DOSoReMI.hu: collection of countrywide DSM products partly according to GSM.net specifications, partly driven by specific user demands

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Takács, Katalin; Szatmári, Gábor; Illés, Gábor; Bakacsi, Zsófia; Szabó, József

2017-04-01

Due to former soil surveys and mapping activities significant amount of soil information has accumulated in Hungary. In traditional soil mapping the creation of a new map was troublesome and laborious. As a consequence, robust maps were elaborated and rather the demands were fitted to the available map products. Until recently spatial soil information demands have been serviced with the available datasets either in their actual form or after certain specific and often enforced, thematic and spatial inference. Considerable imperfection may occur in the accuracy and reliability of the map products, since there might be significant discrepancies between the available data and the expected information. The DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project was started intentionally for the renewal of the national soil spatial infrastructure in Hungary. During our activities we have significantly extended the potential, how soil information requirements could be satisfied. Soil property, soil type as well as functional soil maps were targeted. The set of the applied digital soil mapping techniques has been gradually broadened incorporating and eventually integrating geostatistical, data mining and GIS tools. Soil property maps have been compiled partly according to GSM.net specifications, partly by slightly or more strictly changing some of their predefined parameters (depth intervals, pixel size, property etc.) according to the specific demands on the final products. The elaborated primary maps were further processed, since even DOSoReMI.hu intended to take steps for the regionalization of higher level soil information (processes, functions, and services) involving crop models in the spatial modelling. The framework of DOSoReMI.hu also provides opportunity for the elaboration of goal specific soil maps, with the prescription of the parameters (thematic, resolution, accuracy, reliability etc.) characterizing the map product. As a result, unique digital soil map products (in a more general meaning) were elaborated regionalizing specific soil (related) features, which were never mapped before, even nationally with high ( 1 ha) spatial resolution. Based upon the collected experiences, the full range of GSM.net products were also targeted. The web publishing of the results was also elaborated creating a proper WMS environment. Our paper will present the resulted national maps furthermore some conclusions drawn from the experiences.] Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA) under Grant K105167 and AGRARKLÍMA.2 VKSZ_12-1-2013-0034.

Topsoil organic carbon content of Europe, a new map based on a generalised additive model

NASA Astrophysics Data System (ADS)

de Brogniez, Delphine; Ballabio, Cristiano; Stevens, Antoine; Jones, Robert J. A.; Montanarella, Luca; van Wesemael, Bas

2014-05-01

There is an increasing demand for up-to-date spatially continuous organic carbon (OC) data for global environment and climatic modeling. Whilst the current map of topsoil organic carbon content for Europe (Jones et al., 2005) was produced by applying expert-knowledge based pedo-transfer rules on large soil mapping units, the aim of this study was to replace it by applying digital soil mapping techniques on the first European harmonised geo-referenced topsoil (0-20 cm) database, which arises from the LUCAS (land use/cover area frame statistical survey) survey. A generalized additive model (GAM) was calibrated on 85% of the dataset (ca. 17 000 soil samples) and a backward stepwise approach selected slope, land cover, temperature, net primary productivity, latitude and longitude as environmental covariates (500 m resolution). The validation of the model (applied on 15% of the dataset), gave an R2 of 0.27. We observed that most organic soils were under-predicted by the model and that soils of Scandinavia were also poorly predicted. The model showed an RMSE of 42 g kg-1 for mineral soils and of 287 g kg-1 for organic soils. The map of predicted OC content showed the lowest values in Mediterranean countries and in croplands across Europe, whereas highest OC content were predicted in wetlands, woodlands and in mountainous areas. The map of standard error of the OC model predictions showed high values in northern latitudes, wetlands, moors and heathlands, whereas low uncertainty was mostly found in croplands. A comparison of our results with the map of Jones et al. (2005) showed a general agreement on the prediction of mineral soils' OC content, most probably because the models use some common covariates, namely land cover and temperature. Our model however failed to predict values of OC content greater than 200 g kg-1, which we explain by the imposed unimodal distribution of our model, whose mean is tilted towards the majority of soils, which are mineral. Finally, average OC content predictions for each land cover class compared well between models, with our model always showing smaller standard deviations. We concluded that the chosen model and covariates are appropriate for the prediction of OC content in European mineral soils. We presented in this work the first map of topsoil OC content at European scale based on a harmonised soil dataset. The associated uncertainty map shall support the end-users in a careful use of the predictions.

Distribution of soil organic carbon in the conterminous United States

USGS Publications Warehouse

Bliss, Norman B.; Waltman, Sharon; West, Larry T.; Neale, Anne; Mehaffey, Megan; Hartemink, Alfred E.; McSweeney, Kevin M.

2014-01-01

The U.S. Soil Survey Geographic (SSURGO) database provides detailed soil mapping for most of the conterminous United States (CONUS). These data have been used to formulate estimates of soil carbon stocks, and have been useful for environmental models, including plant productivity models, hydrologic models, and ecological models for studies of greenhouse gas exchange. The data were compiled by the U.S. Department of Agriculture Natural Resources Conservation Service (NRCS) from 1:24,000-scale or 1:12,000-scale maps. It was found that the total soil organic carbon stock in CONUS to 1 m depth is 57 Pg C and for the total profile is 73 Pg C, as estimated from SSURGO with data gaps filled from the 1:250,000-scale Digital General Soil Map. We explore the non-linear distribution of soil carbon on the landscape and with depth in the soil, and the implications for sampling strategies that result from the observed soil carbon variability.

Target-specific digital soil mapping supporting terroir mapping in Tokaj Wine Region, Hungary

NASA Astrophysics Data System (ADS)

Takács, Katalin; Szabó, József; Laborczi, Annamária; Szatmári, Gábor; László, Péter; Koós, Sándor; Bakacsi, Zsófia; Pásztor, László

2016-04-01

Tokaj Wine Region - located in Northeast-Hungary, at Hegyalja, in Tokaj Mountains - is a historical region for botrityzed dessert wine making. Very recently the sustainable quality wine production in the region was targeted, which requires detailed and "terroir-based approach" characterization of viticultural land and the survey of the state of vineyards. Terroir is a homogeneous area that relates to both environmental and cultural factors, that influence the grape and wine quality. Soil plays dominant role determining the viticultural potential and terroir delineation. According to viticultural experts the most relevant soil properties are drainage, water holding capacity, soil depth and pH. Not all of these soil characteristics can be directly measured, therefore the synthesis of observed soil properties is needed to satisfy the requirements of terroir mapping. The sampling strategy was designed to be representative to the combinations of basic environmental parameters (slope, aspect and geology) which determine the main soil properties of the vineyards. Field survey was carried out in two steps. At first soil samples were collected from 200 sites to obtain a general view about the pedology of the area. In the second stage further 650 samples were collected and the sampling strategy was designed based on spatial annealing technique taking into consideration the results of the preliminary survey and the local characteristics of vineyards. The data collection regarded soil type, soil depth, parent material, rate of erosion, organic matter content and further physical and chemical soil properties which support the inference of the proper soil parameters. In the framework of the recent project 33 primary and secondary soil property, soil class and soil function maps were compiled. A set of the resulting maps supports to meet the demands of the Hungarian standard viticultural potential assessment, while the majority of the maps is intended to be applied for terroir delineation. The spatial extension was performed by two, different methods which are widely applied in digital soil mapping. Regression kriging was used for creating continuous soil property maps, category type soil maps were compiled by classification trees method. Accuracy assessment was also provided for all of the soil map products. Our poster will present the summary of the project workflow - the design of sampling strategy, field survey, digital soil mapping process - and some examples of the resulting soil property maps indicating their applicability in terroir delineation. Acknowledgement: The authors are grateful to the Tokaj Kereskedöház Ltd. which has been supporting the project for the survey of the state of vineyards. Digital soil mapping was partly supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Interpreting ground conditions from geologic maps

USGS Publications Warehouse

,

1949-01-01

Intelligent planning for heavy construction, water supply, or other land utilization requires advance knowledge of ground conditions in the area. It is essential to know:the topography, that is, the configuration of the land surface;the geology and soils, that is, the deposits that compose the land and its weathered surface; andthe hydrology, that is, the occurrence of water whether under or on the ground.These elements usually are considered in planning land developments that involve much investment; detailed surveys generally are made of the topography, geology, soils, and hydrology at the site selected for development. Such detailed surveys are essential, but equally essential and often overlooked is the need for general surveys prior to site selection.Only if the general surveys have been made is it possible to know that a particular site is most suitable for the purpose and that no situations in the tributary areas that might affect the project have been overlooked. Moreover, the general regional relations must be known in order to properly interpret the geology, soils, and hydrology at a particular locality. In brief, both the general and the specific are needed in order to avoid costly mistakes either during or after development.The accompanying maps illustrate how a general geologic map can be used for interpreting grc .d conditions during a planning stage prior to site selection. The topographic and geologic maps, which provide the basic data, have been simplified from some existing ones. The interpretive sheets are intended to provide some examples of the kinds of information that trained persons can read from such basic maps.

Mapping of Soil-Ecological Conditions of a Medium-Size Industrial City (Birobidzhan City, Jewish Autonomous Oblast, FarEast of Russia as an Example)

NASA Astrophysics Data System (ADS)

Kalmanova, V. B.; Matiushkina, L. A.

2018-01-01

The authors analyze soil relations with other elements of the city ecosystem (the position in the landscape, soil-forming rocks and lithology, vegetation and its state) to develop the legend and map of soils in the City of Birobidzhan (scale 1:25 000). The focus of study is the morphological structure of urban soils with different degree of disturbance of these relations under the impact of technical effects, economic and recreational activities of the city population. The soil cover structure is composed of four large ecological groups of soils: natural untransformed, natural with a disturbed surface, anthropogenic soils and technogenic surface formations. Using cartometry of the mapped soil contours the authors created the scheme of soil-ecological city zoning, which in a general way depicts the state of soil ecological functions in the city as well as identified zones of soils with preserved, partially and fully distured ecological functions and zones of local geochemical anomalies at the initial formation stage (environmental risk zones).

33 CFR 332.3 - General compensatory mitigation requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... wetland maps; soil surveys; U.S. Geological Survey topographic and hydrologic maps; aerial photographs... appropriate quantitative assessment tools, where available; (iii) Preservation is determined by the district...

33 CFR 332.3 - General compensatory mitigation requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... wetland maps; soil surveys; U.S. Geological Survey topographic and hydrologic maps; aerial photographs... appropriate quantitative assessment tools, where available; (iii) Preservation is determined by the district...

33 CFR 332.3 - General compensatory mitigation requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... wetland maps; soil surveys; U.S. Geological Survey topographic and hydrologic maps; aerial photographs... appropriate quantitative assessment tools, where available; (iii) Preservation is determined by the district...

33 CFR 332.3 - General compensatory mitigation requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... wetland maps; soil surveys; U.S. Geological Survey topographic and hydrologic maps; aerial photographs... appropriate quantitative assessment tools, where available; (iii) Preservation is determined by the district...

33 CFR 332.3 - General compensatory mitigation requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... wetland maps; soil surveys; U.S. Geological Survey topographic and hydrologic maps; aerial photographs... appropriate quantitative assessment tools, where available; (iii) Preservation is determined by the district...

Use of USLE/GIS methodology for predicting soil loss in a semiarid agricultural watershed.

PubMed

Erdogan, Emrah H; Erpul, Günay; Bayramin, Ilhami

2007-08-01

The Universal Soil Loss Equation (USLE) is an erosion model to estimate average soil loss that would generally result from splash, sheet, and rill erosion from agricultural plots. Recently, use of USLE has been extended as a useful tool predicting soil losses and planning control practices in agricultural watersheds by the effective integration of the GIS-based procedures to estimate the factor values in a grid cell basis. This study was performed in the Kazan Watershed located in the central Anatolia, Turkey, to predict soil erosion risk by the USLE/GIS methodology for planning conservation measures in the site. Rain erosivity (R), soil erodibility (K), and cover management factor (C) values of the model were calculated from erosivity map, soil map, and land use map of Turkey, respectively. R values were site-specifically corrected using DEM and climatic data. The topographical and hydrological effects on the soil loss were characterized by LS factor evaluated by the flow accumulation tool using DEM and watershed delineation techniques. From resulting soil loss map of the watershed, the magnitude of the soil erosion was estimated in terms of the different soil units and land uses and the most erosion-prone areas where irreversible soil losses occurred were reasonably located in the Kazan watershed. This could be very useful for deciding restoration practices to control the soil erosion of the sites to be severely influenced.

Introduction of digital soil mapping techniques for the nationwide regionalization of soil condition in Hungary; the first results of the DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Szatmári, Gábor; Takács, Katalin; Bakacsi, Zsófia; Szabó, József; Dobos, Endre

2014-05-01

Due to the former soil surveys and mapping activities significant amount of soil information has accumulated in Hungary. Present soil data requirements are mainly fulfilled with these available datasets either by their direct usage or after certain specific and generally fortuitous, thematic and/or spatial inference. Due to the more and more frequently emerging discrepancies between the available and the expected data, there might be notable imperfection as for the accuracy and reliability of the delivered products. With a recently started project (DOSoReMI.hu; Digital, Optimized, Soil Related Maps and Information in Hungary) we would like to significantly extend the potential, how countrywide soil information requirements could be satisfied in Hungary. We started to compile digital soil related maps which fulfil optimally the national and international demands from points of view of thematic, spatial and temporal accuracy. The spatial resolution of the targeted countrywide, digital, thematic maps is at least 1:50.000 (approx. 50-100 meter raster resolution). DOSoReMI.hu results are also planned to contribute to the European part of GSM.net products. In addition to the auxiliary, spatial data themes related to soil forming factors and/or to indicative environmental elements we heavily lean on the various national soil databases. The set of the applied digital soil mapping techniques is gradually broadened incorporating and eventually integrating geostatistical, data mining and GIS tools. In our paper we will present the first results. - Regression kriging (RK) has been used for the spatial inference of certain quantitative data, like particle size distribution components, rootable depth and organic matter content. In the course of RK-based mapping spatially segmented categorical information provided by the SMUs of Digital Kreybig Soil Information System (DKSIS) has been also used in the form of indicator variables. - Classification and regression trees (CART) were used to improve the spatial resolution of category-type soil maps (thematic downscaling), like genetic soil type and soil productivity maps. The approach was justified by the fact that certain thematic soil maps are not available in the required scale. Decision trees were applied for the understanding of the soil-landscape models involved in existing soil maps, and for the post-formalization of survey/compilation rules. The relationships identified and expressed in decision rules made the creation of spatially refined maps possible with the aid of high resolution environmental auxiliary variables. Among these co-variables, a special role was played by larger scale spatial soil information with diverse attributes. As a next step, the testing of random forests for the same purposes has been started. - Due to the simultaneous richness of available Hungarian legacy soil data, spatial inference methods and auxiliary environmental information, there is a high versatility of possible approaches for the compilation of a given soil (related) map. This suggests the opportunity of optimization. For the creation of an object specific soil (related) map with predefined parameters (resolution, accuracy, reliability etc.) one might intend to identify the optimum set of soil data, method and auxiliary co-variables optimized for the resources (data costs, computation requirements etc.). The first findings on the inclusion and joint usage of spatial soil data as well as on the consistency of various evaluations of the result maps will be also presented. Acknowledgement: Our work has been supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Elaboration of a framework for the compilation of countrywide, digital maps for the satisfaction of recent demands on spatial, soil related information in Hungary

NASA Astrophysics Data System (ADS)

Pásztor, László; Dobos, Endre; Szabó, József; Bakacsi, Zsófia; Laborczi, Annamária

2013-04-01

There is a heap of evidences that demands on soil related information have been significant worldwide and it is still increasing. Soil maps were typically used for long time to satisfy these demands. By the spread of GI technology, spatial soil information systems (SSIS) and digital soil mapping (DSM) took the role of traditional soil maps. Due to the relatively high costs of data collection, new conventional soil surveys and inventories are getting less and less frequent, which fact valorises legacy soil information and the systems which are serving the their digitally processed version. The existing data contain a wealth of information that can be exploited by proper methodology. Not only the degree of current needs for soil information has changed but also its nature. Traditionally the agricultural functions of soils were focussed on, which was also reflected in the methodology of data collection and mapping. Recently the multifunctionality of soils is getting to gain more and more ground; consequently information related to additional functions of soils becomes identically important. The new types of information requirements however cannot be fulfilled generally with new data collections at least not on such a level as it was done in the frame of traditional soil surveys. Soil monitoring systems have been established for the collection of recent information on the various elements of the DPSIR (Driving Forces-Pressures-State-Impacts-Responses) framework, but the primary goal of these systems has not been mapping by all means. And definitely this is the case concerning the two recently working Hungarian soil monitoring systems. In Hungary, presently soil data requirements are fulfilled with the recently available datasets either by their direct usage or after certain specific and generally fortuitous, thematic and/or spatial inference. Due to the more and more frequently emerging discrepancies between the available and the expected data, there might be notable imperfection as for the accuracy and reliability of the delivered products. Since, similarly to the great majority of the world, large-scale, comprehensive new surveys cannot be expected in the near future, the actually available legacy data should be relied on. With a recently started project we would like to significantly extend the potential, how countrywide soil information requirements could be satisfied. In the frame of our project we plan the execution of spatial and thematic data mining of significant amount of soil related information available in the form of legacy soil data as well as digital databases and spatial soil information systems. In the course of the analyses we will lean on auxiliary, spatial data themes related to environmental elements. Based on the established relationships we will convert and integrate the specific data sets for the regionalization of the various, derived soil parameters. By the aid of GIS and geostatistical tools we will carry out the spatial extension of certain pedological variables featuring the (including degradation) state, processes or functions of soils. We plan to compile digital soil maps which fulfil optimally the national and international demands from points of view of thematic, spatial and temporal accuracy. The targeted spatial resolution of the proposed countrywide, digital, thematic soil property and function maps is at least 1:50.000 (approx. 50-100 meter raster). Our stressful objective is the definite solution of the regionalization of the information collected in the frame of two recent, contemporary, national, systematic soil data collection (not designed for mapping purpose) on the recent state of soils, in order to produce countrywide maps for the spatial inventory of certain soil properties, processes and functions with sufficient accuracy and reliability.

Operational Mapping of Soil Moisture Using Synthetic Aperture Radar Data: Application to the Touch Basin (France)

PubMed Central

Baghdadi, Nicolas; Aubert, Maelle; Cerdan, Olivier; Franchistéguy, Laurent; Viel, Christian; Martin, Eric; Zribi, Mehrez; Desprats, Jean François

2007-01-01

Soil moisture is a key parameter in different environmental applications, such as hydrology and natural risk assessment. In this paper, surface soil moisture mapping was carried out over a basin in France using satellite synthetic aperture radar (SAR) images acquired in 2006 and 2007 by C-band (5.3 GHz) sensors. The comparison between soil moisture estimated from SAR data and in situ measurements shows good agreement, with a mapping accuracy better than 3%. This result shows that the monitoring of soil moisture from SAR images is possible in operational phase. Moreover, moistures simulated by the operational Météo-France ISBA soil-vegetation-atmosphere transfer model in the SIM-Safran-ISBA-Modcou chain were compared to radar moisture estimates to validate its pertinence. The difference between ISBA simulations and radar estimates fluctuates between 0.4 and 10% (RMSE). The comparison between ISBA and gravimetric measurements of the 12 March 2007 shows a RMSE of about 6%. Generally, these results are very encouraging. Results show also that the soil moisture estimated from SAR images is not correlated with the textural units defined in the European Soil Geographical Database (SGDBE) at 1:1000000 scale. However, dependence was observed between texture maps and ISBA moisture. This dependence is induced by the use of the texture map as an input parameter in the ISBA model. Even if this parameter is very important for soil moisture estimations, radar results shown that the textural map scale at 1:1000000 is not appropriate to differentiate moistures zones. PMID:28903238

Characterizing Watersheds with Geophysical Methods: Some uses of GPR and EMI in Hydropedological Investigations.

NASA Astrophysics Data System (ADS)

Doolittle, J.; Lin, H.; Jenkinson, B.; Zhou, X.

2006-05-01

The USDA-NRCS and its cooperators use ground-penetrating radar (GPR) and electromagnetic induction (EMI) as rapid, noninvasive tools to support soil surveys at different scales and levels of resolution. The effective use of GPR is site-specific and generally restricted to soils having low electrical conductivity (e.g., soils with low clay and soluble salt contents). In suitable soils, GPR provides high resolution data, which are used to estimate depths to soil horizons and geologic layers that restrict, redirect, and/or concentrate the flow of water through landscapes. In areas of coarse-textured soils, GPR has been used to map spatiotemporal variations in water-table depths and local ground-water flow patterns. Compared with GPR, EMI can be effectively used across a broader spectrum of soils and spatial scales, but provides lower resolution of subsurface features. EMI is used to refine and improve soil maps prepared with traditional soil survey methods. Differences in apparent conductivity (ECa) are associated with different soils and soil properties (e.g., clay, moisture and soluble salt contents). Apparent conductivity maps provide an additional layer of information, which directs soil sampling, aids the identification and delineation of some soil polygons, and enhances the quality of soil maps. More recently, these tools were used to characterize the hydropedological character of a small, steeply sloping, forested watershed. Within the watershed, EMI was used to characterize the principal soil-landscape components, and GPR was used to provide high resolution data on soil depth and layering within colluvial deposits located in swales and depressional areas.

Hungarian contribution to the Global Soil Organic Carbon Map (GSOC17) using advanced machine learning algorithms and geostatistics

NASA Astrophysics Data System (ADS)

Szatmári, Gábor; Laborczi, Annamária; Takács, Katalin; Pásztor, László

2017-04-01

The knowledge about soil organic carbon (SOC) baselines and changes, and the detection of vulnerable hot spots for SOC losses and gains under climate change and changed land management is still fairly limited. Thus Global Soil Partnership (GSP) has been requested to develop a global SOC mapping campaign by 2017. GSPs concept builds on official national data sets, therefore, a bottom-up (country-driven) approach is pursued. The elaborated Hungarian methodology suits the general specifications of GSOC17 provided by GSP. The input data for GSOC17@HU mapping approach has involved legacy soil data bases, as well as proper environmental covariates related to the main soil forming factors, such as climate, organisms, relief and parent material. Nowadays, digital soil mapping (DSM) highly relies on the assumption that soil properties of interest can be modelled as a sum of a deterministic and stochastic component, which can be treated and modelled separately. We also adopted this assumption in our methodology. In practice, multiple regression techniques are commonly used to model the deterministic part. However, this global (and usually linear) models commonly oversimplify the often complex and non-linear relationship, which has a crucial effect on the resulted soil maps. Thus, we integrated machine learning algorithms (namely random forest and quantile regression forest) in the elaborated methodology, supposing then to be more suitable for the problem in hand. This approach has enable us to model the GSOC17 soil properties in that complex and non-linear forms as the soil itself. Furthermore, it has enable us to model and assess the uncertainty of the results, which is highly relevant in decision making. The applied methodology has used geostatistical approach to model the stochastic part of the spatial variability of the soil properties of interest. We created GSOC17@HU map with 1 km grid resolution according to the GSPs specifications. The map contributes to the GSPs GSOC17 proposals, as well as to the development of global soil information system under GSP Pillar 4 on soil data and information. However, we elaborated our adherent code (created in R software environment) in such a way that it can be improved, specified and applied for further uses. Hence, it opens the door to create countrywide map(s) with higher grid resolution for SOC (or other soil related properties) using the advanced methodology, as well as to contribute and support the SOC (or other soil) related country level decision making. Our paper will present the soil mapping methodology itself, the resulted GSOC17@HU map, some of our conclusions drawn from the experiences and their effects on the further uses. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Applications of Skylab EREP photographs to mapping of landforms and environmental geology in the Great Plains and Midwest. [Illinois, Iowa, Kansas, Missouri, Nebraska, and South Dakota

NASA Technical Reports Server (NTRS)

Morrison, R. B. (Principal Investigator)

1974-01-01

The author has identified the following significant results. The utility of Skylab 2 and 3 S-190A multispectral photos for environmental-geologic/geomorphic applications is being tested by using them to prepare 1:250,000-scale maps of geomorphic features, surficial geology, geologic linear features, and soil associations of large, representative parts of the Great Plains and Midwest. Parts of Nebraska, Iowa, Missouri, and South Dakota were mapped. The maps were prepared primarily by interpretation of the S-190A photos, supplemented by information from topographic, geologic, and soil maps and reports. The color band provides the greatest information on geology, soils, and geomorphology; its resolution also is the best of all the multispectral bands and permits maximum detail of mapping. The color-IR band shows well the differences in soil drainage and moisture, and vegetative types, but has only moderate resolution. The B/W-red band is superior for topographic detail and stream alinements. The B/W-infrared bands best show differences in soil moisture and drainage but have poor resolution, especially those from SL 2. The B/W-green band generally is so low contrast and degraded by haze as to be nearly useless. Where stereoscopic coverage is provided, interpretation and mapping are done most efficiently using a Kern PG-2 stereoplotter.

Large-extent digital soil mapping approaches for total soil depth

NASA Astrophysics Data System (ADS)

Mulder, Titia; Lacoste, Marine; Saby, Nicolas P. A.; Arrouays, Dominique

2015-04-01

Total soil depth (SDt) plays a key role in supporting various ecosystem services and properties, including plant growth, water availability and carbon stocks. Therefore, predictive mapping of SDt has been included as one of the deliverables within the GlobalSoilMap project. In this work SDt was predicted for France following the directions of GlobalSoilMap, which requires modelling at 90m resolution. This first method, further referred to as DM, consisted of modelling the deterministic trend in SDt using data mining, followed by a bias correction and ordinary kriging of the residuals. Considering the total surface area of France, being about 540K km2, employed methods may need to be able dealing with large data sets. Therefore, a second method, multi-resolution kriging (MrK) for large datasets, was implemented. This method consisted of modelling the deterministic trend by a linear model, followed by interpolation of the residuals. For the two methods, the general trend was assumed to be explained by the biotic and abiotic environmental conditions, as described by the Soil-Landscape paradigm. The mapping accuracy was evaluated by an internal validation and its concordance with previous soil maps. In addition, the prediction interval for DM and the confidence interval for MrK were determined. Finally, the opportunities and limitations of both approaches were evaluated. The results showed consistency in mapped spatial patterns and a good prediction of the mean values. DM was better capable in predicting extreme values due to the bias correction. Also, DM was more powerful in capturing the deterministic trend than the linear model of the MrK approach. However, MrK was found to be more straightforward and flexible in delivering spatial explicit uncertainty measures. The validation indicated that DM was more accurate than MrK. Improvements for DM may be expected by predicting soil depth classes. MrK shows potential for modelling beyond the country level, at high resolution. Large-extent digital soil mapping approaches for SDt may be improved by (1) taking into account SDt observations which are censored and (2) using high-resolution biotic and abiotic environmental data. The latter may improve modelling the soil-landscape interactions influencing soil pedogenesis. Concluding, this work provided a robust and reproducible method (DM) for high-resolution soil property modelling, in accordance with the GlobalSoilMap requirements and an efficient alternative for large-extent digital soil mapping (MrK).

Leveraging Machine Learning to Estimate Soil Salinity through Satellite-Based Remote Sensing

NASA Astrophysics Data System (ADS)

Welle, P.; Ravanbakhsh, S.; Póczos, B.; Mauter, M.

2016-12-01

Human-induced salinization of agricultural soils is a growing problem which now affects an estimated 76 million hectares and causes billions of dollars of lost agricultural revenues annually. While there are indications that soil salinization is increasing in extent, current assessments of global salinity levels are outdated and rely heavily on expert opinion due to the prohibitive cost of a worldwide sampling campaign. A more practical alternative to field sampling may be earth observation through remote sensing, which takes advantage of the distinct spectral signature of salts in order to estimate soil conductivity. Recent efforts to map salinity using remote sensing have been met with limited success due to tractability issues of managing the computational load associated with large amounts of satellite data. In this study, we use Google Earth Engine to create composite satellite soil datasets, which combine data from multiple sources and sensors. These composite datasets contain pixel-level surface reflectance values for dates in which the algorithm is most confident that the surface contains bare soil. We leverage the detailed soil maps created and updated by the United States Geological Survey as label data and apply machine learning regression techniques such as Gaussian processes to learn a smooth mapping from surface reflection to noisy estimates of salinity. We also explore a semi-supervised approach using deep generative convolutional networks to leverage the abundance of unlabeled satellite images in producing better estimates for salinity values where we have relatively fewer measurements across the globe. The general method results in two significant contributions: (1) an algorithm that can be used to predict levels of soil salinity in regions without detailed soil maps and (2) a general framework that serves as an example for how remote sensing can be paired with extensive label data to generate methods for prediction of physical phenomenon.

Mapping Soil pH Buffering Capacity of Selected Fields

NASA Technical Reports Server (NTRS)

Weaver, A. R.; Kissel, D. E.; Chen, F.; West, L. T.; Adkins, W.; Rickman, D.; Luvall, J. C.

2003-01-01

Soil pH buffering capacity, since it varies spatially within crop production fields, may be used to define sampling zones to assess lime requirement, or for modeling changes in soil pH when acid forming fertilizers or manures are added to a field. Our objective was to develop a procedure to map this soil property. One hundred thirty six soil samples (0 to 15 cm depth) from three Georgia Coastal Plain fields were titrated with calcium hydroxide to characterize differences in pH buffering capacity of the soils. Since the relationship between soil pH and added calcium hydroxide was approximately linear for all samples up to pH 6.5, the slope values of these linear relationships for all soils were regressed on the organic C and clay contents of the 136 soil samples using multiple linear regression. The equation that fit the data best was b (slope of pH vs. lime added) = 0.00029 - 0.00003 * % clay + 0.00135 * % O/C, r(exp 2) = 0.68. This equation was applied within geographic information system (GIS) software to create maps of soil pH buffering capacity for the three fields. When the mapped values of the pH buffering capacity were compared with measured values for a total of 18 locations in the three fields, there was good general agreement. A regression of directly measured pH buffering capacities on mapped pH buffering capacities at the field locations for these samples gave an r(exp 2) of 0.88 with a slope of 1.04 for a group of soils that varied approximately tenfold in their pH buffering capacities.

Peculiarities of changes in the soil cover of landscapes adjacent to a megalopolis

NASA Astrophysics Data System (ADS)

Lazareva, Margarita; Aparin, Boris; Sukhacheva, Elena

2017-04-01

The progressive growth of cities has a significant impact on the soil cover of territories adjacent to the same. Megalopolises are centers of anthropogenic impact on the soils. Generally, forms and intensity of the urban impact on the soil cover weaken with increasing distance from the city's boundaries. In this respect, ample opportunities for the analysis of urban impact on the adjacent territories are provided by the study of the soil cover in the Leningrad Region (the LR). Saint Petersburg is a major European megalopolis, which is the administrative center of the LR. The time period of Saint Petersburg's impact on the environment does not exceed 300 years, which allows us to identify very clearly the character and areas of its impact on the soil cover. Over the past decades, there have been significant changes in the soils and the soil cover of the LR. In a large territory, there appeared new anthropogenic soils and soil cover organization forms, having no natural analogues, with a dramatic increase in the surface area of degraded soils. To access the current state of soil cover, to identify the role of anthropogenic factors of changes in this state; to carry out land reclamation, remediation and rehabilitation measures; to perform land cadastral valuation etc., we need an information resource containing data on the current state of soils and soil cover in the LR, the key element of which should be a map. We carried out mapping and created a 1:200 000 digital soil map (DSM) for the LR's territories. Diagnostics of soil contours were performed using traditionally drawn-up (paper) maps of soils and soil-formation factors; satellite images (Google, Yandex); data of remote sensing (Spot 5, Landsat 7,8); digital maps of main soil-formation factors (topographical ones, etc.). The digital soil map of the LR has been created in the geographic information system - QGIS. The map clarifies the contours of natural soils and soil combinations, and shows, for the first time, the contours of: - non-soil formations; - soils of the initial soil formation; - soils of agricultural lands within their existing boundaries; - soils and soil combinations that are specific for human settlements and horticultural land plots; - fallow lands; - anthropogenically disturbed soils. During the analysis of the created digital medium-scale soil map, we identified some changes in the soil cover of the territories adjacent to Saint Petersburg. Virtually in all the landscapes, we found a large number of soil cover structures, the components of which, along with natural soils, are anthropogenically disturbed soils, anthropogenic soils and non-soil formations. We revealed that the human impact on the soil cover is manifested within the range that varies from insignificant changes in soil parameters to radical transformations of the soil profile, complete destruction of soil and "creation" of new soil forms and soil cover organization forms. We have developed a typology of anthropogenically changed and anthropogenically created soil cover structures, taking into consideration the types of the economic impact on and the quality of environmental functions performed by the soils.

Reports and maps of the Military Geology Unit, 1942-1975

USGS Publications Warehouse

Leith, William; Bonham, Selma

1997-01-01

Included here are reports and maps which were prepared in the Military Geology Unit of the U. S. Geological Survey from 1942 through 1975. In addition to the references prepared primarily for military use and listed here, more than 200 reports of more general geologic interest were prepared for publication as Survey bulletins and professional papers and in outside journals. These reports are listed in "Publications of the Geological Survey" and other bibliographies. Military Geology reports generally include basic subjects such as rock types, soils, water resources, landforms and vegetation, as well as interpretive subjects such as suitability of terrain for cross-country movement and for construction of roads and airfields in areas throughout the world. Reports on specific areas range from generalized texts with small scab maps derived from published sources to detailed texts with large-scale maps commonly based on photo-interpretation and, especially for Alaska and western Pacific islands, involving field mapping. Other reports treat topics of interest in military geology without reference to specific areas. A number of reports covering the moon include the first photogeologic map of the near side.Authors are cited for some kinds of reports; however, many intelligence reports were published anonymously. Most of the reports were prepared by teams made up mainly of geologists but commonly including soils scientists, botanists, climatologists and geographers. Nearly all the soil scientists and climatologists were members of the World Soil Geography Unit, Soil Survey, Soil Conservation Service, U. S. Department of Agriculture. Manuscripts from this Unit were passed through a common review and other processing, as were the manuscripts originating in the Military Geology office, to be issued under the aegis of the latter. In some instances where it has not been possible to list all authors, names of project supervisors are given.File copies of many of the Military Geology reports prepared since 1975 are kept in the Special Geologic Studies Group, U.S. Geological Survey, National Center, Reston, and may be examined there by appropriately cleared persons. Additionally, copies of many of the unclassified studies are in the U.S. Geological Survey Library. Some of the older reports are in the files of the Terrain Analysis Center, Fort Belvoir, Virginia, and other offices within the Corps of Engineers. Most of the reports are out of print and many of the other studies are no longer available.

Prediction of Vehicle Mobility on Large-Scale Soft-Soil Terrain Maps Using Physics-Based Simulation

DTIC Science & Technology

2016-08-04

soil type. The modeling approach is based on (i) a seamless integration of multibody dynamics and discrete element method (DEM) solvers, and (ii...ensure that the vehicle follows a desired path. The soil is modeled as a Discrete Element Model (DEM) with a general cohesive material model that is

Dependence of the cyclization of branched tetraethers (CBT) on soil moisture in the Chinese Loess Plateau and the adjacent areas: implications for palaeorainfall reconstructions

NASA Astrophysics Data System (ADS)

Wang, H.; Liu, W.; Zhang, C. L.

2014-06-01

Branched glycerol dialkyl glycerol tetraethers (bGDGTs) have been show promising for continental paleotemperature studies in loess-paleosol sequences (LPSs). Thus far, however, little is known about the effect of soil moisture on their distributions on the Chinese Loess Plateau (CLP). In this study, the relationships between environmental variables and the cyclization of bGDGTs (the so called CBT index) were investigated in a comprehensive set of surface soils in the CLP and its adjacent arid/semi-arid areas. We find that CBT correlates best with soil water content (SWC) or mean annual precipitation (MAP) for the total sample set. Particularly for the CLP soils, there is a significant positive relationship between CBT and MAP (CBT = -0.0021 · MAP + 1.7, n = 37, R2 = 0.87; MAP range: 210-680 mm). This indicates that CBT is mainly controlled by soil moisture in the alkalescent soils (pH > 7) in arid/semi-arid regions, where it is not sensitive to soil pH. Therefore, we suggest that CBT can potentially be used as a palaeorainfall proxy on the CLP. According to the preliminary CBT-MAP relationship for modern CLP soils, palaeorainfall history was reconstructed from three LPSs (Yuanbao, Lantian, and Mangshan) with published bGDGT data spanning the past 70 ka. The CBT-derived MAP records of the three sites consistently show precession-driven variations resembling the speleothem δ18O monsoon record, and are also in general accord with the fluctuations of the respective magnetic susceptibility (MS) record, supporting CBT as a reasonable proxy for palaeorainfall reconstruction in LPS studies. Moreover, the comparison of CBT-derived MAP and bGDGT-derived temperature may enable us to further assess the relative timing and magnitude of hydrological and thermal changes on the CLP, independent of chronology.

Potential of EnMAP spaceborne imaging spectroscopy for the prediction of common surface soil properties and expected accuracy

NASA Astrophysics Data System (ADS)

Chabrillat, Sabine; Foerster, Saskia; Steinberg, Andreas; Stevens, Antoine; Segl, Karl

2016-04-01

There is a renewed awareness of the finite nature of the world's soil resources, growing concern about soil security, and significant uncertainties about the carrying capacity of the planet. As a consequence, soil scientists are being challenged to provide regular assessments of soil conditions from local through to global scales. However, only a few countries have the necessary survey and monitoring programs to meet these new needs and existing global data sets are out-of-date. A particular issue is the clear demand for a new area-wide regional to global coverage with accurate, up-to-date, and spatially referenced soil information as expressed by the modeling scientific community, farmers and land users, and policy and decision makers. Soil spectroscopy from remote sensing observations based on studies from the laboratory scale to the airborne scale has been shown to be a proven method for the quantitative prediction of key soil surface properties in local areas for exposed soils in appropriate surface conditions such as low vegetation cover and low water content. With the upcoming launch of the next generation of hyperspectral satellite sensors in the next 3 to 5 years (EnMAP, HISUI, PRISMA, SHALOM), a great potential for the global mapping and monitoring of soil properties is appearing. Nevertheless, the capabilities to extend the soil properties current spectral modeling from local to regional scales are still to be demonstrated using robust methods. In particular, three central questions are at the forefront of research nowadays: a) methodological developments toward improved algorithms and operational tools for the extraction of soil properties, b) up scaling from the laboratory into space domain, and c) demonstration of the potential of upcoming satellite systems and expected accuracy of soil maps. In this study, airborne imaging spectroscopy data from several test sites are used to simulate EnMAP satellite images at 30 m scale. Then, different soil algorithms are examined based on the analyses of chemical-physical features from the soil spectral reflectance and/or multivariate established techniques such as Partial-Least Squares PLS, Support-Vector Machine SVM, to determine common surface soil properties, in particular soil organic carbon (SOC), clay and iron oxide content. Results show that EnMAP is able to predict clay, free iron oxide, and SOC with an RV2 between 0.53 and 0.67 compared to airborne imagery with RV2 between 0.64 and 0.74. The correlation between EnMAP and airborne imagery prediction results is high (Pearson coefficients between 0.84 and 0.91). Furthermore, spatial distribution is coherent between the airborne mapping and simulated EnMAP mapping as shown with a spatial structure analysis. In general, this paper demonstrates the high potential of upcoming spaceborne hyperspectral missions for soil science studies but also shows the need for future adapted strategies to fulfill the entire potential of soil spectroscopy for orbital utilization.

The Soil Atlas of Africa: raising awareness and educate to the importance of soil

NASA Astrophysics Data System (ADS)

Dewitte, Olivier; Jones, Arwyn; Bosco, Claudio; Spaargaren, Otto; Montanarella, Luca

2010-05-01

The richness of African soil resources need to be protected for future generations. A number of threats are affecting the functioning of African soils, not only for the purpose of agricultural production, but also for other important environmental services that soil delivers to all of us. This is of particular importance once we know that many health-related problems in Africa are indirectly related to the services of soils. To raise the awareness of the general public, policy makers and other scientists to the importance of soil in Africa, the Joint Research Centre of the European Commission is to produce the first ever Soil Atlas of Africa. This is in collaboration with the African Union Commission, the Food and Agriculture Organization of the United Nations (FAO), the Africa Soil Science Society, ISRIC - World Soil Information and scientists from both Europe and Africa. The Atlas compiles existing information on different soil types as easily understandable maps (both at regional and continental scale) covering the African continent. The Soil Atlas of Africa intends to produce derived maps at continental scale with descriptive text (e.g. vulnerability to desertification, soil nutrient status, carbon stocks and sequestration potential, irrigable areas and water resources) as well as specific maps to illustrate threats such as soil erosion for instance. For each regional overview, large scale examples of soil maps and derived products are presented too. The Atlas will be published as a hardcover book containing 174 A3 pages, which will allow soils maps to be displayed at the A2 scale. Both French and English versions of the Atlas will be edited. The Atlas will be sold at a low cost and will be for free for educational purpose (Schools and Universities). A digital version on CD and eventually freely downloadable on internet will also be available. Together with the publication of the Atlas, associated datasets on soil characteristics for Africa will be made available. These datasets will be useful for making broad distinction among soil types and provide general trends at the global and regional scales. The datasets will be made accessible for free downloading from the portals of the SOIL Action (http://eusoils.jrc.ec.europa.eu/) and the ACP Observatory for Sustainable Development (http://acpobservatory.jrc.ec.europa.eu). The Atlas links the theme of soil with rural development and, at the same time, supports the goals of the EU Thematic Strategy for Soil Protection in conserving a threatened natural resource that is vital to human existence. Not only climate change, but also desertification and loss of biodiversity are strongly affecting soils globally, making the "Soil Atlas of Africa" relevant to a much larger community of stakeholders involved in the implementation of the three "Rio-Conventions" and allowing to explore possible synergies among international multilateral agreements towards global soil protection.

Mapping iron oxides and the color of Australian soil using visible-near-infrared reflectance spectra

NASA Astrophysics Data System (ADS)

Viscarra Rossel, R. A.; Bui, E. N.; de Caritat, P.; McKenzie, N. J.

2010-12-01

Iron (Fe) oxide mineralogy in most Australian soils is poorly characterized, even though Fe oxides play an important role in soil function. Fe oxides reflect the conditions of pH, redox potential, moisture, and temperature in the soil environment. The strong pigmenting effect of Fe oxides gives most soils their color, which is largely a reflection of the soil's Fe mineralogy. Visible-near-infrared (vis-NIR) spectroscopy can be used to identify and measure the abundance of certain Fe oxides in soil, and the visible range can be used to derive tristimuli soil color information. The aims of this paper are (1) to measure the abundance of hematite and goethite in Australian soils from their vis-NIR spectra, (2) to compare these results to measurements of soil color, and (3) to describe the spatial variability of hematite, goethite, and soil color and map their distribution across Australia. We measured the spectra of 4606 surface soil samples from across Australia using a vis-NIR spectrometer with a wavelength range of 350-2500 nm. We determined the Fe oxide abundance for each sample using the diagnostic absorption features of hematite (near 880 nm) and goethite (near 920 nm) and derived a normalized iron oxide difference index (NIODI) to better discriminate between them. The NIODI was generalized across Australia with its spatial uncertainty using sequential indicator simulation, which resulted in a map of the probability of the occurrence of hematite and goethite. We also derived soil RGB color from the spectra and mapped its distribution and uncertainty across the country using sequential Gaussian simulations. The simulated RGB color values were made into a composite true color image and were also converted to Munsell hue, value, and chroma. These color maps were compared to the map of the NIODI, and both were used to interpret our results. The work presented here was validated by randomly splitting the data into training and test data sets, as well as by comparing our results to existing studies on the distribution of Fe oxides in Australian soils.

The threat of soil salinity: A European scale review.

PubMed

Daliakopoulos, I N; Tsanis, I K; Koutroulis, A; Kourgialas, N N; Varouchakis, A E; Karatzas, G P; Ritsema, C J

2016-12-15

Soil salinisation is one of the major soil degradation threats occurring in Europe. The effects of salinisation can be observed in numerous vital ecological and non-ecological soil functions. Drivers of salinisation can be detected both in the natural and man-made environment, with climate and the foreseen climate change also playing an important role. This review outlines the state of the art concerning drivers and pressures, key indicators as well as monitoring, modeling and mapping methods for soil salinity. Furthermore, an overview of the effect of salinisation on soil functions and the respective mechanism is presented. Finally, the state of salinisation in Europe is presented according to the most recent literature and a synthesis of consistent datasets. We conclude that future research in the field of soil salinisation should be focused on among others carbon dynamics of saline soil, further exploration of remote sensing of soil properties and the harmonization and enrichment of soil salinity maps across Europe within a general context of a soil threat monitoring system to support policies and strategies for the protection of European soils. Copyright © 2016 Elsevier B.V. All rights reserved.

Turning soil survey data into digital soil maps in the Energy Region Eger Research Model Area

NASA Astrophysics Data System (ADS)

Pásztor, László; Dobos, Anna; Kürti, Lívia; Takács, Katalin; Laborczi, Annamária

2015-04-01

Agria-Innoregion Knowledge Centre of the Eszterházy Károly College has carried out targeted basic researches in the field of renewable energy sources and climate change in the framework of TÁMOP-4.2.2.A-11/1/KONV project. The project has covered certain issues, which require the specific knowledge of the soil cover; for example: (i) investigation of quantitative and qualitative characteristics of natural and landscape resources; (ii) determination of local amount and characteristics of renewable energy sources; (iii) natural/environmental risk analysis by surveying the risk factors. The Energy Region Eger Research Model Area consists of 23 villages and is located in North-Hungary, at the Western part of Bükkalja. Bükkalja is a pediment surface with erosional valleys and dense river network. The diverse morphology of this area results diversity in soil types and soil properties as well. There was large-scale (1:10,000 and 1:25,000 scale) soil mappings in this area in the 1960's and 1970's which provided soil maps, but with reduced spatial coverage and not with fully functional thematics. To achive the recent tasks (like planning suitable/optimal land-use system, estimating biomass production and development of agricultural and ecomonic systems in terms of sustainable regional development) new survey was planned and carried out by the staff of the College. To map the soils in the study area 10 to 22 soil profiles were uncovered per settlement in 2013 and 2014. Field work was carried out according to the FAO Guidelines for Soil Description and WRB soil classification system was used for naming soils. According to the general goal of soil mapping the survey data had to be spatially extended to regionalize the collected thematic local knowledge related to soil cover. Firstly three thematic maps were compiled by digital soil mapping methods: thickness of topsoil, genetic soil type and rate of surface erosion. High resolution digital elevation model, Earth observation imagery, geology and land cover maps were used as spatial ancillary environmental variables related to soil forming processes. Regression kriging (RK) has been used for the spatial inference of quantitative data (thickness of topsoil); classification and regression trees (CART) were applied for the spatial inference of category type information (genetic soil type and rate of surface erosion) with the aid of the available and properly preprocessed auxiliary co-variables. The applied spatial resolution was 25 meters. The deduced digital soil maps hopefully will significantly promote to plan sustainable economic model in the region which can provide protection and regeneration of local natural conditions and potentials for local inhabitants for a long time. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167) and TÁMOP-4.2.2.A-11/1/KONV project.

Geomorphically based predictive mapping of soil thickness in upland watersheds

NASA Astrophysics Data System (ADS)

Pelletier, Jon D.; Rasmussen, Craig

2009-09-01

The hydrologic response of upland watersheds is strongly controlled by soil (regolith) thickness. Despite the need to quantify soil thickness for input into hydrologic models, there is currently no widely used, geomorphically based method for doing so. In this paper we describe and illustrate a new method for predictive mapping of soil thicknesses using high-resolution topographic data, numerical modeling, and field-based calibration. The model framework works directly with input digital elevation model data to predict soil thicknesses assuming a long-term balance between soil production and erosion. Erosion rates in the model are quantified using one of three geomorphically based sediment transport models: nonlinear slope-dependent transport, nonlinear area- and slope-dependent transport, and nonlinear depth- and slope-dependent transport. The model balances soil production and erosion locally to predict a family of solutions corresponding to a range of values of two unconstrained model parameters. A small number of field-based soil thickness measurements can then be used to calibrate the local value of those unconstrained parameters, thereby constraining which solution is applicable at a particular study site. As an illustration, the model is used to predictively map soil thicknesses in two small, ˜0.1 km2, drainage basins in the Marshall Gulch watershed, a semiarid drainage basin in the Santa Catalina Mountains of Pima County, Arizona. Field observations and calibration data indicate that the nonlinear depth- and slope-dependent sediment transport model is the most appropriate transport model for this site. The resulting framework provides a generally applicable, geomorphically based tool for predictive mapping of soil thickness using high-resolution topographic data sets.

Impact of Plant Functional Types on Coherence Between Precipitation and Soil Moisture: A Wavelet Analysis

NASA Astrophysics Data System (ADS)

Liu, Qi; Hao, Yonghong; Stebler, Elaine; Tanaka, Nobuaki; Zou, Chris B.

2017-12-01

Mapping the spatiotemporal patterns of soil moisture within heterogeneous landscapes is important for resource management and for the understanding of hydrological processes. A critical challenge in this mapping is comparing remotely sensed or in situ observations from areas with different vegetation cover but subject to the same precipitation regime. We address this challenge by wavelet analysis of multiyear observations of soil moisture profiles from adjacent areas with contrasting plant functional types (grassland, woodland, and encroached) and precipitation. The analysis reveals the differing soil moisture patterns and dynamics between plant functional types. The coherence at high-frequency periodicities between precipitation and soil moisture generally decreases with depth but this is much more pronounced under woodland compared to grassland. Wavelet analysis provides new insights on soil moisture dynamics across plant functional types and is useful for assessing differences and similarities in landscapes with heterogeneous vegetation cover.

Chemical-biogeographic survey of secondary metabolism in soil.

PubMed

Charlop-Powers, Zachary; Owen, Jeremy G; Reddy, Boojala Vijay B; Ternei, Melinda A; Brady, Sean F

2014-03-11

In this study, we compare biosynthetic gene richness and diversity of 96 soil microbiomes from diverse environments found throughout the southwestern and northeastern regions of the United States. The 454-pyroseqencing of nonribosomal peptide adenylation (AD) and polyketide ketosynthase (KS) domain fragments amplified from these microbiomes provide a means to evaluate the variation of secondary metabolite biosynthetic diversity in different soil environments. Through soil composition and AD- and KS-amplicon richness analysis, we identify soil types with elevated biosynthetic potential. In general, arid soils show the richest observed biosynthetic diversity, whereas brackish sediments and pine forest soils show the least. By mapping individual environmental amplicon sequences to sequences derived from functionally characterized biosynthetic gene clusters, we identified conserved soil type-specific secondary metabolome enrichment patterns despite significant sample-to-sample sequence variation. These data are used to create chemical biogeographic distribution maps for biomedically valuable families of natural products in the environment that should prove useful for directing the discovery of bioactive natural products in the future.

Quaternary Geologic Map of the Regina 4 Degrees x 6 Degrees Quadrangle, United States and Canada

USGS Publications Warehouse

Fullerton, David S.; Christiansen, Earl A.; Schreiner, Bryan T.; Colton, Roger B.; Clayton, Lee; Bush, Charles A.; Fullerton, David S.

2007-01-01

For scientific purposes, the map differentiates Quaternary surficial deposits and materials on the basis of clast lithology or composition, matrix texture or particle size, structure, genesis, stratigraphic relations, engineering geologic properties, and relative age, as shown on the correlation diagram and indicated in the 'Description of Map Units'. Deposits of some constructional landforms, such as end moraines, are distinguished as map units. Deposits of erosional landforms, such as outwash terraces, are not distinguished, although glaciofluvial, ice-contact, fluvial, and lacustrine deposits that are mapped may be terraced. Differentiation of sequences of fluvial and glaciofluvial deposits at this scale is not possible. For practical purposes, the map is a surficial materials map. Materials are distinguished on the basis of lithology or composition, texture or particle size, and other physical, chemical, and engineering characteristics. It is not a map of soils that are recognized and classified in pedology or agronomy. Rather, it is a generalized map of soils as recognized in engineering geology, or of substrata or parent materials in which pedologic or agronomic soils are formed. As a materials map, it serves as a base from which a variety of maps for use in planning engineering, land-use planning, or land-management projects can be derived and from which a variety of maps relating to earth surface processes and Quaternary geologic history can be derived.

Farmer data sourcing. The case study of the spatial soil information maps in South Tyrol.

NASA Astrophysics Data System (ADS)

Della Chiesa, Stefano; Niedrist, Georg; Thalheimer, Martin; Hafner, Hansjörg; La Cecilia, Daniele

2017-04-01

Nord-Italian region South Tyrol is Europe's largest apple growing area exporting ca. 15% in Europe and 2% worldwide. Vineyards represent ca. 1% of Italian production. In order to deliver high quality food, most of the farmers in South Tyrol follow sustainable farming practices. One of the key practice is the sustainable soil management, where farmers collect regularly (each 5 years) soil samples and send for analyses to improve cultivation management, yield and finally profitability. However, such data generally remain inaccessible. On this regard, in South Tyrol, private interests and the public administration have established a long tradition of collaboration with the local farming industry. This has granted to the collection of large spatial and temporal database of soil analyses along all the cultivated areas. Thanks to this best practice, information on soil properties are centralized and geocoded. The large dataset consist mainly in soil information of texture, humus content, pH and microelements availability such as, K, Mg, Bor, Mn, Cu Zn. This data was finally spatialized by mean of geostatistical methods and several high-resolution digital maps were created. In this contribution, we present the best practice where farmers data source soil information in South Tyrol. Show the capability of a large spatial-temporal geocoded soil dataset to reproduce detailed digital soil property maps and to assess long-term changes in soil properties. Finally, implication and potential application are discussed.

Participatory GIS for Soil Conservation in Phewa Watershed of Nepal

NASA Astrophysics Data System (ADS)

Bhandari, K. P.

2012-07-01

Participatory Geographic Information Systems (PGIS) can integrate participatory methodologies with geo-spatial technologies for the representation of characteristic of particular place. Over the last decade, researchers use this method to integrate the local knowledge of community within a GIS and Society conceptual framework. Participatory GIS are tailored to answer specific geographic questions at the local level and their modes of implementation vary considerably across space, ranging from field-based, qualitative approaches to more complex web-based applications. These broad ranges of techniques, PGIS are becoming an effective methodology for incorporating community local knowledge into complex spatial decision-making processes. The objective of this study is to reduce the soil erosion by formulating the general rule for the soil conservation by participation of the stakeholders. The poster was prepared by satellite image, topographic map and Arc GIS software including the local knowledge. The data were collected from the focus group discussion and the individual questionnaire for incorporate the local knowledge and use it to find the risk map on the basis of economic, social and manageable physical factors for the sensitivity analysis. The soil erosion risk map is prepared by the physical factors Rainfall-runoff erosivity, Soil erodibility, Slope length, Slope steepness, Cover-management, Conservation practice using RUSLE model. After the comparison and discussion among stakeholders, researcher and export group, and the soil erosion risk map showed that socioeconomic, social and manageable physical factors management can reduce the soil erosion. The study showed that the preparation of the poster GIS map and implement this in the watershed area could reduce the soil erosion in the study area compared to the existing national policy.

Landscape scale estimation of soil carbon stock using 3D modelling.

PubMed

Veronesi, F; Corstanje, R; Mayr, T

2014-07-15

Soil C is the largest pool of carbon in the terrestrial biosphere, and yet the processes of C accumulation, transformation and loss are poorly accounted for. This, in part, is due to the fact that soil C is not uniformly distributed through the soil depth profile and most current landscape level predictions of C do not adequately account the vertical distribution of soil C. In this study, we apply a method based on simple soil specific depth functions to map the soil C stock in three-dimensions at landscape scale. We used soil C and bulk density data from the Soil Survey for England and Wales to map an area in the West Midlands region of approximately 13,948 km(2). We applied a method which describes the variation through the soil profile and interpolates this across the landscape using well established soil drivers such as relief, land cover and geology. The results indicate that this mapping method can effectively reproduce the observed variation in the soil profiles samples. The mapping results were validated using cross validation and an independent validation. The cross-validation resulted in an R(2) of 36% for soil C and 44% for BULKD. These results are generally in line with previous validated studies. In addition, an independent validation was undertaken, comparing the predictions against the National Soil Inventory (NSI) dataset. The majority of the residuals of this validation are between ± 5% of soil C. This indicates high level of accuracy in replicating topsoil values. In addition, the results were compared to a previous study estimating the carbon stock of the UK. We discuss the implications of our results within the context of soil C loss factors such as erosion and the impact on regional C process models. Copyright © 2014 Elsevier B.V. All rights reserved.

Considering the spatial-scale factor when modelling sustainable land management.

NASA Astrophysics Data System (ADS)

Bouma, Johan

2015-04-01

Considering the spatial-scale factor when modelling sustainable land management. J.Bouma Em.prof. soil science, Wageningen University, Netherlands. Modelling soil-plant processes is a necessity when exploring future effects of climate change and innovative soil management on agricultural productivity. Soil data are needed to run models and traditional soil maps and the associated databases (based on various soil Taxonomies ), have widely been applied to provide such data obtained at "representative" points in the field. Pedotransferfunctions (PTF)are used to feed simulation models, statistically relating soil survey data ( obtained at a given point in the landscape) to physical parameters for simulation, thus providing a link with soil functionality. Soil science has a basic problem: their object of study is invisible. Only point data are obtained by augering or in pits. Only occasionally roadcuts provide a better view. Extrapolating point to area data is essential for all applications and presents a basic problem for soil science, because mapping units on soil maps, named for a given soil type,may also contain other soil types and quantitative information about the composition of soil map units is usually not available. For detailed work at farm level ( 1:5000-1:10000), an alternative procedure is proposed. Based on a geostatistical analysis, onsite soil observations are made in a grid pattern with spacings based on a geostatistical analysis. Multi-year simulations are made for each point of the functional properties that are relevant for the case being studied, such as the moisture supply capacity, nitrate leaching etc. under standardized boundary conditions to allow comparisons. Functional spatial units are derived next by aggregating functional point data. These units, which have successfully functioned as the basis for precision agriculture, do not necessarily correspond with Taxonomic units but when they do the Taxonomic names should be noted . At lower landscape and watershed scale ( 1:25.000 -1:50000) digital soil mapping can provide soil data for small grids that can be used for modeling, again through pedotransferfunctions. There is a risk, however, that digital mapping results in an isolated series of projects that don't increase the knowledge base on soil functionality, e.g.linking Taxonomic names ( such as soil series) to functionality, allowing predictions of soil behavior at new sites where certain soil series occur. We therefore suggest that aside from collecting 13 soil characteristics for each grid, as occurs in digital soil mapping, also the Taxonomic name of the representative soil in the grid is recorded. At spatial scales of 1:50000 and smaller, use of Taxonomic names becomes ever more attractive because at such small scales relations between soil types and landscape features become more pronounced. But in all cases, selection of procedures should not be science-based but based on the type of questions being asked including their level of generalization. These questions are quite different at the different spatial-scale levels and so should be the procedures.

Historical Perspectives and Recommendations for revision of the Agricultural Handbook 296

USDA-ARS?s Scientific Manuscript database

While the most recent edition of Agriculture Handbook 296 was released in 2006, many of the geographic boundaries consistently mimic historic map products of generalized regional and national soil-survey maps (some dating back to the 1930s). Furthermore, the underlying concepts and technologies used...

A Brief History of Soil Mapping and Classification in the USA

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Hartemink, Alfred E.

2014-05-01

Soil maps show the distribution of soils across an area but also depict soil science theory and ideas on soil formation and classification at the time the maps were created. The national soil mapping program in the USA was established in 1899. The first nation-wide soil map was published by M. Whitney in 1909 and showed soil provinces that were largely based on geology. In 1912, G.N. Coffey published the first country-wide map based on soil properties. The map showed 5 broad soil units that used parent material, color and drainage as diagnostic criteria. The 1913 national map was produced by C.F. Marbut, H.H. Bennett, J.E. Lapham, and M.H. Lapham and showed broad physiographic units that were further subdivided into soil series, soil classes and soil types. In 1935, Marbut drafted a series of maps based on soil properties, but these maps were replaced as official U.S. soil maps in 1938 with the work of M. Baldwin, C.E. Kellogg, and J. Thorp. A series of soil maps similar to modern USA maps appeared in the 1960s with the 7th Approximation followed by revisions with the 1975 and 1999 editions of Soil Taxonomy. This review has shown that soil maps in the United States produced since the early 1900s moved initially from a geologic-based concept to a pedologic concept of soils. Later changes were from property-based systems to process-based, and then back to property-based. The information in this presentation is based on Brevik and Hartemink (2013). Brevik, E.C., and A.E. Hartemink. 2013. Soil Maps of the United States of America. Soil Science Society of America Journal 77:1117-1132. doi:10.2136/sssaj2012.0390.

How to feed environmental studies with soil information to address SDG 'Zero hunger'

NASA Astrophysics Data System (ADS)

Hendriks, Chantal; Stoorvogel, Jetse; Claessens, Lieven

2017-04-01

As pledged by UN Sustainable Development Goal (SDG) 2, there should be zero hunger, food security, improved food nutrition and sustainable agriculture by 2030. Environmental studies are essential to reach SDG 2. Soils play a crucial role, especially in addressing 'Zero hunger'. This study aims to discuss the connection between the supply and demand of soil data for environmental studies and how this connection can be improved illustrating different methods. As many studies are resource constrained, the options to collect new soil data are limited. Therefore, it is essential to use existing soil information, auxiliary data and collected field data efficiently. Existing soil data are criticised in literature as i) being dominantly qualitative, ii) being often outdated, iii) being not spatially exhaustive, iv) being only available at general scales, v) being inconsistent, and vi) lacking quality assessments. Additional field data can help to overcome some of these problems. Outdated maps can, for example, be improved by collecting additional soil data in areas where changes in soil properties are expected. Existing soil data can also provide insight in the expected soil variability and, as such, these data can be used for the design of sampling schemes. Existing soil data are also crucial input for studies on digital soil mapping because they give information on parent material and the relative age of soils. Digital soil mapping is commonly applied as an efficient method to quantitatively predict the spatial variation of soil properties. However, the efficiency of digital soil mapping may increase if we look at functional soil properties (e.g. nutrient availability, available water capacity) for the soil profile that vary in a two-dimensional space rather than at basic soil properties of individual soil layers (e.g. texture, organic matter content, nitrogen content) that vary in a three-dimensional space. Digital soil mapping techniques are based on statistical relations between soil properties and environmental variables. However, in some cases a more mechanistic approach, based on pedological knowledge, might be more convincing to predict soil properties. This study showed that the soil science community is able to provide the required soil information for environmental studies. However, there is not a single solution that provides the required soil data. Case studies are needed to prove that certain methods meet the data requirements, whereafter these case studies function as a lighthouse to other studies. We illustrate data availability and methodological innovations for a case study in Kenya, where the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) aims to contribute to SDG 2.

