3.4. Image classificationBurn sever

3.4. Image classification
Burn severity was classified only for the Survey Line burn
image. This burn was selected for image classification
because it was the largest of the four burns and contained
the greatest number of field plots. We also had high resolution
aerial photography of this burn. Color digital aerial photographs
with 1-m pixel size were acquired on September 15,
2001, shortly after the fire stopped burning. Through visual
interpretation of the color digital photographs, 50 points were
located for each of the four burn severity classes (Table 4).
Based on a correlation analysis of the 13 remotely sensed
indices (Table 7), we selected the Normalized Burn Ratio for
burn severity image classification. The burn severity classes
corresponded to the same classes used in the field-based
Composite Burn Index (Table 4). For each index, we
determined threshold values based on the distribution of pixel
NBR values within each of the four burn severity classes.
These threshold values were then used to predict the burn

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3.4. Image classificationBurn severity was classified only for the Survey Line burnimage. This burn was selected for image classificationbecause it was the largest of the four burns and containedthe greatest number of field plots. We also had high resolutionaerial photography of this burn. Color digital aerial photographswith 1-m pixel size were acquired on September 15,2001, shortly after the fire stopped burning. Through visualinterpretation of the color digital photographs, 50 points werelocated for each of the four burn severity classes (Table 4).Based on a correlation analysis of the 13 remotely sensedindices (Table 7), we selected the Normalized Burn Ratio forburn severity image classification. The burn severity classescorresponded to the same classes used in the field-basedComposite Burn Index (Table 4). For each index, wedetermined threshold values based on the distribution of pixelNBR values within each of the four burn severity classes.These threshold values were then used to predict the burn

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3.4. Klasifikasi citra
Bakar keparahan diklasifikasikan hanya untuk Line Survey membakar
gambar. Luka bakar ini dipilih untuk klasifikasi citra
karena itu yang terbesar dari empat luka bakar dan berisi
jumlah terbesar dari plot lapangan. Kami juga memiliki resolusi tinggi
foto udara dari pembakaran ini. Warna foto udara digital
dengan ukuran pixel 1-m diperoleh pada 15 September,
2001 tak lama setelah api berhenti membakar. Melalui visual yang
interpretasi foto-foto digital warna, 50 poin yang
terletak untuk masing-masing kelas empat luka bakar tingkat keparahan (Tabel 4).
Berdasarkan analisis korelasi dari 13 penginderaan jauh
indeks (Tabel 7), kami memilih Ratio Bakar Normalized untuk
membakar klasifikasi citra keparahan. Kelas keparahan luka bakar
berhubungan dengan kelas yang sama digunakan dalam berbasis lapangan
Composite Index Bakar (Tabel 4). Untuk setiap indeks, kita
ditentukan nilai ambang berdasarkan distribusi pixel
nilai NBR dalam masing-masing kelas beratnya empat luka bakar.
Nilai ambang batas ini kemudian digunakan untuk memprediksi luka bakar

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