Soil Mapping Units Research Articles

Land-site suitability evaluation for tea, cardamom and rubber using Geo-spatial technology in Wayanad district, Kerala

Kerala is one of the important states contributing to the production of plantation crops and spices in the country. Soil and Land evaluation in various land utilization types has been carried out to assess the land suitability for tea, cardamom and rubber in Wayanad district of Kerala. Different soil physico-chemical parameters like, pH, electrical conductivity, organic carbon and physical attributes database of soil mapping units developed in inventorying of soil resources at 1:50K scale using LISS-III satellite data on soil series and its association used to evaluate soil site suitability for tea, cardamom and rubber. The results indicated that for tea around 55.79% area is suitable for cultivation of which 14.62 %, 25.51 % and 15.66 % found highly suitable (S1), moderately suitable (S2) and marginally suitable (S3), respectively. About 26.92 % and 12.10 % found moderately suitable (S2) and marginally suitable (S3) for cardamom and about 32.48 % area marginally suitable (S3) for rubber. The area unsuitable for cultivation (N) of tea, cardamom and rubber were found to be 11.69 %, 28.46 % and 34.99 %, respectively, due to constraints like relief, topography, soil physico-chemical attributes such as base saturation, pH and soil moisture regime etc. The study proposed an integrated methodology for mapping and assessing suitability of land using remote sensing and GIS techniques.

Soil property trends and classification of alluvial floodplains, South Carolina Coastal Plain

Alluvial soils derived from sediments of Piedmont origin occur in the Atlantic Coastal Plain of the southeastern U.S. In South Carolina, high-order rivers receiving sediment are Savannah (SV), Congaree (CN), Wateree (WA), Santee (ST), Lynches (LY), and Great Pee Dee (PD). This study investigated distribution of soil properties on natural levee, valley flat, and backswamp landforms within and among the six river floodplains and compared results to the taxonomic classifications used historically during soil survey production. This study also investigated the contribution of sediment sources to soil characteristics. Data were compiled for 65 soil pedons sampled from 16 soil survey areas during a 41-year time period. Pedons were located in three Major Land Resource Areas (MLRAs), and the results should aid in development of both land resource area and ecological site concepts. Data analyses centered on clay and silt contents, mineralogy, base saturation (BS), and cation exchange activity (CEA) classes. Evaluation of data from the six river floodplains revealed common properties among soils on fluvial landscapes across multiple MLRAs. Four soil systems, each derived from a predominant rock type, composed the Piedmont drainage basin of each river. The absolute area of each soil system differed between rivers, but sediment supplied typically did not result in great soil texture variation per landform. The land area proportion of the Carolina Slate Belt soil system had a close relationship to silt contents of the alluvial soils. On the valley flat landform of five floodplains, particle-size control section (PSCS) median clay content ranged only between 302gkg−1 and 405gkg−1. Among all valley flats median PSCS silt content ranged between 361gkg−1 and 511gkg−1. Slight positive downriver trends for clay were observed on SV, WA, and PD and for silt on SV and WA. Although local BS variation could be high between pedons, slight positive downriver BS trends on valley flats were observed on SV, WA, and ST. Negative BS trends were seen on LY and PD. Kaolinite was the dominant clay mineral in soils of all landforms on the six floodplains. Weatherable primary minerals in sand and silt fractions resulted in higher BS except for the LY soils, where resistant minerals composed sand and silt fractions. The semiactive CEA class occurred predominantly on all three landforms. Taxonomic analysis supported soil assignment to the suborders Aquepts or Udepts on all floodplains. Great group level Eutrudepts in South Carolina are first reported here, and they occur extensively enough on SV, CN, WA, and PD to warrant recognition in soil map units. Because most soil properties showed little variability for soils occurring in floodplains for all six rivers, botanical assessments will be needed to determine the magnitude of the role the properties have toward defining ecological sites. Ultimately, the alluvial systems may be aggregated as a single land resource area within the Coastal Plain.