High-resolution mapping and spatial variability of soil organic carbon storage of permafrost-affected soils

NASA Astrophysics Data System (ADS)

Siewert, Matthias; Hugelius, Gustaf

2017-04-01

Permafrost-affected soils store large amounts of soil organic carbon (SOC). Mapping of this SOC provides a first order spatial input variable for research that relates carbon stored in permafrost regions to carbon cycle dynamics. High-resolution satellite imagery is becoming increasingly available even in circum-polar regions. The presented research highlights findings of high-resolution mapping efforts of SOC from five study areas in the northern circum-polar permafrost region. These study areas are located in Siberia (Kytalyk, Spasskaya Pad /Neleger, Lena delta), Northern Sweden (Abisko) and Northwestern Canada (Herschel Island). Our high spatial resolution analyses show how geomorphology has a strong influence on the distribution of SOC. This is organized at different spatial scales. Periglacial landforms and processes dictate local scale SOC distribution due to patterned ground. Such landforms are non-sorted circles and ice-wedge polygons of different age and scale. Palsas and peat plateaus are formed and can cover larger areas in Sub-Arctic environments. Study areas that have not been affected by Pleistocene glaciation feature ice-rich Yedoma sediments that dominate the local relief through thermokarst formation and create landscape scale macro environments that dictate the distribution of SOC. A general trend indicates higher SOC storage in Arctic tundra soils compared to forested Boreal or Sub-Arctic taiga soils. Yet, due to the shallower active layer depth in the Arctic, much of the SOC may be permanently frozen and thus not be available to ecosystem processes. Significantly more SOC is stored in soils compared to vegetation, indicating that vegetation growth and incorporation of the carbon into the plant phytomass alone will not be able to offset SOC released from permafrost. This contribution also addresses advances in thematic mapping methods and digital soil mapping of SOC in permafrost terrain. In particular machine-learning methods, such as support vector machines, artificial neural networks and random forests show promising results as a toolbox for mapping permafrost-affected soils. Yet, these new methods do not decrease our dependency from soil pedon data from the field. In contrary, soil pedon data represents an urgent research priority. Statistical analyses are provided as an indication for best practice of soil pedon sampling for the quantification and the model representation of SOC stored in permafrost-affected soils.

Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran

NASA Astrophysics Data System (ADS)

Zeraatpisheh, Mojtaba; Ayoubi, Shamsollah; Jafari, Azam; Finke, Peter

2017-05-01

The efficiency of different digital and conventional soil mapping approaches to produce categorical maps of soil types is determined by cost, sample size, accuracy and the selected taxonomic level. The efficiency of digital and conventional soil mapping approaches was examined in the semi-arid region of Borujen, central Iran. This research aimed to (i) compare two digital soil mapping approaches including Multinomial logistic regression and random forest, with the conventional soil mapping approach at four soil taxonomic levels (order, suborder, great group and subgroup levels), (ii) validate the predicted soil maps by the same validation data set to determine the best method for producing the soil maps, and (iii) select the best soil taxonomic level by different approaches at three sample sizes (100, 80, and 60 point observations), in two scenarios with and without a geomorphology map as a spatial covariate. In most predicted maps, using both digital soil mapping approaches, the best results were obtained using the combination of terrain attributes and the geomorphology map, although differences between the scenarios with and without the geomorphology map were not significant. Employing the geomorphology map increased map purity and the Kappa index, and led to a decrease in the 'noisiness' of soil maps. Multinomial logistic regression had better performance at higher taxonomic levels (order and suborder levels); however, random forest showed better performance at lower taxonomic levels (great group and subgroup levels). Multinomial logistic regression was less sensitive than random forest to a decrease in the number of training observations. The conventional soil mapping method produced a map with larger minimum polygon size because of traditional cartographic criteria used to make the geological map 1:100,000 (on which the conventional soil mapping map was largely based). Likewise, conventional soil mapping map had also a larger average polygon size that resulted in a lower level of detail. Multinomial logistic regression at the order level (map purity of 0.80), random forest at the suborder (map purity of 0.72) and great group level (map purity of 0.60), and conventional soil mapping at the subgroup level (map purity of 0.48) produced the most accurate maps in the study area. The multinomial logistic regression method was identified as the most effective approach based on a combined index of map purity, map information content, and map production cost. The combined index also showed that smaller sample size led to a preference for the order level, while a larger sample size led to a preference for the great group level.

Effects of the soil-forming factors climate and time on soils of Mount Cameroon (Central Africa)

NASA Astrophysics Data System (ADS)

Sauer, Daniela; Nguetnkam, Jean Pierre; Tenzer, Selina; Herrmann, Ludger; Rennert, Thilo

2017-04-01

Knowledge on rates of soil-forming processes in humid-tropical climate is limited, mainly because objects that are suitable for studying soil chronosequences are rare in tropical regions. Mt. Cameroon, located at the Gulf of Guinea in SW Cameroon, between latitudes 4°00' to 4°20'N, is an ideal object for this purpose. Its volcanic activity started 11 Ma ago and still continues today, providing lava flows of different ages and rather uniform basaltic composition. The climate of the area is humid-tropical, characterised by a distinct gradient in mean annual precipitation (MAP). MAP amounts to > 9000 mm on the SW flank, near the coast, decreasing to < 2000 mm on the opposite flank, in the rain shadow of Mt. Cameroon's peak. Eight soil profiles, including six on historical lava flows of different ages and two on older (Holocene) lava flows characterised by contrasting MAP, were described and analysed. Soil formation proceeds from Nudilithic Leptosol (on a 13 year-old lava flow) to Skeletic Mollic Leptic Vitric Silandic Andosol (54 years), Umbric Leptic Silandic Andosol (91 and 104 years), and finally to Umbric Silandic Andosol (Holocene, MAP 2400 mm) or Umbric Amphisilandic Endoaluandic Andosol (Holocene, MAP 8000 mm). The general trends of Fed/Fet and (Ca+Mg+K+Na)/Al molar ratios over time indicate progressive weathering, formation of pedogenic iron oxides, and leaching of Ca, Mg, K and Na. Irregular uppermost parts of the depth curves of these ratios in some soils suggest addition of fresh ash or dust. Organic matter (OM) contents are remarkably high in the 104 year-old soils that are located at 3000 m a.s.l., compared to all other analysed soils. A possible explanation is that biomass production and thus OM input are still high at this elevation, whereas the altitudinal temperature decline leads to decreased OM decomposition compared to the lower slope.

7 CFR 1468.30 - Appeals.

Code of Federal Regulations, 2014 CFR

2014-01-01

... allocations; (2) Eligible conservation practices; (3) Payment rates, and cost-share percentages; (4) Science-based formulas and factor values; (5) Soils mapping and information; and (6) Other matters of general...

7 CFR 1468.30 - Appeals.

Code of Federal Regulations, 2013 CFR

2013-01-01

... allocations; (2) Eligible conservation practices; (3) Payment rates, and cost-share percentages; (4) Science-based formulas and factor values; (5) Soils mapping and information; and (6) Other matters of general...

7 CFR 1468.30 - Appeals.

Code of Federal Regulations, 2012 CFR

2012-01-01

... allocations; (2) Eligible conservation practices; (3) Payment rates, and cost-share percentages; (4) Science-based formulas and factor values; (5) Soils mapping and information; and (6) Other matters of general...

7 CFR 1468.30 - Appeals.

Code of Federal Regulations, 2011 CFR

2011-01-01

... allocations; (2) Eligible conservation practices; (3) Payment rates, and cost-share percentages; (4) Science-based formulas and factor values; (5) Soils mapping and information; and (6) Other matters of general...

Analysis of MASTER Thermal Data in the Greeley Area of the Front Range Urban Corridor, Colorado--Delineation of Sites for Infrastructure Resource Characterization

USGS Publications Warehouse

Livo, K. Eric; Watson, Ken

2002-01-01

Sand and soils southwest of Greeley, Colorado, were characterized for mineral composition and industrial quality. Radi-ance data from the thermal channels of the MASTER simulator were calibrated using estimated atmospheric parameters. Chan-nel emissivities were approximated using an estimated ground temperature. Subsequently, a decorrelation algorithm was used to calculate inverse wave emissivity images. Six soil classes, one vegetation class, water, and several small classes were defined using an unsupervised classification algorithm. Ground covered by each of the derived emissivity spectral classes was studied using color-infrared air photos, color-infrared composite MAS-TER data, geologic maps, NASA/JPL Airborne Visible and Infra-red Imaging Spectrometer (AVIRIS) data, and field examination. Spectral classes were characterized by their responses and related to their mineral content through field examination. Classes with a minimum at channel 44, and having a similar spectral shape to quartz, field checked as containing abundant quartz. Classes with a minimum at channel 45, and having a spectral shape similar to the sheet minerals, were found in the field to contain abundant mica and clay. Sandy soil was found to have a positive slope at the longer wavelengths; the more clay rich soils had a negative slope. Spectra with a strong downturn at channel 50 generally indicated low vegetation cover, whereas an upturn indicated more vegetation cover. Mapping revealed a range of classified soils with varying amounts of quartz, silt, clay, and plant humus. Sand and gravel operations along the St. Vrain River, gravel lots, and some fields spectrally classified as quartz-rich sands were confirmed through field examination. Other fields mapped as sandy soils, ranging from quartz-rich sandy soil to quartz-rich silt-sand soil with clay. Flood plains mapped as sandy-silty-organic-rich clay. The city of Greeley contained all classes of materials, with the sand classes mapping as various types of asphalt. Abundant quartz gravel was apparent within the asphalt during field check-ing. The clay classes mapped silt-clay soils in areas of irrigated grass landscaping, some fields, and roofing materials.

40 CFR 230.93 - General compensatory mitigation requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... available from sources such as wetland maps; soil surveys; U.S. Geological Survey topographic and hydrologic... the watershed, the district engineer must use appropriate quantitative assessment tools, where...

40 CFR 230.93 - General compensatory mitigation requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... available from sources such as wetland maps; soil surveys; U.S. Geological Survey topographic and hydrologic... the watershed, the district engineer must use appropriate quantitative assessment tools, where...

40 CFR 230.93 - General compensatory mitigation requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... available from sources such as wetland maps; soil surveys; U.S. Geological Survey topographic and hydrologic... the watershed, the district engineer must use appropriate quantitative assessment tools, where...

40 CFR 230.93 - General compensatory mitigation requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... available from sources such as wetland maps; soil surveys; U.S. Geological Survey topographic and hydrologic... the watershed, the district engineer must use appropriate quantitative assessment tools, where...

40 CFR 230.93 - General compensatory mitigation requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... available from sources such as wetland maps; soil surveys; U.S. Geological Survey topographic and hydrologic... the watershed, the district engineer must use appropriate quantitative assessment tools, where...

Seismic Hazard Maps for Seattle, Washington, Incorporating 3D Sedimentary Basin Effects, Nonlinear Site Response, and Rupture Directivity

USGS Publications Warehouse

Frankel, Arthur D.; Stephenson, William J.; Carver, David L.; Williams, Robert A.; Odum, Jack K.; Rhea, Susan

2007-01-01

This report presents probabilistic seismic hazard maps for Seattle, Washington, based on over 500 3D simulations of ground motions from scenario earthquakes. These maps include 3D sedimentary basin effects and rupture directivity. Nonlinear site response for soft-soil sites of fill and alluvium was also applied in the maps. The report describes the methodology for incorporating source and site dependent amplification factors into a probabilistic seismic hazard calculation. 3D simulations were conducted for the various earthquake sources that can affect Seattle: Seattle fault zone, Cascadia subduction zone, South Whidbey Island fault, and background shallow and deep earthquakes. The maps presented in this document used essentially the same set of faults and distributed-earthquake sources as in the 2002 national seismic hazard maps. The 3D velocity model utilized in the simulations was validated by modeling the amplitudes and waveforms of observed seismograms from five earthquakes in the region, including the 2001 M6.8 Nisqually earthquake. The probabilistic seismic hazard maps presented here depict 1 Hz response spectral accelerations with 10%, 5%, and 2% probabilities of exceedance in 50 years. The maps are based on determinations of seismic hazard for 7236 sites with a spacing of 280 m. The maps show that the most hazardous locations for this frequency band (around 1 Hz) are soft-soil sites (fill and alluvium) within the Seattle basin and along the inferred trace of the frontal fault of the Seattle fault zone. The next highest hazard is typically found for soft-soil sites in the Duwamish Valley south of the Seattle basin. In general, stiff-soil sites in the Seattle basin exhibit higher hazard than stiff-soil sites outside the basin. Sites with shallow bedrock outside the Seattle basin have the lowest estimated hazard for this frequency band.

Fingerprinting: Modelling and mapping physical top soil properties with the Mole

NASA Astrophysics Data System (ADS)

Loonstra, Eddie; van Egmond, Fenny

2010-05-01

The Mole is a passive gamma ray soil sensor system. It is designed for the mobile collection of radioactive energy stemming from soil. As the system is passive, it only measures energy that reaches the surface of soil. In general, this energy comes from upto 30 to 40 cm deep, which can be considered topsoil. The gathered energy spectra are logged every second, are processed with the method of Full Spectrum Analysis. This method uses all available spectral data and processes it with a Chi square optimalisation using a set of standard spectra into individual nuclide point data. A standard spectrum is the measured full spectrum of a specific detector derived when exposed to 1 Bq/kg of a nuclide. With this method the outcome of the surveys become quantitative.The outcome of a field survey with the Mole results in a data file containing point information of position, Total Counts and the decay products of 232Th, 238U, 40K and 137Cs. Five elements are therefor available for the modelling of soil properties. There are several ways for the modelling of soil properties with sensor derived gamma ray data. The Mole generates ratio scale output. For modelling a quantitative deterministic approach is used based on sample locations. This process is called fingerprinting. Fingerprinting is a comparison of the concentration of the radioactive trace elements and the lab results (pH, clay content, etc.) by regression analysis. This results in a mathematical formula describing the relationship between a dependent and independent property. The results of the sensor readings are interpolated into a nuclide map with GIS software. With the derived formula a soil property map is composed. The principle of fingerprinting can be applied on large geographical areas for physical soil properties such as clay, loam or sand (50 micron), grain size and organic matter. Collected sample data of previous field surveys within the same region can be used for the prediction of soil properties elsewhere when adding a relatively small number of new calibration samples. For this purpose stratification of data is necessary. All radioactive trace elements play a part in the fingerprinting process for the mapping of physical soil properties. Clay content is best predicted with 232Th. It has a general R2 of 0.75 up to 0,9. The correlation is positive and basically linear. The variation of loam (or sand) content is very well described by 232Th or the combination of 232Th and 238U. It has a comparable R2 to clay. Grain size can be well modelled with 40K, probably due to the fact that this nuclide is positively correlated with matter. 40K is therefor negatively correlated to grain size. The R2 is good: 0,7 to 0,8 on average. The combination of 40K and 137Cs is generally applied for modelling organic matter content with a quality comparable with that of grain size models. Finally, Total Counts turns out to be a very useful parameter for the identification of different types of parent material and of unnatural or non-parent material. Passive gamma ray soil sensors as the Mole are very suitable for high resolution mapping of physical soil properties. The FSA method has the advantage that data from previous surveys becomes applicable in the fingerprinting procedure of new fields. Being able to model the physical soil properties with gamma ray sensors opens the possibility to run pedotransfer function models for a particular survey.

Development and testing of a contamination potential mapping system for a portion of the General Separations Area, Savannah River Site, South Carolina

USGS Publications Warehouse

Rine, J.M.; Berg, R.C.; Shafer, J.M.; Covington, E.R.; Reed, J.K.; Bennett, C.B.; Trudnak, J.E.

1998-01-01

A methodology was developed to evaluate and map the contamination potential or aquifer sensitivity of the upper groundwater flow system of a portion of the General Separations Area (GSA) at the Department of Energy's Savannah River Site (SRS) in South Carolina. A Geographic Information System (GIS) was used to integrate diverse subsurface geologic data, soils data, and hydrology utilizing a stack-unit mapping approach to construct mapping layers. This is the first time that such an approach has been used to delineate the hydrogeology of a coastal plain environment. Unit surface elevation maps were constructed for the tops of six Tertiary units derived from over 200 boring logs. Thickness or isopach maps were created for five hydrogeologic units by differencing top and basal surface elevations. The geologic stack-unit map was created by stacking the five isopach maps and adding codes for each stack-unit polygon. Stacked-units were rated according to their hydrogeologic properties and ranked using a logarithmic approach (utility theory) to establish a contamination potential index. Colors were assigned to help display relative importance of stacked-units in preventing or promoting transport of contaminants. The sensitivity assessment included the effects of surface soils on contaminants which are particularly important for evaluating potential effects from surface spills. Hydrogeologic/hydrologic factors did not exhibit sufficient spatial variation to warrant incorporation into contamination potential assessment. Development of this contamination potential mapping system provides a useful tool for site planners, environmental scientists, and regulatory agencies.A methodology was developed to evaluate and map the contamination potential or aquifer sensitivity of the upper groundwater flow system of a portion of the General Separations Area (GSA) at the Department of Energy's Savannah River Site (SRS) in South Carolina. A Geographic Information System (GIS) was used to integrate diverse subsurface geologic data, soils data, and hydrology utilizing a stack-unit mapping approach to construct mapping layers. This is the first time that such an approach has been used to delineate the hydrogeology of a coastal plain environment. Unit surface elevation maps were constructed for the tops of six Tertiary units derived from over 200 boring logs. Thickness or isopach maps were created for five hydrogeologic units by differencing top and basal surface elevations. The geologic stack-unit map was created by stacking the five isopach maps and adding codes for each stack-unit polygon. Stacked-units were rated according to their hydrogeologic properties and ranked using a logarithmic approach (utility theory) to establish a contamination potential index. Colors were assigned to help display relative importance of stacked-units in preventing or promoting transport of contaminants. The sensitivity assessment included the effects of surface soils on contaminants which are particularly important for evaluating potential effects from surface spills. Hydrogeologic/hydrologic factors did not exhibit sufficient spatial variation to warrant incorporation into contamination potential assessment. Development of this contamination potential mapping system provides a useful tool for site planners, environmental scientists, and regulatory agencies.

Influence of Elevation Data Resolution on Spatial Prediction of Colluvial Soils in a Luvisol Region

PubMed Central

Penížek, Vít; Zádorová, Tereza; Kodešová, Radka; Vaněk, Aleš

2016-01-01

The development of a soil cover is a dynamic process. Soil cover can be altered within a few decades, which requires updating of the legacy soil maps. Soil erosion is one of the most important processes quickly altering soil cover on agriculture land. Colluvial soils develop in concave parts of the landscape as a consequence of sedimentation of eroded material. Colluvial soils are recognised as important soil units because they are a vast sink of soil organic carbon. Terrain derivatives became an important tool in digital soil mapping and are among the most popular auxiliary data used for quantitative spatial prediction. Prediction success rates are often directly dependent on raster resolution. In our study, we tested how raster resolution (1, 2, 3, 5, 10, 20 and 30 meters) influences spatial prediction of colluvial soils. Terrain derivatives (altitude, slope, plane curvature, topographic position index, LS factor and convergence index) were calculated for the given raster resolutions. Four models were applied (boosted tree, neural network, random forest and Classification/Regression Tree) to spatially predict the soil cover over a 77 ha large study plot. Models training and validation was based on 111 soil profiles surveyed on a regular sampling grid. Moreover, the predicted real extent and shape of the colluvial soil area was examined. In general, no clear trend in the accuracy prediction was found without the given raster resolution range. Higher maximum prediction accuracy for colluvial soil, compared to prediction accuracy of total soil cover of the study plot, can be explained by the choice of terrain derivatives that were best for Colluvial soils differentiation from other soil units. Regarding the character of the predicted Colluvial soils area, maps of 2 to 10 m resolution provided reasonable delineation of the colluvial soil as part of the cover over the study area. PMID:27846230

Vegetation Water Content Mapping for Agricultural Regions in SMAPVEX16

NASA Astrophysics Data System (ADS)

White, W. A.; Cosh, M. H.; McKee, L.; Berg, A. A.; McNairn, H.; Hornbuckle, B. K.; Colliander, A.; Jackson, T. J.

2017-12-01

Vegetation water content impacts the ability of L-band radiometers to measure surface soil moisture. Therefore it is necessary to quantify the amount of water held in surface vegetation for an accurate soil moisture remote sensing retrieval. A methodology is presented for generating agricultural vegetation water content maps using Landsat 8 scenes for agricultural fields of Iowa and Manitoba for the Soil Moisture Active Passive Validation Experiments in 2016 (SMAPVEX16). Manitoba has a variety of row crops across the region, and the study period encompasses the time frame from emergence to reproduction, as well as a forested region. The Iowa study site is dominated by corn and soybeans, presenting an easier challenge. Ground collection of vegetation biomass and water content were also collected to provide a ground truth data source. Errors for the resulting vegetation water content maps ranged depending upon crop type, but generally were less than 15% of the total plant water content per crop type. Interpolation is done between Landsat overpasses to produce daily vegetation water content maps for the summer of 2016 at a 30 meter resolution.

Quaternary Geologic Map of the Lake Nipigon 4 Degrees x 6 Degrees Quadrangle, United States and Canada

USGS Publications Warehouse

Sado, Edward V.; Fullerton, David S.; Farrand, William R.; Edited and Integrated by Fullerton, David S.

1994-01-01

The Quaternary Geologic Map of the Lake Nipigon 4 degree x 6 degree Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the 'ground' on which we walk, the 'dirt' in which we dig foundations, and the 'soil' in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale. This map is a product of collaboration of the Ontario Geological Survey, the University of Michigan, and the U.S. Geological Survey, and is designed for both scientific and practical purposes. It was prepared in two stages. First, separate maps and map explanations were prepared by the compilers. Second, the maps were combined, integrated, and supplemented by the editor. Map unit symbols were revised to a uniform system of classification and the map unit descriptions were prepared by the editor from information received from the compilers and from additional sources listed under Sources of Information. Diagrams accompanying the map were prepared by the editor. For scientific purposes, the map differentiates Quaternary surficial deposits on the basis of lithology or composition, texture or particle size, structure, genesis, stratigraphic relationships, engineering geologic properties, and relative age, as shown on the correlation diagram and indicated in the map unit descriptions. Deposits of some constructional landforms, such as kame moraine deposits, are distinguished as map units. Deposits of erosional landforms, such as outwash terraces, are not distinguished, although glaciofluvial, ice-contact, and lacustrine deposits that are mapped may be terraced. As a Quaternary geologic map it serves as a base from which a variety of maps relating Quaternary geologic history can be derived. For practical purposes, the map is a surficial materials map. Materials are distinguished on the basis of lithology or composition, texture or particle size, and other physical, chemical, and engineering characteristics. It is not a map of soils that are recognized and classified in pedology or agronomy. Rather, it is a generalized map of soils as recognized in engineering geology, or of substrata or parent materials in which pedologic or agronomic soils are formed. As a materials map it serves as a base from which a variety of maps for use in planning engineering, land use, or land management projects can be derived.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, J.M.; Callahan, C.A.; Cline, J.F.

Bioassays were used in a three-phase research project to assess the comparative sensitivity of test organisms to known chemicals, determine if the chemical components in field soil and water samples containing unknown contaminants could be inferred from our laboratory studies using known chemicals, and to investigate kriging (a relatively new statistical mapping technique) and bioassays as methods to define the areal extent of chemical contamination. The algal assay generally was most sensitive to samples of pure chemicals, soil elutriates and water from eight sites with known chemical contamination. Bioassays of nine samples of unknown chemical composition from the Rocky Mountainmore » Arsenal (RMA) site showed that a lettuce seed soil contact phytoassay was most sensitive. In general, our bioassays can be used to broadly identify toxic components of contaminated soil. Nearly pure compounds of insecticides and herbicides were less toxic in the sensitive bioassays than were the counterpart commercial formulations. This finding indicates that chemical analysis alone may fail to correctly rate the severity of environmental toxicity. Finally, we used the lettuce seed phytoassay and kriging techniques in a field study at RMA to demonstrate the feasibility of mapping contamination to aid in cleanup decisions. 25 references, 9 figures, 9 tables.« less

A national framework for monitoring and reporting on environmental sustainability in Canada.

PubMed

Marshall, I B; Scott Smith, C A; Selby, C J

1996-01-01

In 1991, a collaborative project to revise the terrestrial component of a national ecological framework was undertaken with a wide range of stakeholders. This spatial framework consists of multiple, nested levels of ecological generalization with linkages to existing federal and provincial scientific databases. The broadest level of generalization is the ecozone. Macroclimate, major vegetation types and subcontinental scale physiographic formations constitute the definitive components of these major ecosystems. Ecozones are subdivided into approximately 200 ecoregions which are based on properties like regional physiography, surficial geology, climate, vegetation, soil, water and fauna. The ecozone and ecoregion levels of the framework have been depicted on a national map coverage at 1:7 500 000 scale. Ecoregions have been subdivided into ecodistricts based primarily on landform, parent material, topography, soils, waterbodies and vegetation at a scale (1:2 000 000) useful for environmental resource management, monitoring and modelling activities. Nested within the ecodistricts are the polygons that make up the Soil Landscapes of Canada series of 1:1 000 000 scale soil maps. The framework is supported by an ARC-INFO GIS at Agriculture Canada. The data model allows linkage to associated databases on climate, land use and socio-economic attributes.

30 CFR 884.13 - Content of proposed State reclamation plan.

Code of Federal Regulations, 2013 CFR

2013-07-01

... reclamation program, the Rural Abandoned Mine Program administered by the Soil Conservation Service, the... within the State which require reclamation, including— (1) A map showing the general location or known or...

30 CFR 884.13 - Content of proposed State reclamation plan.

Code of Federal Regulations, 2012 CFR

2012-07-01

... reclamation program, the Rural Abandoned Mine Program administered by the Soil Conservation Service, the... within the State which require reclamation, including— (1) A map showing the general location or known or...

30 CFR 884.13 - Content of proposed State reclamation plan.

Code of Federal Regulations, 2014 CFR

2014-07-01

... reclamation program, the Rural Abandoned Mine Program administered by the Soil Conservation Service, the... within the State which require reclamation, including— (1) A map showing the general location or known or...

Quaternary geologic map of the Wolf Point 1° × 2° quadrangle, Montana and North Dakota

USGS Publications Warehouse

Fullerton, David S.; Colton, Roger B.; Bush, Charles A.

2016-09-08

The Wolf Point quadrangle encompasses approximately 16,084 km2 (6,210 mi2). The northern boundary is the Montana/Saskatchewan (U.S.-Canada) boundary. The quadrangle is in the Northern Plains physiographic province and it includes the Peerless Plateau and Flaxville Plain. The primary river is the Missouri River.The map units are surficial deposits and materials, not landforms. Deposits that comprise some constructional landforms (for example, ground-moraine deposits, end-moraine deposits, and stagnation-moraine deposits, all composed of till) are distinguished for purposes of reconstruction of glacial history. Surficial deposits and materials are assigned to 23 map units on the basis of genesis, age, lithology or composition, texture or particle size, and other physical, chemical, and engineering characteristics. It is not a map of soils that are recognized in pedology or agronomy.  Rather, it is a generalized map of soils recognized in engineering geology, or of substrata or parent materials in which pedologic or agronomic soils are formed.  Glaciotectonic (ice-thrust) structures and deposits are mapped separately, represented by a symbol. The surficial deposits are glacial, ice-contact, glaciofluvial, alluvial, lacustrine, eolian, colluvial, and mass-movement deposits.Till of late Wisconsin age is represented by three map units. Till of Illinoian age also is mapped.  Till deposited during pre-Illinoian glaciations is not mapped, but is widespread in the subsurface.  Linear ice-molded landforms (primarily drumlins), shown by symbol, indicate directions of ice flow during late Wisconsin and Illinoian glaciations. The Quaternary geologic map of the Wolf Point quadrangle, northeastern Montana and North Dakota, was prepared to provide a database for compilation of a Quaternary geologic map of the Regina 4° × 6° quadrangle, United States and Canada, at scale 1:1,000,000, for the U.S. Geological Survey Quaternary Geologic Atlas of the United States map series.  This map was compiled from data from many sources, at several different map scales.  That information was generalized and simplified, and then transferred to a base map at 1:250,000 scale to serve as the base for final reduction to 1:1,000,000, the nominal reading scale of maps in the Quaternary Geologic Atlas of the United States map series.  This map is the generalized and simplified 1:250,000 scale compilation.  Letter symbols for the map units are those used for the same units in the Quaternary Geologic Atlas of the United States map series. The map summarizes new, and selected published and unpublished, geologic information for public use and for use by Federal, State, and local governmental agencies for land use planning, including assessment of natural resources, natural hazards, recreation potential, and land use management.  It also is a base from which a variety of maps relating to earth surface processes and Quaternary geologic history can be derived.

Application of cattle slurry containing Mycobacterium avium subsp. paratuberculosis (MAP) to grassland soil and its effect on the relationship between MAP and free-living amoeba.

PubMed

Salgado, M; Alfaro, M; Salazar, F; Badilla, X; Troncoso, E; Zambrano, A; González, M; Mitchell, R M; Collins, M T

2015-01-30

Slurry from dairy farms is commonly used to fertilize crops and pastures. This mixture of manure, urine and water can harbor multiple microbial pathogens among which Mycobacterium avium subsp. paratuberculosis (MAP) is a major concern. Persistence of MAP in soil and infection of soil Acanthamoeba was evaluated by culture, real-time IS900 PCR, and by staining of amoeba with acid-fast and vital stains comparing soils irrigated with MAP-spiked or control dairy farm slurry. MAP DNA was detected in soil for the 8 month study duration. MAP was detected by PCR from more soil samples for plots receiving MAP-spiked slurry (n=61/66) than from soils receiving control slurry (n=10/66 samples). Vital stains verified that intracellular MAP in amoeba was viable. More MAP was found in amoeba at the end of the study than immediately after slurry application. There was no relationship between MAP presence in soil and in amoeba over time. Infection of amoeba by MAP provides a protected niche for the persistence and even possibly the replication of MAP in soils. As others have suggested, MAP-infected amoeba may act like a "Trojan horse" providing a means for persistence in soils and potentially a source of infection for grazing animals. Copyright © 2014 Elsevier B.V. All rights reserved.

Urban soil pollution and the playfields of small children

NASA Astrophysics Data System (ADS)

Jartun, M.; Ottesen, R. T.; Steinnes, E.

2003-05-01

The chemical composition of urban surface soil in Tromsø, northern Norway has been mapped to describe the environmental load of toxic elements in different parts of the city. Surface soil samples were collected from 275 locations throughout the city center and nearby suburban areas. Natural background concentrations were determined in samples of the local bedrock. Surface soil in younger, suburban parts of the city shows low concentrations of heavy metals, reflecting the local geochemistry. The inner and older parts of the city are generally polluted with lead (Pb), zinc (Zn) and tin (Sn). The most important sources of this urban soil pollution are probably city fires, industrial and domestic waste, traffic, and shipyards. In this paper two different approaches have been used. First, as a result of the general mapping, 852 soil and sand samples from kindergartens and playgrounds were analyzed. In this study concentrations of arsenic (As) up to 1800ppm were found, most likely due to the extensive use of CCA (copper, chromium, arsenic) impregnated wood in sandboxes and other playground equipment. This may represent a significant health risk especially to children having a high oral intake of contaminated sand and soil. Secondly a pattern of tin (Sn) concentrations was found in Tromsøcity with especially high values near shipyards. Further investigation indicated that this pattern most probably reflected the use of the highty toxic tributyltin (TBT). Thus détermination of total Sn in surface soils could be a cost-effective way to localize sources of TBT contamination in the environment.

Soil maps as data input for soil erosion models: errors related to map scales

NASA Astrophysics Data System (ADS)

van Dijk, Paul; Sauter, Joëlle; Hofstetter, Elodie

2010-05-01

Soil erosion rates depend in many ways on soil and soil surface characteristics which vary in space and in time. To account for spatial variations of soil features, most distributed soil erosion models require data input derived from soil maps. Ideally, the level of spatial detail contained in the applied soil map should correspond to the objective of the modelling study. However, often the model user has only one soil map available which is then applied without questioning its suitability. The present study seeks to determine in how far soil map scale can be a source of error in erosion model output. The study was conducted on two different spatial scales, with for each of them a convenient soil erosion model: a) the catchment scale using the physically-based Limbourg Soil Erosion Model (LISEM), and b) the regional scale using the decision-tree expert model MESALES. The suitability of the applied soil map was evaluated with respect to an imaginary though realistic study objective for both models: the definition of erosion control measures at strategic locations at the catchment scale; the identification of target areas for the definition of control measures strategies at the regional scale. Two catchments were selected to test the sensitivity of LISEM to the spatial detail contained in soil maps: one catchment with relatively little contrast in soil texture, dominated by loess-derived soil (south of the Alsace), and one catchment with strongly contrasted soils at the limit between the Alsatian piedmont and the loess-covered hills of the Kochersberg. LISEM was run for both catchments using different soil maps ranging in scale from 1/25 000 to 1/100 000 to derive soil related input parameters. The comparison of the output differences was used to quantify the map scale impact on the quality of the model output. The sensitivity of MESALES was tested on the Haut-Rhin county for which two soil maps are available for comparison: 1/50 000 and 1/100 000. The order of resulting target areas (communes) was compared to evaluate the error induced by using the coarser soil data at 1/100 000. Results shows that both models are sensitive to the soil map scale used for model data input. A low sensitivity was found for the catchment with relatively homogeneous soil textures and the use of 1/100 000 soil maps seems allowed. The results for the catchment with strong soil texture variations showed significant differences depending on soil map scale on 75% of the catchment area. Here, the use of 1/100 000 soil map will indeed lead to wrong erosion diagnostics and will hamper the definition of a sound erosion control strategy. The regional scale model MESALES proved to be very sensitive to soil information. The two soil related model parameters (crusting sensitivity, and soil erodibility) reacted very often in the same direction therewith amplifying the change in the final erosion hazard class. The 1/100 000 soil map yielded different results on 40% of the sloping area compared to the 1/50 000 map. Significant differences in the order of target areas were found as well. The present study shows that the degree of sensitivity of the model output to soil map scale is rather variable and depends partly on the spatial variability of soil texture within the study area. Soil (textural) diversity needs to be accounted for to assure a fruitful use of soil erosion models. In some situations this might imply that additional soil data need to be collected in the field to refine the available soil map.

A statistical approach for validating eSOTER and digital soil maps in front of traditional soil maps

NASA Astrophysics Data System (ADS)

Bock, Michael; Baritz, Rainer; Köthe, Rüdiger; Melms, Stephan; Günther, Susann

2015-04-01

During the European research project eSOTER, three different Digital Soil Maps (DSM) were developed for the pilot area Chemnitz 1:250,000 (FP7 eSOTER project, grant agreement nr. 211578). The core task of the project was to revise the SOTER method for the interpretation of soil and terrain data. It was one of the working hypothesis that eSOTER does not only provide terrain data with typical soil profiles, but that the new products actually perform like a conceptual soil map. The three eSOTER maps for the pilot area considerably differed in spatial representation and content of soil classes. In this study we compare the three eSOTER maps against existing reconnaissance soil maps keeping in mind that traditional soil maps have many subjective issues and intended bias regarding the overestimation and emphasize of certain features. Hence, a true validation of the proper representation of modeled soil maps is hardly possible; rather a statistical comparison between modeled and empirical approaches is possible. If eSOTER data represent conceptual soil maps, then different eSOTER, DSM and conventional maps from various sources and different regions could be harmonized towards consistent new data sets for large areas including the whole European continent. One of the eSOTER maps has been developed closely to the traditional SOTER method: terrain classification data (derived from SRTM DEM) were combined with lithology data (re-interpreted geological map); the corresponding terrain units were then extended with soil information: a very dense regional soil profile data set was used to define soil mapping units based on a statistical grouping of terrain units. The second map is a pure DSM map using continuous terrain parameters instead of terrain classification; radiospectrometric data were used to supplement parent material information from geology maps. The classification method Random Forest was used. The third approach predicts soil diagnostic properties based on covariates similar to DSM practices; in addition, multi-temporal MODIS data were used; the resulting soil map is the product of these diagnostic layers producing a map of soil reference groups (classified according to WRB). Because the third approach was applied to a larger test area in central Europe, and compared to the first two approaches, has worked with coarser input data, comparability is only partly fulfilled. To evaluate the usability of the three eSOTER maps, and to make a comparison among them, traditional soil maps 1:200,000 and 1:50,000 were used as reference data sets. Three statistical methods were applied: (i) in a moving window the distribution of the soil classes of each DSM product was compared to that of the soil maps by calculating the corrected coefficient of contingency, (ii) the value of predictive power for each of the eSOTER maps was determined, and (iii) the degree of consistency was derived. The latter is based on a weighting of the match of occurring class combinations via expert knowledge and recalculating the proportions of map appearance with these weights. To re-check the validation results a field study by local soil experts was conducted. The results show clearly that the first eSOTER approach based on the terrain classification / reinterpreted parent material information has the greatest similarity with traditional soil maps. The spatial differentiation offered by such an approach is well suitable to serve as a conceptual soil map. Therefore, eSOTER can be a tool for soil mappers to generate conceptual soil maps in a faster and more consistent way. This conclusion is at least valid for overview scales such as 1.250,000.

Islands of biogeodiversity in arid lands on a polygons map study: Detecting scale invariance patterns from natural resources maps.

PubMed

Ibáñez, J J; Pérez-Gómez, R; Brevik, Eric C; Cerdà, A

2016-12-15

Many maps (geology, hydrology, soil, vegetation, etc.) are created to inventory natural resources. Each of these resources is mapped using a unique set of criteria, including scales and taxonomies. Past research indicates that comparing results of related maps (e.g., soil and geology maps) may aid in identifying mapping deficiencies. Therefore, this study was undertaken in Almeria Province, Spain to (i) compare the underlying map structures of soil and vegetation maps and (ii) investigate if a vegetation map can provide useful soil information that was not shown on a soil map. Soil and vegetation maps were imported into ArcGIS 10.1 for spatial analysis, and results then exported to Microsoft Excel worksheets for statistical analyses to evaluate fits to linear and power law regression models. Vegetative units were grouped according to the driving forces that determined their presence or absence: (i) climatophilous (ii) lithologic-climate; and (iii) edaphophylous. The rank abundance plots for both the soil and vegetation maps conformed to Willis or Hollow Curves, meaning the underlying structures of both maps were the same. Edaphophylous map units, which represent 58.5% of the vegetation units in the study area, did not show a good correlation with the soil map. Further investigation revealed that 87% of the edaphohygrophilous units were found in ramblas, ephemeral riverbeds that are not typically classified and mapped as soils in modern systems, even though they meet the definition of soil given by the most commonly used and most modern soil taxonomic systems. Furthermore, these edaphophylous map units tend to be islands of biodiversity that are threatened by anthropogenic activity in the region. Therefore, this study revealed areas that need to be revisited and studied pedologically. The vegetation mapped in these areas and the soils that support it are key components of the earth's critical zone that must be studied, understood, and preserved. Copyright © 2016 Elsevier B.V. All rights reserved.

Machine learning for predicting soil classes in three semi-arid landscapes

USGS Publications Warehouse

Brungard, Colby W.; Boettinger, Janis L.; Duniway, Michael C.; Wills, Skye A.; Edwards, Thomas C.

2015-01-01

Mapping the spatial distribution of soil taxonomic classes is important for informing soil use and management decisions. Digital soil mapping (DSM) can quantitatively predict the spatial distribution of soil taxonomic classes. Key components of DSM are the method and the set of environmental covariates used to predict soil classes. Machine learning is a general term for a broad set of statistical modeling techniques. Many different machine learning models have been applied in the literature and there are different approaches for selecting covariates for DSM. However, there is little guidance as to which, if any, machine learning model and covariate set might be optimal for predicting soil classes across different landscapes. Our objective was to compare multiple machine learning models and covariate sets for predicting soil taxonomic classes at three geographically distinct areas in the semi-arid western United States of America (southern New Mexico, southwestern Utah, and northeastern Wyoming). All three areas were the focus of digital soil mapping studies. Sampling sites at each study area were selected using conditioned Latin hypercube sampling (cLHS). We compared models that had been used in other DSM studies, including clustering algorithms, discriminant analysis, multinomial logistic regression, neural networks, tree based methods, and support vector machine classifiers. Tested machine learning models were divided into three groups based on model complexity: simple, moderate, and complex. We also compared environmental covariates derived from digital elevation models and Landsat imagery that were divided into three different sets: 1) covariates selected a priori by soil scientists familiar with each area and used as input into cLHS, 2) the covariates in set 1 plus 113 additional covariates, and 3) covariates selected using recursive feature elimination. Overall, complex models were consistently more accurate than simple or moderately complex models. Random forests (RF) using covariates selected via recursive feature elimination was consistently the most accurate, or was among the most accurate, classifiers between study areas and between covariate sets within each study area. We recommend that for soil taxonomic class prediction, complex models and covariates selected by recursive feature elimination be used. Overall classification accuracy in each study area was largely dependent upon the number of soil taxonomic classes and the frequency distribution of pedon observations between taxonomic classes. Individual subgroup class accuracy was generally dependent upon the number of soil pedon observations in each taxonomic class. The number of soil classes is related to the inherent variability of a given area. The imbalance of soil pedon observations between classes is likely related to cLHS. Imbalanced frequency distributions of soil pedon observations between classes must be addressed to improve model accuracy. Solutions include increasing the number of soil pedon observations in classes with few observations or decreasing the number of classes. Spatial predictions using the most accurate models generally agree with expected soil–landscape relationships. Spatial prediction uncertainty was lowest in areas of relatively low relief for each study area.

Map Database for Surficial Materials in the Conterminous United States

USGS Publications Warehouse

Soller, David R.; Reheis, Marith C.; Garrity, Christopher P.; Van Sistine, D. R.

2009-01-01

The Earth's bedrock is overlain in many places by a loosely compacted and mostly unconsolidated blanket of sediments in which soils commonly are developed. These sediments generally were eroded from underlying rock, and then were transported and deposited. In places, they exceed 1000 ft (330 m) in thickness. Where the sediment blanket is absent, bedrock is either exposed or has been weathered to produce a residual soil. For the conterminous United States, a map by Soller and Reheis (2004, scale 1:5,000,000; http://pubs.usgs.gov/of/2003/of03-275/) shows these sediments and the weathered, residual material; for ease of discussion, these are referred to as 'surficial materials'. That map was produced as a PDF file, from an Adobe Illustrator-formatted version of the provisional GIS database. The provisional GIS files were further processed without modifying the content of the published map, and are here published.

[Extracting black soil border in Heilongjiang province based on spectral angle match method].

PubMed

Zhang, Xin-Le; Zhang, Shu-Wen; Li, Ying; Liu, Huan-Jun

2009-04-01

As soils are generally covered by vegetation most time of a year, the spectral reflectance collected by remote sensing technique is from the mixture of soil and vegetation, so the classification precision based on remote sensing (RS) technique is unsatisfied. Under RS and geographic information systems (GIS) environment and with the help of buffer and overlay analysis methods, land use and soil maps were used to derive regions of interest (ROI) for RS supervised classification, which plus MODIS reflectance products were chosen to extract black soil border, with methods including spectral single match. The results showed that the black soil border in Heilongjiang province can be extracted with soil remote sensing method based on MODIS reflectance products, especially in the north part of black soil zone; the classification precision of spectral angel mapping method is the highest, but the classifying accuracy of other soils can not meet the need, because of vegetation covering and similar spectral characteristics; even for the same soil, black soil, the classifying accuracy has obvious spatial heterogeneity, in the north part of black soil zone in Heilongjiang province it is higher than in the south, which is because of spectral differences; as soil uncovering period in Northeastern China is relatively longer, high temporal resolution make MODIS images get the advantage over soil remote sensing classification; with the help of GIS, extracting ROIs by making the best of auxiliary data can improve the precision of soil classification; with the help of auxiliary information, such as topography and climate, the classification accuracy was enhanced significantly. As there are five main factors determining soil classes, much data of different types, such as DEM, terrain factors, climate (temperature, precipitation, etc.), parent material, vegetation map, and remote sensing images, were introduced to classify soils, so how to choose some of the data and quantify the weights of different data layers needs further study.

Preliminary Evaluation of TM for Soils Information

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Henderson, K. E.; Houston, A. G.; Pitts, D. E.

1984-01-01

Thematic mapper data acquired over Mississippi County, Arkansas, were examined for utility in separating soil associations within generally level alluvium deposited by the Mississippi River. The 0.76 to 0.90 micron (Band 4) and the 1.55 to 1.75 micron (Band 5) were found to separate the different soil associations fairly well when compared to the USDA-SCS general soil map. The thermal channel also appeared to provide information at this level. A detailed soil survey was available at the field level along with ground observations of crop type, plant height, percent cover and growth stage. Soils within the fields ranged from uniform to soils that occur as patches of sand that stand out strongly against the intermingled areas of dark soil. Examination of the digital values of individual TM bands at the field level indicates that the influence of the soil is greater in TM than it was in MSS bands. The TM appears to provide greater detail of within field variability caused by soils than MSS and thus should provide improved information relating to crop and soil properties. However, this soil influence may cause crop identification classification procedures to have to account for the soil in their algorithms.

Using Vegetation Maps to Provide Information on Soil Distribution

NASA Astrophysics Data System (ADS)

José Ibáñez, Juan; Pérez-Gómez, Rufino; Brevik, Eric C.; Cerdà, Artemi

2016-04-01

Many different types of maps (geology, hydrology, soil, vegetation, etc.) are created to inventory natural resources. Each of these resources is mapped using a unique set of criteria, including scales and taxonomies. Past research has indicated that comparing the results of different but related maps (e.g., soil and geology maps) may aid in identifying deficiencies in those maps. Therefore, this study was undertaken in the Almería Province (Andalusia, Spain) to (i) compare the underlying map structures of soil and vegetation maps and (ii) to investigate if a vegetation map can provide useful soil information that was not shown on a soil map. To accomplish this soil and vegetation maps were imported into ArcGIS 10.1 for spatial analysis. Results of the spatial analysis were exported to Microsoft Excel worksheets for statistical analyses to evaluate fits to linear and power law regression models. Vegetative units were grouped according to the driving forces that determined their presence or absence (P/A): (i) climatophilous (climate is the only determinant of P/A) (ii); lithologic-climate (climate and parent material determine PNV P/A); and (iii) edaphophylous (soil features determine PNV P/A). The rank abundance plots for both the soil and vegetation maps conformed to Willis or Hollow Curves, meaning the underlying structures of both maps were the same. Edaphophylous map units, which represent 58.5% of the vegetation units in the study area, did not show a good correlation with the soil map. Further investigation revealed that 87% of the edaphohygrophylous units (which demand more soil water than is supplied by other soil types in the surrounding landscape) were found in ramblas, ephemeral riverbeds that are not typically classified and mapped as soils in modern systems, even though they meet the definition of soil given by the most commonly used and most modern soil taxonomic systems. Furthermore, these edaphophylous map units tend to be islands of biodiversity that are threatened by anthropogenic activity in the region. Therefore, this study revealed areas in Almería Province that need to be revisited and studied pedologically. The vegetation mapped in these areas and the soils that support it are key components of the earth's critical zone that must be studied, understood, and preserved.

Appalachian piedmont regolith: Relations of saprolite and residual soils to rock-type

USGS Publications Warehouse

Pavich, M.J.

1996-01-01

Saprolite is a major product of rock weathering on the Appalachian Piedmont from New Jersey to Alabama. On the Piedmont, it is the primary substrate from which residual soils are developed. Properties of saprolite and residual soils are highly related to their parent rocks. Studies of cores and outcrops illustrate that rock structure and mineralogy control upland regolith zonation. Saprolite develops by in situ chemical alteration of a wide variety of mafic to highly silicic rocks. Thickness of upland saprolite varies from a few meters on mafic rocks to tens of meters on silicic rocks. Saprolite thickness decreases with increasing slope and saprolite is generally thin or absent in valley bottoms. Massive residual subsoils and soils develop by physical and chemical processes that alter the upper few meters of saprolite. The fabric, texture and mineralogy of residual soils are distinctly different from underlying saprolite. The boundary between soil and saprolite is often gradual, and often a zone of low permeability. Geologic maps are useful guides to Piedmont regolith thickness and zonation. In regional design studies, geologic maps and regolith characteristics can be useful in environmental decision-making.

GEMAS: The Fennoscandian perspective

NASA Astrophysics Data System (ADS)

Katarzyna Ladenberger, Anna; Uhlbäck, Jo; Andersson, Madelen; Reimann, Clemens; Tarvainen, Timo; Sadeghi, Martiya; Morris, George; Eklund, Mikael

2014-05-01

The GEMAS Project (Geochemical Mapping of Agricultural and Grazing Land Soil in Europe) resulted in a large coherent data set displaying baseline levels of elements in agricultural and grazing land soil, on both a European and a regional scale. The geochemical mapping of agricultural and grazing land soil in Norway, Sweden and Finland revealed regional features, noticeably different from the general geochemical pattern in the rest of Europe. When looking at the European data set as a whole, Norway, Sweden and Finland stand out as geochemically distinct, mainly due to the old bedrock and the extent of the last glaciations. They were thus considered valuable for a study as a separate entity. The interpretation of element maps and statistics identified several factors responsible for the observed trends in the geochemical patterns in Norway, Sweden and Finland, with the most important factors being bedrock geology, the presence of ore deposits, the soil type and its properties, and climate. The soil of the Fennoscandian Shield is very young and the composition of parent material has a crucial influence on the soil chemical signature. On the other hand the occurrence of organic peaty soil and clayey varieties plays an important role in enrichment processes leading to enhanced levels of many elements. Anthropogenic impact on soils appears to have a minor influence on the soil geochemistry of both agricultural and grazing land. In mining regions, with the natural signal from the mineralisation, it is often difficult to discriminate between the original anomaly and any additional anthropogenic contamination. The results of this survey are available to the public and can be used by both local authorities and research groups.

Quaternary geologic map of the Glasgow 1° x 2° quadrangle, Montana

USGS Publications Warehouse

Fullerton, David S.; Colton, Roger B.; Bush, Charles A.

2012-01-01

The Glasgow quadrangle encompasses approximately 16,084 km2 (6,210 mi2). The northern boundary is the Montana/Saskatchewan (U.S./Canada) boundary. The quadrangle is in the Northern Plains physiographic province and it includes the Boundary Plateau, Peerless Plateau, and Larb Hills. The primary river is the Milk River. The map units are surficial deposits and materials, not landforms. Deposits that comprise some constructional landforms (for example, ground-moraine deposits, end-moraine deposits, and stagnation-moraine deposits, all composed of till) are distinguished for purposes of reconstruction of glacial history. Surficial deposits and materials are assigned to 23 map units on the basis of genesis, age, lithology or composition, texture or particle size, and other physical, chemical, and engineering characteristics. It is not a map of soils that are recognized in pedology or agronomy. Rather, it is a generalized map of soils recognized in engineering geology, or of substrata or parent materials in which pedologic or agronomic soils are formed. Glaciotectonic (ice-thrust) structures and deposits are mapped separately, represented by a symbol. The surficial deposits are glacial, ice-contact, glaciofluvial, alluvial, lacustrine, eolian, colluvial, and mass-movement deposits. Residuum, a surficial material, also is mapped. Till of late Wisconsin age is represented by three map units. Till of Illinoian age is also represented locally but is widespread in the subsurface. This map was prepared to serve as a database for compilation of a Quaternary geologic map of the United States and Canada (scale 1:1,000,000). Letter symbols for the map units are those used for the same units in the Quaternary Geologic Atlas of the United States map series.

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images.

PubMed

Hapca, Simona; Baveye, Philippe C; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred

2015-01-01

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution.

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images

PubMed Central

Hapca, Simona; Baveye, Philippe C.; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred

2015-01-01

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution. PMID:26372473

Quaternary Geologic Map of the Lake of the Woods 4 Degrees x 6 Degrees Quadrangle, United States and Canada

USGS Publications Warehouse

Sado, Edward V.; Fullerton, David S.; Goebel, Joseph E.; Ringrose, Susan M.; Edited and Integrated by Fullerton, David S.

1995-01-01

The Quaternary Geologic Map of the Lake of the Woods 4 deg x 6 deg Quadrangle, United States and Canada, was mapped as part of the U.S. Geological Survey Quaternary Geologic Atlas of the United States map series (Miscellaneous Investigations Series I-1420, NM-15). The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the 'ground' on which we walk, the 'dirt' in which we dig foundations, and the 'soil' in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale. This map is a product of collaboration of the Ontario Geological Survey, the Minnesota Geological Survey, the Manitoba Department of Energy and Mines, and the U.S. Geological Survey, and is designed for both scientific and practical purposes. It was prepared in two stages. First, separate maps and map explanations were prepared by the compilers. Second, the maps were combined, integrated, and supplemented by the editor. Map unit symbols were revised to a uniform system of classification and the map unit descriptions were prepared by the editor from information received from the compilers and from additional sources listed under Sources of Information. Diagrams accompanying the map were prepared by the editor. For scientific purposes, the map differentiates Quaternary surficial deposits on the basis of lithology or composition, texture or particle size, structure, genesis, stratigraphic relationships, engineering geologic properties, and relative age, as shown on the correlation diagram and indicated in the description of map units. Deposits of some constructional landforms, such as kame moraine deposits, are distinguished as map units. Deposits of erosional landforms, such as outwash terraces, are not distinguished, although glaciofluvial, ice-contact, and lacustrine deposits that are mapped may be terraced. As a Quaternary geologic map, it serves as a base from which a variety of maps relating Quaternary geologic history can be derived. For practical purposes, the map is a surficial materials map. Materials are distinguished on the basis of lithology or composition, texture or particle size, and other physical, chemical, and engineering characteristics. It is not a map of soils that are recognized and classified in pedology or agronomy. Rather, it is a generalized map of soils as recognized in engineering geology, or of substrata or parent materials in which pedologic or agronomic soils are formed. As a materials map, it serves as a base from which a variety of maps for use in planning engineering, land-use, or land-management projects can be derived.

Quantification of soil mapping by digital analysis of LANDSAT data. [Clinton County, Indiana

NASA Technical Reports Server (NTRS)

Kirschner, F. R.; Kaminsky, S. A.; Hinzel, E. J.; Sinclair, H. R.; Weismiller, R. A.

1977-01-01

Soil survey mapping units are designed such that the dominant soil represents the major proportion of the unit. At times, soil mapping delineations do not adequately represent conditions as stated in the mapping unit descriptions. Digital analysis of LANDSAT multispectral scanner (MSS) data provides a means of accurately describing and quantifying soil mapping unit composition. Digital analysis of LANDSAT MSS data collected on 9 June 1973 was used to prepare a spectral soil map for a 430-hectare area in Clinton County, Indiana. Fifteen spectral classes were defined, representing 12 soil and 3 vegetation classes. The 12 soil classes were grouped into 4 moisture regimes based upon their spectral responses; the 3 vegetation classes were grouped into one all-inclusive class.

Comparing different approaches - data mining, geostatistic, and deterministic pedology - to assess the frequency of WRB Reference Soil Groups in the Italian soil regions

NASA Astrophysics Data System (ADS)

Lorenzetti, Romina; Barbetti, Roberto; L'Abate, Giovanni; Fantappiè, Maria; Costantini, Edoardo A. C.

2013-04-01

Estimating frequency of soil classes in map unit is always affected by some degree of uncertainty, especially at small scales, with a larger generalization. The aim of this study was to compare different possible approaches - data mining, geostatistic, deterministic pedology - to assess the frequency of WRB Reference Soil Groups (RSG) in the major Italian soil regions. In the soil map of Italy (Costantini et al., 2012), a list of the first five RSG was reported in each major 10 soil regions. The soil map was produced using the national soil geodatabase, which stored 22,015 analyzed and classified pedons, 1,413 soil typological unit (STU) and a set of auxiliary variables (lithology, land-use, DEM). Other variables were added, to better consider the influence of soil forming factors (slope, soil aridity index, carbon stock, soil inorganic carbon content, clay, sand, geography of soil regions and soil systems) and a grid at 1 km mesh was set up. The traditional deterministic pedology assessed the STU frequency according to the expert judgment presence in every elementary landscape which formed the mapping unit. Different data mining techniques were firstly compared in their ability to predict RSG through auxiliary variables (neural networks, random forests, boosted tree, supported vector machine (SVM)). We selected SVM according to the result of a testing set. A SVM model is a representation of the examples as points in space, mapped so that examples of separate categories are divided by a clear gap that is as wide as possible. The geostatistic algorithm we used was an indicator collocated cokriging. The class values of the auxiliary variables, available at all the points of the grid, were transformed in indicator variables (values 0, 1). A principal component analysis allowed us to select the variables that were able to explain the largest variability, and to correlate each RSG with the first principal component, which explained the 51% of the total variability. The principal component was used as collocated variable. The results were as many probability maps as the estimated WRB classes. They were summed up in a unique map, with the most probable class at each pixel. The first five more frequent RSG resulting from the three methods were compared. The outcomes were validated with a subset of the 10% of the pedons, kept out before the elaborations. The error estimate was produced for each estimated RSG. The first results, obtained in one of the most widespread soil region (plains and low hills of central and southern Italy) showed that the first two frequency classes were the same for all the three methods. The deterministic method differed from the others at the third position, while the statistical methods inverted the third and fourth position. An advantage of the SVM was the possibility to use in the same elaboration numeric and categorical variable, without any previous transformation, which reduced the processing time. A Bayesian validation indicated that the SVM method was as reliable as the indicator collocated cokriging, and better than the deterministic pedological approach.

Digital soil map of the Ussuri River basin

NASA Astrophysics Data System (ADS)

Bugaets, A. N.; Pschenichnikova, N. F.; Tereshkina, A. A.; Krasnopeev, S. M.; Gartsman, B. I.; Golodnaya, O. M.; Oznobikhin, V. I.

2017-08-01

On the basis of digital soil, topographic, and geological maps; raster topography model; forestry materials; and literature data, the digital soil map of the Ussuri River basin (24400 km2) was created on a scale of 1: 100000. To digitize the initial paper-based maps and analyze the results, an ESRI ArcGIS Desktop (ArcEditor) v.10.1 (http://www.esri.com) and an open-code SAGA GIS v.2.3 (System for Automated Geoscientific Analyses, http://www.saga-gis.org) were used. The spatial distribution of soil areas on the obtained digital soil map is in agreement with modern cartographic data and the SRTM digital elevation model (SRTM DEM). The regional soil classification developed by G.I. Ivanov was used in the legend to the soil map. The names of soil units were also correlated with the names suggested in the modern Russian soil classification system. The major soil units on the map are at the soil subtypes that reflect the entire vertical spectrum of soils in the south of the Far East of Russia (Primorye region). These are mountainous tundra soils, podzolic soils, brown taiga soils, mountainous brown forest soils, bleached brown soils, meadow-brown soils, meadow gley soils, and floodplain soils). With the help of the spatial analysis function of GIS, the comparison of the particular characteristics of the soil cover with numerical characteristics of the topography, geological composition of catchments, and vegetation cover was performed.

Mapping soil texture classes and optimization of the result by accuracy assessment

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Takács, Katalin; Bakacsi, Zsófia; Szabó, József; Pásztor, László

2014-05-01

There are increasing demands nowadays on spatial soil information in order to support environmental related and land use management decisions. The GlobalSoilMap.net (GSM) project aims to make a new digital soil map of the world using state-of-the-art and emerging technologies for soil mapping and predicting soil properties at fine resolution. Sand, silt and clay are among the mandatory GSM soil properties. Furthermore, soil texture class information is input data of significant agro-meteorological and hydrological models. Our present work aims to compare and evaluate different digital soil mapping methods and variables for producing the most accurate spatial prediction of texture classes in Hungary. In addition to the Hungarian Soil Information and Monitoring System as our basic data, digital elevation model and its derived components, geological database, and physical property maps of the Digital Kreybig Soil Information System have been applied as auxiliary elements. Two approaches have been applied for the mapping process. At first the sand, silt and clay rasters have been computed independently using regression kriging (RK). From these rasters, according to the USDA categories, we have compiled the texture class map. Different combinations of reference and training soil data and auxiliary covariables have resulted several different maps. However, these results consequentially include the uncertainty factor of the three kriged rasters. Therefore we have suited data mining methods as the other approach of digital soil mapping. By working out of classification trees and random forests we have got directly the texture class maps. In this way the various results can be compared to the RK maps. The performance of the different methods and data has been examined by testing the accuracy of the geostatistically computed and the directly classified results. We have used the GSM methodology to assess the most predictive and accurate way for getting the best among the several result maps. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

IASMHYN: A web tool for mapping Soil Water Budget and agro-hydrological assessment trough the integration of monitoring and remote sensing data

NASA Astrophysics Data System (ADS)

Bagli, Stefano; Pistocchi, Alberto; Mazzoli, Paolo; Borga, Marco; Bertoldi, Giacomo; Brenner, Johannes; Luzzi, Valerio

2016-04-01

Climate change, increasing pressure on farmland to satisfy the growing demand, and need to ensure environmental quality for agriculture in order to be competitive require an increasing capacity of water management. In this context, web-based for forecasting and monitoring the hydrological conditions of topsoil can be an effective means to save water, maximize crop protection and reduce soil loss and the leaching of pollutants. Such tools need to be targeted to the users and be accessible in a simple way in order to allow adequate take up in the practice. IASMHYN "Improved management of Agricultural Systems by Monitoring and Hydrological evaluation" is a web mapping service designed to provide and update on a daily basis the main water budget variables for farmland management. A beta version of the tool is available at www.gecosistema.com/iasmhyn . IASMHYN is an instrument for "second level monitoring" that takes into account accurate hydro-meteorological information's from ground stations and remote sensing sources, and turns them into practically usable decision variables for precision farming, making use of geostatistical analysis and hydrological models The main routines embedded in IASMYHN exclusively use open source libraries (R packages and Python), to perform following operations: (1) Automatic acquisition of observed data, both from ground stations and remote sensing, concerning precipitation (RADAR) and temperature (MODIS-LST) available from various sources; (2) Interpolation of acquisitions through regression kriging in order to spatially map the meteorological data; (3) Run of hydrological models to obtain spatial information of hydrological soil variables of immediate interest in agriculture. The real time results that are produced are available trough a web interface and provide the user with spatial maps and time series of the following variables, supporting decision on irrigation, soil protection from erosion, pollution risk of groundwater and streams: - Daily precipitation and its characteristics (rain, snow or hail, rain erosiveness); - Maximum, minimum and average daily temperature; - Soil Water Content (SWC); - Infiltration into the deep layers of the soil and surface runoff; - Potential loss of soil due to erosion - Residence time of a possible chemical (pesticides, fertilizers) applied to the soil. Thematic real time maps are produced give the user support decision on irrigation, soil management and pesticide/fertilizer application. The ongoing project will also lead to validation and improvement of estimates of hydrological variables from satellite imagery and radar data. The tool has been cross-validated with estimates of evapotranspiration and soil water content in agricultural sites in South Tyrol (Italy) in the framework of MONALISA project (http://www.monalisa-project.eu). A comparison with physical based models, satellite imagery and radar data will allow further generalization of the product. The ultimate goal of the tool is to make available on the market a service that is generally applicable in Europe , using commonly available data, to provide single farmers and organizations effective and up to date information for planning and programming their activities.

