Showing papers on "Digital soil mapping published in 2001"

Soil Mapping Using GIS, Expert Knowledge, and Fuzzy Logic

Abstract: A geographical information system (GIS) or expert knowledge-based fuzzy soil inference scheme (soil-land inference model, SoLIM) is described. The scheme consists of three major components: (i) a model employing a similarity representation of soils, (ii) a set of inference techniques for deriving the similarity representation, and (iii) use of the similarity representation. The similarity representation allows the soil landscape to be considered as a continuum, and thereby overcomes the generalization of soils in conventional soil mapping. The set of inference techniques is based on the soil factor equation and the soil-landscape model. The soil-landscape concept contends that if one knows the relationships between each soil and its environment for an area, then one is able to infer what soil might be at each location on the landscape by assessing the environmental conditions at that point. Under the SoLIM, soil environmental conditions over an area are characterized using GIS or remote sensing techniques. The relationships between soils and their formative environmental conditions are extracted from local soil experts or from field observations using a set of artificial intelligence techniques. The characterized environmental conditions are then combined with the extracted relationships to derive a similarity representation of soils over an area. It is demonstrated through two case studies that the SoLIM for soil survey has many advantages over the conventional soil survey approach. Soil information products derived through the SoLIM are of high quality in terms of both level of spatial detail and degree of attribute accuracy. In addition, the scheme shows promise for improving the efficiency of soil survey and subsequent updates through reducing time and costs of conducting a survey. However, the degree of success of the SoLIM highly depends on the availability and quality of environmental data, and the quality of knowledge on soil-environmental relationships over the study area.

Soil resources mapping: A remote sensing perspective

Abstract: Timely and reliable information on soils with respect to their nature, extent, spatial distribution, and potential and limitations/hazards, namely soil erosion by water and wind, soil salinity and/ or alkalinity, wetness, soil compaction, etc., is very crucial for optimal utilization of available natural resources on a sustained basis. Soil surveys, which hitherto have been conducted through conventional approach, provide such information. By providing synoptic coverage of the earth's surface at regular intervals remote sensing has augmented the efficiency of soil survey programmes. Beginning with the Landsat‐MSS data in early 1970s, spaceborne multispectral measurements from a variety of sensors, namely Thematic Mapper (TM), SPOT Multi Linear Array (MLA), Panchromatic Linear Array (PLA), Indian Remote Sensing Satellite (IRS) Linear Imaging Self‐scanning Sensor (LISS‐I, ‐II and ‐III), Wide Field Sensor (WiFS) and Panchromatic (PAN) sensor have been extensively used for carrying out soil surveys of varying...

Profile cone penetrometer data used to distinguish between soil materials

Abstract: In young glaciated landscapes the variability of soil materials imparts a major control on crop growth and yield and environmental quality associated with production agriculture. Two common soil materials found on these glaciated landscapes are glacial till and reworked loess. Soil materials can be characterized by a combination of physical and morphological soil attributes. We hypothesized that penetration resistance is the response signal to a complex of multiple soil attributes and can be used as an integrating indicator to map soil materials. Our objective was to test the ability of a profile cone penetrometer to map soil materials at landscape-scale. The study site was located in southern Wisconsin, USA, on soils developed in reworked loess material overlying glacial till, which are classified as Typic or Mollic Hapludalfs and Typic Argiudolls. We collected a dense data set of cone index profiles from a 2.73 ha area on a 10 m grid up to depths of 1.3 m. Additionally, we collected soil cores randomly at 21 penetration locations and analyzed these by layer for texture, bulk density, and water content. We utilized point elevation data collected with a differential global positioning system to create a digital elevation model and derive slope and compound topographic index to subdivide the study area into landform element classes. We used expert knowledge to characterize soil materials and subsequently measured soil attributes to identify soil materials. A hierarchical cluster analysis was used to group cone index profiles. Combining the sparse soil material data with the dense cone index and landform element data resulted in soil material information covering the entire study area. The spatial distribution of soil materials was visualized using a three-dimensional soil layer model. The proposed method is associated with large uncertainties in some areas and can be recommended only for coarse mapping of contrasting soil materials such as glacial till and reworked loess at landscape-scale, when used in combination with landform element data.

