大比例尺土壤数据库的组织与设计研究——以安徽宣城样区为例

以安徽宣城样区为例,就大比例尺土壤数据库的组织与设计进行了系统地研究。分析了大比例尺土壤数据库的特点及组织原则,在此基础上,进一步就大比例尺土壤数据库空间制图单元构建及其属性数据的采集、组织、管理等问题作了详细地探讨,并在GIS软件支持下完成了样区土壤数据库设计。     

以土地利用现状信息为空间框架的大比例尺土壤图制作方法初探——以浙江富阳为例

以1∶10 000土地利用现状图的部分土地利用分类信息为空间框架基础,结合1∶10 000乡镇土壤详查图、1∶50 000土壤图,以及其他影响土壤特性的地形、地质等图件信息和野外剖面调查,探索1∶10 000大比例尺土壤图制作的可行性.结果表明,得到的土壤图不仅在分布上更贴近于实际、分类图斑更细腻、土壤分类的面积精度更高,而且制作方便,易于土壤信息数据库的建设和在实际应用中与土地利用等的无缝叠加.该方法适于县级大比例尺制图,可为更好地掌握区域土壤分布现状、精准农业和土地利用提供准确的土壤信息.     

南方1:100万土壤图的制图综合及编图资料的应用

1:100万土壤图是小比例尺土壤图,它要求能概括地反映土壤分布规律和区域分布特征,是编制全国或某一区域的农业区划,土地资源开发规划的重要资料。本文就编制上海幅1:100万土壤图有关制图综合及编图资料应用谈一点体会与浅见。     

基于归并“土体构型”图的省域耕地地力评价

小比例尺土壤图制图单元内土体构型往往不一致,以土壤图为评价单元,土体构型往往难以作为一个评价指标。本文以河南省为例,基于1∶5万比例尺土壤图,根据县域土种志记载的典型剖面信息,将全省428个土种按照质地构型和障碍土层归纳为32种土体构型,然后在GIS中概括生成1∶50万土体构型图,并分析了该图与1∶50万河南省土壤图在空间表达方面的差异以及土体构型指标对耕地地力评价结果的影响。结果表明:土体构型图图斑多样性低,面积变异系数大,但图斑平均密度大,图斑形状指数复杂,既实现对生产性能变异较低区域的图斑简化,又保持生产性能变异较大区域图斑表达的高精度;在统一的评价体系下,若土体构型参与耕地评价,1∶50万土壤图的评价结果与土体构型图的评价结果在省级尺度上趋势相似,但后者与市级、县级耕地地力评价相比产生的尺度效应较低,与小麦单位产量拟合度更高;若采取剔除土体构型指标的技术路线,评价精度较前两者均明显降低。     

土壤制图中土壤类型配色模型构建与应用

在全国1∶5万土壤图集制图中,土壤类型的配色既需表现土类等高级类型的分布特征,也要表现土属等较低级类型的差别。我国土壤低级类型众多,且1∶5万基本比例尺图幅达2万余幅,采用传统人工设色方法进行土壤制图,不仅效率低,而且难以保持图幅间土壤颜色的协调一致性。针对这一技术难题,本研究采用图幅间相似配色方法和人机交互的设计思想,通过建立1个多层级管理色库、人工设置土壤类型的Q配色单元及其多个近似色系(色组),建立了Q配色单元的避让选色和区域土壤特征分析等5个组件模型,构建了土壤类型配色模型(SCO-Model)。该模型在大比例尺土壤制图中不仅反映了区域土壤的总体分布特征,也表达了土壤类型间的差异,特别是实现了大比例尺土壤制图中土壤类型的快速智能配色,大大提高了制图效率。     

土壤系统分类在大比例尺土壤制图中的应用——以安徽宣城样区为例

提出了制图的指导思想 ,拟订了上图单元类型 ,在此基础上详细地阐述了样区大比例尺土壤制图的过程。     

土壤系统分类在大比较尺土壤制图中的应用—以安徽宣城样区为例

提出了制图的指导思想，拟订了上图单元类型，在此基础上详细地阐述了样区大比例尺土壤制图的过程。     

空间回归模型在区域数字化土壤制图中的应用——以河南封丘县为例

以河南省封丘县为研究区,以环境协变量信息和先期获得的土壤数值化分类结果为基础数据源,在土壤分类距离空间自相关性分析的基础上,构建土壤分类距离—环境协变量空间回归模型,实施土壤分类距离空间预测,并最终实现研究区25 m分辨率数字化土壤制图.输出结果表明,研究区5种主要土壤类型中,普通底锈干润雏形土分布面积最大、弱盐灌於干润雏形土次之,分布比例分别为36％和24％.结合确定性趋势距离和非确定性残差的空间变异特征,阐释了研究区土壤空间分布格局的发生学背景和随机性因素的影响.与基于随机模型的土壤预测制图相比,基于环境协变量空间回归模型的数字化土壤制图输出结果展示了相似的研究区土壤空间分布整体格局,且具有细节清晰、图斑边界自然的特点.一方面能更好地诠释土壤空间分布的连续性和渐变性特征;另一方面能较好地反映微域成土环境对土壤发生学特性空间变异特征的影响.     