Visualizing Soil Landscapes on Mobile Devices

NASA Astrophysics Data System (ADS)

Schulze, Darrell; Lindbo, David

2016-04-01

The Integrating Spatial Educational Experiences (Isee) project utilizes the most detailed US soil survey data to create thematic maps of soil properties that are then combined with a highly optimized hillshade basemap for display. The Isee app, currently available for the iPad platform from the Apple App Store, allows the cached maps to be zoomed and panned quickly to any location down to a scale of 1:18,000. Maps currently available for the states of Indiana, Illinois, Kentucky, Ohio, Texas, West Virginia, and Wisconsin include, Dominant Soil Parent Materials, Natural Soil Drainage Classes, Limiting Layers, Surface Soil Colors, and Acid Subsoils. Other thematic maps will be added in the future. The ability to zoom, pan, and change maps quickly allows the user to see and understand soil landscape relationships that are not often apparent using static maps, while the ability to access the maps conveniently in the field allows the user to see how soil landscape features on the maps appear in the field.

The automated reference toolset: A soil-geomorphic ecological potential matching algorithm

USGS Publications Warehouse

Nauman, Travis; Duniway, Michael C.

2016-01-01

Ecological inventory and monitoring data need referential context for interpretation. Identification of appropriate reference areas of similar ecological potential for site comparison is demonstrated using a newly developed automated reference toolset (ART). Foundational to identification of reference areas was a soil map of particle size in the control section (PSCS), a theme in US Soil Taxonomy. A 30-m resolution PSCS map of the Colorado Plateau (366,000 km2) was created by interpolating ∼5000 field soil observations using a random forest model and a suite of raster environmental spatial layers representing topography, climate, general ecological community, and satellite imagery ratios. The PSCS map had overall out of bag accuracy of 61.8% (Kappa of 0.54, p < 0.0001), and an independent validation accuracy of 93.2% at a set of 356 field plots along the southern edge of Canyonlands National Park, Utah. The ART process was also tested at these plots, and matched plots with the same ecological sites (ESs) 67% of the time where sites fell within 2-km buffers of each other. These results show that the PSCS and ART have strong application for ecological monitoring and sampling design, as well as assessing impacts of disturbance and land management action using an ecological potential framework. Results also demonstrate that PSCS could be a key mapping layer for the USDA-NRCS provisional ES development initiative.

Development of predictive mapping techniques for soil survey and salinity mapping

NASA Astrophysics Data System (ADS)

Elnaggar, Abdelhamid A.

Conventional soil maps represent a valuable source of information about soil characteristics, however they are subjective, very expensive, and time-consuming to prepare. Also, they do not include explicit information about the conceptual mental model used in developing them nor information about their accuracy, in addition to the error associated with them. Decision tree analysis (DTA) was successfully used in retrieving the expert knowledge embedded in old soil survey data. This knowledge was efficiently used in developing predictive soil maps for the study areas in Benton and Malheur Counties, Oregon and accessing their consistency. A retrieved soil-landscape model from a reference area in Harney County was extrapolated to develop a preliminary soil map for the neighboring unmapped part of Malheur County. The developed map had a low prediction accuracy and only a few soil map units (SMUs) were predicted with significant accuracy, mostly those shallow SMUs that have either a lithic contact with the bedrock or developed on a duripan. On the other hand, the developed soil map based on field data was predicted with very high accuracy (overall was about 97%). Salt-affected areas of the Malheur County study area are indicated by their high spectral reflectance and they are easily discriminated from the remote sensing data. However, remote sensing data fails to distinguish between the different classes of soil salinity. Using the DTA method, five classes of soil salinity were successfully predicted with an overall accuracy of about 99%. Moreover, the calculated area of salt-affected soil was overestimated when mapped using remote sensing data compared to that predicted by using DTA. Hence, DTA could be a very helpful approach in developing soil survey and soil salinity maps in more objective, effective, less-expensive and quicker ways based on field data.

A novel approach to validate satellite soil moisture retrievals using precipitation data

NASA Astrophysics Data System (ADS)

Karthikeyan, L.; Kumar, D. Nagesh

2016-10-01

A novel approach is proposed that attempts to validate passive microwave soil moisture retrievals using precipitation data (applied over India). It is based on the concept that the expectation of precipitation conditioned on soil moisture follows a sigmoidal convex-concave-shaped curve, the characteristic of which was recently shown to be represented by mutual information estimated between soil moisture and precipitation. On this basis, with an emphasis over distribution-free nonparametric computations, a new measure called Copula-Kernel Density Estimator based Mutual Information (CKDEMI) is introduced. The validation approach is generic in nature and utilizes CKDEMI in tandem with a couple of proposed bootstrap strategies, to check accuracy of any two soil moisture products (here Advanced Microwave Scanning Radiometer-EOS sensor's Vrije Universiteit Amsterdam-NASA (VUAN) and University of Montana (MONT) products) using precipitation (India Meteorological Department) data. The proposed technique yields a "best choice soil moisture product" map which contains locations where any one of the two/none of the two/both the products have produced accurate retrievals. The results indicated that in general, VUA-NASA product has performed well over University of Montana's product for India. The best choice soil moisture map is then integrated with land use land cover and elevation information using a novel probability density function-based procedure to gain insight on conditions under which each of the products has performed well. Finally, the impact of using a different precipitation (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources) data set over the best choice soil moisture product map is also analyzed. The proposed methodology assists researchers and practitioners in selecting the appropriate soil moisture product for various assimilation strategies at both basin and continental scales.

Mapping soil texture targeting predefined depth range or synthetizing from standard layers?

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Dezső Kaposi, András; Szatmári, Gábor; Takács, Katalin; Pásztor, László

2017-04-01

There are increasing demands nowadays on spatial soil information in order to support environmental related and land use management decisions. Physical soil properties, especially particle size distribution play important role in this context. A few of the requirements can be satisfied by the sand-, silt-, and clay content maps compiled according to global standards such as GlobalSoilMap (GSM) or Soil Grids. Soil texture classes (e. g. according to USDA classification) can be derived from these three fraction data, in this way texture map can be compiled based on the proper separate maps. Soil texture class as well as fraction information represent direct input of crop-, meteorological- and hydrological models. The model inputs frequently require maps representing soil features of 0-30 cm depth, which is covered by three consecutive depth intervals according to standard specifications: 0-5 cm, 5-15 cm, 15-30 cm. Becoming GSM and SoilGrids the most detailed freely available spatial soil data sources, the common model users (e. g. meteorologists, agronomists, or hydrologists) would produce input map from (the weighted mean of) these three layers. However, if the basic soil data and proper knowledge is obtainable, a soil texture map targeting directly the 0-30 cm layer could be independently compiled. In our work we compared Hungary's soil texture maps compiled using the same reference and auxiliary data and inference methods but for differing layer distribution. We produced the 0-30 cm clay, silt and sand map as well as the maps for the three standard layers (0-5 cm, 5-15 cm, 15-30 cm). Maps of sand, silt and clay percentage were computed through regression kriging (RK) applying Additive Log-Ratio (alr) transformation. In addition to the Hungarian Soil Information and Monitoring System as reference soil data, digital elevation model and its derived components, soil physical property maps, remotely sensed images, land use -, geological-, as well as meteorological data were applied as auxiliary variables. We compared the directly compiled and the synthetized clay-, sand content, and texture class maps by different tools. In addition to pairwise comparison of basic statistical features (histograms, scatter plots), we examined the spatial distribution of the differences. We quantified the taxonomical distances of the textural classes, in order to investigate the differences of the map-pairs. We concluded that the directly computed and the synthetized maps show various differences. In the case of clay-, and sand content maps, the map-pairs have to be considered statistically different. On the other hand, the differences of the texture class maps are not significant. However, in all cases, the differences rather concern the extreme ranges and categories. Using of synthetized maps can intensify extremities by error propagation in models and scenarios. Based on our results, we suggest the usage of the directly composed maps.

Applications of Geostatistics in Plant Nematology

PubMed Central

Wallace, M. K.; Hawkins, D. M.

1994-01-01

The application of geostatistics to plant nematology was made by evaluating soil and nematode data acquired from 200 soil samples collected from the Ap horizon of a reed canary-grass field in northern Minnesota. Geostatistical concepts relevant to nematology include semi-variogram modelling, kriging, and change of support calculations. Soil and nematode data generally followed a spherical semi-variogram model, with little random variability associated with soil data and large inherent variability for nematode data. Block kriging of soil and nematode data provided useful contour maps of the data. Change of snpport calculations indicated that most of the random variation in nematode data was due to short-range spatial variability in the nematode population densities. PMID:19279938

Applications of geostatistics in plant nematology.

PubMed

Wallace, M K; Hawkins, D M

1994-12-01

The application of geostatistics to plant nematology was made by evaluating soil and nematode data acquired from 200 soil samples collected from the A(p) horizon of a reed canary-grass field in northern Minnesota. Geostatistical concepts relevant to nematology include semi-variogram modelling, kriging, and change of support calculations. Soil and nematode data generally followed a spherical semi-variogram model, with little random variability associated with soil data and large inherent variability for nematode data. Block kriging of soil and nematode data provided useful contour maps of the data. Change of snpport calculations indicated that most of the random variation in nematode data was due to short-range spatial variability in the nematode population densities.

Remote sensing of physiographic soil units of Bennett County, South Dakota

NASA Technical Reports Server (NTRS)

Frazee, C. J.; Gropper, J. L.; Westin, F. C.

1973-01-01

A study was conducted in Bennett County, South Dakota, to establish a rangeland test site for evaluating the usefulness of ERTS data for mapping soil resources in rangeland areas. Photographic imagery obtained in October, 1970, was analyzed to determine which type of imagery is best for mapping drainage and land use patterns. Imagery of scales ranging from 1:1,000,000 to 1.20,000 was used to delineate soil-vegetative physiographic units. The photo characteristics used to define physiographic units were texture, drainage pattern, tone pattern, land use pattern and tone. These units will be used as test data for evaluating ERTS data. The physiographic units were categorized into a land classification system. The various categories which were delineated at the different scales of imagery were designed to be useful for different levels of land use planning. The land systems are adequate only for planning of large areas for general uses. The lowest category separated was the facet. The facets have a definite soil composition and represent different soil landscapes. These units are thought to be useful for providing natural resource information needed for local planning.

Permeability of soils in Mississippi

USGS Publications Warehouse

O'Hara, Charles G.

1994-01-01

The permeability of soils in Mississippi was determined and mapped using a geographic information system (GIS). Soil permeabilities in Mississippi were determined to range in value from nearly 0.0 to values exceeding 5.0 inches per hour. The U.S. Soil Conservation Service's State Soil Geographic Data Base (STATSGO) was used as the primary source of data for the determination of area-weighted soil permeability. STATSGO provides soil layer properties that are spatially referenced to mapped areas. These mapped areas are referred to as polygons in the GIS. The polygons arc boundaries of soils mapped as a group and are given unique Map Unit Identifiers (MUIDs). The data describing the physical characteristics of the soils within each polygon are stored in a tabular data base format and are referred to as attributes. The U.S. Soil Conservation Service developed STATSGO to be primarily used as a guide for regional resource planning, management, and monitoring. STATSGO was designed so that soil information could be extracted from properties tables at the layer level, combined by component, and statistically expanded to cover the entire map unit. The results of this study provide a mapped value for permeability which is representative of the vertical permeability of soils in that area. The resultant permeability map provides a representative vertical soil permeability for a given area sufficient for county, multi- county, and area planning, and will be used as the soil permeability data component in the evaluation of the susceptibility of major aquifers to contami- nation in Mississippi.

Concepts of soil mapping as a basis for the assessment of soil functions

NASA Astrophysics Data System (ADS)

Baumgarten, Andreas

2014-05-01

Soil mapping systems in Europe have been designed mainly as a tool for the description of soil characteristics from a morphogenetic viewpoint. Contrasting to the American or FAO system, the soil development has been in the main focus of European systems. Nevertheless , recent developments in soil science stress the importance of the functions of soils with respect to the ecosystems. As soil mapping systems usually offer a sound and extensive database, the deduction of soil functions from "classic" mapping parameters can be used for local and regional assessments. According to the used pedo-transfer functions and mapping systems, tailored approaches can be chosen for different applications. In Austria, a system mainly for spatial planning purposes has been developed that will be presented and illustrated by means of best practice examples.

Recent development in preparation of European soil hydraulic maps

NASA Astrophysics Data System (ADS)

Toth, B.; Weynants, M.; Pasztor, L.; Hengl, T.

2017-12-01

Reliable quantitative information on soil hydraulic properties is crucial for modelling hydrological, meteorological, ecological and biological processes of the Critical Zone. Most of the Earth system models need information on soil moisture retention capacity and hydraulic conductivity in the full matric potential range. These soil hydraulic properties can be quantified, but their measurement is expensive and time consuming, therefore measurement-based catchment scale mapping of these soil properties is not possible. The increasing availability of soil information and methods describing relationships between simple soil characteristics and soil hydraulic properties provide the possibility to derive soil hydraulic maps based on spatial soil datasets and pedotransfer functions (PTFs). Over the last decade there has been a significant development in preparation of soil hydraulic maps. Spatial datasets on model parameters describing the soil hydraulic processes have become available for countries, continents and even for the whole globe. Our aim is to present European soil hydraulic maps, show their performance, highlight their advantages and drawbacks, and propose possible ways to further improve the performance of those.

Evaluation of digital soil mapping approaches with large sets of environmental covariates

NASA Astrophysics Data System (ADS)

Nussbaum, Madlene; Spiess, Kay; Baltensweiler, Andri; Grob, Urs; Keller, Armin; Greiner, Lucie; Schaepman, Michael E.; Papritz, Andreas

2018-01-01

The spatial assessment of soil functions requires maps of basic soil properties. Unfortunately, these are either missing for many regions or are not available at the desired spatial resolution or down to the required soil depth. The field-based generation of large soil datasets and conventional soil maps remains costly. Meanwhile, legacy soil data and comprehensive sets of spatial environmental data are available for many regions. Digital soil mapping (DSM) approaches relating soil data (responses) to environmental data (covariates) face the challenge of building statistical models from large sets of covariates originating, for example, from airborne imaging spectroscopy or multi-scale terrain analysis. We evaluated six approaches for DSM in three study regions in Switzerland (Berne, Greifensee, ZH forest) by mapping the effective soil depth available to plants (SD), pH, soil organic matter (SOM), effective cation exchange capacity (ECEC), clay, silt, gravel content and fine fraction bulk density for four soil depths (totalling 48 responses). Models were built from 300-500 environmental covariates by selecting linear models through (1) grouped lasso and (2) an ad hoc stepwise procedure for robust external-drift kriging (georob). For (3) geoadditive models we selected penalized smoothing spline terms by component-wise gradient boosting (geoGAM). We further used two tree-based methods: (4) boosted regression trees (BRTs) and (5) random forest (RF). Lastly, we computed (6) weighted model averages (MAs) from the predictions obtained from methods 1-5. Lasso, georob and geoGAM successfully selected strongly reduced sets of covariates (subsets of 3-6 % of all covariates). Differences in predictive performance, tested on independent validation data, were mostly small and did not reveal a single best method for 48 responses. Nevertheless, RF was often the best among methods 1-5 (28 of 48 responses), but was outcompeted by MA for 14 of these 28 responses. RF tended to over-fit the data. The performance of BRT was slightly worse than RF. GeoGAM performed poorly on some responses and was the best only for 7 of 48 responses. The prediction accuracy of lasso was intermediate. All models generally had small bias. Only the computationally very efficient lasso had slightly larger bias because it tended to under-fit the data. Summarizing, although differences were small, the frequencies of the best and worst performance clearly favoured RF if a single method is applied and MA if multiple prediction models can be developed.

Evaluation of HCMM satellite data for estuarine tidal circulation patterns and thermal inertia soil moisture measurements. [Delaware Bay, Cooper River, and the Potomac River estuaries; Luverne, Minnesota, soil moisture, and water temperature of Lake Anna, Virginia

NASA Technical Reports Server (NTRS)

Wiesnet, D. R.; Mcginnis, D. F., Jr. (Principal Investigator); Matson, M.; Pritchard, J. A.

1981-01-01

Digital thermal maps of the Cooper River (SC) and the Potomac River estuaries were prepared from heat capacity mapping radiometer (HCMR) tapes. Tidal phases were correctly interpreted and verified. Synoptic surface circulation patterns were charted by location thermal fronts and water mass boundaries within the estuaries. Thermal anomalies were detected adjacent of a conventional power plant on the Potomac. Under optimum conditions, estuaries as small as the Cooper River can be monitored for generalized thermal/tidal circulation patterns by the HCMM-type IR sensors. The HCMM thermal inertia approach to estimating soil moisture at the Luverne (MN) test site was found to be unsatisfactory as a NESS operational satellite technique because of cloud cover interference. Thermal-IR data show similar structure of the Baltimore and Washington heat islands when compared to NOAA AVHRR thermal-IR data. Thermal anomalies from the warm water discharge water of a nuclear power plant were mapped in Lake Anna, Virginia.

Exploring the potential offered by legacy soil databases for ecosystem services mapping of Central African soils

NASA Astrophysics Data System (ADS)

Verdoodt, Ann; Baert, Geert; Van Ranst, Eric

2014-05-01

Central African soil resources are characterised by a large variability, ranging from stony, shallow or sandy soils with poor life-sustaining capabilities to highly weathered soils that recycle and support large amounts of biomass. Socio-economic drivers within this largely rural region foster inappropriate land use and management, threaten soil quality and finally culminate into a declining soil productivity and increasing food insecurity. For the development of sustainable land use strategies targeting development planning and natural hazard mitigation, decision makers often rely on legacy soil maps and soil profile databases. Recent development cooperation financed projects led to the design of soil information systems for Rwanda, D.R. Congo, and (ongoing) Burundi. A major challenge is to exploit these existing soil databases and convert them into soil inference systems through an optimal combination of digital soil mapping techniques, land evaluation tools, and biogeochemical models. This presentation aims at (1) highlighting some key characteristics of typical Central African soils, (2) assessing the positional, geographic and semantic quality of the soil information systems, and (3) revealing its potential impacts on the use of these datasets for thematic mapping of soil ecosystem services (e.g. organic carbon storage, pH buffering capacity). Soil map quality is assessed considering positional and semantic quality, as well as geographic completeness. Descriptive statistics, decision tree classification and linear regression techniques are used to mine the soil profile databases. Geo-matching as well as class-matching approaches are considered when developing thematic maps. Variability in inherent as well as dynamic soil properties within the soil taxonomic units is highlighted. It is hypothesized that within-unit variation in soil properties highly affects the use and interpretation of thematic maps for ecosystem services mapping. Results will mainly be based on analyses done in Rwanda, but can be complemented with ongoing research results or prospects for Burundi.

Optimal mapping of site-specific multivariate soil properties.

PubMed

Burrough, P A; Swindell, J

1997-01-01

This paper demonstrates how geostatistics and fuzzy k-means classification can be used together to improve our practical understanding of crop yield-site response. Two aspects of soil are important for precision farming: (a) sensible classes for a given crop, and (b) their spatial variation. Local site classifications are more sensitive than general taxonomies and can be provided by the method of fuzzy k-means to transform a multivariate data set with i attributes measured at n sites into k overlapping classes; each site has a membership value mk for each class in the range 0-1. Soil variation is of interest when conditions vary over patches manageable by agricultural machinery. The spatial variation of each of the k classes can be analysed by computing the variograms of mk over the n sites. Memberships for each of the k classes can be mapped by ordinary kriging. Areas of class dominance and the transition zones between them can be identified by an inter-class confusion index; reducing the zones to boundaries gives crisp maps of dominant soil groups that can be used to guide precision farming equipment. Automation of the procedure is straightforward given sufficient data. Time variations in soil properties can be automatically incorporated in the computation of membership values. The procedures are illustrated with multi-year crop yield data collected from a 5 ha demonstration field at the Royal Agricultural College in Cirencester, UK.

One perspective on spatial variability in geologic mapping

USGS Publications Warehouse

Markewich, H.W.; Cooper, S.C.

1991-01-01

This paper discusses some of the differences between geologic mapping and soil mapping, and how the resultant maps are interpreted. The role of spatial variability in geologic mapping is addressed only indirectly because in geologic mapping there have been few attempts at quantification of spatial differences. This is largely because geologic maps deal with temporal as well as spatial variability and consider time, age, and origin, as well as composition and geometry. Both soil scientists and geologists use spatial variability to delineate mappable units; however, the classification systems from which these mappable units are defined differ greatly. Mappable soil units are derived from systematic, well-defined, highly structured sets of taxonomic criteria; whereas mappable geologic units are based on a more arbitrary heirarchy of categories that integrate many features without strict values or definitions. Soil taxonomy is a sorting tool used to reduce heterogeneity between soil units. Thus at the series level, soils in any one series are relatively homogeneous because their range of properties is small and well-defined. Soil maps show the distribution of soils on the land surface. Within a map area, soils, which are often less than 2 m thick, show a direct correlation to topography and to active surface processes as well as to parent material.

Updating categorical soil maps using limited survey data by Bayesian Markov chain cosimulation.

PubMed

Li, Weidong; Zhang, Chuanrong; Dey, Dipak K; Willig, Michael R

2013-01-01

Updating categorical soil maps is necessary for providing current, higher-quality soil data to agricultural and environmental management but may not require a costly thorough field survey because latest legacy maps may only need limited corrections. This study suggests a Markov chain random field (MCRF) sequential cosimulation (Co-MCSS) method for updating categorical soil maps using limited survey data provided that qualified legacy maps are available. A case study using synthetic data demonstrates that Co-MCSS can appreciably improve simulation accuracy of soil types with both contributions from a legacy map and limited sample data. The method indicates the following characteristics: (1) if a soil type indicates no change in an update survey or it has been reclassified into another type that similarly evinces no change, it will be simply reproduced in the updated map; (2) if a soil type has changes in some places, it will be simulated with uncertainty quantified by occurrence probability maps; (3) if a soil type has no change in an area but evinces changes in other distant areas, it still can be captured in the area with unobvious uncertainty. We concluded that Co-MCSS might be a practical method for updating categorical soil maps with limited survey data.

Updating Categorical Soil Maps Using Limited Survey Data by Bayesian Markov Chain Cosimulation

PubMed Central

Dey, Dipak K.; Willig, Michael R.

2013-01-01

Updating categorical soil maps is necessary for providing current, higher-quality soil data to agricultural and environmental management but may not require a costly thorough field survey because latest legacy maps may only need limited corrections. This study suggests a Markov chain random field (MCRF) sequential cosimulation (Co-MCSS) method for updating categorical soil maps using limited survey data provided that qualified legacy maps are available. A case study using synthetic data demonstrates that Co-MCSS can appreciably improve simulation accuracy of soil types with both contributions from a legacy map and limited sample data. The method indicates the following characteristics: (1) if a soil type indicates no change in an update survey or it has been reclassified into another type that similarly evinces no change, it will be simply reproduced in the updated map; (2) if a soil type has changes in some places, it will be simulated with uncertainty quantified by occurrence probability maps; (3) if a soil type has no change in an area but evinces changes in other distant areas, it still can be captured in the area with unobvious uncertainty. We concluded that Co-MCSS might be a practical method for updating categorical soil maps with limited survey data. PMID:24027447

Binational digital soils map of the Ambos Nogales watershed, southern Arizona and northern Sonora, Mexico

USGS Publications Warehouse

Norman, Laura

2004-01-01

We have prepared a digital map of soil parameters for the international Ambos Nogales watershed to use as input for selected soils-erosion models. The Ambos Nogales watershed in southern Arizona and northern Sonora, Mexico, contains the Nogales wash, a tributary of the Upper Santa Cruz River. The watershed covers an area of 235 km2, just under half of which is in Mexico. Preliminary investigations of potential erosion revealed a discrepancy in soils data and mapping across the United States-Mexican border due to issues including different mapping resolutions, incompatible formatting, and varying nomenclature and classification systems. To prepare a digital soils map appropriate for input to a soils-erosion model, the historical analog soils maps for Nogales, Ariz., were scanned and merged with the larger-scale digital soils data available for Nogales, Sonora, Mexico using a geographic information system.

iSOIL: Interactions between soil related sciences - Linking geophysics, soil science and digital soil mapping

NASA Astrophysics Data System (ADS)

Dietrich, Peter; Werban, Ulrike; Sauer, Uta

2010-05-01

High-resolution soil property maps are one major prerequisite for the specific protection of soil functions and restoration of degraded soils as well as sustainable land use, water and environmental management. To generate such maps the combination of digital soil mapping approaches and remote as well as proximal soil sensing techniques is most promising. However, a feasible and reliable combination of these technologies for the investigation of large areas (e.g. catchments and landscapes) and the assessment of soil degradation threats is missing. Furthermore, there is insufficient dissemination of knowledge on digital soil mapping and proximal soil sensing in the scientific community, to relevant authorities as well as prospective users. As one consequence there is inadequate standardization of techniques. At the poster we present the EU collaborative project iSOIL within the 7th framework program of the European Commission. iSOIL focuses on improving fast and reliable mapping methods of soil properties, soil functions and soil degradation risks. This requires the improvement and integration of advanced soil sampling approaches, geophysical and spectroscopic measuring techniques, as well as pedometric and pedophysical approaches. The focus of the iSOIL project is to develop new and to improve existing strategies and innovative methods for generating accurate, high resolution soil property maps. At the same time the developments will reduce costs compared to traditional soil mapping. ISOIL tackles the challenges by the integration of three major components: (i)high resolution, non-destructive geophysical (e.g. Electromagnetic Induction EMI; Ground Penetrating Radar, GPR; magnetics, seismics) and spectroscopic (e.g., Near Surface Infrared, NIR) methods, (ii)Concepts of Digital Soil Mapping (DSM) and pedometrics as well as (iii)optimized soil sampling with respect to profound soil scientific and (geo)statistical strategies. A special focus of iSOIL lies on the sustainable dissemination of technologies and concepts developed in the projects through workshops for stakeholders and the publication of a handbook "Methods and Technologies for Mapping of Soil Properties, Function and Threat Risks". Besides, the CEN Workshop offers a new mechanism and approach to standardization. During the project we decided that the topic of the CEN Workshop should focus on a voluntary standardization of electromagnetic induction measurement to ensure that results can be evaluated and processed under uniform circumstances and can be comparable. At the poster we will also present the idea and the objectives of our CEN Workshop "Best Practice Approach for electromagnetic induction measurements of the near surface"and invite every interested person to participate.

Spatial Prediction of Soil Classes by Using Soil Weathering Parameters Derived from vis-NIR Spectroscopy

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, Leonardo; Alexandre Dematte, Jose

2010-05-01

There is consensus in the scientific community about the great need of spatial soil information. Conventional mapping methods are time consuming and involve high costs. Digital soil mapping has emerged as an area in which the soil mapping is optimized by the application of mathematical and statistical approaches, as well as the application of expert knowledge in pedology. In this sense, the objective of the study was to develop a methodology for the spatial prediction of soil classes by using soil spectroscopy methodologies related with fieldwork, spectral data from satellite image and terrain attributes in simultaneous. The studied area is located in São Paulo State, and comprised an area of 473 ha, which was covered by a regular grid (100 x 100 m). In each grid node was collected soil samples at two depths (layers A and B). There were extracted 206 samples from transect sections and submitted to soil analysis (clay, Al2O3, Fe2O3, SiO2 TiO2, and weathering index). The first analog soil class map (ASC-N) contains only soil information regarding from orders to subgroups of the USDA Soil Taxonomy System. The second (ASC-H) map contains some additional information related to some soil attributes like color, ferric levels and base sum. For the elaboration of the digital soil maps the data was divided into three groups: i) Predicted soil attributes of the layer B (related to the soil weathering) which were obtained by using a local soil spectral library; ii) Spectral bands data extracted from a Landsat image; and iii) Terrain parameters. This information was summarized by a principal component analysis (PCA) in each group. Digital soil maps were generated by supervised classification using a maximum likelihood method. The trainee information for this classification was extracted from five toposequences based on the analog soil class maps. The spectral models of weathering soil attributes shown a high predictive performance with low error (R2 0.71 to 0.90). The spatial prediction of these attributes also showed a high performance (validations with R2> 0.78). These models allowed to increase spatial resolution of soil weathering information. On the other hand, the comparison between the analog and digital soil maps showed a global accuracy of 69% for the ASC-N map and 62% in the ASC-H map, with kappa indices of 0.52 and 0.45 respectively.

Magnetic properties of soils in boreal regions. Case study from Ukraine

NASA Astrophysics Data System (ADS)

Menshov, Oleksandr; Kruglov, Oleksandr; Sukhorada, Anatoliy

2014-05-01

The investigation of soil magnetism is a part of the general soil researching for solving soil science and agronomy tasks. Soils are rather magnetic and sometimes they are the main near-surface object, which generates local magnetic anomalies. Soils have been studied within the main soil-climatic zones of Ukraine: Polesie, Forest Steppe, Steppe, Dry Steppe, Crimean and Carpathian mountains. The investigated soils types are: soddy-podsolic, gray forest, chestnut, chernozems leached, typical, ordinary, southern, and meadow, turf, bog soils, brawn and mountains soils. A part of Ukraine soils are from boreal regions. Among them are chernozems of Polesie soil-climatic zone. This territory was under influence of ice age. Another part of Ukraine boreal region is Carpathian maintains with special type of climate, landscapes and soils. The comprehensive analyze of Ukraine soils from the boreal territories and other parts is presented. Soil magnetism increases from North to South in the transition between the soil-climatic zones of Ukraine. The most magnetic are ordinary and south chernozems. The least magnetic are soddy-podzolic, meadaw and bog soils. The maximal values of the magnetic parameters are fixed in the watersheds, plateaus of the landscapes, minimal values are fixed in the floods, ravines, bor terraces. Magnetic susceptibility mapping is useful for agricultural mapping of lands, investigation of erosion, soil fertility, the necessity for mineral and organic fertilizers. Magnetic methods of investigations are high speed, effective and low-cost. Moreover, the magnetic methods a very important if the dangerous soil processes could not be fixed with visual image. In the same time, these hazards effect on the conditioning and the productivity of agricultural land. We have marked the decreasing of the magnetic susceptibility values within the risk of erosion sections of the catena.

Spatial correlation of shear-wave velocity in the San Francisco Bay Area sediments

USGS Publications Warehouse

Thompson, E.M.; Baise, L.G.; Kayen, R.E.

2007-01-01

Ground motions recorded within sedimentary basins are variable over short distances. One important cause of the variability is that local soil properties are variable at all scales. Regional hazard maps developed for predicting site effects are generally derived from maps of surficial geology; however, recent studies have shown that mapped geologic units do not correlate well with the average shear-wave velocity of the upper 30 m, Vs(30). We model the horizontal variability of near-surface soil shear-wave velocity in the San Francisco Bay Area to estimate values in unsampled locations in order to account for site effects in a continuous manner. Previous geostatistical studies of soil properties have shown horizontal correlations at the scale of meters to tens of meters while the vertical correlations are on the order of centimeters. In this paper we analyze shear-wave velocity data over regional distances and find that surface shear-wave velocity is correlated at horizontal distances up to 4 km based on data from seismic cone penetration tests and the spectral analysis of surface waves. We propose a method to map site effects by using geostatistical methods based on the shear-wave velocity correlation structure within a sedimentary basin. If used in conjunction with densely spaced shear-wave velocity profiles in regions of high seismic risk, geostatistical methods can produce reliable continuous maps of site effects. ?? 2006 Elsevier Ltd. All rights reserved.

Application of multispectral remote sensing to soil survey research in Indiana

NASA Technical Reports Server (NTRS)

Zachary, A. L.; Cipra, J. E.; Diderickson, R. I.; Kristof, S. J.; Baumgardner, M. F.

1972-01-01

Computer-implemented mappings based on spectral properties of bare soil surfaces were compared with mapping units of interest to soil surveyors. Some soil types could be differentiated by their spectral properties. In other cases, soils with similar surface colors and textures could not be distinguished spectrally. The spectral maps seemed useful for delineating boundaries between soils in many cases.

High resolution digital soil mapping as a future instrument for developing sustainable landuse strategies

NASA Astrophysics Data System (ADS)

Gries, Philipp; Funke, Lisa-Marie; Baumann, Frank; Schmidt, Karsten; Behrens, Thorsten; Scholten, Thomas

2016-04-01

Climate change, increase in population and intensification of land use pose a great challenge for sustainable handling of soils. Intelligent landuse systems are able to minimize and/or avoid soil erosion and loss of soil fertility. A successful application of such systems requires area-wide soil information with high resolution. Containing three consecutive steps, the project INE-2-H („innovative sustainable landuse") at the University of Tuebingen is about creating high-resolution soil information using Digital Soil Mapping (DSM) techniques to develop sustainable landuse strategies. Input data includes soil data from fieldwork (texture and carbon content), the official digital soil and geological map (1:50.000) as well as a wide selection of local, complex and combined terrain parameters. First, soil maps have been created using the DSM approach and Random Forest (RF). Due to high resolution (10x10 m pixels), those maps show a more detailed spatial variability of soil information compared to the official maps used. Root mean square errors (RMSE) of the modelled maps vary from 2.11 % to 6.87 % and the coefficients of determination (R²) go from 0.42 to 0.68. Second, soil erosion potentials have been estimated according to the Universal Soil Loss Equation (USLE). Long-term average annual soil loss ranges from 0.56 to 24.23 [t/ha/a]. Third, combining high-resolution erosion potentials with expert-knowledge of local farmers will result in a landuse system adapted to local conditions. This system will include sustainable strategies reducing soil erosion and conserving soil fertility.

Impact of Sub-grid Soil Textural Properties on Simulations of Hydrological Fluxes at the Continental Scale Mississippi River Basin

NASA Astrophysics Data System (ADS)

Kumar, R.; Samaniego, L. E.; Livneh, B.

2013-12-01

Knowledge of soil hydraulic properties such as porosity and saturated hydraulic conductivity is required to accurately model the dynamics of near-surface hydrological processes (e.g. evapotranspiration and root-zone soil moisture dynamics) and provide reliable estimates of regional water and energy budgets. Soil hydraulic properties are commonly derived from pedo-transfer functions using soil textural information recorded during surveys, such as the fractions of sand and clay, bulk density, and organic matter content. Typically large scale land-surface models are parameterized using a relatively coarse soil map with little or no information on parametric sub-grid variability. In this study we analyze the impact of sub-grid soil variability on simulated hydrological fluxes over the Mississippi River Basin (≈3,240,000 km2) at multiple spatio-temporal resolutions. A set of numerical experiments were conducted with the distributed mesoscale hydrologic model (mHM) using two soil datasets: (a) the Digital General Soil Map of the United States or STATSGO2 (1:250 000) and (b) the recently collated Harmonized World Soil Database based on the FAO-UNESCO Soil Map of the World (1:5 000 000). mHM was parameterized with the multi-scale regionalization technique that derives distributed soil hydraulic properties via pedo-transfer functions and regional coefficients. Within the experimental framework, the 3-hourly model simulations were conducted at four spatial resolutions ranging from 0.125° to 1°, using meteorological datasets from the NLDAS-2 project for the time period 1980-2012. Preliminary results indicate that the model was able to capture observed streamflow behavior reasonably well with both soil datasets, in the major sub-basins (i.e. the Missouri, the Upper Mississippi, the Ohio, the Red, and the Arkansas). However, the spatio-temporal patterns of simulated water fluxes and states (e.g. soil moisture, evapotranspiration) from both simulations, showed marked differences; particularly at a shorter time scale (hours to days) in regions with coarse texture sandy soils. Furthermore, the partitioning of total runoff into near-surface interflows and baseflow components was also significantly different between the two simulations. Simulations with the coarser soil map produced comparatively higher baseflows. At longer time scales (months to seasons) where climatic factors plays a major role, the integrated fluxes and states from both sets of model simulations match fairly closely, despite the apparent discrepancy in the partitioning of total runoff.

Modelling Soil-Landscapes in Coastal California Hills Using Fine Scale Terrestrial Lidar

NASA Astrophysics Data System (ADS)

Prentice, S.; Bookhagen, B.; Kyriakidis, P. C.; Chadwick, O.

2013-12-01

Digital elevation models (DEMs) are the dominant input to spatially explicit digital soil mapping (DSM) efforts due to their increasing availability and the tight coupling between topography and soil variability. Accurate characterization of this coupling is dependent on DEM spatial resolution and soil sampling density, both of which may limit analyses. For example, DEM resolution may be too coarse to accurately reflect scale-dependent soil properties yet downscaling introduces artifactual uncertainty unrelated to deterministic or stochastic soil processes. We tackle these limitations through a DSM effort that couples moderately high density soil sampling with a very fine scale terrestrial lidar dataset (20 cm) implemented in a semiarid rolling hillslope domain where terrain variables change rapidly but smoothly over short distances. Our guiding hypothesis is that in this diffusion-dominated landscape, soil thickness is readily predicted by continuous terrain attributes coupled with catenary hillslope segmentation. We choose soil thickness as our keystone dependent variable for its geomorphic and hydrologic significance, and its tendency to be a primary input to synthetic ecosystem models. In defining catenary hillslope position we adapt a logical rule-set approach that parses common terrain derivatives of curvature and specific catchment area into discrete landform elements (LE). Variograms and curvature-area plots are used to distill domain-scale terrain thresholds from short range order noise characteristic of very fine-scale spatial data. The revealed spatial thresholds are used to condition LE rule-set inputs, rendering a catenary LE map that leverages the robustness of fine-scale terrain data to create a generalized interpretation of soil geomorphic domains. Preliminary regressions show that continuous terrain variables alone (curvature, specific catchment area) only partially explain soil thickness, and only in a subset of soils. For example, at spatial scales up 20, curvature explains 40% of soil thickness variance among soils <3 m deep, while soils >3 m deep show no clear relation to curvature. To further demonstration our geomorphic segmentation approach, we apply it to DEM domains where diffusion processes are less dominant than in our primary study area. Classified landform map derived from fine scale terrestrial lidar. Color classes depict hydrogeomorphic process domains in zero order watersheds.

Determining and representing width of soil boundaries using electrical conductivity and MultiGrid

NASA Astrophysics Data System (ADS)

Greve, Mogens Humlekrog; Greve, Mette Balslev

2004-07-01

In classical soil mapping, map unit boundaries are considered crisp even though all experienced survey personnel are aware of the fact, that soil boundaries really are transition zones of varying width. However, classification of transition zone width on site is difficult in a practical survey. The objective of this study is to present a method for determining soil boundary width and a way of representing continuous soil boundaries in GIS. A survey was performed using the non-contact conductivity meter EM38 from Geonics Inc., which measures the bulk Soil Electromagnetic Conductivity (SEC). The EM38 provides an opportunity to classify the width of transition zones in an unbiased manner. By calculating the spatial rate of change in the interpolated EM38 map across the crisp map unit delineations from a classical soil mapping, a measure of transition zone width can be extracted. The map unit delineations are represented as transition zones in a GIS through a concept of multiple grid layers, a MultiGrid. Each layer corresponds to a soil type and the values in a layer represent the percentage of that soil type in each cell. As a test, the subsoil texture was mapped at the Vindum field in Denmark using both the classical mapping method with crisp representation of the boundaries and the new map with MultiGrid and continuous boundaries. These maps were then compared to an independent reference map of subsoil texture. The improvement of the prediction of subsoil texture, using continuous boundaries instead of crisp, was in the case of the Vindum field, 15%.

The History of Soil Mapping and Classification in Europe: The role of the European Commission

NASA Astrophysics Data System (ADS)

Montanarella, Luca

2014-05-01

Early systematic soil mapping in Europe dates back to the early times of soil science in the 19th Century and was developed at National scales mostly for taxation purposes. National soil classification systems emerged out of the various scientific communities active at that time in leading countries like Germany, Austria, France, Belgium, United Kingdom and many others. Different scientific communities were leading in the various countries, in some cases stemming from geological sciences, in others as a branch of agricultural sciences. Soil classification for the purpose of ranking soils for their capacity to be agriculturally productive emerged as the main priority, allowing in some countries for very detailed and accurate soil maps at 1:5,000 scale and larger. Detailed mapping was mainly driven by taxation purposes in the early times but evolved in several countries also as a planning and management tool for farms and local administrations. The need for pan-European soil mapping and classification efforts emerged only after World War II in the early 1950's under the auspices of FAO with the aim to compile a common European soil map as a contribution to the global soil mapping efforts of FAO at that time. These efforts evolved over the next decades, with the support of the European Commission, towards the establishment of a permanent network of National soil survey institutions (the European Soil Bureau Network). With the introduction of digital soil mapping technologies, the new European Soil Information System (EUSIS) was established, incorporating data at multiple scales for the EU member states and bordering countries. In more recent years, the formal establishment of the European Soil Data Centre (ESDAC) hosted by the European Commission, together with a formal legal framework for soil mapping and soil classification provided by the INSPIRE directive and the related standardization and harmonization efforts, has led to the operational development of advanced digital soil mapping techniques supporting the contribution of Europe to a common global soil information system under the coordination of the Global Soil Partnership (GSP) of FAO. Further information: http://eusoils.jrc.ec.europa.eu/ References: Mark G Kibblewhite, Ladislav Miko, Luca Montanarella, Legal frameworks for soil protection: current development and technical information requirements, Current Opinion in Environmental Sustainability, Volume 4, Issue 5, November 2012, Pages 573-577. Luca Montanarella, Ronald Vargas, Global governance of soil resources as a necessary condition for sustainable development, Current Opinion in Environmental Sustainability, Volume 4, Issue 5, November 2012, Pages 559-564.

Remote sensing of soils, land forms, and land use in the northern great plains in preparation for ERTS applications

NASA Technical Reports Server (NTRS)

Frazee, C. J.; Westin, F. C.; Gropper, J.; Myers, V. I.

1972-01-01

Research to determine the optimum time or season for obtaining imagery to identify and map soil limitations was conducted in the proposed Oahe irrigation project area in South Dakota. The optimum time for securing photographs or imagery is when the soil surface patterns are most apparent. For cultivated areas similar to the study area, May is the optimum time. The fields are cultivated or the planted crop has not yet masked soil surface features. Soil limitations in 59 percent of the field of the flight line could be mapped using the above criteria. The remaining fields cannot be mapped because the vegetation or growing crops do not express features related to soil differences. This suggests that imagery from more than one year is necessary to map completely the soil limitations of Oahe area by remote sensing techniques. Imagery from the other times studied is not suitable for identifying and mapping soil limitations of Oahe area by remote sensing techniques. Imagery from the other times studied is not suitable for identifying and mapping soil limitations because the vegetative cover masked the soil surface and does not reflect soil differences.

Engineering geological mapping in Wallonia (Belgium) : present state and recent computerized approach

NASA Astrophysics Data System (ADS)

Delvoie, S.; Radu, J.-P.; Ruthy, I.; Charlier, R.

2012-04-01

An engineering geological map can be defined as a geological map with a generalized representation of all the components of a geological environment which are strongly required for spatial planning, design, construction and maintenance of civil engineering buildings. In Wallonia (Belgium) 24 engineering geological maps have been developed between the 70s and the 90s at 1/5,000 or 1/10,000 scale covering some areas of the most industrialized and urbanized cities (Liège, Charleroi and Mons). They were based on soil and subsoil data point (boring, drilling, penetration test, geophysical test, outcrop…). Some displayed data present the depth (with isoheights) or the thickness (with isopachs) of the different subsoil layers up to about 50 m depth. Information about geomechanical properties of each subsoil layer, useful for engineers and urban planners, is also synthesized. However, these maps were built up only on paper and progressively needed to be updated with new soil and subsoil data. The Public Service of Wallonia and the University of Liège have recently initiated a study to evaluate the feasibility to develop engineering geological mapping with a computerized approach. Numerous and various data (about soil and subsoil) are stored into a georelational database (the geotechnical database - using Access, Microsoft®). All the data are geographically referenced. The database is linked to a GIS project (using ArcGIS, ESRI®). Both the database and GIS project consist of a powerful tool for spatial data management and analysis. This approach involves a methodology using interpolation methods to update the previous maps and to extent the coverage to new areas. The location (x, y, z) of each subsoil layer is then computed from data point. The geomechanical data of these layers are synthesized in an explanatory booklet joined to maps.

Integrated terrain mapping with digital Landsat images in Queensland, Australia

USGS Publications Warehouse

Robinove, Charles Joseph

1979-01-01

Mapping with Landsat images usually is done by selecting single types of features, such as soils, vegetation, or rocks, and creating visually interpreted or digitally classified maps of each feature. Individual maps can then be overlaid on or combined with other maps to characterize the terrain. Integrated terrain mapping combines several terrain features into each map unit which, in many cases, is more directly related to uses of the land and to methods of land management than the single features alone. Terrain brightness, as measured by the multispectral scanners in Landsat 1 and 2, represents an integration of reflectance from the terrain features within the scanner's instantaneous field of view and is therefore more correlatable with integrated terrain units than with differentiated ones, such as rocks, soils, and vegetation. A test of the feasibilty of the technique of mapping integrated terrain units was conducted in a part of southwestern Queensland, Australia, in cooperation with scientists of the Queensland Department of Primary Industries. The primary purpose was to test the use of digital classification techniques to create a 'land systems map' usable for grazing land management. A recently published map of 'land systems' in the area (made by aerial photograph interpretation and ground surveys), which are integrated terrain units composed of vegetation, soil, topography, and geomorphic features, was used as a basis for comparison with digitally classified Landsat multispectral images. The land systems, in turn, each have a specific grazing capacity for cattle (expressed in beasts per km 2 ) which is estimated following analysis of both research results and property carrying capacities. Landsat images, in computer-compatible tape form, were first contrast-stretched to increase their visual interpretability, and digitally classified by the parallelepiped method into distinct spectral classes to determine their correspondence to the land systems classes and to areally smaller, but readily recognizable, 'land units.' Many land systems appeared as distinct spectral classes or as acceptably homogeneous combinations of several spectral classes. The digitally classified map corresponded to the general geographic patterns of many of the land systems. Statistical correlation of the digitally classified map and the published map was not possible because the published map showed only land systems whereas the digitally classified map showed some land units as well as systems. The general correspondence of spectral classes to the integrated terrain units means that the digital mapping of the units may precede fieldwork and act as a guide to field sampling and detailed terrain unit description as well as measuring of the location, area, and extent of each unit. Extension of the Landsat mapping and classification technique to other arid and semi-arid regions of the world may be feasible.

Taxonomic classification of soils using digital information from LANDSAT data. Huayllamarca and eucaliptus areas. M.S. Thesis - Bolivia Univ.

NASA Technical Reports Server (NTRS)

Quiroga, S. Q.

1977-01-01

The applicability of LANDSAT digital information to soil mapping is described. A compilation of all cartographic information and bibliography of the study area is made. LANDSAT MSS images on a scale of 1:250,000 are interpreted and a physiographic map with legend is prepared. The study area is inspected and a selection of the sample areas is made. A digital map of the different soil units is produced and the computer mapping units are checked against the soil units encountered in the field. The soil boundaries obtained by automatic mapping were not substantially changed by field work. The accuracy of the automatic mapping is rather high.

Using digital soil maps to infer edaphic affinities of plant species in Amazonia: Problems and prospects.

PubMed

Moulatlet, Gabriel Massaine; Zuquim, Gabriela; Figueiredo, Fernando Oliveira Gouvêa; Lehtonen, Samuli; Emilio, Thaise; Ruokolainen, Kalle; Tuomisto, Hanna

2017-10-01

Amazonia combines semi-continental size with difficult access, so both current ranges of species and their ability to cope with environmental change have to be inferred from sparse field data. Although efficient techniques for modeling species distributions on the basis of a small number of species occurrences exist, their success depends on the availability of relevant environmental data layers. Soil data are important in this context, because soil properties have been found to determine plant occurrence patterns in Amazonian lowlands at all spatial scales. Here we evaluate the potential for this purpose of three digital soil maps that are freely available online: SOTERLAC, HWSD, and SoilGrids. We first tested how well they reflect local soil cation concentration as documented with 1,500 widely distributed soil samples. We found that measured soil cation concentration differed by up to two orders of magnitude between sites mapped into the same soil class. The best map-based predictor of local soil cation concentration was obtained with a regression model combining soil classes from HWSD with cation exchange capacity (CEC) from SoilGrids. Next, we evaluated to what degree the known edaphic affinities of thirteen plant species (as documented with field data from 1,200 of the soil sample sites) can be inferred from the soil maps. The species segregated clearly along the soil cation concentration gradient in the field, but only partially along the model-estimated cation concentration gradient, and hardly at all along the mapped CEC gradient. The main problems reducing the predictive ability of the soil maps were insufficient spatial resolution and/or georeferencing errors combined with thematic inaccuracy and absence of the most relevant edaphic variables. Addressing these problems would provide better models of the edaphic environment for ecological studies in Amazonia.

Neighborhood size of training data influences soil map disaggregation

USDA-ARS?s Scientific Manuscript database

Soil class mapping relies on the ability of sample locations to represent portions of the landscape with similar soil types; however, most digital soil mapping (DSM) approaches intersect sample locations with one raster pixel per covariate layer regardless of pixel size. This approach does not take ...

Assimilation of optical and radar remote sensing data in 3D mapping of soil properties over large areas.

PubMed

Poggio, Laura; Gimona, Alessandro

2017-02-01

Soil is very important for many land functions. To achieve sustainability it is important to understand how soils vary over space in the landscape. Remote sensing data can be instrumental in mapping and spatial modelling of soil properties, resources and their variability. The aims of this study were to compare satellite sensors (MODIS, Landsat, Sentinel-1 and Sentinel-2) with varying spatial, temporal and spectral resolutions for Digital Soil Mapping (DSM) of a set of soil properties in Scotland, evaluate the potential benefits of adding Sentinel-1 data to DSM models, select the most suited mix of sensors for DSM to map the considered set of soil properties and validate the results of topsoil (2D) and whole profile (3D) models. The results showed that the use of a mixture of sensors proved more effective to model and map soil properties than single sensors. The use of radar Sentinel-1 data proved useful for all soil properties, improving the prediction capability of models with only optical bands. The use of MODIS time series provided stronger relationships than the use of temporal snapshots. The results showed good validation statistics with a RMSE below 20% of the range for all considered soil properties. The RMSE improved from previous studies including only MODIS sensor and using a coarser prediction grid. The performance of the models was similar to previous studies at regional, national or continental scale. A mix of optical and radar data proved useful to map soil properties along the profile. The produced maps of soil properties describing both lateral and vertical variability, with associated uncertainty, are important for further modelling and management of soil resources and ecosystem services. Coupled with further data the soil properties maps could be used to assess soil functions and therefore conditions and suitability of soils for a range of purposes. Copyright © 2016 Elsevier B.V. All rights reserved.

Mapping Copper and Lead Concentrations at Abandoned Mine Areas Using Element Analysis Data from ICP–AES and Portable XRF Instruments: A Comparative Study

PubMed Central

Lee, Hyeongyu; Choi, Yosoon; Suh, Jangwon; Lee, Seung-Ho

2016-01-01

Understanding spatial variation of potentially toxic trace elements (PTEs) in soil is necessary to identify the proper measures for preventing soil contamination at both operating and abandoned mining areas. Many studies have been conducted worldwide to explore the spatial variation of PTEs and to create soil contamination maps using geostatistical methods. However, they generally depend only on inductively coupled plasma atomic emission spectrometry (ICP–AES) analysis data, therefore such studies are limited by insufficient input data owing to the disadvantages of ICP–AES analysis such as its costly operation and lengthy period required for analysis. To overcome this limitation, this study used both ICP–AES and portable X-ray fluorescence (PXRF) analysis data, with relatively low accuracy, for mapping copper and lead concentrations at a section of the Busan abandoned mine in Korea and compared the prediction performances of four different approaches: the application of ordinary kriging to ICP–AES analysis data, PXRF analysis data, both ICP–AES and transformed PXRF analysis data by considering the correlation between the ICP–AES and PXRF analysis data, and co-kriging to both the ICP–AES (primary variable) and PXRF analysis data (secondary variable). Their results were compared using an independent validation data set. The results obtained in this case study showed that the application of ordinary kriging to both ICP–AES and transformed PXRF analysis data is the most accurate approach when considers the spatial distribution of copper and lead contaminants in the soil and the estimation errors at 11 sampling points for validation. Therefore, when generating soil contamination maps for an abandoned mine, it is beneficial to use the proposed approach that incorporates the advantageous aspects of both ICP–AES and PXRF analysis data. PMID:27043594

Mapping Copper and Lead Concentrations at Abandoned Mine Areas Using Element Analysis Data from ICP-AES and Portable XRF Instruments: A Comparative Study.

PubMed

Lee, Hyeongyu; Choi, Yosoon; Suh, Jangwon; Lee, Seung-Ho

2016-03-30

Understanding spatial variation of potentially toxic trace elements (PTEs) in soil is necessary to identify the proper measures for preventing soil contamination at both operating and abandoned mining areas. Many studies have been conducted worldwide to explore the spatial variation of PTEs and to create soil contamination maps using geostatistical methods. However, they generally depend only on inductively coupled plasma atomic emission spectrometry (ICP-AES) analysis data, therefore such studies are limited by insufficient input data owing to the disadvantages of ICP-AES analysis such as its costly operation and lengthy period required for analysis. To overcome this limitation, this study used both ICP-AES and portable X-ray fluorescence (PXRF) analysis data, with relatively low accuracy, for mapping copper and lead concentrations at a section of the Busan abandoned mine in Korea and compared the prediction performances of four different approaches: the application of ordinary kriging to ICP-AES analysis data, PXRF analysis data, both ICP-AES and transformed PXRF analysis data by considering the correlation between the ICP-AES and PXRF analysis data, and co-kriging to both the ICP-AES (primary variable) and PXRF analysis data (secondary variable). Their results were compared using an independent validation data set. The results obtained in this case study showed that the application of ordinary kriging to both ICP-AES and transformed PXRF analysis data is the most accurate approach when considers the spatial distribution of copper and lead contaminants in the soil and the estimation errors at 11 sampling points for validation. Therefore, when generating soil contamination maps for an abandoned mine, it is beneficial to use the proposed approach that incorporates the advantageous aspects of both ICP-AES and PXRF analysis data.

An evaluation of machine processing techniques of ERTS-1 data for user applications. [urban land use and soil association mapping in Indiana

NASA Technical Reports Server (NTRS)

Landgrebe, D.

1974-01-01

A broad study is described to evaluate a set of machine analysis and processing techniques applied to ERTS-1 data. Based on the analysis results in urban land use analysis and soil association mapping together with previously reported results in general earth surface feature identification and crop species classification, a profile of general applicability of this procedure is beginning to emerge. Put in the hands of a user who knows well the information needed from the data and also is familiar with the region to be analyzed it appears that significantly useful information can be generated by these methods. When supported by preprocessing techniques such as the geometric correction and temporal registration capabilities, final products readily useable by user agencies appear possible. In parallel with application, through further research, there is much potential for further development of these techniques both with regard to providing higher performance and in new situations not yet studied.

STATEWIDE MAPPING OF FLORIDA SOIL RADON POTENTIALS VOLUME 2. APPENDICES A-P

EPA Science Inventory

The report gives results of a statewide mapping of Florida soil radon potentials. Statewide maps identify Florida Regions with different levels of soil radon potential. The maps provide scientific estimates of regional radon potentials that can serve as a basis for implementing r...

STATEWIDE MAPPING OF FLORIDA SOIL RADON POTENTIALS VOLUME 1. TECHNICAL REPORT

EPA Science Inventory

The report gives results of a statewide mapping of Florida soil radon potentials. Statewide maps identify Florida Regions with different levels of soil radon potential. The maps provide scientific estimates of regional radon potentials that can serve as a basis for implementing r...

Principles of soil mapping of a megalopolis with St. Petersburg as an example

NASA Astrophysics Data System (ADS)

Aparin, B. F.; Sukhacheva, E. Yu.

2014-07-01

For the first time, a soil map of St. Petersburg has been developed on a scale of 1 : 50000 using MicroStation V8i software. The legend to this map contains more than 60 mapping units. The classification of urban soils and information on the soil cover patterns are principally new elements of this legend. New concepts of the urbanized soil space and urbopedocombinations have been suggested for soil mapping of urban territories. The typification of urbopedocombinations in St. Petersburg has been performed on the basis of data on the geometry and composition of the polygons of soils and nonsoil formations. The ratio between the areas of soils and nonsoil formations and their spatial distribution patterns have been used to distinguish between six types of the urbanized soil space. The principles of classification of the soils of urban territories have been specified, and a separate order of pedo-allochthonous soils has been suggested for inclusion into the Classification and Diagnostic System of Russian Soils (2004). Six types of pedo-allochthonous soils have been distinguished on the basis of data on their humus and organic horizons and the character of the underlying mineral substrate.

Soil property maps of Africa at 250 m resolution

NASA Astrophysics Data System (ADS)

Kempen, Bas; Hengl, Tomislav; Heuvelink, Gerard B. M.; Leenaars, Johan G. B.; Walsh, Markus G.; MacMillan, Robert A.; Mendes de Jesus, Jorge S.; Shepherd, Keith; Sila, Andrew; Desta, Lulseged T.; Tondoh, Jérôme E.

2015-04-01

Vast areas of arable land in sub-Saharan Africa suffer from low soil fertility and physical soil constraints, and significant amounts of nutrients are lost yearly due to unsustainable soil management practices. At the same time it is expected that agriculture in Africa must intensify to meet the growing demand for food and fiber the next decades. Protection and sustainable management of Africa's soil resources is crucial to achieve this. In this context, comprehensive, accurate and up-to-date soil information is an essential input to any agricultural or environmental management or policy and decision-making model. In Africa, detailed soil information has been fragmented and limited to specific zones of interest for decades. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. AfSIS builds on recent advances in digital soil mapping, infrared spectroscopy, remote sensing, (geo)statistics, and integrated soil fertility management to improve the way soils are evaluated, mapped, and monitored. Over the period 2008-2014, the AfSIS project has compiled two soil profile data sets (about 28,000 unique locations): the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site (new soil samples) database -- the two data sets represent the most comprehensive soil sample database of the African continent to date. In addition a large set of high-resolution environmental data layers (covariates) was assembled. The point data were used in the AfSIS project to generate a set of maps of key soil properties for the African continent at 250 m spatial resolution: sand, silt and clay fractions, bulk density, organic carbon, total nitrogen, pH, cation-exchange capacity, exchangeable bases (Ca, K, Mg, Na), exchangeable acidity, and Al content. These properties were mapped for six depth intervals up to 2 m: 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm. Random forests modelling was used to relate the soil profile observations to a set covariates, that included global soil class and property maps, MODIS imagery and a DEM, in a 3D mapping framework. The model residuals were interpolated by 3D kriging, after which the kriging predictions were added to the random forests predictions to obtain the soil property predictions. The model predictions were validated with 5-fold cross-validation. The random forests models explained between 37% (exch. Na) and 85% (Al content) of the variation in the data. Results also show that globally predicted soil classes help improve continental scale mapping of the soil nutrients and are often among the most important predictors. We conclude that the first mapping results look promising. We used an automated modelling framework that enables re-computing the maps as new data becomes arrives, hereby gradually improving the maps. We showed that global maps of soil classes and properties produced with models that were predominantly calibrated on areas with plentiful observations can be used to improve the accuracy of predictions in regions with less plentiful data, such as Africa.

An overview on the history of pedology and soil mapping in Italy

NASA Astrophysics Data System (ADS)

Calzolari, C.

2012-04-01

In Italy, the word pedology (pedologia) was introduced in a text book as synonym of soil science for the first time in 1904 by Vinassa de Regny. In the literature, the term cohabitates with the words agrology (agrologia), agro-geology (agro-geologia), agricultural geognostic (geognostica agraria), geopedology (geo-pedologia) used in different historical moments by differently rooted soil scientists. When early pedologists started with systematic studies of soils, their characteristics and geography, they were strongly influenced by their cultural background, mainly geology and agro-chemistry. Along the time, the soil concept evolved, as did the concept of pedology, and this is somehow witnessed by the use of different Italian words with reference to soil: suolo, terreno, terra. Differently from agro-chemists, early pedologists based the soil study on the field description of soil profile. This was firstly based on the vertical differentiation between humus rich layers and "inactive" layers and later on, as long as the discipline evolved, on the presence of genetic horizons. The first complete soil map of Italy is dated 1928. Its Author, the geologist De Angelis d'Ossat, was the president of the organising committee of the 1924 International Soil Conference of Rome, where the International Society of Soil Science was founded. The map was based on the geological map of Italy, drafted in scale 1:1,000,000 after the creation of the Kingdom of Italy in 1861. The internal disputes within the Geological Society, together with the scarce interest of most of geologists for soil, did not facilitate the birth of a central soil survey. Soil mapping was mainly conducted by universities and research institutes, and we had to wait until 1953 for a new soil map (scale 1:3,125,000) at national level to be realised by Paolo Principi, based on literature data. In 1966 a new 1:1,000,000 soil map of Italy was eventually published by a national committee, led by Fiorenzo Mancini. This was based on literature data and on field surveys, and the mapping units limits, based on geomorphology, are still the basis of the most updated European 1:1,000,000 soil map. At the end of the 80ies of the past century, soil survey and mapping were taken over by the Italian regional administrations, which set up regional soil surveys working in co-ordination among them and with the research institutions.

