Soil Association Map Research Articles

Evaluasi Kesesuaian Lahan Untuk Tanaman Durian Menggunakan Metode Matching

Land suitability evaluation is a process of assessing the potential of land for a particular use, whether in agriculture, plantation, tourism, land conservation, or other types of use. This study aims to determine the land suitability class for durian plants in Aranio District and determine the inhibiting factors on the land using the matching method. The population in this study was 12 land units and each unit was taken 2 samples. Land units are obtained from overlay maps of landforms, slope maps, geological maps, soil association maps, and land use maps. The results showed that the land in Aranio District was included in the suitability class S2 (moderately suitable) with an area of 15069.68 hectares or 33.13%, S3 (marginally suitable) with an area of 1485.78 hectares or 3.27%, and N1 (not current suitable) with an area of 3980.03 hectares or 8.75%. The limiting factor is slope, erosion hazard, pH, soil depth, surface rock, alkaline saturation, flood hazard, phosphate, K2O, and N-Total. The villages in the Aranio sub-district are used to develop durian plants because they have land suitability classes of S2 and the use of shrubs, fields, and mixed gardens are above 50%, namely Tiwingan Baru and Tiwingan Lama villages.

Mapping Soil Erosion Sensitive Areas in Organic Matter Amended Soil Associations in the Ntabelanga area, Eastern Cape Province, South Africa

The study aims to map areas sensitive to erosion by water and rainfall erosivity after addition of organic matter (OM) in highly unstable soils. A soil association map was created using digital soil mapping methodology. Soil samples from six soil associations were incubated and analysed for several soil erodibility measures and inferred to the soil association map. Soil stabilization against soil erosion by use of OM was evaluated for 30 weeks under two simulated rainstorms, intermittent rainstorms (IR) and single rainstorm (SR). Rainfall erosivity (R-factor) was calculated from theduration of a rainstorm and the total amount of rainfall received under rainfall simulations. Erodibility factor (K-factor) was estimated using the soil OM content and texture. Largest area (40%) was covered by shallow soils and K-factor range of 0.0693-0.0778 t.ha.hha-1MJ-1mm-1. Largest (60.2%) area had a structural stability index of 0.8 and 42.7% of the area was covered by a dispersion ratio value range of 0.65-0.70. The area size with erosion rates of > 15 t/ha/yr was drastically reduced from 1 to 8 weeks after OM application thereafter gradually increased under both IR and SR. Soil erosion rates of < 5 t-1 ha-1 yr-1 and > 15 t-1 ha-1 yr-1 were most and least observed respectively under both storms. R-factor was higher under IR than SR and the smallest areas with soil erosion rates of > 15 t-1 ha-1 yr-1 contributed most to the lost soil. Organic matter confers soil resistance to erosion up to a certain period before losing its effectiveness. The study provided first assessment of erosion dynamics, basis for identifying conservation priorities which may be applicable in similar areas.
 Keywords: Erosivity, planning, rainstorm, soil conservation, soil degradation

A pedogenetic method for land type survey disaggregation into soil association maps

There is an increasing demand worldwide for spatial soil information. Unfortunately, gathering new soil data is expensive, leading to a focus on extracting detailed information from existing datasets. The most extensive dataset in South Africa is that of the land type survey. This paper proposes a method of disaggregating land type inventories into a soil association map, using a pedogenetic approach. The method is illustrated by the disaggregation of land types in landscapes with simple (Cathedral Peak) and complex (Ntabelanga) soil distribution patterns. The maps were validated with independent datasets. The Cathedral Peak map was produced with a Kappa value of 0.66, indicating a substantial agreement with reality, but the Ntabelanga soil association map only achieved a Kappa value of 0.20, indicating a slight agreement with reality. These values, comparable to results obtained using the automated disaggregated algorithm DSMART, show that the method is useful in landscapes with a simple soil distribution pattern, but not in areas where there is a complex soil distribution pattern. The pedogenetic method would be useful to soil surveyors with a moderate level of GIS skills and access to pedogenetic knowledge of the study area. Sites consisting of numerous land types are better analysed by the automated DSMART method.