Characteristics of spatial variability of soil thickness in China

Abstract: The spatial variability of soil properties is very important to agriculture, soil quality assessment, sustainable development and global change research Geostatistics is a means of spatial variability, spatial structures and spatial prediction that is used widely for soil properties overseas However, this kind of research was started relatively late in China On the other hand, our research on soils paid more attention to chemical and biological properties than to physical properties This paper aimed to study spatial distribution characteristics of soil depth in China, especially that of physical ones using Geostatistics and Geographic Information System, and provide raster data for global change research This paper built the China Soil Geographic Database which includes soil physical and chemical properties database and 1 627 soil samplers database by data from the second national soil surveys and primarily studied the spatial distribution characteristics of the thickness of soil layer using GIS and Geostatistics The spatial distribution features were quantitatively described by semi variogram Based on the semi variogram, the maps illustrating soil thickness are made by ordinary Kriging with cell of 30km×30km Soil thickness being studied has relatively good spatial structures, and their experimental semi variogram could be fitted by exponential model with nuggets And optimal interpolation could be done depended on the semi variogram features Basically, the experimental semi variogram of soil properties being studied increases with increasing lag distance to approach or attain a maximum The range of soil thickness semi variogram is up to 680km, which is consistent with average distances among patches with the same feature in the distribution maps This indicates the significant trend known as “drift” in distribution maps

Remote sensing in the recognition and mapping of tropical soils developed on topographic sequences

Abstract: The authors compare information on soil maps of the Sao Paulo region, Brazil (obtained by four different methodologies) with ground truth data and a preexisting semi-detailed soil map. The methodologies for compiling the new soil maps included: (1) conventional (field) cartographic methods; (2) air photo interpretation; (3) automated processing of radiometric data; and (4) use of radiometric data in conjunction with air photo analysis and planimetric/altimetric observations. The remote sensing methodologies produced soil maps similar to the detailed map (1) and substantially better than the pre-existing semi-detailed one. The utility of these techniques to soil surveys at rather large scales, and for tropical soil mapping in general, is assessed.

State and Transition Ecosystem Models⎯Application to Soil Survey and Dynamic Soil Properties Databases

Abstract: State and transition models. Arid and semiarid rangelands are hypothesized to function as nonequilibrium systems (Westoby et al. 1989). Models that capture these nonequilibrium dynamics at the site (groups of similar soil map units; sensu, Shiflet 1973) level are called state and transition models (STMs). Although the application of STMs is at an early stage, relatively large gains in understanding rangeland function are being realized by implementing this new approach. Developing an information system to manage this knowledge will require the reinterpretation of existing data and new observations and experiments within a precisely defined structure if we are to make progress in providing better quality information for land management decisions.

Integrating multi-source remote sensing data for soil mapping in Victoria

Abstract: Mapping of soils at paddock level is being undertaken at 3 selected sites in Victoria by using remote sensing data from a variety of sources. The three sites represent different agricultural practices in high and low rainfall zones across Victoria. The project work is divided into 4 stages: (1) soil analysis at sample points, (2) analysis and integration of remotely sensed information, (3) exploring relationships between soil properties and remotely sensed variables, and (4) extrapolating soil mapping to a wider area using relationships established at stage 3. Detailed soil surveys were initially conducted to characterise the soils of each site at the sub-paddock scale to obtain information on the physical and chemical properties of the soil, particularly those relating to limiting factors such as salinity, toxicity (boron, aluminium), acidity, alkalinity and soil moisture regimes. To achieve this, exploratory soil cores were collected across the site from locations representing different soil types and landform patterns. Soil pits (ranging between 4-10 per site) were then dug. Chemical and physical analyses were also completed for each pit to assist in understanding the soil characteristics across each site and down the soil profile. This site specific soil information is then used to aid soil feature extraction from the remotely sensed data sets. High resolution remote sensing information acquired for this study includes airborne synthetic aperture radar (PACRIM 2 AIRSAR), Landsat 7 ETM+, conductivity measurements from EM38 and EM31, and ground penetrating radar data sets. All data sets are integrated into raster format. The sets of remotely sensed data are treated as explanatory variables with soil properties as response variables. The integrated approach enables a number of space, air and ground borne data sets to be evaluated in terms of their potential to be able to identify soil components both on the surface and at depth. The differences in the resolution of these sensors also allow evaluation on the type of soil information that can be obtained at varying scales, from the sub-paddock to catchment.

