Principles of soil mapping of a megalopolis with St. Petersburg as an example

For the first time, a soil map of St. Petersburg has been developed on a scale of 1 : 50000 using MicroStation V8i software. The legend to this map contains more than 60 mapping units. The classification of urban soils and information on the soil cover patterns are principally new elements of this legend. New concepts of the urbanized soil space and urbopedocombinations have been suggested for soil mapping of urban territories. The typification of urbopedocombinations in St. Petersburg has been performed on the basis of data on the geometry and composition of the polygons of soils and nonsoil formations. The ratio between the areas of soils and nonsoil formations and their spatial distribution patterns have been used to distinguish between six types of the urbanized soil space. The principles of classification of the soils of urban territories have been specified, and a separate order of pedo-allochthonous soils has been suggested for inclusion into the Classification and Diagnostic System of Russian Soils (2004). Six types of pedo-allochthonous soils have been distinguished on the basis of data on their humus and organic horizons and the character of the underlying mineral substrate.     

Soil cover patterns in the Dzhida Depression and their representation on the soil map of 1: 500000 scale

A map of the soil cover patterns in the Dzhida Depression (Baikal region) has been compiled on a scale of 1: 500 000. The grouping of the soil cover patterns into larger categories makes it possible to retain the information contained on large-scale soil maps upon their generalization to the small-scale soil map. The latter displays the regularities of soil distribution at the levels of soil types and subtypes. The areas of the major soil groups have been calculated. It is shown that podburs predominate in the northern taiga ecosystems (72%), whereas acid soddy taiga soils (71%) and podburs (22%) predominate in the middle taiga zone. Minor areas in these zones are occupied by podzolic soils (9%) and permafrost-affected taiga gley soils (14%).     

A map of the soil cover patterns in the western part of the Transbaikal region (1: 500000 scale)

The results of soil surveys in the Khorinsk district of the Buryat Republic have been generalized on a map of the soil cover patterns on a scale of 1: 500000. The map reflects the soil cover patterns in the zones of mountainous tundra and taiga, mountainous forest-steppes, sand massifs on piedmonts, and plain steppes and dry steppes. The areas of each component of the soil combinations shown on the map have been calculated. In the course of the generalization of large-scale soil maps, information on the genetic types and subtypes of soils has been preserved. The new map adequately displays the real pattern of the soil distribution in the studied area.     

Soil cover patterns and land resources in the south of the Selenga mountainous region

Soil cover patterns within the Kyakhta area of pine stands and the Kudarinsk area of dry steppes in the south of the Selenga mountainous region are characterized. The groups of soil combinations are shown on the map developed on a scale of 1: 500000. The areas of particular soils composing the combinations have been calculated. Thus, this small-scale soil map generally preserves information reflected on large- and medium-scale soil maps.     

基于GIS和RS的土地利用与土壤侵蚀关系研究——以冀北地区为例

 冀北地区土壤侵蚀以水蚀和风蚀为主,根据水利部颁布的《土壤侵蚀分类分级标准》(1997),参考有关学者提出的土壤风蚀强度分级指标,构建研究区土壤侵蚀强度的分级指标。运用GIS和RS技术,提取土地利用、坡度、植被覆盖度、土壤质地等信息,通过GIS空间叠加分析,得出冀北地区土壤侵蚀强度分级图,详细研究土壤侵蚀强度的空间分布特征;进一步与土地利用图叠加,分析不同土壤侵蚀强度下的土地利用特征和不同土地利用类型的土壤侵蚀状况。     

Quantitative Evaluation of Pedodiversity in the Russian Arctic and Subarctic (by Cartographic Data)

Eurasian Soil Science - A quantitative assessment of the diversity of the soil cover components of the Arctic and Subarctic as shown on the Soil Map of Russian Federation, scale 1: 2.5 M was...     

市域尺度的稀有濒危土壤类型的界定与评价——以郑州市为例

在当今世界城市化高速发展的背景下,土壤资源的保护也越来越受到人们的关注,土壤多样性骤减也成为了全球关注的焦点,界定和评价稀有濒危土壤对于保护土壤资源及其多样性具有非常重要的指导意义。本文以郑州市为例,应用土壤类型密度和土壤多样性两种多样性测度方法分别对郑州市1 km×1 km和5 km×5 km网格尺度下基于不同分类级别的土壤空间多样性分布格局进行了分析和定量化研究;利用1988、2001、2007和2013年4期遥感资料进行土地利用分类,结合基于第二次土壤普查的1∶20万郑州市土壤图,采用多时相连续对比法对郑州市近25年来土地利用变化对土壤的扰动情况进行了分析;结合土壤多样性方法和传统评价方法界定和评价了稀有濒危土壤。结果表明,郑州市土壤整体分布较为均匀,且随着分类单元级别的降低,构成组分多样性指数升高,即分类越细,土壤类型分布越均匀;1988~2013年郑州市土壤受到非农建设扰动剧烈,干扰比例为16.01%,随着时间的推移,土壤受扰动的速度是呈上升趋势的;稀有土属有16种,濒危土属有2种,稀有濒危土属有4种。截止2013年濒危土属整体受到扰动比例高达35.38%,而稀有土属受到扰动比例为8.76%。     