Machine learning digital soil mapping to inform gully erosion mitigation measures in the Eastern Cape, South Africa

Soil erosion is probably the most common form of land degradation, leading to on and off site detrimental effects, such as an increase in river sediment load which have been shown to drastically decrease dam storage capacity. The South African Government has announced plans to build two large dams within an area with a very high erosion rate, thus necessitating soil erosion mitigation efforts. These efforts should consider the mechanism of gully formation, as it determines which conservation measures could be used. With overland flow gullies the kinetic energy of flowing water needs to be curbed, while gullies form by piping in dispersive soils where free water could accumulate. This paper describes how a soil association map for the quarternary catchments T35DE was created with digital soil mapping methods, in order to indicate areas where piping could occur. Soil were described and classified at 600 locations determined with the conditioned Latin hypercube sampling method, within a 500 m buffer around the available road network. This soil database was then used with the multinomial logistic regression algorithm to create an initial soil association map with seven soil associations, based on their soil erosion properties. Additionally, a soil depth map was created using the cubist algorithm. The soil association map was then created again, but with the soil depth map added as an additional covariate. Including the soil depth map as a covariate improved the accuracy (68% vs 64%) and level of detail of the final soil association map, even though the soil depth map was a poor reflection of reality. The final soil association map was compared to the best current available spatial soil dataset, and found to contain 123 times more detail. Superimposing the gully extent of the soil association map confirmed that the planosols are the most susceptible to gully erosion and mitigation efforts should avoid increasing free water in the subsoil on the planosol area, and the as yet ungullied planosol should be prioritized as it could become a hotspot for gully formation if it degrades.

Digital soil mapping approaches to address real world problems in southern Africa

Soil spatial information is increasingly sought after for various agricultural, environmental and developmental uses, but is often unavailable, also in southern Africa. Digital soil mapping (DSM) can provide the tools to fill this gap, but the uptake in developing countries have been slow. Local research is required to adapt internationally developed methodologies to unique local situations. In southern Africa DSM research have reached the level where DSM tools can now be used in commercial soil related projects. Several DSM case studies, conducted across Southern Africa, have provided the platform from which this work is presented. These case studies were done for a range of situations, including environmental settings with variations, size, data availability and aim of the soil map. Three different approaches have been identified as useful DSM tools, with varying costs and level of information it provides. Land type disaggregation is the cheapest, as it is largely desktop based, but can only produce small scale soil association maps. The expert knowledge approach is the most widely used commercially. Large scale soil associations can be mapped, and 30 soil observations per homogeneous soil distribution area are required. Machine learning methods can map soil properties, but rely on large data sources, consequently it is the costliest. Machine learning is therefore used to produce large scale maps large areas, where cost can be diluted. This paper gives an outline of DSM research in southern Africa and presents a case study of each of the DSM approaches, showing the methodology, potential and limitations of the approach within a commercial context. Specific case studies presented in this paper include the agricultural assessment of 166 km of pipeline for a water distribution project in Limpopo (land type disaggregation), a land capability assessment of a 15,000 ha open coal mining area in Mozambique (expert knowledge) and hydropedological mapping in Johannesburg (machine learning).

Soil map and 3D virtual tour using a database of soil-forming factors

Soils are non-renewable resources and therefore must be conserved, particularly in protected natural areas. Correct and rational planning of human activities in fragile conservation landscapes should be based on detailed studies of soil-forming factors, such as climate, geology (lithology and surficial deposits), geomorphology (topography, morphology, slope and hydrology), biology (vegetation and human activity) and time and their relationships with the landscape and landforms. This study analyses the geospatial distribution of different soil units in the natural areas of “Las Batuecas-Sierra de Francia” and “Quilamas” and is based on a soil sampling field programme and textural analyses that resulted in soil association maps, dominant soil maps and toposequences that could be extrapolated to natural resource and environmental problems (natural and/or human). In this study, a set of GIS-based digital maps was developed to illustrate the physical attributes of these natural areas. In particular, georeferencing of the various soil-forming factors was used to generate a specific soil map for each natural area and to create a geospatial database, including fact sheets and photographs, of characteristic soil profiles. This soil information was converted into the “kmz” format to geospatially visualise the various soil units in 3D virtual tours using viewers, such as Google Earth, to obtain information regarding the spatial referencing and elevation of the area, interact with the 3D modelling of the tour in Google Earth, overlay the soil map on the orthophoto, activate or deactivate the visible layers, modify the spatial resolution of every point by zooming in or out and obtain the numeric and graphical information for every stop. This soil map can be used in multidisciplinary approaches by adding other thematic layers: lithology, geomorphology, topography, morphology, slope, hydrology, vegetation, et cetera, which would facilitate decision-making by managers and directors of nature areas/parks.

