应用土壤-景观定量模型预测土壤属性空间分布及制图

以土壤-景观定量模型为基础的土壤制图方法在世界范围内得到了广泛研究。本文在皖南宣城的丘陵地带内选择研究区,从该区的数字高程模型(DEM)中获取景观信息:地形因子,定量地分析了土壤属性与地形因子之间的相关关系,并建立基于该关系的线性土壤-景观定量模型,最后应用该模型来预测土壤属性在空间上的分布并制图。结果表明:土体厚度和表层有机质含量与地形因子之间有着显著相关性;建立的线性回归模型分别能解释土体厚度、表层有机质含量空间变异的32.2%和35.3%;依据该模型预测的土体厚度和表层有机质含量具有较高的准确度,并能制图表达土壤属性在空间上的自然连续性。     

应用遥感技术进行土壤制图的优点

作为遥感产品的航、卫片影像,是地面或地表以下一定深度的地物反射和发射电磁波,经传感器接收,光学或电算处理,在像片上的客观记录与反映。因此,它是地表形态(包括高差和阴影)植被(包括农业利用)、水文(包括地表水和地下水)和地表物质组成(岩石与土壤)等环境因素的综合反映,具有环境(或景观)因素的综合信息特征。而土壤正是环境诸因素综合作用下发生发育、演变,并与环境协调统一的自然产物。     

基于Fisher判别分析的数字土壤制图研究

利用已知类型的土壤样点及其所处位置的高程、坡度、平面曲率、剖面曲率、复合地形指数等数据,基于Fisher判别分析方法对安徽宣城样区的土壤类型进行预测和制图表达。结果表明,土纲级别的预测效果较好,正确率达到84.2%。但随着从土纲到亚类级别的降低,由于受土壤样点数量限制,土壤类型预测的准确率也逐步降低。通过与样区1986年基于发生分类的土壤图进行对比,采用的方法无论是在制图精度,还是图面信息的负载量方面都要优于传统方法,能够更加客观真实地反映土壤在自然界的空间分布。     

广义线性地统计模型在典型亚热带丘陵区数字土壤制图中的应用

数字土壤制图(DSM)在当前的应用越来越广泛,其方法主要包括环境相关模型、空间自相关模型,以及这些模型的混合模型。理论上,混合模型相对单一模型具有明显的优势。广义线性地统计模型(GLGM)也是一种混合模型,相对于最常用的混合模型——回归克里格(RK),又具有能加入随机效应来解决土壤变异的非平稳性等优势。然而,GLGM因计算繁琐等缺点,在国内外应用较少。本文以广西南宁高峰林场内一小面积(3.03km2)丘陵为研究区,以14个地形因子为预测变量,使用GLMM及其与普通克里格(OK)相结合的模型(GLGM),对土壤有机碳(SOC)、pH、黏粒和阳离子交换量(CEC)的空间分布进行预测,并与常用的多元线性回归(MLR)、地理加权回归(GWR)、回归森林(RF)、普通克里格(OK)、RK和广义可加模型(GAM)进行比较。结果表明：GLMM在预测黏粒上准确度较高;GLMM和GLGM在预测CEC上准确度中等;GLMM和GLGM在预测SOC和pH上准确度较低。综合线性回归模型的调整决定系数、块金效应和全局莫兰指数,本文认为,当土壤属性与环境变量具有较低的线性回归调整决定系数(即小于5%)、土壤属性具有较弱的空间自相关性(即块金效应大于71%)和较强的局部空间变异(即全局莫兰指数小于0.09)时,GLMM和GLGM具有较高的适用性,例如本文中的黏粒。反之,GLMM和GLGM的适用性不好,例如本文中的SOC和pH。鉴于土壤空间变异的高度异质性和多尺度性,本文认为GLMM和GLGM具有较好的应用前景。但是,在未来的研究中还需要进一步研究如何提高GLMM和GLGM的模拟效率。     

土壤质量数字制图方法浅论

本文简要论述了土壤质量数字制图的一般过程及其与传统土壤制图的异同,并依据土壤制图原理确定数字制图的几个重要参数,同时简述了数字制图对野外土壤调查的要求以及对传统图件的处理。     

土壤专题图中采样点点位标识模型的构建

采样点图在直观展示已采集样点分布同时,也为确定补充采样点的位置提供了参考。制图时,通常以采样点编码在地图图面标识各个采样点,但由于受空间地理位置影响,采样点标识常呈无序排列,当地图中采样点密度及地图幅面较大时,读图时难以查找目标采样点。为实现制图后的采样点标识呈有序排列,构建了"土壤专题图中采样点位标识模型(Soil Sampling Point Labeling Model for Thematic Soil Maps:SAMPLA)",该模型主要有读图视区划分模型;土壤采样点位归属读图视区判定模型;土壤采样点顺序标识模型等3个子模型组成。基于Arc GIS 10.0,采用C#语言进行计算机编程,实现了SAMPLA。用1∶50 000国家标准分幅和县级地图的土壤采样点对模型进行验证,验证结果表明,模型可适用于不同类型分幅地图、不同比例尺,有助于实现规范化、批量化制图,提高了读图效率;但是读图视区划分方案对标识结果有一定影响;其他行业专业领域,如环境科学、水科学、地质科学等在制作类似于土壤采样点的点位图层时也可采用此模型。     

