Difficulty: Medium
Correct Answer: All of these
Explanation:
Introduction / Context:
Fresh, clean snow has a distinctive spectral signature that underpins snow mapping, albedo estimation, and melt monitoring from satellites. Understanding how reflectance changes from the visible through the near-infrared (near-IR) into the shortwave and thermal infrared helps choose optimal bands and interpret seasonal trends in cryospheric products.
Given Data / Assumptions:
Concept / Approach:
Snow's high visible reflectance arises from multiple scattering by air–ice interfaces in fine grains. As wavelength increases into the near-IR, ice absorption increases, reducing reflectance. In the shortwave IR beyond ~1.4 μm, strong absorption bands make reflectance low; thermal IR is governed by emission rather than reflection.
Step-by-Step Solution:
Visible: strong multiple scattering ⇒ high reflectance (bright snow).Near-IR: increasing ice absorption coefficient ⇒ reflectance decreases rapidly.Longer wavelengths (SWIR/TIR): strong absorption and thermal emission dominance ⇒ low apparent reflectance.
Verification / Alternative check:
Common snow indices (e.g., using a green/near-IR or red/SWIR contrast) exploit snow's bright-in-visible, dark-in-SWIR behaviour for robust discrimination from clouds/soil.
Why Other Options Are Wrong:
Common Pitfalls:
Confusing dirty/old snow (lower visible reflectance) with fresh snow, or assuming near-IR stays high like vegetation; in snow it falls markedly.
Final Answer:
All of these
Discussion & Comments