Correction of a large-scale soil map with the use of the new classification system of Russian soils

A large-scale soil map of one of the farms in the south of Karelia has been analyzed. This map was initially compiled in 1979 on the basis of the official Classification and Diagnostics of Soils of the Soviet Union (1977). We have corrected it with the use of the new Classification and Diagnostics of Russian Soils. Both the names of the map units and the particular delineations on the map have been changed. These changes are related to differences in the principles of soil diagnostics in the old and new classification systems and to real changes in the soil cover that have taken place after the map’s compilation. In particular, large areas of peat bogs have been drained, and the cultivated peat soils have been subjected to accelerated mineralization. Surface planing works after digging drainage channels have also changed the soil cover pattern. The revised large-scale soil map developed on the basis of the new classification system gives more adequate information about the real soil cover.     

Digitized version of the state soil map on a scale of 1 : 1 M: Problems and solutions

Problems of the creation of a high-quality digitized version of the State Soil Map (SSM) on a scale of 1 : 1 M for the European part of Russia are discussed. Sheets of the SSM have been compiled for the entire territory of Russia. For the European part of Russia, they have been digitized, and a corresponding geographic information system has been created. At present, the attribute database to the map is being developed. In the course of the digitization of separate sheets of the map and the creation of a general legend, certain drawbacks of the map have been revealed. They are related to the insufficient completeness of information on the genesis of soil-forming rocks shown on different sheets; to the inconsistency in the names of some soils; and to the use of the same conventional signs for describing the soil texture in the upper horizons and in the parent material, which is incorrect in the case of texture-differentiated soils. The reasons for these drawbacks of the original map are explained. It is stressed that the SSM is a highly informative map that has played a crucial role in the development of pedology and soil cartography in Russia. A digitized version of this map makes it possible to introduce certain corrections to the original map sheets. The essence of the first stage of the work on the correction of the SSM in the digitized version and the methods applied for this purpose are characterized. Problems related to the creation of the database for the digitized version of this map are also discussed.     

Digital soil map of the Ussuri River basin

On the basis of digital soil, topographic, and geological maps; raster topography model; forestry materials; and literature data, the digital soil map of the Ussuri River basin (24400 km²) was created on a scale of 1: 100000. To digitize the initial paper-based maps and analyze the results, an ESRI ArcGIS Desktop (ArcEditor) v.10.1 (http://www.esri.com) and an open-code SAGA GIS v.2.3 (System for Automated Geoscientific Analyses, http://www.saga-gis.org) were used. The spatial distribution of soil areas on the obtained digital soil map is in agreement with modern cartographic data and the SRTM digital elevation model (SRTM DEM). The regional soil classification developed by G.I. Ivanov was used in the legend to the soil map. The names of soil units were also correlated with the names suggested in the modern Russian soil classification system. The major soil units on the map are at the soil subtypes that reflect the entire vertical spectrum of soils in the south of the Far East of Russia (Primorye region). These are mountainous tundra soils, podzolic soils, brown taiga soils, mountainous brown forest soils, bleached brown soils, meadow-brown soils, meadow gley soils, and floodplain soils). With the help of the spatial analysis function of GIS, the comparison of the particular characteristics of the soil cover with numerical characteristics of the topography, geological composition of catchments, and vegetation cover was performed.     

Large‐scale soil maps and a supplementary database for land use planning in Estonia

A soil map at the scale 1:10,000 serves as a major important document for land owners and local governments, which allows them to use soil information in their daily activity. The intensity of exploitation of soil maps will increase when the very map and its legend are supplemented, within colored and indexed polygons, with information about soil texture and reaction by layers, but also about the thickness and characterization of the epipedon, quality indices for soil assessment, classes of stoniness, and prevalent fractions of stones, erosion risk, etc. Special maps of agronomical status, with a list of proper measures for improvement of soils and their associations, should form a regular component of large‐scale mapping. As decrease in arable land and increase in the forest area are common trends in land use, these maps and general soil data should serve as the fundamental source of information for decision making concerning land use. Data indicating the suitability of any soil for any crop should be entered in a database. Application of GIS on any level of national economy, digitization of a large‐scale soil database and making it accessible to land users would allow to expand the amount of available information for each soil map polygon.     

