Flashcards

9 cards showing.

NDVI typical value ranges by land cover?

likely veg
  • 🪨 ≤ 0.1 — barren rock, sand, snow
  • 🌾 0.2 – 0.3 — shrubland, grassland
  • 🌳 0.6 – 0.8 — temperate / tropical rainforest
  • 💧 Negative — water, shadow

Beyond standard VIs — two linear transforms?

maybe veg
  • PCA (Principal Component Analysis) — decorrelates bands into components ordered by variance. PC1 usually captures brightness.
  • K-T (Kauth-Thomas) Tasseled Cap — fixed linear transform for Landsat. Produces interpretable axes: Brightness, Greenness, Wetness.

EVI — formula and coefficients?

essential veg

Think of EVI as NDVI’s smarter cousin. It does two extra tricks:

  • Uses the blue band to subtract atmospheric haze that fools NDVI on smoggy days.
  • Adds a soil-adjustment factor so dry dirt doesn’t artificially inflate the score.

Use EVI when NDVI flatlines — i.e., over thick rainforest canopy where every leaf already maxes NDVI out. EVI keeps climbing where NDVI gets stuck.

🔬 Science / formula

EVI = [(NIR − Red) / (NIR + C₁·Red − C₂·Blue + L)] · (1 + L)

C₁ = 6.0, C₂ = 7.5, L = 1.0 (MODIS standard). Corrects NDVI for atmosphere (blue band) and soil (L).

💡

EVI = Enhanced with the Blue band. Coefficients 6-7-1 (six-seven-one). Doesn't saturate in dense canopy like NDVI does.

NDVI of AVHRR imagery — what does it show?

maybe veg

Continental US NDVI through the seasons (Jan → Dec):

  • 🌴 Coasts + South stay green year-round
  • 🌽 Midwest pulses with the growing season
  • 📊 Used for: drought monitoring, crop stress, continental phenology

🛰️ AVHRR on NOAA polar orbiters, ~1 km resolution.

Why does EVI need blue, C1, C2, and L?

maybe veg
  • Blue band via C₁, C₂ — corrects for atmospheric aerosol scattering.
  • L term — soil-adjustment factor; damps bare-soil brightness.
  • (1 + L) multiplier — rescales output after soil correction.

Result: EVI doesn’t saturate in high-biomass canopies the way NDVI does.

Spectral signature of healthy vegetation?

essential veg
  • Low red reflectance — chlorophyll absorbs red for photosynthesis.
  • High NIR reflectance — scattered by spongy mesophyll leaf structure.

That contrast is why NDVI, SR, and EVI all work.

💡

Leaves DRINK red (chlorophyll eats it), BOUNCE NIR. That 'red dip, NIR jump' is THE vegetation fingerprint.

Simple Ratio (SR) — formula and who’s credited?

essential veg

The first vegetation index. Divide NIR by Red — see how much more NIR came back. A jungle gives you 30+, a parking lot gives you 1. Simple but the number has no upper limit, so you can’t easily compare scenes against each other.

That’s why NDVI replaced it for most modern work — same idea, but locked between −1 and +1.

🔬 Science / formula

SR = NIR / Red. Cohen (1991) identified it as the first true vegetation index. On Landsat TM: Band 4 / Band 3.

💡

Simple Ratio = Simple division. No subtraction, no normalization — just NIR/Red. Unbounded. Cohen 1991 (not Rouse, that's NDVI).

Phenology — definition and why it matters for RS?

likely veg

Phenology — periodic biological phenomena tied to annual climate (🌱 planting → 🌿 greening → 🌾 senescence → 🚜 harvest).

Why it matters for remote sensing: - 📅 Imaging date changes what you see - 🌾 Peak biomass maximizes vegetation / soil contrast - 📊 Multi-date NDVI series separates crops that overlap when green

NDVI — formula and range?

essential veg

Plants pull a sneaky trick with light: chlorophyll drinks red light for photosynthesis but bounces back invisible near-infrared. NDVI just compares the two bands — the bigger the gap, the healthier the vegetation. Numbers land between −1 (water / shadow) and +1 (lush rainforest). The middle is bare ground.

It’s basically a ‘how green is this place’ score that NASA, USDA, and every satellite ag company uses every day.

🔬 Science / formula

NDVI = (NIR − Red) / (NIR + Red). Range −1 to +1. Rouse et al. (1974).

  • Well-vegetated: high (0.6–0.8)
  • Bare rock/sand/snow: ≤ 0.1
  • Water: negative
💡

NDVI = Normalized to −1..+1. Unlike SR which has no upper bound, and unlike EVI which adds the Blue band.