Soils of Walker Branch Watershed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lietzke, D.A.

1994-03-01

The soil survey of Walker Branch Watershed (WBW) utilized the most up-to-date knowledge of soils, geology, and geohydrology in building the soils data base needed to reinterpret past research and to begin new research in the watershed. The soils of WBW were also compared with soils mapped elsewhere along Chestnut Ridge on the Oak Ridge Reservation to (1) establish whether knowledge obtained elsewhere could be used within the watershed, (2) determine whether there were any soils restricted to the watershed, and (3) evaluate geologic formation lateral variability. Soils, surficial geology, and geomorphology were mapped at a scale of 1:1,200 usingmore » a paper base map having 2-ft contour intervals. Most of the contours seemed to reasonably represent actual landform configurations, except for dense wooded areas. For example, the very large dolines or sinkholes were shown on the contour base map, but numerous smaller ones were not. In addition, small drainageways and gullies were often not shown. These often small but important features were located approximately as soil mapping progressed.« less

Comparing the performance of various digital soil mapping approaches to map physical soil properties

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Takács, Katalin; Pásztor, László

2015-04-01

Spatial information on physical soil properties is intensely expected, in order to support environmental related and land use management decisions. One of the most widely used properties to characterize soils physically is particle size distribution (PSD), which determines soil water management and cultivability. According to their size, different particles can be categorized as clay, silt, or sand. The size intervals are defined by national or international textural classification systems. The relative percentage of sand, silt, and clay in the soil constitutes textural classes, which are also specified miscellaneously in various national and/or specialty systems. The most commonly used is the classification system of the United States Department of Agriculture (USDA). Soil texture information is essential input data in meteorological, hydrological and agricultural prediction modelling. Although Hungary has a great deal of legacy soil maps and other relevant soil information, it often occurs, that maps do not exist on a certain characteristic with the required thematic and/or spatial representation. The recent developments in digital soil mapping (DSM), however, provide wide opportunities for the elaboration of object specific soil maps (OSSM) with predefined parameters (resolution, accuracy, reliability etc.). Due to the simultaneous richness of available Hungarian legacy soil data, spatial inference methods and auxiliary environmental information, there is a high versatility of possible approaches for the compilation of a given soil map. This suggests the opportunity of optimization. For the creation of an OSSM one might intend to identify the optimum set of soil data, method and auxiliary co-variables optimized for the resources (data costs, computation requirements etc.). We started comprehensive analysis of the effects of the various DSM components on the accuracy of the output maps on pilot areas. The aim of this study is to compare and evaluate different digital soil mapping methods and sets of ancillary variables for producing the most accurate spatial prediction of texture classes in a given area of interest. Both legacy and recently collected data on PSD were used as reference information. The predictor variable data set consisted of digital elevation model and its derivatives, lithology, land use maps as well as various bands and indices of satellite images. Two conceptionally different approaches can be applied in the mapping process. Textural classification can be realized after particle size data were spatially extended by proper geostatistical method. Alternatively, the textural classification is carried out first, followed by the spatial extension through suitable data mining method. According to the first approach, maps of sand, silt and clay percentage have been computed through regression kriging (RK). Since the three maps are compositional (their sum must be 100%), we applied Additive Log-Ratio (alr) transformation, instead of kriging them independently. Finally, the texture class map has been compiled according to the USDA categories from the three maps. Different combinations of reference and training soil data and auxiliary covariables resulted several different maps. On the basis of the other way, the PSD were classified firstly into the USDA categories, then the texture class maps were compiled directly by data mining methods (classification trees and random forests). The various results were compared to each other as well as to the RK maps. The performance of the different methods and data sets has been examined by testing the accuracy of the geostatistically computed and the directly classified results to assess the most predictive and accurate method. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Digital soils survey map of the Patagonia Mountains, Arizona

USGS Publications Warehouse

Norman, Laura; Wissler, Craig; Guertin, D. Phillip; Gray, Floyd

2002-01-01

The ‘Soil Survey of Santa Cruz and Parts of Cochise and Pima Counties, Arizona,' a product of the USDA’s Soil Conservation Service and the Forest Service in cooperation with the Arizona Agricultural Experiment Station, released in 1979, was created according to the site conditions in 1971, when soil scientists identified soils types on aerial photographs. The scale at which these maps were published is 1:20,000. These soil maps were automated for incorporation into the hydrologic modeling within a GIS. The aerial photos onto which the soils units were drawn had not been orthoganalized, and contained distortion. A total of 15 maps composed the study area. These maps were scanned into TIFF format using an 8-bit black and white drum scanner at 100 dpi. The images were imported into ERDAS IMAGINE and the white borders were removed through subset decollaring processes. Five CD-ROM’s containing Digital Orthophoto Quarter Quads (DOQQ’s) were used to register and rectify the scanned soils maps. Polygonal data was then attributed according to the datasets.

Digital soil mapping as a tool for quantifying state-and-transition models

USDA-ARS?s Scientific Manuscript database

Ecological sites and associated state-and-transition models (STMs) are rapidly becoming important land management tools in rangeland systems in the US and around the world. Descriptions of states and transitions are largely developed from expert knowledge and generally accepted species and community...

National Dam Safety Program. Structure F-1 (MO 20512), Verdigris - Neosho River Basin, Newton County, Missouri. Phase I Inspection Report.

DTIC Science & Technology

1980-08-01

soil series. These soils generally make good fill material when properly compacted. The "Geologic Map ot Missouri" indicates that two known faults run in...appurtenant structures, reser- voir, and downstream features are presented in Appendix D. B. Dam: The dam appears to be in good condition. No sloughing...or sliding of the embankment was noted. The horizontal and vertical alignments of the crest were good , and no surfacing cracking or unusual movement

Mapping permeability over the surface of the Earth

USGS Publications Warehouse

Gleeson, T.; Smith, L.; Moosdorf, N.; Hartmann, J.; Durr, H.H.; Manning, A.H.; Van Beek, L. P. H.; Jellinek, A. Mark

2011-01-01

Permeability, the ease of fluid flow through porous rocks and soils, is a fundamental but often poorly quantified component in the analysis of regional-scale water fluxes. Permeability is difficult to quantify because it varies over more than 13 orders of magnitude and is heterogeneous and dependent on flow direction. Indeed, at the regional scale, maps of permeability only exist for soil to depths of 1-2 m. Here we use an extensive compilation of results from hydrogeologic models to show that regional-scale (>5 km) permeability of consolidated and unconsolidated geologic units below soil horizons (hydrolithologies) can be characterized in a statistically meaningful way. The representative permeabilities of these hydrolithologies are used to map the distribution of near-surface (on the order of 100 m depth) permeability globally and over North America. The distribution of each hydrolithology is generally scale independent. The near-surface mean permeability is of the order of ???5 ?? 10-14 m2. The results provide the first global picture of near-surface permeability and will be of particular value for evaluating global water resources and modeling the influence of climate-surface-subsurface interactions on global climate change. Copyright ?? 2011 by the American Geophysical Union.

Mapping permeability over the surface of the Earth

USGS Publications Warehouse

Gleeson, Tom; Smith, Leslie; Moosdorf, Nils; Hartmann, Jens; Durr, Hans H.; Manning, Andrew H.; van Beek, Ludovicus P. H.; Jellinek, A. Mark

2011-01-01

Permeability, the ease of fluid flow through porous rocks and soils, is a fundamental but often poorly quantified component in the analysis of regional-scale water fluxes. Permeability is difficult to quantify because it varies over more than 13 orders of magnitude and is heterogeneous and dependent on flow direction. Indeed, at the regional scale, maps of permeability only exist for soil to depths of 1-2 m. Here we use an extensive compilation of results from hydrogeologic models to show that regional-scale (>5 km) permeability of consolidated and unconsolidated geologic units below soil horizons (hydrolithologies) can be characterized in a statistically meaningful way. The representative permeabilities of these hydrolithologies are used to map the distribution of near-surface (on the order of 100 m depth) permeability globally and over North America. The distribution of each hydrolithology is generally scale independent. The near-surface mean permeability is of the order of -5 x 10-14 m2. The results provide the first global picture of near-surface permeability and will be of particular value for evaluating global water resources and modeling the influence of climate-surface-subsurface interactions on global climate change.

The Dokuchaev hypothesis as a basis for predictive digital soil mapping (on the 125th anniversary of its publication)

NASA Astrophysics Data System (ADS)

Florinsky, I. V.

2012-04-01

Predictive digital soil mapping is widely used in soil science. Its objective is the prediction of the spatial distribution of soil taxonomic units and quantitative soil properties via the analysis of spatially distributed quantitative characteristics of soil-forming factors. Western pedometrists stress the scientific priority and principal importance of Hans Jenny's book (1941) for the emergence and development of predictive soil mapping. In this paper, we demonstrate that Vasily Dokuchaev explicitly defined the central idea and statement of the problem of contemporary predictive soil mapping in the year 1886. Then, we reconstruct the history of the soil formation equation from 1899 to 1941. We argue that Jenny adopted the soil formation equation from Sergey Zakharov, who published it in a well-known fundamental textbook in 1927. It is encouraging that this issue was clarified in 2011, the anniversary year for publications of Dokuchaev and Jenny.

Effects of anthropogenic particles on the chemical and geophysical properties of urban soils, Detroit, Michigan

NASA Astrophysics Data System (ADS)

Orlicki, Katharine M.

There is a great need in many cities for a better quality of urban soil maps. This is due to the increasing interest in repurposing vacant land for urban redevelopment, agriculture, and green infrastructure. Mapping vacant urban land in Detroit can be very difficult because anthropogenic soils were often highly variable and frequently contained demolition debris (such as brick), making it difficult to use a hand auger. This study was undertaken in Detroit, MI to create a more efficient way to map urban soils based on their geophysical and chemical properties. This will make the mapping process faster, less labor intensive, and therefore more cost effective. Optical and chemical criteria for the identification and classification of microartifacts (MAs) were made from a set of reference artifacts of a known origin. These MAs were then observed and tested in urban topsoil samples from sites in Detroit, Michigan that represent three different land use types (residential demolition, fly ash-impacted, and industrial). Optical analyses, SEM, EDAX, and XRD showed that reference MAs may be classified into five basic compositional types (carbonaceous, calcareous, siliceous, ferruginous and miscellaneous). Reference MAs were generally distinguishable using optical microscopy by color, luster, fracture and microtexture. MAs that were more difficult to classify were further differentiable when using SEM, EDAX, and XRD. MAs were found in all of the anthropogenic soils studied, but were highly variable. All three study sites had concentrations coal-related wastes were the most common types of MAs observed and often included coal, ash (microspheres, microagglomerate), cinders, and burnt shale. MAs derived from waste building materials such as brick, mortar, and glass, were typically found on residential demolition sites. Manufacturing waste MAs, which included iron-making slag and coked coal were commonly observed on industrial sites. Fly ash-impacted sites were composed of only microspheres and microagglomerate that were concentrated within the soils by airborne deposition, making it widespread. These results support the hypothesis that MA assemblages of distinct composition vary with land use. Therefore, it seems likely that magnetic susceptibility surveying and other geophysical methods will prove effective for mapping anthropogenic soils on vacant urban land. Anthropogenic soils and MAs were assessed for pH, electrical conductivity (EC), and magnetic susceptibility (MS). The A horizons of urban soils at residential demolition, industrial-impacted, and fly ash-impacted sites were found to be distinguishable from those of native soils. Anthropogenic soils were higher by one pH unit or more than the background level, had an EC value two to three times the background level, and had MS measurements up to 20 times greater than the background level. The analysis of reference artifacts suggested that the elevated pH of anthropogenic soils was caused by calcareous building material wastes, the elevated EC were the result of both calcareous and ferruginous wastes, and elevated MS were attributable to ferromagnetic materials. Anthropogenic soils collected at residential demolition sites were differentiable by EC, whereas those at collected form industrial sites were distinguishable using MS. Therefore, anthropogenic soils and native soils have a unique chemical and geophysical signature which can be highly dependent on the concentration of MAs. This suggests that EC and MS surveying methods may be used to remotely sense and map urban soils more effectively than using traditional methods alone.

Analyzing existing conventional soil information sources to be incorporated in thematic Spatial Data Infrastructures

NASA Astrophysics Data System (ADS)

Pascual-Aguilar, J. A.; Rubio, J. L.; Domínguez, J.; Andreu, V.

2012-04-01

New information technologies give the possibility of widespread dissemination of spatial information to different geographical scales from continental to local by means of Spatial Data Infrastructures. Also administrative awareness on the need for open access information services has allowed the citizens access to this spatial information through development of legal documents, such as the INSPIRE Directive of the European Union, adapted by national laws as in the case of Spain. The translation of the general criteria of generic Spatial Data Infrastructures (SDI) to thematic ones is a crucial point for the progress of these instruments as large tool for the dissemination of information. In such case, it must be added to the intrinsic criteria of digital information, such as the harmonization information and the disclosure of metadata, the own environmental information characteristics and the techniques employed in obtaining it. In the case of inventories and mapping of soils, existing information obtained by traditional means, prior to the digital technologies, is considered to be a source of valid information, as well as unique, for the development of thematic SDI. In this work, an evaluation of existing and accessible information that constitutes the basis for building a thematic SDI of soils in Spain is undertaken. This information framework has common features to other European Union states. From a set of more than 1,500 publications corresponding to the national territory of Spain, the study was carried out in those documents (94) found for five autonomous regions of northern Iberian Peninsula (Asturias, Cantabria, Basque Country, Navarra and La Rioja). The analysis was performed taking into account the criteria of soil mapping and inventories. The results obtained show a wide variation in almost all the criteria: geographic representation (projections, scales) and geo-referencing the location of the profiles, map location of profiles integrated with edaphic units, description and taxonomic classification systems of soils (FAO, Soil taxonomy, etc.), amount and type of soil analysis parameters and dates of the inventories. In conclusion, the construction of thematic SDI on soil should take into account, prior to the integration of all maps and inventories, a series of processes of harmonization that allows spatial continuity between existing information and also temporal identification of the inventories and maps. This should require the development of at least two types of integration tools: (1) enabling spatial continuity without contradictions between maps made at different times and with different criteria and (2) the development of information systems data (metadata) to highlight the characteristics of information and connection possibilities with other sources that comprise the Spatial Data Infrastructure. Acknowledgements This research has financed by the European Union within the framework of the GS Soil project (eContentplus Programme ECP-2008-GEO-318004).

A study of the utilization of ERTS-1 data from the Wabash River Basin. [crop identification, water resources, urban land use, soil mapping, and atmospheric modeling

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1974-01-01

The author has identified the following significant results. The most significant results were obtained in the water resources research, urban land use mapping, and soil association mapping projects. ERTS-1 data was used to classify water bodies to determine acreages and high agreement was obtained with USGS figures. Quantitative evaluation was achieved of urban land use classifications from ERTS-1 data and an overall test accuracy of 90.3% was observed. ERTS-1 data classifications of soil test sites were compared with soil association maps scaled to match the computer produced map and good agreement was observed. In some cases the ERTS-1 results proved to be more accurate than the soil association map.

Assessment of the postagrogenic transformation of soddy-podzolic soils: Cartographic and analytic support

NASA Astrophysics Data System (ADS)

Sorokina, N. P.; Kozlov, D. N.; Kuznetsova, I. V.

2013-10-01

The results of experimental studies of the postagrogenic transformation of loamy soddy-podzolic soils on the southern slope of the Klin-Dmitrov Moraine Ridge are discussed. A chronosequence of soils (arable soils (cropland)-soils under fallow with meadow vegetation-soils under secondary forests of different ages-soils under a conventionally initial native forest) was examined, and the stages of the postagrogenic transformation of the automorphic soddy-podzolic soils were identified. The differentiation of the former plow horizon into the A1 and A1A2 horizons (according to the differences in the humus content, texture, and acidity) served as the major criterion of the soil transformation. A stage of textural differentiation with clay depletion from the uppermost layer was identified in the soils of the 20- to 60-year-old fallows. The specificity of the postagrogenic transformation of the soils on the slopes was demonstrated. From the methodological point of view, it was important to differentiate between the chronosequences of automorphic and semihydromorphic soils of the leveled interfluves and the soils of the slopes. For this purpose, a series of maps reflecting the history of the land use and the soil cover pattern was analyzed. The cartographic model included the attribute data of the soil surveys, the cartographic sources (a series of historical maps of the land use, topographic maps, remote sensing data, and a digital elevation model), and two base maps: (a) the integral map of the land use and (b) the map of the soil combinations with the separation of the zonal automorphic, semihydromorphic, and erosional soil combinations. This scheme served as a matrix for the organization and analysis of the already available and new materials.

Mapping the spatial patterns of field traffic and traffic intensity to predict soil compaction risks at the field scale

NASA Astrophysics Data System (ADS)

Duttmann, Rainer; Kuhwald, Michael; Nolde, Michael

2015-04-01

Soil compaction is one of the main threats to cropland soils in present days. In contrast to easily visible phenomena of soil degradation, soil compaction, however, is obscured by other signals such as reduced crop yield, delayed crop growth, and the ponding of water, which makes it difficult to recognize and locate areas impacted by soil compaction directly. Although it is known that trafficking intensity is a key factor for soil compaction, until today only modest work has been concerned with the mapping of the spatially distributed patterns of field traffic and with the visual representation of the loads and pressures applied by farm traffic within single fields. A promising method for for spatial detection and mapping of soil compaction risks of individual fields is to process dGPS data, collected from vehicle-mounted GPS receivers and to compare the soil stress induced by farm machinery to the load bearing capacity derived from given soil map data. The application of position-based machinery data enables the mapping of vehicle movements over time as well as the assessment of trafficking intensity. It also facilitates the calculation of the trafficked area and the modeling of the loads and pressures applied to soil by individual vehicles. This paper focuses on the modeling and mapping of the spatial patterns of traffic intensity in silage maize fields during harvest, considering the spatio-temporal changes in wheel load and ground contact pressure along the loading sections. In addition to scenarios calculated for varying mechanical soil strengths, an example for visualizing the three-dimensional stress propagation inside the soil will be given, using the Visualization Toolkit (VTK) to construct 2D or 3D maps supporting to decision making due to sustainable field traffic management.

Predicting and mapping soil available water capacity in Korea.

PubMed

Hong, Suk Young; Minasny, Budiman; Han, Kyung Hwa; Kim, Yihyun; Lee, Kyungdo

2013-01-01

The knowledge on the spatial distribution of soil available water capacity at a regional or national extent is essential, as soil water capacity is a component of the water and energy balances in the terrestrial ecosystem. It controls the evapotranspiration rate, and has a major impact on climate. This paper demonstrates a protocol for mapping soil available water capacity in South Korea at a fine scale using data available from surveys. The procedures combined digital soil mapping technology with the available soil map of 1:25,000. We used the modal profile data from the Taxonomical Classification of Korean Soils. The data consist of profile description along with physical and chemical analysis for the modal profiles of the 380 soil series. However not all soil samples have measured bulk density and water content at -10 and -1500 kPa. Thus they need to be predicted using pedotransfer functions. Furthermore, water content at -10 kPa was measured using ground samples. Thus a correction factor is derived to take into account the effect of bulk density. Results showed that Andisols has the highest mean water storage capacity, followed by Entisols and Inceptisols which have loamy texture. The lowest water retention is Entisols which are dominated by sandy materials. Profile available water capacity to a depth of 1 m was calculated and mapped for Korea. The western part of the country shows higher available water capacity than the eastern part which is mountainous and has shallower soils. The highest water storage capacity soils are the Ultisols and Alfisols (mean of 206 and 205 mm, respectively). Validation of the maps showed promising results. The map produced can be used as an indication of soil physical quality of Korean soils.

Cokriging of Electromagnetic Induction Soil Electrical Conductivity Measurements and Soil Textural Properties to Demarcate Sub-field Management Zones for Precision Irrigation.

NASA Astrophysics Data System (ADS)

Ding, R.; Cruz, L.; Whitney, J.; Telenko, D.; Oware, E. K.

2017-12-01

There is the growing need for the development of efficient irrigation management practices due to increasing irrigation water scarcity as a result of growing population and changing climate. Soil texture primarily controls the water-holding capacity of soils, which determines the amount of irrigation water that will be available to the plant. However, while there are significant variabilities in the textural properties of the soil across a field, conventional irrigation practices ignore the underlying variability in the soil properties, resulting in over- or under-irrigation. Over-irrigation leaches plant nutrients beyond the root-zone leading to fertilizer, energy, and water wastages with dire environmental consequences. Under-irrigation, in contrast, causes water stress of the plant, thereby reducing plant quality and yield. The goal of this project is to leverage soil textural map of a field to create water management zones (MZs) to guide site-specific precision irrigation. There is increasing application of electromagnetic induction methods to rapidly and inexpensively map spatially continuous soil properties in terms of the apparent electrical conductivity (ECa) of the soil. ECa is a measure of the bulk soil properties, including soil texture, moisture, salinity, and cation exchange capacity, making an ECa map a pseudo-soil map. Data for the project were collected from a farm site at Eden, NY. The objective is to leverage high-resolution ECa map to predict spatially dense soil textural properties from limited measurements of soil texture. Thus, after performing ECa mapping, we conducted particle-size analysis of soil samples to determine the textural properties of soils at selected locations across the field. We cokriged the high-resolution ECa measurements with the sparse soil textural data to estimate a soil texture map for the field. We conducted irrigation experiments at selected locations to calibrate representative water-holding capacities of each estimated soil textural unit. Estimated soil units with similar water-holding characteristics were merged to create sub-field water MZs to guide precision irrigation of each MZ, instructed by each MZ's calibrated water-holding properties.

Soil mapping and process modeling for sustainable land use management: a brief historical review

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Pereira, Paulo; Muñoz-Rojas, Miriam; Miller, Bradley A.; Cerdà, Artemi; Parras-Alcántara, Luis; Lozano-García, Beatriz

2017-04-01

Basic soil management goes back to the earliest days of agricultural practices, approximately 9,000 BCE. Through time humans developed soil management techniques of ever increasing complexity, including plows, contour tillage, terracing, and irrigation. Spatial soil patterns were being recognized as early as 3,000 BCE, but the first soil maps didn't appear until the 1700s and the first soil models finally arrived in the 1880s (Brevik et al., in press). The beginning of the 20th century saw an increase in standardization in many soil science methods and wide-spread soil mapping in many parts of the world, particularly in developed countries. However, the classification systems used, mapping scale, and national coverage varied considerably from country to country. Major advances were made in pedologic modeling starting in the 1940s, and in erosion modeling starting in the 1950s. In the 1970s and 1980s advances in computing power, remote and proximal sensing, geographic information systems (GIS), global positioning systems (GPS), and statistics and spatial statistics among other numerical techniques significantly enhanced our ability to map and model soils (Brevik et al., 2016). These types of advances positioned soil science to make meaningful contributions to sustainable land use management as we moved into the 21st century. References Brevik, E., Pereira, P., Muñoz-Rojas, M., Miller, B., Cerda, A., Parras-Alcantara, L., Lozano-Garcia, B. Historical perspectives on soil mapping and process modelling for sustainable land use management. In: Pereira, P., Brevik, E., Muñoz-Rojas, M., Miller, B. (eds) Soil mapping and process modelling for sustainable land use management (In press). Brevik, E., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A. 2016. Historical perspectives and future needs in soil mapping, classification and pedological modelling, Geoderma, 264, Part B, 256-274.

Incorporation of satellite remote sensing pan-sharpened imagery into digital soil prediction and mapping models to characterize soil property variability in small agricultural fields

NASA Astrophysics Data System (ADS)

Xu, Yiming; Smith, Scot E.; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P.

2017-01-01

Soil prediction models based on spectral indices from some multispectral images are too coarse to characterize spatial pattern of soil properties in small and heterogeneous agricultural lands. Image pan-sharpening has seldom been utilized in Digital Soil Mapping research before. This research aimed to analyze the effects of pan-sharpened (PAN) remote sensing spectral indices on soil prediction models in smallholder farm settings. This research fused the panchromatic band and multispectral (MS) bands of WorldView-2, GeoEye-1, and Landsat 8 images in a village in Southern India by Brovey, Gram-Schmidt and Intensity-Hue-Saturation methods. Random Forest was utilized to develop soil total nitrogen (TN) and soil exchangeable potassium (Kex) prediction models by incorporating multiple spectral indices from the PAN and MS images. Overall, our results showed that PAN remote sensing spectral indices have similar spectral characteristics with soil TN and Kex as MS remote sensing spectral indices. There is no soil prediction model incorporating the specific type of pan-sharpened spectral indices always had the strongest prediction capability of soil TN and Kex. The incorporation of pan-sharpened remote sensing spectral data not only increased the spatial resolution of the soil prediction maps, but also enhanced the prediction accuracy of soil prediction models. Small farms with limited footprint, fragmented ownership and diverse crop cycle should benefit greatly from the pan-sharpened high spatial resolution imagery for soil property mapping. Our results show that multiple high and medium resolution images can be used to map soil properties suggesting the possibility of an improvement in the maps' update frequency. Additionally, the results should benefit the large agricultural community through the reduction of routine soil sampling cost and improved prediction accuracy.

LANDSAT-1 data, its use in a soil survey program

NASA Technical Reports Server (NTRS)

Westin, F. C.; Frazee, C. J.

1975-01-01

The following applications of LANDSAT imagery were investigated: assistance in recognizing soil survey boundaries, low intensity soil surveys, and preparation of a base map for publishing thematic soils maps. The following characteristics of LANDSAT imagery were tested as they apply to the recognition of soil boundaries in South Dakota and western Minnesota: synoptic views due to the large areas covered, near-orthography and lack of distortion, flexibility of selecting the proper season, data recording in four parts of the spectrum, and the use of computer compatible tapes. A low intensity soil survey of Pennington County, South Dakota was completed in 1974. Low intensity inexpensive soil surveys can provide the data needed to evaluate agricultural land for the remaining counties until detailed soil surveys are completed. In using LANDSAT imagery as a base map for publishing thematic soil maps, the first step was to prepare a mosaic with 20 LANDSAT scenes from several late spring passes in 1973.

ERTS-1 MSS imagery: Its use in delineating soil associations and as a base map for publishing soils information. [South Dakota

NASA Technical Reports Server (NTRS)

Westin, F. C.

1974-01-01

ERTS 1 imagery is a useful tool in the identification and refinement of soil association areas and an excellent base map upon which soil association information can be published. Prints of bands 5 and 7 were found to be most useful to help delineate major soil and vegetation areas. After delineating major soil areas, over 4800 land sale prices covering a period of 1967-72 were located in the soil areas and averaged. The soil association then were described as soil association value areas and published on a 1:1,000,000 scale ERTS mosaic of South Dakota constructed using negative prints of band 7. The map is intended for use by state and county revenue officers, by individual buyers and sellers of land and lending institutions, and as a reference map by those planning road routes and cable lines and pipelines.

Geostatistical approach for management of soil nutrients with special emphasis on different forms of potassium considering their spatial variation in intensive cropping system of West Bengal, India.

PubMed

Chatterjee, Sourov; Santra, Priyabrata; Majumdar, Kaushik; Ghosh, Debjani; Das, Indranil; Sanyal, S K

2015-04-01

A large part of precision agriculture research in the developing countries is devoted towards precision nutrient management aspects. This has led to better economics and efficiency of nutrient use with off-farm advantages of environmental security. The keystone of precision nutrient management is analysis and interpretation of spatial variability of soils by establishing management zones. In this study, spatial variability of major soil nutrient contents was evaluated in the Ghoragacha village of North 24 Parganas district of West Bengal, India. Surface soil samples from 100 locations, covering different cropping systems of the village, was collected from 0 to 15 cm depth using 100×100 m grid system and analyzed in the laboratory to determine organic carbon (OC), available nitrogen (N), phosphorus (P), and potassium (K) contents of the soil as well as its water-soluble K (KWS), exchangeable K (KEX), and non-exchangeable forms of K (KNEX). Geostatistical analyses were performed to determine the spatial variation structure of each nutrient content within the village, followed by the generation of surface maps through kriging. Four commonly used semivariogram models, i.e., spherical, exponential, Gaussian, and linear models were fitted to each soil property, and the best one was used to prepare surface maps through krigging. Spherical model was found the best for available N and P contents, while linear and exponential model was the best for OC and available K, and for KWS and KNEK, Gausian model was the best. Surface maps of nutrient contents showed that N content (129-195 kg ha(-1)) was the most limiting factor throughout the village, while P status was generally very high ( 10-678 kg ha(-1)) in the soils of the present village. Among the different soil K fractions, KWS registered the maximum variability (CV 75%), while the remaining soil K fractions showed moderate to high variation. Interestingly, KNEX content also showed high variability, which essentially indicates reserve native K exploitation under intensive cultivation. These maps highlight the necessity of estimating the other soil K fractions as well for better understanding of soil K supplying capacity and K fertilization strategy rather than the current recommendations, based on the plant-available K alone. In conclusion, the present study revealed that the variability of nutrient distribution was a consequence of complex interactions between the cropping system, nutrient application rates, and the native soil characteristics, and such interactions could be utilized to develop the nutrient management strategies for intensive small-holder system.

Use of slope, aspect, and elevation maps derived from digital elevation model data in making soil surveys

USGS Publications Warehouse

Klingebiel, A.A.; Horvath, E.H.; Moore, D.G.; Reybold, W.U.

1987-01-01

Maps showing different classes of slope, aspect, and elevation were developed from U.S. Geological Survey digital elevation model data. The classes were displayed on clear Mylar at 1:24 000-scale and registered with topographic maps and orthophotos. The maps were used with aerial photographs, topographic maps, and other resource data to determine their value in making order-three soil surveys. They were tested on over 600 000 ha in Wyoming, Idaho, and Nevada under various climatic and topographic conditions. Field evaluations showed that the maps developed from digital elevation model data were accurate, except for slope class maps where slopes were <4%. The maps were useful to soil scientists, especially where (i) class boundaries coincided with soil changes, landform delineations, land use and management separations, and vegetation changes, and (ii) rough terrain and dense vegetation made it difficult to traverse the area. In hot, arid areas of sparse vegetation, the relationship of slope classes to kinds of soil and vegetation was less significant.

Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete.

PubMed

Karydas, Christos G; Sekuloska, Tijana; Silleos, Georgios N

2009-02-01

Due to inappropriate agricultural management practices, soil erosion is becoming one of the most dangerous forms of soil degradation in many olive farming areas in the Mediterranean region, leading to significant decrease of soil fertility and yield. In order to prevent further soil degradation, proper measures are necessary to be locally implemented. In this perspective, an increase in the spatial accuracy of remote sensing datasets and advanced image analysis are significant tools necessary and efficient for mapping soil erosion risk on a fine scale. In this study, the Revised Universal Soil Loss Equation (RUSLE) was implemented in the spatial domain using GIS, while a very high resolution satellite image, namely a QuickBird image, was used for deriving cover management (C) and support practice (P) factors, in order to map the risk of soil erosion in Kolymvari, a typical olive farming area in the island of Crete, Greece. The results comprised a risk map of soil erosion when P factor was taken uniform (conventional approach) and a risk map when P factor was quantified site-specifically using object-oriented image analysis. The results showed that the QuickBird image was necessary in order to achieve site-specificity of the P factor and therefore to support fine scale mapping of soil erosion risk in an olive cultivation area, such as the one of Kolymvari in Crete. Increasing the accuracy of the QB image classification will further improve the resulted soil erosion mapping.

Soil mapping and processes modelling for sustainable land management: a review

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Brevik, Eric; Muñoz-Rojas, Miriam; Miller, Bradley; Smetanova, Anna; Depellegrin, Daniel; Misiune, Ieva; Novara, Agata; Cerda, Artemi

2017-04-01

Soil maps and models are fundamental for a correct and sustainable land management (Pereira et al., 2017). They are an important in the assessment of the territory and implementation of sustainable measures in urban areas, agriculture, forests, ecosystem services, among others. Soil maps represent an important basis for the evaluation and restoration of degraded areas, an important issue for our society, as consequence of climate change and the increasing pressure of humans on the ecosystems (Brevik et al. 2016; Depellegrin et al., 2016). The understanding of soil spatial variability and the phenomena that influence this dynamic is crucial to the implementation of sustainable practices that prevent degradation, and decrease the economic costs of soil restoration. In this context, soil maps and models are important to identify areas affected by degradation and optimize the resources available to restore them. Overall, soil data alone or integrated with data from other sciences, is an important part of sustainable land management. This information is extremely important land managers and decision maker's implements sustainable land management policies. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. References Brevik, E., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A. (2016) Historical perspectives and future needs in soil mapping, classification and pedological modelling, Geoderma, 264, Part B, 256-274. Depellegrin, D.A., Pereira, P., Misiune, I., Egarter-Vigl, L. (2016) Mapping Ecosystem Services in Lithuania. International Journal of Sustainable Development and World Ecology, 23, 441-455. Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B., Smetanova, A., Depellegrin, D., Misiune, I., Novara, A., Cerda, A. (2017) Soil mapping and process modelling for sustainable land management. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006

Selected Aspects of Soil Science History in the USA - 1980s to the 2010s

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Homburg, Jeffrey A.; Miller, Bradley A.; Fenton, Thomas E.; Doolittle, James A.; Indorante, Samuel J.

2017-04-01

The beginning of the 20th century through the 1970s were good times for soil science in the USA, with relatively strong funding and overall growth in the profession. However, the soil science discipline in the USA hit hard times in the 1980s and 1990s. Federal funding for soil survey work began to decline as did student numbers in university programs and membership in the Soil Science Society of America (SSSA). Despite this, there were still many positive advances within soil science in the USA during these two decades. There was an increased use of geophysical instrumentation, remote sensing, geographic information systems (GIS), and global positioning systems (GPS), and research began in digital soil mapping, all of which lead to better understanding of the spatial distribution and variability of soils. Many NRCS soil products were put online, making them widely available to the general public, and the use of soil knowledge was expanded into new areas such as archaeology and environmental work, and historic connections to geology were re-established. While expansion into new areas required soil science to evolve as a field, separating the discipline to an extent from its agricultural roots, it also helped reinvigorate the discipline. As we move through the early parts of the 21st century, student numbers are increasing in university soil science programs and membership in SSSA is at an all-time high. Digital soil mapping is being incorporated into the National Cooperative Soil Survey, and the impact of humans on the soil system is being fully recognized. The importance of soils is being recognized by events such as the United Nations declaration of 2015 as the "International Year of Soils". The expansion of soils into new areas and widening recognition of the importance of soils gives the field hope for a bright future in the USA.

Quantifying soil burn severity for hydrologic modeling to assess post-fire effects on sediment delivery

NASA Astrophysics Data System (ADS)

Dobre, Mariana; Brooks, Erin; Lew, Roger; Kolden, Crystal; Quinn, Dylan; Elliot, William; Robichaud, Pete

2017-04-01

Soil erosion is a secondary fire effect with great implications for many ecosystem resources. Depending on the burn severity, topography, and the weather immediately after the fire, soil erosion can impact municipal water supplies, degrade water quality, and reduce reservoirs' storage capacity. Scientists and managers use field and remotely sensed data to quickly assess post-fire burn severity in ecologically-sensitive areas. From these assessments, mitigation activities are implemented to minimize post-fire flood and soil erosion and to facilitate post-fire vegetation recovery. Alternatively, land managers can use fire behavior and spread models (e.g. FlamMap, FARSITE, FOFEM, or CONSUME) to identify sensitive areas a priori, and apply strategies such as fuel reduction treatments to proactively minimize the risk of wildfire spread and increased burn severity. There is a growing interest in linking fire behavior and spread models with hydrology-based soil erosion models to provide site-specific assessment of mitigation treatments on post-fire runoff and erosion. The challenge remains, however, that many burn severity mapping and modeling products quantify vegetation loss rather than measuring soil burn severity. Wildfire burn severity is spatially heterogeneous and depends on the pre-fire vegetation cover, fuel load, topography, and weather. Severities also differ depending on the variable of interest (e.g. soil, vegetation). In the United States, Burned Area Reflectance Classification (BARC) maps, derived from Landsat satellite images, are used as an initial burn severity assessment. BARC maps are classified from either a Normalized Burn Ratio (NBR) or differenced Normalized Burned Ratio (dNBR) scene into four classes (Unburned, Low, Moderate, and High severity). The development of soil burn severity maps requires further manual field validation efforts to transform the BARC maps into a product more applicable for post-fire soil rehabilitation activities. Alternative spectral indices and modeled output approaches may prove better predictors of soil burn severity and hydrologic effects, but these have not yet been assessed in a model framework. In this project we compare field-verified soil burn severity maps to satellite-derived and modeled burn severity maps. We quantify the extent to which there are systematic differences in these mapping products. We then use the Water Erosion Prediction Project (WEPP) hydrologic soil erosion model to assess sediment delivery from these fires using the predicted and observed soil burn severity maps. Finally, we discuss differences in observed and predicted soil burn severity maps and application to watersheds in the Pacific Northwest to estimate post-fire sediment delivery.

Global soil-climate-biome diagram: linking soil properties to climate and biota

NASA Astrophysics Data System (ADS)

Zhao, X.; Yang, Y.; Fang, J.

2017-12-01

As a critical component of the Earth system, soils interact strongly with both climate and biota and provide fundamental ecosystem services that maintain food, climate, and human security. Despite significant progress in digital soil mapping techniques and the rapidly growing quantity of observed soil information, quantitative linkages between soil properties, climate and biota at the global scale remain unclear. By compiling a large global soil database, we mapped seven major soil properties (bulk density [BD]; sand, silt and clay fractions; soil pH; soil organic carbon [SOC] density [SOCD]; and soil total nitrogen [STN] density [STND]) based on machine learning algorithms (regional random forest [RF] model) and quantitatively assessed the linkage between soil properties, climate and biota at the global scale. Our results demonstrated a global soil-climate-biome diagram, which improves our understanding of the strong correspondence between soils, climate and biomes. Soil pH decreased with greater mean annual precipitation (MAP) and lower mean annual temperature (MAT), and the critical MAP for the transition from alkaline to acidic soil pH decreased with decreasing MAT. Specifically, the critical MAP ranged from 400-500 mm when the MAT exceeded 10 °C but could decrease to 50-100 mm when the MAT was approximately 0 °C. SOCD and STND were tightly linked; both increased in accordance with lower MAT and higher MAP across terrestrial biomes. Global stocks of SOC and STN were estimated to be 788 ± 39.4 Pg (1015 g, or billion tons) and 63 ± 3.3 Pg in the upper 30-cm soil layer, respectively, but these values increased to 1654 ± 94.5 Pg and 133 ± 7.8 Pg in the upper 100-cm soil layer, respectively. These results reveal quantitative linkages between soil properties, climate and biota at the global scale, suggesting co-evolution of the soil, climate and biota under conditions of global environmental change.

Synchrotron-based Infrared-microspectroscopy reveals the impact of land management on carbon storage in soil micro-aggregates

NASA Astrophysics Data System (ADS)

Hernandez-Soriano, Maria C.; Dalal, Ram C.; Menzies, Neal W.; Kopittke, Peter M.

2015-04-01

Carbon stabilization in soil microaggregates results from chemical and biological processes that are highly sensitive to changes in land use. Indeed, such processes govern soil capability to store carbon, this being essential for soil health and productivity and to regulate emissions of soil organic carbon (SOC) as CO2. The identification of carbon functionalities using traditional mid-infrared analysis can be linked to carbon metabolism in soil but differences associated to land use are generally limited. The spatial resolution of synchrotron-based Infrared-microspectroscopy allows mapping microaggregate-associated forms of SOC because it has 1000 times higher brightness than a conventional thermal globar source. These maps can contribute to better understand molecular organization of SOC, physical protection in the soil particles and co-localization of carbon sources with microbial processes. Spatially-resolved analyses of carbon distribution in micro-aggregates (<200 μm diameter) have been conducted using FTIR microspectroscopy (Infrared Microspectroscopy beamline, Australian Synchrotron). Two soil types (Ferralsol and Vertisol, World Reference Base 2014) were collected from undisturbed areas and from a location(s) immediately adjacent which has a long history of agricultural use (>20 years). Soils were gently screened (250 μm) to obtain intact microaggregates which were humidified and frozen at -20°C, and sectioned (200 μm thickness) using a diamond knife and a cryo-ultramicrotome. The sections were placed between CaF2 windows and the spectra were acquired in transmission mode. The maps obtained (5 µm step-size over ca. 150 × 150 µm) revealed carbon distribution in microaggregates from soils under contrasting land management, namely undisturbed and cropping land. Accumulation of aromatic and carboxylic functions on specific spots and marginal co-localization with clays was observed, which suggests processes other than organo-mineral associations being responsible for carbon stabilization. A substantial decrease in carboxylic compounds was observed for agricultural soils. Clays were mostly co-localized with alkenes and polysaccharides, particularly in agricultural soils, likely due to enhanced microbial activity in those spots. Results will be linked to currently ongoing analysis of soil enzymes activities and characterization of dissolved organic carbon components. This novel methodological approach combines biological and chemical information on organic carbon dynamics in soil at a molecular level and will constitute a substantial advance towards understanding carbon storage in soil and the long term impact of land management.

Description and spatial inference of soil drainage using matrix soil colours in the Lower Hunter Valley, New South Wales, Australia

PubMed Central

McBratney, Alex B.; Minasny, Budiman

2018-01-01

Soil colour is often used as a general purpose indicator of internal soil drainage. In this study we developed a necessarily simple model of soil drainage which combines the tacit knowledge of the soil surveyor with observed matrix soil colour descriptions. From built up knowledge of the soils in our Lower Hunter Valley, New South Wales study area, the sequence of well-draining → imperfectly draining → poorly draining soils generally follows the colour sequence of red → brown → yellow → grey → black soil matrix colours. For each soil profile, soil drainage is estimated somewhere on a continuous index of between 5 (very well drained) and 1 (very poorly drained) based on the proximity or similarity to reference soil colours of the soil drainage colour sequence. The estimation of drainage index at each profile incorporates the whole-profile descriptions of soil colour where necessary, and is weighted such that observation of soil colour at depth and/or dominantly observed horizons are given more preference than observations near the soil surface. The soil drainage index, by definition disregards surficial soil horizons and consolidated and semi-consolidated parent materials. With the view to understanding the spatial distribution of soil drainage we digitally mapped the index across our study area. Spatial inference of the drainage index was made using Cubist regression tree model combined with residual kriging. Environmental covariates for deterministic inference were principally terrain variables derived from a digital elevation model. Pearson’s correlation coefficients indicated the variables most strongly correlated with soil drainage were topographic wetness index (−0.34), mid-slope position (−0.29), multi-resolution valley bottom flatness index (−0.29) and vertical distance to channel network (VDCN) (0.26). From the regression tree modelling, two linear models of soil drainage were derived. The partitioning of models was based upon threshold criteria of VDCN. Validation of the regression kriging model using a withheld dataset resulted in a root mean square error of 0.90 soil drainage index units. Concordance between observations and predictions was 0.49. Given the scale of mapping, and inherent subjectivity of soil colour description, these results are acceptable. Furthermore, the spatial distribution of soil drainage predicted in our study area is attuned with our mental model developed over successive field surveys. Our approach, while exclusively calibrated for the conditions observed in our study area, can be generalised once the unique soil colour and soil drainage relationship is expertly defined for an area or region in question. With such rules established, the quantitative components of the method would remain unchanged. PMID:29682425

Description and spatial inference of soil drainage using matrix soil colours in the Lower Hunter Valley, New South Wales, Australia.

PubMed

Malone, Brendan P; McBratney, Alex B; Minasny, Budiman

2018-01-01

Soil colour is often used as a general purpose indicator of internal soil drainage. In this study we developed a necessarily simple model of soil drainage which combines the tacit knowledge of the soil surveyor with observed matrix soil colour descriptions. From built up knowledge of the soils in our Lower Hunter Valley, New South Wales study area, the sequence of well-draining → imperfectly draining → poorly draining soils generally follows the colour sequence of red → brown → yellow → grey → black soil matrix colours. For each soil profile, soil drainage is estimated somewhere on a continuous index of between 5 (very well drained) and 1 (very poorly drained) based on the proximity or similarity to reference soil colours of the soil drainage colour sequence. The estimation of drainage index at each profile incorporates the whole-profile descriptions of soil colour where necessary, and is weighted such that observation of soil colour at depth and/or dominantly observed horizons are given more preference than observations near the soil surface. The soil drainage index, by definition disregards surficial soil horizons and consolidated and semi-consolidated parent materials. With the view to understanding the spatial distribution of soil drainage we digitally mapped the index across our study area. Spatial inference of the drainage index was made using Cubist regression tree model combined with residual kriging. Environmental covariates for deterministic inference were principally terrain variables derived from a digital elevation model. Pearson's correlation coefficients indicated the variables most strongly correlated with soil drainage were topographic wetness index (-0.34), mid-slope position (-0.29), multi-resolution valley bottom flatness index (-0.29) and vertical distance to channel network (VDCN) (0.26). From the regression tree modelling, two linear models of soil drainage were derived. The partitioning of models was based upon threshold criteria of VDCN. Validation of the regression kriging model using a withheld dataset resulted in a root mean square error of 0.90 soil drainage index units. Concordance between observations and predictions was 0.49. Given the scale of mapping, and inherent subjectivity of soil colour description, these results are acceptable. Furthermore, the spatial distribution of soil drainage predicted in our study area is attuned with our mental model developed over successive field surveys. Our approach, while exclusively calibrated for the conditions observed in our study area, can be generalised once the unique soil colour and soil drainage relationship is expertly defined for an area or region in question. With such rules established, the quantitative components of the method would remain unchanged.

Evaluation of automated global mapping of Reference Soil Groups of WRB2015

NASA Astrophysics Data System (ADS)

Mantel, Stephan; Caspari, Thomas; Kempen, Bas; Schad, Peter; Eberhardt, Einar; Ruiperez Gonzalez, Maria

2017-04-01

SoilGrids is an automated system that provides global predictions for standard numeric soil properties at seven standard depths down to 200 cm, currently at spatial resolutions of 1km and 250m. In addition, the system provides predictions of depth to bedrock and distribution of soil classes based on WRB and USDA Soil Taxonomy (ST). In SoilGrids250m(1), soil classes (WRB, version 2006) consist of the RSG and the first prefix qualifier, whereas in SoilGrids1km(2), the soil class was assessed at RSG level. Automated mapping of World Reference Base (WRB) Reference Soil Groups (RSGs) at a global level has great advantages. Maps can be updated in a short time span with relatively little effort when new data become available. To translate soil names of older versions of FAO/WRB and national classification systems of the source data into names according to WRB 2006, correlation tables are used in SoilGrids. Soil properties and classes are predicted independently from each other. This means that the combinations of soil properties for the same cells or soil property-soil class combinations do not necessarily yield logical combinations when the map layers are studied jointly. The model prediction procedure is robust and probably has a low source of error in the prediction of RSGs. It seems that the quality of the original soil classification in the data and the use of correlation tables are the largest sources of error in mapping the RSG distribution patterns. Predicted patterns of dominant RSGs were evaluated in selected areas and sources of error were identified. Suggestions are made for improvement of WRB2015 RSG distribution predictions in SoilGrids. Keywords: Automated global mapping; World Reference Base for Soil Resources; Data evaluation; Data quality assurance References 1 Hengl T, de Jesus JM, Heuvelink GBM, Ruiperez Gonzalez M, Kilibarda M, et al. (2016) SoilGrids250m: global gridded soil information based on Machine Learning. Earth System Science Data (ESSD), in review. 2 Hengl T, de Jesus JM, MacMillan RA, Batjes NH, Heuvelink GBM, et al. (2014) SoilGrids1km — Global Soil Information Based on Automated Mapping. PLoS ONE 9(8): e105992. doi:10.1371/journal.pone.0105992

Generalized vegetation map of north Merrit Island based on a simplified multispectral analysis

NASA Technical Reports Server (NTRS)

Poonai, P.; Floyd, W. J.; Rahmani, M. A.

1977-01-01

A simplified system for classification of multispectral data was used for making a generalized map of ground features of North Merritt Island. Subclassification of vegetation within broad categories yielded promising results which led to a completely automatic method and to the production of satisfactory detailed maps. Changes in an area north of Happy Hammocks are evidently related to water relations of the soil and are not associated with the last winter freeze-damage which affected mainly the mangrove species, likely to reestablish themselves by natural processes. A supplementary investigation involving reflectance studies in the laboratory has shown that the reflectance by detached citrus leaves, of wavelengths lying between 400 microns and 700 microns, showed some variation over a period of seven days during which the leaves were kept in a laboratory atmosphere.

Pervasive Local-Scale Tree-Soil Habitat Association in a Tropical Forest Community.

PubMed

Allié, Elodie; Pélissier, Raphaël; Engel, Julien; Petronelli, Pascal; Freycon, Vincent; Deblauwe, Vincent; Soucémarianadin, Laure; Weigel, Jean; Baraloto, Christopher

2015-01-01

We examined tree-soil habitat associations in lowland forest communities at Paracou, French Guiana. We analyzed a large dataset assembling six permanent plots totaling 37.5 ha, in which extensive LIDAR-derived topographical data and soil chemical and physical data have been integrated with precise botanical determinations. Map of relative elevation from the nearest stream summarized both soil fertility and hydromorphic characteristics, with seasonally inundated bottomlands having higher soil phosphate content and base saturation, and plateaus having higher soil carbon, nitrogen and aluminum contents. We employed a statistical test of correlations between tree species density and environmental maps, by generating Monte Carlo simulations of random raster images that preserve autocorrelation of the original maps. Nearly three fourths of the 94 taxa with at least one stem per ha showed a significant correlation between tree density and relative elevation, revealing contrasted species-habitat associations in term of abundance, with seasonally inundated bottomlands (24.5% of species) and well-drained plateaus (48.9% of species). We also observed species preferences for environments with or without steep slopes (13.8% and 10.6%, respectively). We observed that closely-related species were frequently associated with different soil habitats in this region (70% of the 14 genera with congeneric species that have a significant association test) suggesting species-habitat associations have arisen multiple times in this tree community. We also tested if species with similar habitat preferences shared functional strategies. We found that seasonally inundated forest specialists tended to have smaller stature (maximum diameter) than species found on plateaus. Our results underline the importance of tree-soil habitat associations in structuring diverse communities at fine spatial scales and suggest that additional studies are needed to disentangle community assembly mechanisms related to dispersal limitation, biotic interactions and environmental filtering from species-habitat associations. Moreover, they provide a framework to generalize across tropical forest sites.

Pervasive Local-Scale Tree-Soil Habitat Association in a Tropical Forest Community

PubMed Central

Allié, Elodie; Pélissier, Raphaël; Engel, Julien; Petronelli, Pascal; Freycon, Vincent; Deblauwe, Vincent; Soucémarianadin, Laure; Weigel, Jean; Baraloto, Christopher

2015-01-01

We examined tree-soil habitat associations in lowland forest communities at Paracou, French Guiana. We analyzed a large dataset assembling six permanent plots totaling 37.5 ha, in which extensive LIDAR-derived topographical data and soil chemical and physical data have been integrated with precise botanical determinations. Map of relative elevation from the nearest stream summarized both soil fertility and hydromorphic characteristics, with seasonally inundated bottomlands having higher soil phosphate content and base saturation, and plateaus having higher soil carbon, nitrogen and aluminum contents. We employed a statistical test of correlations between tree species density and environmental maps, by generating Monte Carlo simulations of random raster images that preserve autocorrelation of the original maps. Nearly three fourths of the 94 taxa with at least one stem per ha showed a significant correlation between tree density and relative elevation, revealing contrasted species-habitat associations in term of abundance, with seasonally inundated bottomlands (24.5% of species) and well-drained plateaus (48.9% of species). We also observed species preferences for environments with or without steep slopes (13.8% and 10.6%, respectively). We observed that closely-related species were frequently associated with different soil habitats in this region (70% of the 14 genera with congeneric species that have a significant association test) suggesting species-habitat associations have arisen multiple times in this tree community. We also tested if species with similar habitat preferences shared functional strategies. We found that seasonally inundated forest specialists tended to have smaller stature (maximum diameter) than species found on plateaus. Our results underline the importance of tree-soil habitat associations in structuring diverse communities at fine spatial scales and suggest that additional studies are needed to disentangle community assembly mechanisms related to dispersal limitation, biotic interactions and environmental filtering from species-habitat associations. Moreover, they provide a framework to generalize across tropical forest sites. PMID:26535570

Influence of soil environmental parameters on thoron exhalation rate.

PubMed

Hosoda, M; Tokonami, S; Sorimachi, A; Ishikawa, T; Sahoo, S K; Furukawa, M; Shiroma, Y; Yasuoka, Y; Janik, M; Kavasi, N; Uchida, S; Shimo, M

2010-10-01

Field measurements of thoron exhalation rates have been carried out using a ZnS(Ag) scintillation detector with an accumulation chamber. The influence of soil surface temperature and moisture saturation on the thoron exhalation rate was observed. When the variation of moisture saturation was small, the soil surface temperature appeared to induce a strong effect on the thoron exhalation rate. On the other hand, when the variation of moisture saturation was large, the influence of moisture saturation appeared to be larger than the soil surface temperature. The number of data ranged over 405, and the median was estimated to be 0.79 Bq m(-2) s(-1). Dependence of geology on the thoron exhalation rate from the soil surface was obviously found, and a nationwide distribution map of the thoron exhalation rate from the soil surface was drawn by using these data. It was generally high in the southwest region than in the northeast region.

Sulfates on Mars: TES Observations and Thermal Inertia Data

NASA Astrophysics Data System (ADS)

Cooper, C. D.; Mustard, J. F.

2001-05-01

The high resolution thermal emission spectra returned by the TES spectrometer on the MGS spacecraft have allowed the mapping of a variety of minerals and rock types by different sets of researchers. Recently, we have used a linear deconvolution approach to compare sulfate-palagonite soil mixtures created in the laboratory with Martian surface spectra. This approach showed that a number of areas on Mars have spectral properties that match those of sulfate-cemented soils (but neither loose powder mixtures of sulfates and soils nor sand-sized grains of disaggregated crusted soils). These features do not appear to be caused by atmospheric or instrumental effects and are thus believed to be related to surface composition and texture. The distribution and physical state of sulfate are important pieces of information for interpreting surface processes on Mars. A number of different mechanisms could have deposited sulfate in surface layers. Some of these include evaporation of standing bodies of water, aerosol deposition of volcanic gases, hydrothermal alteration from groundwater, and in situ interaction between the atmosphere and soil. The areas on Mars with cemented sulfate signatures are spread across a wide range of elevations and are generally large in spatial scale. Some of the areas are associated with volcanic regions, but many are in dark red plains that have previously been interpreted as duricrust deposits. Our current work compares the distribution of sulfate-cemented soils as mapped by the spectral deconvolution approach with thermal inertia maps produced from both Viking and MGS-TES. Duricrust regions, interpreted from intermediate thermal inertia values, are large regions thought to be sulfate-cemented soils similar to coherent, sulfate-rich materials seen at the Viking lander sites. Our observations of apparent regions of cemented sulfate are also large in spatial extent. This scale information is important for evaluating formation mechanisms for the sulfate material, although we currently lack the data to analyze sulfates on the outcrop scale. Analyzing our sulfate maps from spectral deconvolution together with thermal inertia data gives more information on the distribution of possible duricrusts, which provides insight into possible surface processes on Mars.

Maps of averaged spectral deviations from soil lines and their comparison with traditional soil maps

NASA Astrophysics Data System (ADS)

Rukhovich, D. I.; Rukhovich, A. D.; Rukhovich, D. D.; Simakova, M. S.; Kulyanitsa, A. L.; Bryzzhev, A. V.; Koroleva, P. V.

2016-07-01

The analysis of 34 cloudless fragments of Landsat 5, 7, and 8 images (1985-2014) on the territory of Plavsk, Arsen'evsk, and Chern districts of Tula oblast has been performed. It is shown that bare soil surface on the RED-NIR plots derived from the images cannot be described in the form of a sector of spectral plane as it can be done for the NDVI values. The notion of spectral neighborhood of soil line (SNSL) is suggested. It is defined as the sum of points of the RED-NIR spectral space, which are characterized by spectral characteristics of the bare soil applied for constructing soil lines. The way of the SNSL separation along the line of the lowest concentration density of points on the RED-NIR spectral space is suggested. This line separates bare soil surface from vegetating plants. The SNSL has been applied to construct soil line (SL) for each of the 34 images and to delineate bare soil surface on them. Distances from the points with averaged RED-NIR coordinates to the SL have been calculated using the method of moving window. These distances can be referred to as averaged spectral deviations (ASDs). The calculations have been performed strictly for the SNSL areas. As a result, 34 maps of ASDs have been created. These maps contain ASD values for 6036 points of a grid used in the study. Then, the integral map of normalized ASD values has been built with due account for the number of points participating in the calculation (i.e., lying in the SNSL) within the moving window. The integral map of ASD values has been compared with four traditional soil maps on the studied territory. It is shown that this integral map can be interpreted in terms of soil taxa: the areas of seven soil subtypes (soddy moderately podzolic, soddy slightly podzolic, light gray forest. gray forest, dark gray forest, podzolized chernozems, and leached chernozems) belonging to three soil types (soddy-podzolic, gray forest, and chernozemic soils) can be delineated on it.

Downscaling essential climate variable soil moisture using multisource data from 2003 to 2010 in China

NASA Astrophysics Data System (ADS)

Wang, Hui-Lin; An, Ru; You, Jia-jun; Wang, Ying; Chen, Yuehong; Shen, Xiao-ji; Gao, Wei; Wang, Yi-nan; Zhang, Yu; Wang, Zhe; Quaye-Ballard, Jonathan Arthur

2017-10-01

Soil moisture plays an important role in the water cycle within the surface ecosystem, and it is the basic condition for the growth of plants. Currently, the spatial resolutions of most soil moisture data from remote sensing range from ten to several tens of km, while those observed in-situ and simulated for watershed hydrology, ecology, agriculture, weather, and drought research are generally <1 km. Therefore, the existing coarse-resolution remotely sensed soil moisture data need to be downscaled. This paper proposes a universal and multitemporal soil moisture downscaling method suitable for large areas. The datasets comprise land surface, brightness temperature, precipitation, and soil and topographic parameters from high-resolution data and active/passive microwave remotely sensed essential climate variable soil moisture (ECV_SM) data with a spatial resolution of 25 km. Using this method, a total of 288 soil moisture maps of 1-km resolution from the first 10-day period of January 2003 to the last 10-day period of December 2010 were derived. The in-situ observations were used to validate the downscaled ECV_SM. In general, the downscaled soil moisture values for different land cover and land use types are consistent with the in-situ observations. Mean square root error is reduced from 0.070 to 0.061 using 1970 in-situ time series observation data from 28 sites distributed over different land uses and land cover types. The performance was also assessed using the GDOWN metric, a measure of the overall performance of the downscaling methods based on the same dataset. It was positive in 71.429% of cases, indicating that the suggested method in the paper generally improves the representation of soil moisture at 1-km resolution.

Digital soil mapping as a basis for climatically oriented agriculture a thematic on the territory of the national crop testing fields of the Republic of Tatarstan, Russia

NASA Astrophysics Data System (ADS)

Sahabiev, I. A.; Giniyatullin, K. G.; Ryazanov, S. S.

2018-01-01

The concept of climate-optimized agriculture (COA) of the UN FAO implies the transformation of agriculture techniques in conditions of changing climate. It is important to implement a timely transition to the concept of COA and sustainable development of soil resources, accurate digital maps of spatial distribution of soils and soil properties are needed. Digital mapping of soil humus content was carried out on the territory of the national crop testing fields (NCTF) of the Republic of Tatarstan (Russian Federation) and the accuracy of the maps obtained was estimated.

Ecological effects of the Hayman Fire - Part 3: Soil properties, erosion, and implications for rehabilitation and aquatic ecosystems

Treesearch

Jan E. Cipra; Eugene F. Kelly; Lee MacDonald; John Norman

2003-01-01

This team was asked to address three questions regarding soil properties, erosion and sedimentation, and how aquatic and terrestrial ecosystems have responded or could respond to various land management options. We have used soil survey maps, burn severity maps, and digital elevation model (DEM) maps as primary map data. We used our own field measurements and...

