Showing papers on "Digital soil mapping published in 2002"

Mapping of several soil properties using DAIS-7915 hyperspectral scanner data - a case study over clayey soils in Israel

Abstract: The data acquired from the hyperspectral airborne sensor DAIS-7915 over Izrael Valley in northern Israel was processed to yield quantitative soil properties maps of organic matter, soil field moisture, soil saturated moisture, and soil salinity. The method adopted for this purpose was the Visible and Near Infrared Analysis (VNIRA) approach, which yields an empirical model for predicting the soil property in question from both wet chemistry and spectral information of a representative set of samples (calibration set). Based on spectral laboratory data that show a significant capability to predict the above soil properties and populations using the VNIRA strategy, the next step was to examine this feasibility under a hyperspectral remote sensing (HSR) domain. After atmospherically rectifying the DAIS-7915 data and omitting noisy bands, the VNIRA routine was performed to yield a prediction equation model for each property, using the reflectance image data. Applying this equation on a pixel-bypixel basis reve...

Prediction of soil properties by digital terrain modelling

Abstract: We investigated two approaches for large-scale analysis and prediction of the spatial distribution of soil properties in an agricultural landscape in the Canadian prairies. The first approach was based on the implementation of nine types of digital terrain models (DTMs) and regression analysis of soil and topographic data. The second approach used a concept of accumulation, transit, and dissipation zones of the landsurface. Soil properties were soil moisture, residual phosphorus, solum thickness, depth to calcium carbonate, and organic carbon content. The dependence of soil properties on topography was supported by correlations for the upper soil layer. However, topographic control of soil moisture and residual phosphorus decreased with depth. Also, correlation coefficients and regression equations describing topographic control of soil moisture and residual phosphorus differed among seasons. This imposes limitations on regression-based predictions of the spatial distribution of soil properties. The prediction of soil property distribution with the concept of accumulation, transit and dissipation zones can be more successful and appropriate than the prediction based on linear regression. The variability in relationships between soil and topographic characteristics with depth may stem from spatial variability in the rate of decline of hydraulic conductivity with depth. Temporal variability in soil–topography relationships occurs because soil properties result from interactions of a variety of pedogenetic factors and processes marked by different temporal variability. In soil studies with digital terrain modelling, there is a need to take into account four types of variability in relations between soil and relief: regional, temporal, depth, and scale.

Mapping the volumetric soil water content of a California vineyard using high-frequency GPR ground wave data

Abstract: Water distribution in the top 1 m of the earth's surface soil layer often controls the success of agricultural crops. In this near-surface zone, large spatial and temporal variations in soil water content are associated with soil heterogeneities, topography, land cover, evapotranspiration, and precipitation. Conventional techniques of measuring soil water content for agricultural purposes—e.g., time domain reflectometry (TDR), neutron probe, or gravimetric techniques, are intrusive and provide information at a point scale only, which is often inadequate for capturing the variations in soil water content with sufficient resolution. Both passive and active remote sensing methods have also been investigated as a tool to provide soil water content in the top 0–5 cm of the subsurface over large spatial areas and in a rapid manner. However, it is still a challenge to obtain information about soil water content from remote sensing data in the presence of a mature crop cover. At the spatial and temporal scales ne...

Identification and Characterization of Pedogeomorphological Processes on a Hillslope

Abstract: This study aims to identify process-response relationships between pedogeomorphological processes and the spatial distribution of soil properties on a hillslope. Thirty-two physical and chemical attributes of 502 soil samples collected from 64 soil profiles on a hillslope in Somerset, UK, were analyzed using an ordination technique. Five factors explaining 80% of the total variation were first identified. Each factor was then regressed with terrain attributes to examine the influence of hillslope geomorphometry on soil distributions. Two-way ANOVA was used to separate the total variance of individual soil properties into vertical and lateral components, and the results were compared with the results of the ordination. The five factors were interpreted as demonstrating the effects of podzolization, nutrient dynamics, Mn leaching, erosion weathering, and soil acidification. The ability to predict soil properties over the landscape using terrain information varies widely among soil properties measured. In general, topsoil properties are better correlated with terrain attributes than subsoil properties. Contemporary pedological and geomorphological processes are most active in the surface horizon, which results in clear lateral differentiation of soil properties. For subsurface soils, only those few soil properties that showed a clear spatial pattern could be successfully modeled using terrain attributes. This research demonstrates that dear differences in the spatial distribution of individual soil properties are mainly determined by differential involvement in in situ pedogenesis and lateral slope processes. Future soil-landscape modeling attempts should pay more attention to the selection of soil properties and the interpretation of statistical results in relation to process-response dynamics.

