Blog

Notes on remote sensing.

Practical explanations of the methods behind land cover classification, trend detection, and spectral indices — written for people who'll actually use the numbers.

NDVI Explained: How Satellites Measure Vegetation Health

How NDVI is calculated from red and near-infrared reflectance, what the values actually mean, and the three places it commonly breaks down.

The Mann-Kendall Trend Test, Explained for Remote Sensing

Why a slope alone can't tell you if a trend is real, and how a non-parametric significance test separates genuine change from year-to-year noise.

Random Forest vs CART vs SVM for Land Cover Classification

A practical comparison of the three most common classifiers, and why your validation method matters more than which one you pick.