Mapping Soil Salinity/Sodicity by using Landsat OLI Imagery and PLSR Algorithm over Semiarid West Jilin Province, China

PubMed Central

Liu, Mingyue; Du, Baojia; Zhang, Bai

2018-01-01

Soil salinity and sodicity can significantly reduce the value and the productivity of affected lands, posing degradation, and threats to sustainable development of natural resources on earth. This research attempted to map soil salinity/sodicity via disentangling the relationships between Landsat 8 Operational Land Imager (OLI) imagery and in-situ measurements (EC, pH) over the west Jilin of China. We established the retrieval models for soil salinity and sodicity using Partial Least Square Regression (PLSR). Spatial distribution of the soils that were subjected to hybridized salinity and sodicity (HSS) was obtained by overlay analysis using maps of soil salinity and sodicity in geographical information system (GIS) environment. We analyzed the severity and occurring sizes of soil salinity, sodicity, and HSS with regard to specified soil types and land cover. Results indicated that the models’ accuracy was improved by combining the reflectance bands and spectral indices that were mathematically transformed. Therefore, our results stipulated that the OLI imagery and PLSR method applied to mapping soil salinity and sodicity in the region. The mapping results revealed that the areas of soil salinity, sodicity, and HSS were 1.61 × 106 hm2, 1.46 × 106 hm2, and 1.36 × 106 hm2, respectively. Also, the occurring area of moderate and intensive sodicity was larger than that of salinity. This research may underpin efficiently mapping regional salinity/sodicity occurrences, understanding the linkages between spectral reflectance and ground measurements of soil salinity and sodicity, and provide tools for soil salinity monitoring and the sustainable utilization of land resources. PMID:29614727

Three-dimensional mapping of soil chemical characteristics at micrometric scale: Statistical prediction by combining 2D SEM-EDX data and 3D X-ray computed micro-tomographic images

NASA Astrophysics Data System (ADS)

Hapca, Simona

2015-04-01

Many soil properties and functions emerge from interactions of physical, chemical and biological processes at microscopic scales, which can be understood only by integrating techniques that traditionally are developed within separate disciplines. While recent advances in imaging techniques, such as X-ray computed tomography (X-ray CT), offer the possibility to reconstruct the 3D physical structure at fine resolutions, for the distribution of chemicals in soil, existing methods, based on scanning electron microscope (SEM) and energy dispersive X-ray detection (EDX), allow for characterization of the chemical composition only on 2D surfaces. At present, direct 3D measurement techniques are still lacking, sequential sectioning of soils, followed by 2D mapping of chemical elements and interpolation to 3D, being an alternative which is explored in this study. Specifically, we develop an integrated experimental and theoretical framework which combines 3D X-ray CT imaging technique with 2D SEM-EDX and use spatial statistics methods to map the chemical composition of soil in 3D. The procedure involves three stages 1) scanning a resin impregnated soil cube by X-ray CT, followed by precision cutting to produce parallel thin slices, the surfaces of which are scanned by SEM-EDX, 2) alignment of the 2D chemical maps within the internal 3D structure of the soil cube, and 3) development, of spatial statistics methods to predict the chemical composition of 3D soil based on the observed 2D chemical and 3D physical data. Specifically, three statistical models consisting of a regression tree, a regression tree kriging and cokriging model were used to predict the 3D spatial distribution of carbon, silicon, iron and oxygen in soil, these chemical elements showing a good spatial agreement between the X-ray grayscale intensities and the corresponding 2D SEM-EDX data. Due to the spatial correlation between the physical and chemical data, the regression-tree model showed a great potential in predicting chemical composition in particular for iron, which is generally sparsely distributed in soil. For carbon, silicon and oxygen, which are more densely distributed, the additional kriging of the regression tree residuals improved significantly the prediction, whereas prediction based on co-kriging was less consistent across replicates, underperforming regression-tree kriging. The present study shows a great potential in integrating geo-statistical methods with imaging techniques to unveil the 3D chemical structure of soil at very fine scales, the framework being suitable to be further applied to other types of imaging data such as images of biological thin sections for characterization of microbial distribution. Key words: X-ray CT, SEM-EDX, segmentation techniques, spatial correlation, 3D soil images, 2D chemical maps.

Space imagery and some geomorphological problems of the Guiana Shield, South America

NASA Technical Reports Server (NTRS)

Melhorn, W. N.

1985-01-01

Some ongoing involvement in regional geomorphologic research in South America is described. Because of association with LARS at Purdue University, there has been engagement, vicarious or adivsory, in projects which led to LANDSAT 1-2 mapping of the natural resources of Bolivia (1:8,000,000 scale), and preparation of a geographic information system which mapped the general hydrology, geology, soils, and vegetation of Ecuador (1:4,000,000 scale). Currently we are involved more specifically in geological-geomorphological mapping of the Venezuelan portion of the Guiana shield, and because of manuscript limitations only questions pertinent to this region are posed in the ensuing discussion.

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

NASA Astrophysics Data System (ADS)

Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Reemt Bogena, Heye; Vereecken, Harry

2017-05-01

In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm-3 for the assimilation period and 0.05 cm3 cm-3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm-3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

Assessment of possibilities and conditions of irrigation in Hungary by digital soil map products

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Bakacsi, Zsófia; Takács, Katalin; Szatmári, Gábor; Szabó, József; Pásztor, László

2016-04-01

Sustaining proper soil moisture is essentially important in agricultural management. However, irrigation can be really worth only, if we lay sufficient emphasis on soil conservation. Nationwide planning of irrigation can be taken place, if we have spatially exhaustive maps and recommendations for the different areas. Soil moisture in the pores originate from 'above' (precipitation), or from 'beneath' (from groundwater by capillary lift). The level of groundwater depends on topography, climatic conditions and water regime of the nearby river. The thickness of capillary zone is basicly related to the physical and water management properties of the soil. Accordingly the capillary rise of sandy soils - with very high infiltration rate and very poor water retaining capacity - are far smaller than in the case of clay soils - with very poor infiltration rate and high water retaining capacity. Applying irrigation water can be considered as a reinforcement from 'above', and it affects the salinity and sodicity as well as the soil structure, nutrient supply and soil formation. We defined the possibilities of irrigation according to the average salt content of the soil profile. The nationwide mapping of soil salinity was based on legacy soil profile data, and it was carried out by regression kriging. This method allows that environmental factors with exhaustive spatial extension, such as climatic-, vegetation-, topographic-, soil- and geologic layers can be taken into consideration to the spatial extension of the reference data. According to soil salinity content categories, the areas were delineated as 1. to be irrigated, 2. to be irrigated conditionally, 3. not to be irrigated. The conditions of irrigation was determined by the comparison of the 'actual' and the 'critical' depth of the water table. Since, if the water rises above the critical level, undesirable processes, such as salinization and alkalinization can be developed. The critical depth of the water table was calculated according to the literature, and based on average soil content of the soil profile, the water regime category of soil, salt content of the groundwater, and soil pH. The water regime category map originated from legacy polygon-based map of physical soil properties. The soil content, and the actual level of groundwater as well as the soil pH map - similarly to the soil salinity map - was compiled by regression kriging. The conditions are classified into the following three categories: 1. level of groundwater have to be sinked, 2. rising of groundwater level have to be hindered, 3. level of groundwater have to be regularly controlled. The newly compiled maps can help decision makers to improve land use management, taking soil conservation into consideration. Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167) and the Research Institute of Agricultural Economics.

Hyperspectral Soil Mapper (HYSOMA) software interface: Review and future plans

NASA Astrophysics Data System (ADS)

Chabrillat, Sabine; Guillaso, Stephane; Eisele, Andreas; Rogass, Christian

2014-05-01

With the upcoming launch of the next generation of hyperspectral satellites that will routinely deliver high spectral resolution images for the entire globe (e.g. EnMAP, HISUI, HyspIRI, HypXIM, PRISMA), an increasing demand for the availability/accessibility of hyperspectral soil products is coming from the geoscience community. Indeed, many robust methods for the prediction of soil properties based on imaging spectroscopy already exist and have been successfully used for a wide range of soil mapping airborne applications. Nevertheless, these methods require expert know-how and fine-tuning, which makes them used sparingly. More developments are needed toward easy-to-access soil toolboxes as a major step toward the operational use of hyperspectral soil products for Earth's surface processes monitoring and modelling, to allow non-experienced users to obtain new information based on non-expensive software packages where repeatability of the results is an important prerequisite. In this frame, based on the EU-FP7 EUFAR (European Facility for Airborne Research) project and EnMAP satellite science program, higher performing soil algorithms were developed at the GFZ German Research Center for Geosciences as demonstrators for end-to-end processing chains with harmonized quality measures. The algorithms were built-in into the HYSOMA (Hyperspectral SOil MApper) software interface, providing an experimental platform for soil mapping applications of hyperspectral imagery that gives the choice of multiple algorithms for each soil parameter. The software interface focuses on fully automatic generation of semi-quantitative soil maps such as soil moisture, soil organic matter, iron oxide, clay content, and carbonate content. Additionally, a field calibration option calculates fully quantitative soil maps provided ground truth soil data are available. Implemented soil algorithms have been tested and validated using extensive in-situ ground truth data sets. The source of the HYSOMA code was developed as standalone IDL software to allow easy implementation in the hyperspectral and non-hyperspectral communities. Indeed, within the hyperspectral community, IDL language is very widely used, and for non-expert users that do not have an ENVI license, such software can be executed as a binary version using the free IDL virtual machine under various operating systems. Based on the growing interest of users in the software interface, the experimental software was adapted for public release version in 2012, and since then ~80 users of hyperspectral soil products downloaded the soil algorithms at www.gfz-potsdam.de/hysoma. The software interface was distributed for free as IDL plug-ins under the IDL-virtual machine. Up-to-now distribution of HYSOMA was based on a close source license model, for non-commercial and educational purposes. Currently, the HYSOMA is being under further development in the context of the EnMAP satellite mission, for extension and implementation in the EnMAP Box as EnSoMAP (EnMAP SOil MAPper). The EnMAP Box is a freely available, platform-independent software distributed under an open source license. In the presentation we will focus on an update of the HYSOMA software interface status and upcoming implementation in the EnMAP Box. Scientific software validation, associated publication record and users responses as well as software management and transition to open source will be discussed.

Oxygen-17 anomaly in soil nitrate: A new precipitation proxy for desert landscapes

NASA Astrophysics Data System (ADS)

Wang, Fan; Ge, Wensheng; Luo, Hao; Seo, Ji-Hye; Michalski, Greg

2016-03-01

The nitrogen cycle in desert soil ecosystems is particularly sensitive to changes in precipitation, even of relatively small magnitude and short duration, because it is already under water stress. This suggests that desert soils may have preserved past evidence of small variations in continental precipitation. We have measured nitrate (NO3-) concentrations in soils from the Atacama (Chile), Kumtag (China), Mojave (US), and Thar (India) deserts, and stable nitrogen and oxygen isotope (15N, 17O, and 18O) abundances of the soil NO3-. 17O anomalies (Δ17O), the deviations from the mass-independent isotopic fractionation, were detected in soil NO3- from almost all sites of these four deserts. There was a strong negative correlation between the mean annual precipitation (MAP) and soil NO3- Δ17O values (Δ

Application of laboratory reflectance spectroscopy to target and map expansive soils: example of the western Loiret, France

NASA Astrophysics Data System (ADS)

Hohmann, Audrey; Dufréchou, Grégory; Grandjean, Gilles; Bourguignon, Anne

2014-05-01

Swelling soils contain clay minerals that change volume with water content and cause extensive and expensive damage on infrastructures. Based on spatial distribution of infrastructure damages and existing geological maps, the Bureau de Recherches Géologiques et Minières (BRGM, i.e. the French Geological Survey) published in 2010 a 1:50 000 swelling hazard map of France, indexing the territory to low, moderate, or high swelling risk. This study aims to use SWIR (1100-2500 nm) reflectance spectra of soils acquired under laboratory controlled conditions to estimate the swelling potential of soils and improve the swelling risk map of France. 332 samples were collected at the W of Orléans (France) in various geological formations and swelling risk areas. Comparisons of swelling potential of soil samples and swelling risk areas of the map show several inconsistent associations that confirm the necessity to redraw the actual swelling risk map of France. New swelling risk maps of the sampling area were produce from soil samples using three interpolation methods. Maps produce using kriging and Natural neighbour interpolation methods did not permit to show discrete lithological units, introduced unsupported swelling risk zones, and did not appear useful to refine swelling risk map of France. Voronoi polygon was also used to produce map where swelling potential estimated from each samples were extrapolated to a polygon and all polygons were thus supported by field information. From methods tested here, Voronoi polygon appears thus the most adapted method to produce expansive soils maps. However, size of polygon is highly dependent of the samples spacing and samples may not be representative of the entire polygon. More samples are thus needed to provide reliable map at the scale of the sampling area. Soils were also sampled along two sections with a sampling interval of ca. 260 m and ca. 50 m. Sample interval of 50 m appears more adapted for mapping of smallest lithological units. The presence of several samples close to themselves indicating the same swelling potential is a good indication of the presence of a zone with constant swelling potential. Combination of Voronoi method and sampling interval of ca. 50 m appear adapted to produce local swelling potential maps in areas where doubt remain or where infrastructure damages attributed to expansive soils are knew.

Highly spatially- and seasonally-resolved predictive contamination maps for persistent organic pollutants: development and validation.

PubMed

Ballabio, Cristiano; Guazzoni, Niccoló; Comolli, Roberto; Tremolada, Paolo

2013-08-01

A reliable spatial assessment of the POPs contamination in soils is essential for burden studies and flux evaluations. Soil characteristics and properties vary enormously even within small spatial scale and over time; therefore soil capacity of accumulating POPs varies greatly. In order to include this very high spatial and temporal variability, models can be used for assessing soil accumulation capacity in a specific time and space and, from it, the spatial distribution and temporal trends of POPs concentrations. In this work, predictive contamination maps of the accumulation capacity of soils were developed at a space resolution of 1×1m with a time frame of one day, in a study area located in the central Alps. Physical algorithms for temperature and organic carbon estimation along the soil profile and across the year were fitted to estimate the horizontal, vertical and seasonal distribution of the contamination potential for PCBs in soil (Ksa maps). The resulting maps were cross-validated with an independent set of PCB contamination data, showing very good agreement (e.g. for CB-153, R(2)=0.80, p-value≤2.2·10(-06)). Slopes of the regression between predicted Ksa and experimental concentrations were used to map the soil contamination for the whole area, taking into account soil characteristics and temperature conditions. These maps offer the opportunity to evaluate burden (concentration maps) and fluxes (emission maps) with highly resolved temporal and spatial detail. In addition, in order to explain the observed low autumn PCB concentrations in soil related to the high Ksa values of this period, a dynamic model of seasonal variation of soil concentrations was developed basing on rate parameters fitted on measured concentrations. The model was able to describe, at least partially, the observed different behavior between the quite rapid discharge phase in summer and the slow recharge phase in autumn. Copyright © 2013 Elsevier B.V. All rights reserved.

Quaternary geologic map of the Shelby 1° x 2° quadrangle, Montana

USGS Publications Warehouse

Fullerton, David S.; Colton, Roger B.; Bush, Charles A.

2013-01-01

The Shelby quadrangle encompasses approximately 16,084 km2 (6,210 mi2). The northern boundary is the Montana/Saskatchewan (U.S./Canada) boundary. The quadrangle is in the Northern Plains physiographic province and it includes the Sweet Grass Hills. The primary river is the Marias River. The ancestral Missouri River was diverted south of the Bearpaw Mountains by a Laurentide ice sheet. The fill in the buried ancestral valleys of the Missouri River and Marias River in the southeast quarter of the quadrangle contains a complex stratigraphy of fluvial, glaciofluvial, ice-contact, glacial, lacustrine, and eolian deposits. The map units are surficial deposits and materials, not landforms. Deposits that comprise some constructional landforms (for example, ground-moraine deposits, end-moraine deposits, stagnation-moraine deposits, all composed of till) are distinguished for purposes of reconstruction of glacial history. Surficial deposits and materials are assigned to 21 map units on the basis of genesis, age, lithology or composition, texture or particle size, and other physical, chemical, and engineering characteristics. It is not a map of soils that are recognized in pedology or agronomy. Rather, it is a generalized map of soils recognized in engineering geology, or of substrata or parent materials in which pedologic or agronomic soils are formed. Glaciotectonic (ice-thrust) structures and deposits are mapped separately, represented by a symbol. On the glaciated plains, the surficial deposits are glacial, ice-contact, glaciofluvial, alluvial, lacustrine, eolian, colluvial, and mass-movement deposits. In the Sweet Grass Hills, beyond the limit of Quaternary glaciation they are fluvial, colluvial, and mass-movement deposits. Till of late Wisconsin age is represented by three map units. Tills of Illinoian and pre-Illinoian glaciations are not mapped, but are widespread in the subsurface. Linear ice-molded landforms (primarily drumlins) indicate directions of ice flow during late Wisconsin glaciation.

Effective use of ERTS multisensor data in the Northern Great Plains

NASA Technical Reports Server (NTRS)

Myers, V. I.; Westin, F. C.; Horton, M. L.; Lewis, J. K. (Principal Investigator)

1974-01-01

The author has identified the following significant results. ERTS imagery was used as a tool in the identification and refinement of soil association areas; to classify land use patterns between crop and fallow fields; to identify corn, soybeans, and oats; and to identify broad generalized range ecosystems. Various data handling techniques were developed and applied to accomplish these tasks. A map outlining soil associations and relative land values was completed on a base mosaic of ERTS imagery and is included as an appendix to the report.

Digital mapping of soil properties in Canadian managed forests at 250 m of resolution using the k-nearest neighbor method

NASA Astrophysics Data System (ADS)

Mansuy, N. R.; Paré, D.; Thiffault, E.

2015-12-01

Large-scale mapping of soil properties is increasingly important for environmental resource management. Whileforested areas play critical environmental roles at local and global scales, forest soil maps are typically at lowresolution.The objective of this study was to generate continuous national maps of selected soil variables (C, N andsoil texture) for the Canadian managed forest landbase at 250 m resolution. We produced these maps using thekNN method with a training dataset of 538 ground-plots fromthe National Forest Inventory (NFI) across Canada,and 18 environmental predictor variables. The best predictor variables were selected (7 topographic and 5 climaticvariables) using the Least Absolute Shrinkage and Selection Operator method. On average, for all soil variables,topographic predictors explained 37% of the total variance versus 64% for the climatic predictors. Therelative root mean square error (RMSE%) calculated with the leave-one-out cross-validation method gave valuesranging between 22% and 99%, depending on the soil variables tested. RMSE values b 40% can be considered agood imputation in light of the low density of points used in this study. The study demonstrates strong capabilitiesfor mapping forest soil properties at 250m resolution, compared with the current Soil Landscape of CanadaSystem, which is largely oriented towards the agricultural landbase. The methodology used here can potentiallycontribute to the national and international need for spatially explicit soil information in resource managementscience.

A guide for the use of digital elevation model data for making soil surveys

USGS Publications Warehouse

Klingebiel, A.A.; Horvath, Emil H.; Reybold, William U.; Moore, D.G.; Fosnight, E.A.; Loveland, Thomas R.

1988-01-01

The intent of this publication is twofold: (1) to serve as a user guide for soil scientists and others interested in learning about the value and use of digital elevation model (DEM) data in making soil surveys and (2) to provide documentation of the Soil Landscape Analysis Project (SLAP). This publication provides a step-by-step guide on how digital slope-class maps are adjusted to topographic maps and orthophotoquads to obtain accurate slope-class maps, and how these derivative maps can be used as a base for soil survey premaps. In addition, guidance is given on the use of aspect-class maps and other resource data in making pre-maps. The value and use of tabular summaries are discussed. Examples of the use of DEM products by the authors and by selected field soil scientists are also given. Additional information on SLAP procedures may be obtained from USDA, Soil Conservation Service, Soil Survey Division, P.O. Box 2890, Washington, D.C. 20013, and from references (Horvath and others, 1987; Horvath and others, 1983; Klingebiel and others, 1987; and Young, 1987) listed in this publication. The slope and aspect products and the procedures for using these products have evolved during 5 years of cooperative research with the USDA, Soil Conservation Service and Forest Service, and the USDI, Bureau of Land Management.

Validating a spatially distributed hydrological model with soil morphology data

NASA Astrophysics Data System (ADS)

Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.

2014-09-01

Spatially distributed models are popular tools in hydrology claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for inputs of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography and artificial drainage. We translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to observed groundwater levels and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the the groundwater level predictions were not accurate enough to be used for the prediction of saturated areas. Groundwater level dynamics were not adequately reproduced and the predicted spatial saturation patterns did not correspond to those estimated from the soil map. Our results indicate that an accurate prediction of the groundwater level dynamics of the shallow groundwater in our catchment that is subject to artificial drainage would require a model that better represents processes at the boundary between the unsaturated and the saturated zone. However, data needed for such a more detailed model are not generally available. This severely hampers the practical use of such models despite their usefulness for scientific purposes.

Ecogeochemical mapping of urban soils as a tool for indication of risk factors

NASA Astrophysics Data System (ADS)

Sahakyan, Lilit; Saghetalyan, Armen; Asmaryan, Shushanik

2010-05-01

Today, most global and local environmental issues are connected with the disturbance of natural equilibrium of chemical elements, which is manifested by two contrary but synchronous and interconnected geochemical processes: dispersion and concentration of chemical elements. The ecological consequence of those intensively running processes is pollution of environmental compartments. High intensity and multi-component character of pollution is common to urban ecosystems. In this respect emphasized should be mining centers representing biogeochemical provinces where the whole range of geochemical processes connected with socio-economic activities of the man reaches its maximum and high natural background of chemical elements is coupled with their man-made load. Ecogeochemical mapping of soils of mining regions and cities is one of major tools while assessing ecological state of the territory and indicating risk factors. When systemizing indices of geochemical pollution, the produced case specific maps coupled with ecogeochemical mapping techniques are territorial generalization of levels of pollution and levels of its danger. This allows indicating its spatial differentiation and finally ranging the city's territory by features of the defined level of ecological risk. Moreover, ecogeochemical mapping of soils allows indicating dominating pollutants, peculiarities of their distribution and major risk factors as well and thus revealing risk groups in the population. An alternative method of ecogeochemical mapping of urban soils which allows to notably reduce the process of pollution level assessment and identification of risk factor is that of remote sensing. Collation between spatially conjugated data of soil analyses and multi-zonal satellite images allows developing spectral characteristics (signatures) of pollution of the territory with heavy metals (HM) and development of appropriate assessment criteria which may be reflected as diverse case specific maps. This work considers the outcomes of application of ecogeochemical mapping of urban soils while revealing risk factors on a case of one of Armenia's mining centers - the city of Kajaran. It lies within the bounds of sulfide copper-molybdenum deposit, on which base a mining and dressing set of plants - a city-forming enterprise - operates. As established, the city's territory is polluted predominantly with major ore elements: Mo, Cu. At the same time locally indicated are anomalies of a series of elements found in the ore in insignificant concentrations: As, Hg, Cd. Proceeding from fact that soils are indicators of atmospheric pollution, investigated were HM contents in dust. As established, the dust of the quarry and tailing repositories contains high contents of Cu, Mo, Zn and also Hg, As, Cd. The assessment of farm crops cultivated on polluted soils indicated Mo, Cu, Pb, Ni, Cr, Zn, Hg excesses vs. MPC in potatoes, beans, beetroot and dill. Thus, the dust of the quarry and tailing repositories and farm crops has been defined as the major risk factors. Data on detailed above-surface investigations with clear spatial and temporal coordination were collated with multi-zonal satellite images (Landsat ETM +28m) of the territory. As a result spectral signatures have been obtained which allows differentiation of the territory by the value of summary pollution with HM.

VARIABLE RATE APPLICATION OF SOIL HERBICIDES IN ARABLE CROPS: FROM THEORY TO PRACTICE.

PubMed

Heijting, S; Kempenaar, C

2014-01-01

Soil herbicides are applied around crop emergence and kill germinating weeds in the surface layer of the soil. These herbicides play an important role in the chemical management of weeds in major arable crops. From an environmental point of view there is a clear need for smarter application of these chemicals. This paper presents research done in The Netherlands on Variable Rate Application (VRA) of soil herbicides by taking into account spatial variation of the soil. Herbicides adsorbed to soil parameters such as clay or organic matter are not available for herbicidal activity. Decision Support Rules (DSR) describe the relation between the soil parameter and herbicide dosage needed for effectively controlling weeds. Research methods such as greenhouse trials, models and on farm research to develop DSR are discussed and results are presented. Another important ingredient for VRA of soil herbicides is an accurate soil map of the field. Sampling and subsequent interpolation is costly. Soil scans measuring a proxy that is subsequently translated into soil properties such as clay fraction and soil organic matter content offer a quicker way to achieve such maps but validation is needed. DSR is applied to the soil map to get the variable dosage map. The farmer combines this map with the routing, spray volume and spray boom width in the Farm Management Information System (FMIS), resulting in a task file. This task file can subsequently be read by the board computer resulting in a VRA spray map. Reduction in soil herbicide depends on the DSR, the spatial variation and pattern of the soil, the spatial configuration of the routing and the technical advances of the spray equipment. Recently, within the framework the Programma Precisie Landbouw, first steps were made to test and implement this in practice. Currently, theory and practice of VRA of soil herbicides is developed within the research program IJKakker in close cooperation with pioneering farmers in The Netherlands.

Understanding the effect of watershed characteristic on the runoff using SCS curve number

NASA Astrophysics Data System (ADS)

Damayanti, Frieta; Schneider, Karl

2015-04-01

Runoff modeling is a key component in watershed management. The temporal course and amount of runoff is a complex function of a multitude of parameters such as climate, soil, topography, land use, and water management. Against the background of the current rapid environmental change, which is due to both i) man-made changes (e.g. urban development, land use change, water management) as well as ii) changes in the natural systems (e.g. climate change), understanding and predicting the impacts of these changes upon the runoff is very important and affects the wellbeing of many people living in the watershed. A main tool for predictions is hydrologic models. Particularly process based models are the method of choice to assess the impact of land use and climate change. However, many regions which experience large changes in the watersheds can be described as rather data poor, which limits the applicability of such models. This is particularly also true for the Telomoyo Watershed (545 km2) which is located in southern part of Central Java province. The average annual rainfall of the study area reaches 2971 mm. Irrigated paddy field are the dominating land use (35%), followed by built-up area and dry land agriculture. The only available soil map is the FAO soil digital map of the world, which provides rather general soil information. A field survey accompanied by a lab analysis 65 soil samples of was carried out to provide more detailed soil texture information. The soil texture map is a key input in the SCS method to define hydrological soil groups. In the frame of our study on 'Integrated Analysis on Flood Risk of Telomoyo Watershed in Response to the Climate and Land Use Change' funded by the German Academic Exchange service (DAAD) we analyzed the sensitivity of the modeled runoff upon the choice of the method to estimate the CN values using the SCS-CN method. The goal of this study is to analyze the impact of different data sources on the curve numbers and the estimated runoff. CN values were estimated using the field measurements of soil textures for different combinations of land use and topography. To transfer the local soil texture measurements to the watershed domain a statistical analysis using the frequency distribution of the measured soil textures is applied and used to derive the effective CN value for a given land use, topography and soil texture combination. Since the curve numbers change as a function of parameter combinations, the effect of different methods to estimate the curve number upon the runoff is analyzed and compared to the straight forward method of using the data from the FAO soil map.

Remote sensing in Iowa agriculture. [land use, crop identification, and soil mapping

NASA Technical Reports Server (NTRS)

Mahlstede, J. P. (Principal Investigator); Carlson, R. E.; Fenton, T. E.

1974-01-01

The author has identified the following significant results. Analysis of 1972 single-date coverage indicated that a complete crop classification was not attainable at the test sites. Good multi-date coverage during 1973 indicates that many of the problems encountered in 1972 will be minimized. In addition, the compilation of springtime imagery covering the entire state of Iowa has added a new dimension to interpretation of Iowa's natural resources. ERTS-1 has provided data necessary to achieve the broad synoptic view not attainable through other means. This should provide soils and crop researchers and land use planners a base map of Iowa. Granted and due to the resolution of ERTS-1, not all details are observable for many land use planning needs, but this gives a general and current view of Iowa.

A semester-long soil mapping project for an undergraduate pedology course

NASA Astrophysics Data System (ADS)

Brown, David J.

2015-04-01

Most students taking a pedology course will never work as soil mappers. But many will use soil maps at some point in their careers. At Montana State University, students spent 3 "lab" hours a week, complementing two lectures a week, in the field learning how to study soils literally from the ground up. The only prerequisites for enrollment were completion of an introductory soil science class and 3rd year standing at the university. The area to be mapped, just a km from campus, included a steep mountain backslope, and a complex footslope-toeslope area with diverse soils. Students were divided into teams of 3-4, with approximately 40 students altogether split over two sections that overlapped in the field by one hour. In the first lab session, groups completed a very basic description of just one soil profile. In subsequent weeks, they rotated through multiple pits excavated in a small area, and expanded their soil profile descriptions and interpretations. As students developed proficiency, they were assigned more dispersed locations to study, working for the most part independently as I hiked between pits. Throughout this process, every pit was geolocated using a GPS unit, and every profile description was copied and retained in a designated class file. Student groups delineated map units using stereo air photography, then used these delineations to guide the selection of their final locations to describe. At the end of the course, groups used all of the combined and georeferenced profile descriptions to construct a soil map of the study area complete with map unit descriptions. Most students struggled to make sense of the substantial variability within their map units, but through this struggle -- and their semester of field work -- they gained an appreciation for the value and limitations of a soil map that could not be obtained from even the most entertaining lecture. Both the class and particularly the field sessions received consistently high student reviews during the four years I had students map soils at Montanta State University.

Mapping specific soil functions based on digital soil property maps

NASA Astrophysics Data System (ADS)

Pásztor, László; Fodor, Nándor; Farkas-Iványi, Kinga; Szabó, József; Bakacsi, Zsófia; Koós, Sándor

2016-04-01

Quantification of soil functions and services is a great challenge in itself even if the spatial relevance is supposed to be identified and regionalized. Proxies and indicators are widely used in ecosystem service mapping. Soil services could also be approximated by elementary soil features. One solution is the association of soil types with services as basic principle. Soil property maps however provide quantified spatial information, which could be utilized more versatilely for the spatial inference of soil functions and services. In the frame of the activities referred as "Digital, Optimized, Soil Related Maps and Information in Hungary" (DOSoReMI.hu) numerous soil property maps have been compiled so far with proper DSM techniques partly according to GSM.net specifications, partly by slightly or more strictly changing some of its predefined parameters (depth intervals, pixel size, property etc.). The elaborated maps have been further utilized, since even DOSoReMI.hu was intended to take steps toward the regionalization of higher level soil information (secondary properties, functions, services). In the meantime the recently started AGRAGIS project requested spatial soil related information in order to estimate agri-environmental related impacts of climate change and support the associated vulnerability assessment. One of the most vulnerable services of soils in the context of climate change is their provisioning service. In our work it was approximated by productivity, which was estimated by a sequential scenario based crop modelling. It took into consideration long term (50 years) time series of both measured and predicted climatic parameters as well as accounted for the potential differences in agricultural practice and crop production. The flexible parametrization and multiple results of modelling was then applied for the spatial assessment of sensitivity, vulnerability, exposure and adaptive capacity of soils in the context of the forecasted changes in climatic conditions in the Carpathian Basin. In addition to soil fertility, degradation risk due to N-leaching was also assessed by the model runs by taking into account the movement of nitrate in the profile during the simulated periods. Our paper will present the resulted national maps and some conclusions drawn from the experiences. Acknowledgement: Our work was supported by Iceland, Liechtenstein and Norway through the EEA Grants and the REC (Project No: EEA C12-12) and the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Combining land use data acquired from Landsat with soil map data

NASA Technical Reports Server (NTRS)

Westin, F. C.; Brandner, T. M.

1981-01-01

A method currently used to derive agrophysical units (APUs), i.e., geographical areas having definable/comparable agronomic and physical parameters which reflect a range in agricultural use and management, is discussed with reference to results obtained for South Dakota and an area in China. The method consists of combining agricultural land use data acquired from Landsat with soil map data. The resulting map units are soil associations characterized by cropland use intensity, and they can be used to identify major cropland areas and to develop a rating reflecting the relative potential of the soils in the delineated area for crop production, as well as to update small-scale soil maps.

On-the-go mapping of soil mechanical resistance using a linear depth effect model.

USDA-ARS?s Scientific Manuscript database

An instrumented blade sensor was developed to map soil mechanical resistance as well as its change with depth. The sensor has become a part of the Integrated Soil Physical Properties Mapping System (ISPPMS), which also includes an optical and a capacitor-based sensor. The instrumented blade of the...

7 CFR 12.31 - On-site wetland identification criteria.

Code of Federal Regulations, 2011 CFR

2011-01-01

... CONSERVATION Wetland Conservation § 12.31 On-site wetland identification criteria. (a) Hydric soils. (1) NRCS shall identify hydric soils through the use of published soil maps which reflect soil surveys completed by NRCS or through the use of on-site reviews. If a published soil map is unavailable for a given...

7 CFR 12.31 - On-site wetland identification criteria.

Code of Federal Regulations, 2014 CFR

2014-01-01

... CONSERVATION Wetland Conservation § 12.31 On-site wetland identification criteria. (a) Hydric soils. (1) NRCS shall identify hydric soils through the use of published soil maps which reflect soil surveys completed by NRCS or through the use of on-site reviews. If a published soil map is unavailable for a given...

7 CFR 12.31 - On-site wetland identification criteria.

Code of Federal Regulations, 2010 CFR

2010-01-01

... CONSERVATION Wetland Conservation § 12.31 On-site wetland identification criteria. (a) Hydric soils. (1) NRCS shall identify hydric soils through the use of published soil maps which reflect soil surveys completed by NRCS or through the use of on-site reviews. If a published soil map is unavailable for a given...

7 CFR 12.31 - On-site wetland identification criteria.

Code of Federal Regulations, 2013 CFR

2013-01-01

... CONSERVATION Wetland Conservation § 12.31 On-site wetland identification criteria. (a) Hydric soils. (1) NRCS shall identify hydric soils through the use of published soil maps which reflect soil surveys completed by NRCS or through the use of on-site reviews. If a published soil map is unavailable for a given...

7 CFR 12.31 - On-site wetland identification criteria.

Code of Federal Regulations, 2012 CFR

2012-01-01

... CONSERVATION Wetland Conservation § 12.31 On-site wetland identification criteria. (a) Hydric soils. (1) NRCS shall identify hydric soils through the use of published soil maps which reflect soil surveys completed by NRCS or through the use of on-site reviews. If a published soil map is unavailable for a given...

Mathematical models application for mapping soils spatial distribution on the example of the farm from the North of Udmurt Republic of Russia

NASA Astrophysics Data System (ADS)

Dokuchaev, P. M.; Meshalkina, J. L.; Yaroslavtsev, A. M.

2018-01-01

Comparative analysis of soils geospatial modeling using multinomial logistic regression, decision trees, random forest, regression trees and support vector machines algorithms was conducted. The visual interpretation of the digital maps obtained and their comparison with the existing map, as well as the quantitative assessment of the individual soil groups detection overall accuracy and of the models kappa showed that multiple logistic regression, support vector method, and random forest models application with spatial prediction of the conditional soil groups distribution can be reliably used for mapping of the study area. It has shown the most accurate detection for sod-podzolics soils (Phaeozems Albic) lightly eroded and moderately eroded soils. In second place, according to the mean overall accuracy of the prediction, there are sod-podzolics soils - non-eroded and warp one, as well as sod-gley soils (Umbrisols Gleyic) and alluvial soils (Fluvisols Dystric, Umbric). Heavy eroded sod-podzolics and gray forest soils (Phaeozems Albic) were detected by methods of automatic classification worst of all.

Spatial disaggregation of complex soil map units at regional scale based on soil-landscape relationships

NASA Astrophysics Data System (ADS)

Vincent, Sébastien; Lemercier, Blandine; Berthier, Lionel; Walter, Christian

2015-04-01

Accurate soil information over large extent is essential to manage agronomical and environmental issues. Where it exists, information on soil is often sparse or available at coarser resolution than required. Typically, the spatial distribution of soil at regional scale is represented as a set of polygons defining soil map units (SMU), each one describing several soil types not spatially delineated, and a semantic database describing these objects. Delineation of soil types within SMU, ie spatial disaggregation of SMU allows improved soil information's accuracy using legacy data. The aim of this study was to predict soil types by spatial disaggregation of SMU through a decision tree approach, considering expert knowledge on soil-landscape relationships embedded in soil databases. The DSMART (Disaggregation and Harmonization of Soil Map Units Through resampled Classification Trees) algorithm developed by Odgers et al. (2014) was used. It requires soil information, environmental covariates, and calibration samples, to build then extrapolate decision trees. To assign a soil type to a particular spatial position, a weighed random allocation approach is applied: each soil type in the SMU is weighted according to its assumed proportion of occurrence in the SMU. Thus soil-landscape relationships are not considered in the current version of DSMART. Expert rules on soil distribution considering the relief, parent material and wetlands location were proposed to drive the procedure of allocation of soil type to sampled positions, in order to integrate the soil-landscape relationships. Semantic information about spatial organization of soil types within SMU and exhaustive landscape descriptors were used. In the eastern part of Brittany (NW France), 171 soil types were described; their relative area in the SMU were estimated, geomorphological and geological contexts were recorded. The model predicted 144 soil types. An external validation was performed by comparing predicted with effectively observed soil types derived from available soil maps at scale of 1:25.000 or 1:50.000. Overall accuracies were 63.1% and 36.2%, respectively considering or not the adjacent pixels. The introduction of expert rules based on soil-landscape relationships to allocate soil types to calibration samples enhanced dramatically the results in comparison with a simple weighted random allocation procedure. It also enabled the production of a comprehensive soil map, retrieving expected spatial organization of soils. Estimation of soil properties for various depths is planned using disaggregated soil types, according to the GlobalSoilmap.net specifications. Odgers, N.P., Sun, W., McBratney, A.B., Minasny, B., Clifford, D., 2014. Disaggregating and harmonising soil map units through resampled classification trees. Geoderma 214, 91-100.

Digital Soil Mapping - A platform for enhancing soil learning

NASA Astrophysics Data System (ADS)

Owens, Phillip; Libohova, Zamir; Monger, Curtis; Lindbo, David; Schmidt, Axel

2017-04-01

The expansion of digital infrastructure and tools has generated massive data and information as well as a need for reliable processing and accurate interpretations. Digital Soil Mapping is no exception in that it has provided opportunities for professionals and the public to interact at field and training/workshop levels in order to better understand soils and their benefits. USDA-NRCS National Cooperative Soil Survey regularly conducts training and workshops for soil scientists and other professionals in the US and internationally. A combination of field experiences with workshops conducted in a class environment offers ideal conditions for enhancing soil learning experiences. Examples from US, Haiti and Central America show that Digital Soil Mapping (DSM) tools are very effective for understanding and visualizing soils and their functioning at different scales.

Effects of simulated daily precipitation patterns on annual plant populations depend on life stage and climatic region.

PubMed

Köchy, Martin

2008-03-27

To improve the understanding of consequences of climate change for annual plant communities, I used a detailed, grid-based model that simulates the effect of daily rainfall variability on individual plants in five climatic regions on a gradient from 100 to 800 mm mean annual precipitation (MAP). The model explicitly considers moisture storage in the soil. I manipulated daily rainfall variability by changing the daily mean rain (DMR, rain volume on rainy days averaged across years for each day of the year) by +/- 20%. At the same time I adjusted intervals appropriately between rainy days for keeping the mean annual volume constant. In factorial combination with changing DMR I also changed MAP by +/- 20%. Increasing MAP generally increased water availability, establishment, and peak shoot biomass. Increasing DMR increased the time that water was continuously available to plants in the upper 15 to 30 cm of the soil (longest wet period, LWP). The effect of DMR diminished with increasing humidity of the climate. An interaction between water availability and density-dependent germination increased the establishment of seedlings in the arid region, but in the more humid regions the establishment of seedlings decreased with increasing DMR. As plants matured, competition among individuals and their productivity increased, but the size of these effects decreased with the humidity of the regions. Therefore, peak shoot biomass generally increased with increasing DMR but the effect size diminished from the semiarid to the mesic Mediterranean region. Increasing DMR reduced via LWP the annual variability of biomass in the semiarid and dry Mediterranean regions. More rainstorms (greater DMR) increased the recharge of soil water reservoirs in more arid sites with consequences for germination, establishment, productivity, and population persistence. The order of magnitudes of DMR and MAP overlapped partially so that their combined effect is important for projections of climate change effects on annual vegetation.

The use of crop rotation for mapping soil organic content in farmland

NASA Astrophysics Data System (ADS)

Yang, Lin; Song, Min; Zhu, A.-Xing; Qin, Chengzhi

2017-04-01

Most of the current digital soil mapping uses natural environmental covariates. However, human activities have significantly impacted the development of soil properties since half a century, and therefore become an important factor affecting soil spatial variability. Many researches have done field experiments to show how soil properties are impacted and changed by human activities, however, spatial variation data of human activities as environmental covariates have been rarely used in digital soil mapping. In this paper, we took crop rotation as an example of agricultural activities, and explored its effectiveness in characterizing and mapping the spatial variability of soil. The cultivated area of Xuanzhou city and Langxi County in Anhui Province was chosen as the study area. Three main crop rotations,including double-rice, wheat-rice,and oilseed rape-cotton were observed through field investigation in 2010. The spatial distribution of the three crop rotations in the study area was obtained by multi-phase remote sensing image interpretation using a supervised classification method. One-way analysis of variance (ANOVA) for topsoil organic content in the three crop rotation groups was performed. Factor importance of seven natural environmental covariates, crop rotation, Land use and NDVI were generated by variable importance criterion of Random Forest. Different combinations of environmental covariates were selected according to the importance rankings of environmental covariates for predicting SOC using Random Forest and Soil Landscape Inference Model (SOLIM). A cross validation was generated to evaluated the mapping accuracies. The results showed that there were siginificant differences of topsoil organic content among the three crop rotation groups. The crop rotation is more important than parent material, land use or NDVI according to the importance ranking calculated by Random Forest. In addition, crop rotation improved the mapping accuracy, especially for the flat clutivated area. This study demonstrates the usefulness of human activities in digital soil mapping and thus indicates the necessity for human activity factors in digital soil mapping studies.

Modelling Soil Erosion in the Densu River Basin Using RUSLE and GIS Tools.

PubMed

Ashiagbori, G; Forkuo, E K; Laari, P; Aabeyir, R

2014-07-01

Soil erosion involves detachment and transport of soil particles from top soil layers, degrading soil quality and reducing the productivity of affected lands. Soil eroded from the upland catchment causes depletion of fertile agricultural land and the resulting sediment deposited at the river networks creates river morphological change and reservoir sedimentation problems. However, land managers and policy makers are more interested in the spatial distribution of soil erosion risk than in absolute values of soil erosion loss. The aim of this paper is to model the spatial distribution of soil erosion in Densu River Basin of Ghana using RUSLE and GIS tools and to use the model to explore the relationship between erosion susceptibility, slope and land use/land cover (LULC) in the Basin. The rainfall map, digital elevation model, soil type map, and land cover map, were input data in the soil erosion model developed. This model was then categorized into four different erosion risk classes. The developed soil erosion map was then overlaid with the slope and LULC maps of the study area to explore their effects on erosion susceptibility of the soil in the Densu River Basin. The Model, predicted 88% of the basin as low erosion risk and 6% as moderate erosion risk, 3% as high erosion risk and 3% as severe risk. The high and severe erosion areas were distributed mainly within the areas of high slope gradient and also sections of the moderate forest LULC class. Also, the areas within the moderate forest LULC class found to have high erosion risk, had an intersecting high erodibility soil group.

Mapping Soil Erosion Factors and Potential Erosion Risk for the National Park "Central Balkan"

NASA Astrophysics Data System (ADS)

Ilieva, Diliana; Malinov, Ilia

2014-05-01

Soil erosion is widely recognised environmental problem. The report aims at presenting the main results from assessment and mapping of the factors of sheet water erosion and the potential erosion risk on the territory of National Park "Central Balkan". For this purpose, the Universal Soil Loss Equation (USLE) was used for predicting soil loss from erosion. The influence of topography (LS-factor) and soil erodibility (K-factor) was assessed using small-scale topographic and soil maps. Rainfall erosivity (R-factor) was calculated from data of rainfalls with amounts exceeding 9.5 mm from 14 hydro-meteorological stations. The values of the erosion factors (R, K and LS) were presented for the areas of forest, sub-alpine and alpine zones. Using the methods of GIS, maps were plotted presenting the area distribution among the classes of the soil erosion factors and the potential risk in the respective zones. The results can be used for making accurate decisions for soil conservation and sustainable land management in the park.

The informativeness of coefficients a and b of the soil line for the analysis of remote sensing materials

NASA Astrophysics Data System (ADS)

Rukhovich, D. I.; Rukhovich, A. D.; Rukhovich, D. D.; Simakova, M. S.; Kulyanitsa, A. L.; Bryzzhev, A. V.; Koroleva, P. V.

2016-08-01

The coefficients of the soil line are often taken into account in calculations of vegetation indices. These coefficients are usually calculated for the entire satellite image, or are taken as constants without any calculations. In both cases, the informativeness of these coefficients is low and insufficient for the needs of soil mapping. In our study, we calculated soil line coefficients at 8000 lattice points for the territory of Plavsk, Arsen'evsk, and Chern districts of Tula oblast on the basis of 34 Landsat 5, 7, and 8 images obtained in 1985-2014. In order to distinguish between the soil line calculated for a given image and the soil line calculated for lattice points on the basis of dozens of multitemporal images, we suggest that the latter can be referred to as the temporal soil line. The temporal soil line is described by a classical equation: NIR = RED a + b, where a is its slope relative to the horizontal axis (RED), and b is the Y-axis (NIR) intercept. Both coefficients were used to create soil maps. The verification of the maps was performed with the use of data on 1985 soil pits. The informativeness of these coefficients appeared to be sufficient for delineation of eight groups of soils of different taxonomic levels: soddy moderately podzolic soils, soddy slightly podzolic soils, soddy-podzolic soils, light gray forest soils, gray forest soils, dark gray forest soils, podzolized chernozems, and leached chernozems. The b coefficient proved to be more informative, as it allowed us to create the soil map precisely on its basis. In order to create the soil map on the basis of the a coefficient, we had to apply some threshold values of the b coefficient. The bare soil on each of Landsat scenes was separated with the help of the mask of agricultural fields and the notion of the spectral neighborhood of soil line (SNSL).

Generalized geologic map of bedrock lithologies and surficial deposits in the Great Smoky Mountains National Park region, Tennessee and North Carolina

USGS Publications Warehouse

Southworth, Scott; Schultz, Art; Denenny, Danielle

2005-01-01

The geology of the Great Smoky Mountain National Park (GSMNP) region of Tennessee and North Carolina was studied from 1993 to 2003 as part of a cooperative investigation with the National Park Service (NPS). This work has been compiled as a 1:100,000-scale map derived from mapping done at 1:24,000 and 1:62,500 scale. The geologic data are intended to support cooperative investigations with NPS, the development of a new soil map by the Natural Resources Conservation Service, and the All Taxa Biodiversity Inventory (http://www.discoverlifeinamerica.org/). At the request of NPS, we mapped areas previously not visited, revised the geology where stratigraphic and structural problems existed, and developed a map database for use in interdisciplinary research, land management, and interpretive programs for park visitors.

Making US Soil Taxonomy more scientifically applicable to environmental and food security issues.

NASA Astrophysics Data System (ADS)

Monger, Curtis; Lindbo, David L.; Wysocki, Doug; Schoeneberger, Phil; Libohova, Zamir

2017-04-01

US Department of Agriculture began mapping soils in the 1890s on a county-by-county basis until most of the conterminous United States was mapped by the late 1930s. This first-generation mapping was followed by a second-generation that re-mapped the US beginning in the 1940s. Soil classification during these periods evolved into the current system of Soil Taxonomy which is based on (1) soil features as natural phenomena and on (2) soil properties important for agriculture and other land uses. While this system has enabled communication among soil surveyors, the scientific applicability of Soil Taxonomy to address environmental and food security issues has been under-utilized. In particular, little effort has been exerted to understand how soil taxa interact and function together as larger units—as soil systems. Thus, much soil-geomorphic understanding that could be applied to process-based modeling remains unexploited. The challenge for soil taxonomists in the United States and elsewhere is to expand their expertise and work with modelers to explore how soil taxa are linked to each other, how they influence water, nutrient, and pollutant flow through the landscape, how they interact with ecology, and how they change with human land use.

On the interpolation of volumetric water content in research catchments

NASA Astrophysics Data System (ADS)

Dlamini, Phesheya; Chaplot, Vincent

Digital Soil Mapping (DSM) is widely used in the environmental sciences because of its accuracy and efficiency in producing soil maps compared to the traditional soil mapping. Numerous studies have investigated how the sampling density and the interpolation process of data points affect the prediction quality. While, the interpolation process is straight forward for primary attributes such as soil gravimetric water content (θg) and soil bulk density (ρb), the DSM of volumetric water content (θv), the product of θg by ρb, may either involve direct interpolations of θv (approach 1) or independent interpolation of ρb and θg data points and subsequent multiplication of ρb and θg maps (approach 2). The main objective of this study was to compare the accuracy of these two mapping approaches for θv. A 23 ha grassland catchment in KwaZulu-Natal, South Africa was selected for this study. A total of 317 data points were randomly selected and sampled during the dry season in the topsoil (0-0.05 m) for θg by ρb estimation. Data points were interpolated following approaches 1 and 2, and using inverse distance weighting with 3 or 12 neighboring points (IDW3; IDW12), regular spline with tension (RST) and ordinary kriging (OK). Based on an independent validation set of 70 data points, OK was the best interpolator for ρb (mean absolute error, MAE of 0.081 g cm-3), while θg was best estimated using IDW12 (MAE = 1.697%) and θv by IDW3 (MAE = 1.814%). It was found that approach 1 underestimated θv. Approach 2 tended to overestimate θv, but reduced the prediction bias by an average of 37% and only improved the prediction accuracy by 1.3% compared to approach 1. Such a great benefit of approach 2 (i.e., the subsequent multiplication of interpolated maps of primary variables) was unexpected considering that a higher sampling density (∼14 data point ha-1 in the present study) tends to minimize the differences between interpolations techniques and approaches. In the context of much lower sampling densities, as generally encountered in environmental studies, one can thus expect approach 2 to yield significantly greater accuracy than approach 1. This approach 2 seems promising and can be further tested for DSM of other secondary variables.

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS

PubMed Central

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data. PMID:26090852

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS.

PubMed

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data.

Evaluating the new soil erosion map of Hungary

NASA Astrophysics Data System (ADS)

Waltner, István; Centeri, Csaba; Takács, Katalin; Pirkó, Béla; Koós, Sándor; László, Péter; Pásztor, László

2017-04-01

With growing concerns on the effects of climate change and land use practices on our soil resources, soil erosion by water is becoming a significant issue internationally. Since the 1964 publication of the first soil erosion map of Hungary, there have been several attempts to provide a countrywide assessment of erosion susceptibility. However, there has been no up-to-date map produced in the last decade. In 2016, a new, 1:100 000 scale soil erosion map was published, based on available soil, elevation, land use and meteorological data for the extremely wet year of 2010. The map utilized combined outputs for two spatially explicit methods: the widely used empirical Universal Soil Loss Equation (USLE) and the process-based Pan-European Soil Erosion Risk Assessment (PESERA) models. The present study aims to provide a detailed analysis of the model results. In lieu of available national monitoring data, information from other sources were used. The Soil Degradation Subsystem (TDR) of the National Environmental Information System (OKIR) is a digital database based on a soil survey and farm dairy data collected from representative farms in Hungary. During the survey all kind of degradation forms - including soil erosion - were considered. Agricultural and demographic data was obtained from the Hungarian Central Statistical Office (KSH). Data from an interview-based survey was also used in an attempt to assess public awareness of soil erosion risks. Point-based evaluation of the model results was complemented with cross-regional assessment of soil erosion estimates. This, combined with available demographic information provides us with an opportunity to address soil erosion on a community level, with the identification of regions with the highest risk of being affected by soil erosion.

The sensitivity of US wildfire occurrence to pre-season soil moisture conditions across ecosystems.

PubMed

Jensen, Daniel; Reager, John T; Zajic, Brittany; Rousseau, Nick; Rodell, Matthew; Hinkley, Everett

2018-01-01

It is generally accepted that year-to-year variability in moisture conditions and drought are linked with increased wildfire occurrence. However, quantifying the sensitivity of wildfire to surface moisture state at seasonal lead-times has been challenging due to the absence of a long soil moisture record with the appropriate coverage and spatial resolution for continental-scale analysis. Here we apply model simulations of surface soil moisture that numerically assimilate observations from NASA's Gravity Recovery and Climate Experiment (GRACE) mission with the US Forest Service's historical Fire-Occurrence Database over the contiguous United States. We quantify the relationships between pre-fire-season soil moisture and subsequent-year wildfire occurrence by land-cover type and produce annual probable wildfire occurrence and burned area maps at 0.25-degree resolution. Cross-validated results generally indicate a higher occurrence of smaller fires when months preceding fire season are wet, while larger fires are more frequent when soils are dry. This result is consistent with the concept of increased fuel accumulation under wet conditions in the pre-season. These results demonstrate the fundamental strength of the relationship between soil moisture and fire activity at long lead-times and are indicative of that relationship's utility for the future development of national-scale predictive capability.

The sensitivity of US wildfire occurrence to pre-season soil moisture conditions across ecosystems

NASA Astrophysics Data System (ADS)

Jensen, Daniel; Reager, John T.; Zajic, Brittany; Rousseau, Nick; Rodell, Matthew; Hinkley, Everett

2018-01-01

It is generally accepted that year-to-year variability in moisture conditions and drought are linked with increased wildfire occurrence. However, quantifying the sensitivity of wildfire to surface moisture state at seasonal lead-times has been challenging due to the absence of a long soil moisture record with the appropriate coverage and spatial resolution for continental-scale analysis. Here we apply model simulations of surface soil moisture that numerically assimilate observations from NASA’s Gravity Recovery and Climate Experiment (GRACE) mission with the USDA Forest Service’s historical Fire-Occurrence Database over the contiguous United States. We quantify the relationships between pre-fire-season soil moisture and subsequent-year wildfire occurrence by land-cover type and produce annual probable wildfire occurrence and burned area maps at 0.25 degree resolution. Cross-validated results generally indicate a higher occurrence of smaller fires when months preceding fire season are wet, while larger fires are more frequent when soils are dry. This is consistent with the concept of increased fuel accumulation under wet conditions in the pre-season. These results demonstrate the fundamental strength of the relationship between soil moisture and fire activity at long lead-times and are indicative of that relationship’s utility for the future development of national-scale predictive capability.

Preliminary map of peak horizontal ground acceleration for the Hanshin-Awaji earthquake of January 17, 1995, Japan - Description of Mapped Data Sets

USGS Publications Warehouse

Borcherdt, R.D.; Mark, R.K.

1995-01-01

The Hanshin-Awaji earthquake (also known as the Hyogo-ken Nanbu and the Great Hanshin earthquake) provided an unprecedented set of measurements of strong ground shaking. The measurements constitute the most comprehensive set of strong- motion recordings yet obtained for sites underlain by soft soil deposits of Holocene age within a few kilometers of the crustal rupture zone. The recordings, obtained on or near many important structures, provide an important new empirical data set for evaluating input ground motion levels and site amplification factors for codes and site-specific design procedures world wide. This report describes the data used to prepare a preliminary map summarizing the strong motion data in relation to seismicity and underlying geology (Wentworth, Borcherdt, and Mark., 1995; Figure 1, hereafter referred to as Figure 1/I). The map shows station locations, peak acceleration values, and generalized acceleration contours superimposed on pertinent seismicity and the geologic map of Japan. The map (Figure 1/I) indicates a zone of high acceleration with ground motions throughout the zone greater than 400 gal and locally greater than 800 gal. This zone encompasses the area of most intense damage mapped as JMA intensity level 7, which extends through Kobe City. The zone of most intense damage is parallel, but displaced slightly from the surface projection of the crustal rupture zone implied by aftershock locations. The zone is underlain by soft-soil deposits of Holocene age.

Spatial mapping of lead, arsenic, iron, and polycyclic aromatic hydrocarbon soil contamination in Sydney, Nova Scotia: community impact from the coke ovens and steel plant.

PubMed

Lambert, Timothy W; Boehmer, Jennifer; Feltham, Jason; Guyn, Lindsay; Shahid, Rizwan

2011-01-01

This paper presents spatial maps of the arsenic, lead, and polycyclic aromatic hydrocarbon (PAH) soil contamination in Sydney, Nova Scotia, Canada. The spatial maps were designed to create exposure cohorts to help understand the observed increase in health effects. To assess whether contamination can be a proxy for exposures, the following hypothesis was tested: residential soils were impacted by the coke oven and steel plant industrial complex. The spatial map showed contaminants are centered on the industrial facility, significantly correlated, and exceed Canadian health risk-based soil quality guidelines. Core samples taken at 5-cm intervals suggest a consistent deposition over time. The concentrations in Sydney significantly exceed background Sydney soil concentrations, and are significantly elevated compared with North Sydney, an adjacent industrial community. The contaminant spatial maps will also be useful for developing cohorts of exposure and guiding risk management decisions.

Spatial variability of soil carbon stock in the Urucu river basin, Central Amazon-Brazil.

PubMed

Ceddia, Marcos Bacis; Villela, André Luis Oliveira; Pinheiro, Érika Flávia Machado; Wendroth, Ole

2015-09-01

The Amazon Forest plays a major role in C sequestration and release. However, few regional estimates of soil organic carbon (SOC) stock in this ecoregion exist. One of the barriers to improve SOC estimates is the lack of recent soil data at high spatial resolution, which hampers the application of new methods for mapping SOC stock. The aims of this work were: (i) to quantify SOC stock under undisturbed vegetation for the 0-30 and the 0-100 cm under Amazon Forest; (ii) to correlate the SOC stock with soil mapping units and relief attributes and (iii) to evaluate three geostatistical techniques to generate maps of SOC stock (ordinary, isotopic and heterotopic cokriging). The study site is located in the Central region of Amazon State, Brazil. The soil survey covered the study site that has an area of 80 km(2) and resulted in a 1:10,000 soil map. It consisted of 315 field observations (96 complete soil profiles and 219 boreholes). SOC stock was calculated by summing C stocks by horizon, determined as a product of BD, SOC and the horizon thickness. For each one of the 315 soil observations, relief attributes were derived from a topographic map to understand SOC dynamics. The SOC stocks across 30 and 100 cm soil depth were 3.28 and 7.32 kg C m(-2), respectively, which is, 34 and 16%, lower than other studies. The SOC stock is higher in soils developed in relief forms exhibiting well-drained soils, which are covered by Upland Dense Tropical Rainforest. Only SOC stock in the upper 100 cm exhibited spatial dependence allowing the generation of spatial variability maps based on spatial (co)-regionalization. The CTI was inversely correlated with SOC stock and was the only auxiliary variable feasible to be used in cokriging interpolation. The heterotopic cokriging presented the best performance for mapping SOC stock. Copyright © 2015 Elsevier B.V. All rights reserved.

Covariate selection with iterative principal component analysis for predicting physical

USDA-ARS?s Scientific Manuscript database

Local and regional soil data can be improved by coupling new digital soil mapping techniques with high resolution remote sensing products to quantify both spatial and absolute variation of soil properties. The objective of this research was to advance data-driven digital soil mapping techniques for ...

Preliminary soil-slip susceptibility maps, southwestern California

USGS Publications Warehouse

Morton, Douglas M.; Alvarez, Rachel M.; Campbell, Russell H.; Digital preparation by Bovard, Kelly R.; Brown, D.T.; Corriea, K.M.; Lesser, J.N.

2003-01-01

This group of maps shows relative susceptibility of hill slopes to the initiation sites of rainfall-triggered soil slip-debris flows in southwestern California. As such, the maps offer a partial answer to one part of the three parts necessary to predict the soil-slip/debris-flow process. A complete prediction of the process would include assessments of “where”, “when”, and “how big”. These maps empirically show part of the “where” of prediction (i.e., relative susceptibility to sites of initiation of the soil slips) but do not attempt to show the extent of run out of the resultant debris flows. Some information pertinent to “when” the process might begin is developed. “When” is determined mostly by dynamic factors such as rainfall rate and duration, for which local variations are not amenable to long-term prediction. “When” information is not provided on the maps but is described later in this narrative. The prediction of “how big” is addressed indirectly by restricting the maps to a single type of landslide process—soil slip-debris flows. The susceptibility maps were created through an iterative process from two kinds of information. First, locations of sites of past soil slips were obtained from inventory maps of past events. Aerial photographs, taken during six rainy seasons that produced abundant soil slips, were used as the basis for soil slip-debris flow inventory. Second, digital elevation models (DEM) of the areas that were inventoried were used to analyze the spatial characteristics of soil slip locations. These data were supplemented by observations made on the ground. Certain physical attributes of the locations of the soil-slip debris flows were found to be important and others were not. The most important attribute was the mapped bedrock formation at the site of initiation of the soil slip. However, because the soil slips occur in surficial materials overlying the bedrocks units, the bedrock formation can only serve as a surrogate for the susceptibility of the overlying surficial materials. The maps of susceptibility were created from those physical attributes learned to be important from the inventories. The multiple inventories allow a model to be created from one set of inventory data and evaluated with others. The resultant maps of relative susceptibility represent the best estimate generated from available inventory and DEM data. Slope and aspect values used in the susceptibility analysis were 10-meter DEM cells at a scale of 1:24,000. For most of the area 10-meter DEMs were available; for those quadrangles that have only 30-meter DEMs, the 30-meter DEMS were resampled to 10-meters to maintain resolution of 10-meter cells. Geologic unit values used in the susceptibility analysis were five-meter cells. For convenience, the soil slip susceptibility values are assembled on 1:100,000-scale bases. Any area of the 1:100,000-scale maps can be transferred to 1:24,000-scale base without any loss of accuracy. Figure 32 is an example of part of a 1:100,000-scale susceptibility map transferred back to a 1:24,000-scale quadrangle.

Soils of Walker Branch Watershed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lietzke, D.A.

