On-the-Go Digital Soil Mapping for Precision Agriculture

The objectives of precision agriculture are to increase crop production profitability, improve product quality, and protect the environment. One of the first and most important areas in which precision agriculture has been applied is in managing the variability in soil properties, which is essential for the decision-making process. The success of precision agriculture depends strongly upon highly efficient and reliable methods for gathering and processing site-specific field information. The inability to obtain soil characteristics rapidly and inexpensively remains one of the biggest limitations of precision agriculture. ＂Predictive or digital＂ soil mapping is one of the hottest topics in soil science which demand of precision-agriculture for high-resolution spatial soil information. The objective of this article is to review current research into new mapping methodologies and assess whether they could be usefully applied with respect to precision agriculture. This paper determines the state of the art of predictive soil mapping, and discusses the potential of predictive soil mapping as part of an integrated management tool for precision agriculture. The various recent approaches and methods that have been, or could be, used for fitting quantitative relationships between soil properties or classes and their 'environment' are reviewed and discussed. To conclude the results, approaches to soil mapping can be divided into knowledge-based ones and data-driven ones. Conventional soil mapping has been criticized for being too qualitative. However, the pedometric methods have also been criticized for being too expensive as they require too many samples for them to be worthwhile. Of course the best features of these two may be combined into a mixed approach. Predictive soil mapping aims at spatial prediction of soil properties by combining soil observations at points with auxiliary information and remote sensing.

並列關鍵字

Precision Farming ； Geostatistics ； Pedometrics ； Remote Sensing ； Global Positioning System ； Soil Mapping ； Soil Properties

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