Artificial intelligence has penetrated into various industries. The forestry and grassland industry actively embraces artificial intelligence and deepens its intelligent leadership. This is not only an important measure to comprehensively build a smart forestry and grassland industry, but also a good opportunity for the forestry and grassland industry to adapt to the trend of the times and achieve innovative development

Zhu Jiaojun, an academician of the CAE Member and director of the Shenyang Institute of Applied Ecology of the Chinese Academy of Sciences, stressed the strategic significance of high and new technologies such as artificial intelligence for the high-quality development of forestry and grass cause at the second China Forestry and Grass High tech Application Conference held in Shenzhen.

Ecological monitoring urgently needs artificial intelligence and is difficult to crack

Faced with the global challenge of comprehensive monitoring and precise management of forest, grassland, wetland, and desert ecosystems, Academician Zhu Jiaojun pointed out that traditional research and management methods have many limitations. For example, the growth cycle of forests can range from decades to hundreds of years, with a wide spatial distribution and complex composition structure. The structural parameters that determine forest function are diverse, making monitoring work time-consuming, laborious, and difficult to quantify. In addition, forests have dynamic and global characteristics, coupled with multiple processes and high trial and error costs. Traditional manual monitoring and management are inefficient, like "blind men feeling an elephant".

At present, China is promoting the high-quality construction of forest "four reservoirs", and the primary task is to deeply understand the formation mechanism, change laws, and total inventory of forest "four reservoirs". The achievement of this goal cannot be separated from the assistance of high-tech such as artificial intelligence. Otherwise, it will be difficult to accurately understand the "four reserves" of the forest, let alone high-quality construction.

Academician Zhu Jiaojun introduced that in 2018, under the commission of the National Forestry and Grassland Administration, he led a comprehensive evaluation of the 40 year construction effectiveness of the "Three North" project. He used laser radar unmanned aerial vehicle remote sensing technology, combined with satellite remote sensing for scale conversion, and integrated ground monitoring and remote sensing monitoring data using big data models to ensure the accuracy and reliability of the evaluation results.

In 2021, the Chinese Academy of Sciences launched the "Big Data+Artificial Intelligence (AI)" scientific research paradigm change application demonstration project. Among them, Liaoning Qingyuan Forest Ecosystem National Field Scientific Observation and Research Station (Chinese Academy of Sciences Qingyuan Forest Ecosystem Observation and Research Station), as the only representative of the field ecological positioning station, carried out a demonstration study on artificial intelligence to change the scientific research and management paradigm of forestry and forest ecology. The research results indicate that information technology and AI technology have revolutionized the basic data acquisition methods for stereoscopic perception and efficient transmission. The use of remote sensing and deep learning technology enables real-time monitoring of forest ecosystems, timely detection of forest growth and decline changes, and dynamic assessment of forest health status; By combining forestry models and artificial intelligence methods, a forest growth and harvest estimation model system has been established for major forest types, distinguishing between natural and management conditions, promoting sustainable management of forest resources; We have developed a new generation of aviation data tables using advanced technologies such as remote sensing satellites, drones, and big data to support precise monitoring and quality improvement of forest resources, and optimize forest management decision-making models; By utilizing technologies such as satellite monitoring, drone patrol, and intelligent thermal imaging recognition, an integrated forest and grassland fire monitoring and early warning system has been constructed, which enhances the ability to predict fire hazards, monitor fire situations, and respond to emergencies, and promotes intelligent and refined management of forest and grassland fire prevention.

Taking the investigation of 330000 individual trees in a demonstration study forest watershed as an example, compared with traditional methods, the use of information technology+AI technology has increased data acquisition efficiency by 500 times and significantly improved accuracy. In addition, the three-dimensional monitoring network of AI remote sensing and the Internet of Things has increased the efficiency of disease and pest identification by 85%, and shortened the fire response time to less than 10 minutes... Behind this series of technological applications is the substantial reinforcement of ecological security barriers. However, information technology and AI technology have not yet been fully applied in the high-quality development of forestry and grassland industry. It is urgent to integrate mature information technology and AI technology to empower the modernization of forestry and grassland industry.

