Ada beberapa metode transformasi spektral di Earth Engine. Hal ini mencakup metode
instance pada gambar seperti normalizedDifference()
, unmix()
,
rgbToHsv()
, dan hsvToRgb()
.
Penajaman pan
Pan sharpening meningkatkan resolusi gambar multiband melalui
peningkatan yang disediakan oleh gambar pankromatik yang sesuai dengan resolusi yang lebih baik.
Metode rgbToHsv()
dan hsvToRgb()
berguna untuk ketajaman panning.
Editor Kode (JavaScript)
// Load a Landsat 8 top-of-atmosphere reflectance image. var image = ee.Image('LANDSAT/LC08/C02/T1_TOA/LC08_044034_20140318'); Map.addLayer( image, {bands: ['B4', 'B3', 'B2'], min: 0, max: 0.25, gamma: [1.1, 1.1, 1]}, 'rgb'); // Convert the RGB bands to the HSV color space. var hsv = image.select(['B4', 'B3', 'B2']).rgbToHsv(); // Swap in the panchromatic band and convert back to RGB. var sharpened = ee.Image.cat([ hsv.select('hue'), hsv.select('saturation'), image.select('B8') ]).hsvToRgb(); // Display the pan-sharpened result. Map.setCenter(-122.44829, 37.76664, 13); Map.addLayer(sharpened, {min: 0, max: 0.25, gamma: [1.3, 1.3, 1.3]}, 'pan-sharpened');
import ee import geemap.core as geemap
Colab (Python)
# Load a Landsat 8 top-of-atmosphere reflectance image. image = ee.Image('LANDSAT/LC08/C02/T1_TOA/LC08_044034_20140318') # Convert the RGB bands to the HSV color space. hsv = image.select(['B4', 'B3', 'B2']).rgbToHsv() # Swap in the panchromatic band and convert back to RGB. sharpened = ee.Image.cat( [hsv.select('hue'), hsv.select('saturation'), image.select('B8')] ).hsvToRgb() # Define a map centered on San Francisco, California. map_sharpened = geemap.Map(center=[37.76664, -122.44829], zoom=13) # Add the image layers to the map and display it. map_sharpened.add_layer( image, { 'bands': ['B4', 'B3', 'B2'], 'min': 0, 'max': 0.25, 'gamma': [1.1, 1.1, 1], }, 'rgb', ) map_sharpened.add_layer( sharpened, {'min': 0, 'max': 0.25, 'gamma': [1.3, 1.3, 1.3]}, 'pan-sharpened', ) display(map_sharpened)
Pemisahan spektrum
Pemisahan spektral diterapkan di Earth Engine sebagai metode image.unmix()
.
(Untuk metode yang lebih fleksibel, lihat halaman Transformasi Matriks). Berikut adalah contoh pemisahan Landsat 5 dengan endmember perkotaan,
vegetasi, dan air yang telah ditentukan sebelumnya:
Editor Kode (JavaScript)
// Load a Landsat 5 image and select the bands we want to unmix. var bands = ['B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7']; var image = ee.Image('LANDSAT/LT05/C02/T1/LT05_044034_20080214') .select(bands); Map.setCenter(-122.1899, 37.5010, 10); // San Francisco Bay Map.addLayer(image, {bands: ['B4', 'B3', 'B2'], min: 0, max: 128}, 'image'); // Define spectral endmembers. var urban = [88, 42, 48, 38, 86, 115, 59]; var veg = [50, 21, 20, 35, 50, 110, 23]; var water = [51, 20, 14, 9, 7, 116, 4]; // Unmix the image. var fractions = image.unmix([urban, veg, water]); Map.addLayer(fractions, {}, 'unmixed');
import ee import geemap.core as geemap
Colab (Python)
# Load a Landsat 5 image and select the bands we want to unmix. bands = ['B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7'] image = ee.Image('LANDSAT/LT05/C02/T1/LT05_044034_20080214').select(bands) # Define spectral endmembers. urban = [88, 42, 48, 38, 86, 115, 59] veg = [50, 21, 20, 35, 50, 110, 23] water = [51, 20, 14, 9, 7, 116, 4] # Unmix the image. fractions = image.unmix([urban, veg, water]) # Define a map centered on San Francisco Bay. map_fractions = geemap.Map(center=[37.5010, -122.1899], zoom=10) # Add the image layers to the map and display it. map_fractions.add_layer( image, {'bands': ['B4', 'B3', 'B2'], 'min': 0, 'max': 128}, 'image' ) map_fractions.add_layer(fractions, None, 'unmixed') display(map_fractions)