SoilWeb: A Multifaceted Interface to Soil Survey Information

Core Ideas SoilWeb has evolved into new soil data visualization tools. SoilWeb tools are interactive maps that work with smartphones, tablets and desktops. The development of digital soil survey data has prompted the National Cooperative Soil Survey to envision new ways in which people interact with soil survey information. Access to online soil survey data must be easy to use, fast, and should accommodate how the data are used by clientele. In collaboration with the USDA-NRCS, the California Soil Resource Laboratory at University of California, Davis, began and continues to evolve its online soil survey products for this purpose. SoilWeb attempts to cater to the diverse ways in which users interact with soil survey data. SoilWeb has evolved into a series of software applications (apps) to inform users about how soil map units are designed, and to imitate how a digital soil survey is used in geographic information systems. Apps were created specifically to be fast and easy to use. Here, we communicate the evolution of SoilWeb and the design and operation of the new soil survey apps that comprise SoilWeb. We also demonstrate the widespread use of SoilWeb. All apps can be accessed at https://casoilresource.lawr.ucdavis.edu/soilweb-apps/ (accessed 22 June 2017).

Comparing SSURGO Data with Geospatial Field Measurements to Estimate Soil Texture and Infiltration Rate Classes in Glaciated Soils

ABSTRACTThe infiltration rate (IR) of water is a key soil property related to hydrological processes, soil health, and ecosystem services. However, detailed measurements of IR in the field and/or laboratory are labor-intensive and expensive to perform. Soil judging in the field provides a rapid and inexpensive method to estimate IR classes based on soil texture, soil organic carbon/matter, and soil structure. The objectives of this study were to classify and compare soil texture and IR for the A horizon across the 147 ha Cornell University Willsboro Research Farm using the Soil Survey Geographic (SSURGO) database and field-based measurements. Soil texture was the dominating factor to explain the general trend of Entisols > Inceptisols > Alfisols with regard to IR in the A horizon. In general, the variability in soil texture observed in field measurements was consistent with the variability reported in the SSURGO database, although the SSURGO representative values for soil texture did not completely match measured mean values for all soil map units. With the exception of one soil map unit, estimates of IR classes utilizing soil judging in the field criteria also were consistent when using either SSURGO or field-based data. Estimating infiltration rate classes for ecosystem services frameworks using geospatial analysis of field and/or SSURGO data can be enhanced with emerging technologies (e.g., sensors) and/or easily measured conventional soil properties.

Landscape, Soil, and Plant Analysis of Japanese Stiltgrass (Microstegium vimineum) Invasion in the Piedmont Region, SC

ABSTRACTJapanese stiltgrass (Microstegium vimineum), an exotic invasive plant, is native to Southeast Asia. This study was conducted to determine the chemical composition of Japanese stiltgrass as well as soil and landscape characteristics that correlate with invasion of Japanese stiltgrass around Lake Issaqueena in the upper Piedmont of South Carolina. Geographic Information Systems (GISs) and Light Detection and Ranging (LiDAR) were used to determine the spatial pattern of invasion with respect to the aspect, slope, canopy cover, soils, and distance to roads and trails. Japanese stiltgrass was distributed on both sides of Lake Issaqueena in Pacolet and Madison soil map units (Fine, kaolinitic, thermic Typic Kanhapludults) on the average slopes of 21%, but it was particularly common on the eastern shore of the lake in low-lying wet and shaded areas (mean canopy cover 51%). In addition, invasion by Japanese stiltgrass was correlated with the proximity to roads and trails. Plant tissue analysis revealed many differences in the distribution of macronutrients, macrominerals, and micronutrients in the leaves, stems, and roots of Japanese stiltgrass, although those differences were not always statistically significant. Concentrations of nitrogen (N), phosphorus (P), and calcium (Ca) were the highest in leaves while zinc (Zn) concentrations were the highest in stems and concentrations of magnesium (Mg), copper (Cu), manganese (Mn), iron (Fe), and sodium (Na) tended to be higher in roots. Carbon (C), sulfur (S), and potassium (K) concentrations were generally higher in above-ground tissues versus roots. Soil chemical analysis revealed no statistical differences between control and invaded plots. Our findings suggest that watershed areas surrounding lakes may be particularly susceptible to the invasion of Japanese stiltgrass due to their microclimates, low-lying wet pathways for seed distribution and recreational uses.