Application of a mobile electromagnetic sensing system (MESS) to assess cause and management of soil salinization in an irrigated cotton‐growing field

Abstract: . Generally, traditional soil surveys do not adequately account for the spatial variability of soil properties. Maps that are derived using these cursory soil data are likely to contain errors and thus make interpretation and soil management difficult. On the other hand quantitative methods of soil inventory at the field scale involve the design and adoption of sampling regimes and laboratory analysis that are time consuming and costly. In the latter case new technologies are required to efficiently sample and observe the soil in the field. This is particularly the case where soil salinization is prevalent, and detailed quantitative information for determining its cause is required. In this paper, a Mobile Electromagnetic Sensing System (MESS) is described and its application in an irrigated-cotton field, located in the lower Namoi valley in New South Wales, Australia. Results from the EM38 instrument were found to be correlated with the effective cation exchange capacity (r2= 0.81). This was related to variability in soil mineralogy across the field. In addition, differences in soil chemical and textural variables, measured along a transect and adjacent to water storage, were used to identify seepage areas near a water reservoir where soil salinization was evident.

Rainfall-runoff and soil erosion modeling using Remote Sensing and GIS technique — a case study of tons watershed

Abstract: In the present study, the rainfall-runoff relationship is determined using USDA Soil Conservation Service (SCS) method. The coefficient of determination (R2) is 0.99, which indicates a high correlation between rainfall and runoff. The runoff potential map was prepared by assigning individual class weight and scores input map. Annual spatial soil loss estimation was computed using Morgan, Morgan and Finney mathematical model in conjunction with remote sensing and GIS techniques. Higher soil erosion was found to occur in the northern part of the Tons watershed. The soil texture in the affected area is coarse loamy to loamy skeletal and soil detachment is higher. Moreover the land use has open forests, which does not reduce the impact of rainfall. The average soil loss for all the four sub-watersheds was calculated, and it was found that the maximum average soil loss of 24.1 t/ha occurred in the sub-watershed 1.

Using GIS in passive microwave soil moisture mapping and geostatistical analysis

Abstract: Soil moisture is an important hydrologic variable in both natural and agricultural ecosystems. Recent experiments, based on remote sensing data, provided observations of soil moisture distributions at a regional scale. One of the instruments is the Electronically Scanned Thinned Array Radiometer (ESTAR). Deployed on the aircraft, it measures brightness temperature (with the spatial resolution about 400 m) that can be converted into estimates of volumetric soil moisture. The soil moisture retrieval algorithm requires additional data layers (like soil physical temperature, land cover, and soil texture) that come from different sources and have to be combined together in a uniform GIS. The objective of this paper is to report results of the GIS use to map soil surface moisture from passive microwave measurements and to quantify spatial structure of soil moisture distributions. The data were collected across a 10 000 km 2 area in Oklahoma during June and July 1997. The precipitation data and ground measuremen...

The Use of DEM and Satellite Data for Regional Scale Soil Databases

Abstract: New, quantitative methods and data sources for characterizing small scale soil resources have been demonstrated. AVHRR and coarse spatial resolution DEM were designed for mapping large areas of the world quickly and cost effectively. The method combines digital elevation data, “ground truth” information, including the soil taxonomic class for measured soil locations, and a time series of satellite images to form a digital soil database. The results show that using ancillary information such as AVHRR data and DEM derivatives from the national to continental level surveys is among the most promising tools for geographers and soil surveyors. The AVHRR data is often used for land cover studies but its usefulness in soil studies has not yet been proven. This study is a representative example of the usefulness of AVHRR data in characterizing the soil-forming environment and delineating soil patterns, particularly when integrated with other data for describing the soil landscape, such as the DEM, slope, curvatur...