Remote Sensing Study on Soil Erosion Backed by GIS --Take Soil Erosion in Hubei Province for Example

Abstract: The research of soil erosion is a core and focus point for study on protection of environment.In order to study soil erosion,the technologies of remote sensing and geographical information system were used to analyze the spatial distribution of soil erosion.Take soil erosion in Hubei province for example,the mathematical methodology for study on soil erosion was explored and developed.And,the quantitative approach and track of study on soil erosion were given in this paper.

Soil resource mapping for precision farming using remote sensing

Abstract: Multispectral airborne remote sensing was used to improve the inventory of soil heterogeneity at the sub-field level. A bioindicative model was developed, based on cause-and-effect relationships of the soil-plant-sensor system. The spectral information was transformed into soil information using bioindicative transfer functions. This procedure enables quantitatively the spatial detection of the limiting soil quality e.g. the plant available water capacity of the root zone. Remote sensing based maps as developed in this study will support farmers and agricultural advisors to practice precision farming using site-specific management.

Categorical Model of Estimating Soil Erosion Based on GIS ——A Case Study in Xihanshui Watershed

Abstract: Based on factor analysis of soil erosion, a categorical model of estimating soil erosion based on GIS has been proposed The key to this model is to set up the relationship between soil erosion and driven factors, such as rainfall, terrain, cleuch density, percentage of vegetation coverage, soil texture and so on It so happened that Geographical Information Systems provide the functions to manage manipulate those datasets Case study of Xihanshui watershed showed that the categorical model based on GIS has the advantage of quantitative estimation of soil erosion,can be used to monitor soil erosion dynamically

Soil moisture mapping with passive microwave imagery and geostatistical analysis.

Abstract: Remote sensing, and in particular passive microwave, has a great potential for providing areal estimates of soil moisture. It can be implemented with aircraft-based sensors as described here. The result of the measurements, the brightness temperature images, can be converted into volumetric soil moisture maps using additional environmental information. These maps display information on soil moisture distribution over space and time. Semi-variogram analysis was performed to investigate spatial variation of soil moisture and its scale dependence with the environmental features. Analysis revealed a dependency of soil moisture distribution at two scales. On the regional scale, rainfall is the dominant factor influencing soil moisture distribution. On the local scale, soil texture dominates.

Spatial Patterns of Soil Seed-Bank Related to Some Soil Properties

Abstract: Precision agriculture requires new approaches to research that are designed explicitly to improve understanding of the complex interactions among multiple factors affecting crop growth and farm decision making. The variability of weed distribution is related to several pedoclimatic and agronomic factors. The strategy to control the most competitive weeds, able to significantly reduce crop production, should be based on the knowledge of both weed biology and spatial- temporal variation. To understand the infestation dynamics, a georeferred data-set of soil properties coupled with the so called seed-bank, which provides information on potential occurrence of different types of weeds, was used in an integrated analysis. In the present work Principal Component Analysis (PCA) and Indicator Kriging (IK) were applied to relate soil characteristics with the distribution of broad-leaf weeds and grasses.

Possibilities of Geoinformation Technologies in Mapping and Management of Soils in Croatia

Abstract: SUMMARY The paper mentions some major issues considering the application of geoinformation technologies in mapping and management of soils in Croatia. Results taken from two independent projects are described. In one, use of DGPS receivers and remote sensing in soil mapping is described and in other, use of GIS tools and SGDB for decision making. GPS has proven to be efficient and powerful tool for mapping soils and navigation in the field. The accuracy of positioning (95% probability radius) ranged from 5 m for DGPS with averaging to 19.1 m for single fix DGPS and 144 m for single fix uncorrected GPS method. Landsat TM image was used to map organic matter content (%) ranging from 0 to 15% with precision of ±4.6%. GIS software was used to derive interpretation maps such as suitability for crop production, vineyards and suggest measures for the improvements and protection of soil. To objectively evaluate use of different methods of positioning, 95% probability error radius should be used. Use of the remote sensing and GIS tools is also a promising improvement. A GIS Soil Information System - soil map linked with the database of soil properties is an objective tool to come to decisions on land use. The conventional mapping units (Soil mapping units) can be replaced with the raster-based maps of single soil properties of fine grain of detail (30x30m) by using remote sensing and terrain data. The applications of these systems can bring management of soils in Croatia to a finer and more objective level – precision management.