Data mining methods applied to map soil units on tropical hillslopes in Rio de Janeiro, Brazil

A soil survey is the main source of soil spatial information and is very useful in supporting land use decisions, especially for agronomic purposes. However, the continuity of soil surveying in Brazil has been compromised due the minimal amount of government investment in the sector. The goal of this study was to evaluate the performance of three data mining methods—decision trees (DT), random forest (RF), and artificial neural networks (ANN)—with R software to predict soil map units from the Guapi-Macacu watershed in Rio de Janeiro State, Brazil. Terrain attributes derived from a digital elevation model (DEM), remote sensing data (Landsat 5), and a geology map were used as predictors. Evaluation of the models' performance was based on statistical indices obtained from a confusion matrix by using validation samples. Furthermore, a comparison was performed to analyze the agreement between the maps created from the models and from a conventional soil map (legacy data); sampling locations were not used as input data in the training process. The results indicated better performance from the RF model compared with the DT and ANN models. The accuracy was calculated through validation samples indicating values in the Kappa index corresponding to 0.76 (RF), 0.72 (ANN) and 0.66 (DT). A comparison between the maps obtained from the models and the conventional soil map exhibited better agreement with the RF model (68.7%), followed by the ANN (62.8%), and DT (62.3%) models. The classification accuracy, obtained through comparisons with sampling locations, exhibited correct classification of 57.6% in the RF model, 56.8% in the DT, and 56.1% in the ANN model; the conventional soil map had 69.7% correct classification. In general, most of the confusion between soil map units was observed in Haplic Gleysols, Haplic Acrisols (Clayic) and Fluvisols. In terms of covariates importance, in general, the terrain attributes derived from the DEM had more influence as predictor covariates than the indices obtained from the Landsat data. The application of data mining can improve the methods applied to soil map units, thereby contributing to increasing information related to soil-landscape relationships and enhancing the products of soil surveys.

Evaluation of agricultural land resources for irrigation in the cotton growing Yavatmal district, Maharashtra, India

The main objective of this study is to evaluate suitability of shrink-swell soils for surface irrigation system based upon a parametric evaluation system in low irrigation potential (7%) of cotton growing Yavatmal district, Maharashtra, India. The thirty three shrink-swell soil series on basaltic landforms were identified from reconnaissance soil survey on 1:50,000 scale and evaluated for surface irrigation methods using Geographic Information System (GIS). The standard weekwise rainfall data showed that the rainfall is less than 20% of total precipitation during September and December, the top A horizon reaches to wilting point and needs supplementary protective irrigation to cotton based cropping systems . It was estimated that ten soil mapping units (1.8 Mha and 13.89%) of shrink-swell soils on moderate slopes (5 to 8%) were evaluated as suitable for surface methods and calculated the irrigation intervals that vary from 8.61±1.35 days for cotton to 8.9±1.4 days for wheat and 10±1.64 days for sugar cane. The study emphasized the utility of soil resource maps helps to delineate the soils with large PAWC(>200mm) with slight yield advantage and will serve as benchmark sites to monitor the interrelationships of soil water dynamics with respect to climate and cotton yields.

Using Credible Soil Loss Tolerance Value for Conservation Planning and Managing Diverse Physiographic Regions in Rajasthan

Accelerated soil erosion degrades soil quality and undermines ecosystem functions and services. It is important to assess the severity of erosion, demarcate tolerable limits for sustainable crop production, conservation planning for soil resources, and identify the alternative land uses. Irrespective of soil type, climate and vegetation cover, the tolerable level of soil erosion in India has traditionally been taken as 11.2 Mg ha−1 year−1. However, this is an excessive rate for most agro-ecosystems and land uses; hence, this study aims to establish credible soil loss tolerance (‘T’ values) for some soils of western India on the basis of critical soil parameters (i.e., bulk density, infiltration rate, total organic carbon and soil reaction). The condition of a soil or ‘soil state’ (S) is defined through a quantitative model involving different soil functions. The ‘T’ values for some soils of western India ranged between 2.5 and 12.5 Mg ha−1 year−1 compared to default ‘T’ value of 11.2 Mg ha−1 year−1. About 50% of the land area has ‘T’ value >10 Mg ha−1 year−1, and the remaining 50% has <7.5 Mg ha−1 year−1, of which 13.02 M ha is having only ‘T’ value of 2.5 Mg ha−1 year−1. Using the revised ‘T’ values for soil mapping units will help in planning of appropriate conservation measures for effective erosion control, sustainable crop production and improved watershed management in the Rajasthan State of western India.

