Remote Sensing Archives - Page 2 of 4

SRTM Shuttle Radar Topography Mission

During an 11-day mission, Space Shuttle Radar Topography (SRTM) mission captured Earth’s elevation at 1 arc-second (30 meters) for over 80% of the Earth.

Learn Synthetic Aperture Radar (SAR) by Example

Synthetic Aperture Radar (SAR) is an emerging technology in remote sensing with the advantage to see in any weather condition and even at night.

Polar Orbit vs Sun Synchronous Orbit

A polar orbit satellite travels pole-to-pole. For a sun-synchronous orbit, it passes over any given point on Earth’s surface at the same local solar time.

OBIA – Object-Based Image Analysis (GEOBIA) – Think Objects, Not Pixels

Object-based Image Analysis (OBIA) segments an image by grouping pixels together into vector objects. Using these objects, you classify as land cover types.

ndvi united states - normalized difference vegetation index

What is NDVI (Normalized Difference Vegetation Index)?

NDVI quantifies vegetation with the difference between near-infrared (which is reflected by vegetation) and red light (which is absorbed by vegetation).

Why the Atmospheric Window Matters in Earth Science

The atmospheric window allows specific bands of electromagnetic (EM) radiation to reach the Earth. On the other hand, absorption bands prevent EM radiation.

GPS Accuracy: HDOP, PDOP, GDOP, Multipath & the Atmosphere

Have you ever wondered about your GPS accuracy? A well-designed GPS receiver can achieve a horizontal accuracy of 3 meters or better. But factors affect it.

Geosynchronous vs Geostationary Orbits

While geosynchronous satellites can have any inclination, the key difference is that satellites in geostationary orbit lie on the same plane as the equator.

Trilateration vs Triangulation – How GPS Receivers Work

Have you ever wondered how your GPS receiver works? They use a technique called trilateration, which measures distances, not angles as in triangulation.

Lossy Compression vs Lossless Compression

Lossless Compression vs Lossy Compression

Lossless compression (like JPEG) retains values and lowers file size. However, lossy compression (like LZ77) reduces file size by eliminating redundancy.