Published
Edited
Apr 23, 2021
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md`### Landsat 8
<pre><code><strong>Sensors:</strong> <em>OLI</em> bands(1-9) and <em>TIRS</em> (bands 10-11)</code></pre>
<pre><code><strong>Spatial Resolution:</strong> bands 1-7,9 = <em>30m</em>. Band 8 = <em>15m</em>. Bands 10-11 = <em>100m</em></code></pre>
<pre><code><strong>Temporal Resolution:</strong> 16 Days</code></pre>
<pre><code><strong>Scene size:</strong> 185 km × 180 km </code></pre>
<pre><code><strong>Map Projection:</strong> UTM </code></pre>
`
md`### Acquiring Data:
Find a tile using https://search.remotepixel.ca.
Here's what we use in this dataset: https://landsatonaws.com/L8/045/032/LC08_L1TP_045032_20180811_20180815_01_T1
`
html`<img src="http://landsat-pds.s3.amazonaws.com/c1/L8/045/032/LC08_L1TP_045032_20180811_20180815_01_T1/LC08_L1TP_045032_20180811_20180815_01_T1_thumb_small.jpg" width="300">`
geoblaze = require('geoblaze@0.3.2')
md `### Band 5, NIR (Near Infrared), comprises wavelengths 0.851 - 0.879µm`
band5Raster = geoblaze.load(urlBand5)
band5Raster.noDataValue = 0;
band5Raster.toCanvas({width: 500, height: 500})
md`### Band 7, SWIR (Short-Wave Infrared) 2, comprises wavelengths 2.107 - 2.294 µm`
urlBand7 = "https://s3.amazonaws.com/geoblaze/LC08_L1TP_045032_20180811_20180815_01_T1_B7_100x100.TIF"
band7Raster = geoblaze.load(urlBand7)
band7Raster.noDataValue = 0;
band7Raster.toCanvas({width:500, height:500})
newValues = {
// we know each raster is only one band, so used index [0]
const band5Values = band5Raster.values[0];
const band7Values = band7Raster.values[0];
// we know height and width same between rasters
const { height, width } = band5Raster;
return [band5Values.map((band5Row, rowIndex) => {
const band7Row = band7Values[rowIndex];
// iterates through cells or columns in the current row
return band5Row.map((band5Value, band5ColumnIndex) => {
if (band5Value == band5Raster.noDataValue) {
return 999;
}
const band7Value = band7Row[band5ColumnIndex];
const R75 = band7Value / band5Value;
if (R75 > 0.25 && (band7Value - band5Value) > 0.3 && band7Value > 0.5) {
return 1;
} else {
return 0;
}
});
})];
};
parseGeoRaster = require("georaster@1.5.4")
newGeoRaster = {
const { height, pixelHeight, pixelWidth, width, xmin, xmax, ymin, ymax } = band5Raster;
const metadata = {
height,
noDataValue: 999,
pixelHeight,
pixelWidth,
width,
xmin,
xmax,
ymin,
ymax
};
return parseGeoRaster(newValues, metadata)
}
resultCanvas = newGeoRaster.toCanvas({ height: 500, width: 500 })
Type JavaScript, then Shift-Enter. Ctrl-space for more options. Arrow ↑/↓ to switch modes.
md`#### You can read more about the algorithm utilized here: Wilfrid Schroeder, Patricia Oliva, Louis Giglio et al. Active fire detection using Landsat-8/OLI data
https://doi.org/10.1016/j.rse.2015.08.032.
(http://www.sciencedirect.com/science/article/pii/S0034425715301206)`
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