Remote sensing data

Remote Sensing (RS) is a type of geospatial technology that collects samples of emitted and reflected electromagnetic (EM) radiation from terrestrial, atmospheric, and aquatic ecosystems to detect and monitor the physical characteristics of the terrain without physical contact. This method of data collection typically involves aerial (currently exclusively UAVs) and satellite sensors, which are classified as passive or active sensors. Ground sensors (instruments) are used at the local level and to enhance the quality of satellite and aerial data.

In recent years, ground RS sensors have been included in the field of remote sensing, which, in combination with space and aviation as carriers of sensors, allows for a new level of detail in the studied area or object.

Passive sensors respond to external stimuli by collecting radiation that is reflected or emitted by an object or the surrounding space. The most common source of radiation measured by passive remote sensing is reflected sunlight. Popular examples of passive remote sensors include charge-coupled devices, digital photography and video recording, radiometers, hyperspectral, and infrared sensors.

Satellite imagery. Satellite data

SAR imagery (Radar satellite data)

Remote sensing of the earth (RS)

Aerial & UAV imagery

LIDAR Aerial Survey

Types of Remote Sensing

Types of remote sensing can be classified according to various criteria reflecting the peculiarities of their application and technologies. One of the main methods of classification is based on the division by ranges of electromagnetic radiation, such as visible light, infrared and ultraviolet radiation, microwaves, and radio waves. Additionally, remote sensing types can be divided into active and passive, depending on whether the system uses its own source of radiation or detects reflected radiation. There is also a classification based on the type of platform on which sensing sensors are installed, such as satellites, UAVs, or aerostats. Each of these types has its own characteristics and provides valuable information for a wide range of applications, from monitoring climate change and the environment to urban development planning and agriculture.

Electromagnetic Spectrum

1. Optical Sensing:

Features: Uses visible and infrared spectrum to obtain images of the Earth.
Advantages: Provides high spatial resolution, allows for detailed surface imaging.

2. Thermal Sensing:

Features: Measures thermal radiation from the surface to analyze temperature characteristics.
Advantages: Allows for the detection of temperature changes, identification of hot spots (including oil leaks), useful for monitoring the thermal state of objects.

3. Radar Sensing:

Features: Uses the radio frequency range of electromagnetic waves to image the surface, penetrates through clouds, and operates in various weather conditions.
Advantages: Provides the ability to work in low-light conditions or adverse weather, detects changes in terrain and surface structure.

4. Hyperspectral Sensing:

Features: Measures reflected or emitted electromagnetic radiation at discrete wavelengths across a wide spectrum with narrow bands.
Advantages: Allows for obtaining spectral characteristics of objects across a broad spectrum, provides high ability to distinguish surface types and substances.

Classification by Spatial Resolution of Aerospace Imagery:

Very Low (worse than 100 m).
Low (15–100 m).
Medium (5–15 m).
High (1–2.5 m).
Very High (0.3–0.5 m).
Ultra High (0.02–0.5 m).

Example of Different Spatial Resolutions over One Territory

Satellite Image from "Meteor-M" Satellite, Spatial Resolution 50 m

Average spatial resolution satellite imagery (10 m) is the most popular due to the availability of public portals and catalogs of images, such as US Geological Survey (USGS) and Sentinel Hub. Scientists and students from around the world use data from these portals for scientific research and practice in remote sensing.
However, engineering works require data with higher resolution (from 0.15 m to 1 m).

There are also other categories of remote sensing.

Passive Method

In passive sensing, measurements are made using radiation emitted from objects on the Earth's surface, thus not requiring the use of a radiation source in the required spectrum range.

Active Method

In active sensing, its own radiation source is used, which illuminates the Earth's surface, and then the signal returned from the objects is detected and analyzed.

For example, RADAR and LiDAR sensors are typical active remote sensing instruments that measure the time delay between emission and return to establish the location, direction, and speed of an object. The collected remote sensing data is then processed and analyzed using remote sensing equipment and computer software (the most complex solution being analytical products presented in near real-time), which are available in various applications, primarily in geographic information systems (GIS).

Types of Sensing:

1. Satellite Sensing:

Includes the use of spacecraft to recognize Earth's surface features, weather conditions, and other parameters.
Applications: used for a wide range of research, monitoring, mapping, and other applications.

2. Aerial Photography:

Based on the use of a camera mounted on an aircraft, helicopter, or other manned vehicle to capture images of the Earth's surface from flight altitude.
Application: used in geography, cartography, scientific conditions, and in searching for the human factor in wilderness areas.

3. UAV Imaging (Unmanned Aerial Vehicles):

Specialized devices that allow for aerial photography without a person on board.
Application: used in monitoring fields, forests, and industrial forest areas for safe and efficient problem recognition. It has the highest spatial resolution.

For example, generalized characteristics of the most demanded remote sensing data sources on the market today are shown in table below.

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