Remote sensing is a comprehensive earth observation technology developed in the 1960s. It generally refers to all non-contact long-distance detection, including detection of electromagnetic fields, force fields and mechanical waves (sound waves and seismic waves).
The remote sensing system mainly includes remote sensing information source, remote sensing information acquisition, remote sensing information processing and remote sensing information application.
With the development of the past few decades, remote sensing technology has the characteristics of wide range of data acquisition, fast information acquisition speed, short information acquisition cycle, few information acquisition conditions, many means of information acquisition, and large amount of information. Remote sensing technology has been widely used in national defense, military, agriculture, forestry, land, ocean, surveying and mapping, meteorology, ecological environment, water conservancy, aerospace, geology, mining, archaeology and other fields.
Remote sensing data is the starting point for remote sensing information services. Without timely, comprehensive and high-quality data supply, remote sensing applications cannot be operationalized. With the continuous development of the remote sensing application market and the continuous expansion of user groups, different users have their own needs for remote sensing information services, higher requirements.
With the development of artificial intelligence technology, the processing of remote sensing big data has gradually become intelligent. Intelligent algorithms represented by deep learning have made breakthroughs in the field of computer vision. The thinking of "artificial intelligence" is subtly affecting the practice of remote sensing. There have been many applications in remote sensing image target detection and remote sensing coverage classification.
As an important means of information acquisition, satellite remote sensing has great potential to provide social services for many industries. It is an indisputable fact that artificial intelligence replaces some human work. "Artificial intelligence + remote sensing" has done a lot of excellent work in refined agricultural services, typical target recognition, and urban structure extraction.
The application of high-resolution remote sensing data to urban planning analysis is one of the main aspects of remote sensing applications, such as:
Dynamic monitoring of urban construction
Extraction of urban road network
Urban expansion monitoring
Urban environmental monitoring and assessment
Remote sensing image has always been a powerful tool for environmental monitoring. Some of the feasible applications are:
Environmental impact assessment for a wide range of projects (natural resources exploitation, infrastructure development, etc)
River/Lake water bodies monitoring
Desertification processes monitoring and mitigation activities
Erosive processes analysis, restoration techniques planning and implementation
There is able to provide data for monitoring, mapping and deriving biophysical parameters and state of agricultural lands. Some of the possible applications are:
Crop spatial distribution
Crop condition monitoring
Agricultural reservation supervision
Agricultural disaster monitoring
The remote sensing information products based on high spatial resolution images can be fully applied to the field of forestry resource management. Some feasible examples are as follows:
Forest resources investigation
Wetland resources monitoring
Desertification monitoring and evaluation
Forestry ecological engineering monitoring
Forest disaster monitoring
High resolution satellite remote sensing technology has developed rapidly in recent years, which plays an important role in mining production and management, such as:
Illegal mining monitoring
Investigation on the development of mineral resources
Environmental monitoring and assessment of mining area
Massive imagery data in both daily archived or task programming is changing the way you see the world.