Soil Classification and Land Suitability for Agroforestry of Solo Hulu Watershed

Watershed requires management to diversify the function of sustainable biomass production, provide benefits for the socio-economic benefits and environmental aspects of land cover as a function of media production and water management regulator. It is known that upstream Solo watershed contributes sediment substantially to the silting of Gajah Mungkur reservoirs and carry sediment through Bengawan Solo river flow. Purpose of this study was to determine characteristics of soil and vegetation diversity in upstream Solo watershed area. Research was carried out by analysis of satellite observation and field survey with stratified random sampling method. Result showed that upstream Solo watershed is divided into six soil map units (SMU), soil was encountered into orders of Vertisols, Entisols, Alfisols and Inceptisols. Most areas of upstream Solo watershed was opened-vegetation with steep slope. Agroforestry type applied by public was simple agroforestry included mixed-cropping, barrier of bound and terrace and barrier of land ownership. Main vegetations were teak, mahogany and acacia. Land utilization was marginal with dry month length as an inhibitor factor.

Soils and climate of Cul de Sac Valley, Haiti: A soil water and geomorphology perspective

Soil is an important natural resource, yet for many countries, including Haiti, the only soil inventory is a general soil map at 1:250,000 scale, which is not suitable for management planning at the farm level. A soil survey for a 3,000 ha (7,400 ac) segment of Cul de Sac Valley was conducted at 1:24,000 scale. Eleven soil types and soil map units were identified. Approximately 60% of the study area consisted of soils on Floodplains, while 40% were soils on Foothills, Hills, and Dissected Alluvial Fans. The combination of the parent material, predominantly marine sediment and limestone bedrock, and spatial-temporal precipitation patterns resulted in soils dominated by calcium carbonate (CaCO3) and sodium (Na) accumulations throughout their profile. The new soil geomorphology map derived from the detailed soil map was similar to the existing general soil map and geomorphology map. It was spatially more accurate and provided better understanding of soil and climate influence on soil water movement. Cul de Sac Valley resulted from uplifting and erosion and deposition processes. This, combined with aridic to semiaridic climate conditions, resulted in cemented CaCO3 accumulation and Na rich soils. The water management for irrigation was limited by a combination of soil properties such as high gravel and steep slopes for Dissected Alluvial Fans and Hills soil geomorphic units, presence of cemented CaCO3 for Foothills, and high Na content for Lower Flat Plains. Further studies are needed for a complete and comprehensive understanding of the soil geomorphology processes and climate interactions of this complex system.

Analysis of Digital Elevation Model and LNDSAT Data Using Geographic Information System for Soil Mapping in Urban Areas

This study applies digital analysis methods of topographic data derived from digital elevation models (DEMs) and Landsat remotely sensed spectral data using GIS tools to evaluate the quality and limitations of the morphometric parameters (terrain attributes: TAs). This aims to check its suitability for digital soil mapping (DSM) and survey in urban areas at the target scale 1:50,000. This scale represents the standard scale level for compiling soil inventories within all German states. The study is conducted on an urban area of 112.68 km2 in the southwest part of the state of Berlin in Germany. These relief units are the basis for determining the soil mapping units at the scale of 1:50,000. The generated preliminary soil map was compared to soil maps made using traditional soil survey methods. For the mainly natural soils, the equivalence area is 94.91%, and for the anthropogenic soils, the equivalence area is 95.34%. The proposed methodology is adequate for preliminary mapping of soil units based on the digital derivation of TAs. Landsat scenes are spatially explicit, physical representations of environmental covariates on the land surface. The free DEM-ASTER in combination with Landsat OLI images is found to be the appropriate model to represent the terrain surface and derive the TAs for environmental modeling and fitting of derivation the relief units and their topography features. However, the 30 m spatial resolution and the fairly coarse spectral resolution of DEMs and Landsat images limit their utility for digital soil mapping at this scale in urban areas with little topographic variation.