对全国第二次土壤普查中土类、亚类划分及其调查制图的辨析

按照中国发生分类对新采集的68个北京市山区的土壤剖面进行了分类命名,并与剖面点所在土壤普查图上的分类名称进行比较,结果是只有18个剖面的分类名称一致。造成分类名称不一致的原因:1发生分类以区域典型土壤剖面分类命名,而区域内很多土壤不同于典型土壤剖面;2发生分类往往以现代生物气候带为主要分类标准命名区域土壤,而不是根据土壤性质;3分类不一致的最大原因可能是制图精度不够。研究认为,土壤分类必须依据土壤性质本身,而不是土壤形成因素;采取野外单土壤性质调查制图,室内叠加单土壤性质图形成多属性图斑,根据分类系统对它们进行综合分类,以提高分类制图精度。     

卫星图象土壤类型自动识别与制图的研究——Ⅱ.自动识别结果的成图及其与常规土壤图的比较

自动识别的非监督和监督分类图(谱类图)变成正式土壤图的关键,是根据谱类的内在序列、聚类树系图、波段辐射曲线和地理控制系统,建立谱类与实际土壤类间的对应关系。然后在谱类图上勾绘地理控制线并进而勾绘土壤累线。再后调整纵横比例尺并转绘成正式的土壤图。把这样编出的土壤图与用常规方法编出的土壤图进行了比较。结论是以卫星遥感数据自动识别为基础,同时运用常规调查、编图资料进行分类制图的方法,是能够在中、小比例尺土壤分类制图的实践中加以采用的。     

Humus Forms in Forest Soils: Concepts and Classifications

The concepts and classifications of humus forms developed since the time of scientific pedology formation are critically discussed. The concept of humus forms (types) relates to the classification of a set of topsoil organic and organomineral horizons, which reflects morphologically distinct phases of plant litter and soil organic matter decomposition, but not to the fractions of soil organic matter. Humus forms reflect various types of transformation and accumulation of organic matter in the soil. The stages of development and modern classifications of humus forms abroad are described. The taxonomy of humus forms in Russian literature and its application for the mapping and evaluation of forest soils are considered, as well as its use for the mathematical simulation of soil organic matter mineralization and humification. Prospects for the development of the classification of humus forms in combination with the basic soil classification of European Russia are discussed. A call for an understanding and a common language in soil science at the international level is underlined.     

Integrating properties of soil map delineations into ordinary kriging

Stratification of a region based on soil map delineations followed by within-stratum interpolation is sometimes used to combine soil maps and spatial interpolation. However, not all delineations are equally suitable to subdivide an area into precisely located mutually exclusive strata. This paper proposes a flow-path to characterize the nature of soil map delineations and a methodology to integrate the properties of map delineations into ordinary kriging.Four types of delineations were distinguished based on three criteria: the nature of transition (discontinuous or gradual), the mapping accuracy, and the structure of the within-unit spatial variation. For each type of delineation the ordinary kriging algorithm was modified to integrate its properties in the interpolation.As a test case, the sand content of the topsoil in the province of West-Flanders (Belgium) was mapped, using independent test data for validation. Inside the mapping units and at delineations identified as gradual transitions, our procedure, termed ordinary kriging integrating properties of map delineations (OKPD) , performed similarly to stratified ordinary kriging (SOK). However, close to the delineations identified as inaccurately mapped discontinuities the mean square prediction error of OKPD was 0.64 times that of SOK. Moreover, near these delineations, the prediction variance was largely underestimated by SOK (relative variance = 5.1), whereas OKPD produced a more realistic value (relative variance = 1.5).     

基于支持向量机的典型冻土区土壤制图研究

基于青藏高原大片连续多年冻土分布的东部边缘,青海省兴海县温泉地区的野外调查数据,通过对研究区遥感数据的分析,开展了土壤制图方法的探讨。以成土因素学说和土壤-景观模型理论为基础,筛选土壤分类潜在变量,在不同的变量组合下运用支持向量机(SVM)的方法建立土壤-景观模型,对整个研究区进行预测性分类。为了更好地检验该方法的有效性,采用五折交叉方式进行结果的验证。并通过对比不同变量组合的交叉验证结果和分布模拟结果图,确定了适合典型冻土区土壤分类的环境变量组合,以较少的样本知识较好地预测该区土壤类型的空间分布。     

