Shulou(Shulou.com)06/02 Report--

Although remote sensing monitoring provided a global solution to environmental protection and played an indispensable role in environmental protection, remote sensing also had problems: the time lag between problem detection and solution.

There is no doubt that shortening this time difference to the greatest extent is the inevitable way for remote sensing monitoring to cope with environmental protection. On this issue, AI's powerful computing power adds a pair of wings to environmental remote sensing monitoring.

China has a long history of environmental protection, which can be traced back to Yao and Shun periods. Yu, an organization specially set up to protect and manage mountains, forests and rivers, has a long history.

Since then, successive dynasties have set up special supervision organizations for environmental protection, such as Yu Hengsi in Tang, Song and Ming Dynasties; there are also wise men who have added strong environmental protection ideas to their political opinions, such as Mencius 'saying that "axes enter mountains and forests at the right time" and "several nets do not enter pools."

Under the basic environmental protection program, what brings is the supervision and implementation of environmental protection. In ancient times, environmental protection monitoring was mainly based on manpower, such as patrol and inspection.

With the change of dynasties and the perfection of the system, the work undertaken by the environmental protection department is getting heavier and heavier. It not only has to manage the mountains, forests and rivers in an all-round way, but also has no rest all year round. The people who do things are simply tired to vomit blood.

It can be said that the history of environmental protection in ancient China for more than 4,000 years is a history of artificial labor.

In the second half of the 20th century, with the rise of the information revolution and the worldwide attention to environmental protection, a series of technical and environmental monitoring means began to go into battle, such as fixed-point automatic monitoring, sampling detection, biological monitoring, etc., which greatly liberated manpower and directly brought environmental protection into the information age.

However, in comparison, the limitations of the above monitoring methods are also obvious, that is, they can only analyze local environmental data. To realize data monitoring in large areas, repeated monitoring must be carried out, which obviously still calls for a lot of manpower.

It seems out of place in an age of intelligence that emphasizes hands-free thinking.

From this point of view, the times call for a monitoring means that can provide comprehensive and high-precision monitoring means as a whole to add new impetus to the accelerated car of environmental protection.

Remote sensing, however, seems to be the best candidate for the task.

Wide coverage, multi-type, global: what is the value of remote sensing monitoring to environmental protection?

Remote sensing technology emerged in the 1970s, and has been widely used in many fields such as geographic data acquisition, emergency disaster monitoring, agricultural remote sensing monitoring, water quality monitoring, and air pollution monitoring.

From an environmental point of view, it has the following significant characteristics:

The coverage is extensive. Combined with the application of satellites, aircraft and other aircraft, it can achieve coverage of large areas and vast environments, not limited to a certain river or a certain vegetation area, which is unmatched by other environmental monitoring means; monitoring integrity. The direct advantage of large-scale monitoring is that staff can observe the environment as a whole, start from the overall situation, and then control the environmental problems more scientifically and reasonably; the coverage types are diverse. One of the characteristics of traditional environmental monitoring methods is that they are divided into scenes and categories. Water, vegetation and atmosphere have different monitoring equipment respectively. Remote sensing is different. It can be widely used in many scenarios such as water pollution, air pollution, vegetation coverage, greenhouse effect, etc. The change to be made mainly lies in the terminal algorithm. Therefore, it can be said that remote sensing can achieve coverage of most environmental protection types; long-term, continuous and dynamic monitoring. Taking satellite remote sensing monitoring as an example, it can realize 24-hour all-weather monitoring without data interruption; at the same time, it can quantitatively analyze the change process of monitoring objects from data of different periods, thus providing decision-making guidance for operators.

Overall, remote sensing monitoring environmental protection provides a global solution. In fact, remote sensing technology has played an important role in environmental monitoring and has become an indispensable force.

However, the force of this force seemed to be a little heavy.

Processing dilemma under huge data volume

The immediate problem with the extremely wide coverage area is the huge amount of data. With the development of remote sensing observation technology, the data of different imaging modes, bands and resolutions are put together to constitute the diversification of remote sensing data; especially in the aspect of remote sensing images, the increase of frequency and remote sensing accuracy shows an exponential increase.

