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On January 16, 2020 at 4:16:19 PM +1100, National Native Title Tribunal:

Updated description of Google Earth Engine Burnt Area Map (GEEBAM) from
In collaboration with the University of NSW, the NSW Department of Planning Infrastructure and Environment (DPIE) Remote Sensing and Landscape Science team has developed a rapid mapping approach to find out where wildfires in NSW have affected vegetation. We call it the Google Earth Engine Burnt Area Map (GEEBAM) and it relies on Sentinel 2 satellite imagery. The product output is a TIFF image with a resolution of 15m. Burnt Area Classes: 1. Little change observed between pre and post fire 2. Canopy unburnt - A green canopy within the fire ground that may act as refugia for native fauna, may be affected by fire 3. Canopy partially affected - A mix of burnt and unburnt canopy vegetation 4. Canopy fully affected -The canopy and understorey are most likely burnt Using GEEBAM at a local scale requires visual interpretation with reference to satellite imagery. This will ensure the best results for each fire or vegetation class. It has been designed for rapid response and is not trained with ground data. Nor does it offer a confidence interval or report on accuracy. Important Note: GEEBAM is an interim product and there is no ground truthing or assessment of accuracy. It is updated fortnightly. GEEBAM version: GEEBAMvX_YYYYMMDD - uses a start date of the 1 July 2019 and an end date written as YYYYMMDD. The date is recorded in the VerDate field of the attribute table.
to
In collaboration with the University of NSW, the NSW Department of Planning Infrastructure and Environment (DPIE) Remote Sensing and Landscape Science team has developed a rapid mapping approach to find out where wildfires in NSW have affected vegetation. We call it the Google Earth Engine Burnt Area Map (GEEBAM) and it relies on Sentinel 2 satellite imagery. The product output is a TIFF image with a resolution of 15m. Burnt Area Classes: 1. Little change observed between pre and post fire 2. Canopy unburnt - A green canopy within the fire ground that may act as refugia for native fauna, may be affected by fire 3. Canopy partially affected - A mix of burnt and unburnt canopy vegetation 4. Canopy fully affected -The canopy and understorey are most likely burnt Using GEEBAM at a local scale requires visual interpretation with reference to satellite imagery. This will ensure the best results for each fire or vegetation class. It has been designed for rapid response and is not trained with ground data. Nor does it offer a confidence interval or report on accuracy. Important Note: GEEBAM is an interim product and there is no ground truthing or assessment of accuracy. It is updated fortnightly. GEEBAM version: GEEBAMvX_YYYYMMDD - uses a start date of the 1 July 2019 and an end date written as YYYYMMDD. The date is recorded in the VerDate field of the attribute table. Please see Google Earth Engine Burnt Area Factsheet

              
    
          
          
        
        
