Add existing Dataset Title/Name

S-Bronson commented 1 year ago

Follow the underlying template when creating an update request for an existing dataset in the awesome-gee-community-catalog.

Dataset Name and Catalog Page

Dataset Name and provide a link to the current dataset page.

Canada Landsat Derived Wildfire disturbance 1985-2020 https://gee-community-catalog.org/projects/ca_forest_fire/

Dataset update, version, and release date

Describe updates made to the dataset, including update date, release, and/or version number pertaining to it.

“Canada Landsat-Derived Wildfire disturbance 1985-2020” remains the same as original upload, “Canada Landsat-Derived Forest Wildfire Change Magnitude dNBR (1985-2020)” dataset has been added. Wildfire Change Magnitude dNBR 1985-2020 data is a product of the original Canada Landsat Derived Wildfire disturbance 1985-2020 upload.

Updated dataset link

Link to the updated dataset. If the dataset is already an Earth Engine image collection provide the snippet

See links below. Separate links for “Canada Landsat-Derived Wildfire disturbance 1985-2020” and “Canada Landsat-Derived Forest Wildfire Change Magnitude dNBR (1985-2020)”

Reason for update

If you own a particular dataset you should provide a reason for dataset update like reanalysis performed, a version was upgraded or if the data was temporarily removed for assessment, and so on.

Adding datasets that are related to the original upload. Original “Canada Landsat-Derived Wildfire disturbance 1985-2020” text and links remain unchanged, new text and links added for “Canada Landsat-Derived Forest Wildfire Change Magnitude dNBR (1985-2020)”.

Updated License

If the license remains the same just mention N/A

N/A

Relationship to Dataset

Owner/Maintainer/Curator or Reporter

Curator

Sample Code: Add a sample code maybe just adding your datasets in the code editor.

See code below (same code for “Canada Landsat-Derived Wildfire disturbance 1985-2020” new code for “Canada Landsat-Derived Forest Wildfire Change Magnitude dNBR (1985-2020)”.

Last updated: Last date the dataset was updated if known

Same as previous version, GEE: 2023-01-28

##################################################################################### ##################################################################################### This Text might be useful when updating the previous webpage

Title: Canada Landsat Derived Wildfire Disturbance 1985-2020 ##################################################################################### #####################################################################################

Canada Landsat-Derived Wildfire Disturbance 1985-2020

The annual forest change data included in this product is national in scope (entire forested ecosystem) and represents the wall-to-wall characterization of wildfire in Canada at a 30-m spatial resolution. The information outcomes represent 36 years of wildfire change over Canada’s forests, derived from a single, consistent, spatially explicit data source, derived in a fully automated manner. This demonstrated capacity to characterize forests at a resolution that captures human impacts is key to establishing a baseline for detailed monitoring of forested ecosystems from management and science perspectives. Time series of Landsat data were used to characterize national trends in stand replacing forest disturbances caused by wildfire and harvest for the period 1985–2020 for Canada's 650 Mha forested ecosystems.

Landsat data has a 30 m spatial resolution, so the change information is highly detailed and informative regarding both natural and human driven changes. These data represent annual stand replacing forest changes. The stand replacing disturbance types labeled are wildfire and harvest, with lower confidence wildfire and harvest, also shared. The distinction and sharing of lower class membership likelihoods is to indicate to users that some change events were more difficult to allocate to a change type, but are generally found to be in the correct category. For an overview on the data, image processing, and time series change detection methods applied, as well as information on independent accuracy assessment of the data, see (Hermosilla et al. 2016). The data available is Change year for Wildfire Events.

Disclaimer: Whole or parts of the dataset description were provided by the author(s) or their works.

Canada Landsat-Derived Forest Wildfire Change Magnitude dNBR (1985-2020)

Wildfire change magnitude dNBR 1985-2020. Spectral change magnitude for wildfires that occurred from 1985 and 2020 expressed via differenced Normalized Burn Ratio (dNBR), computed as the variation between the spectral values before and after a given change event. This layer value has been transformed for data storage efficiency. The actual dNBR value can be calculated as follows dNBR = value / 100. Higher dNBR values are related to higher burn severity.

Dataset Citation

Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, 2016. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054. (Hermosilla et al. 2016).

Code Snippet: Canada Landsat-Derived Wildfire Disturbance 1985-2020

var ca_forest_fire = ee.Image("projects/sat-io/open-datasets/CA_FOREST/CA_Forest_Fire_1985-2020");

Sample Code: https://code.earthengine.google.com/?scriptPath=users/sat-io/awesome-gee-catalog-examples:agriculture-vegetation-forestry/CA-FOREST-FIRE-1985-2020

Code Snippet: Canada Forest Wildfire dNBR (1985-2020)

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Will need new code here
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Sample Code:


// Define a dictionary which will be used to make legend and visualize image on map
var dict = {
  "names": [ 
    "1", "2","3","4","5","6","7","8","9","10","11","12","13","14","15","16",
    "17","18","19","20","21","22","23","24","25","26","27","28","29","30","31","32",
    "33","34","35","36","37","38","39","40","41","42","43","44","45","46","47","48",
    "49","50","51","52","53","54","55","56","57","58","59","60","61","62","63","64",
    "65","66","67","68","69","70","71","72","73","74","75","76","77","78","79","80",
    "81","82","83","84","85","86","87","88","89","90","91","92","93","94","95","96",
    "97","98","99","100","101","102","103","104","105","106","107","108","109","110 - 199",

