What remote sensing metric is commonly used to proxy chlorophyll and vegetation health?

• A. NDVI
• B. LIDAR height
• C. Thermal inertia
• D. Radar backscatter

Answer: (A)

The key idea is that chlorophyll affects how plants reflect light, and NDVI captures that signal using two specific light bands. NDVI compares red light, which chlorophyll strongly absorbs, with near-infrared light, which healthy vegetation reflects strongly. When vegetation is lush and actively photosynthesizing, red reflectance is low and NIR reflectance is high, producing a high NDVI value. This makes NDVI a widely used proxy for chlorophyll content and overall vegetation health across large spatial scales from satellite sensors.

In practice, NDVI is calculated from readily available red and NIR bands on many satellites, and values tend to rise with vegetation vigor and fall with stress or sparse cover. It’s a robust, interpretable first-look index for monitoring phenology, drought impact, and crop conditions, though it has limitations like sensitivity to soil color, atmosphere, and sensor calibration.

LIDAR height measures how tall and structured the vegetation is, not its chlorophyll content. Thermal inertia relates to how quickly surfaces heat up or cool down, which reflects temperature dynamics more than leaf pigment. Radar backscatter depends on moisture and surface roughness, and while related to biomass, it doesn’t directly proxy chlorophyll or vegetation health.