A natural terroir unit is a tract of land whose natural characteristics form a unique assemblage of factors (soil, terrain and climate) which together impart specific high-quality characteristics to an agricultural product. In order to map and describe Danish natural terroir units, we built on previous efforts to quantitatively map and describe Danish natural terroir units based on soil, terrain, climatic and historical crop yield data. Our work consists of four stages: (1) The OSACA algorithm was applied to define soil centroids and measure taxonomic distance between soil profiles and soil centroids based on a Danish soil spectral library; (2) nine Danish terron classes were established by fuzzy c-means clustering based on soil, terrain and climate information; (3) a Danish terron map was generated by Cubist regression tree models and the uncertainty of this map was assessed by a terron membership map; (4) Danish natural terroir units were described by linking historical crop yield data to the terron map. The results suggested that the OSACA algorithm and Vis-NIR spectral data could be used as an efficient tool to facilitate terron identification. The terron predictions also showed that the addition of terrain and climatic predictors improved the previously created Danish terron map. The description of Danish natural terroir units showed that seven natural terroir units could be an optimal number for Denmark for specific crop types. Further investigations are needed that link more agricultural yield data to this terron map in order to describe natural terroir units for different agricultural products. The methods developed in this study could be tested in other countries to facilitate sustainable soil management and minimize environmental risks.

天然风土单元是一块土地，其自然特征形成了独特的因素集合（土壤，地形和气候），这些因素共同为农产品赋予了特定的高质量特征。为了绘制和描述丹麦的自然风土单位，我们在先前的工作基础上，根据土壤，地形，气候和历史农作物产量数据定量绘制和描述了丹麦的自然风土单位。我们的工作包括四个阶段：（1）使用OSACA算法定义土壤质心，并基于丹麦土壤谱库测量土壤剖面与土壤质心之间的分类距离；（2）通过模糊C建立了9个丹麦Terron类-基于土壤，地形和气候信息的聚类；（3）通过立体主义回归树模型生成丹麦地形图，并通过地形成员图评估该图的不确定性；（4）通过将历史农作物产量数据与地形图联系起来，描述了丹麦的自然风土单位。结果表明，OSACA算法和Vis-NIR光谱数据可以用作促进Terron识别的有效工具。Terron预测还显示，添加地形和气候预测因子可以改善以前创建的丹麦Terron地图。丹麦自然风土单位的描述表明，对于特定农作物类型，七个自然风土单位可能是丹麦的最佳数量。为了描述不同农产品的自然风土单位，需要进一步的调查，将更多的农业产量数据与该地形图联系起来。这项研究中开发的方法可以在其他国家进行测试，以促进可持续的土壤管理并最大程度地减少环境风险。