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.     

Digital map of salt-affected soils of Khakassia

A new methodological approach aimed at the creation and correction of digital soil maps on the basis of systematized and georeferenced available cartographic and attribute information arranged into a GIS project has been tested. The particular stages and methods of the creation of a digital map of salt-affected soils of Khakassia with the use of GIS technologies in the ArcInfo format are described. All the available cartographic materials, including the Soils of Russia GIS project, digital elevation models, remote sensing data, and analytical data on 82 soil pits (including the authors?? materials and previously published data), have been used for the creation of this new map.     

Experience in digital mapping of soil cover patterns

Methodological problems of large-scale soil mapping with the use of digital mapping technologies are discussed. Two variants of obtaining the maps of soil combinations for a test polygon (30 km²) in the area of soddy-podzolic soils with 996 studied soil pits are described. In the first variant, the initial state of soils at studied points was characterized by the taxonomic name of the soil (at the level of soil subtypes); the probability of occurrence of different subtypes within operation cells of the digital map was estimated, and the most probable soil subtypes were assigned to them. This approach was tested for the first time. In the second variant, the initial state of soils at studied points was described with the help of the grades of ecologically meaningful features of soil morphology; the degree of soil gleying and the degree of soil erosion or aggradation were indicated. The integral digital map represented the areas of different agroecological groups of soil combinations. The maps obtained with the help of these two approaches show a satisfactory agreement with the maps of soil cover patterns compiled by traditional methods earlier.     

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.     

Soil map of the Russian Arctic on a 1 : 1 M scale: Contents and compilation methods

A new soil map of the Russian Arctic on a scale of 1 : 1 M shows the soil cover in the north of Eurasia and on the islands of the Arctic Ocean to the north of 68° N. This map has been developed in a geoinformation system in the vector format with the wide use of remote sensing data. The delineated soil polygons show dominant and accompanying soils and the structure of soil cover patterns with indication of soil associations and soil complexes, the character of parent materials, and the topographic conditions. The map of the soil-geographic zoning of the Russian Arctic developed on the basis of the soil map differs from its earlier analogues in a greater degree of detail. The soil map of the Russian Arctic on a scale of 1 : 1 M displays the most detailed information on the soil cover patterns and can be used for solving various problems related to the exploration and development of this territory. Soil names from the new classification system of Russian soils [10] have been introduced into the legend of the map. New soil information and the use of remote sensing data have made it possible to enlarge the number of soil polygons shown on the map and to correct their boundaries in comparison with previous soil maps of the Russian Arctic.     

Classification of soil types using geographic object-based image analysis and random forests

There is increasing interest in developing automatic procedures to segment landscapes into soil spatial entities that replace conventional, expensive manual procedures for delineating and classifying soils. Geographic object-based image analysis (GEOBIA) partitions remote sensing imagery or digital elevation models into homogeneous image objects based on image segmentation. We used an object-based methodology for the detailed delineation and classification of soil types using digital maps of topography and vegetation as soil covariates, based on the Random Forests (RF) classifier. We compared the object-based method's results with those of a pixel-based classification using the same classifier. We used 18 digital elevation model derivatives and 5 remote sensing indices that were related to vegetation cover and soil. Using 171 soil profiles with their associated environmental variable values, the RF method was used to identify the most important soil type predictors for use in the segmentation process. A stack of raster-geodatasets corresponding to the selected predictors was segmented using a multi-resolution segmentation algorithm, which resulted in homogeneous objects related to soil types. These objects were further classified as soil types using the same method, RF. We also conducted a pixel-based classification using the same classifier and soil profiles, and the resulting maps were assessed in terms of their accuracy using 30% of the soil profiles for validation. We found that GEOBIA was an effective method for soil type mapping, and was superior to the pixel-based approach. The optimized object-based soil map had an overall accuracy of 58%, which was 10% higher than that of the optimized pixel-based map.     

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.     

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.     

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。     

Soils and the soil cover of mountainous tundra and forest landscapes in the Central Khangai of Mongolia

Specific features of the soil formation and soil cover patterns in the mountainous alpine tundra and forest landscapes of the Central Khangai Range are analyzed. It is shown that the specific mucky grayhumus permafrost-affected soils are only formed under larch forests within the tundra-alpine and forest zones. Other soils have a wider geographic area. The morphological, physicochemical, and chemical characteristics of the widespread soils are given. A medium-scale map of the soil cover patterns—soil complexes, combinations, and mosaics—has been developed for the studied area.     

