农业展望2023，Vol.19Issue(12)：81-86,6.
深度学习在土壤监测中的应用及展望
Application and Prospect of Deep Learning in Soil Monitoring
摘要
Abstract
In recent years,with the increase in image processing power and the development of image acquisition systems,computer vision-based image analysis methods have attracted significant attention and spread in many fields,including soil science.The acquisition of dynamic or static soil images by cameras in the form of multiple spectral combinations,which are then classified by appropriate computer programs,allows further assessment of soil properties,including moisture,temperature and organic carbon.In order to further enhance agricultural farming capabilities,further predictions of future parameters of soils in agricultural production are required,and high-quality soil time series predictions are important for both relevant research and agricultural production.This paper reviewed the application of deep learning in soil monitoring,pointed out that deep learning is an artificial neural network-based representation learning algorithm that can extract meaningful information from various types of geospatial imagery and data.This review therefore collated and summarized the application and research status of deep learning in soil monitoring on the basis of summarizing the concepts and features of deep learning,and proposed that based on this prediction method it can give relevant researchers and agricultural and management personnel to achieve dynamic monitoring and prediction of soil properties in agricultural production with lower cost data,so as to better guide agricultural production.Finally,the outlook was presented in terms of data acquisition and quality,computer vision,etc.,which is expected to provide a reference for the application of deep learning in soil monitoring and to support the development of refined agricultural planting management,modern industrial planting and the Internet of Things in agriculture.关键词
深度学习/土壤监测/人工智能/数据获取/数据处理Key words
deep learning/soil monitoring/artificial intelligence/data acquisition/data processing引用本文复制引用
张超,张海峰,张宇,张效霏,来永才,毕洪文,郑妍妍..深度学习在土壤监测中的应用及展望[J].农业展望,2023,19(12):81-86,6.基金项目
黑龙江省省属科研院所科研业务费项目(CZKYF2021-2-A002) （CZKYF2021-2-A002）
