基于近红外光谱的喀斯特地区土壤适宜性数字评价体系研究

项目名称： 基于近红外光谱的喀斯特地区土壤适宜性数字评价体系研究

项目编号： No.41461076

项目类型： 地区科学基金项目

立项/批准年度： 2015

项目学科： 地质学

项目作者： 邓燔

作者单位： 黔南民族师范学院

项目金额： 51万元

中文摘要： 土壤信息用户经常需要复杂、难以测定的土壤功能评价、威胁分析、风险评估，例如土壤质量、土壤侵蚀、土壤污染等。以往的土壤质量评价研究忽视了信息所具有的误差，给土壤管理带来不准确性。新近提出的数字土壤评价以数字土壤制图为基础，通过模型分析，提供用户自己设定的、容易理解和使用的土壤信息，因此可以满足不同用户的土壤信息需求。本研究基于近端土壤检测中的近红外光谱技术和数字土壤评价理论，在贵州省黔南州范围内，以条件拉丁超立方取样法进行取样，应用近红外光谱仪Labspec 5100，获取土壤样品的容重、含水量，质地、pH、电导率、有机碳、氮、磷、钾、CEC以及DTPA提取的铜、铁、锰、锌和水提取的硼等指标，利用数字土壤制图方法，对这些影响土壤质量的指标制图，在GIS支持下建立土壤质量评价系统。目的在于建立一套可以评估喀斯特地区的土壤质量的方法体系。

中文关键词： 土壤生物指标；土壤环境质量；土壤质量图；地理信息系统；地统计学

英文摘要： Soil information users usually demand for information of soil functions, soil threats and soil risks,such as soil quality, soil erosion,soil pollution.In order to meet this demand,digital soil assessment was recently proposed based on digital soil mapping and modeling to generate information of soil attributes that are set by users and easy to understand and use,as well as associated errors.Hence,digital soil assessmentcan meet various kinds of soil informaiton demands.However,few studies on soil quality evaluation so far have accounted for associated errors.Based on the theory of digital soil assessment,this study would first use proximal soil sensing technology, including near infrared spectroscopy and digital soil mapping techinques to map soil quality indicators in a study area of Qiannan,Guizhou,where conditioned latin hypercube sampling method was adapted to choose the sampling point.. It will introduce near infrared spectroscopy machine Labspec 5100 for soil analysis, to get soil bulk density, moisture content, texture, pH, conductivity, organic carbon, nitrogen, phosphorus, potassium, CEC, boron and DTPA extraction of copper, iron, manganese, zinc..Afterwards,soil quality evaulation systems will be constructed to evaluate soil quality of the study area using the maps and simulations of soil quality indicators as inputsThe objective of this study is to develop a method of soil quality assessment system in the karst region.

英文关键词： Soil biologibal Index;soil quality assessment;soil quality map;GIS;Geostatitics