1994-01-01

The soil survey of Walker Branch Watershed (WBW) utilized the most up-to-date knowledge of soils, geology, and geohydrology in building the soils data base needed to reinterpret past research and to begin new research in the watershed. The soils of WBW were also compared with soils mapped elsewhere along Chestnut Ridge on the Oak Ridge Reservation to (1) establish whether knowledge obtained elsewhere could be used within the watershed, (2) determine whether there were any soils restricted to the watershed, and (3) evaluate geologic formation lateral variability. Soils, surficial geology, and geomorphology were mapped at a scale of 1:1200 usingmore » a paper base map having 2-ft contour intervals. Most of the contours seemed to reasonably represent actual landform configurations, except for dense wooded areas. For example, the very large dolines or sinkholes were shown on the contour base map, but numerous smaller ones were not. In addition, small drainageways and gullies were often not shown. These often small but important features were located approximately as soil mapping progressed. WBW is underlain by dolostones of the Knox Group, but only a very small part of the surface area contains outcroppings of rock and most outcrops were located in the lower part. Soil mapping revealed the presence of both ancient alluvium and ancient colluvium deposits, not recognized in previous soil surveys, that have been preserved in high-elevation stable portions of present-day landforms. An erosional geomorphic process of topographic inversion requiring several millions of years within the Pleistocene is necessary to bring about the degree of inversion that is expressed in the watershed. Indeed, some of these ancient alluvial and colluvial remnants may date back into the Tertiary. Also evident in the watershed, and preserved in the broad, nearly level bottoms of dolines, are multiple deposits of silty material either devoid or nearly devoid of coarse fragments. Recent research indicates that most of this silty material is the result of slope wash processed during the Holocene Age. Residual soils of the watershed were related to the underlying geologic formations by their morphology and types of chert. Colluvial soils were identified and mapped whenever the colluvium thickness exceeded 20 in. (50 cm). Except for the ancient colluvial soils (colluvium without a present-day source area), colluvial soils were not separated according to their geologic age, but stacked colluvial deposits are located in low footslope landforms. Colluvial soils in the watershed were identified and mapped according to their morphologic properties that would influence the perching and subsurface movement of water. Alluvial soils were restricted to present floodplains, low fan terraces, and low fan deltas. Nearly all alluvial soils contained very young surficial sediments derived from slopewash resulting from land clearing and subsequent agricultural activities.« less

Creating soil moisture maps based on radar satellite imagery

NASA Astrophysics Data System (ADS)

Hnatushenko, Volodymyr; Garkusha, Igor; Vasyliev, Volodymyr

2017-10-01

The presented work is related to a study of mapping soil moisture basing on radar data from Sentinel-1 and a test of adequacy of the models constructed on the basis of data obtained from alternative sources. Radar signals are reflected from the ground differently, depending on its properties. In radar images obtained, for example, in the C band of the electromagnetic spectrum, soils saturated with moisture usually appear in dark tones. Although, at first glance, the problem of constructing moisture maps basing on radar data seems intuitively clear, its implementation on the basis of the Sentinel-1 data on an industrial scale and in the public domain is not yet available. In the process of mapping, for verification of the results, measurements of soil moisture obtained from logs of the network of climate stations NOAA US Climate Reference Network (USCRN) were used. This network covers almost the entire territory of the United States. The passive microwave radiometers of Aqua and SMAP satellites data are used for comparing processing. In addition, other supplementary cartographic materials were used, such as maps of soil types and ready moisture maps. The paper presents a comparison of the effect of the use of certain methods of roughening the quality of radar data on the result of mapping moisture. Regression models were constructed showing dependence of backscatter coefficient values Sigma0 for calibrated radar data of different spatial resolution obtained at different times on soil moisture values. The obtained soil moisture maps of the territories of research, as well as the conceptual solutions about automation of operations of constructing such digital maps, are presented. The comparative assessment of the time required for processing a given set of radar scenes with the developed tools and with the ESA SNAP product was carried out.

Map showing landslide susceptibility in Prince Georges County, Maryland

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pomeroy, J.S.

1989-01-01

Prince Georges County was identified during a statewide investigation of landslide susceptibility (MF-2048) as the county with the most serious slope-stability problems. This map uses a ranking system ranging from 1 (nil to very low susceptibility) to 4 (moderate to severe susceptibility). Geologic factors and precipitation are major elements in the initiation of landslides in the county. The Potomac Group and the Marlboro Clay are the most slideprone units. This map should enable users to make a rapid, generalized evaluation of the potential for mass movement. Planners, engineers, soil scientists, geologist, university faculty, and elected officials should find it usefulmore » in the assessment of slope hazards for county-wide analyses.« less

The creation of digital thematic soil maps at the regional level (with the map of soil carbon pools in the Usa River basin as an example)

NASA Astrophysics Data System (ADS)

Pastukhov, A. V.; Kaverin, D. A.; Shchanov, V. M.

2016-09-01

A digital map of soil carbon pools was created for the forest-tundra ecotone in the Usa River basin with the use of ERDAS Imagine 2014 and ArcGIS 10.2 software. Supervised classification and thematic interpretation of satellite images and digital terrain models with the use of a georeferenced database on soil profiles were applied. Expert assessment of the natural diversity and representativeness of random samples for different soil groups was performed, and the minimal necessary size of the statistical sample was determined.

Mapping Soil Organic Carbon Resources Across Agricultural Land Uses in Highland Lesotho Using High Resolution Satellite Imagery

NASA Astrophysics Data System (ADS)

Knight, J.; Adam, E.

2015-12-01

Mapping spatial patterns of soil organic carbon (SOC) using high resolution satellite imagery is especially important in inaccessible or upland areas that have limited field measurements, where land use and land cover (LULC) are changing rapidly, or where the land surface is sensitive to overgrazing and high rates of soil erosion and thus sediment, nutrient and carbon export. Here we outline the methods and results of mapping soil organic carbon in highland areas (~2400 m) of eastern Lesotho, southern Africa, across different land uses. Bedrock summit areas with very thin soils are dominated by xeric alpine grassland; terrace agriculture with strip fields and thicker soils is found within river valleys. Multispectral Worldview 2 imagery was used to map LULC across the region. An overall accuracy of 88% and kappa value of 0.83 were achieved using a support vector machine model. Soils were examined in the field from different LULC areas for properties such as soil depth, maturity and structure. In situ soils in the field were also evaluated using a portable analytical spectral device (ASD) in order to ground truth spectral signatures from Worldview. Soil samples were examined in the lab for chemical properties including organic carbon. Regression modeling was used in order to establish a relationship between soil characteristics and soil spectral reflectance. We were thus able to map SOC across this diverse landscape. Results show that there are notable differences in SOC between upland and agricultural areas which reflect both soil thickness and maturity, and land use practices such as manuring of fields by cattle. Soil erosion and thus carbon (nutrient) export is significant issue in this region, which this project will now be examining.

Mapping soil features from multispectral scanner data

NASA Technical Reports Server (NTRS)

Kristof, S. J.; Zachary, A. L.

1974-01-01

In being able to identify quickly gross variations in soil features, the computer-aided classification of multispectral scanner data can be an effective aid to soil surveying. Variations in soil tone are easily seen as well as variations in features related to soil tone, e.g., drainage patterns and organic matter content. Changes in surface texture also affect the reflectance properties of soils. Inasmuch as conventional soil classes are based on both surface and subsurface soil characteristics, the technique described here can be expected only to augment and not replace traditional soil mapping.

GlobalSoilMap France: High-resolution spatial modelling the soils of France up to two meter depth.

PubMed

Mulder, V L; Lacoste, M; Richer-de-Forges, A C; Arrouays, D

2016-12-15

This work presents the first GlobalSoilMap (GSM) products for France. We developed an automatic procedure for mapping the primary soil properties (clay, silt, sand, coarse elements, pH, soil organic carbon (SOC), cation exchange capacity (CEC) and soil depth). The procedure employed a data-mining technique and a straightforward method for estimating the 90% confidence intervals (CIs). The most accurate models were obtained for pH, sand and silt. Next, CEC, clay and SOC were found reasonably accurate predicted. Coarse elements and soil depth were the least accurate of all models. Overall, all models were considered robust; important indicators for this were 1) the small difference in model diagnostics between the calibration and cross-validation set, 2) the unbiased mean predictions, 3) the smaller spatial structure of the prediction residuals in comparison to the observations and 4) the similar performance compared to other developed GlobalSoilMap products. Nevertheless, the confidence intervals (CIs) were rather wide for all soil properties. The median predictions became less reliable with increasing depth, as indicated by the increase of CIs with depth. In addition, model accuracy and the corresponding CIs varied depending on the soil variable of interest, soil depth and geographic location. These findings indicated that the CIs are as informative as the model diagnostics. In conclusion, the presented method resulted in reasonably accurate predictions for the majority of the soil properties. End users can employ the products for different purposes, as was demonstrated with some practical examples. The mapping routine is flexible for cloud-computing and provides ample opportunity to be further developed when desired by its users. This allows regional and international GSM partners with fewer resources to develop their own products or, otherwise, to improve the current routine and work together towards a robust high-resolution digital soil map of the world. Copyright © 2016 Elsevier B.V. All rights reserved.

Digital mapping of soil properties in Zala County, Hungary for the support of county-level spatial planning and land management

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Szatmári, Gábor; Fodor, Nándor; Bakacsi, Zsófia; Szabó, József; Illés, Gábor

2014-05-01

The main objective of the DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project is to significantly extend the potential, how demands on spatial soil related information could be satisfied in Hungary. Although a great amount of soil information is available due to former mappings and surveys, there are more and more frequently emerging discrepancies between the available and the expected data. The gaps are planned to be filled with optimized DSM products heavily based on legacy soil data, which still represent a valuable treasure of soil information at the present time. Impact assessment of the forecasted climate change and the analysis of the possibilities of the adaptation in the agriculture and forestry can be supported by scenario based land management modelling, whose results can be incorporated in spatial planning. This framework requires adequate, preferably timely and spatially detailed knowledge of the soil cover. For the satisfaction of these demands in Zala County (one of the nineteen counties of Hungary), the soil conditions of the agricultural areas were digitally mapped based on the most detailed, available recent and legacy soil data. The agri-environmental conditions were characterized according to the 1:10,000 scale genetic soil mapping methodology and the category system applied in the Hungarian soil-agricultural chemistry practice. The factors constraining the fertility of soils were featured according to the biophysical criteria system elaborated for the delimitation of naturally handicapped areas in the EU. Production related soil functions were regionalized incorporating agro-meteorological modelling. The appropriate derivatives of a 20m digital elevation model were used in the analysis. Multitemporal MODIS products were selected from the period of 2009-2011 representing different parts of the growing season and years with various climatic conditions. Additionally two climatic data layers, the 1:100.000 Geological Map of Hungary and the map of groundwater depth were used as auxiliary environmental covariables. Various soil related information were mapped in three distinct sets: (i) basic soil properties determining agri-environmental conditions (soil type according to the Hungarian genetic classification, rootable depth, sand and clay content for the 1st and 2nd soil layers, pH, OM and carbonate content for the plough layer); (ii) biophysical criteria of natural handicaps defined by common European system and (iii) agro-meteorologically modelled yield values for different crops, meteorological and management scenarios. The applied method(s) for the spatial inference of specific themes was/were suitably selected: regression and classification trees for categorical data, indicator kriging for probabilistic management of criterion information; and typically regression kriging for quantitative data. Our paper will present the mapping processes themselves, the resulted maps and some conclusions drawn from the experiences. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167) and by the European Union with the co-financing of the European Social Fund (TÁMOP-4.2.2.A-11/1/KONV-2012-0013.).

Estimating Surface Soil Moisture in Simulated AVIRIS Spectra

NASA Technical Reports Server (NTRS)

Whiting, Michael L.; Li, Lin; Ustin, Susan L.

2004-01-01

Soil albedo is influenced by many physical and chemical constituents, with moisture being the most influential on the spectra general shape and albedo (Stoner and Baumgardner, 1981). Without moisture, the intrinsic or matrix reflectance of dissimilar soils varies widely due to differences in surface roughness, particle and aggregate sizes, mineral types, including salts, and organic matter contents. The influence of moisture on soil reflectance can be isolated by comparing similar soils in a study of the effects that small differences in moisture content have on reflectance. However, without prior knowledge of the soil physical and chemical constituents within every pixel, it is nearly impossible to accurately attribute the reflectance variability in an image to moisture or to differences in the physical and chemical constituents in the soil. The effect of moisture on the spectra must be eliminated to use hyperspectral imagery for determining minerals and organic matter abundances of bare agricultural soils. Accurate soil mineral and organic matter abundance maps from air- and space-borne imagery can improve GIS models for precision farming prescription, and managing irrigation and salinity. Better models of soil moisture and reflectance will also improve the selection of soil endmembers for spectral mixture analysis.

Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models: the case study of Denmark.

PubMed

Bou Kheir, Rania; Greve, Mogens H; Bøcher, Peder K; Greve, Mette B; Larsen, René; McCloy, Keith

2010-05-01

Soil organic carbon (SOC) is one of the most important carbon stocks globally and has large potential to affect global climate. Distribution patterns of SOC in Denmark constitute a nation-wide baseline for studies on soil carbon changes (with respect to Kyoto protocol). This paper predicts and maps the geographic distribution of SOC across Denmark using remote sensing (RS), geographic information systems (GISs) and decision-tree modeling (un-pruned and pruned classification trees). Seventeen parameters, i.e. parent material, soil type, landscape type, elevation, slope gradient, slope aspect, mean curvature, plan curvature, profile curvature, flow accumulation, specific catchment area, tangent slope, tangent curvature, steady-state wetness index, Normalized Difference Vegetation Index (NDVI), Normalized Difference Wetness Index (NDWI) and Soil Color Index (SCI) were generated to statistically explain SOC field measurements in the area of interest (Denmark). A large number of tree-based classification models (588) were developed using (i) all of the parameters, (ii) all Digital Elevation Model (DEM) parameters only, (iii) the primary DEM parameters only, (iv), the remote sensing (RS) indices only, (v) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME) and the lowest number of nodes (N) as well are: (i) the tree (T1) combining all of the parameters (ME=29.5%; N=54); (ii) the tree (T2) based on the parent material, soil type and landscape type (ME=31.5%; N=14); and (iii) the tree (T3) constructed using parent material, soil type, landscape type, elevation, tangent slope and SCI (ME=30%; N=39). The produced SOC maps at 1:50,000 cartographic scale using these trees are highly matching with coincidence values equal to 90.5% (Map T1/Map T2), 95% (Map T1/Map T3) and 91% (Map T2/Map T3). The overall accuracies of these maps once compared with field observations were estimated to be 69.54% (Map T1), 68.87% (Map T2) and 69.41% (Map T3). The proposed tree models are relatively simple, and may be also applied to other areas. Copyright 2010 Elsevier Ltd. All rights reserved.

Taxonomic classification of world map units in crop producing areas of Argentina and Brazil with representative US soil series and major land resource areas in which they occur

NASA Technical Reports Server (NTRS)

Huckle, H. F. (Principal Investigator)

1980-01-01

The most probable current U.S. taxonomic classification of the soils estimated to dominate world soil map units (WSM)) in selected crop producing states of Argentina and Brazil are presented. Representative U.S. soil series the units are given. The map units occurring in each state are listed with areal extent and major U.S. land resource areas in which similar soils most probably occur. Soil series sampled in LARS Technical Report 111579 and major land resource areas in which they occur with corresponding similar WSM units at the taxonomic subgroup levels are given.

Geostatistics, remote sensing and precision farming.

PubMed

Mulla, D J

1997-01-01

Precision farming is possible today because of advances in farming technology, procedures for mapping and interpolating spatial patterns, and geographic information systems for overlaying and interpreting several soil, landscape and crop attributes. The key component of precision farming is the map showing spatial patterns in field characteristics. Obtaining information for this map is often achieved by soil sampling. This approach, however, can be cost-prohibitive for grain crops. Soil sampling strategies can be simplified by use of auxiliary data provided by satellite or aerial photo imagery. This paper describes geostatistical methods for estimating spatial patterns in soil organic matter, soil test phosphorus and wheat grain yield from a combination of Thematic Mapper imaging and soil sampling.

Soil resources and potential for agricultural development in Bahr El Jebel in southern Sudan, Jonglei Canal project area

NASA Technical Reports Server (NTRS)

Myers, V. I.; Moore, D. G.; Abdel-Hady, M. A.; Abdel-Samie, A. G.; Elshazly, E. M. (Principal Investigator); Youvis, H.; Worcester, B. K.; Klingebiel, A. A.; Elshazly, M. M.; Hamad, M. A.

1978-01-01

The author has identified the following significant results. Fourteen LANDSAT scenes were used to produce mosaics of the 167, 474 sq km study area. These were black and white MSS 7 images and false color composite images. Five major soil-landscape units were delineated on the mosaics, and these were subdivided into a total of 40 soil mapping units. Aerial reconnaissance was useful in defining boundaries between mapping units and in estimating the proportion of the various soils which composed each mapping unit. Ground surveying permitted first-hand observation of major soils and sampling for quantitative laboratory analysis. Soil interpretations were made, including properties, potentials, and limitations.

A Comparison of Satellite Data-Based Drought Indicators in Detecting the 2012 Drought in the Southeastern US

NASA Technical Reports Server (NTRS)

Yagci, Ali Levent; Santanello, Joseph A.; Rodell, Matthew; Deng, Meixia; Di, Liping

2018-01-01

The drought of 2012 in the North America devastated agricultural crops and pastures, further damaging agriculture and livestock industries and leading to great losses in the economy. The drought maps of the United States Drought Monitor (USDM) and various drought monitoring techniques based on the data collected by the satellites orbiting in space such as the Gravity Recovery and Climate Experiment (GRACE) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are inter-compared during the 2012 drought conditions in the southeastern United States. The results indicated that spatial extent of drought reported by USDM were in general agreement with those reported by the MODIS-based drought maps. GRACE-based drought maps suggested that the southeastern US experienced widespread decline in surface and root-zone soil moisture and groundwater resources. Disagreements among all drought indicators were observed over irrigated areas, especially in Lower Mississippi region where agriculture is mainly irrigated. Besides, we demonstrated that time lag of vegetation response to changes in soil moisture and groundwater partly contributed to these disagreements, as well.

Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys

PubMed Central

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield. PMID:27203697

Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys.

PubMed

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield.

Identifying environmental features for land management decisions

NASA Technical Reports Server (NTRS)

1983-01-01

Pairs of HCMM day-night thermal infrared (IR) data were selected to examine patterns of surface temperature and thermal inertia (TI) of peninsular Florida. GOES and NOAA-6 thermal IR, as well as National Climatic Center temperatures and rainfall, were also used. The HCMM apparent thermal inertia (ATI) images closely correspond to the General Soil Map of Florida, based on soil drainage classes. Areas with low ATI overlay well-drained soils, such as deep sands and drained organic soils. Areas with high ATI overlay areas with wetlands and bodies of water. The HCMM ATI images also correspond well with GOES-detected winter nocturnal cold-prone areas. Use of HCMM data with Carlson's energy balance model shows both high moisture availability (MA) and high thermal inertia (TI) of wetland-type surfaces and low MA and low TI of upland, well-drained soils. Since soil areas with low TI develop higher temperatures during the day, then antecedent patterns of highest maximum daytime surface temperature can also be used to predict nocturnal cold-prone areas in Florida.

Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area

NASA Astrophysics Data System (ADS)

Oh, Hyun-Joo; Pradhan, Biswajeet

2011-09-01

This paper presents landslide-susceptibility mapping using an adaptive neuro-fuzzy inference system (ANFIS) using a geographic information system (GIS) environment. In the first stage, landslide locations from the study area were identified by interpreting aerial photographs and supported by an extensive field survey. In the second stage, landslide-related conditioning factors such as altitude, slope angle, plan curvature, distance to drainage, distance to road, soil texture and stream power index (SPI) were extracted from the topographic and soil maps. Then, landslide-susceptible areas were analyzed by the ANFIS approach and mapped using landslide-conditioning factors. In particular, various membership functions (MFs) were applied for the landslide-susceptibility mapping and their results were compared with the field-verified landslide locations. Additionally, the receiver operating characteristics (ROC) curve for all landslide susceptibility maps were drawn and the areas under curve values were calculated. The ROC curve technique is based on the plotting of model sensitivity — true positive fraction values calculated for different threshold values, versus model specificity — true negative fraction values, on a graph. Landslide test locations that were not used during the ANFIS modeling purpose were used to validate the landslide susceptibility maps. The validation results revealed that the susceptibility maps constructed by the ANFIS predictive models using triangular, trapezoidal, generalized bell and polynomial MFs produced reasonable results (84.39%), which can be used for preliminary land-use planning. Finally, the authors concluded that ANFIS is a very useful and an effective tool in regional landslide susceptibility assessment.

Regional-scale Assessment of Soil Salinity in the Red River Valley Using Multi-year MODIS EVI

USDA-ARS?s Scientific Manuscript database

The ability to inventory and map soil salinity at regional scales remains a significant challenge to soil, environmental, and natural resource scientists. Previous attempts to use satellite or aerial imagery to assess and map soil salinity have resulted in limited success due, in part, to the inabi...

Hyper-temporal remote sensing for digital soil mapping: Characterizing soil-vegetation response to climatic variability

USDA-ARS?s Scientific Manuscript database

Indices derived from remotely-sensed imagery are commonly used to predict soil properties with digital soil mapping (DSM) techniques. The use of images from single dates or a small number of dates is most common for DSM; however, selection of the appropriate images is complicated by temporal variabi...

Mapping high-resolution soil moisture and properties using distributed temperature sensing data and an adaptive particle batch smoother

USDA-ARS?s Scientific Manuscript database

This study demonstrated a new method for mapping high-resolution (spatial: 1 m, and temporal: 1 h) soil moisture by assimilating distributed temperature sensing (DTS) observed soil temperatures at intermediate scales. In order to provide robust soil moisture and property estimates, we first proposed...

Evaluating Soil Health Using Remotely Sensed Evapotranspiration on the Benchmark Barnes Soils of North Dakota

NASA Astrophysics Data System (ADS)

Bohn, Meyer; Hopkins, David; Steele, Dean; Tuscherer, Sheldon

2017-04-01

The benchmark Barnes soil series is an extensive upland Hapludoll of the northern Great Plains that is both economically and ecologically vital to the region. Effects of tillage erosion coupled with wind and water erosion have degraded Barnes soil quality, but with unknown extent, distribution, or severity. Evidence of soil degradation documented for a half century warrants that the assumption of productivity be tested. Soil resilience is linked to several dynamic soil properties and National Cooperative Soil Survey initiatives are now focused on identifying those properties for benchmark soils. Quantification of soil degradation is dependent on a reliable method for broad-scale evaluation. The soil survey community is currently developing rapid and widespread soil property assessment technologies. Improvements in satellite based remote-sensing and image analysis software have stimulated the application of broad-scale resource assessment. Furthermore, these technologies have fostered refinement of land-based surface energy balance algorithms, i.e. Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) algorithm for evapotranspiration (ET) mapping. The hypothesis of this study is that ET mapping technology can differentiate soil function on extensive landscapes and identify degraded areas. A recent soil change study in eastern North Dakota resampled legacy Barnes pedons sampled prior to 1960 and found significant decreases in organic carbon. An ancillary study showed that evapotranspiration (ET) estimates from METRIC decreased with Barnes erosion class severity. An ET raster map has been developed for three eastern North Dakota counties using METRIC and Landsat 5 imagery. ET pixel candidates on major Barnes soil map units were stratified into tertiles and classified as ranked ET subdivisions. A sampling population of randomly selected points stratified by ET class and county proportion was established. Morphologic and chemical data will be recorded at each sampling site to test whether soil properties correlate to ET, thus serving as a non-biased proxy for soil health.

Passive microwave remote sensing of soil moisture - Results from HAPEX, FIFE and MONSOON 90

NASA Technical Reports Server (NTRS)

Schmugge, T.; Jackson, T. J.; Kustas, W. P.; Wang, J. R.

1992-01-01

HAPEX (Hydrologic Atmospheric Pilot Experiment), FIFE (First ISLSCP Field Experiment) and MONSOON 90 which used an imaging microwave radiometer operating at a frequency of 1.42 GHz are reported. For FIFE and MONSOON 90, a wide range of moisture conditions were present and it was possible to observe the drydown of the soil following heavy rain and to map its spatial variation. The quantitative agreement of microwave observations and ground measurements was very good. In HAPEX there were no significant rains and conditions were generally rather dry, however, moisture variations due to irrigation were observed.

Passive microwave remote sensing of soil moisture: Results from HAPEX, FIFE, and MONSOON 90

NASA Technical Reports Server (NTRS)

Schmugge, Thomas; Jackson, T. J.; Wang, J. R.

1991-01-01

HAPEX (Hydrologic Atmospheric Pilot Experiment), FIFE (First ISLSCP Field Experiment) and MONSOON 90 which used an imaging microwave radiometer operating at a frequency of 1.42 GHz are reported. For FIFE and MONSOON 90, a wide range of moisture conditions were present and it was possible to observe the drydown of the soil following heavy rain and to map its spatial variation. The quantitive agreement of microwave observations and ground measurements was very good. In HAPEX there were no significant rains and conditions were generally rather dry, however, moisture variations due to irrigation were observed.

Development of a national geodatabase (Greece) for soil surveys and land evaluation using space technology and GIS

NASA Astrophysics Data System (ADS)

Bilas, George; Dionysiou, Nina; Karapetsas, Nikolaos; Silleos, Nikolaos; Kosmas, Konstantinos; Misopollinos, Nikolaos

2016-04-01

This project was funded by OPEKEPE, Ministry of Agricultural Development and Food, Greece and involves development of a national geodatabase and a WebGIS that encompass soil data of all the agricultural areas of Greece in order to supply the country with a multi-purpose master plan for agricultural land management. The area mapped covered more than 385,000 ha divided in more than 9.000 Soil Mapping Units (SMUs) based on physiographic analysis, field work and photo interpretation of satellite images. The field work included description and sampling in three depths (0-30, 30-60 and >60 cm) of 2,000 soil profiles and 8,000 augers (sampling 0-30 and >30 cm). In total more than 22,000 soil samples were collected and analyzed for determining main soil properties associated with soil classification and soil evaluation. Additionally the project included (1) integration of all data in the Soil Geodatabase, (2) finalization of SMUs, (3) development of a Master Plan for Agricultural Land Management and (4) development and operational testing of the Web Portal for e-information and e-services. The integrated system is expected, after being fully operational, to provide important electronic services and benefits to farmers, private sector and governmental organizations. An e-book with the soil maps of Greece was also provided including 570 sheets with data description and legends. The Master Plan for Agricultural Land Management includes soil quality maps for 30 agricultural crops, together with maps showing soil degradation risks, such as erosion, desertification, salinity and nitrates, thus providing the tools for soil conservation and sustainable land management.

Multisensor on-the-go mapping of readily dispersible clay, particle size and soil organic matter

NASA Astrophysics Data System (ADS)

Debaene, Guillaume; Niedźwiecki, Jacek; Papierowska, Ewa

2016-04-01

Particle size fractions affect strongly the physical and chemical properties of soil. Readily dispersible clay (RDC) is the part of the clay fraction in soils that is easily or potentially dispersible in water when small amounts of mechanical energy are applied to soil. The amount of RDC in the soil is of significant importance for agriculture and environment because clay dispersion is a cause of poor soil stability in water which in turn contributes to soil erodibility, mud flows, and cementation. To obtain a detailed map of soil texture, many samples are needed. Moreover, RDC determination is time consuming. The use of a mobile visible and near-infrared (VIS-NIR) platform is proposed here to map those soil properties and obtain the first detailed map of RDC at field level. Soil properties prediction was based on calibration model developed with 10 representative samples selected by a fuzzy logic algorithm. Calibration samples were analysed for soil texture (clay, silt and sand), RDC and soil organic carbon (SOC) using conventional wet chemistry analysis. Moreover, the Veris mobile sensor platform is also collecting electrical conductivity (EC) data (deep and shallow), and soil temperature. These auxiliary data were combined with VIS-NIR measurement (data fusion) to improve prediction results. EC maps were also produced to help understanding RDC data. The resulting maps were visually compared with an orthophotography of the field taken at the beginning of the plant growing season. Models were developed with partial least square regression (PLSR) and support vector machine regression (SVMR). There were no significant differences between calibration using PLSR or SVMR. Nevertheless, the best models were obtained with PLSR and standard normal variate (SNV) pretreatment and the fusion with deep EC data (e.g. for RDC and clay content: RMSECV = 0,35% and R2 = 0,71; RMSECV = 0,32% and R2 = 0,73 respectively). The best models were used to predict soil properties from the field spectra collected with the VIS-NIR platform. Maps of soil properties were generated using natural neighbour (NN) interpolation. Calibration results were satisfactory for all soil properties and allowed for the generation of detailed maps. The spatial variability of RDC was in accordance with the field orthophotography. Areas of high RDC content were corresponding to area of bad plant development. Soil texture has been correctly predicted by VIS-NIR spectroscopy (laboratory or on-the-go) before. However, readily dispersible clay (an important parameter for soil stability) has never been investigated before. This study introduces the possibility of using VIS-NIR for predicting readily dispersible clay at field level. The results obtained could be used in preventing soil erosion. Acknowledgement: This research was financed by a National Science Centre grant (NCN - Poland) with decision number UMO-2012/07/B/ST10/04387

Mapping fire effects on ash and soil properties. Current knowledge and future perspectives.

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Cerda, Artemi; Strielko, Irina

2014-05-01

Fire has heterogeneous impacts on ash and soil properties, depending on severity, topography of the burned area, type of soil and vegetation affected, and meteorological conditions during and post-fire. The heterogeneous impacts of fire and the complex topography of wildland environments impose the challenge of understand fire effects at diverse scales in space and time. Mapping is fundamental to identify the impacts of fire on ash and soil properties because allow us to recognize the degree of the fire impact, vulnerable areas, soil protection and distribution of ash and soil nutrients, important to landscape recuperation. Several methodologies have been used to map fire impacts on ash soil properties. Burn severity maps are very useful to understand the immediate and long-term impacts of fire on the ecosystems (Wagtendonk et al., 2004; Kokaly et al., 2007). These studies normally are carried out with remote sensing techniques and study large burned areas. On a large scale it is very important to detect the most vulnerable areas (e.g. with risk of runoff increase, flooding, erosion, sedimentation and debris flow) and propose -if necessary- immediate rehabilitation measures. Post-fire rehabilitation measures can be extremely costly. Thus the identification of the most affected areas will reduce the erosion risks and soil degradation (Miller and Yool, 2002; Robichaud et al., 2007; Robichaud, 2009), as the consequent economical, social and ecological impacts. Recently, the United States Department of Agriculture created a field guide to map post-fire burn severity, based on remote sensing and Geographical Information Systems (GIS) technologies. The map produced should reflect the effects of fire on soil properties, and identify areas where fire was more severe (Parsons et al. 2010). Remote sensing studies have made attempts to estimate soil and ash properties after the fire, as hydrophobicity (Lewis et al., 2008), water infiltration (Finnley and Glenn, 2010), forest floor consumption (Lewis et al., 2011), ash cover (Robichaud et al., 2007) and other aspects related with soil as the vegetation factors that affect post-fire erosion risk (Fox et al., 2008). Field studies had also indented to estimate and map the impacts of fire in soil properties. Contrary to remote sensing studies, the mapping of fire effects on ash and soil properties in the field is specially carried out at small scale (e.g. slope or plot). The small scale resolution studies are important because identify small patterns that are normally ignored by remote sensing studies, but fundamental to understand the post-fire evolution of the burned areas. One of the important aspects of the small scale studies of fire effect on ash and soil properties is the great spatial variability, showing that the impact of fire is extremely heterogeneous in space and time (Outeiro et al., 2008; Pereira et al. in press). The small scale mapping of fire effects on soil properties normally is carried out using Geostatistical methods or using deterministic interpolation methods (Robichaud and Miller, 1999; Pereira et al., 2013). Several reports were published on the spatial distribution and mapping of ash and duff thickness (Robichaud and Miller, 1999; Pereira et al., 2013; Pereira et al. in press), fire severity (Pereira et al., 2014), ash chemical characteristics as total nitrogen (Pereira et al., 2010a), and ash extractable elements (Pereira et al., 2010b). Also, previous works mapped fire effects on soil temperature (Gimeno-Garcia et al., 2004), soil hydrophobicity (Woods et al., 2007), total nitrogen (Hirobe et al., 2003), phosphorous (Rodriguez et al., 2009) and major cations (Outeiro et al., 2008). It is important to integrate remote sensing and field based works of fire effects on ash and soil properties in order to have a better validation of the models predicted. The aim of this work is present the current knowledge about mapping fire effects in ash and soil properties at diverse scales and the future perspectives. References Finley, C.D., Glenn, N.F. (2010) Fire and vegetation type effects on soil hydrophobicity and infiltration in the sagebrussh-steppe: II. Hyperspectral analysis. Journal of Arid Environments, 74: 660-666. Fox, D.A., Maselli, F., Carrega, P. (2008) Using SPOT images and field sampling to map burn severity and vegetation factors affecting post-fire erosion risk. Catena, 75: 326-335. Gimeno-Garcia. E., Andreu., V., Rubio, J.L. (2004) Spatial patterns of soil temperatures during experiemntal fires. Geoderma, 118: 17-34. Hirobe, M., Tokushi, N., Wachrinrat, C., Takeda, H. (2003) Fire history influences on the spatial heterogeneity of soil nitrogen transformations in three adjacent stands in a dry tropical forest in Thailand. Plant and Soil, 249: 309-318. Kokaly, R.F., Rockwell, B.W., Haire, S.L., King, T.V.V. (2007) Characterization of post fire surface cover, soils, and burn severity at the Cerro Grande fire, New Mexico, using hyperspectral and multispectral remote sensing. Remote Sensing of the Environment, 106: 305-325. Lewis, S.A., Hudak, A.T., Ottmar, R.D., Robichaud, P.R., Lentile, L.B., Hood, S.M., Cronan, J.B., Morgan, P. (2012) Using hyperspectral imagery to estimate forest floor consumption from wildfire in boreal forests of Alaska. International Journal of Wildland Fire, 20: 255-271. Lewis, S.A., Robichaud, P.R., Frazier, B.E., Wu, J.Q., Laes, D.Y.M. (2008) Using hyperspectral imagery to predict post-wildfire soil repellency. Geomorphology, 98, 192-205. Miller, J.D., Yool, S. (2002) Mapping forest post-fire canopy consumption in several overstory types using multi-temporal Landsat TM and ETM data. Remote Sensing of the Environment, 82: 481-496. Outeiro, L., Aspero, F., Ubeda, X. (2008) Geostatistical methods to study spatial variability of soil cation after a prescribed fire and rainfall. Catena, 74: 310-320. Parsons, A., Robichaud, P.R., Lewis, S.A., Napper, C., Clark, J.T. (2010) Field guide for mapping post-fire soil burn severity. Gen. Tech. Rep. RMRS-GTR-243. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 49 p. Pereira, P. Úbeda X., Martin D A (2010b) Mapping wildfire effects on Ca2+ and Mg2+ released from ash. A microplot analysis, EGU General Assembly 2010, Geophysical Research Abstracts, 12,EGU 2010 - 30 Vienna. ISSN: 1607-7962. Pereira, P., Cerdà, A., Úbeda, X., Mataix-Solera, J. Arcenegui, V., Zavala, L. Modelling the impacts of wildfire on ash thickness in a short-term period, Land Degradation and Development, (In Press), DOI: 10.1002/ldr.2195 Pereira, P., Cerdà, A., Úbeda, X., Mataix-Solera, J., Jordan, A. Burguet, M. (2013) Spatial models for monitoring the spatio-temporal evolution of ashes after fire - a case study of a burnt grassland in Lithuania, Solid Earth, 4: 153-165. Pereira, P., Úbeda, X., Baltrenaite, E. (2010a) Mapping Total Nitrogen in ash after a Wildfire, a microplot analysis, Ekologija, 56 (3-4), 144-152. Pereira, P., Cerda, A., Ubeda, X., Mataix-Solera, J., Martin, D.A., Jordan, A., Martin, D.A., Mierauskas, P., Arcenegui, V., Zavala, L. (2014) Do fire severity effects change with the time?, What ash tell us, Flamma, 5: 23-27. Robichaud, P.R. (2009) Post-fire stabilization and rehabilitation. In: Cerda, A., Robichaud, P. (eds) Fire Effects on Soils and Restoration Strategies, Science Publishers, 299-320. Robichaud, P.R., Lewis, S.A., Laes, D.Y.M., Hudak, A.T., Kokaly, R.F., Zamudio, J.Z. (2007) Post-fire burn severity mapping with hyperspectral image unmixing. Remote Sensing of the Environment, 108: 467-480. Robichaud, P.R., Miller, S.M. (1999) Spatial interpolation and simulation of post-burn duff thickness after prescribed fire. International Journal of Wildland Fire, 9: 137-143. Rodriguez, A., Duran, J., Fernandez-Palacios, J.M., Gallardo, A. (2009) Short-term wildfire effects on the spatial pattern and scale of labile organic-N and inorganic-N and P pools. Forest Ecology and Management, 257: 739-746. Wagtendonk, J.W., Root, R.R., Key, C.H. (2004) Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity. Remote Sensing of the Environment, 92: 397-408. Woods, S.W., Birkas, A., Ahl, R. (2007) Spatial variability of soil hydrophobicity after wildfires in Montana and Colorado. Geomorphology, 86: 465-479.

Nickel, Cobalt, Chromium and Copper in agricultural and grazing land soils of Europe

NASA Astrophysics Data System (ADS)

Albanese, Stefano; Sadeghi, Martiya; De Vivo, Benedetto; Lima, Annamaria; Cicchella, Domenico; Dinelli, Enrico

2014-05-01

In the framework of the GEMAS (Geochemical Mapping of Agricultural and Grazing Land Soils) project, concentrations of Ni, Co, Cu and Cr were determined for the whole available dataset (2218 samples of agricultural soil and 2127 samples of grazing land soil) covering a total area of 5.6 million sq km all over Europe. The distribution pattern of Ni in the European soils (both agricultural and grazing land soils) shows the highest concentrations in correspondence with the Mediterranean area (especially in Greece, the Balcan Peninsula and NW Italy) with average values generally ranging between 40 mg/kg and 140 mg/kg and anomalous areas characterized by peaks higher than 2400 mg/kg. Concentrations between 10 mg/kg and 40 mg/kg characterize Continental Europe north of Alps and, partly, the Scandinavian countries. Lower concentrations (< 10 mg/kg) occurs near the Trans-European Suture Zone, one of the main tectonic borders in Europe, and they are limited on the south by the maximum extent limit of the last glaciation. Cobalt and Cr show distribution patterns similar to Ni in both agricultural and grazing land soils. The maximum concentration peaks of Cobalt and Cr rise up to respectively 126 mg/kg and 696 mg/kg in agricultural soils and up to 255 mg/kg and 577 mg/kg in grazing land soils. Copper distribution in the soils collected across Europe, although has a general correspondence with the patterns of Ni, Co, Cr, shows some peculiarities. Specifically, Cu is characterized by high concentration values (up to 395 mg/kg in agricultural soils and 373 mg/kg in Grazing land soils) also in correspondence with the Roman Comagmatic Province and the south western coast of France characterized by a wide spread of vineyards.

The soil-water system as basis for a climate proof and healthy urban environment: opportunities identified in a Dutch case-study.

PubMed

Claessens, Jacqueline; Schram-Bijkerk, Dieneke; Dirven-van Breemen, Liesbet; Otte, Piet; van Wijnen, Harm

2014-07-01

One of the effects of climate change expected to take place in urban areas in the Netherlands is an increase in periods of extreme heat and drought. How the soil can contribute to making cities more climate proof is often neglected. Unsealed soil and green spaces increase water storage capacity and can consequently prevent flooding. The planning of public or private green spaces can have a cooling effect and, in general, have a positive effect on how people perceive their health. This paper reviews existing guidelines from Dutch policy documents regarding unsealed soil and green spaces in the Netherlands; do they support climate adaptation policies? Scientific literature was used to quantify the positive effects of green spaces on water storage capacity, cooling and public health. Finally we present a case study of a model town where different policy areas are linked together. Maps were made to provide insight into the ratio of unsealed soil and the number of green spaces in relation to existing guidelines using Geographical Information Systems (GIS). Maps marking the age and social-economic status of the population were also made. The benefits of green spaces are difficult to express in averages because they depend on many different factors such as soil properties, type of green spaces, population characteristics and spatial planning. Moreover, it is not possible to provide quantifications of the benefits of green spaces because of a lack of scientific evidence at the moment. Based on the maps, however, policy assessments can be made, for example, in which site a neighborhood will most benefit from investment in parks and public gardens. Neighborhoods where people have a low social-economic status have for example fewer green spaces than others. This offers opportunities for efficient adaptation policies linking goals of several policy fields. Copyright © 2014 Elsevier B.V. All rights reserved.

Mercury Slovenian soils: High, medium and low sample density geochemical maps

NASA Astrophysics Data System (ADS)

Gosar, Mateja; Šajn, Robert; Teršič, Tamara

2017-04-01

Regional geochemical survey was conducted in whole territory of Slovenia (20273 km2). High, medium and low sample density surveys were compared. High sample density represented the regional geochemical data set supplemented by local high-density sampling data (irregular grid, n=2835). Medium-density soil sampling was performed in a 5 x 5 km grid (n=817) and low-density geochemical survey was conducted in a sampling grid 25 x 25 km (n=54). Mercury distribution in Slovenian soils was determined with models of mercury distribution in soil using all three data sets. A distinct Hg anomaly in western part of Slovenia is evident on all three models. It is a consequence of 500-years of mining and ore processing in the second largest mercury mine in the world, the Idrija mine. The determined mercury concentrations revealed an important difference between the western and the eastern parts of the country. For the medium scale geochemical mapping is the median value (0.151 mg /kg) for western Slovenia almost 2-fold higher than the median value (0.083 mg/kg) in eastern Slovenia. Besides the Hg median for the western part of Slovenia exceeds the Hg median for European soil by a factor of 4 (Gosar et al., 2016). Comparing these sample density surveys, it was shown that high sampling density allows the identification and characterization of anthropogenic influences on a local scale, while medium- and low-density sampling reveal general trends in the mercury spatial distribution, but are not appropriate for identifying local contamination in industrial regions and urban areas. The resolution of the pattern generated is the best when the high-density survey on a regional scale is supplemented with the geochemical data of the high-density surveys on a local scale. References: Gosar, M, Šajn, R, Teršič, T. Distribution pattern of mercury in the Slovenian soil: geochemical mapping based on multiple geochemical datasets. Journal of geochemical exploration, 2016, 167/38-48.

Hydrogeomorphic Classification of Wetlands on Mt. Desert Island, Maine, Including Hydrologic Susceptibility Factors for Wetlands in Acadia National Park

USGS Publications Warehouse

Nielsen, Martha G.

2006-01-01

The U.S. Geological Survey, in cooperation with the National Park Service, developed a hydrogeomorphic (HGM) classification system for wetlands greater than 0.4 hectares (ha) on Mt. Desert Island, Maine, and applied this classification using map-scale data to more than 1,200 mapped wetland units on the island. In addition, two hydrologic susceptibility factors were defined for a subset of these wetlands, using 11 variables derived from landscape-scale characteristics of the catchment areas of these wetlands. The hydrologic susceptibility factors, one related to the potential hydrologic pathways for contaminants and the other to the susceptibility of wetlands to disruptions in water supply from projected future changes in climate, were used to indicate which wetlands (greater than 1 ha) in Acadia National Park (ANP) may warrant further investigation or monitoring. The HGM classification system consists of 13 categories: Riverine-Upper Perennial, Riverine-Nonperennial, Riverine- Tidal, Depressional-Closed, Depressional-Semiclosed, Depressional-Open, Depressional-No Ground-Water Input, Mineral Soil Flat, Organic Soil Flat, Tidal Fringe, Lacustrine Fringe, Slope, and Hilltop/Upper Hillslope. A dichotomous key was developed to aid in the classification of wetlands. The National Wetland Inventory maps produced by the U.S. Fish and Wildlife Service provided the wetland mapping units used for this classification. On the basis of topographic map information and geographic information system (GIS) layers at a scale of 1:24,000 or larger, 1,202 wetland units were assigned a preliminary HGM classification. Two of the 13 HGM classes (Riverine-Tidal and Depressional-No Ground-Water Input) were not assigned to any wetlands because criteria for determining those classes are not available at that map scale, and must be determined by more site-specific information. Of the 1,202 wetland polygons classified, which cover 1,830 ha in ANP, 327 were classified as Slope, 258 were Depressional (Open, Semiclosed, and Closed), 231 were Riverine (Upper Perennial and Nonperennial), 210 were Soil Flat (Mineral and Organic), 68 were Lacustrine Fringe, 51 were Tidal Fringe, 22 were Hilltop/Upper Hillslope, and another 35 were small open water bodies. Most small, isolated wetlands classified on the island are Slope wetlands. The least common, Hilltop/Upper Hillslope wetlands, only occur on a few hilltops and shoulders of hills and mountains. Large wetland complexes generally consist of groups of Depressional wetlands and Mineral Soil Flat or Organic Soil Flat wetlands, often with fringing Slope wetlands at their edges and Riverine wetlands near streams flowing through them. The two analyses of wetland hydrologic susceptibility on Mt. Desert Island were applied to 186 wetlands located partially or entirely within ANP. These analyses were conducted using individually mapped catchments for each wetland. The 186 wetlands were aggregated from the original 1,202 mapped wetland polygons on the basis of their HGM classes. Landscape-level hydrologic, geomorphic, and soil variables were defined for the catchments of the wetlands, and transformed into scaled scores from 0 to 10 for each variable. The variables included area of the wetland, area of the catchment, area of the wetland divided by the area of the catchment, the average topographic slope of the catchment, the amount of the catchment where bedrock crops out with no soil cover or excessively thin soil cover, the amount of storage (in lakes and wetlands) in the catchment, the topographic relief of the catchment, the amount of clay-rich soil in the catchment, the amount of manmade impervious surface, whether the wetland had a stream inflow, and whether the wetland had a hydraulic connection to a lake or estuary. These data were determined using a GIS and data layers mapped at a scale of 1:24,000 or larger. These landscape variables were combined in different ways for the two hydrologic susceptibility fact

A Comparative Assessment of the Influences of Human Impacts on Soil Cd Concentrations Based on Stepwise Linear Regression, Classification and Regression Tree, and Random Forest Models

PubMed Central

Qiu, Lefeng; Wang, Kai; Long, Wenli; Wang, Ke; Hu, Wei; Amable, Gabriel S.

2016-01-01

Soil cadmium (Cd) contamination has attracted a great deal of attention because of its detrimental effects on animals and humans. This study aimed to develop and compare the performances of stepwise linear regression (SLR), classification and regression tree (CART) and random forest (RF) models in the prediction and mapping of the spatial distribution of soil Cd and to identify likely sources of Cd accumulation in Fuyang County, eastern China. Soil Cd data from 276 topsoil (0–20 cm) samples were collected and randomly divided into calibration (222 samples) and validation datasets (54 samples). Auxiliary data, including detailed land use information, soil organic matter, soil pH, and topographic data, were incorporated into the models to simulate the soil Cd concentrations and further identify the main factors influencing soil Cd variation. The predictive models for soil Cd concentration exhibited acceptable overall accuracies (72.22% for SLR, 70.37% for CART, and 75.93% for RF). The SLR model exhibited the largest predicted deviation, with a mean error (ME) of 0.074 mg/kg, a mean absolute error (MAE) of 0.160 mg/kg, and a root mean squared error (RMSE) of 0.274 mg/kg, and the RF model produced the results closest to the observed values, with an ME of 0.002 mg/kg, an MAE of 0.132 mg/kg, and an RMSE of 0.198 mg/kg. The RF model also exhibited the greatest R2 value (0.772). The CART model predictions closely followed, with ME, MAE, RMSE, and R2 values of 0.013 mg/kg, 0.154 mg/kg, 0.230 mg/kg and 0.644, respectively. The three prediction maps generally exhibited similar and realistic spatial patterns of soil Cd contamination. The heavily Cd-affected areas were primarily located in the alluvial valley plain of the Fuchun River and its tributaries because of the dramatic industrialization and urbanization processes that have occurred there. The most important variable for explaining high levels of soil Cd accumulation was the presence of metal smelting industries. The good performance of the RF model was attributable to its ability to handle the non-linear and hierarchical relationships between soil Cd and environmental variables. These results confirm that the RF approach is promising for the prediction and spatial distribution mapping of soil Cd at the regional scale. PMID:26964095

A Comparative Assessment of the Influences of Human Impacts on Soil Cd Concentrations Based on Stepwise Linear Regression, Classification and Regression Tree, and Random Forest Models.

PubMed

Qiu, Lefeng; Wang, Kai; Long, Wenli; Wang, Ke; Hu, Wei; Amable, Gabriel S

2016-01-01

Soil cadmium (Cd) contamination has attracted a great deal of attention because of its detrimental effects on animals and humans. This study aimed to develop and compare the performances of stepwise linear regression (SLR), classification and regression tree (CART) and random forest (RF) models in the prediction and mapping of the spatial distribution of soil Cd and to identify likely sources of Cd accumulation in Fuyang County, eastern China. Soil Cd data from 276 topsoil (0-20 cm) samples were collected and randomly divided into calibration (222 samples) and validation datasets (54 samples). Auxiliary data, including detailed land use information, soil organic matter, soil pH, and topographic data, were incorporated into the models to simulate the soil Cd concentrations and further identify the main factors influencing soil Cd variation. The predictive models for soil Cd concentration exhibited acceptable overall accuracies (72.22% for SLR, 70.37% for CART, and 75.93% for RF). The SLR model exhibited the largest predicted deviation, with a mean error (ME) of 0.074 mg/kg, a mean absolute error (MAE) of 0.160 mg/kg, and a root mean squared error (RMSE) of 0.274 mg/kg, and the RF model produced the results closest to the observed values, with an ME of 0.002 mg/kg, an MAE of 0.132 mg/kg, and an RMSE of 0.198 mg/kg. The RF model also exhibited the greatest R2 value (0.772). The CART model predictions closely followed, with ME, MAE, RMSE, and R2 values of 0.013 mg/kg, 0.154 mg/kg, 0.230 mg/kg and 0.644, respectively. The three prediction maps generally exhibited similar and realistic spatial patterns of soil Cd contamination. The heavily Cd-affected areas were primarily located in the alluvial valley plain of the Fuchun River and its tributaries because of the dramatic industrialization and urbanization processes that have occurred there. The most important variable for explaining high levels of soil Cd accumulation was the presence of metal smelting industries. The good performance of the RF model was attributable to its ability to handle the non-linear and hierarchical relationships between soil Cd and environmental variables. These results confirm that the RF approach is promising for the prediction and spatial distribution mapping of soil Cd at the regional scale.

Preduction of Vehicle Mobility on Large-Scale Soft-Soil Terrain Maps Using Physics-Based Simulation

DTIC Science & Technology

2016-08-02

PREDICTION OF VEHICLE MOBILITY ON LARGE-SCALE SOFT- SOIL TERRAIN MAPS USING PHYSICS-BASED SIMULATION Tamer M. Wasfy, Paramsothy Jayakumar, Dave...NRMM • Objectives • Soft Soils • Review of Physics-Based Soil Models • MBD/DEM Modeling Formulation – Joint & Contact Constraints – DEM Cohesive... Soil Model • Cone Penetrometer Experiment • Vehicle- Soil Model • Vehicle Mobility DOE Procedure • Simulation Results • Concluding Remarks 2UNCLASSIFIED

Modelling and mapping the topsoil organic carbon content for Tanzania

NASA Astrophysics Data System (ADS)

Kempen, Bas; Kaaya, Abel; Ngonyani Mhaiki, Consolatha; Kiluvia, Shani; Ruiperez-Gonzalez, Maria; Batjes, Niels; Dalsgaard, Soren

2014-05-01

Soil organic carbon (SOC), held in soil organic matter, is a key indicator of soil health and plays an important role in the global carbon cycle. The soil can act as a net source or sink of carbon depending on land use and management. Deforestation and forest degradation lead to the release of vast amounts of carbon from the soil in the form of greenhouse gasses, especially in tropical countries. Tanzania has a high deforestation rate: it is estimated that the country loses 1.1% of its total forested area annually. During 2010-2013 Tanzania has been a pilot country under the UN-REDD programme. This programme has supported Tanzania in its initial efforts towards reducing greenhouse gas emission from forest degradation and deforestation and towards preserving soil carbon stocks. Formulation and implementation of the national REDD strategy requires detailed information on the five carbon pools among these the SOC pool. The spatial distribution of SOC contents and stocks was not available for Tanzania. The initial aim of this research, was therefore to develop high-resolution maps of the SOC content for the country. The mapping exercise was carried out in a collaborative effort with four Tanzanian institutes and data from the Africa Soil Information Service initiative (AfSIS). The mapping exercise was provided with over 3200 field observations on SOC from four sources; this is the most comprehensive soil dataset collected in Tanzania so far. The main source of soil samples was the National Forest Monitoring and Assessment (NAFORMA). The carbon maps were generated by means of digital soil mapping using regression-kriging. Maps at 250 m spatial resolution were developed for four depth layers: 0-10 cm, 10-20 cm, 20-30 cm, and 0-30 cm. A total of 37 environmental GIS data layers were prepared for use as covariates in the regression model. These included vegetation indices, terrain parameters, surface temperature, spectral reflectances, a land cover map and a small-scale Soil and Terrain (SOTER) map. Prediction uncertainty was quantified by the 90% prediction interval and the predictions were validated by cross-validation. The SOTER map proved to be the best predictor of SOC content, followed by the terrain parameters, mid-infrared reflectance, surface temperature, several vegetation indices, and the land cover map. The maps show that the SOC content decreases with depth, which is typically observed in soils. For the 0-10 cm layer the average predicted SOC content is 1.31%, for the 10-20 cm layer this is 0.93%, for the 20-30cm layer 0.72%, and for the 0-30cm layer 1.00%. The mean absolute error of the 0-10cm layer was 0.54%, that of the 10-20cm layer 0.38%, that of the 20-30cm layer 0.31%, and that of the 0-30cm layer 0.34%. The R2-value of the 0-10 cm layer was 0.47, that of the 10-20cm layer 0.49, that of the 20-30cm layer 0.44, and that of the 0-30cm layer 0.59. The next step will be the development of maps of SOC stock and key properties that are of interest for soil fertility management such as pH and the textural fractions.

Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

NASA Astrophysics Data System (ADS)

DY, C. Y.; Fung, J. C. H.

2016-08-01

A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.

Soil and plant contamination with Mycobacterium avium subsp. paratuberculosis after exposure to naturally contaminated mouflon feces.

PubMed

Pribylova, Radka; Slana, Iva; Kaevska, Marija; Lamka, Jiri; Babak, Vladimir; Jandak, Jiri; Pavlik, Ivo

2011-05-01

The aim of this study was to demonstrate the persistence of Mycobacterium avium subsp. paratuberculosis (MAP) in soil and colonization of different plant parts after deliberate exposure to mouflon feces naturally contaminated with different amounts of MAP. Samples of aerial parts of plants, their roots, and the soil below the roots were collected after 15 weeks and examined using IS900 real-time quantitative PCR (qPCR) and cultivation. Although the presence of viable MAP cells was not demonstrated, almost all samples were found to be positive using qPCR. MAP IS900 was not only found in the upper green parts, but also in the roots and soil samples (from 1.00 × 10(0) to 6.43 × 10(3)). The level of soil and plant contamination was influenced mainly by moisture, clay content, and the depth from which the samples were collected, rather than by the initial concentration of MAP in the feces at the beginning of the experiment.

Vegetation types on acid soils of Micronesia

Treesearch

Marjorie C. Falanruw; Thomas G.. Cole; Craig D. Whitesell

1987-01-01

The soils and vegetation of the Caroline high islands, Federated States of Micronesia, are being mapped by the U.S. Department of Agriculture's Forest Service and Soil Conservation Service. By the end of 1987, vegetation maps and reports on Kosrae, Pohnpei, Yap, four Truk Islands, and Palau are expected to be available. To compare soil types with vegetation types...

Mapping of hydropedologic spatial patterns in a steep headwater catchment

Treesearch

Cody P. Gillin; Scott W. Bailey; Kevin J. McGuire; John P. Gannon

2015-01-01

A hydropedologic approach can be used to describe soil units affected by distinct hydrologic regimes. We used field observations of soil morphology and geospatial information technology to map the distribution of five hydropedologic soil units across a 42-ha forested headwater catchment. Soils were described and characterized at 172 locations within Watershed 3, the...

Matching soil grid unit resolutions with polygon unit scales for DNDC modelling of regional SOC pool

NASA Astrophysics Data System (ADS)

Zhang, H. D.; Yu, D. S.; Ni, Y. L.; Zhang, L. M.; Shi, X. Z.

2015-03-01

Matching soil grid unit resolution with polygon unit map scale is important to minimize uncertainty of regional soil organic carbon (SOC) pool simulation as their strong influences on the uncertainty. A series of soil grid units at varying cell sizes were derived from soil polygon units at the six map scales of 1:50 000 (C5), 1:200 000 (D2), 1:500 000 (P5), 1:1 000 000 (N1), 1:4 000 000 (N4) and 1:14 000 000 (N14), respectively, in the Tai lake region of China. Both format soil units were used for regional SOC pool simulation with DeNitrification-DeComposition (DNDC) process-based model, which runs span the time period 1982 to 2000 at the six map scales, respectively. Four indices, soil type number (STN) and area (AREA), average SOC density (ASOCD) and total SOC stocks (SOCS) of surface paddy soils simulated with the DNDC, were attributed from all these soil polygon and grid units, respectively. Subjecting to the four index values (IV) from the parent polygon units, the variation of an index value (VIV, %) from the grid units was used to assess its dataset accuracy and redundancy, which reflects uncertainty in the simulation of SOC. Optimal soil grid unit resolutions were generated and suggested for the DNDC simulation of regional SOC pool, matching with soil polygon units map scales, respectively. With the optimal raster resolution the soil grid units dataset can hold the same accuracy as its parent polygon units dataset without any redundancy, when VIV < 1% of all the four indices was assumed as criteria to the assessment. An quadratic curve regression model y = -8.0 × 10-6x2 + 0.228x + 0.211 (R2 = 0.9994, p < 0.05) was revealed, which describes the relationship between optimal soil grid unit resolution (y, km) and soil polygon unit map scale (1:x). The knowledge may serve for grid partitioning of regions focused on the investigation and simulation of SOC pool dynamics at certain map scale.

Integration of remote sensing and ground-based techniques for the study of land degradation phenomena in coastal areas.

NASA Astrophysics Data System (ADS)

Imbrenda, Vito; Coluzzi, Rosa; Calamita, Giuseppe; Luigia Giannossi, Maria; D'Emilio, Mariagrazia; Lanfredi, Maria; Makris, John; Palombo, Angelo; Pascucci, Simone; Santini, Federico; Margiotta, Salvatore; Emanuela Bonomo, Agnese; De Martino, Gregory; Perrone, Angela; Rizzo, Enzo; Pignatti, Stefano; Summa, Vito; Simoniello, Tiziana

2015-04-01

Land degradation processes, such as salinization and waterlogging, are increasingly affecting extensive areas devoted to agriculture threatening the sustainability of farming practices. Soil salinization typically appears as an excess accumulation of salt generally pronounced at the soil surface. Commonly, soil salinity is defined and measured by means of laboratory measurements of the electrical conductivity of liquid extracted from saturated soil-paste or different soil-water suspensions. Lab measurements are generally time consuming, costly, destructive, untimely for practical situations where the determination of the causes and/or the assessment of management practices are of interest. Recently, emerging survey techniques proved to be powerful tools to support soil salinity appraisal reducing costs and increasing the amount of spatial information. In the frame of PRO-LAND project (PO-FESR Basilicata 2007-2013) the research activities have been focused on the study of a complex salinization phenomenon occurring in a coastal environment of the Basilicata region (Southern Italy) as a result of natural and anthropic disturbances. The study area is located in the southernmost part of the Bradanic Trough along the sandy Ionian coastal plain. The hydrogeological conditions affect shallowness of the aquifer (45-50 cm below the ground) allowing the occurrence of seawater intrusion. Moreover, during last century, human activities, i.e. built-up of dams, the emergence of farms and industries, played a relevant role in the alteration of soil and groundwater quality of the area. In this work, both ground-based and remote sensing data were used. First, a geophysical mapping of electrical conductivity was carried out using a multi-frequency portable electro-magnetic induction (EMI) sensor. Based on the geophysical mapping and on optimization sampling approach, a number of locations were identified to collect soil samples for the geomineralogical characterization. Airborne images were acquired on the study area by the hyperspectral Compact Airborne Spectrographic Imager (CASI) - 1500 to derive indices sensitive to soil degradation. The main aim of this research activity was to improve the knowledge about the most relevant driving forces, contributing to the analyzed degradation process, and their interplay within the study area. In the light of this, we also would like to suggest the most appropriate best practices and restoration activities to be undertaken.

Recharge to the surficial aquifer system in Lee and Hendry counties, Florida

USGS Publications Warehouse

Krulikas, R.K.; Giese, G.L.

1995-01-01

Protection of ground-water recharge areas against contamination is of great interest in Florida, a State whose population depends heavily on ground water and that is experiencing rapid growth. The Florida Legislature is considering implementation of a tax incentive program to owners of high-rate recharge lands that remain undeveloped. High-rate recharge was arbitrarily set at 10 or more inches per year. The U.S. Geological Survey, in cooperation with the South Florida Water Management District, conducted a study to investigate the efficacy of several methods for estimating recharge to the surficial aquifer system in southwestern Florida and to map recharge at a scale of 1:100,000. Four maps were constructed at a scale of 1:100,000 for Lee and Hendry Counties, depicting the configuration of the water table of the surficial aquifer system, direction of ground-water flow, general soil characteristics, and recharge rates. Point recharge rates calculated for 25 sites in Lee County from comparisons of chloride concentrations in precipitation and in water from the surficial aquifer system ranged from 0.6 to 9.0 inches per year. Local recharge rates estimated by increases in flow along theoretical flow tubes in the surficial aquifer system were 8.0 inches per year in a part of Lee County and 8.2 inches per year in a part of Hendry County. Information on oxygen isotopes in precipitation and water from the surficial aquifer system was used to verify that the source of chlorides in the aquifer system was from precipitation rather than upward leakage of saline water. Soil maps and general topographic and hydrologic considerations were used with calculated point and local recharge rates to regionalize rates throughout Lee and Hendry Counties. The areas of greatest recharge were found in soils of flatwoods and sloughs, which were assigned estimated recharge rates of 0 to 10 inches per year. Soils of swamps and sloughs were assigned values of 0 to 3.0 inches per year; soils of tidal areas and barrier islands, soils of the Everglades, and soils of sloughs and freshwater marshes were assigned values of 0 to 2.0 inches per year; lastly, soils of manmade areas were assigned values of 0.5 to 1.5 inches per year. Small isolated areas of high-rate recharge (greater than 10 inches per year) might exist in Lee and Hendry Counties, but the maximum rate calculated in this study was 9.0 inches per year. Despite low natural recharge rates, lowering of the water table through pumping or canalization could create a potential for induced recharge in excess of 10 inches per year in parts of Lee and Hendry Counties.