            f 1 { f 1 {
            2   "author": null, 2   "author": null,
            3   "author_email": null, 3   "author_email": null,
            4   "creator_user_id": "8d2ac61a-d63a-4456-a00d-b35fee4c4025", 4   "creator_user_id": "8d2ac61a-d63a-4456-a00d-b35fee4c4025",
            5   "id": "60fe872a-daf7-49d4-8a54-49ee414aaed2", 5   "id": "60fe872a-daf7-49d4-8a54-49ee414aaed2",
            6   "license_id": "cc-by", 6   "license_id": "cc-by",
            7   "maintainer": null, 7   "maintainer": null,
            8   "maintainer_email": null, 8   "maintainer_email": null,
            9   "metadata_created": "2020-01-16T05:04:44.730939", 9   "metadata_created": "2020-01-16T05:04:44.730939",
            n 10   "metadata_modified": "2020-01-16T05:13:32.482091", n 10   "metadata_modified": "2020-01-16T05:16:18.848897",
            11   "name": "google-earth-engine-burnt-area-map-geebam", 11   "name": "google-earth-engine-burnt-area-map-geebam",
            12   "notes": "In collaboration with the University of NSW, the NSW  12   "notes": "In collaboration with the University of NSW, the NSW 
            13 Department of Planning Infrastructure and Environment (DPIE) Remote  13 Department of Planning Infrastructure and Environment (DPIE) Remote 
            14 Sensing and Landscape Science team has developed a rapid mapping  14 Sensing and Landscape Science team has developed a rapid mapping 
            15 approach to find out where wildfires in NSW have affected vegetation.  15 approach to find out where wildfires in NSW have affected vegetation. 
            16 We call it the Google Earth Engine Burnt Area Map (GEEBAM) and it  16 We call it the Google Earth Engine Burnt Area Map (GEEBAM) and it 
            17 relies on Sentinel 2 satellite imagery. The product output is a TIFF  17 relies on Sentinel 2 satellite imagery. The product output is a TIFF 
            18 image with a resolution of 15m.\r\nBurnt Area Classes: \r\n1. Little  18 image with a resolution of 15m.\r\nBurnt Area Classes: \r\n1. Little 
            19 change observed between pre and post fire \r\n2. Canopy unburnt - A  19 change observed between pre and post fire \r\n2. Canopy unburnt - A 
            20 green canopy within the fire ground that may act as refugia for native  20 green canopy within the fire ground that may act as refugia for native 
            21 fauna, may be affected by fire \r\n3. Canopy partially affected - A  21 fauna, may be affected by fire \r\n3. Canopy partially affected - A 
            22 mix of burnt and unburnt canopy vegetation \r\n4. Canopy fully  22 mix of burnt and unburnt canopy vegetation \r\n4. Canopy fully 
            23 affected -The canopy and understorey are most likely burnt\r\nUsing  23 affected -The canopy and understorey are most likely burnt\r\nUsing 
            24 GEEBAM at a local scale requires visual interpretation with reference  24 GEEBAM at a local scale requires visual interpretation with reference 
            25 to satellite imagery. This will ensure the best results for each fire  25 to satellite imagery. This will ensure the best results for each fire 
            26 or vegetation class. It has been designed for rapid response and is  26 or vegetation class. It has been designed for rapid response and is 
            27 not trained with ground data. Nor does it offer a confidence interval  27 not trained with ground data. Nor does it offer a confidence interval 
            28 or report on accuracy.\r\nImportant Note: GEEBAM is an interim product  28 or report on accuracy.\r\nImportant Note: GEEBAM is an interim product 
            29 and there is no ground truthing or assessment of accuracy. It is  29 and there is no ground truthing or assessment of accuracy. It is 
            30 updated fortnightly.\r\n\r\nGEEBAM version: \r\n\r\nGEEBAMvX_YYYYMMDD  30 updated fortnightly.\r\n\r\nGEEBAM version: \r\n\r\nGEEBAMvX_YYYYMMDD 
            31 -  uses a start date of the 1 July 2019 and an end date written as  31 -  uses a start date of the 1 July 2019 and an end date written as 
            32 YYYYMMDD. The date is recorded in the VerDate field of the attribute  32 YYYYMMDD. The date is recorded in the VerDate field of the attribute 
            n 33 table.\r\n\r\n", n 33 table.\r\n\r\nPlease see Google Earth Engine Burnt Area 
            34 Factsheet\r\n",
            34   "owner_org": "da61219b-ad9a-4667-bb71-7fa5f99333b1", 35   "owner_org": "da61219b-ad9a-4667-bb71-7fa5f99333b1",
            35   "private": false, 36   "private": false,
            t 36   "revision_id": "810bc5ac-7c63-4b87-8443-9b057c00c6e6", t 37   "revision_id": "19e467ff-162e-4910-8742-787a085eb539",
            37   "state": "active", 38   "state": "active",
            38   "title": "Google Earth Engine Burnt Area Map (GEEBAM)", 39   "title": "Google Earth Engine Burnt Area Map (GEEBAM)",
            39   "type": "dataset", 40   "type": "dataset",
            40   "url": "", 41   "url": "",
            41   "version": null 42   "version": null
            42 } 43 }