数字土壤制图研究综述与展望
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摘要
土壤的空间分布是土壤形成与发展过程的体现。数字土壤制图是一种新兴的、高效表达土壤空间分布的技术方法,在过去的30年取得了飞速发展。其理论基础为土壤成土因子学说和地理学第一定律。国内外学者在获取环境变量数据、采样方法、制图模型方法和土壤图产生及评价方面开展了大量的研究,应用案例也从小范围到大区域,甚至是全球尺度。未来数字土壤制图的发展方向包括:环境变量刻画的新技术,特别是体现人类活动方面的环境因子;新型数据和遗留数据的有效利用;土壤发生学知识与数学模型的紧密结合的新型推理方法;支持大数据多终端的计算模式。
The spatial distribution of soil reflects its formation and development.Digital soil mapping is a new and efficient technique to represent the spatial distribution of soil,which has experienced a rapid development over the last three decades.The theoretical bases are the soil forming factor theory and the first law of geography.Researchers have done significant work on the generation of environmental covariates,soil sampling methods,mapping methods,and production and evaluation of soil maps.The application cases are from small areas to big regions,even at the global scale.Future directions for digital soil mapping include: new techniques for depicting environmental covariates,especially for expressing human activities; efficient use of new data and legacy data; the reconciling of pedometric knowledge and mathematic models; and new computation ways supporting the use of big data.
The spatial distribution of soil reflects its formation and development.Digital soil mapping is a new and efficient technique to represent the spatial distribution of soil,which has experienced a rapid development over the last three decades.The theoretical bases are the soil forming factor theory and the first law of geography.Researchers have done significant work on the generation of environmental covariates,soil sampling methods,mapping methods,and production and evaluation of soil maps.The application cases are from small areas to big regions,even at the global scale.Future directions for digital soil mapping include: new techniques for depicting environmental covariates,especially for expressing human activities; efficient use of new data and legacy data; the reconciling of pedometric knowledge and mathematic models; and new computation ways supporting the use of big data.
引文
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