Disaggregation of land types using terrain analysis, expert knowledge and GIS methods

Soil maps’ value is increasingly recognised for enabling the optimal management of ecosystems. Digital soil mapping (DSM) can overcome the cost constraints of traditional mapping methods, but requires local area-specific research. As South Africa is blessed with the land type survey, local DSM research should start with the disaggregation of this resource. This paper shows how two land types (Ea34 and Ca11) near Newcastle in KwaZulu-Natal were disaggregated using DSM methods. A series of soil maps were created. With each map, more information was incorporated when creating the map. For Map 1 only the land type inventory and terrain analysis were used. A reconnaissance field visit with the land type surveyor was added for the second map. Field work and a simplified soil association legend improved the map accuracy for Maps 3 and 4, which were created using 30% and 60%, respectively, of the observation points as training data. The accuracy of the maps increased when more information was utilised. Map 1 reached an accuracy of 35%, whereas Map 4 achieved a commendable accuracy of 67%. Thus DSM methods can be used to disaggregate land types into accurate soil association maps. Emerging principles include that lithology rather than hard geology should be used as parent material input, field work is critical to obtain acceptable results, and simplifying the map legend into soil associations improves the accuracy of the map.

Aquifer Sensitivity to Pesticide Leaching: Testing a Soils and Hydrogeologic Index Method

AbstractFor years, researchers have sought index and other methods to predict aquifer sensitivity and vulnerability to nonpoint pesticide contamination. In 1995, an index method and map were developed to define aquifer sensitivity to pesticide leaching based on a combination of soil and hydrogeologic factors. The soil factor incorporated three soil properties: hydraulic conductivity, amount of organic matter within individual soil layers, and drainage class. These properties were obtained from a digital soil association map. The hydrogeologic factor was depth to uppermost aquifer material. To test this index method, a shallow ground water monitoring well network was designed, installed, and sampled in Illinois. The monitoring wells had a median depth of 7.6 m and were located adjacent to corn and soybean fields where the only known sources of pesticides were those used in normal agricultural production. From September 1998 through February 2001, 159 monitoring wells were sampled for 14 pesticides but no pesticide metabolites. Samples were collected and analyzed to assess the distribution of pesticide occurrence across three units of aquifer sensitivity. Pesticides were detected in 18% of all samples and nearly uniformly from samples from the three units of aquifer sensitivity. The new index method did not predict pesticide occurrence because occurrence was not dependent on the combined soil and hydrogeologic factors. However, pesticide occurrence was dependent on the tested hydrogeologic factor and was three times higher in areas where the depth to the uppermost aquifer was <6 m than in areas where the depth to the uppermost aquifer was 6 to <15 m.

Sensitivity of the SWAT model to the soil and land use data parametrisation: a case study in the Thyle catchment, Belgium

The sensitivity of the distributed hydrological SWAT model to the pre-processing of soil and land use data was tested for modelling rainfall-runoff processes in the Thyle catchment in Belgium. To analyse this sensitivity, 32 different soil and land use parameterisation scheme were generated and evaluated. The soil input data sources were a generalised soil association map at a scale of 1:500,000, a detailed soil map at a scale of 1:25,000 and the soil profile analytical database AARDEWERK. These soil data were combined with a detailed and a generalised land use map. The results suggest that the SWAT model is extremely sensitive to the quality of the soil and land use data and the adopted pre-processing procedures of the geographically distributed data. The resolution and fragmentation of the original map objects are significantly affected by the internal aggregation procedures of the SWAT model. The catchment size threshold value (CSTV) is thereby a key parameter controlling the internal aggregation procedure in the model. It is shown that a parabolic function characterises the relationship between the CSTV and the hydrological modelling performance of the uncalibrated model, suggesting that optimal uncalibrated modelling results are not obtained when the CSTV is minimised. The hydrological response of the SWAT model to the calculated soil properties is significant. Therefore preference should be given to the calculation of the derived hydrologic soil properties prior to averaging of the profile data. Finally some general guidelines are suggested for parameterising soil and land use in the SWAT model application.

IMPORTANCE OF SOIL MAP DETAIL IN PREDICTING PESTICIDE MOBILITY IN TERRACE SOILS1

Soil surveys can be used to group soils according to taxonomic classification and potential for pesticide transport, but estimation of pesticide mobility may be limited by inclusions of dissimilar soils within map units. Estimation of pesticide mobility may also be affected by the level of detail of soil maps as dictated by the needs and purposes of the soil survey. The objective of this research was to determine the most appropriate level of soil map detail for predicting pesticide mobility in terrace soils. Soil cores were collected on river terrace landscape positions in southwestern, south-central, and southeastern Nebraska. Soil thin-layer chromotography was used to measure the relative mobility (R f ) of benchmark pesticides (alachlor, atrazine, carbofuran, and dicamba) in samples from each core. Composite R f values were calculated for each soil pedon to compare pesticide mobility among map units and sample areas. Mobility was affected more by pesticide solubility and K 0C , and by the general physical and chemical properties of parent materials at the sample sites, than by specific soil type. The research suggests that soil association maps, comprised of map units that are groupings of soil series associated geographically in a repeating pattern, may be the most appropriate for predicting pesticide mobility in terrace soils.