  ],
    "colors": [
    "#0c1cad", "#171fb0", "#1f1db2", "#271db5", "#2f1db8", "#341cba",
    "#391cba", "#421cbd", "#481dbf", "#4a1bc2", "#511bc4", "#561ac7", "#5d1ac9", "#641bcc",
    "#6819cf", "#6f19d1", "#7217d4", "#7a18d6", "#7c15d6", "#8416d9", "#8814db", "#8d14de",
    "#9512e0", "#9910e3", "#9e0ee6", "#a60ce8", "#ab09eb", "#b007ed", "#b407ed", "#bf07ed",
    "#c707ed", "#ce07ed", "#d807f0", "#e007f0", "#ec07f0", "#f007ec", "#f007e4", "#f207df",
    "#f207d3", "#f207cb", "#f207c3", "#f505bd", "#f505b5", "#f505a9", "#f505a1", "#f50599",
    "#f70592", "#f70586", "#f7057e", "#f70576", "#fa056f", "#fa0567", "#fa055b", "#fa0553",
    "#fa054a", "#ff1500", "#ff2200", "#ff3300", "#ff3c00", "#ff4400", "#ff5100", "#ff5900",
    "#ff6200", "#ff6a00", "#ff7300", "#ff7b00", "#ff8400", "#ff8c00", "#ff9000", "#ff9900",
    "#ffa200", "#ffaa00", "#ffb200", "#ffbb00", "#ffc300", "#ffcc00", "#ffd400", "#ffd900",
    "#ffe100", "#ffea00", "#fff200", "#fffb00", "#ffff0a", "#ffff14", "#ffff21", "#ffff29",
    "#ffff2e", "#fffc36", "#fffc3d", "#fcf942", "#fcf947", "#fcfa4c", "#fcfa51", "#fcfa56",
    "#fcfa5d", "#fcfa60", "#faf764", "#faf56b", "#faf56e", "#faf575", "#faf67a", "#f7f37c",
    "#f7f383", "#f7f488", "#f7f48d", "#f5f190", "#f5f395", "#f5f39a", "#f2f19d", "#f2f1a2",

  ]};

Map.setCenter(-97.61655457157725,55.6280720462063,4)

// Add image to the map
Map.addLayer(image, {min:1, max:110, palette:dict['colors']}, 'Wildfire Change Magnitude dNBR')

/////////////////////////////////////////////////////////////////////////

var legend = ui.Panel({
  style: {
    position: 'middle-right',
    padding: '8px 15px'
  }
});

// Create and add the legend title.
var legendTitle = ui.Label({
  value: 'Wildfire Change Magnitude dNBR',
  style: {
    fontWeight: 'bold',
    fontSize: '18px',
    margin: '0 0 4px 0',
    padding: '0'
  }
});
legend.add(legendTitle);

var loading = ui.Label('Loading legend...', {margin: '2px 0 4px 0'});
legend.add(loading);

  // Creates and styles 1 row of the legend.
  var makeRow = function(color, name) {
    // Create the label that is actually the colored box.
    var colorBox = ui.Label({
      style: {
        backgroundColor: color,
        // Use padding to give the box height and width.
        padding: '8px',
        margin: '0 0 4px 0'
      }
    });

  // Create the label filled with the description text.
  var description = ui.Label({
    value: name,
    style: {margin: '0 0 4px 6px'}
  });

  return ui.Panel({
    widgets: [colorBox, description],
    layout: ui.Panel.Layout.Flow('horizontal')
  });
};
  var palette = dict['colors'];
  var names = dict['names'];
  loading.style().set('shown', false);

  for (var i = 0; i < names.length; i++) {
    legend.add(makeRow(palette[i], names[i]));
  }

// Print the panel containing the legend
print(legend);

Created by: Hermosilla et al. 2016

Curated by: Spencer Bronson and Samapriya Roy

keywords: Forest Fire, Forest inventory, Land cover, Landsat, Machine learning, Spectral change magnitude, Differenced Normalized Burn Ratio (dNBR),

Last updated: 2023-05-10

S-Bronson commented 1 year ago

Hey Sam,

I just want to point out that i have added this request to update the "Canada Landsat Derived Wildfire disturbance 1985-2020" dataset, but i have also reformatted the entry so it will be easier for you to upload.

The section of my request under these lines, "##################################################################################### ##################################################################################### This Text might be useful when updating the previous webpage" is the same format as your "To submit a new dataset for the community catalog use this link" option.

I hope this helps!

S-Bronson commented 1 year ago

Hello,

I wanted to double check that this request is still on the roster for updates. If there is any additional information that i can provide to help, i would be happy to provide it

All the best, Spencer

samapriya commented 1 year ago

Apologies for the delay @S-Bronson Been busy with a few things, on track and I will have time to work on this next week. Thank you for being patient

samapriya commented 1 year ago

This has now been completed will be released this week :) thank you for being patient

S-Bronson commented 1 year ago

Thank you again for taking the time to make these uploads! Very much appreciated!

samapriya / awesome-gee-community-datasets