县域土壤质量数字制图方法比较

土壤质量研究几乎涵盖土壤研究的所有领域,土壤质量制图理论与方法是土壤质量研究的一项重要研究内容。该研究以北京市密云县为研究区,基于土壤质量评价最小数据集和指数和法计算的土壤质量指数,探究了在地学模型支持下区域土壤质量数字制图方法。研究设计了5种区域土壤质量数字制图方法,并比较了不同方法的空间数字制图精度。结果显示,目前广泛使用的基于参评指标空间插值结果的土壤质量数字制图方法精度最低、工序较繁琐,且无法反映研究区景观高度异质的特点;而基于计算后的土壤质量指数（soil quality index,SQI）,借助于地统计学方法的土壤质量数字制图方法相对比较科学合理,其中又以基于计算后的SQI和回归克里格法预测效果最好,均方根误差最小,仅为0.01897,相对于基于参评指标空间插值结果的土壤质量数字制图方法,精度相对提高率最大,达到50%以上。综合考虑空间制图精度、工序的繁简程度,在该研究设计的5种方法中基于计算的SQI和回归克里格法最佳,该法避免了地统计插值在景观高度异质区的应用局限性,预测结果与实际最为相符。     

DEM栅格分辨率对多元线性土壤—景观模型及其制图应用的影响

以亚热带丘陵地区为对象,以该区4 km×3 km的5 m、10 m、15 m、20 m、25 m、30 m数字高程模型(DEM)为基础,建立多元线性土壤景观模型,并应用该模型预测研究区内土壤表层有机质含量分布,进而比较不同分辨率DEM中土壤景观模型及其预测制图的精度。结果表明:在本研究区11 km2范围内,随着DEM栅格分辨率降低,坡度、曲率、比汇水面积(对数)频度均表现出了向其中值区集中的趋势;地形因子的这一变化规律对土壤景观模型的影响较小,例如模型的变量、变量系数及R2在不同分辨率DEM中的差异很小;但地形因子的这一变化规律对模型预测制图的精度具有较大影响,各项指标均说明,模型在10~25 m DEM中的制图精度较高,而在更高分辨率(5 m)或更低分辨率(30 m)DEM中较低。本研究结果对其他亚热带丘陵地区具有一定的指示意义。     

我国土壤调查制图及土壤分类工作的回顾与展望

建国以来,我国围绕国土整治与区域治理任务,在各地开展了土壤调查、制图及分类工作,为土壤资源的开发利用、建立土壤信息系统以及制定以诊断层为基础的土壤分类系统作出了贡献。今后应加强遥感技术与土壤信息系统的结合,使之步入新的发展阶段。     

基于模糊集理论提取土壤—地形定量关系及制图应用

通过对研究区地形因子的模糊聚类,提取了地形因子组合与特定土壤属性的定量隶属度关系,然后对隶属度高值区土壤进行目的性采样为隶属度函数赋值,制作研究区土层厚度连续分布图。通过野外实地验证,将观测值与图中预测值比较,结果显示该方法制图精度在82%左右,具有一定的可靠性。进一步考察认为该模型在地形部位较低,地势较为平坦,土壤发育较好,土层较厚,成土环境相对稳定的地区预测效果更好,适用性更强。该方法能提高土壤制图效率,降低制图成本,提高制图精度,对土壤微域变异的表现更为详细,图面信息负载量更高。应用该方法制作大比例尺土壤详图不失为土壤调查与制图领域一种可行的新方法。     

Quantitative mapping of soil types based on regression kriging of taxonomic distances with landform and land cover attributes

