHUUx XDOyjI2nByOtOZgoyelAGfOwa7GM+STtdgwwG6ZyDxjpVkTxiV1IJkBGUHJHHXHbvVeGO5g+0PNM gV8SDIGAecj17D8Pfmq2l6vFdS/ZUCm4HzygHjB7gjIPUcEg/jWCvGW+5o9V6GjbEBSN25uuT1we QD+f/wCqrFVFZoZFQIREvAZmyf17Y5/Lrmrdb2S0RmFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFF FFABRRRQAUUUUAFMk24Ct36U+mSsqruc4Ud/Q9KTD0K9sz+Xkq4jHCqw+dfYj6Y/OrBB3Dc2QTwA tUFS3trhppJZi0sm8Ix+WM4AOOBgeue5PrU9riKJsySEM7EeYMFQSTj8M4pLTQp23LX3gQG/+tWc tgINUnvwIQ0iJGAEwcA+vvn+XIq0YX+2ibz3EZTb5fbOc5H65p7shccjKfMRjJxg0NX3D0IYlVJJ ACnZmCnBU4wOD0zg1ZU5z3A4zUcQG9myCTnOFxjvg9+5/OpBnJzjHaq06EsdRRRQAUUUUAFFFFAB RRRQAUUUUAFFFFABRRRQAUUUUAFFFFABTJU3p05HIOASD7Z70+igCnd8NGZI/Mjz8zAfd9+vvUqx 4jVGYr5eDkN296lIyen60pAOcgHIweKTQ7jdisBkZ6HP0ORSFAiu0aLvI/MgcU4/c+UZz0wcUwJK UQPICf48LgNx2Hbn3oBCQRsIkDsWZe5HP+ffipDgKc9BTcgk4bGGGcY59jTuqnOcduOaaQhqbkJD OrZPHYgf15+lSVG4YOpU+zdMt1pYyduGHK8HnNAD6KKKACiiigAooooAKKKKACiiigAooooAKKKK ACiiigAo79KKQnA70ALSHnjPPWlowM5xzQAi5wM0tAx2ooAaxwueePTmmsNiOWORjJ+Wn4+bPcD8 KTbxjAIOc5oGRxDYmMAbRj5R/SkRvKKrK43sTzx68Dt/nNMDOZJAVKqcfN0/X/P8qJFjbDOu1iRt woJU9Pfnkj05o6Ai1RTIXWSMMhytPoEFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABSc56DFL RQAnbB/SloooAaiLGgRRhR05pRnBzj2oJx9KWgA6U0EH5gBz39RSOpdCuRyMHIyD+FOAAJx396AG NGC2QdrZByOvH9KikRmdSC2FbI569sH27/gKlDN3XP0GP500lNhDNgemeTQ9hrcahwSwySVBwTjt +VTqcqDggkZwetU2XE6kAqCQoKDJHX8vy6VcUgg4x15we9Sm3uOSQtFFFUSFFFFABRRRQAUUUUAF FFFABRRRQAUUUUAFFFFABRRRQAjAkYDFfcUtFJtBzkZz60AHOfagjI/+vS0x03/xH6dqAIRIsyM6 Elx0D8dzg/jioyqyo25SpYZPGSCPp9fp+dWPIU/eZmGMY6CnLGFYkZ56+9CYFK1csGQMfMX1PqTj +X0q+rKy5VgwPcGmGIMxY8E+nUingADAo6j6C0UUUCCiiigAooooAKKKKACiiigAooooAKKKKACi iigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigD/9k= qld_landsat_fire_scars_2010_x Feature Class 452438 Fire scars over the period January to December 2010 Landsat 5 and 7 OBJECTID OBJECTID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. ID ID Double 8 0 0 Feature number ID Numerical GRIDCODE GRIDCODE Double 8 0 0 1-12: month (of Landsat acquisition) when fire scar was first detected; 254: crop/water masked (using Current Queensland Land Use Mapping) - no fire scar detection conducted. Landsat imagery 0 255 OVERRIDE Override Blob 0 0 0 Associated with data representation linked to GRIDCODE GRIDCODE Representation RuleID RuleID Integer 4 0 0 Associated with data representation linked to GRIDCODE GRIDCODE January, February, March, April, May, June, July, August, September, October, November, December AREA AREA Double 8 0 0 LEN LEN Double 8 0 0 month month Integer 4 0 0 fire_id fire_id String 255 0 0 state state String 255 0 0 agency agency String 255 0 0 year year Integer 4 0 0 capt_method capt_method String 255 0 0 area_ha area_ha Double 8 0 0 perim_km perim_km Double 8 0 0 MONTH_DESC MONTH_DESC String 25 0 0 Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. Shape_Area Shape_Area Double 8 0 0 Area of feature in internal units squared. Esri Positive real numbers that are automatically generated. {4AA63701-2A04-48D3-9FFF-03D5AC6233E6} dataset DSITI, Lisa Collett Department of Science, Information Technology and Innovation Senior Scientist, Remote Sensing Centre (07) 3170 5673 lisa.collett@dsiti.qld.gov.au 20240311 ArcGIS Metadata 1.0 File Geodatabase Feature Class 10.4.1 DNRM, Open Data Department of Natural Resources and Mines Senior Product Officer (07) 3330 4438 opendata@dnrm.qld.gov.au Open the Queensland Spatial Catalogue (QSpatial). Select the large SEARCH button and all available records are displayed. Select one of the four filter options provided and then the further options within the filter. The resultant search is then displayed. Select your record and complete the order. Queensland Spatial Catalogue 2.0 FGDB Whole of dataset, although clipped areas are available through QSpatial 1000 http://qldspatial.information.qld.gov.au/catalogue/custom/search.page?q=%22Landsat fire scars 2010 Queensland%22 qld_landsat_fire_scars_2010_x Landsat fire scars 2010 2013-11-14 DSITI, Lisa Collett Department of Science, Information Technology and Innovation Senior Scientist, Remote Sensing Centre (07) 3170 5673 lisa.collett@dsiti.qld.gov.au DSITI, Dan Tindall Department of Science, Information Technology and Innovation Principal Scientist, Remote Sensing Centre (07) 3170 5688 AU dan.tindall@dsiti.qld.gov.au http://www.qld.gov.au/environment/land/vegetation/mapping/firescar/ DSITI, Dan Tindall Department of Science, Information Technology and Innovation Principal Scientist, Remote Sensing Centre (07) 3170 5688 dan.tindall@dsiti.qld.gov.au DSITI, Dan Tindall Department of Science, Information Technology and Innovation Principal Scientist, Remote Sensing Centre DSITI, Assistant Director General, Science Delivery Department of Science, Information Technology