Whether you're a student encountering land-cover classification for the first time, or a researcher who needs a quick refresher on the Mann-Kendall test — this is meant to be useful either way.
Quick, plain-language definitions for the terms you'll run into across GIS and remote sensing — NDVI, Kappa coefficient, zonal statistics, and more.
A technical reference table for the satellite and gridded data sources used across the platform — resolution, revisit time, coverage period, and citations for each.
A searchable library of 38 remote-sensing indices and analyses — NDVI, NBR, NDWI, NDBI, terrain and spatial stats — each with its formula, Sentinel-2 / Landsat band configuration, value interpretation, limitations, and primary citation.
A dashboard of 13 practical utilities — unit conversion, band combinations, a spectral index calculator, UTM zones, map scale, classification accuracy, a bounding-box / GeoJSON extractor and more — all running entirely in your browser.
Deeper explanations of the methods behind the numbers — how NDVI is calculated, why a trend needs a significance test, what separates a good classifier from an overfit one.
How these methods get used in practice — urban heat islands, coastal tourism sustainability, agricultural monitoring, and other applied research questions.
Notable new datasets, techniques, and research in remote sensing and spatial analysis — for staying current beyond your own subfield.