基于GIS的中国土壤分类专家系统设计

土壤系统分类以定量化指标划分土壤类型,为土壤自动分类系统的建立提供了依据;地理信息系统(CIS)的应用扩展了土壤空间信息表达的能力,为实现土壤分类自动制图提供了手段。本文着重模仿专家的思维过程,探讨如何实现土壤自动分类。(1)采用面向对象的方法表达专家经验规则、诊断层和诊断特性知识,并在此基础上提出了决策树的构造方式和推理方法;(2)从土壤系统分类专家的知识表示和推理机的构建两个方面,提出了土壤分类专家系统(SCES)的体系结构、土壤自动分类与地理信息融合的方法和基于GIS和专家系统(ES)的土壤自动分类检索系统的框架结构。     

Soil Delineations on Public Cadaster Maps as Elements of the Soil–Land Cover Mapping

Eurasian Soil Science - The depiction of soil delineations on a public cadastral map clearly demonstrates the potentialities of large-scale soil mapping. The development of land legislation...     

The effect of survey density on the results of geopedological approach in soil mapping: A case study in the Borujen region, Central Iran

Landscapes are considered to be complex systems that are hierarchically structured and spatially scale-dependent. Geopedology allows a systematic approach in geomorphic analysis for soil mapping that extrapolates the results obtained at sample areas up to similar units. This paper examines the influence of sampling intervals on the accuracy of geopedological results in the Borujen region, Central Iran. After a primary interpretation of the study area on air photos (1:20 000), a geomorphic unit that encompassed the maximum surface of the sample area (and also the study area) was selected and was surveyed at three different scales: 500, 250 and 125 m intervals. The credibility of generalization of the results of the geopedological approach for the studied unit was tested by comparison with three profiles in a similar unit outside the sample area, named the validation area. Although the type of mapping unit in the sample area and the validation area was the same (complex) at the three different scales, the dominant soil in the validation area was different in comparison with the sample area at 125 and 250 m intervals. The results indicate that the geopedological approach to soil mapping is better carried out in reconnaissance or exploratory surveys. Comparison of soil types between the unit in the sample area and the validation area at three scales indicated that by increasing the taxonomic accuracy, the hidden aspects of the soils may be more identifiable. Therefore, although the geopedological approach tries to distinguish more homogeneous soil mapping units, it still is not able to fully define and represent the variability and apparent chaotic nature of the soils. We recommend further investigations on different techniques of stratifying the landscape in order to better analyze and understand the soil forming processes and soil variability and to improve sampling and mapping approaches.     

土壤侵蚀调查与制图方法的初步研究

讨论土壤侵蚀调查的目的、方法、内容和提交的成果。土壤侵蚀调查目的是研究土壤侵蚀类型及其区域差异,揭示发生发展规律,为水土保持及其规划服务。土壤侵蚀类型的划分应该科学性和生产性相结合,侵蚀方式、形态和强度相结合,用遥感资料为侵蚀调查提供大量的有用信息。以地形图作基础,遥感技术和地面调查结合是土壤侵蚀制图的有效手段,它快速、准确,节省人力、财力,能广泛应用。     

基于高分5号影像的东北典型黑土区土壤分类

高精度的土壤分类及制图结果有助于更好地制定土地环境保护和土地资源利用策略。为探究星载高光谱影像实现区域尺度高精度土壤分类及制图的可能性,该研究获取东北黑土区拜泉县、明水县共计4幅高分5号(GF-5)星载高光谱遥感影像。首先,将原始反射率数据(Original Reflectance,OR)进行包络线去除处理获得去包络线数据(Continuum Removal,CR);其次,对OR和CR进行主成分分析(Principal Component Analysis,PCA)处理,分别得到反射率主成分信息(OR-PCA)和去包络线主成分信息(CR-PCA),并在OR-PCA和CR-PCA的基础上结合地形因子(Terrain,TA)。最后,OR、CR、OR-PCA、CR-PCA、OR-PCA-TA、CR-PCA-TA分别作为输入量结合随机森林分类模型,进行土壤分类并实现数字土壤制图。结果表明:1)包络线去除法可有效地提高星载高光谱土壤分类精度,与OR相比,CR的总精度提高了5.48%,Kappa系数提高了0.12。2)PCA可有效地降低高光谱数据的冗余性,提高模型的运算效率以及分类精度;与CR作为输入量相比,CR-PCA的土壤分类总精度提高了3.67%,Kappa系数提高了0.02。3)TA的引入显著提升了土壤分类精度,以CR-PCA-TA作为输入量的土壤分类精度最高,总精度为81.61%,Kappa系数为0.72,实现了高精度的土壤分类模型及土壤制图。研究结果可为大范围、高精度的土壤分类及制图提供新的思路。