Knowledge Based Soil Attribute Mapping In GIS: The Expector Method

Abstract: EXPECTOR is a method of combining data and ‘expert’ knowledge within a Geographic Information System to provide information on the occurrence of spatially distributed attributes. It was developed to predict soil property values from spatially variable input data. Although initially developed to provide soil surveyors with a quantitative soil mapping method, it also has applications in land evaluation, land capability assessment, geological mapping and in precision agriculture. It operates on the basis that the state of a particular property, which may be difficult to measure directly, can be inferred from other (more measurable) entities and a knowledge of their inter-relationships. The method has been implemented as a stand-alone ‘Knowledge Editing’ module for the PC that can be linked to raster GIS packages. This paper describes the basis of the method and illustrates its use with an example describing the production of a surface clay content map for a small catchment in south-western Western Australia.

Spatio-temporal modelling of broad scale heterogeneity in soil moisture content : a basis for an ecologically meaningful classification of soil landscapes

Abstract: We describe the classification of landscapes characterised bymineral soil using a model that calculates soil moisture availability on amonthly basis. Scotland is used as a case study area. The model uses potentialsoil moisture deficit, estimated using broad scale (40 × 40 km)climate patterns, in conjunction with meteorological station measurements toobtain finer scale values of climatic soil moisture deficit. Point estimates ofsoil available water are obtained for soil characteristics using appropriatepedotransfer functions, and geostatistical techniques are used to upscale theresults and interpolate to a 1-km grid. Known heterogeneityin soil physical characteristics is used to provide local corrections to thepotential soil moisture deficit, estimated using the climatic variables above.Temporal profiles of monthly water content are modelled for each1-km location and classified into six classes usingunsupervised cluster analysis. The spatial distribution of these classesreflects regional variations in the availability of moisture and energy, onwhich finer-grained topographic patterns are superimposed. In the case study,the broad scale spatial heterogeneity of heathlands and grasslands on mineralsoils in Scotland is shown to be strongly related to the soil moistureclassification. The results can be used in studies investigating the patternsofdistribution of communities at the landscape and regional scale.

Importance of local soil erodibility measurements in soil loss prediction

Abstract: Soil is a non-renewable natural resource. An accurate estimate of soil loss is essential for making agricultural policy decisions and for planning land use at all scales from farm to national levels. A wide range of erosion models, most of them combined with GIS and varying in purpose and details, are available for predicting soil loss. The Universal Soil Loss Equation (USLE) consists of statistical summaries of annual average soil loss data from plot studies in the United States. The equation has been worked out on the basis of the data of over 10,000 plot-years collected on erosion plots in the USA. However, the basic problem is the possibility of transferring empirical relations from the climatic and soil conditions in which they are measured into other geographical areas. This paper investigates the possibility of calculating the soil erodibility factor of the USLE with rainfall simulations and its importance in soil loss prediction.

The Soil Information System

Abstract: The collection and analysis of soil information in an efficient and effective manner at a field or sitespecific scale is a scientific and technical challenge. Resource managers often have access to highresolution airborne and spaceborne imagery or other landscape attributes, but detailed soil and topographic information has become a major limiting factor for high intensity land use and management practices. The mapping of soil at a scale larger than 1:12,000 requires the collection of soil samples, their laboratory analysis, documentation, and association with landscape position for the creation of maps. Often, additional excursions to the field are necessary to supplement previously collected data. This iterative procedure is time consuming, expensive, and often subjective. The amount of data obtained is not sufficient to characterize soil properties and their variability at a field or site-specific scale. A real-time, mobile Soil Information System SIS) is being developed to improve the process of performing high intensity soil surveys and site investigations.

Soil Classification and Soil Research

Abstract: Since the middle of the 20th century, society has been generous in funding research, and this was a period when almost every field of scientific endeavor saw great advances. The development of new research techniques and technologies greatly boosted research outputs during this period. “Classification is a basic requirement of all science and needs to be revised periodically as knowledge increases”. This is the case for all natural systems. For natural sciences, classification “serves as a framework for organizing our knowledge of natural systems including soils and provides a means of communication among scientists, and between scientists and users of the land”. Information on properties of the soil is used to structure a soil classification system. Scientific research from other fields within Soil Sciences, such as Soil Physics, Soil Chemistry, and Soil Mineralogy, provides the basis for the identification and selection of appropriate diagnostic soil properties and attributes for classification, especially for the development of meaningful class limits.