In sharp contrast to the explosion of data, it is the lag of data information processing. Taking remote sensing image comparison as an example, there are still many units that use more manpower when performing detection dynamic analysis, which directly consumes a lot of time.

This is like the police in the movie who rely on the human eye to screen thousands of camera images one by one. Whether they can accurately find them depends on whether this person has the aura of the protagonist.

Secondly, in addition to large-scale deserts, soil erosion and other environmental problems requiring long-term treatment, daily environmental pollution events are often dynamic, such as long-distance discharge of sewage, illegal mining and sand excavation, industrial waste gas discharge, etc. These pollution behaviors are not continuous, but occur within a certain period of time.

The best state of environmental protection is to cut off the source of pollution completely and to stop pollution as early as possible when it appears.

Prevention is better than cure, which is a basic principle.

For example, sewage discharge, exhaust gas discharge, mining and sand excavation mentioned above may end the "battle" within one or two hours.

It wasn't a problem for the remote sensing to detect these behaviors, but they had to send the photos back to the data processing center for analysis and comparison, and finally make a decision to stop them…After a series of procedures, they had already finished work and gone home.

In other words, remote sensing has a time lag beyond data analysis: the time lag between problem detection and solution. There is no doubt that shortening this time difference to the greatest extent is the inevitable way for remote sensing monitoring to cope with environmental protection.

When it comes to data analysis and low latency in task processing, AI is naturally in charge.

AI, a pair of environmental remote sensing monitoring wings

AI+ remote sensing, in simple terms, can provide solutions to the following problems.

It solves the problems of real-time inspection and real-time reporting in a large range, and provides the possibility for environmental protection in the event of rapid stop loss. For example, as soon as the sluice is opened, the sewage is immediately monitored by remote sensing. AI quickly analyzes the time and then directly provides reference opinions to the processing center, greatly shortening the time difference between finding problems and solving problems; for the remote sensing data rising exponentially, relying on the remote sensing accuracy of high resolution, coupled with the super recognition ability of AI, it can quickly analyze and process them and improve the work efficiency at the same time. For example, a city's Bureau of Land and Resources identifies illegal buildings. After using AI to automatically analyze, identify and compare satellite remote sensing photos, it takes only one minute to complete the workload of professional monitoring experts for more than three months; through comparing data in different periods, AI can judge pollution trends, thus helping staff to propose solutions with advanced prediction. The value of this ability deserves special attention in the prevention and control of air pollution and water pollution.

No matter what advantages AI brings to remote sensing, in fact, we can see that the center revolves around the word "fast." It can be said,"AI remote sensing, fast word first."

As we all know, on the way of AI's light shining into reality, there is no shortage of data and algorithms. The only thing that limits its progress is computing power.

The same is true for remote sensing.

The computing power determines the absolute time within which AI performs data analysis processing and output. Then, abundant end-side AI computing power has become a necessity for aircraft such as drones.

At the same time, the realization of regional real-time remote sensing monitoring also puts forward requirements for the number of drones. However, the cost of drones loaded with AI technology is not low, which also hinders its large-scale promotion.

Then, the industrialization and low cost of UAV formation is one of the supplements to the construction of supporting facilities.

In addition, on the whole, just as autonomous driving is not just a matter of cars but involves the transformation of the entire road system, AI+ remote sensing does not mean only the supplement of equipment or the addition of AI capabilities of a certain module, but to build a remote sensing cloud platform mechanism including acquisition, processing, feedback, decision-making, etc., which requires high-speed network and stable cloud services as support.

The 5G network service close at hand may become an important link in the construction of remote sensing cloud platform mechanism.

From the near future, AI+ remote sensing in environmental protection is almost an inevitable thing. The clouds and dust that blocked its light on the earth would eventually dissipate, and a page would be filled with the names of AI in the book of credits for protecting a clear and clean earth.

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