What are the best sensors for drone remote sensing in urban areas?

1 Sensor types

There are many types of sensors that can be mounted on drones, but they can be broadly classified into two categories: passive and active. Passive sensors rely on natural or artificial sources of light or radiation, such as the sun, the sky, or street lamps. Active sensors emit their own signals, such as laser pulses, radar waves, or sound waves, and measure the reflection or echo from the target. Passive sensors are usually cheaper, lighter, and simpler to operate, but they are affected by weather, illumination, and atmospheric conditions. Active sensors are more expensive, heavier, and complex to operate, but they can penetrate clouds, fog, smoke, and vegetation, and provide more accurate and detailed information.

2 Resolution and coverage

One of the main factors that determine the quality and usefulness of the data collected by sensors is the resolution and coverage. Resolution refers to the smallest detail that can be distinguished by the sensor, while coverage refers to the area that can be scanned by the sensor in a single flight. Resolution and coverage are inversely related, meaning that higher resolution means lower coverage, and vice versa. For example, a camera with a high-resolution lens can capture sharp images of small objects, but it can only cover a small area. A camera with a low-resolution lens can cover a large area, but it will produce blurry images of large objects. Depending on the purpose and scale of the remote sensing project, you need to balance the resolution and coverage of the sensor.

3 Spectral range

Another factor that affects the performance and suitability of the sensors is the spectral range. Spectral range refers to the range of wavelengths of the electromagnetic spectrum that the sensor can detect and record. Different types of sensors have different spectral ranges, such as visible, infrared, thermal, ultraviolet, or microwave. Different spectral ranges have different advantages and disadvantages for remote sensing in urban areas. For example, visible sensors can capture colors and textures of the urban landscape, but they are limited by daylight and shadows. Infrared sensors can detect heat and vegetation health, but they are sensitive to temperature and moisture. Thermal sensors can measure surface temperature and identify hotspots, but they are affected by emissivity and reflectivity. Ultraviolet sensors can detect air pollution and surface damage, but they are blocked by clouds and smog. Microwave sensors can penetrate buildings and vegetation and provide elevation data, but they are noisy and expensive.

4 Sensor integration

The final factor that you need to consider when choosing sensors for drone remote sensing in urban areas is the sensor integration. Sensor integration refers to the ability of the sensors to work together and complement each other. By integrating multiple sensors on a single drone, you can collect more diverse and comprehensive data, and overcome the limitations and challenges of each sensor. For example, you can combine a camera with a lidar (light detection and ranging) to capture both the visual and the geometric features of the urban environment. You can also combine a multispectral sensor with a hyperspectral sensor to capture both the broad and the narrow bands of the electromagnetic spectrum. However, sensor integration also requires more power, weight, and complexity, and may pose legal and ethical issues.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?