Challenges, Development and Frontiers of Smart Agriculture and Forestry

Dear Colleagues,

With the development of agriculture and forestry stepping into the digital era, the digital technology of agricultural and forestry is becoming increasingly used. We call it smart agriculture and forestry, which is characterized by “information + knowledge + intelligent equipment”, realizing the deep cross-domain integration of modern information technology and agriculture and forestry. In the future, the development of smart agriculture and forestry will focus on information and intelligent technology in order to build an integrated platform for smart perception, wireless transmission, smart decision making and intelligent control so as to realize the intelligent supervision of the entire agricultural and forestry industry chain (production, processing, operation, management and service) and finally achieve the purpose of cost reduction, quality improvement and efficiency increase. The rapid development of artificial intelligence, UAV, remote sensing, Big Data analysis and other technologies provides substantial support for agriculture and forestry to move forward into the intelligent era. This topic aims to fully tap frontier technologies including Internet of Things, multi-modal and multi-angle stereo observation, cloud computing, Big Data, machine learning, intelligent decision-making, etc., thereby exploring its application potential in smart agriculture and forestry and accelerating the development of precision agriculture and forestry.

The topic “Challenges, Development and Frontiers of Smart Agriculture and Forestry” welcomes high-quality studies that focus on the innovation of five core technologies including remote sensing, advanced sensor, Big Data and cloud services, precision operation technology and equipment, Internet of Things and Robots and the solutions, strategies, pilot cases and examples of these frontier technologies applied in the fields of forest and farmland investigation and change monitoring; plant protection; disaster prevention; precision cultivation; visual management; ecological protection and reconstruction; and evaluation of ecological service value. Relevant themes include but are not limited to the following.

Intelligent sensing technology and equipment for agriculture and Forestry

• Advanced agroforestry sensors and data analysis
• Intelligent robot integrating cloud computing, Big Data and machine learning technology
• Intelligent agricultural and forestry machinery equipment and technology
• Development and test of agricultural and forestry intelligent equipment

New methods and technologies for precision forestry investigation, monitoring and evaluation

• New methods and technology of forest resources investigation based on multi-source remote sensing
• Forest change and disturbance detection using multi-modal remote sensing technology
• Forest degradation–restoration monitoring combining remote sensing and geographic Big Data
• Forest disaster monitoring and prediction integrating remote sensing and geographic Big Data
• Precision estimation and modelling of forest structure and function parameters
• Forest visualization and management

Technological innovation in agriculture 4.0 era

• Innovative sensors and technologies for smart agriculture
• Application of deep learning and geographic Big Data in smart breeding and germplasm resources
• Smart technologies and decision support for precision orchard production
• Multi-technology integration for high-throughput plant phenotyping
• Intelligent in situ monitoring and decision-making of crop typical stress

Sustainable development of agriculture and forestry ecology

• Assessment of ecosystem service function based on geographic Big Data analysis
• Precise estimation of agricultural and forestry carbon storage
• Vegetation species diversity evaluation based on remote sensing and machine learning
• Agriculture and forestry approaches and contributions to achieve carbon neutralization
• Challenges and opportunities to the construction of smart agriculture and forestry

Prof. Dr. Xiaoli Zhang
Prof. Dr. Dengsheng Lu
Prof. Dr. Xiujuan Chai
Prof. Dr. Guijun Yang
Dr. Langning Huo
Topic Editors