Nowadays, French soil scientists tend to gather new and existing soil data into a common database. The use of this database potentially allows for resolving environmental issues, largely through soil mapping. The purpose of this study is to present a methodology for mapping soil types illustrated by typical observations in the soil database, in this case from the La Rochelle area on the French Mid-Atlantic Coast. The main hypothesis underlying the method is that soil types result from environmental factors such as landform, parent material, and land cover. The method can be divided into four stages. The first step is to construct a local soil type classification from the database by a two-stage continuous classification procedure. The result of this procedure is that at each observation point, the soil is described by a vector of taxonomic distances to each of k centroidal soil types. In the example given, k=18. The second step involves fitting soil–environment equations, one for each centroidal soil type, by regressing taxonomic distances on layers of multivariate environmental data observed on a fine 20-m grid, by multiple linear regression. In this case, the layers are terrain attributes derived from a digital elevation model and land cover attributes derived from three bands of a SPOT image. The third step is to predict k maps or raster GIS layers representing taxonomic distances to soil types on the 20-m grid, using the soil–environment equations and the kriging of the residuals from the regressions. This results in many potential maps: a summary map depicting the nearest centroidal soil type (the soil type for which the taxonomic distance is least) at each location is possibly the most useful, and another one representing the minimum taxonomic distance which, if considered too large, might suggest locations for further field survey to refine the soil types. A map of standard errors of the kriged taxonomic distance residuals to the nearest centroidal soil type can be made to indicate spatial uncertainty. Continuous fuzzy membership maps can also be constructed from the distances. The fourth step involves validation with an independent soil data set allowing discovery of the nature of the actual prediction errors. Thirty-eight percent of sites in a validation sample of 1234 sites was unequivocally validated, 23% was equivocally validated, and the remainder was predicted wrongly by the method.     

Incidence of soil surface crust types in semi-arid Niger

Soil water availability is most essential in the Sahelian agriculture but is hampered by several factors. Surface crusts or crust-like surfaces, which are characteristic of most Sahelian soils, have been shown to decrease water infiltrability and increase runoff. Their type and structure are influenced by soil texture, vegetation cover, erosion and deposition effects of wind and water. A soil and terrain survey in semi-arid SW-Niger was carried out to explain the patterns of soil surface crusts and the deterioration of the land. The soil surface crusts were shown to depend also on specific terrain factors including land use type and intensity, and terrain type and position. Chemical and physical soil factors such as organic carbon, soil colour and texture occurring with specific crusts indicate soil degradation, especially in sloping terrain, which increases runoff and soil erosion. For sandy soils, surface tillage is required to break up the crusts. Higher surface organic matter is recommended to enhance water infiltration in soils.     

中亚热带四种森林土壤团聚体及其有机碳分布特征

选择中亚热带地区4种典型森林类型:杉木林、湿地松林、毛竹林和次生林4种森林土壤为研究对象,研究了森林类型对土壤不同发生层水稳性团聚体及其有机碳分布特征的影响。结果表明:不同森林类型对>5 mm和2~5 mm土壤团聚体含量影响显著(p<0.05),表现为次生林>杉木林>毛竹林>湿地松林,而在其他粒径无显著差异。0~30 cm土层内团聚体R0.25和MWD次生林显著高于其他人工林,杉木林次之,湿地松林和毛竹林最低,其他土层无显著差异。各森林类型同土层不同粒径团聚体中有机碳含量随粒径大小变化,团聚体粒径越小,有机碳含量越高。0~10 cm土层同粒径土壤团聚体有机碳含量从大到小依次是次生林、杉木林、湿地松林和毛竹林,而在其他土层各森林类型之间差异不显著。     

Accounting for extensive topographic and pedologic secondary information to improve soil mapping

Soils generally vary in a quite complex way. To assess and model spatial variability, several variables can be sampled in addition to the target used to quantify and describe the main phenomenon under study. One of the major advantages of geostatistics over simpler spatialization methods is that sparsely observations of the primary attribute can be complemented by secondary attributes that are more densely sampled. Two methods were applied to incorporate dense secondary information: multicollocated cokriging, which restricts the neighbourhood to the only secondary data collocated with the available data of the primary variable and simple cokriging with varying local means related to crisp classes. The objective of this paper was to find the method that best improves the estimation of primary attributes through dense secondary information for the study area, which was the province of Siena in central Italy, an area of about 3820 km². Soil samples were taken at 742 locations and depth, sand and clay contents and available water capacity were determined.     

面向土壤系统分类的土壤调查制图方法的初步研究

我国的土壤系统分类方案已经基本形成,但还没有相应的土壤调查方法技术研究。按照传统土壤调查的主要剖面、检查剖面、定界剖面的思想与办法,采用空间内插技术,在研究区的4条实验路线上共挖掘了64个剖面点,通过这些剖面点的诊断层和诊断特性确定了研究区的土壤类型并勾绘了土壤类型界线。再用1条检验路线对勾绘的土壤图进行检查,结果表明,在检验路线上设置的20个检查剖面点中,其中19个剖面点与实际情况相符,正确率95%,说明使用内插法进行面向土壤系统分类的土壤调查制图是可行的。再结合土壤景观可以辅助土壤调查工作者更高效地确定土壤类型、勾绘土壤界线。     