Application of airborne gamma-ray imagery to assist soil survey: A case study from Thailand

Airborne gamma-ray imagery (AGRI) provides coarse-resolution (approximately 400×400m pixel) spatial information on gamma-ray emitting elements, i.e. potassium (K), thorium (Th) and uranium (U), in the upper half meter of the soil. These radioelements are a potential information source for soil mapping since their abundance is related to soil geochemistry, specifically the chemical composition of parent materials and their weathering products resulting from geomorphic and pedogenic processes.The aim of this study was to evaluate the potential of AGRI for improving digital soil survey process in two phases: (1) a preliminary phase, where hypotheses of soil-landscape relationships are developed, and (2) a phase where soil map unit boundaries are placed or revised. The study also evaluated the match between AGRI and existing lithologic, geopedologic, and soil series maps. The study was conducted in a well-characterized complex soil landscape: the 560km2 upper Pa Sak watershed in Petchaboon province, Thailand. The relationship between gamma-ray data and geological units was examined with box-and-whisker plots and confirmed by rock and soil samples. Rock and soil sample classifications were compared with the gamma-ray image and to typical radioelement responses found in the literature.To interpret AGRI data in terms of regolith and soil genesis, we compared AGRI to two existing soil maps: geopedologic and soil series maps. First, the geopedologic map was split into four maps according to the geopedologic hierarchy: landscape, lithology, relief, and landform; at the latter (lowest) level, soil units are also associated. Secondly, soil series and geopedologic soil units were used to examine the distribution of radioelement response to selected soil characteristics: parent material, texture, mineralogy, and thickness. The interpretations from best correlation in both soil maps were described in terms of the radioelement changes during pedogenic and geomorphic processes, based on a review of literature and supported by soil samples.In the hypotheses-generating stage, AGRI provided useful information in three forms (single signal, ratio, and ternary images enhanced with a hill shaded DEM) by relating these to lithology, material transport, and internal pedogenetic processes. AGRI correlated well with the classes of the geopedologic map (1:50,000) at the two higher levels (landscape and lithology) but to a lesser degree at the two lower levels (relief and landform in geopedologic approach). In the mapping stage, AGRI showed deficiencies in the soil series map (1:50,000) made by conventional aerial photo analysis and limited field surveys, especially in inaccessible areas but also in low-relief terraces and flood plains, which provided a basis for future field sampling to correct these deficiencies. AGRI suggested new boundaries, differentiating topsoil properties and the presence of plinthite, despite its coarse resolution.Clustering of gamma ray and elevation data (DEM) was carried out using fuzzy logic to generate various classification layers. Final map was produced using total weighted inverse distance of all the classes in a 3 by 3 window. Class label was assigned to the one with the largest total inverse distance over the entire set of fuzzy classification bands. The result shows relatively higher classification accuracy for soil parent material differentiation (overall accuracy of 72%) as compared to the classification for soil types (67%).

Crop model- and satellite imagery-based recommendation tool for variable rate N fertilizer application for the US Corn system