The World Soil Museum: education and advocacy on soils of the world

NASA Astrophysics Data System (ADS)

Mantel, Stephan; Land, Hiske

2013-04-01

The World Soil Museum (WSM) in Wageningen, is part of ISRIC World Soil Information and was founded in 1966 on request of the United Nations Educational, Scientific and Cultural Organization (UNESCO) and the International Soil Science Society. The World Soil Museum has a collection of over 1100 soil profiles from more than 70 countries. This soil profiles are vertical sections and show the composition, layering and structure of the soil. The collection is unique in the world and includes a significant number of soil profiles from the Netherlands. The Dutch soil collection is important for serving broader visitor groups, as some visitors, such as secondary school classes, are specifically interested in the Dutch landscape and soils. Broadly speaking, the World Soil Museum has five functions: (i) education and courses, (ii) research, (iii) information and edutainment, (iv) social function, and (v) a real museum function (Art). The World Soil Museum (World Soil Museum) is well known in national and international circles soil and the English name has almost 1,000 references on the Internet. The World Soil Museum is visited by about 1000 people a year, mainly university and college students from Western Europe. Other visitor groups that have found their way to the museum are students from disciplines broader then soil science, such as geography and rural development. Secondary school classes visit the museum for geography classes. The uniqueness and the value of the collection of soil profiles (soil monoliths) and associated collections, such as soil samples, hand pieces, thin sections, slides, is emphasized by the fact ISRIC is the only World Data Centre for Soils (WDC-Soils) within the World Data System of the International Council of Science (ICSU). The collection provides an insight in and overview of the diversity of soils in the world, their properties and their limitations and possibilities for use. A new building is under construction for the WSM, which is expected to be ready mid-2013. The location is appropriately placed on the Wageningen University Campus, close to the students and research centres of the University. The new exposition space will provide new opportunities for serving different visitor groups. The selection of about 80 soil monoliths representing the world's soils will be maintained in the new exposition. In addition, interactive displays will support education. A circular, interactive map of the world will be placed centrally in the exposition and will serve as a portal to the soil information. The map data refer to the monoliths on the walls and vice versa. Around the central map six theme stations communicate current topics that show the relevance of soil in different fields. For the general public it will explain the principles of soil formation and it will show the relevance to actual issues like food production and climate change. High school students in their final years can come here for work assignments and orientation days. Academic students and scientists, from both the Netherlands and other (mainly) northern European countries can continue to come to the WSM for education, study and research.

Geochemical cartography as a tool for assessing the degree of soil contamination with heavy metals in Poland

NASA Astrophysics Data System (ADS)

Szymon Borkowski, Andrzej; Kwiatkowska-Malina, Jolanta

2016-04-01

Spatial disposition of chemical elements including heavy metals in the soil environment is a very important information during preparation of the thematic maps for the environmental protection and/or spatial planning. This knowledge is also essential for the earth's surface and soil's monitoring, designation of areas requiring improvement including remediation. The main source of anthropogenic pollution of soil with heavy metals are industry related to the mining coal and liquid fuels, mining and metallurgy, chemical industry, energy production, waste management, agriculture and transport. The geochemical maps as a kind of specific thematic maps made on the basis of datasets obtained from the Polish Geological Institute's resources allow to get to know the spatial distribution of different chemical elements including heavy metals in soil. The results of the research carried out by the Polish Geological Institute showed strong contamination in some regions in Poland mainly with arsenic, cadmium, lead and nickel. For this reason it was the point to prepare geochemical maps showing contamination of soil with heavy metals, and determine main sources of contamination and zones where heavy metals concentration was higher than acceptable contents. It was also presented a summary map of soil contamination with heavy metals. Additionally, location of highly contaminated zones was compiled with predominant in those areas types of arable soils and then results were thoroughly analyzed. This information can provide a base for further detailed studies on the soil contamination with heavy metals.

Landslides of Palestinian Region

NASA Astrophysics Data System (ADS)

Alwahsh, H.

2013-12-01

Natural disasters are extreme sudden events caused by environmental and natural actors that take away the lives of many thousands of people each year and damage large amount of properties. They strike anywhere on earth, often without any warning. A risk maps of natural disaster are very useful to identify the places that might be adversely affected in the event of natural disaster. The earthquakes are one of natural disaster that have the greatest hazards and will cause loss of life and properties due to damaging the structures of building, dams, bridges. In addition, it will affect local geology and soil conditions. The site effects play an important role in earthquake risk because of its amplification or damping simulation. Another parameter in developing risk map is landslide, which is also one of the most important topics in site effect hazards. Palestine region has been suffering landslide hazards because of the topographical and geological conditions of this region. Most Palestine consists of mountainous area, which has great steep slopes and the type of soil is mainly grayish to yellowish silty clay (Marl Soil). Due to the above mentioned factors many landslides have been occurred from Negev south to the northern borders of Palestine. An example of huge and destruction landslide in a Palestine authority is the landslide in the White Mountain area in the city of Nablus, which occurred in 1997. The geotechnical and geophysical investigation as well as slope stability analysis should be considered in making landslide maps that are necessary to develop risk levels of the natural disaster. Landslides occurred in slopes that are created naturally or by human beings. Failure of soil mass occurs, and hence landslide of soil mass happen due to sliding of soil mass along a plane or curved surface. In general, the slopes become unstable when the shear stresses (driving force) generated in the soil mass exceed the available shearing resistance on the rupture surface. There are many factors which affect directly or indirectly the slope stability, the stability of a slope depends on the geometry and soil engineering properties which include geological, topography, climate, hydrologic conditions, weather and land use (human effects). There are many things that can be used to mitigate landslides disaster. The most important one is the control of the landslides by establishing landslide maps. Other methods such as geometrical, hydrological, mechanical and chemical methods would also be effective in mitigate landslides. Recently, due to the development of the technology in all aspects, a safe and economical design for slopes can be achieved easily.

Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

NASA Astrophysics Data System (ADS)

Wang, W.; Rinke, A.; Moore, J. C.; Cui, X.; Ji, D.; Li, Q.; Zhang, N.; Wang, C.; Zhang, S.; Lawrence, D. M.; McGuire, A. D.; Zhang, W.; Delire, C.; Koven, C.; Saito, K.; MacDougall, A.; Burke, E.; Decharme, B.

2015-03-01

We perform a land surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies between 6 modern stand-alone land surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by 5 different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99-135 x 104 km2) between the two diagnostic methods based on air temperature which are also consistent with the best current observation-based estimate of actual permafrost area (101 x 104 km2). However the uncertainty (1-128 x 104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air temperature based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification and snow cover. Models are particularly poor at simulating permafrost distribution using definition that soil temperature remains at or below 0°C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in permafrost distribution can be made for the Tibetan Plateau.

Soil mapping and processes models to support climate change mitigation and adaptation strategies: a review

NASA Astrophysics Data System (ADS)

Muñoz-Rojas, Miriam; Pereira, Paulo; Brevik, Eric; Cerda, Artemi; Jordan, Antonio

2017-04-01

As agreed in Paris in December 2015, global average temperature is to be limited to "well below 2 °C above pre-industrial levels" and efforts will be made to "limit the temperature increase to 1.5 °C above pre-industrial levels. Thus, reducing greenhouse gas emissions (GHG) in all sectors becomes critical and appropriate sustainable land management practices need to be taken (Pereira et al., 2017). Mitigation strategies focus on reducing the rate and magnitude of climate change by reducing its causes. Complementary to mitigation, adaptation strategies aim to minimise impacts and maximize the benefits of new opportunities. The adoption of both practices will require developing system models to integrate and extrapolate anticipated climate changes such as global climate models (GCMs) and regional climate models (RCMs). Furthermore, integrating climate models driven by socio-economic scenarios in soil process models has allowed the investigation of potential changes and threats in soil characteristics and functions in future climate scenarios. One of the options with largest potential for climate change mitigation is sequestering carbon in soils. Therefore, the development of new methods and the use of existing tools for soil carbon monitoring and accounting have therefore become critical in a global change context. For example, soil C maps can help identify potential areas where management practices that promote C sequestration will be productive and guide the formulation of policies for climate change mitigation and adaptation strategies. Despite extensive efforts to compile soil information and map soil C, many uncertainties remain in the determination of soil C stocks, and the reliability of these estimates depends upon the quality and resolution of the spatial datasets used for its calculation. Thus, better estimates of soil C pools and dynamics are needed to advance understanding of the C balance and the potential of soils for climate change mitigation. Here, we discuss the most recent advances on the application of soil mapping and modeling to support climate change mitigation and adaptation strategies; and These strategies are a key component of the implementation of sustainable land management policies need to be integrated are critical to. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. Muñoz-Rojas, M., Pereira, P., Brevic, E., Cerda, A., Jordan, A. (2017) Soil mapping and processes models for sustainable land management applied to modern challenges. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006

High-resolution soil moisture mapping in Afghanistan

NASA Astrophysics Data System (ADS)

Hendrickx, Jan M. H.; Harrison, J. Bruce J.; Borchers, Brian; Kelley, Julie R.; Howington, Stacy; Ballard, Jerry

2011-06-01

Soil moisture conditions have an impact upon virtually all aspects of Army activities and are increasingly affecting its systems and operations. Soil moisture conditions affect operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, military engineering activities, blowing dust and sand, watershed responses, and flooding. This study further explores a method for high-resolution (2.7 m) soil moisture mapping using remote satellite optical imagery that is readily available from Landsat and QuickBird. The soil moisture estimations are needed for the evaluation of IED sensors using the Countermine Simulation Testbed in regions where access is difficult or impossible. The method has been tested in Helmand Province, Afghanistan, using a Landsat7 image and a QuickBird image of April 23 and 24, 2009, respectively. In previous work it was found that Landsat soil moisture can be predicted from the visual and near infra-red Landsat bands1-4. Since QuickBird bands 1-4 are almost identical to Landsat bands 1- 4, a Landsat soil moisture map can be downscaled using QuickBird bands 1-4. However, using this global approach for downscaling from Landsat to QuickBird scale yielded a small number of pixels with erroneous soil moisture values. Therefore, the objective of this study is to examine how the quality of the downscaled soil moisture maps can be improved by using a data stratification approach for the development of downscaling regression equations for each landscape class. It was found that stratification results in a reliable downscaled soil moisture map with a spatial resolution of 2.7 m.

Considerations for applying digital soil mapping to ecological sites

USDA-ARS?s Scientific Manuscript database

Recent advancements in the spatial prediction of soil properties are not currently being fully utilized for ecological studies. Linking digital soil mapping (DSM) with ecological sites (ES) has the potential to better land management decisions by improving spatial resolution and precision as well as...

Cone-penetrometer exploration of sinkholes: Stratigraphy and soil properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bloomberg, D.; Upchurch, S.B.; Hayden, M.L.

1988-10-01

Four sinkholes with varying surficial expressions were subjected to detailed stratigraphic and soil analysis by means of Standard Penetration Tests (SPT) and Electric Friction Cone Penetration Tests (CPT) in order to evaluate applications of CPT to sinkhole investigations. Although widely used, SPT data are of limited value and difficult to apply to sinkhole mapping. CPT is sensitive to minor lithologic variability and is superior to SPT as a cost-effective technique for determining geotechnical properties of sinkholes. The effectiveness of CPT data results from the force measurements made along the sleeve of the cone. The friction ratio (ratio of sleeve tomore » tip resistance) is a good indicator of soil stratigraphy and properties. By smoothing the friction-ratio data, general stratigraphy and changes in soil properties are easily identified. Stratigraphy of the sinks has been complicated by intense weathering, karstification and marine transgressions. The resulting deposits include five stratigraphic units. 1 and 2 represent Plio-Pleistocene marine sediments with Unit 2 being the zone of soil clay accumulation. 3 and 4 are horizons residual from Miocene strata and indicate an episode of karstification prior to deposition of Units 1 and 2. CPT provides sufficient information for recognition of sinkhole stratigraphy and geotechnical properties. When coupled with laboratory soil analysis, CPT provides unique information about sinkhole geometry and dynamics. In contrast, SPT indicates general, inconclusive trends.« less

Soil and ecological sites of the Santa Rita Experimental Range

Treesearch

Donald J. Breckenfeld; Daniel Robinett

2003-01-01

A soil survey and rangeland resource inventory of the Santa Rita Experimental Range (SRER) was conducted by staff from the Tucson office of the Natural Resources Conservation Service (NRCS) during April and May of 1997. Thirty-two soils series and taxadjuncts were mapped on the SRER and delineated in 24 different mapping units. These soils all occur in an Aridic and...

Determining baseline element composition of lichens. I. Parmelia sulcata at Theodore Roosevelt national park, North Dakota

USGS Publications Warehouse

Gough, L.P.; Severson, R.C.; Jackson, L.L.

1988-01-01

Element-concentration baselines are given for Parmelia sulcata and associated soils. Parmelia chlorochroa was found sporadically and therefore only representative concentration ranges are reported for this species. Element data include (1) for lichens; Al, As, Ba, B, Ca, Cr, Cu, Fe, Hg, Mn, Ni, P, Sr, S, Ti, V, Y, and Zn; and (2) for soils: Al, Ba, Be, Ca, Cs, Cr, Cu, Fe, Hg, Mg, Mn, Ni, Nb, P, Pb, Sr, S, Ti, V, Y, and Zn. Very little (usually 7.2 km); thus, P sulcata is, in general, chemically similar throughout the park. This same uniformity was found for soil geochemistry. Numerous samples collected at close intervals would be required, therefore, to produce detailed element-concentration maps for P. sulcata and soils. No instances of elemental phytotoxic conditions were found; however, P. sulcata apparently possesses large concentrations of Ba, Cu, Fe, Pb, S, V, and possibly Zn.

Space-Time Dynamics of Soil Moisture and Temperature: Scale issues

NASA Technical Reports Server (NTRS)

Mohanty, Binayak P.; Miller, Douglas A.; Th.vanGenuchten, M.

2003-01-01

The goal of this project is to gain further understanding of soil moisture/temperature dynamics at different spatio-temporal scales and physical controls/parameters.We created a comprehensive GIS database, which has been accessed extensively by NASA Land Surface Hydrology investigators (and others), is located at the following URL: http://www.essc.psu.edu/nasalsh. For soil moisture field experiments such as SGP97, SGP99, SMEX02, and SMEX03, cartographic products were designed for multiple applications, both pre- and post-mission. Premission applications included flight line planning and field operations logistics, as well as general insight into the extent and distribution of soil, vegetation, and topographic properties for the study areas. The cartographic products were created from original spatial information resources that were imported into Adobe Illustrator, where the maps were created and PDF versions were made for distribution and download.

Spectral mapping of soil organic matter

NASA Technical Reports Server (NTRS)

Kristof, S. J.; Baumgardner, M. F.; Johannsen, C. J.

1974-01-01

Multispectral remote sensing data were examined for use in the mapping of soil organic matter content. Computer-implemented pattern recognition techniques were used to analyze data collected in May 1969 and May 1970 by an airborne multispectral scanner over a 40-km flightline. Two fields within the flightline were selected for intensive study. Approximately 400 surface soil samples from these fields were obtained for organic matter analysis. The analytical data were used as training sets for computer-implemented analysis of the spectral data. It was found that within the geographical limitations included in this study, multispectral data and automatic data processing techniques could be used very effectively to delineate and map surface soils areas containing different levels of soil organic matter.

Mapping regional soil water erosion risk in the Brittany-Loire basin for water management agency

NASA Astrophysics Data System (ADS)

Degan, Francesca; Cerdan, Olivier; Salvador-Blanes, Sébastien; Gautier, Jean-Noël

2014-05-01

Soil water erosion is one of the main degradation processes that affect soils through the removal of soil particles from the surface. The impacts for environment and agricultural areas are diverse, such as water pollution, crop yield depression, organic matter loss and reduction in water storage capacity. There is therefore a strong need to produce maps at the regional scale to help environmental policy makers and soil and water management bodies to mitigate the effect of water and soil pollution. Our approach aims to model and map soil erosion risk at regional scale (155 000 km²) and high spatial resolution (50 m) in the Brittany - Loire basin. The factors responsible for soil erosion are different according to the spatial and time scales considered. The regional scale entails challenges about homogeneous data sets availability, spatial resolution of results, various erosion processes and agricultural practices. We chose to improve the MESALES model (Le Bissonnais et al., 2002) to map soil erosion risk, because it was developed specifically for water erosion in agricultural fields in temperate areas. The MESALES model consists in a decision tree which gives for each combination of factors the corresponding class of soil erosion risk. Four factors that determine soil erosion risk are considered: soils, land cover, climate and topography. The first main improvement of the model consists in using newly available datasets that are more accurate than the initial ones. The datasets used cover all the study area homogeneously. Soil dataset has a 1/1 000 000 scale and attributes such as texture, soil type, rock fragment and parent material are used. The climate dataset has a spatial resolution of 8 km and a temporal resolution of mm/day for 12 years. Elevation dataset has a spatial resolution of 50 m. Three different land cover datasets are used where the finest spatial resolution is 50 m over three years. Using these datasets, four erosion factors are characterized and quantified: the soil factors (soil sealing, erodibility and runoff), the rate of land cover over three years for each season and for 77 land use classes, the topographic factor (slope and drainage area) and the climate hazard (seasonal amount and rainfall erosivity). These modifications of the original MESALES model allow to better represent erosion risk for arable and bare land. We validated model results by stakeholder consultations and meetings over all the study area. The model has finally been modified taking into account validation results. Results are provided with a spatial resolution of 1 km, and then integrated into 2121 catchments. An erosion risk map for each season and an annual erosion risk map are produced. These new maps allow to organize in hierarchy 2121 catchments into three erosion risk classes. In the annual erosion risk map, 347 catchments have the highest erosion risk, which corresponds to 16 % of total Brittany-Loire basin area. Water management agency now uses these maps to identify priority areas and to plan specific preservation practices.

Using a spatial and tabular database to generate statistics from terrain and spectral data for soil surveys

USGS Publications Warehouse

Horvath , E.A.; Fosnight, E.A.; Klingebiel, A.A.; Moore, D.G.; Stone, J.E.; Reybold, W.U.; Petersen, G.W.

1987-01-01

A methodology has been developed to create a spatial database by referencing digital elevation, Landsat multispectral scanner data, and digitized soil premap delineations of a number of adjacent 7.5-min quadrangle areas to a 30-m Universal Transverse Mercator projection. Slope and aspect transformations are calculated from elevation data and grouped according to field office specifications. An unsupervised classification is performed on a brightness and greenness transformation of the spectral data. The resulting spectral, slope, and aspect maps of each of the 7.5-min quadrangle areas are then plotted and submitted to the field office to be incorporated into the soil premapping stages of a soil survey. A tabular database is created from spatial data by generating descriptive statistics for each data layer within each soil premap delineation. The tabular data base is then entered into a data base management system to be accessed by the field office personnel during the soil survey and to be used for subsequent resource management decisions.Large amounts of data are collected and archived during resource inventories for public land management. Often these data are stored as stacks of maps or folders in a file system in someone's office, with the maps in a variety of formats, scales, and with various standards of accuracy depending on their purpose. This system of information storage and retrieval is cumbersome at best when several categories of information are needed simultaneously for analysis or as input to resource management models. Computers now provide the resource scientist with the opportunity to design increasingly complex models that require even more categories of resource-related information, thus compounding the problem.Recently there has been much emphasis on the use of geographic information systems (GIS) as an alternative method for map data archives and as a resource management tool. Considerable effort has been devoted to the generation of tabular databases, such as the U.S. Department of Agriculture's SCS/S015 (Soil Survey Staff, 1983), to archive the large amounts of information that are collected in conjunction with mapping of natural resources in an easily retrievable manner.During the past 4 years the U.S. Geological Survey's EROS Data Center, in a cooperative effort with the Bureau of Land Management (BLM) and the Soil Conservation Service (SCS), developed a procedure that uses spatial and tabular databases to generate elevation, slope, aspect, and spectral map products that can be used during soil premapping. The procedure results in tabular data, residing in a database management system, that are indexed to the final soil delineations and help quantify soil map unit composition.The procedure was developed and tested on soil surveys on over 600 000 ha in Wyoming, Nevada, and Idaho. A transfer of technology from the EROS Data Center to the BLM will enable the Denver BLM Service Center to use this procedure in soil survey operations on BLM lands. Also underway is a cooperative effort between the EROS Data Center and SCS to define and evaluate maps that can be produced as derivatives of digital elevation data for 7.5-min quadrangle areas, such as those used during the premapping stage of the soil surveys mentioned above, the idea being to make such products routinely available.The procedure emphasizes the applications of digital elevation and spectral data to order-three soil surveys on rangelands, and will:Incorporate digital terrain and spectral data into a spatial database for soil surveys.Provide hardcopy products (that can be generated from digital elevation model and spectral data) that are useful during the soil pre-mapping process.Incorporate soil premaps into a spatial database that can be accessed during the soil survey process along with terrain and spectral data.Summarize useful quantitative information for soil mapping and for making interpretations for resource management.

High mountain soils and periglacial features at the Torres del Paine, National Park Torres del Paine, Chile.

NASA Astrophysics Data System (ADS)

Senra, Eduardo; Schaefer, Carlos; Simas, Felipe; Gjorup, Davi

2015-04-01

The Torres del Paine National Park (TPNP) is located on the southern limit of the Andean Southern Ice Field, part of the Magallanes and Antartica Chilena region, in the province of Ultima Esperanza. The TPNP has a very heterogeneous climate due to orographic influence and wet air masses from the Pacific. The geology is basically Cretaceous metasedimentary rocks and Miocene granitic plutons and batholiths. We studied the main soils and geoenvironments of Mt Ferrier mountain and its surroundings, based on soils , landforms and vegetation aspects. The geoenvironmental stratification was based on the combined variation and integration of pedo-litho-geomorphological features with the vegetation. WE used detailed geological maps, a DEM and slope maps and WorlView II satellite images. Fifteen soils profiles were sampled and classified according to Soil Taxonomy (2010) at all genovironments, ranging from 50 m a.s.l to the at high plateau just below the permanent snowline, under periglacial conditions (~1004m asl). Three soil temperature and moisture monitoring sites were set, allowing for 24 consecutive months (2011 to 2013). Seven geoenvironments were identified with distinct soil and landform characteristics, all with a similar geological substrate. The landform and vegetation have a strong connection with the landscape dynamic, controlling erosional and depositional processes, resulting from glacier advances and retreats in the Late Quaternary. Wind blown materials is widespread, in the form of loess material, accumulating in the higher parts of the landscape. On the other hand, accumulation of organic matter in the water-saturated depressions is common in all altitudes. Generally the soils are acidic and dystrophic, with little exceptions. The following geoenvironments were identified: Periglacial Tundra, Loess slopes, Talus and scarpmentd, Fluvio-glacial terraces, Fluvio-lacustrine plains, Moraines and Paleodunes. The regional pedology show the occurrence of five soil orders (Soil Taxonomy, 2010): Histosols, Mollisols, Inceptsols, Entisols and Andisols.

Measuring spatial variability in soil characteristics

DOEpatents

Hoskinson, Reed L.; Svoboda, John M.; Sawyer, J. Wayne; Hess, John R.; Hess, J. Richard

2002-01-01

The present invention provides systems and methods for measuring a load force associated with pulling a farm implement through soil that is used to generate a spatially variable map that represents the spatial variability of the physical characteristics of the soil. An instrumented hitch pin configured to measure a load force is provided that measures the load force generated by a farm implement when the farm implement is connected with a tractor and pulled through or across soil. Each time a load force is measured, a global positioning system identifies the location of the measurement. This data is stored and analyzed to generate a spatially variable map of the soil. This map is representative of the physical characteristics of the soil, which are inferred from the magnitude of the load force.

7 CFR 657.4 - NRCS responsibilities.

Code of Federal Regulations, 2014 CFR

2014-01-01

... inventories. (2) Identify the soil mapping units within the State that qualify as prime. In doing this, State Conservationists, in consultation with the cooperators of the National Cooperative Soil Survey, have the... the framework of this memorandum. (3) Prepare a statewide list of: (i) Soil mapping units that meet...

7 CFR 657.4 - NRCS responsibilities.

Code of Federal Regulations, 2011 CFR

2011-01-01

... inventories. (2) Identify the soil mapping units within the State that qualify as prime. In doing this, State Conservationists, in consultation with the cooperators of the National Cooperative Soil Survey, have the... the framework of this memorandum. (3) Prepare a statewide list of: (i) Soil mapping units that meet...

7 CFR 657.4 - NRCS responsibilities.

Code of Federal Regulations, 2012 CFR

2012-01-01

... inventories. (2) Identify the soil mapping units within the State that qualify as prime. In doing this, State Conservationists, in consultation with the cooperators of the National Cooperative Soil Survey, have the... the framework of this memorandum. (3) Prepare a statewide list of: (i) Soil mapping units that meet...

7 CFR 657.4 - NRCS responsibilities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... inventories. (2) Identify the soil mapping units within the State that qualify as prime. In doing this, State Conservationists, in consultation with the cooperators of the National Cooperative Soil Survey, have the... the framework of this memorandum. (3) Prepare a statewide list of: (i) Soil mapping units that meet...

7 CFR 657.4 - NRCS responsibilities.

Code of Federal Regulations, 2013 CFR

2013-01-01

... inventories. (2) Identify the soil mapping units within the State that qualify as prime. In doing this, State Conservationists, in consultation with the cooperators of the National Cooperative Soil Survey, have the... the framework of this memorandum. (3) Prepare a statewide list of: (i) Soil mapping units that meet...

Utilizing soil polypedons to improve model performance for digital soil mapping

USDA-ARS?s Scientific Manuscript database

Most digital soil mapping approaches that use point data to develop relationships with covariate data intersect sample locations with one raster pixel regardless of pixel size. Resulting models are subject to spurious values in covariate data which may limit model performance. An alternative approac...

Spatial prediction of Soil Organic Carbon contents in croplands, grasslands and forests using environmental covariates and Generalized Additive Models (Southern Belgium)

NASA Astrophysics Data System (ADS)

Chartin, Caroline; Stevens, Antoine; van Wesemael, Bas

2015-04-01

Providing spatially continuous Soil Organic Carbon data (SOC) is needed to support decisions regarding soil management, and inform the political debate with quantified estimates of the status and change of the soil resource. Digital Soil Mapping techniques are based on relations existing between a soil parameter (measured at different locations in space at a defined period) and relevant covariates (spatially continuous data) that are factors controlling soil formation and explaining the spatial variability of the target variable. This study aimed at apply DSM techniques to recent SOC content measurements (2005-2013) in three different landuses, i.e. cropland, grassland, and forest, in the Walloon region (Southern Belgium). For this purpose, SOC databases of two regional Soil Monitoring Networks (CARBOSOL for croplands and grasslands, and IPRFW for forests) were first harmonized, totalising about 1,220 observations. Median values of SOC content for croplands, grasslands, and forests, are respectively of 12.8, 29.0, and 43.1 g C kg-1. Then, a set of spatial layers were prepared with a resolution of 40 meters and with the same grid topology, containing environmental covariates such as, landuses, Digital Elevation Model and its derivatives, soil texture, C factor, carbon inputs by manure, and climate. Here, in addition to the three classical texture classes (clays, silt, and sand), we tested the use of clays + fine silt content (particles < 20 µm and related to stable carbon fraction) as soil covariate explaining SOC variations. For each of the three land uses (cropland, grassland and forest), a Generalized Additive Model (GAM) was calibrated on two thirds of respective dataset. The remaining samples were assigned to a test set to assess model performance. A backward stepwise procedure was followed to select the relevant environmental covariates using their approximate p-values (the level of significance was set at p < 0.05). Standard errors were estimated for each of the three models. The backward stepwise procedure selected coordinates, elevation and clays + fine silt content as environment covariates to model SOC variation in cropland soils; latitude, precipitation, and clays + fine silt content (< 20 µm) for grassland soils; and latitude, elevation, topographic position index and clays + fine silt content (< 20 µm) for forest soils. The validation of the models gave a R² of 0.62 for croplands, 0.38 for grasslands, and 0.35 for forests. These results will be developed and discussed based on implications of natural against anthropogenic drivers on SOC distribution for these three landuses. To finish, a map combining detailed information of SOC content for agricultural soils and forests was for the first time computed for the Walloon region.

Infrared thermal remote sensing for soil salinity assessment on landscape scale

NASA Astrophysics Data System (ADS)

Ivushkin, Konstantin; Bartholomeus, Harm; Bregt, Arnold K.; Pulatov, Alim; Bui, Elisabeth N.; Wilford, John

2017-04-01

Soil salinity is considered as one of the most severe land degradation aspects. An increased soil salt level inhibits growth and development of crops. Therefore, up to date soil salinity information is vital for appropriate management practices and reclamation strategies. This information is required at increasing spatial and temporal resolution for appropriate management adaptations. Conventional soil sampling and associated laboratory analyses are slow, expensive, and often cannot deliver the temporal and spatial resolution required. The change of canopy temperature is one of the stress indicators in plants. Its behaviour in response to salt stress on individual plant level is well studied in laboratory and greenhouse experiments, but its potential for landscape scale studies using remote sensing techniques is not investigated yet. In our study, possibilities of satellite thermography for landscape scale soil salinity assessment of cropped areas were studied. The performance of satellite thermography is compared with other approaches that have been used before, like Normalised Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). The study areas were Syrdarya province of Uzbekistan and four study areas in four Australian states namely, Western Australia, South Australia, Queensland and New South Wales. The diversity of the study areas allowed us to analyse behaviour of canopy temperature of different crops (wheat, cotton, barley) and different agriculture practices (rain fed and irrigated). MODIS and Landsat TM multiannual satellite images were used to measure canopy temperature. As ground truth for Uzbekistan study area we used a provincial soil salinity map. For the Australian study areas we used the EC map for the whole country. ANOVA was used to analyse relations between the soil salinity maps and canopy temperature, NDVI, EVI. Time series graphs were created to analyse the dynamics of the indicators during the growing season. The results showed significant relations between the soil salinity maps and canopy temperature. The amplitude of canopy temperature difference between salinity classes varies for different crops, but the trend of temperature increase under increased salinity is present in all cases. The calculated F-values were higher for canopy temperature than for all other compared indicators. The vegetation indices also showed significant differences, but F-values were lower compared to canopy temperature. Also the visual comparison of the soil salinity map and the canopy temperature map show similar spatial patterns. The NDVI and EVI maps look more random and noisy and patterns are less pronounced than for the canopy temperature map. The strongest relation between the soil salinity map and canopy temperature was usually observed at the end of a dry season and in the period of maximum crop development. Satellite thermography appeared to be a valuable approach to detect soil salinity under agricultural crops at landscape scale.

Landmarks of History of Soil Science in Sri Lanka

NASA Astrophysics Data System (ADS)

Mapa, R.

2012-04-01

Sri Lanka is a tropical Island in the Southern tip of Indian subcontinent positioned at 50 55' to 90 50' N latitude and 790 42' to 810 53' E longitude surrounded by the Indian Ocean. It is an island 435 km in length and 224 km width consisting of a land are of 6.56 million ha with a population of 20 million. In area wise it is ranked as 118th in the world, where at present ranked as 47 in population wise and ranked 19th in population density. The country was under colonial rule under Portuguese, Dutch and British from 1505 to 1948. The majority of the people in the past and present earn their living from activities based on land, which indicates the important of the soil resource. The objective of this paper is to describe the landmarks of the history of Soil Science to highlight the achievements and failures, which is useful to enrich our present understanding of Sri Lankan soils. The landmarks of the history of Soil Science in Sri Lanka can be divided to three phases namely, the early period (prior to 1956), the middle period (1956 to 1972) and the present period (from 1972 onwards). During the early period, detailed analytical studies of coffee and tea soils were compiled, and these gave mainly information on up-country soils which led to fertilizer recommendations based on field trials. In addition, rice and forest soils were also studied in less detail. The first classification of Sri Lankan soils and a provisional soil map based on parent material was published by Joachim in 1945 which is a major landmark of history of Soil Science in Sri Lanka. In 1959 Ponnamperuma proposed a soil classification system for wetland rice soils. From 1963 to 1968 valuable information on the land resource was collected and documented by aerial resource surveys funded by Canada-Ceylon Colombo plan aid project. This covered 18 major river basins and about 1/4th of Sri Lanka, which resulted in producing excellent soil maps and information of the areas called the Kelani Aruvi Ara and Walawe basins. The provisional soil map was updated by many other workers as Moorman and Panabokke in 1961 and 1972 using this information. The soil map produced by De Alwis and Panabokke in 1972 at a scale of 1:500,000 was the soil maps mostly used during the past years During the present era, the need for classification of Soils of Sri Lanka according to international methods was felt. A major leap forward in Soil Survey, Classification leading to development of a soil data base was initiated in 1995 with the commencement of the "SRICANSOL" project which was a twining project between the Soil Science Societies of Sri Lanka and Canada. This project is now completed with detail soil maps at a scale of 1:250,000 and soil classified according to international methods for the Wet, Intermediate and Dry zones of Sri Lanka. A digital database consisting of soil profile description and physical and chemical data is under preparation for 28, 40 and 51 benchmark sites of the Wet, Intermediate and Dry zones respectively. The emphases on studies on Soil Science in the country at present is more towards environmental conservation related to soil erosion control, reducing of pollution of soil and water bodies from nitrates, pesticide residues and heavy metal accumulation. Key words: Sri Lanka, Provisional soil map

Spectral signature selection for mapping unvegetated soils

NASA Technical Reports Server (NTRS)

May, G. A.; Petersen, G. W.

1975-01-01

Airborne multispectral scanner data covering the wavelength interval from 0.40-2.60 microns were collected at an altitude of 1000 m above the terrain in southeastern Pennsylvania. Uniform training areas were selected within three sites from this flightline. Soil samples were collected from each site and a procedure developed to allow assignment of scan line and element number from the multispectral scanner data to each sampling location. These soil samples were analyzed on a spectrophotometer and laboratory spectral signatures were derived. After correcting for solar radiation and atmospheric attenuation, the laboratory signatures were compared to the spectral signatures derived from these same soils using multispectral scanner data. Both signatures were used in supervised and unsupervised classification routines. Computer-generated maps using the laboratory and multispectral scanner derived signatures resulted in maps that were similar to maps resulting from field surveys. Approximately 90% agreement was obtained between classification maps produced using multispectral scanner derived signatures and laboratory derived signatures.

Modelisation spatio-temporelle de la vulnerabilite du milieu a la degradation des sols en milieu semi-aride a partir de donnees radar

NASA Astrophysics Data System (ADS)

Sylla, Daouda

Defined as a process that reduces the potential of soil production or the usefulness of natural resources, soil degradation is a major environmental problem which affects over 41 % of the land and, over 80 % of people affected by this phenomenon live in developing countries. The general objective of the present project is the characterisation of different types of land use and land cover and the detection of their spatio-temporal changes from radar data (ERS-1, RADARSAT-1 and ENVISAT) for a spatio-temporal modeling of environmental vulnerability to soil degradation in semi-arid area. Due to the high sensitivity of the radar signal to the observing conditions of the sensor and the target, a partition of the radar images with respect to their angular configurations (23° and [33°-35°-47°]) and to environmental conditions (wet and dry) was first performed. A good characterisation and a good temporal evolution of the four types of land use and land cover of interest are obtained with different levels of contrast depending on the incidence angles and environmental conditions. In addition to pixel-based approach used for change detection (images differences, Principal component analysis), a monitoring of land cover from an object-oriented approach which focused on two types of land cover is developed. The method allows a detailed mapping of bare soil occurrences as a function of environmental conditions. Finally, using different sources of information, a modeling of the environmental vulnerability to soil degradation is performed in the South-west of Niger from the probabilistic fusion rule of Dempster-Shafer. The resulting decision maps are statistically acceptable at 93 % and 91 % with Kappa values of 86 % and 84 %, for respectively dry and wet conditions. Besides, they are used to produce a global map of the environmental vulnerability to soil degradation in this semi-arid area. Key-words: Environmental vulnerability to soil degradation; data fusion; radar images; land use changes; semi-arid environment; South-west of Niger.

Mapping contact metamorphic aureoles in Extremadura, Spain, using Landsat thematic mapper images

USGS Publications Warehouse

Rowan, L.C.; Anton-Pacheco, C.; Brickey, D.W.; Kingston, M.J.; Payas, A.

1987-01-01

In the Extremadura region of western Spain, Ag, Pb, Zn, and Sn deposits occur in the pieces of late Hercynian granitic plutons and near the pluton contacts in late Proterozoic slate and metagraywacke that have been regionally metamorphosed to the green schist facies. The plutons generally are well exposed and have distinctive geomorphological expression and vegetation; poor exposures of the metasedimentary host rocks and extensive cultivation, however, make delineation of the contact aureoles difficult. Landsat Thematic Mapper (TM) images have been used to distinguish soil developed on the contact metamorphic rocks from soil formed on the stratigraphically equivalent slate-metagraywacke sequence. The mineral constituents of these soils are similar, except that muscovite is more common in the contact metamorphic soil; carbonaceous material is common in both soils. Contact metamorphic soil have lower reflectance, especially in the 1.6-micrometers wavelength region (TM 5), and weaker Al-OH, Mg-OH, and Fe3+ absorption features than do spectra of the slate-metagraywacke soil. The low-reflectance and subdued absorption features exhibited by the contact metamorphic soil spectra are attributed to the high absorption coefficient f the carbonaceous material caused by heating during emplacement of the granitic plutons. These spectral differences are evident in a TM 4/3, 4/5, 3/1 color-composite image. Initially, this image was used to outline the contact aureoles, but digital classification of the TM data was necessary for generating internally consistent maps of the distribution of the exposed contact metamorphic soil. In an August 1984, TM scene of the Caceras area, the plowed, vegetation-free fields were identified by their low TM 4/3 values. Then, ranges of TM 4/5 and 3/1 values were determine for selected plower fields within and outside the contact aureoles; TM 5 produced results similar to TM 4/5. Field evaluation, supported by X-ray diffraction and petrographic studies, confirmed the presence of more extensive aureoles than shown in published geologic maps; few misclassified areas were noted. Additional plowed fields consisting of exposed contact metamorphic soil were mapped digitally in an August 1985 TM scene. Subsequently, this approach was used to map two 1-km-wide linear zones of contact metamorphosed rock and oil in the San Nicolas-Sn-W Mine area, which is located approximated 125 km southeast of the Caceras study area. Exposures of granite in the San Nicolas area are limited to a few unaltered granitic dikes in the mine and a small exposure of unaltered pegmatite-bearing granite in a quarry about 1.5 km west of the mine. The present of coarsely crystalline biotite and beryl in the granite in the quarry and of contact metamorphosed slate up to 2.5 km from the nearest granite exposure suggest that only the apical part of a pluton is exposed in the quarry and that a larger, shallowly buried body is probably present. These results indicate that potential application of TM image analysis to mineral exploration in lithologically similar areas that are cultivated in spite of poor rock exposures.

Distribution of Heavy Metal Pollution in Surface Soil Samples in China: A Graphical Review.

PubMed

Duan, Qiannan; Lee, Jianchao; Liu, Yansong; Chen, Han; Hu, Huanyu

2016-09-01

Soil pollution in China is one of most wide and severe in the world. Although environmental researchers are well aware of the acuteness of soil pollution in China, a precise and comprehensive mapping system of soil pollution has never been released. By compiling, integrating and processing nearly a decade of soil pollution data, we have created cornerstone maps that illustrate the distribution and concentration of cadmium, lead, zinc, arsenic, copper and chromium in surficial soil across the nation. These summarized maps and the integrated data provide precise geographic coordinates and heavy metal concentrations; they are also the first ones to provide such thorough and comprehensive details about heavy metal soil pollution in China. In this study, we focus on some of the most polluted areas to illustrate the severity of this pressing environmental problem and demonstrate that most developed and populous areas have been subjected to heavy metal pollution.

Environmental Monitoring Networks Optimization Using Advanced Active Learning Algorithms

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail; Volpi, Michele; Copa, Loris

2010-05-01

The problem of environmental monitoring networks optimization (MNO) belongs to one of the basic and fundamental tasks in spatio-temporal data collection, analysis, and modeling. There are several approaches to this problem, which can be considered as a design or redesign of monitoring network by applying some optimization criteria. The most developed and widespread methods are based on geostatistics (family of kriging models, conditional stochastic simulations). In geostatistics the variance is mainly used as an optimization criterion which has some advantages and drawbacks. In the present research we study an application of advanced techniques following from the statistical learning theory (SLT) - support vector machines (SVM) and the optimization of monitoring networks when dealing with a classification problem (data are discrete values/classes: hydrogeological units, soil types, pollution decision levels, etc.) is considered. SVM is a universal nonlinear modeling tool for classification problems in high dimensional spaces. The SVM solution is maximizing the decision boundary between classes and has a good generalization property for noisy data. The sparse solution of SVM is based on support vectors - data which contribute to the solution with nonzero weights. Fundamentally the MNO for classification problems can be considered as a task of selecting new measurement points which increase the quality of spatial classification and reduce the testing error (error on new independent measurements). In SLT this is a typical problem of active learning - a selection of the new unlabelled points which efficiently reduce the testing error. A classical approach (margin sampling) to active learning is to sample the points closest to the classification boundary. This solution is suboptimal when points (or generally the dataset) are redundant for the same class. In the present research we propose and study two new advanced methods of active learning adapted to the solution of MNO problem: 1) hierarchical top-down clustering in an input space in order to remove redundancy when data are clustered, and 2) a general method (independent on classifier) which gives posterior probabilities that can be used to define the classifier confidence and corresponding proposals for new measurement points. The basic ideas and procedures are explained by applying simulated data sets. The real case study deals with the analysis and mapping of soil types, which is a multi-class classification problem. Maps of soil types are important for the analysis and 3D modeling of heavy metals migration in soil and prediction risk mapping. The results obtained demonstrate the high quality of SVM mapping and efficiency of monitoring network optimization by using active learning approaches. The research was partly supported by SNSF projects No. 200021-126505 and 200020-121835.

Alternate data sources for soil surveys on rangeland

USGS Publications Warehouse

Horvath, Emil H.; Klingebiel, A.A.; Moore, D.G.; Fosnight, E.A.

1983-01-01

the feasibility of using this approach for producing physiographic maps as an aid for mapping soils and range sites. The project is a cooperative investigation of the Earth Resources Observation Systems Data Center of the U.S. Geological Survey, the Soil Conservation Service, and the Bureau of Land Management.

Multi-scale soil salinity mapping and monitoring with proximal and remote sensing

USDA-ARS?s Scientific Manuscript database

This talk is part of a technical short course on “Soil mapping and process modelling at diverse scales”. In the talk, guidelines, special considerations, protocols, and strengths and limitations are presented for characterizing spatial and temporal variation in soil salinity at several spatial scale...

Digital Soil Mapping – A platform for enhancing soil learning.

USDA-ARS?s Scientific Manuscript database

The expansion of digital infrastructure and tools has generated massive data and information as well as a need for reliable processing and accurate interpretations. Digital Soil Mapping is no exception in that it has provided opportunities for professionals and the public to interact at field and tr...

Mapping Soil Organic Matter with Hyperspectral Imaging

NASA Astrophysics Data System (ADS)

Moni, Christophe; Burud, Ingunn; Flø, Andreas; Rasse, Daniel

2014-05-01

Soil organic matter (SOM) plays a central role for both food security and the global environment. Soil organic matter is the 'glue' that binds soil particles together, leading to positive effects on soil water and nutrient availability for plant growth and helping to counteract the effects of erosion, runoff, compaction and crusting. Hyperspectral measurements of samples of soil profiles have been conducted with the aim of mapping soil organic matter on a macroscopic scale (millimeters and centimeters). Two soil profiles have been selected from the same experimental site, one from a plot amended with biochar and another one from a control plot, with the specific objective to quantify and map the distribution of biochar in the amended profile. The soil profiles were of size (30 x 10 x 10) cm3 and were scanned with two pushbroomtype hyperspectral cameras, one which is sensitive in the visible wavelength region (400 - 1000 nm) and one in the near infrared region (1000 - 2500 nm). The images from the two detectors were merged together into one full dataset covering the whole wavelength region. Layers of 15 mm were removed from the 10 cm high sample such that a total of 7 hyperspectral images were obtained from the samples. Each layer was analyzed with multivariate statistical techniques in order to map the different components in the soil profile. Moreover, a 3-dimensional visalization of the components through the depth of the sample was also obtained by combining the hyperspectral images from all the layers. Mid-infrared spectroscopy of selected samples of the measured soil profiles was conducted in order to correlate the chemical constituents with the hyperspectral results. The results show that hyperspectral imaging is a fast, non-destructive technique, well suited to characterize soil profiles on a macroscopic scale and hence to map elements and different organic matter quality present in a complete pedon. As such, we were able to map and quantify biochar in our profile. Smaller interesting regions can also easily be selected from the hyperspectral images for more detailed study at microscopic scale.

Soils and the soil cover of the Valley of Geysers

NASA Astrophysics Data System (ADS)

Kostyuk, D. N.; Gennadiev, A. N.

2014-06-01

The results of field studies of the soil cover within the tourist part of the Valley of Geysers in Kamchatka performed in 2010 and 2011 are discussed. The morphology of soils, their genesis, and their dependence on the degree of hydrothermal impact are characterized; the soil cover patterns developing in the valley are analyzed. On the basis of the materials provided by the Kronotskii Biospheric Reserve and original field data, the soil map of the valley has been developed. The maps of vegetation conditions, soil temperature at the depth of 15 cm, and slopes of the surface have been used for this purpose together with satellite imagery and field descriptions of reference soil profiles. The legend to the soil map includes nine soil units and seven units of parent materials and their textures. Soil names are given according to the classification developed by I.L. Goldfarb (2005) for the soils of hydrothermal fields. The designation of soil horizons follows the new Classification and Diagnostic System of Russian Soils (2004). It is suggested that a new horizon—a thermometamorphic horizon TRM—can be introduced into this system by analogy with other metamorphic (transformed in situ) horizons distinguished in this system. This horizon is typical of the soils partly or completely transformed by hydrothermal impacts.

Regional mapping of soil parent material by machine learning based on point data

NASA Astrophysics Data System (ADS)

Lacoste, Marine; Lemercier, Blandine; Walter, Christian

2011-10-01

A machine learning system (MART) has been used to predict soil parent material (SPM) at the regional scale with a 50-m resolution. The use of point-specific soil observations as training data was tested as a replacement for the soil maps introduced in previous studies, with the aim of generating a more even distribution of training data over the study area and reducing information uncertainty. The 27,020-km 2 study area (Brittany, northwestern France) contains mainly metamorphic, igneous and sedimentary substrates. However, superficial deposits (aeolian loam, colluvial and alluvial deposits) very often represent the actual SPM and are typically under-represented in existing geological maps. In order to calibrate the predictive model, a total of 4920 point soil descriptions were used as training data along with 17 environmental predictors (terrain attributes derived from a 50-m DEM, as well as emissions of K, Th and U obtained by means of airborne gamma-ray spectrometry, geological variables at the 1:250,000 scale and land use maps obtained by remote sensing). Model predictions were then compared: i) during SPM model creation to point data not used in model calibration (internal validation), ii) to the entire point dataset (point validation), and iii) to existing detailed soil maps (external validation). The internal, point and external validation accuracy rates were 56%, 81% and 54%, respectively. Aeolian loam was one of the three most closely predicted substrates. Poor prediction results were associated with uncommon materials and areas with high geological complexity, i.e. areas where existing maps used for external validation were also imprecise. The resultant predictive map turned out to be more accurate than existing geological maps and moreover indicated surface deposits whose spatial coverage is consistent with actual knowledge of the area. This method proves quite useful in predicting SPM within areas where conventional mapping techniques might be too costly or lengthy or where soil maps are insufficient for use as training data. In addition, this method allows producing repeatable and interpretable results, whose accuracy can be assessed objectively.

Mapping of available heavy metals in Catamarca (Argentina)

NASA Astrophysics Data System (ADS)

Roca, N.; Pazos, M. S.; Bech, J.

2009-04-01

Copper, iron, manganese and zinc are four essential elements for plant growth. Mapping heavy metal migration and distribution in soils is a preliminary step in assessing heavy metal availability in soils. However, data of qualitative and quantitative trace elements composition of soils of Argentina are scarce. Despite the small amounts required by plants, agricultural soils are usually deficient in one or more micronutrients, therefore, their concentration in plant tissues falls below the levels that allow optimal growth. Soil nature plays a fundamental role in the availability of micronutrients and their behaviour at a soil-plant level. The aim of this study is to determine the plant availability and areas of deficiency in agricultural soils with risk of salinization. The presented maps have been elaborated on the basis of the information provided by the monochromatic aerial photographs, scale 1:7000 and projected using the topographic information of the National Topographic Maps. Soils were sampled according to the spatial variation of soil types and land use. Sampling points were geo-referenced. Soil samples were analyzed at the laboratory for complete physicochemical and mineralogical characteristics. The percentage of organic matter is the determining factor in the presence and distribution of the available metals in the soils of the studied area, being the top horizon the one of greatest accumulation. CuDTPA, FeDPTA and MnDPTA are mobile within the profile, whereas ZnDPTA remains adsorbed without vertical displacement. ZnDTPA is the only available metal which also shows differences due to soil salinity and textural classes. However, soil geochemical conditions imply low extractability and a certain difficulty for micronutrient absorption by plants.

Variations in Soil Carbon and Nitrogen Stocks of Deep Profile Following Re-vegetation along Precipitation Gradient in the Loess Plateau of China

NASA Astrophysics Data System (ADS)

Tuo, D.; Gao, G.; Fu, B.

2017-12-01

Precipitation is one of the most important limit factor affect soil organic carbon (SOC) and total nitrogen (TN) following re-vegetation; however, the effect of precipitation on the C and N cycling in deep soils is poorly understood. This study was designed to measure SOC and TN stocks and C/N ratio to a depth of 300 cm following re-vegetation along a precipitation gradient (280 to 540 mm yr-1) on the Loess Plateau of China. The results showed that the relationship of soil C-N coupling after cropland abandoned was related to mean annual precipitation (MAP) and soil depth. SOC and TN stocks in the shallow layers of 0-100 cm were 3.8 and 0.41 kg m-2, respectively, and that in the deep layers of 100-300 cm can represent about 62.7-72.5% and 60.2-88.7% to a depth of 0-300 cm, respectively. Positive linearly relationships were obtained between MAP and SOC and TN stocks at most soil layers of 0-300 cm (p < 0.05). The relationships between the MAP and changes of SOC and TN stocks following short-term restoration were highly dependent on soil depth. Changes of SOC and TN stocks after re-vegetation in shallow soils (0-100 cm) were gaining at regional scale, but in deep soils (100-300 cm), which were losing at wetter sites (MAP > 400 mm). The initial soil C loss may be attributed to greater C decomposition and lower belowground C input. The change of C/N ratio had significantly negatively correlation with MAP in each soil depth, except for 0-20 cm, indicating the effect of soil N on C accumulation is higher at drier areas rather than wetter sites. Based on the investigated factors, precipitation, soil water and clay had a dominant control over the spatial distribution of SOC, TN and C/N ratio to a 300 cm soil depth. This information is helpful our understanding of the dynamics of soil C and N of deep soils following re-vegetation in the semiarid regions.

Goal oriented soil mapping: applying modern methods supported by local knowledge: A review

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Brevik, Eric; Oliva, Marc; Estebaranz, Ferran; Depellegrin, Daniel; Novara, Agata; Cerda, Artemi; Menshov, Oleksandr

2017-04-01

In the recent years the amount of soil data available increased importantly. This facilitated the production of better and accurate maps, important for sustainable land management (Pereira et al., 2017). Despite these advances, the human knowledge is extremely important to understand the natural characteristics of the landscape. The knowledge accumulated and transmitted generation after generation is priceless, and should be considered as a valuable data source for soil mapping and modelling. The local knowledge and wisdom can complement the new advances in soil analysis. In addition, farmers are the most interested in the participation and incorporation of their knowledge in the models, since they are the end-users of the study that soil scientists produce. Integration of local community's vision and understanding about nature is assumed to be an important step to the implementation of decision maker's policies. Despite this, many challenges appear regarding the integration of local and scientific knowledge, since in some cases there is no spatial correlation between folk and scientific classifications, which may be attributed to the different cultural variables that influence local soil classification. The objective of this work is to review how modern soil methods incorporated local knowledge in their models. References Pereira, P., Brevik, E., Oliva, M., Estebaranz, F., Depellegrin, D., Novara, A., Cerda, A., Menshov, O. (2017) Goal Oriented soil mapping: applying modern methods supported by local knowledge. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006

Application of Remote Sensing Data to Improve the Water and Soil Resource Management of Rwanda

NASA Astrophysics Data System (ADS)

Csorba, Ádám; Bukombe, Benjamin; Naramabuye, Francois Xavier; Szegi, Tamás; Vekerdy, Zoltán; Michéli, Erika

2017-04-01

The Rwandan agriculture strongly relies in the dry seasons on the water stored in artificial reservoirs of various sizes for irrigation purposes. Furthermore, the success of irrigation depends on a wide range of soil properties which directly affect the moisture regime of the growing medium. By integrating remote sensing and auxiliary data the objectives of our study are to monitor the water level fluctuation in the reservoirs, estimate the volume of water available for irrigation and to combine this information with soil property maps to support the decision making for sustainable irrigation water management in a study area in Southern Rwanda. For water level and volume estimation a series of Sentinel-1 (product type: GRD, acquisition mode: IW, polarizations HH and VH) data were obtained covering the study area and spanning over a period of two years. To map the extent of water bodies the Radar-Based Water Body Mapping module of the Water Observation and Information System (WOIS) was used. High-resolution optical data (Sentinel-2) were used for validation in cloud-free periods. To estimate the volume changes in the reservoirs, we combined the information derived from the water body mapping procedure and digital elevation models. For sustainable irrigation water management, digital soil property maps were developed by the application of wide range of environmental covariates related to soil forming factors. To develop covariates which represent the land use a time series analysis of the 2 years of Sentinel-1 data was performed. As auxiliary soil data, the ISRIC-WISE harmonized soil profile database was used. The developed digital soil mapping approach is integrated into a new WOIS workflow.

Land Ecology Essay I: The siren song of the finish line

USDA-ARS?s Scientific Manuscript database

As the National Cooperative Soils Survey nears the completion of initial mapping and description activities, the options for next steps are being considered. One option is to deploy new and emerging mapping technologies for existing and refined concepts of soil behavior to create more precise maps ...

Dynamic prescription maps for site-specific variable rate irrigation of cotton

USDA-ARS?s Scientific Manuscript database

A prescription map is a set of instructions that controls a variable rate irrigation (VRI) system. These maps, which may be based on prior yield, soil texture, topography, or soil electrical conductivity data, are often manually applied at the beginning of an irrigation season and remain static. The...

Topographic soil wetness index derived from combined Alaska-British Columbia datasets for the Gulf of Alaska region

NASA Astrophysics Data System (ADS)

D'Amore, D. V.; Biles, F. E.

2016-12-01

The flow of water is often highlighted as a priority in land management planning and assessments related to climate change. Improved measurement and modeling of soil moisture is required to develop predictive estimates for plant distributions, soil moisture, and snowpack, which all play important roles in ecosystem planning in the face of climate change. Drainage indexes are commonly derived from GIS tools with digital elevation models. Soil moisture classes derived from these tools are useful digital proxies for ecosystem functions associated with the concentration of water on the landscape. We developed a spatially explicit topographically derived soil wetness index (TWI) across the perhumid coastal temperate rainforest (PCTR) of Alaska and British Columbia. Developing applicable drainage indexes in complex terrain and across broad areas required careful application of the appropriate DEM, caution with artifacts in GIS covers and mapping realistic zones of wetlands with the indicator. The large spatial extent of the model has facilitated the mapping of forest habitat and the development of water table depth mapping in the region. A key element of the TWI is the merging of elevation datasets across the US-Canada border where major rivers transect the international boundary. The unified TWI allows for seemless mapping across the international border and unified ecological applications. A python program combined with the unified DEM allows end users to quickly apply the TWI to all areas of the PCTR. This common platform can facilitate model comparison and improvements to local soil moisture conditions, generation of streamflow, and ecological site conditions. In this presentation we highlight the application of the TWI for mapping risk factors related to forest decline and the development of a regional water table depth map. Improved soil moisture maps are critical for deriving spatial models of changes in soil moisture for both plant growth and streamflow across future climate conditions.

Use of thermal inertia determined by HCMM to predict nocturnal cold prone areas in Florida

NASA Technical Reports Server (NTRS)

Allen, L. H., Jr. (Principal Investigator)

1983-01-01

Pairs of HCMM day-night thermal infrared (IR) data were selected during the 1978-79 winter to examine patterns of surface temperature and thermal inertia (TI) of peninsular Florida. The GOES and NOAA-6 thermal IR, as well as National Climatic Center temperatures and rainfall, were also used. The HCMM apparent thermal inertia (ATI) images closely corresponded to the general soil map of Florida, based on soil drainage classes. Areas with low ATI overlay well-drained soils, such as deep sands and drained organic soils, whereas with high ATI overlay areas with wetlands and bodies of water. The HCMM ATI images also corresponded well with GOES-detected winter nocturnal cold-prone areas. Use of HCMM data with Carlson's energy balance model showed both high moisture availability (MA) and high thermal inertia (TI) of wetland-type surfaces and low MA and low TI of upland, well-drained soils. Since soil areas with low TI develop higher temperatures during the day, then antecedent patterns of highest maximum daytime surface temperature can also be used to predict nocturnal cold-prone areas in Florida.

Hydrogeologic and geospatial data for the assesment of focused recharge to the Carbonate-Rock Aquifer in Genesee County, New York

USGS Publications Warehouse

Reddy, James E.; Kappel, William M.

2010-01-01

Existing hydrogeologic and geospatial data useful for the assessment of focused recharge to the carbonate-rock aquifer in the central part of Genesee County, NY, were compiled from numerous local, State, and Federal agency sources. Data sources utilized in this pilot study include available geospatial datasets from Federal and State agencies, interviews with local highway departments and the Genesee County Soil and Water Conservation District, and an initial assessment of karst features through the analysis of ortho-photographs, with minimal field verification. The compiled information is presented in a series of county-wide and quadrangle maps. The county-wide maps present generalized hydrogeologic conditions including distribution of geologic units, major faults, and karst features, and bedrock-surface and water-table configurations. Ten sets of quadrangle maps of the area that overlies the carbonate-rock aquifer present more detailed and additional information including distribution of bedrock outcrops, thin and (or) permeable soils, and karst features such as sinkholes and swallets. Water-resource managers can utilize the information summarized in this report as a guide to their assessment of focused recharge to, and the potential for surface contaminants to reach the carbonate-rock aquifer.

Use of airborne hyperspectral imagery to map soil parameters in tilled agricultural fields

USGS Publications Warehouse

Hively, W. Dean; McCarty, Gregory W.; Reeves, James B.; Lang, Megan W.; Oesterling, Robert A.; Delwiche, Stephen R.

2011-01-01

Soil hyperspectral reflectance imagery was obtained for six tilled (soil) agricultural fields using an airborne imaging spectrometer (400–2450 nm, ~10 nm resolution, 2.5 m spatial resolution). Surface soil samples (n = 315) were analyzed for carbon content, particle size distribution, and 15 agronomically important elements (Mehlich-III extraction). When partial least squares (PLS) regression of imagery-derived reflectance spectra was used to predict analyte concentrations, 13 of the 19 analytes were predicted with R2 > 0.50, including carbon (0.65), aluminum (0.76), iron (0.75), and silt content (0.79). Comparison of 15 spectral math preprocessing treatments showed that a simple first derivative worked well for nearly all analytes. The resulting PLS factors were exported as a vector of coefficients and used to calculate predicted maps of soil properties for each field. Image smoothing with a 3 × 3 low-pass filter prior to spectral data extraction improved prediction accuracy. The resulting raster maps showed variation associated with topographic factors, indicating the effect of soil redistribution and moisture regime on in-field spatial variability. High-resolution maps of soil analyte concentrations can be used to improve precision environmental management of farmlands.

Abiotic versus biotic controls on soil nitrogen cycling in drylands along a 3200 km transect

NASA Astrophysics Data System (ADS)

Liu, Dongwei; Zhu, Weixing; Wang, Xiaobo; Pan, Yuepeng; Wang, Chao; Xi, Dan; Bai, Edith; Wang, Yuesi; Han, Xingguo; Fang, Yunting

2017-03-01

Nitrogen (N) cycling in drylands under changing climate is not well understood. Our understanding of N cycling over larger scales to date relies heavily on the measurement of bulk soil N, and the information about internal soil N transformations remains limited. The 15N natural abundance (δ15N) of ammonium and nitrate can serve as a proxy record for the N processes in soils. To better understand the patterns and mechanisms of N cycling in drylands, we collected soils along a 3200 km transect at about 100 km intervals in northern China, with mean annual precipitation (MAP) ranging from 36 to 436 mm. We analyzed N pools and δ15N of ammonium, dual isotopes (15N and 18O) of nitrate, and the microbial gene abundance associated with soil N transformations. We found that N status and its driving factors were different above and below a MAP threshold of 100 mm. In the arid zone with MAP below 100 mm, soil inorganic N accumulated, with a large fraction being of atmospheric origin, and ammonia volatilization was strong in soils with high pH. In addition, the abundance of microbial genes associated with soil N transformations was low. In the semiarid zone with MAP above 100 mm, soil inorganic N concentrations were low and were controlled mainly by biological processes (e.g., plant uptake and denitrification). The preference for soil ammonium over nitrate by the dominant plant species may enhance the possibility of soil nitrate losses via denitrification. Overall, our study suggests that a shift from abiotic to biotic controls on soil N biogeochemistry under global climate changes would greatly affect N losses, soil N availability, and other N transformation processes in these drylands in China.

Application of digital soil mapping in Argentina: An example using apparent soil electrical conductivity

NASA Astrophysics Data System (ADS)

Domenech, Marisa; Castro Franco, Mauricio; Costa, Jose Luis; Aparicio, Virginia

2017-04-01

Apparent soil electrical conductivity (ECa) has been used to capture soil data in several Argentinean Pampas locations. The aim of this study was to generate digital soil mapping on the basis of understanding the relation among ECa and soil properties in three farming fields of the southeast Buenos Aires province. We carried out a geostatistical analysis using ECa data obtained at two depths 0-30cm (ECa_30cm) and 0-90cm (ECa_90cm). Then, two zones derived from ECa measurements were delimited in each field. A soil-sampling scheme was applied in each zone using two depths: 0-30cm and 30-90cm. Texture, Organic Matter Content (OMC), cation-exchange capacity (CEC), pH, saturated paste electrical conductivity (ECe) and effective depth were analyzed. The relation between zones and soil properties were studied using nested factor ANOVA. Our results indicated that clay content and effective depth showed significant differences among ECa_30 zones in all fields. In Argentine Pampas, the presence of petrocalcic horizons limits the effective soil depth at field scale. These horizons vary in depth, structure, hardness and carbonates content. In addition, they influence the spatial pattern of clay content. The relation among other physical and chemical soil properties was not consistent. Two soil unit maps were delimited in each field. These results might support irrigation management due to clay content and effective depth would be controlling soil water storage. Our findings highlight the high accuracy use of soil sensors in developing digital soil mapping at field scale, irrigation management zones, precision agriculture and hydrological modeling in Pampas region conditions.