我国主要类型土壤的有效态硒及其与某些土壤性质的关系

Forty-eight soil profiles were sampled from different ecological and pedogeochemical areas of China and their available selenium (Av-Se) contents were determined. Results showed that the content of Av-Se in the profiles of soils in China ranged within 2.49~18.10 μg kg^-1, with a mean value of 10.01 μg kg^-1, and was in the sequence of Ferralisols > Luvisols > Isohumisols > Aridisols. The correlation analysis between Av-Se and the soil physical-chemical properties revealed that the correlations between Av-Se and O.M., CEC, Fe₂O₃, Al₂O₃, ignition loss, Co and Zn were positive at a highly significant level, but those between Av-Se and pH, base saturation, CaO, Ba and Sr were all negative at a highly significant level. The reason of some diseases related to the Se deficiency might be the leaching loss of selenium in some soils.     

延边烟区不同土壤的根际土壤微生物生态效应研究

为揭示烤烟根际微生物数量及酶活性的变化规律,阐明烤烟-土壤-微生物之间的协同作用机理,在延边烟区采集不同土壤类型的烤烟根际土壤,研究了烤烟根际土壤微生物生态效应.结果表明:不同土壤条件下烤烟各时期根际微生物区系和微生物生理菌群数量存在着较大的差异,其中暗棕壤黏土和暗棕壤黑砂土比白浆土更适合细菌和解钾菌的生长,白浆土真菌数的变化幅度较大可能是引起烟叶质量变差的原因之一,暗棕壤黏土和暗棕壤黑砂土在烤烟生育期内放线菌数量的变化较大,明显大于白浆土;自生固氮菌在移栽后 60 天前数量均较低,60 天后急剧升高,100 天时暗棕壤黏土和暗棕壤黑砂土自生固氮菌数量显著高于白浆土;氨化菌生长的最适宜期出现的早晚顺序为:暗棕壤黏土＞暗棕壤黑砂土＞白浆土;生育期内根际土壤解磷菌数变化较大,暗棕壤黏土烟株在旺盛生长时期的解磷菌数显著高于其他 2 种类型土壤.过氧化氢酶活性的变化规律很大程度上受土壤类型的影响,而转化酶和多酚氧化酶变化受土壤类型影响较小,但两者的大小受土壤类型的影响.     

SoilFlex: A model for prediction of soil stresses and soil compaction due to agricultural field traffic including a synthesis of analytical approaches

Soil compaction is one of the most important factors responsible for soil physical degradation. Soil compaction models are important tools for controlling traffic-induced soil compaction in agriculture. A two-dimensional model for calculation of soil stresses and soil compaction due to agricultural field traffic is presented. It is written as a spreadsheet that is easy to use and therefore intended for use not only by experts in soil mechanics, but also by e.g. agricultural advisers. The model allows for a realistic prediction of the contact area and the stress distribution in the contact area from readily available tyre parameters. It is possible to simulate the passage of several machines, including e.g. tractors with dual wheels and trailers with tandem wheels. The model is based on analytical equations for stress propagation in soil. The load is applied incrementally, thus keeping the strains small for each increment. Several stress–strain relationships describing the compressive behaviour of agricultural soils are incorporated. Mechanical properties of soil can be estimated by means of pedo-transfer functions. The model includes two options for calculation of vertical displacement and rut depth, either from volumetric strains only or from both volumetric and shear strains. We show in examples that the model provides satisfactory predictions of stress propagation and changes in bulk density. However, computation results of soil deformation strongly depend on soil mechanical properties that are labour-intensive to measure and difficult to estimate and thus not readily available. Therefore, prediction of deformation might not be easily handled in practice. The model presented is called SoilFlex, because it is a soil compaction model that is flexible in terms of the model inputs, the constitutive equations describing the stress–strain relationships and the model outputs.     

土壤制图中多等级代表性采样与分层随机采样的对比研究

采样设计是土壤地理研究中备受关注的重要问题。本文以区域尺度土壤属性制图为例,将多等级代表性采样与经典采样中的分层随机采样进行对比研究。以安徽宣城研究区的表层砂粒含量为目标要素,采集数量均为59个的两套样点,设计不同数量(46、58和59)的样点分组,采用两种制图方法进行制图并利用独立验证点进行评价。结果表明:1)无论是采用多元线性回归方法还是基于环境相似度的制图方法,在同等样点数量下,利用代表性样点所得土壤图精度均高于利用随机样点所得精度,并且利用少量代表性样点(46个)所得土壤图精度也高于利用多量随机样点(59个)所得精度;2)随着代表性较低样点的增加,土壤制图精度基本有一个提高的趋势,而采用随机样点所得土壤图的精度波动较大。因此,可认为多等级代表性采样方法是一种可用于区域尺度土壤调查的有效采样方法,且比分层随机采样高效、稳定。     

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。