Active Remote Sensing
The use of sensors that emit energy and measure its reflection from the earth’s surface, important for spatial data collection.
How do you define Active Remote Sensing?
Active remote sensing is a technique in which a sensor emits its energy—usually in the form of radio waves, microwaves, or lasers—toward the Earth's surface and then measures the energy that is reflected or backscattered from objects or features on the ground. Unlike passive remote sensing, which relies on natural energy sources like sunlight, active systems can operate day or night and in various weather conditions.
Examples of active remote sensing technologies include RADAR (Radio Detection and Ranging) and LiDAR (Light Detection and Ranging). These systems are commonly used for applications such as terrain mapping, vegetation analysis, flood monitoring, and infrastructure assessment. Because they generate their signals, active remote sensing systems offer greater control and consistency in data collection.
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In order to collect data, active remote sensing devices direct their own energy—typically in the form of radio waves, microwaves, or lasers—into a target and measure the signal that is reflected or backscattered. Since they are not dependent on sunlight like passive systems are, data can be collected day or night and in a variety of weather conditions. LiDAR, SAR, and RADAR are a few examples
Radar (such as Synthetic Aperture Radar, or SAR), LiDAR (Light Detection and Ranging), and altimeters are examples of active remote sensing. These devices send out their own energy signals, such as microwaves or laser pulses, and measure the reflected response from the Earth's surface to collect data, independent of the weather or the time of day.
Active remote sensing collects data regardless of sunlight and occasionally even through clouds by directing its own signal—such as radar or LiDAR—at a target and measuring the reflected energy. Similar to optical or thermal imaging, passive remote sensing depends on natural energy sources like sunlight or heat emissions, therefore weather and lighting can have an impact.
Active remote sensing is suitable even at night or in hazy conditions because it directs its own signal—such as a laser beam or radar pulse—to a target and detects the reflected energy. In contrast, passive remote sensing relies on external light sources and is more influenced by the weather and time of day because it detects natural energy, typically sunlight, that is reflected or emitted by objects.