Precision nitrogen (N) management for corn has gained popularity due to both economic and environmental considerations. There is sufficient evidence demonstrating that N fertilizer efficiency can be improved by implementing sidedress and variable rate fertilization. In this paper, a crop model- and satellite imagery-based decision-support tool for recommending variable rate N fertilization at a high resolution of 5 m × 5 m is introduced. The sub-field management zones were delineated by overlapping the soil survey geographic (SSURGO) soil map units with wide dynamic range vegetation index (WDRVI)-derived relative productivity zones. The calibrated Agricultural Production Systems sIMulator (APSIM) was used to simulate a range of soil N processes, corn growth and N uptake by assimilating real-time weather data from the National Climate Data Center (NCDC). Sidedress N rates were estimated based on the target rate, N loss via leaching and denitrification, plant uptake and leftover N in the soil. The tool was tested on a 66 ha corn field in Illinois, USA for the growing season of 2015. Results showed that N-Prescription was able to give reasonable management zone delineation and sidedress N recommendation. The recommended sidedress N ranged from 60 to over 120 kg ha−1. Corn yield was greater in areas with higher sidedress recommendation, but the benefit from sidedress decreased with the increasing rate and plateaued above 110 kg ha−1. Sensitivity analysis suggested that soil hydraulic properties and soil organic matter content were critical to the sidedress accounting. Corn growth, and hence the cumulative N uptake, can be well simulated by calibrating the WDRVI derived leaf area index. This tool could serve as a good foundation for further development in precision N management.

Earth Observation and Geospatial techniques for Soil Salinity and Land Capability Assessment over Sundarban Bay of Bengal Coast, India

Abstract To guarantee food security and job creation of small scale farmers to commercial farmers, unproductive farms in the South 24 PGS, West Bengal need land reform program to be restructured and evaluated for agricultural productivity. This study established a potential role of remote sensing and GIS for identification and mapping of salinity zone and spatial planning of agricultural land over the Basanti and Gosaba Islands(808.314sq. km) of South 24 PGS. District of West Bengal. The primary data i.e. soil pH, Electrical Conductivity (EC) and Sodium Absorption ratio (SAR) were obtained from soil samples of various GCP (Ground Control Points) locations collected at 50 mts. intervals by handheld GPS from 0–100 cm depths. The secondary information is acquired from the remotely sensed satellite data (LANDSAT ETM+) in different time scale and digital elevation model. The collected field samples were tested in the laboratory and were validated with Remote Sensing based digital indices analysisover the temporal satellite data to assess the potential changes due to over salinization. Soil physical properties such as texture, structure, depth and drainage condition is stored as attributes in a geographical soil database and linked with the soil map units. The thematic maps are integrated with climatic and terrain conditions of the area to produce land capability maps for paddy. Finally, The weighted overlay analysis was performed to assign theweights according to the importance of parameters taken into account for salineareaidentification and mapping to segregate higher, moderate, lower salinity zonesover the study area.

Characterization of soil fertility and soil biodiversity with dsDNA as a covariate in a regression estimator for mean microbial biomass C

The analytical determination of microbial biomass carbon is time‐consuming, which limits its use as a reference biochemical property for characterizing soil fertility and soil biodiversity of soil mapping units (SMUs). This paper explores whether the efficiency of sampling strategies for estimating the means of microbial biomass C (MBC) of SMUs can be increased with dsDNA as an ancillary variable in a regression estimator, leading to a model‐assisted sampling strategy. The map unit means of dsDNA are unknown; therefore, to implement the regression estimator a two‐phase sampling strategy is required. The two‐phase sampling design was tested in three soil units of the Brtonigla area (Istria, Croatia) that are widely involved in wine production. In the first phase, 20 locations per SMU were selected at which the ancillary variable dsDNA was determined in field‐moist and air‐dried soil. In the second phase, a subsample of ten locations per map unit were selected at which MBC was determined. The estimated sampling variances of the regression estimator were compared with the sampling variances of the design‐based estimator with a cost‐equivalent number of sampling points. The model‐assisted strategy was more accurate in two of the soil units in which the correlation between MBC and dsDNA was strong (adjusted R2 larger than 0.55). Measurements of dsDNA on field‐moist samples gave more precise estimated means of MBC than those on air‐dried samples.HighlightsUse of dsDNA to estimate the means of microbial biomass C (MBC) within soil mapping units (SMUs). Comparison of model‐assisted and design‐based sampling strategies to estimate mean MBC of SMUs. Model‐assisted strategy was more efficient in two SMUs; field‐moist dsDNA was better than air‐dried dsDNA. dsDNA increased the efficiency of sampling strategies to estimate mean MBC of SMUs with homogeneous land use.

