Comprehensive Analysis of Smart Agriculture on Ecosystem Service and Sustainable Development

Dear Colleagues,

With the development of smart/intelligent agriculture (S/IA), the world, especially developing countries represented by China, is undergoing a "new agricultural technology revolution" - a "digital revolution in agriculture". S/IA rapidly promotes a transformation from traditional agriculture to modern agriculture, enabling smart or intelligent operation of agricultural planting, growth monitoring, and management.

Therefore, we need to attach great importance to the research of technologies and methods such as extraction of spatiotemporal distribution information of crops and monitoring of growth process; integrate new technologies such as remote sensing, GIS, GPS, Internet of Things, and multidisciplinary knowledge such as agronomy, ecology, plant physiology, and pedology in S/IA; develop innovative methods for accurate acquisition and identification of crop planting structures under different terrain conditions; and scientifically and accurately identify the best use of cultivated land and estimation of grain yield. In addition, S/IA studies automatic and accurate acquisition of irrigation information and intelligent irrigation monitoring technology to achieve scientific scheduling of farm watering and crop scientific irrigation, practices real-time dynamic monitoring of crop growth processes, examines the lagging effects of external factors such as meteorology on crops, constructs scientific crop drought monitoring and evaluation models, and advocates intelligent crops management.

This special issue focuses on research about the construction of smart/intelligent agricultural scenarios from a wide range of perspectives (i.e., precise crop classification, integrated 3D monitoring technologies of air-space-land, accurate acquisition of agricultural irrigation information, agrarian drought, disease and pest monitoring, etc.). Specifically, it includes the impact of crop planting structure fragmentation on the accuracy of information extraction, classification model, agricultural drought model, multi-source monitoring technological convergence, and scenario-building technologies.

We invite papers including, but not limited to, precise crop classification models, crop monitoring techniques, multi-source data fusion, the impact of meteorological factors on crop growth, drought monitoring, pest and disease monitoring, irrigation monitoring, and growth process simulation-related topics.

We look forward to receiving your original research articles and reviews.

Prof. Dr. Yichun Xie
Prof. Dr. Anbing Zhang
Guest Editors

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• multi source remote sensing data fusion
• integrated monitoring technology
• classification model
• accurate acquisition and monitoring technology for agricultural irrigation
• agricultural drought monitoring
• disease and pest monitoring
• estimation of crop yield