and Innovation A/D-G, Science Delivery This data set is a statewide annual composite of fire scars (burnt area) derived from all available Landsat 5 and 7 images acquired over Queensland in the period January to December 2010. Fire scars have been mapped using automated Landsat time series change detection. Provides a graphical representation of fire scars in Queensland over the period January to December 2010 for use in characterising burning patterns and changing fire regimes. © State of Queensland (Department of Science, Information Technology and Innovation), 2017 DSITI, Dan Tindall Department of Science, Information Technology and Innovation Principal Scientist, Remote Sensing Centre (07) 3170 5688 41 Boggo Road Dutton Park Qld 4102 AU dan.tindall@dsiti.qld.gov.au http://www.qld.gov.au/environment/land/vegetation/mapping/firescar/ DSITI, Lisa Collett Department of Science, Information Technology and Innovation Senior Scientist, Remote Sensing Centre (07) 3170 5673 lisa.collett@dsiti.qld.gov.au Queensland ANZLIC Search Words 2007-08-01 HAZARDS Fire HAZRDS Fire Mapping ANZLIC Search Words 2007-08-01 fire risk fire history fire regime emergency services burnt area Landsat Sentinel2 Common Search Terms 2015-05-22 Queensland HAZARDS Fire HAZRDS Fire Mapping fire risk fire history fire regime emergency services burnt area Landsat Sentinel2 All available Landsat 5 and 7 imagery acquired over Queensland in 2010 has been used. Due to limitations of satellite revist time, cloud cover and other data loss, this data set should not be considered a complete record of fire history for the period. Please review the quality reports below. © State of Queensland (Department of Science, Information Technology and Innovation), 2015 This material is licensed under a Creative Commons - Attribution 4.0 International licence. The Department of Science, Information Technology and Innovation requests attribution in the following manner: © State of Queensland (Department of Science, Information Technology and Innovation) 2017. Updated data available at http://qldspatial.information.qld.gov.au/catalogue/ . Unrestricted to all levels of government and community. Data is available to all government agencies, community groups and individuals. Dataset is available through physical supply and may be made available via web delivery tools, for example, through DNRM's internet sites. ISO 19115 (mapped from Qld Govt Information Security Standard IS18) Spatial Information Resource (SIR) Feature Class 2013-11-14 RSC.QLD_LANDSAT_FIRE_SCARS_2010_X Esri ArcGIS 13.0.6.36057 Bounding Box true 137.5 154.1 -30 -8.7 true ANZLIC Geographic Extent Name Register 2003-09-19 2 Queensland 2010-01-01T00:00:00 2010-12-31T00:00:00 true 137.994863 153.545706 -29.177647 -10.059912 Fire scars were automatically detected in Landsat imagery using time series change detection. A Landsat pixel is mapped as burnt if there has been a significant change in reflectance relative to the time series due to the effects of fire e.g. presence of charcoal or ash, removal of foliage, scorch. 1-12: month (of Landsat acquisition) when fire scar was first detected; 254: crop/water masked (using Current Queensland Land Use Mapping) - no fire scar detection conducted. Note: fire scars may persist and continue to be detected for several months in the image time sequence. Where there has been fire scar persistence or multiple fire scars recorded for a given pixel within the compositing year, the earliest month of detection is recorded. Public Metadata Access Level Landsat does not provide a complete record of fire history for this period. This is mostly due to the sensor revisit time of 8-16 days which may be further limited by cloud and cloud shadow obstruction and striping in the imagery. A fire scar signal may not be evident in the image sequence for long time periods, particularly in savanna regions in North Queensland. Ash/char can be blown or washed away over short periods of time (~weeks) and the fire scar is often rapidly masked by green-flush and vegetation resprouting in subsequent images. Data loss from SLC-Off image striping in Landsat-7 imagery (2003 onwards), cloud cover, haze and smoke, as well as errors in removing cloud and shadow (fire scars which are mapped as cloud shadow) can result in missed fires. Additionally, fires may be captured in the Landsat imagery but missed or under-mapped by the classifier for the following reasons: the fire may be too small or patchy to detect; cool grass/understorey fires may be obscured by the unburnt tree canopy; or the fire may be misclassified as non-fire related change or cloud shadow. An assumption that burnt areas decline in