On computerized soil mapping

Abstract: Experimental results and long-term experience in solving some methodological problems of soil mapping are considered. These problems are related to the appropriate choice of a topographic base, materials of aerial and-satellite survey, and the necessary number of pits for compilation of adequate soil maps as a function of their scale and designation. It is argued that traditional techniques of soil mapping are also of great importance for creating computerized soil maps and data banks for a geoinformation system. Methodological errors in computerized mapping can lead to compilation of inadequate soil maps and, hence, erroneous recommendations on soil management.

Assessment of China Potential Soil and Water Loss Based on GIS

Abstract: China is one of the suffering severe soil erosion in the word, and soil loss becomes the important social and environment issues in socialeconomy sustainable development. Therefore, it is necessary for scientists to evaluate soil and water loss in countrywide. Based on analysis of soil erosion processing and the environment characters, factors and variables, basic unit map and database potential erosion assessment, evaluation of potential soil erosion in China has been researched in digital map platform. The main results are:(1)Soil and water loss type and environment characters in China are analyzed; based on remote sensing interpret and geographical thematic mapping, using digital cartography method, soil loss typezone in China is mapped, which build a unified base for integration of multiple data and mapping of soil loss assessing.(2)Based on the newest research on assessment of soil and water loss in home and abroad, according to soil and water loss and environment characters in China, variable of China potential soil and water loss assessing are developed. The involved data are collected and integrated, a spatial database of China potential soil and water loss assessing has been built.(3)Based on the spatial database of China potential soil and water loss assessing, main factors affecting potential soil and water loss, including meteorology, topography and soil, are analyzed and mapped. Comprehensive assessment and mapping of China potential soil and water loss has been completed using expert knowledge.(4)Based on the GIS, integration of multiple data was initially programmed, which applied a theoretic and technique support for rapid integration of multiple spatial data and effective management in assessment mapping of regional soil and water loss. 

The Importance and Value of Soil Information

Abstract: Soil information has been used for centuries to manage and understand crop growth. Growers have used soil information to guide their decisions since the first plow was put in the ground. The quality, quantity, type, and location of soil information needed for site-specific management varies as a function of intended use. Soil maps must be accurate both in terms of information and location if they are to be used in agriculture. The natural heterogeneity of most soils means that accurate characterization requires a large number of observations. The high cost associated with collecting soil information at a large scale (high resolution) using standard tools and techniques is usually cost and time prohibitive. New technology and methodologies can collect information at a rate, resolution, and format that makes it feasible to map soil at a scale useful for variable rate technology, crop and hydrological models, nutrient and water budgeting, and other precision monitoring and management applications.

Knowledge Classfication on Soil Automatic Mapping

Abstract: The existing soil maps reflect the mental models developed by soil surveyors, and the association between soil map units and other environmental spatial data can be remodeled to infer formal survey rules. Then these inferred rules can be applied to reinterpreted the soil type for the same area or another similar area. Based on the existing soil map, geology map, landuse, DEM and its derived topographic attributes, bi temporal Landsat TM imageries, classification trees modeling was used to extract soil mapping rules of Longyou County in Zhejiang Province, China. The result showed that these regional soil landscape rules achieved comparable success to predicting most of soil types of study area.

Soil Survey Scale and its Effect on Land use Planning

Abstract: Soil survey maps compiled at a variety of scales (1:5,000; 1:100,000; 1:500,000) were incorporated into a GIS and compared in terms of the number of soil classes (and discrete soil units belonging ...

Mapping construction of soil variability within the landscape

Abstract: The research aimed to construct mapping soil variability within the landscape. The research was located in Central Lampung (308 ha). The survey type was detailed using topographic maps (scales of 1:5,000) and the aerial photo interpretations. The soil samples were performed by soil pits and borings for whole survey area (1 composite sample/ha), classified and analyzed. The balancing methods used transect diagrams, delineated soil bodies and area point statistics. The research resulted that the aerial photo interpretation was a very useful method to delineate soil units on the map. A combination of aerial imagery, topographical maps and field observations provide the most effective approach for soil mapping in complex landscapes with simple soil patterns. Although the soil sampling was carried out relatively systematic according to relief form and the driving lanes of tractors, there was some agreement between point statistics and map data. The difference between both methods was maximally 3 %. The result combination from both methods shows that 60 % of the landscape was classified as eroded, 35 % as normal and 5 % as colluviated. There was no balance of erosion and onsite sedimentation. Keywords : Construction, landscape, mapping, soil variability