Spatial variability of soil development indices and their compatibility with soil taxonomic classes in a hilly landscape: a case study at Bandar village, Northern Iran

Soil complexity and its multivariable nature restrict the precision of soil maps that are essential tools for soil sustainable management. Most methods developed for reducing impurities of soil map units focus on soil external properties. Taking into account the soil internal properties like geochemical weathering indices could increase the map unit's purity. However, the compatibility of these indices with Soil Taxonomic Classes has not been studied yet. This study has been performed in a hilly region with different soil types, vegetation and diverse topographic attributes to illustrate the spatial variability of soil weathering indices and their compatibility with Soil Taxonomic Classes. The grid sampling is at 100 m interval. Physico-chemical and total elemental analyses were performed on 184 and 56 soil samples respectively. Eight topographic attributes and 14 common soil development indices were determined. Principal components analysis (PCA) was done to identify the most important components. The results indicated that Morphological Index (MI) was the best index to show the degree of soil development in the studied region. Spatial distribution of Soil Taxonomic Classes showed relatively good compatibility with the first principal component (PC1), Vogt (V) and morphological indices. This study showed that using soil development indices with the conventional methods could be helpful tools in soil survey investigations.

Using spatial data mining to analyze area-diversity patterns among soil, vegetation, and climate: A case study from Almería, Spain

Area-pedodiversity, area–vegetation diversity, area-bioclimatic belts, diversity and pedodiversity-vegetation diversity-bioclimatic diversity relationships were analyzed for the most arid region of Western Europe (SE Spain). The study is novel in that it analyzed these relationships using as operational geographic units (OGUs) the set of polygons belonging to the same character state (i.e., typology) that defines a zone in a given thematic map. We considered three thematic maps: 1) the map of soil associations (SMU) with 303 different soil associations (i.e., 303 areas or zones); 2) the map of potential vegetation (PNV) with 40 vegetation series or zones and 3) the map of bioclimatic belts (BB) with 7 bioclimatic zones. Using GIS tools, we analyzed the contents (richness) of soil mapping units (polygons) with regard to vegetation series and bioclimatic belts as well as the contents of vegetation series and bioclimatic belts with regard to SMU. The results indicate that the relationships between the area and the richness of zones follow a power law, the “fingerprint of fractal geometry”, irrespective of the way the area has been defined and their relative magnitude (the areas defined by SMU are the smallest, while the areas defined by bioclimatic belts are the largest). The results also indicate a significant correlation between the α diversities of the zones and between their β diversities. We conclude that the methods used to measure such correlations, based on α and β diversities are useful to investigate and quantify the relationships between the pedosphere, vegetation and climate.

Geospatial approach in mapping soil erodibility using CartoDEM – A case study in hilly watershed of Lower Himalayan Range

Soil erodibility is one of the most important factors used in spatial soil erosion risk assessment. Soil information derived from soil map is used to generate soil erodibility factor map. Soil maps are not available at appropriate scale. In general, soil maps at small scale are used in deriving soil erodibility map that largely generalized spatial variability and it largely ignores the spatial variability since soil map units are discrete polygons. The present study was attempted to generate soil erodibilty map using terrain indices derived from DTM and surface soil sample data. Soil variability in the hilly landscape is largely controlled by topography represented by DTM. The CartoDEM (30 m) was used to derive terrain indices such as terrain wetness index (TWI), stream power index (SPI), sediment transport index (STI) and slope parameters. A total of 95 surface soil samples were collected to compute soil erodibility factor (K) values. The K values ranged from 0.23 to 0.81 t ha−1R−1 in the watershed. Correlation analysis among K-factor and terrain parameters showed highest correlation of soil erodibilty with TWI (r 2= 0.561) followed by slope (r 2= 0.33). A multiple linear regression model was developed to derive soil erodibilty using terrain parameters. A set of 20 soil sample points were used to assess the accuracy of the model. The coefficient of determination (r 2) and RMSE were computed to be 0.76 and 0.07 t ha−1R−1 respectively. The proposed methodology is quite useful in generating soil erodibilty factor map using digital elevation model (DEM) for any hilly terrain areas. The equation/model need to be established for the particular hilly terrain under the study. The developed model was used to generate spatial soil erodibility factor (K) map of the watershed in the lower Himalayan range.