The development of detailed soil maps on the basis of interpolation of data on soil properties

A methodology for creating detailed soil maps on the basis of a dense grid of soil testing points and the numerical interpolation of experimental data on the soil properties is discussed. The study of the soil cover patterns combines regular sampling grids with equal spacing and additional sampling points chosen with due account for the soil cover specificity in particular areas. Soil diagnostics are performed at each of the points, and the diagnostic features of the soils are recorded in the field. In a laboratory, these data are arranged into a database, and a legend to the soil map is created. The necessary and sufficient set of the quantitative soil characteristics is selected, and quantitative criteria of the boundaries between the separate soil polygons are determined on the basis of numerical interpolation. Algorithms to delineate soil polygons on the basis of the selected indices are developed. Separate thematic map layers are produced for each of the selected soil characteristics. An integral soil map for the investigated area is obtained via the superposition of these layers. The thickness and/or the depths of the upper/lower boundaries of the soil layer with definite diagnostic characteristics making it possible to distinguish the given soil from its neighbors are used as the criteria for delineating the boundaries between soil polygons. Special criteria based on the proportions between the thicknesses or depths of several layers can also be applied for this purpose. The creation of a detailed soil map of a plot on the Kamennaya Steppe is discussed as an example of the practical application of this methodology.     

Automated updating of medium-scale soil maps

An approach towards an automated updating of medium-scale soil maps via imitation of traditional mapping technologies is suggested. It is based on formulation of the rules of mapping in the form of classification trees for separating different soil cover patterns and on creation of the maps of soil-forming factors with the use of satellite data. Algorithms for mapping alluvial soils (Fluvisols), eroded (abraded), and anthropogenically transformed soils are presented. This approach was tested for the southern (Trans-Oka) part of Moscow oblast. The model for an automated soil mapping was realized using ILWIS software. The polygons of alluvial soils were mapped with a higher accuracy via the automated separation of floodplains according to the digital terrain model. The total area of alluvial soils shown on the medium-scale soil map decreased from 373 to 340 km². Calculations of slope angles according to digital terrain models allowed us to localize soil cover patterns with participation of eroded soils with a higher accuracy; their area decreased insignificantly: from 791 to 781 km². Anthropogenically transformed soils of building areas were mapped for the territory of Moscow oblast on the basis of satellite data for the first time. Their areas were delineated taking into account land use types and comprised 551 km², i.e., 15.4% of the total area (3570 km²) of the Trans-Oka part of Moscow oblast.     

Soil cover patterns in the Tugnuisk Depression of the Transbaikal region

A map of soil cover patterns in the Tugnuisk Depression of the Transbaikal region has been compiled on a scale of 1:500 000. This map contains information on the distribution of soil complexes and soil combinations and on the genetic and geometric characteristics of soil areas. It is derived from the original large-scale soil maps. The theory of soil cover patterns was used as the basis for cartographic generalization. This made it possible to preserve information on soil types and subtypes identified on the original maps and to show the real distribution pattern for all the components of the soil cover.     

The soil cover pattern in Western Transbaikal region as displayed on a 1: 500 000 scale map

Specific features of the soil cover in the Western Transbaikal region are discussed. The soil cover has been studied during soil survey works on scales of 1: 25000 and 1: 100000 in the Kizhinga district. On this basis, a generalized map of the soil cover patterns has been compiled on a scale of 1: 500 000. Data of the large-and medium-scale soil mapping are not lost upon the generalization procedure due to the reflection of soil combinations on the small-scale map, which makes the latter very informative.     

基于GF-1影像的冬小麦种植面积核算及直补政策实施评价

粮食直接补贴政策的实施,对于促进粮食生产和农民增收、推动农业农村发展发挥了积极的作用。补贴资金发放的精准程度在一定程度上影响着财政资金的支农效率。该文拟研究基于卫星数据进行粮食直补政策落实效果评价的可行性。以安徽省濉溪县为研究区,采用GF-1卫星16 m多光谱影像,在扣除线状地物、小地物的基础上,精准核算冬小麦种植面积。以乡镇为单位,比较统计发放面积与遥感核算面积,完成基于GF-1卫星数据的粮食补贴政策落实效果评价。结果表明：1）全县范围内,冬小麦直补发放统计面积与遥感核算面积较为吻合。直补发放统计面积为1239.17 km2,遥感核算面积为1227.37 km2,相对误差仅为0.96%;2）在乡镇尺度上,11个乡镇和1个开发区中共5个乡镇直补发放统计面积与遥感核算面积的相对误差<10%,8个乡镇<13%。相对误差最大的开发区、濉溪镇2个乡镇,以工商业用地为主,冬小麦种植面积少,地块零碎,遥感解译难度大。整体上,直补发放统计面积与遥感核算面积的 Nash-Sutcliffe 系数（Nash-Sutcliffe coefficient,ENS）为0.90,决定系数为0.93,两者相关程度较高。研究可为改进完善粮食补贴政策提供参考提供依据。     

