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Remote Sensing

Definition

Remote sensing acquires information about Earth’s surface without direct contact using sensors on satellites, aircraft, drones, or ground platforms. Sensors measure reflected or emitted energy across the electromagnetic spectrum (visible, NIR, SWIR, thermal, microwave). Multispectral and hyperspectral imagery reveal materials and vegetation; SAR provides all-weather day/night imaging and deformation via InSAR; LiDAR captures precise 3D structure. Data vary in spatial, spectral, temporal, and radiometric resolution. Processing includes radiometric and atmospheric correction, orthorectification, mosaicking, and classification. Remote sensing underpins mapping, monitoring, and change detection across scales, from fields to the globe.

Application

Agriculture tracks crop vigor; forestry monitors harvest and regrowth; urban planners map imperviousness; disaster response detects floods and fires; climate science quantifies ice and heat trends; mining monitors pits and tailings; oceanography tracks blooms and fronts.

FAQ

What’s the best sensor for clouds?

SAR penetrates clouds and works at night; optical needs cloud-free windows or compositing. Choose based on phenomenon and revisit needs.

How to ensure comparability over time?

Apply consistent corrections and use sensor harmonization; anchor analyses to stable targets and cross-calibration.

Can small drones replace satellites?

They complement: drones provide high resolution and flexibility locally; satellites provide broad coverage and long time series.

What about licensing?

Open data (e.g., Landsat, Sentinel) enables reproducible science; commercial data offer higher resolution but have usage limits—track licenses carefully.