reflectance over time may not always be true and missed fire scars have been noted (e.g. spinifex grasses). Fire scars smaller than 1 ha (approximately 3 pixels) may not be resolved. Validation of Queensland automated Landsat fire scar maps (1987-2012) found the method mapped over 80% of all fire scars captured in Landsat imagery. The omission error does not include fire scars missed because of Landsat data loss e.g. SLC-Off striping, or gaps in the Landsat record e.g. due to cloud or revisit time. This has not been quantified due to the lack of a validation data set which is independent from the sensor being used (Landsat). The automated Queensland fire scar maps (1987-2012) were validated using a Landsat-derived data set of 500,000 points, sampling the spatial and temporal variabillity across Queensland. See Goodwin and Collett, 2016. Development of an automated method for mapping fire history captured in Landsat TM and ETM+ time series across Queensland, Australia. Remote Sensing of Environment 148 pp 206-221. Department of Science, Information Technology and Innovation capture process 2013-11-14 The data set is to a standard determined as fit for the purpose for which it was produced. true False fires or over-mapping of fire scars may result from the presence of cloud shadows, areas of high land-use change (e.g. cropping), black soils, and inundation e.g. tidal flats, wetlands, ephemeral lakes and channels. These features often spectrally and temporally resemble fire scars. Validation of Queensland automated Landsat fire scar maps (1987-2012) measured the average rate of false fires (commission error) at 30%. False fires are far more common in image dates affected by striping in the Landsat-7 source imagery (particularly 2010-2013) as the data is fragmented and less reliable. The automated Queensland fire scar maps (1987-2012) were validated using a Landsat-derived data set of 500,000 points, sampling the spatial and temporal variabillity across Queensland. See Goodwin and Collett, 2016. Development of an automated method for mapping fire history captured in Landsat TM and ETM+ time series across Queensland, Australia. Remote Sensing of Environment 148 pp 206-221. Department of Science, Information Technology and Innovation capture process 2013-11-14 The data set is to a standard determined as fit for the purpose for which it was produced.. true All the data described here has been generated from the analysis of Landsat TM and ETM+ data acquired as ortho-rectified L1T images from USGS. Landsat imagery has a spatial resolution of 30m. Analyses by the USGS suggest that the geometric error is well below a single pixel (Storey et al, 2014). Reference: Storey J, Choate M, and Lee K, (2014) Landsat 8 Operational Land Imagery On-Orbit Geometric Calibration and Performance Remote Sensing, 6(11), pp. 11127-11152. Department of Science, Information Technology and Innovation capture process 2013-11-14 The data is to a standard determined as fit for the purpose for which it was collected. true Validation of individual Landsat fire scar classifications for Queensland (1987-2012) measured the average fire scar omission error (missed fires) at 15% in the automated outputs. The average fire scar commission rate (false fires) was measured at 30%. The average fire scar classification accuracy was measured at greater than 99%. This is more a reflection of the small fraction of landscape burnt than the ability to detect fire scars. Annual composites from 2003 onwards are affected by data loss due to systematic striping in the Landsat 7 ETM+ imagery. This is due to the failure of the instrument's Scan Line Corrector (SLC-Off). This results in striping and fragmentation in the fire scar maps derived from SLC-Off imagery, decreased rates of detection, and increased number of false fires. Striping is particularly apparent in the fire scar products for the period 2011-2013, as Landsat 7 SLC-Off, was the predominant source of imagery available for fire scar mapping. Error rates are likely to be higher for this period. Rates of omissions are likely to be higher during wet season periods (Nov-February) in tropical and coastal regions where cloud cover may obscure the view of the surface for months at a time. The automated Queensland fire scar maps (1987-2012) were validated using a Landsat-derived data set of 500,000 points, sampling the spatial and temporal variabillity across Queensland. See Goodwin and Collett, 2016. Development of an automated method for mapping fire history captured in Landsat TM and ETM+ time series across Queensland, Australia. Remote Sensing of Environment 148 pp 206-221. Department of Science, Information Technology and