Colour additive viewing techniques for small-scale soil mapping in an area of Karimnagar district, Andhra Pradesh, India

Abstract Multi-spectral imagery from Landsat relating to the Karimnagar district of Andhra Pradesh, in South India was analysed using colour additive viewing techniques. The results were correlated with an existing soil association map prepared from aerial photo-interpretation with adequate ground truth. The four landscapes and their subdivisions that were identified on the soil map also could be identified on the Landsat map. An overall classification performance of 83·9, 82·4, 80·9 and 95·7 percent respectively has been achieved for rugged (R), undulating hummocky (U), very gently sloping (V) and river alluvium (A) landscapes. The best class performance was in the order of 95·7, 97·6, 81.8 and 95·7 percent and that of the lowest class performance of 50·5, 57·3, 70·1 and 95·7 percent for R, U, V and A landscapes, respectively. The overall combined performance of 85·7 percent has been achieved with respect to soilscape boundary delineations for all the four landscapes. The Student's t-test of significance revealed that for units R4, U4 and V2 the differences were significant and the rest were found to be nonsignificant. This study has demonstrated the usefulness of colour additive viewing techniques in the analysis of Landsat-MSS data for small-scale soil mapping and the same could be used for the preparation of small-scale soil maps of the States and the country.

A description of acid soils and the relationships between properties of acid soils and the nutrient status of grazed pastures in the southeast of South Australia

Areas of low soil pH in the south-east of South Australia were delineated by using previously submitted soil samples and soil association maps. A survey was then undertaken in the major soil associations to determine the severity and characteristics of highly acid soils. The acid soil types identified were a siliceous sand over clay (Db/Dy) and a siliceous sand over organic matter/sesquioxide pan (Uc). The top 2.5 cm of both soil types was significantly less acid than the remaining portion of the A horizon, with pH decreasing rapidly with depth until the B horizon, where a substantial soil pH increase occurred. As soil pH (0.01 M CaCl2) decreased below 4.5, extractable soil aluminium (0.01 M CaCl2) increased rapidly, to a maximum extractable concentration of 17 �g g-l. These soil types were also found to be deficient in both phosphorus and potassium, with 65% of the sites having extractable phosphorus concentrations below the critical value of 20 �g g-1 and 35% below the critical value for extractable potassium of 80 �g g-l. For subterranean clover, significant positive correlations were observed between soil pH and plant calcium and sulfur, and between extractable soil aluminium and plant aluminium. Significant negative correlations were observed between soil pH and plant manganese and between extractable soil aluminium and plant calcium and magnesium. For ryegrass, significant positive correlations were observed between extractable soil aluminium and plant aluminium and manganese. Significant negative correlations were observed between soil pH and plant manganese and between extractable soil aluminium and plant calcium. No other significant correlations were obtained. The results are discussed in relation to further acidification and management of these acid siliceous sands.

Use of Satellite Imagery to Delineate Soil Associations in the Sand Hills Region of Nebraska

Published soil association maps of counties within the Sand Hills region of Nebraska were used to establish relationships between satellite imagery and soil associations mapped by conventional methods. Soils formed in the eolian sand of this region range from somewhat excessively drained soils formed on major dunes to poorly drained soils of subirrigated valleys. These soils represent a hydrosequence; soil patterns are closely associated with differences in topography, near-surface hydrology, and rangeland vegetation. In view of these relationships, multispectral satellite imagery acquired during the growing season was useful in stratifying soil associations including subirrigated soils, whereas imagery obtained during periods of continuous snow cover and relatively low solar elevation angles was useful in stratifying soil associations characterized by differences in topography. Relationships established between published soil associations and satellite imagery were used to stratify soil associations at the mesosociation level of cartographic generalization in an adjacent area within the Sand Hills region.

Soil Classification and Land Sale Prices

AbstractOver 4,800 verified land sales in South Dakota covering a period of 1967–1972 were located on the South Dakota Soil Association Map (scale 1:500,000). The first‐named soil in the association was classified in the U. S. Comprehensive Soil Classification System as to order, suborder, great group, subgroup, and family and related to the average price paid per acre. Using coefficient of variation as a measure of homogeneity of a classification category, the most homogeneous units in South Dakota at each level of classification are: Mollisols, Borolls, Haploborolls, Glossic Natrustolls, and Typic Argiustolls, fine, mixed, mesic. In general not all units at the same categorical level are defined with the same precision, but climatically defined units were more homogeneous. In comparing categories, two of seven suborders were more homogeneous than the most homogeneous order, three of ten great groups were more homogeneous than the most homogeneous suborder, nine of twenty‐seven subgroups were more homogeneous than the most homogeneous great group and two of thirty‐seven families were more homogeneous than the most homogeneous subgroup. Some precision was gained at each level, with the greatest gain in homogeneity appearing between order and suborder and the least between subgroup and family.