Integration of "Three Modernizations" and Reconstruction of New Quality Productivity of Forests and Grasslands

At the conference, Academician Zhu Jiaojun gave a keynote speech on "Transformation of Forest Ecological Research Paradigm: Digitization, Networking, and Intelligence", and proposed a progressive development path for the "three modernizations" of forest and grassland systems: building a foundation with digitization and achieving full element collection of data on mountains, waters, forests, fields, lakes, grasses, and sands; Establish an integrated monitoring system for air, space, and earth through networked connectivity; Ultimately, through intelligent advancement, we aim to create an ecological decision-making brain with self-learning capabilities.

He believes that from the AI biodiversity monitoring platform in Northeast Tiger and Leopard National Park, to the intelligent afforestation robot experiment in the "Three North" project area, and to the new generation of aviation data tables based on remote sensing satellites, drones, big data and other technologies, these practices have confirmed that artificial intelligence is not only a tool innovation, but also a thinking revolution.

Academician Zhu Jiaojun emphasized that relying on the new generation of information and artificial intelligence (AI) technology driven by digitization, networking, and intelligence can not only change the traditional scientific research and management mode of forest ecology, but also promote a deeper understanding of the interaction mechanism between forest ecosystems and climate change, providing support for sustainable management solutions of forest ecosystems based on natural climate. Ultimately, artificial intelligence will promote the efficient, stable, and sustainable development of forest ecosystem functions, achieving harmonious coexistence between humans and nature. The forestry and grassland system should fully utilize the "three modernizations" technologies of digitization, networking, and intelligence, and deeply integrate them in research, management, decision-making, evaluation, and other aspects to reconstruct the new quality productivity of forestry and grassland.

We must adhere to the bottom line thinking of "human-machine collaboration"

Artificial intelligence can break through the limitations of time and space in our cognition, but it can never replace ecologists' profound understanding of natural laws. "Academician Zhu Jiaojun emphasized that no matter how widely artificial intelligence is applied, we must adhere to the bottom line thinking of" human-machine collaboration "and" respecting nature ".

Due to the fact that the monitoring results of artificial intelligence are generated by machines, it still requires the cooperation of top experts and artificial intelligence for real-time evaluation. For example, artificial research on a forest ecosystem may take 50-60 years to produce results, while artificial intelligence may take two years to complete. However, the accuracy of the results requires real-time monitoring, evaluation, and timely improvement and optimization of identified problems. To ensure the efficient operation of artificial intelligence, experienced top experts and real-time monitoring and evaluation systems are indispensable.

Looking ahead to the future, Academician Zhu Jiaojun pointed out that with the continuous development of climate smart forestry, it is necessary to create a new paradigm centered on "data acquisition analysis management" as soon as possible, promote the establishment of industry models, promote the implementation of forest "four reservoirs" linkage and collaborative efficiency technology, and help the green industry flourish. At the same time, the development of new intelligent equipment, the construction of a smart forest and grass new system combining three-dimensional perception, forestry big models, and AI analysis, and the development of a new forest and grass management model based on the harmonious coexistence between humans and nature have become the trend. Especially the combination of the new generation of aviation data tables and artificial intelligence algorithms can achieve more accurate real-time monitoring and quality assessment of forest resources. The data support provided by it is the key foundation for efficient and accurate monitoring of forest resources. The breakthrough and promotion of this technology are directly related to the future of sustainable management of forest resources, and must attract high attention from the whole society, especially forestry management departments, and be quickly put into practice to ensure the long-term protection and sustainable utilization of forest resources.

This scientist who has been deeply involved in forest ecology for 40 years is looking forward to an "ecological intelligence revolution" driven by artificial intelligence, which is moving from the laboratory to green mountains and rivers, driving the modernization of forestry and grassland industry. (Liu Shenyuan)