Innovation capture process 2013-11-14 The data is to a standard determined as fit for the purpose for which it was produced. true Single date fire scar maps have been produced for all Queensland Landsat images (with up to 60% cloud cover), held by the Remote Sensing Centre, covering the period from 1987 (earliest Landsat 5 imagery) to present. The automated method for detecting fire scars was applied to the time series stack of Landsat imagery, for each of the 100 Landsat WRS Path/Rows covering Queensland. The 2010 fire scar product was produced using a dense time series of imagery covering the period from 1987 - 2013. Imagery in each time series stack was pre-processed to convert to surface reflectance, and screen out cloud and cloud shadow, topographic shadow, crop and water (described in Source). The automated time series method identifies large negative outliers in reflectance indices (based on NIR and SWIR1 bands) relative to the time series. Median filters were applied to smooth the time series and provide a reference for no change. A threshold of change was used to determine outliers. A watershed filter from the VIGRA Computer Vision Library (http://hci.iwr.uni-heidelberg.de/vigra) was then used to map a larger spatial extent of the hange using the detected outliers as seeds. The segmented change objects were then attributed as either burnt or unburnt using their thermal, reflective and contextual characteristics in a classification tree. All required thresholds and rules for classification were derived from a statewide calibration based on random points sampled from ten Path/Rows located strategically across Queensland. The method was validated using 500,000 independent random points from a further 10 Path/Rows across Queensland. Calibrated thresholds may not apply outside of the calibration region (i.e. Qld). Annual composites of fire scar maps for a given Path/Row were compiled from all available fire scar maps for the given year. Where a pixel was classified as burnt more than twice in a year, the earliest date of detection was recorded. Annual composites were mosaicked to produce state-wide annual fire scar maps. Finally, the statewide fire scar mosaic was converted from raster to polygon feature class (with no simplifying of polygons). References: Goodwin, N., and Collett, L. 2013. Development of an automated method for mapping fire history captured in Landsat TM and ETM time series across Queensland, Australia. Remote Sensing of Environment 148, 206-221. The set of all available Landsat-5 TM, Landsat-7 ETM+ and Landsat-8 OLI (with less than 60% cloud cover) acquired over Queensland for the period 1987 to 2013. Landsat imagery (including SLC-Off and cloud affected) was downloaded from the USGS (http://glovis.usgs.gov/) as ortho-corrected L1T images containing scaled radiance values. Images were converted from radiance to a standardised surface reflectance, to minimise atmospheric, topographic, and bi-directional effects following Flood et al, 2013. The thermal infrared band 6 was converted to top-of-atmosphere brightness temperature (Chander, Markham, and Helder, 2009) and resampled to 30m x 30m pixels to match reflectance data. No atmospheric correction for the thermal band was applied. All data were scaled to 16 bit range. Images containing moderate to high levels of cloud cover (up to 60%) were included in the time series stacks. Cloud and cloud shadow affected pixels were screened using time series based cloud and shadow masking described in Goodwin et al. 2013. Topographic shadow affected pixels were masked out using a ray casting technique described in Robertson (1989). The satellite and sun azimuth and zenith angles were calculated per pixel directly from the orbital geometry. Crops and permanent water bodies were masked out of all imagery using the most current Queensland Land Use Mapping (http://www.qld.gov.au/environment/land/vegetation/mapping/qlump/). References: Chander, G., Markham, B. L., and Helder, D. L. (2009). Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment, 113(5), 893-903. Flood, N., Danaher, T., Gill, T., and Gillingham, S. (2013). An Operational Scheme for Deriving Standardised Surface Reflectance from Landsat TM/ETM+ and SPOT HRG Imagery for Eastern Australia. Remote Sensing, 5(1), 83-109. Goodwin, N. R., Collett, L. J., Denham, R. J., Flood, N., and Tindall, D. (2013). Cloud and cloud shadow screening across Queensland, Australia: An automated method for Landsat TM/ETM+ time series. Remote Sensing of Environment, 134, 50-65. Robertson, K. Spatial transformation for rapid scan-line surface shadowing, IEEE Computer Graphics and Applications, 1989. 452438 EPSG 8.9.4(10.5.0)