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Remote sensing is a non-contact, long-distance detection technology. Relying on the unique global data set of JL1, using our big data intelligence tool to understand the changes taking place in the areas you are most concerned about, and help you make decisions faster and better.

Types of Satellite Remote Sensing

Satellite Remote Sensing In Agriculture

Satellite Remote Sensing In Forestry

Satellite Remote Sensing In Environment

Satellite Remote Sensing In Change Monitoring

Satellite Remote Sensing In Greenbelt

Satellite Remote Sensing In Insurance

Multispectral Remote Sensing

Ocean Remote Sensing

Optical Remote Sensing

Photogrammetry Remote Sensing

Thermal Remote Sensing

Customized Satellite Remote Sensing

REMOTE SENSING SATELLITE SYSTEMS-DETECTING THE EARTH

What is Remote Sensing

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).

What is a Remote Sensing System

The remote sensing system mainly includes remote sensing information source, remote sensing information acquisition, remote sensing information processing and remote sensing information application.

Remote Sensing Information Application

With the development of the past few decades, satellite 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

Satellite 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.

Our Advantages

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.

Outlook

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.

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EXPLORE REMOTE SENSING SATELLITE MARKETS

high resolution hyperspectral remote sensing satellites list

Urban Planning

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

Environment

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

Agriculture

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

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