基于GIS和DEM的北京西部山区经济林果适宜性评价

山区地形多变,造成了自然资源立体差异显著,如何定量表示各种农业资源在山区的具体分布状况和建立土地评价模型,是山区资源开发利用和农业结构调整所需要的。该文利用数字高程模型,建立山区日照的地形遮蔽分析模型,在此基础上可进行任一时间、位置的日照时数,辐射等气候因子的地形校正,同时利用统计模型和GISSpline插值技术对温度、降水进行简单的地形校正,与土壤质地图、土壤母质图、土壤厚度图以及土壤pH图,坡度、坡向和海拔高度一起建立了评价因素数据库,从而为土地评价、生态环境分析等领域提供基本参数。以果树适宜性评价为例,利用模糊隶属度函数表征和量化了果树生长生态要求和生态评价因素间的关系,有利于评价专家知识和关系的简化计算。采用简单的等权求和完成多评价因素综合,回避权值确定的主观性等复杂问题。最后以7种有发展潜力的果树利用该评价模型,以门头沟为例,进行了实证研究。除樱桃外,其余6种果树高度适宜的面积都在上千或万公顷以上,因此该区有极大的经济果林发展潜力。该区域现在的果树面积与20世纪90年代初期相比,扩大了3倍多。该评价结果帮助当地政府确立了林果特色经济发展区的农业结构调整政策。通过DEM校正技术,可以较为准确地建立山区生态因子数据库,通过模糊隶属度函数可完成定性和定量的土地评价知识的综合表示,通过等权求和方法,在GIS技术的支持下可以准确快速完成评价过程,从而为山区综合可持续发展服务     

An experience in using the world reference base for soil resources for the soils of western Georgia

New and previously published data on the soils of western Georgia are generalized, and traditional soil names are correlated with the units of the World Reference Base for Soil Resources. It is argued that krasnozems (red ferrallitic soils) can be attributed to the group of Nitisols (the soils characterized by intense weathering (ferralization) and having shiny ped faces in the nitic horizon); yellow and yellow-brown soils (zheltozems), to the group of Luvisols (the soils with relatively high adsorption capacity in the eluvial horizons and with the horizon of the illuvial accumulation of clay); yellow-podzolic (zheltozem-podzolic) soils, to Alisols (slightly acid soils with the low adsorption capacity, poor aggregation of the upper horizons, low-activity (kaolinite) clay, and with the horizon of clay accumulation (argic horizon)); brown forest soils, to Cambisols (the soils with the cambic horizon characterized by some alteration of the lithogenic texture and structure into the pedogenic texture and structure); and mountainous forest-meadow and meadow soils, to Umbrisols (the soils with the dark-colored unsaturated umbric horizon).     

基于GIS的土壤侵蚀数字图接边方法研究

土壤侵蚀宏观调查与制图 ,往往需要多个单位、利用多个图幅同时开展工作 ,图幅之间常常出现属性差异和界线位移的问题。GIS技术的出现 ,实现了图形形状的“无缝接边” ,但属性差异仍然存在。针对这些问题 ,提出土壤侵蚀图接边的程序、原则和数字图的接边方法。为了提高工作效率 ,基于ARC/INFO软件的数字图接边 ,可以根据 2个图幅和对应遥感影像的总数据量 ,选用单编辑层接边、编辑层和背景层切换接边、图幅分割后接边等 3种方式     

珠穆朗玛峰自然保护区地层地貌与植被覆盖变化关系的研究

根据2000—2009年MODIS NDVI/EVIMOD13Q1数据、2004—2007年TM、ETM数据、SRTM 90m分辨率高程数据和国家1∶250万地质图,通过对图像的处理和解译,生成珠穆朗玛峰自然保护区的地质图、植被图、高程图、NDVI—Max变化状况图以及坡度图。在分析了各图间空间分布关系之后得出,珠穆朗玛峰自然保护区内出露最多的岩层为中—上元古界地层和第四系地层,其中在2000—2009年间,中—上元古界地层之上的植被覆盖变化情况要好于第四系地层之上的植被。其原因主要是因为中—上元古界地层主要位于珠峰南坡,该区域地形相对复杂,海拔落差较大,平均坡度也较大;第四系地层主要位于珠峰北坡,这一区域海拔高度较为稳定,地势相对平缓,坡度较小。虽然珠峰南坡的气候条件优于北坡,但地质地貌的因素造成北坡的环境更适合人类居住。因此造成了这两种地层上植被覆盖变化的不同。     

Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed

This research integrates the Revised Universal Soil Loss Equation (RUSLE) with a Geographic Information System (GIS) to model erosion potential for soil conservation planning within the Sierra de Manantlán Biosphere Reserve (SMBR), Mexico. Mountainous topography and a tropical uni-modal precipitation regime characterize this region. These unique climatic and topographic characteristics required a modification of the standard RUSLE factors and their derivation. The resulting RUSLE–GIS model provides a robust soil conservation planning tool readily transferable and accessible to other land managers in similar environments. Future pressure to expand agriculture and grazing operations within the SMBR will unquestionably accentuate the already high rate of soil erosion and resultant sediment loading of watercourses occurring in this region. Until recently there did not exist a reliable or financially viable means to model and map soil erosion within large remote areas. An increase in the reliability and resolution of remote sensing techniques, modifications and advancements in watershed scale soil erosion modelling techniques, and advances in GIS, represent significantly improved tools that can be applied to both monitoring and modelling the effects of land use on soil erosion potential. Data used in this study to generate the RUSLE variables include a Landsat Thematic Mapper image (land cover), digitized topographic and soil maps, and tabular precipitation data. Soil erosion potential was modelled within Zenzontla, a sub-catchment of the Rı́o Ayuquı́la, located in the SMBR, and the results are presented as geo-referenced maps for each of the wet and dry precipitation seasons. These maps confirm that high and extreme areas of soil loss occur within the Zenzontla sub-catchment, and that erosion potential differs significantly between wet and dry seasons.     

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.     

Nitrogen Fertility Island Stability around Prosopis glandulosa Sprouts after Mechanical Shrub Control in a Degraded Grassland

We examined the effects of mechanical chopping to reduce shrub cover for grassland restoration in a semi-desert environment near Douglas, Arizona, USA. Specifically, soils were sampled to determine spatial and treatment differences, after 10 years, in soil-N fertility islands associated with undisturbed honey mesquite shrubs (Prosopis glandulosa Torr. var. glandulosa) compared with resprouted mesquite shrubs. Honey mesquite is the dominant shrub of this degraded grassland community.

One decade after mechanical crushing of shrubs for grassland restoration, soil amino sugar nitrogen (N) values and patterns for resprouted honey mesquite and undisturbed shrubs did not differ from one another according to a repeated measures analysis of variance. However, the concentrations in samples of the surficial 30-cm of soil around undisturbed and resprouted shrubs combined differed statistically at 161 parts per million (ppm) at trunk, 100 ppm midway between trunk and dripline, 78 ppm at the dripline, and 46 ppm beyond the dripline.

The results indicate that soil N fertility remained stable, but with decreasing levels at regular, radial sample points extending from the trunk to beyond the dripline, around mesquite shrubs that resprouted 10 years after mechanical crushing of tops for grassland restoration.     

Quantified evaluation of agricultural soil capability at the local scale: a GIS-assisted case study from Ontario, Canada

Abstract. Rural agricultural areas in southern Ontario, Canada, with potential for aggregate extraction have become a focus of conflict over proposed land use change. Geophysical and soil physical field measurements were used to map soil variation for quantitative land evaluation at the farm level. Apparent electrical conductivity of terrain was shown to be strongly correlated with depth to the groundwater table on two separate test sites. A digital terrain model was used to create thematic maps of the predicted pre-growing season soil water regime by contouring irregularly spaced electromagnetic survey and soil inspection points. Overlay analysis with a geographical information system (GIS) was used to produce an agricultural soil capability map for crop production. Adoption of a larger map scale provided significant refinement in detail over the published Canada Land Inventory soil capability ratings for agriculture, but both showed that Class 2 soils are dominant. The approach can improve the reproducibility of land capability assessments.