Soil Association Maps and Proposed Nomenclature

AbstractInformation on the distribution of soils is needed for areas ranging in size from individual farms to the country as a whole. Detailed soil maps serve for individual farms or tracts of comparable size. General soil maps are needed for areas of larger size. Such maps may show soil associations or they may be schematic. The first kind serves a greater number of pragmatic objectives because the patterns and proportions of component soils within associations can be indicated. It is suggested that soil association maps are needed for a minimum of four universes in the United States. From largest to smallest, these have approximate areas of 250,000 sq km or more (one hundred thousand square miles or more), 2,500–250,000 sq km (thousands or ten of thousands of square miles), 250–2,500 sq km (hundreds of square miles), and less than 250 sq km (tens of square miles). Regardless of the size of universe covered by a map, the maximum number of soil associations in the legend should be about the same. This maximum should be about 18. The smallest number that does not do violence to soil patterns is best. A hierarchy of names is proposed for soil associations in the four universes. Again from largest to smallest, these are megasociation, macrosociation, mesosociation, and microsociation. It is further proposed that soil association and association be used as generic terms.

Accuracy in the Identification of Subgroups Delineated by a Sample‐Based Soil Association Map

AbstractA procedure to develop Seventh Approximation primary and secondary subgroup soil maps was applied to sample data for Christian county, Ill. A measure of accuracy of the resulting subgroup soil association map was determined by comparison with the modern detailed Christian county soil survey. The two most dominant subgroups of soils in two‐thirds of the county were identified correctly using a sample‐based soil association map. One of the two most dominant subgroups of soils was identified correctly in most of the remainder of the county. The virtual absence of areas where the two dominant subgroups of soils were incorrectly identified is further evidence that the Seventh Approximation maps based on sample data can be used in those areas of the world needing modern soil information.

Use of Sample Data and Seventh Approximation Criteria in Delineating Areas of Similar Soils

AbstractSoil series data, from the Soil and Water Conservation Needs Inventory 2% sample for a nine county study area in east‐central Illinois, were transformed into Seventh Approximation nomenclature at the order, suborder, great group, and subgroup categories. The dominant and second most dominant classes of soil within each sample area, with an indication of the degree of dominance, were plotted on outline maps. Stream locations were placed on the maps before soil boundaries were drawn. Soil regions were delineated by placing boundaries midway between sample areas of a different classification.Analysis of the maps indicates that the resulting subgroup map shows characteristics of soil distribution generally comparable to currently used county soil association maps. The development of this method is not intended to replace traditional methods of map construction in pedologically advanced areas. However, it may be a useful method for constructing accurate soil maps at various selected levels of generalization in areas of the world where soil distribution patterns are unknown or incompletely understood.

Reconnaissance Soil Survey in Northern Surinam

By aerial photography and numerous field observations a map with soil landscapes of the northern part of Surinam on a scale of approximately 1: 600,000 was constructed. On this map three main landscapes were distinguished: the landscapes with young soils from sedimentary parent materials on young coastal plain, old soils from sedimentary materials or old coastal plain and soils from residual parent materials. The last group included soil landscapes on schists, on granite and on subgreywacke and all lateritic or laterite-like soils. Near Paramaribo part of the young and the old coastal plain was examined more closely and the results were shown on a reconnaissance soil association map on a scale 1:100,000. Methods were discussed and ways were considered of using aerial photographs for soil mapping in humid tropical areas covered by dense forests. With expensive and therefore limited fieldwork the relation between soil and aerial photographic image needed to be determined. Individual soils had to be grouped into soil mapping units recognizable on aerial photographs, thus making it possible to follow their boundaries on photographs and to plot them directly. Real physiographic soil maps 1:100,000 could be made with mapping units distinguished on a reconnaissance soil map but with boundaries as detailed as from a detailed soil map.

Some remarks about the soils of the alluvial plain of Iraq, South of Baghdad.

Soil characteristics of the area surveyed are discussed on the basis of a general soil-association map (I: 250, 000) and a detailed map (I: 50, 000) prepared by means of systematic air-photo analysis. The technique is suitable for mapping large areas with a limited amount of field work. (Abstract retrieved from CAB Abstracts by CABI’s permission)