Priorities of Agricultural Utilization for Some New Areas of El-Minia Governorate Desert fringe - Egypt

Due to the continuous decrease of agricultural lands, it is necessary to identify the most relevant lands for sustainable agriculture development at desert areas in which being socially equitable. The main objective of this study is to determine priorities of agricultural utilization for some areas at the western desert fringe of El-Minia Governorate. The selected area is bounded by longitudes 30о 30` 00``E and 30о 45` 00``E and latitudes 28о 26` 56``N and 28о 46` 1``N, covering an area of approximately 124691 feddan. It includes five new village of El-Minia namely; new Al-Atf, new Ash ShaykhMas’ud, new Al-Bahnasa, new Al-Hema and new Abu Algod villages. Soils of the area were surveyed using 90 profiles. Seventeen soil profiles were chosen to represent dominant landforms of the area. Soil samples were collected for further laboratory analysis to determine their properties. Based on ground truth data, laboratory analysis and imagery interpretation in cooperation with geographic information system (GIS) utilities, the geomorphic map was generated and nine geomorphic units could be differentiated. These are; pediment; alluvial fans and outwash plains; upper, moderate and lower rubble terraces; old river terraces; dissected plateaus; wind-blown sand dunes; hilly areas and rock out crops. Soils of these landforms were investigated and classified mainly as Lithic Torripsamments, Typic Torripsamments, Typic Torriorthents, Typic Haplogypsids, Calcic Haplosalids, and Typic Haplocalcids subgroups. They were grouped into four soil mapping units varying in soil depth and gravel content. Land capability was assessed to define the most suitable areas for agricultural production using MicroLEIS microcomputer program (CERVATANA capability model). Soils of the area classified into two capability classes, moderate-S (37.1 %) and non productive-N (36.13 %), while rest of the area belong to dissected plateau, hilly terrain and dunes. Further, three capability subclasses were recognized abbreviated as S3 l, S3 lr, and N l in accordance to limitations type and severity. Priorities of Agricultural Utilization Model (PAUM) was designed. Four priority grads were identified where the first priority in the studied area occupy 25.84 % of the total terrain and belongs mainly to soils of alluvial fans and outwash plains, lower rubble terraces, and partially old river terraces. Only new AshShaykh Mas’ud village belongs to the first priority for agricultural utilization, while, other investigated villages were classified as third priority. The study is considered of vital importance for decision makers through the management of natural resources in desert fringe.

Ferramentas de pedometria para caracterização da composição granulométrica de perfis de solos hidromórficos

Resumo O objetivo deste trabalho foi avaliar ferramentas pedométricas para caracterização da composição granulométrica (areia, silte e argila) e comparação de perfis de solos hidromórficos. O estudo foi realizado na bacia hidrográfica do rio Guapi-Macacu, RJ. Foram aplicados o algoritmo "slice-wise" para o fatiamento do perfil em intervalos de 1 cm, e a função "spline" para harmonizar o conjunto de dados segundo seis intervalos de profundidade predefinidos. A análise do conjunto de perfis, por meio das funções de profundidade (slice-wise e spline) e de dendrograma de dissimilaridade, revelou que Planossolos e Gleissolos são relativamente rasos e apresentam camadas arenosas nos horizontes superficiais e teores de argila e silte irregulares em subsuperficie. Essas duas ordens ocorrem na área da bacia hidrográfica geralmente em planícies aluviais, em vales e em sopés de elevação. Os Neossolos Flúvicos apresentaram maiores quantidades de argila e silte em superfície, as quais decrescem em profundidade, e são mais profundos e ocorrem nos terraços aluviais. A abordagem permitiu descrever a variabilidade da textura dos solos hidromórficos em perfil e realizar a análise de similaridade entre as ordens, o que pode apoiar a distinção de fases em unidades de mapeamento e a identificação de critérios quantitativos para a classificação dos solos.