Assessment of the postagrogenic transformation of soddy-podzolic soils: Cartographic and analytic support

The results of experimental studies of the postagrogenic transformation of loamy soddy-podzolic soils on the southern slope of the Klin-Dmitrov Moraine Ridge are discussed. A chronosequence of soils (arable soils (cropland)-soils under fallow with meadow vegetation-soils under secondary forests of different ages-soils under a conventionally initial native forest) was examined, and the stages of the postagrogenic transformation of the automorphic soddy-podzolic soils were identified. The differentiation of the former plow horizon into the A1 and A1A2 horizons (according to the differences in the humus content, texture, and acidity) served as the major criterion of the soil transformation. A stage of textural differentiation with clay depletion from the uppermost layer was identified in the soils of the 20- to 60-year-old fallows. The specificity of the postagrogenic transformation of the soils on the slopes was demonstrated. From the methodological point of view, it was important to differentiate between the chronosequences of automorphic and semihydromorphic soils of the leveled interfluves and the soils of the slopes. For this purpose, a series of maps reflecting the history of the land use and the soil cover pattern was analyzed. The cartographic model included the attribute data of the soil surveys, the cartographic sources (a series of historical maps of the land use, topographic maps, remote sensing data, and a digital elevation model), and two base maps: (a) the integral map of the land use and (b) the map of the soil combinations with the separation of the zonal automorphic, semihydromorphic, and erosional soil combinations. This scheme served as a matrix for the organization and analysis of the already available and new materials.     

Remote sensing and GIS for identification of suitable sites for soil and water conservation structures

Formulation of a proper watershed management plan requires reliable and up‐to‐date information about various factors such as morphologic (size and shape of the watershed, drainage parameters, topography), soil and their characteristics, land use, and land cover, etc. that affect the behavior of a watershed. Satellite based remote sensing technology and GIS meets both the requirements of reliability and speed and are ideal tools for generating spatial information needs. In this study, a locale‐specific watershed development plan was generated for the case study area of a small agricultural watershed of Karso, Hazaribagh, India using remote sensing and GIS techniques. Indian Remote Sensing Satellite (IRS‐1C), Linear Imaging Self Scanner (LISS‐III) satellite data along with other datasets, e.g. existing maps and field observation data have been utilized for generating a land use/land cover map and to extract information on morphological parameters (bifurcation ratio, elongation ratio, drainage density, ruggedness number, relief ratio, and circulatory ratio) and other thematic maps which are an essential prerequisites for watershed development. Morphological parameters of subwatersheds were derived to understand its usefulness for surface water development. The conceptual framework for plan and site suitability mapping for soil and water conservation structures is developed and subsequently, these parameters were integrated with other thematic information viz., land use/cover, drainage, slope, and soil in the GIS environment to arrive at a decision regarding a suitable site for having soil and water conservation structures ( nala bund , check dam, and percolation tank) in its place adopting a holistic approach. Copyright © 2010 John Wiley & Sons, Ltd.     

Cartographic Assessment of Soil Diversity in Russia

The paper describes approaches assessing the diversity of soils in Russia, as well as algorithms for quantitatively assessing the differentiation of soil bodies and covers. To assess soil diversity (or the degree of differentiation of parent rock materials into soil bodies and soil covers), two indices have been introduced: the vertical differentiation index (Ird) and the spatial lateral differentiation index (Ild (red)). These indices were computed based on the soil cover structure shown on the Soil Map of the Russian Federation on a scale of 1: 2.5 M within the spatial framework of the Map of Soil-Ecological Zoning of the Russian Federation on a scale of 1: 2.5 M. Based on the data obtained, the most complex soil covers and soil profiles on plains were identified at the boundary of the Boreal and Subboreal geographical belts in the zones of soddy-podzolic soils (umbric albeluvisols/umbric podzols) of the southern taiga and gray forest soils (albic luvisols/luvic greyic phaeozems) of deciduous forests characterized by widespread occurrence of dynamically mature soils, as well as in mountainous soil provinces of the Altai and Caucasus.