Mapping soil total nitrogen of cultivated land at county scale by using hyperspectral image

NASA Astrophysics Data System (ADS)

Gu, Xiaohe; Zhang, Li Yan; Shu, Meiyan; Yang, Guijun

2018-02-01

Monitoring total nitrogen content (TNC) in the soil of cultivated land quantitively and mastering its spatial distribution are helpful for crop growing, soil fertility adjustment and sustainable development of agriculture. The study aimed to develop a universal method to map total nitrogen content in soil of cultivated land by HSI image at county scale. Several mathematical transformations were used to improve the expression ability of HSI image. The correlations between soil TNC and the reflectivity and its mathematical transformations were analyzed. Then the susceptible bands and its transformations were screened to develop the optimizing model of map soil TNC in the Anping County based on the method of multiple linear regression. Results showed that the bands of 14th, 16th, 19th, 37th and 60th with different mathematical transformations were screened as susceptible bands. Differential transformation was helpful for reducing the noise interference to the diagnosis ability of the target spectrum. The determination coefficient of the first order differential of logarithmic transformation was biggest (0.505), while the RMSE was lowest. The study confirmed the first order differential of logarithm transformation as the optimal inversion model for soil TNC, which was used to map soil TNC of cultivated land in the study area.

Mapping soil textural fractions across a large watershed in north-east Florida.

PubMed

Lamsal, S; Mishra, U

2010-08-01

Assessment of regional scale soil spatial variation and mapping their distribution is constrained by sparse data which are collected using field surveys that are labor intensive and cost prohibitive. We explored geostatistical (ordinary kriging-OK), regression (Regression Tree-RT), and hybrid methods (RT plus residual Sequential Gaussian Simulation-SGS) to map soil textural fractions across the Santa Fe River Watershed (3585 km(2)) in north-east Florida. Soil samples collected from four depths (L1: 0-30 cm, L2: 30-60 cm, L3: 60-120 cm, and L4: 120-180 cm) at 141 locations were analyzed for soil textural fractions (sand, silt and clay contents), and combined with textural data (15 profiles) assembled under the Florida Soil Characterization program. Textural fractions in L1 and L2 were autocorrelated, and spatially mapped across the watershed. OK performance was poor, which may be attributed to the sparse sampling. RT model structure varied among textural fractions, and the model explained variations ranged from 25% for L1 silt to 61% for L2 clay content. Regression residuals were simulated using SGS, and the average of simulated residuals were used to approximate regression residual distribution map, which were added to regression trend maps. Independent validation of the prediction maps showed that regression models performed slightly better than OK, and regression combined with average of simulated regression residuals improved predictions beyond the regression model. Sand content >90% in both 0-30 and 30-60 cm covered 80.6% of the watershed area. Copyright 2010 Elsevier Ltd. All rights reserved.

Preliminary investigation of Large Format Camera photography utility in soil mapping and related agricultural applications

NASA Technical Reports Server (NTRS)

Pelletier, R. E.; Hudnall, W. H.

1987-01-01

The use of Space Shuttle Large Format Camera (LFC) color, IR/color, and B&W images in large-scale soil mapping is discussed and illustrated with sample photographs from STS 41-6 (October 1984). Consideration is given to the characteristics of the film types used; the photographic scales available; geometric and stereoscopic factors; and image interpretation and classification for soil-type mapping (detecting both sharp and gradual boundaries), soil parent material topographic and hydrologic assessment, natural-resources inventory, crop-type identification, and stress analysis. It is suggested that LFC photography can play an important role, filling the gap between aerial and satellite remote sensing.

Use of LANDSAT data to define soil boundaries in Carroll County, Missouri

NASA Technical Reports Server (NTRS)

Davidson, S. E.

1981-01-01

Bands 4, 5 and 7 false color composite photographs were prepared using data from LANDSAT scenes acquired during April 1977 and April 1981 on computer compatible tapes, and these color composites were compared with band 7 black and white photographs prepared for the entire county. Delineations of soil boundaries at the soil association level were achieved using LANDSAT spectral reflectance data and slope maps for a portion of Carroll County, Missouri. Forty two spectral reflectance classes from April 1977 LANDSAT data were overlaid on digitized slope maps of nine USGS 7.5 minute series topographic quadrangle slope maps to achieve boundary delineations of the soil associations.

Introduction to the special section ‘Applications of electromagnetic induction to digital soil mapping’

USDA-ARS?s Scientific Manuscript database

Use of electromagnetic induction (EMI) instruments has increased as a tool to map soils because it provides a means of locating suitable sampling sites that provide the basis for mapping the spatial variability of various soil properties either directly or indirectly measured with EMI, including sa...

A history of Soil Survey in England and Wales

NASA Astrophysics Data System (ADS)

Hallett, S.; Deeks, L.

2012-04-01

Early soil mapping in Britain was dominated, as in the USA, by soil texture with maps dating back to the early 1900's identifying surface texture and parent rock materials. Only in the 1920's did Dokuchaev's work in Russia involving soil morphology and the development of the soil profile start to gain popularity, drawing in the influence of climate and topography on pedogenesis. Intentions to create a formal body at this time responsible for soil survey were not implemented and progress remained slow. However, in 1939 definite steps were taken to address this and the soil survey was created. In 1947, its activities were transferred from Bangor to the research branch of the Rothamsted experimental station in Hertfordshire under Professor G.W. Robinson. Soon after, a number of regional offices were also established to act as a link with the National Agricultural Advisory Service. At this time a Pedology Department was established at Rothamsted, focussing on petrological, X-ray, spectrographic and chemical analyses. Although not a Rothamsted Department itself, the Survey did fall under the 'Lawes Agricultural Trust'. A Soil Survey Research Advisory Board was also formed to act as a liaison with the Agricultural Field Council. In Scotland by contrast, soil survey activities became centred on the Macaulay Institute in Aberdeen. Developments in the survey of British soils were accompanied in parallel by the development of soil classification systems. In 1930 a Soils Correlation Committee had been formed to ensure consistency in methods and naming of soil series and to ensure the classification was applied uniformly. In England and Wales the zonal system adopted was similar to that used in the USA, where soil series were named after the location where they were first described. American soil scientists such as Veitch and Lee provided stimulus to the development of mapping methods. In Scotland a differing classification was adopted, being similar to that used in Canada, recognising the importance of the soil drainage characteristics within areas of similar parent material. This led to the adoption of the soil catena approach and the usage of soil 'associations'. With Britain entering the Second World War in 1939, there followed the almost complete cessation of survey activities and it was only in the aftermath of that war that recruitment of surveyors could re-commence. The first Soil Survey Field Handbook was published in 1940. Systematic and formal national soil survey activities across both England and Wales can be dated back to 1947 when work commenced to provide a complete picture of the soil resources of the two countries. Mapping at 1:25,000 scale, almost half the land was covered when, in 1979, the survey received instructions, together with the Scottish survey, to complete respective national maps at 1:250,000, which were published in the early 1980s. Attention then turned again to mapping lowland areas in more detail as well as specialised and thematic maps. However, in 1987 systematic survey was terminated and staff of the Soil Survey of England and Wales disbanded to form the Soil Survey and Land Research Centre (SSLRC) at what became Cranfield University - where its successor, the National Soil Resources Institute (NSRI) operates currently.

Integrationof Remote Sensing and Geographic information system in Ground Water Quality Assessment and Management

NASA Astrophysics Data System (ADS)

Shakak, N.

2015-04-01

Spatial variations in ground water quality in the Khartoum state, Sudan, have been studied using geographic information system (GIS) and remote sensing technique. Gegraphical informtion system a tool which is used for storing, analyzing and displaying spatial data is also used for investigating ground water quality information. Khartoum landsat mosac image aquired in 2013was used, Arc/Gis software applied to extract the boundary of the study area, the image was classified to create land use/land cover map. The land use map,geological and soil map are used for correlation between land use , geological formations, and soil types to understand the source of natural pollution that can lower the ground water quality. For this study, the global positioning system (GPS), used in the field to identify the borehole location in a three dimentional coordinate (Latitude, longitude, and altitude), water samples were collected from 156 borehole wells, and analyzed for physico-chemical parameters like electrical conductivity, Total dissolved solid,Chloride, Nitrate, Sodium, Magnisium, Calcium,and Flouride, using standard techniques in the laboratory and compared with the standards.The ground water quality maps of the entire study area have been prepared using spatial interpolation technique for all the above parameters.then the created maps used to visualize, analyze, and understand the relationship among the measured points. Mapping was coded for potable zones, non-potable zones in the study area, in terms of water quality sutability for drinking water and sutability for irrigation. In general satellite remote sensing in conjunction with geographical information system (GIS) offers great potential for water resource development and management.

BOREAS TE-2 NSA Soil Lab Data

NASA Technical Reports Server (NTRS)

Veldhuis, Hugo; Hall, Forrest G. (Editor); Knapp, David E. (Editor)

2000-01-01

This data set contains the major soil properties of soil samples collected in 1994 at the tower flux sites in the Northern Study Area (NSA). The soil samples were collected by Hugo Veldhuis and his staff from the University of Manitoba. The mineral soil samples were largely analyzed by Barry Goetz, under the supervision of Dr. Harold Rostad at the University of Saskatchewan. The organic soil samples were largely analyzed by Peter Haluschak, under the supervision of Hugo Veldhuis at the Centre for Land and Biological Resources Research in Winnipeg, Manitoba. During the course of field investigation and mapping, selected surface and subsurface soil samples were collected for laboratory analysis. These samples were used as benchmark references for specific soil attributes in general soil characterization. Detailed soil sampling, description, and laboratory analysis were performed on selected modal soils to provide examples of common soil physical and chemical characteristics in the study area. The soil properties that were determined include soil horizon; dry soil color; pH; bulk density; total, organic, and inorganic carbon; electric conductivity; cation exchange capacity; exchangeable sodium, potassium, calcium, magnesium, and hydrogen; water content at 0.01, 0.033, and 1.5 MPascals; nitrogen; phosphorus: particle size distribution; texture; pH of the mineral soil and of the organic soil; extractable acid; and sulfur. These data are stored in ASCII text files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Application of ERTS-1 imagery to detecting and mapping modern erosion features, and to monitoring erosional changes, in southern Arizona

NASA Technical Reports Server (NTRS)

Morrison, R. B.; Cooley, M. E.

1973-01-01

The author has identified the following significant results. The red MSS band 5 gives the sharpest definition of modern arroyos. On the best images, modern arroy0s can be distinguished as narrow as 150 to 200 feet in reaches where their contrast with adjacent areas is only moderate, and as narrow as 60 to 75 feet where their contrast is high. Both the red and infrared bands show differences is soils and vegetation. In the late fall and winter imagery, band 7 generally is the most useful for mapping the areas of the more erodible soils. A map at 1:1,000,000 scale has been prepared that shows all the arroyos within the 17,000 square mile study area that have been identified from ERTS-1 images. Also, from U-2 color infrared airphotos, a 1:125,000 scale map has been made of a 50 mile reach along San Simon Wash, in southeastern Arizona. This map shows not only the arroyo channels and narrow flood plains that have developed since 1890, but also areas within a few miles of the wash that are severely guilled, severely sheet-eroded, and moderately sheet-eroded. Two important effects of the third largest recorded flood of the upper Gila River also have been determined from the ERTS-1 images. The inundated area is best displayed on band 7, and the areas of severe sand/gravel erosion/deposition show best on band 5.

Quaternary geologic map of the Lake Erie 4 degrees x 6 degrees quadrangle, United States and Canada

USGS Publications Warehouse

Fullerton, David S.; Richmond, Gerald M.; state compilations by Fullerton, David S.; Cowan, W.R.; Sevon, W.D.; Goldthwait, R.P.; Farrand, W.R.; Muller, E.H.; Behling, R.E.; Stravers, J.A.; edited and integrated by Fullerton, David S.; Richmond, Gerald Martin

1991-01-01

The Quaternary Geologic Map of the Lake Erie 4? x 6? Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the 'ground' on which we walk, the 'dirt' in which we dig foundations, and the 'soil' in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale.

Quaternary geologic map of the Quebec 4 degrees x 6 degrees quadrangle, United States and Canada

USGS Publications Warehouse

State compilations by Borns, H. W.; Gadd, N.R.; LaSalle, Pierre; Martineau, Ghismond; Chauvin, Luc; Fulton, R.J.; Chapman, W.F.; Wagner, W.P.; Grant, D.R.; edited and integrated by Richmond, Gerald Martin; Fullerton, David S.

1987-01-01

The Quaternary Geologic Map of the Quebec 4? x 6? Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the Earth. They make up the 'ground' on which we walk, the 'dirt' in which we dig foundations, and the 'soil' in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale.

Quaternary geologic map of the Chicago 4 degrees x 6 degrees quadrangle, United States

USGS Publications Warehouse

State compilations by Lineback, Jerry A.; Bleuer, Ned K.; Mickelson, David M.; Farrand, William R.; Goldthwait, Richard P.; Edited and integrated by Richmond, Gerald M.; Fullerton, David S.

1983-01-01

The Quaternary Geologic Map of the Chicago 4 degree x 6 degree Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the 'ground' on which we walk, the 'dirt' in which we dig foundations, and the 'soil' in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale.

Quaternary geologic map of the Sudbury 4 degree by 6 degree quadrangle, United States and Canada

USGS Publications Warehouse

Fullerton, David S.; Sado, Edward V.; Baker, C.L.; Farrand, William R.

2004-01-01

The Quaternary Geologic Map of the Sudbury 4 degrees x 6 degrees Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the 'ground' on which we walk, the 'dirt' in which we dig foundations, and the 'soil' in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale.

Quaternary geologic map of the Ottawa 4 degrees x 6 degrees quadrangle, United States and Canada

USGS Publications Warehouse

Fullerton, David S.; Gadd, N. R.; Veillette, J.J.; Wagner, P.W.; Chapman, W.F.

1993-01-01

The Quaternary Geologic Map of the Ottawa 4 degree x 6 degree Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the 'ground' on which we walk, the 'dirt' in which we dig foundations, and the 'soil' in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale.

Quaternary geologic map of the Dallas 4° x 6° quadrangle, United States

USGS Publications Warehouse

State compilations by Luza, Kenneth V.; Jensen, Kathryn M.; Fishman, W.D.; Wermund, E.G.; Richmond, Gerald Martin; edited and integrated by Richmond, Gerald Martin; Christiansen, Ann Coe; Bush, Charles A.

1994-01-01

The Quaternary Geologic Map of the Dallas 4° x 6° Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the Earth. They make up the ground on which we walk, the dirt in which we dig foundations, and the soil in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale.

Quaternary geologic map of the Chesapeake Bay 4 degrees x 6 degrees quadrangle, United States

USGS Publications Warehouse

State compilations by Cleaves, Emery T.; Glaser, John D.; Howard, Alan D.; Johnson, Gerald H.; Wheeler, Walter H.; Sevon, William D.; Judson, Sheldon; Owens, James P.; Peebles, Pamela C.; edited and integrated by Richmond, Gerald Martin; Fullerton, David S.; Weide, David L.

1987-01-01

The Quaternary Geologic Map of the Chesapeake Bay 4? x 6? Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the Earth. They make up the 'ground' on which we walk, the 'dirt' in which we dig foundations, and the 'soil' in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale.

Quaternary geologic map of the Lake Superior 4 degrees x 6 degrees quadrangle, United States and Canada

USGS Publications Warehouse

Richmond, Gerald M.; Fullerton, David S.; state compilations by Farrand, William R.; Mickelson, D.M.; Cowan, W.R.; Goebel, J.E.; edited and integrated by Richmond, Gerald Martin

1984-01-01

The Quaternary Geologic Map of the Lake Superior 4? x 6? Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the 'ground' on which we walk, the 'dirt' in which we dig foundations, and the 'soil' in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale.

Quaternary geologic map of the Hudson River 4 degree x 6 degree quadrangle, United States and Canada

USGS Publications Warehouse

State and province compilations by Fullerton, David S.; Sevon, William D.; Muller, Ernest H.; Judson, Sheldon; Black, Robert F.; Wagner, Phillip W.; Hartshorn, Joseph H.; Chapman, William F.; Cowan, William D.; edited and integrated by Fullerton, David S.

1992-01-01

The Quaternary Geologic Map of the Hudson River 4? x 6? Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the 'ground' on which we walk, the 'dirt' in which we dig foundations, and the 'soil' in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale.

Quaternary geologic map of the Ozark Plateau 4 ° x 6 ° quadrangle, United States

USGS Publications Warehouse

State compilations by Whitfield, John William; Ward, R.A.; Denne, J.E.; Holbrook, D.F.; Bush, W.V.; Lineback, J.A.; Luza, K.V.; Jensen, Kathleen M.; Fishman, W.D.; Richmond, Gerald Martin; Weide, David L.; Bush, Charles A.

1993-01-01

The Quaternary Geologic Map of the Ozark Plateau 4° x 6° Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the "ground" on which we walk, the "dirt" in which we dig foundations, and the "soil" in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale.

Quaternary geologic map of the Boston 4 degrees x 6 degrees quadrangle, United States and Canada

USGS Publications Warehouse

State compilations by Hartshorn, Joseph H.; Thompson, W.B.; Chapman, W.F.; Black, R.F.; Richmond, Gerald Martin; Grant, D.R.; Fullerton, David S.; edited and integrated by Richmond, Gerald Martin

1991-01-01

The Quaternary Geologic Map of the Boston 4 deg x 6 deg Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the 'ground' on which we walk, the 'dirt' in which we dig foundations, and the 'soil' in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale.

A study of the utilization of ERTS-1 data from the Wabash River Basin

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1974-01-01

The author has identified the following significant results. The identification and area estimation of crops experiment tested the usefulness of ERTS data for crop survey and produced results indicating that crop statistics could be obtained from ERTS imagery. Soil association mapping results showed that strong relationships exist between ERTS data derived maps and conventional soil maps. Urban land use analysis experiment results indicate potential for accurate gross land use mapping. Water resources mapping demonstrated the feasibility of mapping water bodies using ERTS imagery.

Can next-generation soil data products improve soil moisture modelling at the continental scale? An assessment using a new microclimate package for the R programming environment

NASA Astrophysics Data System (ADS)

Kearney, Michael R.; Maino, James L.

2018-06-01

Accurate models of soil moisture are vital for solving core problems in meteorology, hydrology, agriculture and ecology. The capacity for soil moisture modelling is growing rapidly with the development of high-resolution, continent-scale gridded weather and soil data together with advances in modelling methods. In particular, the GlobalSoilMap.net initiative represents next-generation, depth-specific gridded soil products that may substantially increase soil moisture modelling capacity. Here we present an implementation of Campbell's infiltration and redistribution model within the NicheMapR microclimate modelling package for the R environment, and use it to assess the predictive power provided by the GlobalSoilMap.net product Soil and Landscape Grid of Australia (SLGA, ∼100 m) as well as the coarser resolution global product SoilGrids (SG, ∼250 m). Predictions were tested in detail against 3 years of root-zone (3-75 cm) soil moisture observation data from 35 monitoring sites within the OzNet project in Australia, with additional tests of the finalised modelling approach against cosmic-ray neutron (CosmOz, 0-50 cm, 9 sites from 2011 to 2017) and satellite (ASCAT, 0-2 cm, continent-wide from 2007 to 2009) observations. The model was forced by daily 0.05° (∼5 km) gridded meteorological data. The NicheMapR system predicted soil moisture to within experimental error for all data sets. Using the SLGA or the SG soil database, the OzNet soil moisture could be predicted with a root mean square error (rmse) of ∼0.075 m3 m-3 and a correlation coefficient (r) of 0.65 consistently through the soil profile without any parameter tuning. Soil moisture predictions based on the SLGA and SG datasets were ≈ 17% closer to the observations than when using a chloropleth-derived soil data set (Digital Atlas of Australian Soils), with the greatest improvements occurring for deeper layers. The CosmOz observations were predicted with similar accuracy (r = 0.76 and rmse of ∼0.085 m3 m-3). Comparisons at the continental scale to 0-2 cm satellite data (ASCAT) showed that the SLGA/SG datasets increased model fit over simulations using the DAAS soil properties (r ∼ 0.63 &rmse 15% vs. r 0.48 &rmse 18%, respectively). Overall, our results demonstrate the advantages of using GlobalSoilMap.net products in combination with gridded weather data for modelling soil moisture at fine spatial and temporal resolution at the continental scale.

The Use of AIS Data for Identifying and Mapping Calcareous Soils in Western Nebraska

NASA Technical Reports Server (NTRS)

Samson, S. A.

1985-01-01

The identification of calcareous soils, through unique spectral responses of the vegetation to the chemical nature of calcareous soils, can improve the accuracy of delineating the boundaries of soil mapping units over conventional field techniques. The objective of this experiment is to evaluate the use of the Airborne Imaging Spectrometer (AIS) in the identification and delineation of calcareous soils in the western Sandhills of Nebraska. Based upon statistical differences found in separating the spectral curves below 1.3 microns, calcareous and non-calcareous soils may be identified by differences in species of vegetation. Additional work is needed to identify biogeochemical differences between the two soils.

Quaternary geologic map of the Florida Keys 4 degrees x 6 degrees quadrangle, United States

USGS Publications Warehouse

Compilations: Scott, Thomas M.; Knapp, Michael S.; Weide, David L.; Edited and integrated by Richmond, Gerald M.; Fullerton, David S.; Bush, Charles A.

2010-01-01

This map is part of the Quaternary Geologic Atlas of the United States (I-1420). It was first published as a printed edition in 1986. The geologic data have now been captured digitally and are presented here along with images of the printed map sheet and component parts as PDF files. The Quaternary Geologic Map of the Florida Keys 4 degrees x 6 degrees Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the Earth. They make up the ground on which we walk, the dirt in which we dig foundations, and the soil in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale. In recent years, surficial deposits and materials have become the focus of much interest by scientists, environmentalists, governmental agencies, and the general public. They are the foundations of ecosystems, the materials that support plant growth and animal habitat, and the materials through which travels much of the water required for our agriculture, our industry, and our general well being. They also are materials that easily can become contaminated by pesticides, fertilizers, and toxic wastes. In this context, the value of the surficial geologic map is evident.

Quaternary geologic map of the Mobile 4 degrees x 6 degrees quadrangle, United States

USGS Publications Warehouse

State compilations by Copeland, Charles W.; Rheams, K.F.; Neathery, T.L.; Gilliland, W.A.; Schmidt, Walter; Clark, W.C.; Pope, D.E.; edited and integrated by Richmond, Gerald Martin; Fullerton, David S.; Weide, David L.; Digital database by Bush, Charles A.

1988-01-01

This map is part of the Quaternary Geologic Atlas of the United States (I-1420). It was first published as a printed edition in 1988. The geologic data have now been captured digitally and are presented here along with images of the printed map sheet and component parts as PDF files. The Quaternary Geologic Map of the Mobile 4 degrees x 6 degrees Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the Earth. They make up the ground on which we walk, the dirt in which we dig foundations, and the soil in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale. In recent years, surficial deposits and materials have become the focus of much interest by scientists, environmentalists, governmental agencies, and the general public. They are the foundations of ecosystems, the materials that support plant growth and animal habitat, and the materials through which travels much of the water required for our agriculture, our industry, and our general well being. They also are materials that easily can become contaminated by pesticides, fertilizers, and toxic wastes. In this context, the value of the surficial geologic map

Quaternary geologic map of the Lookout Mountain 4° x 6° quadrangle, United States

USGS Publications Warehouse

State compilations by Miller, Robert A.; Maher, Stuart W.; Copeland, Charles W.; Rheams, Katherine F.; Neathery, Thorton L.; Gilliland, William A.; Friddell, Michael S.; Van Nostrand, Arnie K.; Wheeler, Walter H.; Holbrook, Drew F.; Bush, William V.; Edited and integrated by Richmond, Gerald M.; Fullerton, David S.; Bush, Charles A.

1988-01-01

This map is part of the Quaternary Geologic Atlas of the United States (I–1420). It was first published as a printed edition in 1988. The geologic data have now been captured digitally and are presented here along with images of the printed map sheet and component parts as PDF files. The Quaternary Geologic Map of the Lookout Mountain 4° x 6° Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the Earth. They make up the "ground" on which we walk, the "dirt" in which we dig foundations, and the "soil" in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale. In recent years, surficial deposits and materials have become the focus of much interest by scientists, environmentalists, governmental agencies, and the general public. They are the foundations of ecosystems, the materials that support plant growth and animal habitat, and the materials through which travels much of the water required for our agriculture, our industry, and our general well being. They also are materials that easily can become contaminated by pesticides, fertilizers, and toxic wastes. In this context, the value of the surficial geologic map is evident.

Quaternary geologic map of the Vicksburg 4° x 6° quadrangle, United States

USGS Publications Warehouse

State compilations by Holbrook, Drew F.; Gilliland, W.A.; Luza, K.V.; Pope, D.E.; Wermund, E.G.; Miller, R.A.; Bush, W.V.; Jensen, K.N.; Fishman, W.D.; edited and integrated by Richmond, Gerald Martin; Fullerton, David S.; Weide, David L.; Bush, Charles A.

1990-01-01

This map is part of the Quaternary Geologic Atlas of the United States (I-1420). It was first published as a printed edition in 1990. The geologic data have now been captured digitally and are presented here along with images of the printed map sheet and component parts as PDF files. The Quaternary Geologic Map of the Vicksburg 4° x 6° Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the Earth. They make up the ground on which we walk, the dirt in which we dig foundations, and the soil in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale. In recent years, surficial deposits and materials have become the focus of much interest by scientists, environmentalists, governmental agencies, and the general public. They are the foundations of ecosystems, the materials that support plant growth and animal habitat, and the materials through which travels much of the water required for our agriculture, our industry, and our general well being. They also are materials that easily can become contaminated by pesticides, fertilizers, and toxic wastes. In this context, the value of the surficial geologic map is evident.

Quaternary geologic map of the White Lake 4° x 6° quadrangle, United States

USGS Publications Warehouse

State compilations by Pope, David E.; Gilliland, William A.; Wermund, E.G.; edited and integrated by Richmond, Gerald Martin; Weide, David L.; Moore, David W.; Bush, Charles A.

1990-01-01

This map is part of the Quaternary Geologic Atlas of the United States (I-1420). It was first published as a printed edition in 1990. The geologic data have now been captured digitally and are presented here along with images of the printed map sheet and component parts as PDF files. The Quaternary Geologic Map of the White Lake 4° x 6° Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the Earth. They make up the ground on which we walk, the dirt in which we dig foundations, and the soil in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale. In recent years, surficial deposits and materials have become the focus of much interest by scientists, environmentalists, governmental agencies, and the general public. They are the foundations of ecosystems, the materials that support plant growth and animal habitat, and the materials through which travels much of the water required for our agriculture, our industry, and our general well being. They also are materials that easily can become contaminated by pesticides, fertilizers, and toxic wastes. In this context, the value of the surficial geologic map is evident.

Quaternary geologic map of the Monterrey 4 degrees x 6 degrees quadrangle, United States

USGS Publications Warehouse

Moore, David W.; Wermund, E.G.; edited and integrated by Moore, David W.; Richmond, Gerald Martin

1993-01-01

This map is part of the Quaternary Geologic Atlas of the United States (I-1420). It was first published as a printed edition in 1993. The geologic data have now been captured digitally and are presented here along with images of the printed map sheet and component parts as PDF files. The Quaternary Geologic Map of the Monterrey 4 degrees x 6 degrees Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the Earth. They make up the ground on which we walk, the dirt in which we dig foundations, and the soil in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale. In recent years, surficial deposits and materials have become the focus of much interest by scientists, environmentalists, governmental agencies, and the general public. They are the foundations of ecosystems, the materials that support plant growth and animal habitat, and the materials through which travels much of the water required for our agriculture, our industry, and our general well being. They also are materials that easily can become contaminated by pesticides, fertilizers, and toxic wastes. In this context, the value of the surficial geologic map is evident.

Quaternary geologic map of the Austin 4° x 6° quadrangle, United States

USGS Publications Warehouse

State compilations by Moore, David W.; Wermund, E.G.; edited and integrated by Moore, David W.; Richmond, Gerald Martin; Christiansen, Ann Coe; Bush, Charles A.

1993-01-01

This map is part of the Quaternary Geologic Atlas of the United States (I-1420). It was first published as a printed edition in 1993. The geologic data have now been captured digitally and are presented here along with images of the printed map sheet and component parts as PDF files. The Quaternary Geologic Map of the Austin 4° x 6° Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the Earth. They make up the ground on which we walk, the dirt in which we dig foundations, and the soil in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale. In recent years, surficial deposits and materials have become the focus of much interest by scientists, environmentalists, governmental agencies, and the general public. They are the foundations of ecosystems, the materials that support plant growth and animal habitat, and the materials through which travels much of the water required for our agriculture, our industry, and our general well being. They also are materials that easily can become contaminated by pesticides, fertilizers, and toxic wastes. In this context, the value of the surficial geologic map is evident.

Quaternary geologic map of the Wichita 4 degrees x 6 degrees quadrangle, United States

USGS Publications Warehouse

State compilations by Denne, Jane E.; Luza, V.; Richmond, Gerald Martin; Jensen, Kathleen M.; Fishman, W.D.; Wermund, E.G.; Richmond, Gerald Martin; Christiansen, Ann Coe; Bush, Charles A.

1993-01-01

This map is part of the Quaternary Geologic Atlas of the United States (I-1420). It was first published as a printed edition in 1993. The geologic data have now been captured digitally and are presented here along with images of the printed map sheet and component parts as PDF files. The Quaternary Geologic Map of the Wichita 4° x 6° Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the "ground" on which we walk, the "dirt" in which we dig foundations, and the "soil" in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale. In recent years, surficial deposits and materials have become the focus of much interest by scientists, environmentalists, governmental agencies, and the general public. They are the foundations of ecosystems, the materials that support plant growth and animal habitat, and the materials through which travels much of the water required for our agriculture, our industry, and our general well being. They also are materials that easily can become contaminated by pesticides, fertilizers, and toxic wastes. In this context, the value of the surficial geologic map is evident.

Quaternary geologic map of the Jacksonville 4 degrees x 6 degrees quadrangle, United States

USGS Publications Warehouse

State compilations by Scott, Thomas M.; Knapp, M.S.; Friddell, M.S.; Weide, David L.; edited and integrated by Richmond, Gerald Martin; Fullerton, David S.

1986-01-01

This map is part of the Quaternary Geologic Atlas of the United States (I-1420). It was first published as a printed edition in 1986. The geologic data have now been captured digitally and are presented here along with images of the printed map sheet and component parts as PDF files. The Quaternary Geologic Map of the Jacksonville 4 degrees x 6 degrees Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the Earth. They make up the ground on which we walk, the dirt in which we dig foundations, and the soil in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale. In recent years, surficial deposits and materials have become the focus of much interest by scientists, environmentalists, governmental agencies, and the general public. They are the foundations of ecosystems, the materials that support plant growth and animal habitat, and the materials through which travels much of the water required for our agriculture, our industry, and our general well being. They also are materials that easily can become contaminated by pesticides, fertilizers, and toxic wastes. In this context, the value of the surficial geologic map is evident.

High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models

PubMed Central

Welp, Gerhard; Thiel, Michael

2017-01-01

Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties–sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen–in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models–multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)–were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources. PMID:28114334

High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models.

PubMed

Forkuor, Gerald; Hounkpatin, Ozias K L; Welp, Gerhard; Thiel, Michael

2017-01-01

Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties-sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen-in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models-multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)-were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources.

The Soil Series in Soil Classifications of the United States

NASA Astrophysics Data System (ADS)

Indorante, Samuel; Beaudette, Dylan; Brevik, Eric C.

2014-05-01

Organized national soil survey began in the United States in 1899, with soil types as the units being mapped. The soil series concept was introduced into the U.S. soil survey in 1903 as a way to relate soils being mapped in one area to the soils of other areas. The original concept of a soil series was all soil types formed in the same parent materials that were of the same geologic age. However, within about 15 years soil series became the primary units being mapped in U.S. soil survey. Soil types became subdivisions of soil series, with the subdivisions based on changes in texture. As the soil series became the primary mapping unit the concept of what a soil series was also changed. Instead of being based on parent materials and geologic age, the soil series of the 1920s was based on the morphology and composition of the soil profile. Another major change in the concept of soil series occurred when U.S. Soil Taxonomy was released in 1975. Under Soil Taxonomy, the soil series subdivisions were based on the uses the soils might be put to, particularly their agricultural uses (Simonson, 1997). While the concept of the soil series has changed over the years, the term soil series has been the longest-lived term in U.S. soil classification. It has appeared in every official classification system used by the U.S. soil survey (Brevik and Hartemink, 2013). The first classification system was put together by Milton Whitney in 1909 and had soil series at its second lowest level, with soil type at the lowest level. The second classification system used by the U.S. soil survey was developed by C.F. Marbut, H.H. Bennett, J.E. Lapham, and M.H. Lapham in 1913. It had soil series at the second highest level, with soil classes and soil types at more detailed levels. This was followed by another system in 1938 developed by M. Baldwin, C.E. Kellogg, and J. Thorp. In this system soil series were again at the second lowest level with soil types at the lowest level. The soil type concept was dropped and replaced by the soil phase in the 1950s in a modification of the 1938 Baldwin et al. classification (Simonson, 1997). When Soil Taxonomy was released in 1975, soil series became the most detailed (lowest) level of the classification system, and the only term maintained throughout all U.S. classifications to date. While the number of recognized soil series have increased steadily throughout the history of U.S. soil survey, there was a rapid increase in the recognition of new soil series following the introduction of Soil Taxonomy (Brevik and Hartemink, 2013). References Brevik, E.C., and A.E. Hartemink. 2013. Soil maps of the United States of America. Soil Science Society of America Journal 77:1117-1132. doi:10.2136/sssaj2012.0390. Simonson, R.W. 1997. Evolution of soil series and type concepts in the United States. Advances in Geoecology 29:79-108.

Comparing physiographic maps with different categorisations

NASA Astrophysics Data System (ADS)

Zawadzka, J.; Mayr, T.; Bellamy, P.; Corstanje, R.

2015-02-01

This paper addresses the need for a robust map comparison method suitable for finding similarities between thematic maps with different forms of categorisations. In our case, the requirement was to establish the information content of newly derived physiographic maps with regards to set of reference maps for a study area in England and Wales. Physiographic maps were derived from the 90 m resolution SRTM DEM, using a suite of existing and new digital landform mapping methods with the overarching purpose of enhancing the physiographic unit component of the Soil and Terrain database (SOTER). Reference maps were seven soil and landscape datasets mapped at scales ranging from 1:200,000 to 1:5,000,000. A review of commonly used statistical methods for categorical comparisons was performed and of these, the Cramer's V statistic was identified as the most appropriate for comparison of maps with different legends. Interpretation of multiple Cramer's V values resulting from one-by-one comparisons of the physiographic and baseline maps was facilitated by multi-dimensional scaling and calculation of average distances between the maps. The method allowed for finding similarities and dissimilarities amongst physiographic maps and baseline maps and informed the recommendation of the most suitable methodology for terrain analysis in the context of soil mapping.

Effective use of ERTS multisensor data in the Great Plains

NASA Technical Reports Server (NTRS)

Myers, V. I. (Principal Investigator)

1972-01-01

The author has identified the following significant results. One unique advantage of ERTS imagery for delineating soil associations is the large area that can be scanned with one photo. Although soil associations usually are published at scales of 1:500,000 or 1:1,000,000, the delineations are drawn on much larger scale maps covering small pieces of the scene and then pieced together. Alluvial areas are usually swollen out of proportion to other soil areas. ERTS imagery puts alluvial areas into their proper size. A second feature of ERTS imagery is that a soil association map constructed with its aid assures that the cartographic level of the associations is more nearly the same. Another advantage of ERTS imagery is that the actual shape and configuration of soil associations are apparent. Also with ERTS imagery significant new delineations may become apparent which were missed when constructing soil association maps from conventional large scale photos.

Evaluation of freely available ancillary data used for detailed soil mapping in Brazil

NASA Astrophysics Data System (ADS)

Samuel-Rosa, Alessandro; Anjos, Lúcia; Vasques, Gustavo; Heuvelink, Gerard

2014-05-01

Brazil is one of the world's largest food producers, and is home of both largest rainforest and largest supply of renewable fresh water on Earth. However, it lacks detailed soil information in extensive areas of the country. The best soil map covering the entire country was published at a scale of 1:5,000,000. Termination of governmental support for systematic soil mapping in the 1980's made detailed soil mapping of the whole country a very difficult task to accomplish. Nowadays, due to new user-driven demands (e.g. precision agriculture), most detailed soil maps are produced for small size areas. Many of them rely on as is freely available ancillary data, although their accuracy is usually not reported or unknown. Results from a validation exercise that we performed using ground control points from a small hilly catchment (20 km²) in Southern Brazil (-53.7995ºE, -29.6355ºN) indicate that most freely available ancillary data needs some type of correction before use. Georeferenced and orthorectified RapidEye imagery (recently acquired by the Brazilian government) has a horizontal accuracy (root-mean-square error, RMSE) of 37 m, which is worse than the value published in the metadata (32 m). Like any remote sensing imagery, RapidEye imagery needs to be correctly registered before its use for soil mapping. Topographic maps produced by the Brazilian Army and derived geological maps (scale of 1:25,000) have a horizontal accuracy of 65 m, which is more than four times the maximum value allowed by Brazilian legislation (15 m). Worse results were found for geological maps derived from 1:50,000 topographic maps (RMSE = 147 m), for which the maximum allowed value is 30 m. In most cases positional errors are of systematic origin and can be easily corrected (e.g., affine transformation). ASTER GDEM has many holes and is very noisy, making it of little use in the studied area. TOPODATA, which is SRTM kriged from originally 3 to 1 arc-second by the Brazilian National Institute for Space Research, has a vertical accuracy of 19 m and is strongly affected by double-oblique stripes which were intensified by kriging. Many spurious sinks were created which are not easily corrected using either frequency filters or sink-filling algorithms. The exceptions are SRTM v4.1, which is the most vertically accurate DEM available (RMSE = 18.7 m), and Google Earth imagery compiled from various sources (positional accuracy of RMSE = 8 m). It is likely that most mapping efforts will continue to be employed in small size areas to fulfill local user-driven demands in the forthcoming years. Also, many new techniques and technologies will possibly be developed and employed for soil mapping. However, employing better quality ancillary data still is a challenge to be overcome to produce high-quality soil information to allow better decision making and land use policy in Brazil.

Predictable bacterial composition and hydrocarbon degradation in Arctic soils following diesel and nutrient disturbance.

PubMed

Bell, Terrence H; Yergeau, Etienne; Maynard, Christine; Juck, David; Whyte, Lyle G; Greer, Charles W

2013-06-01

Increased exploration and exploitation of resources in the Arctic is leading to a higher risk of petroleum contamination. A number of Arctic microorganisms can use petroleum for growth-supporting carbon and energy, but traditional approaches for stimulating these microorganisms (for example, nutrient addition) have varied in effectiveness between sites. Consistent environmental controls on microbial community response to disturbance from petroleum contaminants and nutrient amendments across Arctic soils have not been identified, nor is it known whether specific taxa are universally associated with efficient bioremediation. In this study, we contaminated 18 Arctic soils with diesel and treated subsamples of each with monoammonium phosphate (MAP), which has successfully stimulated degradation in some contaminated Arctic soils. Bacterial community composition of uncontaminated, diesel-contaminated and diesel+MAP soils was assessed through multiplexed 16S (ribosomal RNA) rRNA gene sequencing on an Ion Torrent Personal Genome Machine, while hydrocarbon degradation was measured by gas chromatography analysis. Diversity of 16S rRNA gene sequences was reduced by diesel, and more so by the combination of diesel and MAP. Actinobacteria dominated uncontaminated soils with <10% organic matter, while Proteobacteria dominated higher-organic matter soils, and this pattern was exaggerated following disturbance. Degradation with and without MAP was predictable by initial bacterial diversity and the abundance of specific assemblages of Betaproteobacteria, respectively. High Betaproteobacteria abundance was positively correlated with high diesel degradation in MAP-treated soils, suggesting this may be an important group to stimulate. The predictability with which bacterial communities respond to these disturbances suggests that costly and time-consuming contaminated site assessments may not be necessary in the future.

Prediction of iron oxide contents using diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Marques, José, Jr.; Arantes Camargo, Livia

2015-04-01

Determining soil iron oxides using conventional analysis is relatively unfeasible when large areas are mapped, with the aim of characterizing spatial variability. Diffuse reflectance spectroscopy (DRS) is rapid, less expensive, non-destructive and sometimes more accurate than conventional analysis. Furthermore, this technique allows the simultaneous characterization of many soil attributes with agronomic and environmental relevance. This study aims to assess the DRS capability to predict iron oxides content -hematite and goethite - , characterizing their spatial variability in soils of Brazil. Soil samples collected from an 800-hectare area were scanned in the visible and near-infrared spectral range. Moreover, chemometric calibration was obtained through partial least-squares regression (PLSR). Then, spatial distribution maps of the attributes were constructed using predicted values from calibrated models through geostatistical methods. The studied area presented soils with varied contents of iron oxides as examples for the Oxisols and Entisols. In the spectra of each soil is observed that the reflectance decreases with the content of iron oxides present in the soil. In soils with a high content of iron oxides can be observed more pronounced concavities between 380 and 1100 nm which are characteristic of the presence of these oxides. In soils with higher reflectance it were observed concavity characteristics due to the presence of kaolinite, in agreement with the low iron contents of those soils. The best accuracy of prediction models [residual prediction deviation (RPD) = 1.7] was obtained for goethite within the visible region (380-800 nm), and for hematite (RPD = 2.0) within the visible near infrared (380-2300 nm). The maps of goethite and hematite predicted showed the spatial distribution pattern similar to the maps of clay and iron extracted by dithionite-citrate-bicarbonate, being consistent with the iron oxide contents of soils present in the study area. These results confirm the value of DRS in the mapping of iron oxides in large areas at detailed scale.

Critical carbon input to maintain current soil organic carbon stocks in global wheat systems

PubMed Central

Wang, Guocheng; Luo, Zhongkui; Han, Pengfei; Chen, Huansheng; Xu, Jingjing

2016-01-01

Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1° × 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha−1 yr−1, with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content. PMID:26759192

Soil Texture Mediates the Response of Tree Cover to Rainfall Intensity in African Savannas

NASA Astrophysics Data System (ADS)

Case, M. F.; Staver, A. C.

2017-12-01

Global circulation models predict widespread shifts in the frequency and intensity of rainfall, even where mean annual rainfall does not change. Resulting changes in soil moisture dynamics could have major consequences for plant communities and ecosystems, but the direction of potential vegetation responses can be challenging to predict. In tropical savannas, where tree and grasses coexist, contradictory lines of evidence have suggested that tree cover could respond either positively or negatively to less frequent, more intense rainfall. Here, we analyzed remote sensing data and continental-scale soils maps to examine whether soil texture or fire could explain heterogeneous responses of savanna tree cover to intra-annual rainfall variability across sub-Saharan Africa. We find that tree cover generally increases with mean wet-season rainfall, decreases with mean wet-season rainfall intensity, and decreases with fire frequency. However, soil sand content mediates these relationships: the response to rainfall intensity switches qualitatively depending on soil texture, such that tree cover decreases dramatically with less frequent, more intense rainfall on clay soils but increases with rainfall intensity on sandy soils in semi-arid savannas. We propose potential ecohydrological mechanisms for this heterogeneous response, and emphasize that predictions of savanna vegetation responses to global change should account for interactions between soil texture and changing rainfall patterns.

Quantified carbon input for maintaining existing soil organic carbon stocks in global wheat systems

NASA Astrophysics Data System (ADS)

Wang, G.

2017-12-01

Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1°× 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha-1 yr-1, with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content.

Mapping forest soil organic matter on New Jersey's coastal plain

Treesearch

Brian J. Clough; Edwin J. Green; Richard B. Lathrop

2012-01-01

Managing forest soil organic matter (SOM) stocks is a vital strategy for reducing the impact of anthropogenic carbon dioxide emissions. However, the SOM pool is highly variable, and developing accurate estimates to guide management decisions has remained a difficult task. We present the results of a spatial model designed to map soil organic matter for all forested...

Field guide for mapping post-fire soil burn severity

Treesearch

Annette Parson; Peter R. Robichaud; Sarah A. Lewis; Carolyn Napper; Jess T. Clark

2010-01-01

Following wildfires in the United States, the U.S. Department of Agriculture and U.S. Department of the Interior mobilize Burned Area Emergency Response (BAER) teams to assess immediate post-fire watershed conditions. BAER teams must determine threats from flooding, soil erosion, and instability. Developing a postfire soil burn severity map is an important first step...

The Use of Electromagnetic Induction Techniques for Soil Mapping

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Doolittle, Jim

2015-04-01

Soils have high natural spatial variability. This has been recognized for a long time, and many methods of mapping that spatial variability have been investigated. One technique that has received considerable attention over the last ~30 years is electromagnetic induction (EMI). Particularly when coupled with modern GPS and GIS systems, EMI techniques have allowed the rapid and relatively inexpensive collection of large spatially-related data sets that can be correlated to soil properties that either directly or indirectly influence electrical conductance in the soil. Soil electrical conductivity is directly controlled by soil water content, soluble salt content, clay content and mineralogy, and temperature. A wide range of indirect controls have been identified, such as soil organic matter content and bulk density; both influence water relationships in the soil. EMI techniques work best in areas where there are large changes in one soil property that influences soil electrical conductance, and don't work as well when soil properties that influence electrical conductance are largely homogenous. This presentation will present examples of situations where EMI techniques were successful as well as a couple of examples of situations where EMI was not so useful in mapping the spatial variability of soil properties. Reasons for both the successes and failures will be discussed.

Detection of terrain indices related to soil salinity and mapping salt-affected soils using remote sensing and geostatistical techniques.

PubMed

Triki Fourati, Hela; Bouaziz, Moncef; Benzina, Mourad; Bouaziz, Samir

2017-04-01

Traditional surveying methods of soil properties over landscapes are dramatically cost and time-consuming. Thus, remote sensing is a proper choice for monitoring environmental problem. This research aims to study the effect of environmental factors on soil salinity and to map the spatial distribution of this salinity over the southern east part of Tunisia by means of remote sensing and geostatistical techniques. For this purpose, we used Advanced Spaceborne Thermal Emission and Reflection Radiometer data to depict geomorphological parameters: elevation, slope, plan curvature (PLC), profile curvature (PRC), and aspect. Pearson correlation between these parameters and soil electrical conductivity (EC soil ) showed that mainly slope and elevation affect the concentration of salt in soil. Moreover, spectral analysis illustrated the high potential of short-wave infrared (SWIR) bands to identify saline soils. To map soil salinity in southern Tunisia, ordinary kriging (OK), minimum distance (MD) classification, and simple regression (SR) were used. The findings showed that ordinary kriging technique provides the most reliable performances to identify and classify saline soils over the study area with a root mean square error of 1.83 and mean error of 0.018.

Mapping Surface Soil Organic Carbon for Crop Fields with Remote Sensing

NASA Technical Reports Server (NTRS)

Chen, Feng; Kissel, David E.; West, Larry T.; Rickman, Doug; Luvall, J. C.; Adkins, Wayne

2004-01-01

The organic C concentration of surface soil can be used in agricultural fields to vary crop production inputs. Organic C is often highly spatially variable, so that maps of soil organic C can be used to vary crop production inputs using precision farming technology. The objective of this research was to demonstrate the feasibility of mapping soil organic C on three fields, using remotely sensed images of the fields with a bare surface. Enough soil samples covering the range in soil organic C must be taken from each field to develop a satisfactory relationship between soil organic C content and image reflectance values. The number of soil samples analyzed in the three fields varied from 22 to 26. The regression equations differed between fields, but gave highly significant relationships with R2 values of 0.93, 0.95, and 0.89 for the three fields. A comparison of predicted and measured values of soil organic C for an independent set of 2 soil samples taken on one of the fields gave highly satisfactory results, with a comparison equation of % organic C measured + 1.02% organic C predicted, with r2 = 0.87.

Geologic research in support of sustainable agriculture

USGS Publications Warehouse

Gough, L.P.; Herring, J.R.

1993-01-01

The importance and role of the geosciences in studies of sustainable agriculture include such traditional research areas as, agromineral resource assessments, the mapping and classification of soils and soil amendments, and the evaluation of landscapes for their vulnerability to physical and chemical degradation. Less traditional areas of study, that are increasing in societal importance because of environmental concerns and research into sustainable systems in general, include regional geochemical studies of plant and animal trace element deficiencies and toxicities, broad-scale water quality investigations, agricultural chemicals and the hydrogeologic interface, and minimally processed and ion-exchange agrominerals. We discuss the importance and future of phosphate in the US and world based on human population growth, projected agromineral demands in general, and the unavailability of new, high-quality agricultural lands. We also present examples of studies that relate geochemistry and the hydrogeologic characteristics of a region to the bioavailability and cycling of trace elements important to sustainable agricultural systems. ?? 1993.

Cartographic modeling of heterogeneous landscape for footprint analysis of Eddy Covariance Measurements (Central Forest and Central Chernozem reserves, Russia)

NASA Astrophysics Data System (ADS)

Kozlov, Daniil

2014-05-01

The topographical, soil and vegetation maps of FLUXNET study areas are widely used for interpretation of eddy covariance measurements, for calibration of biogeochemical models and for making regional assessments of carbon balance. The poster presents methodological problems and results of ecosystem mapping using GIS, remote sensing, statistical and field methods on the example of two RusFluxNet sites in the Central Forest (33° E, 56°30'N) and Central Chernozem (36°10' E, 51°36'N) reserves. In the Central Forest reserve tacheometric measurements were used for topographical and peat surveys of bogged sphagnum spruce forest of 20-hectare area. Its common borders and its areas affected by windfall were determined. The supplies and spatial distribution of organic matter were obtained. The datasets of groundwater monitoring measurements on ten wells were compared with each other and the analysis of spatial and temporal groundwater variability was performed. The map of typical ecosystems of the reserve and its surroundings was created on the basis of analysis of multi-temporal Landsat images. In the Central Chernozem reserve the GNSS topographical survey was used for flux tower footprint mapping (22 ha). The features of microrelief predetermine development of different soils within the footprint. Close relationship between soil (73 drilling site) and terrain attributes (DEM with 2.5 m) allowed to build maps of soils and soil properties: carbon content, bulk density, upper boundary of secondary carbonates. Position for chamber-based soil respiration measurements was defined on the basis of these maps. The detailed geodetic and soil surveys of virgin lands and plowland were performed in order to estimate the effect of agrogenic processes such as dehumification, compaction and erosion on soils during the whole period of agricultural use of Central Chernozem reserve area and around. The choice of analogous soils was based on the similarity of their position within the landscape as judged from the terrain attributes of the DEM. The dynamics of soil cover during the last 50 years was estimated on the basis of repetitive detailed surveys of the five key plots conducted in 1963, 1984 and 2013. All results of this study and map analysis conclusions are presented in the poster.

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function

PubMed Central

Groenendyk, Derek G.; Ferré, Ty P.A.; Thorp, Kelly R.; Rice, Amy K.

2015-01-01

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth’s surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function. PMID:26121466

High-resolution Mapping of Permafrost and Soil Freeze/thaw Dynamics in the Tibetan Plateau Based on Multi-sensor Satellite Observations

NASA Astrophysics Data System (ADS)

Zhang, W.; Yi, Y.; Yang, K.; Kimball, J. S.

2016-12-01

The Tibetan Plateau (TP) is underlain by the world's largest extent of alpine permafrost ( 2.5×106 km2), dominated by sporadic and discontinuous permafrost with strong sensitivity to climate warming. Detailed permafrost distributions and patterns in most of the TP region are still unknown due to extremely sparse in-situ observations in this region characterized by heterogeneous land cover and large temporal dynamics in surface soil moisture conditions. Therefore, satellite-based temperature and moisture observations are essential for high-resolution mapping of permafrost distribution and soil active layer changes in the TP region. In this study, we quantify the TP regional permafrost distribution at 1-km resolution using a detailed satellite data-driven soil thermal process model (GIPL2). The soil thermal model is calibrated and validated using in-situ soil temperature/moisture observations from the CAMP/Tibet field campaign (9 sites: 0-300 cm soil depth sampling from 1997-2007), a multi-scale soil moisture and temperature monitoring network in the central TP (CTP-SMTMN, 57 sites: 5-40 cm, 2010-2014) and across the whole plateau (China Meteorology Administration, 98 sites: 0-320 cm, 2000-2015). Our preliminary results using the CAMP/Tibet and CTP-SMTMN network observations indicate strong controls of surface thermal and soil moisture conditions on soil freeze/thaw dynamics, which vary greatly with underlying topography, soil texture and vegetation cover. For regional mapping of soil freeze/thaw and permafrost dynamics, we use the most recent soil moisture retrievals from the NASA SMAP (Soil Moisture Active Passive) sensor to account for the effects of temporal soil moisture dynamics on soil thermal heat transfer, with surface thermal conditions defined by MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature records. Our study provides the first 1-km map of spatial patterns and recent changes of permafrost conditions in the TP.

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function.

PubMed

Groenendyk, Derek G; Ferré, Ty P A; Thorp, Kelly R; Rice, Amy K

2015-01-01

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth's surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function.

Duplicate and Conquer: Multiple Homologs of PHOSPHORUS-STARVATION TOLERANCE1 Enhance Phosphorus Acquisition and Sorghum Performance on Low-Phosphorus Soils1[C][W][OPEN

PubMed Central

Hufnagel, Barbara; de Sousa, Sylvia M.; Assis, Lidianne; Guimaraes, Claudia T.; Leiser, Willmar; Azevedo, Gabriel C.; Negri, Barbara; Larson, Brandon G.; Shaff, Jon E.; Pastina, Maria Marta; Barros, Beatriz A.; Weltzien, Eva; Rattunde, Henry Frederick W.; Viana, Joao H.; Clark, Randy T.; Falcão, Alexandre; Gazaffi, Rodrigo; Garcia, Antonio Augusto F.; Schaffert, Robert E.; Kochian, Leon V.; Magalhaes, Jurandir V.

2014-01-01

Low soil phosphorus (P) availability is a major constraint for crop production in tropical regions. The rice (Oryza sativa) protein kinase, PHOSPHORUS-STARVATION TOLERANCE1 (OsPSTOL1), was previously shown to enhance P acquisition and grain yield in rice under P deficiency. We investigated the role of homologs of OsPSTOL1 in sorghum (Sorghum bicolor) performance under low P. Association mapping was undertaken in two sorghum association panels phenotyped for P uptake, root system morphology and architecture in hydroponics and grain yield and biomass accumulation under low-P conditions, in Brazil and/or in Mali. Root length and root surface area were positively correlated with grain yield under low P in the soil, emphasizing the importance of P acquisition efficiency in sorghum adaptation to low-P availability. SbPSTOL1 alleles reducing root diameter were associated with enhanced P uptake under low P in hydroponics, whereas Sb03g006765 and Sb03g0031680 alleles increasing root surface area also increased grain yield in a low-P soil. SbPSTOL1 genes colocalized with quantitative trait loci for traits underlying root morphology and dry weight accumulation under low P via linkage mapping. Consistent allelic effects for enhanced sorghum performance under low P between association panels, including enhanced grain yield under low P in the soil in Brazil, point toward a relatively stable role for Sb03g006765 across genetic backgrounds and environmental conditions. This study indicates that multiple SbPSTOL1 genes have a more general role in the root system, not only enhancing root morphology traits but also changing root system architecture, which leads to grain yield gain under low-P availability in the soil. PMID:25189534

Effect of spatial variability on solute velocity and dispersion in two soils of the Argentinian Pampas

NASA Astrophysics Data System (ADS)

Aparicio, Virginia; Costa, José; Domenech, Marisa; Castro Franco, Mauricio

2013-04-01

Predicting how solutes move through the unsaturated zone is essential to determine the potential risk of groundwater contamination (Costa et al., 1994). The estimation of the spatial variability of solute transport parameters, such as velocity and dispersion, enables a more accurate understanding of transport processes. Apparent electrical conductivity (ECa) has been used to characterize the spatial behavior of soil properties. The objective of this study was to characterize the spatial variability of soil transport parameters at field scale using ECa measurements. ECa measurements of 42 ha (Tres Arroyos) and 50 ha (Balcarce) farms were collected for the top 0-30 cm (ECa(s)) soil using the Veris® 3100. ECa maps were generated using geostatistical interpolation techniques. From these maps, three general areas were delineated, named high, medium, and low ECa zones. At each zone, three sub samples were collected. Soil samples were taken at 0-30 cm. Clay content and organic matter (OM) was analyzed. The transport assay was performed in the laboratory using undisturbed soil columns, under controlled conditions of T ° (22 ° C).Br- determinations were performed with a specific Br- electrode. The breakthrough curves were fitted using the model CXTFIT 2.1 (Toride et al., 1999) to estimate the transport parameters Velocity (V) and Dispersion (D). In this study we found no statistical significant differences for V and D between treatments. Also, there were no differences in V and D between sites. The average V and D value was 9.3 cm h-1 and 357.5 cm2 h-2, respectively. Despite finding statistically significant differences between treatments for the other measured physical and chemical properties, in our work it was not possible to detect the spatial variability of solute transport parameters.

Revisiting Melton: Analyzing the correlation structure of geomorphological and climatological parameters

NASA Astrophysics Data System (ADS)

Carothers, R. A.; Sangireddy, H.; Passalacqua, P.

2013-12-01

In his expansive 1957 study of over 80 basins in Arizona, Colorado, New Mexico, and Utah, Mark Melton measured key morphometric, soil, land cover, and climatic parameters [Melton, 1957]. He identified correlations between morphological parameters and climatic regimes in an attempt to characterize the geomorphology of the basin as a function of climate and vegetation. Using modern techniques such as high resolution digital terrain models in combination with high spatial resolution weather station records, vector soil maps, seamless raster geological data, and land cover vector maps, we revisit Melton's 1957 dataset with the following hypotheses: (1) Patterns of channelization carry strong, codependent signatures in the form of statistical correlations of rainfall variability, soil type, and vegetation patterns. (2) Channelization patterns reflect the erosion processes on sub-catchment scale and the subsequent processes of vegetation recovery and gullying. In order to characterize various topographic and climatic parameters, we obtain elevation and land cover data from the USGS National Elevation dataset, climate data from the Western Regional Climate Center and PRISM climate group database, and soil type from the USDA STATSGO soil database. We generate a correlative high resolution database on vegetation, soil cover, lithology, and climatology for the basins identified by Melton in his 1957 study. Using the GeoNet framework developed by Passalacqua et al. [2010], we extract various morphological parameters such as slope, drainage density, and stream frequency. We also calculate metrics for patterns of channelization such as number of channelized pixels in a basin and channel head density. In order to understand the correlation structure between climate and morphological variables, we compute the Pearson's correlation coefficient similar to Melton's analysis and also explore other statistical procedures to characterize the feedbacks between these variables. By identifying the differences in Melton's and our results, we address the influence of climate over the degree of channel dissection in the landscape. References: Melton, M. A. (1957). An analysis of the relations among elements of climate, surface properties, and geomorphology (No. CU-TR-11). COLUMBIA UNIV NEW YORK Passalacqua, P., Do Trung, T., Foufoula-Georgiou, E., Sapiro, G., & Dietrich, W. E. (2010). A geometric framework for channel network extraction from lidar: Nonlinear diffusion and geodesic paths. Journal of Geophysical Research: Earth Surface (2003-2012), 115(F1). PRISM Climate Group, Oregon State University, http://prism.oregonstate.edu, created 4 Feb 2004 Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture. U.S. General Soil Map (STATSGO2). Available online at http://soildatamart.nrcs.usda.gov USGS National Map Viewer, United States Geological Survey. Web. 10 June 2013. http://viewer.nationalmap.gov/viewer/ Western U.S. Historical Climate Summaries, Western Regional Climate Group, 2013. Web. 10 June 2013. http://www.wrcc.dri.edu/Climsum.html

Three-dimensional prediction of soil physical, chemical, and hydrological properties in a forested catchment of the Santa Catalina CZO

NASA Astrophysics Data System (ADS)

Shepard, C.; Holleran, M.; Lybrand, R. A.; Rasmussen, C.

2014-12-01

Understanding critical zone evolution and function requires an accurate assessment of local soil properties. Two-dimensional (2D) digital soil mapping provides a general assessment of soil characteristics across a sampled landscape, but lacks the ability to predict soil properties with depth. The utilization of mass-preserving spline functions enable the extrapolation of soil properties with depth, extending predictive functions to three-dimensions (3D). The present study was completed in the Marshall Gulch (MG) catchment, located in the Santa Catalina Mountains, 30 km northwest of Tucson, Arizona, as part of the Santa Catalina-Jemez Mountains Critical Zone Observatory. Twenty-four soil pits were excavated and described following standard procedures. Mass-preserving splines were used to extrapolate mass carbon (kg C m-2); percent clay, silt, and sand (%); sodium mass flux (kg Na m-2); and pH for 24 sampled soil pits in 1-cm depth increments. Saturated volumetric water content (θs) and volumetric water content at 10 kPa (θ10) were predicted using ROSETTA and established empirical relationships. The described profiles were all sampled to differing depths; to compensate for the unevenness of the profile descriptions, the soil depths were standardized from 0.0 to 1.0 and then split into five equal standard depth sections. A logit-transformation was used to normalize the target variables. Step-wise regressions were calculated using available environmental covariates to predict the properties of each variable across the catchment in each depth section, and interpolated model residuals added back to the predicted layers to generate the final soil maps. Logit-transformed R2 for the predictive functions varied widely, ranging from 0.20 to 0.79, with logit-transformed RMSE ranging from 0.15 to 2.77. The MG catchment was further classified into clusters with similar properties based on the environmental covariates, and representative depth functions for each target variable in each cluster calculated. Mass-preserving splines combined with stepwise regressions are an effective tool for predicting soil physical, chemical, and hydrological properties with depth, enhancing our understanding of the critical zone.

High-Resolution Global Soil Moisture Map

NASA Image and Video Library

2015-05-19

High-resolution global soil moisture map from NASA SMAP combined radar and radiometer instruments, acquired between May 4 and May 11, 2015 during SMAP commissioning phase. The map has a resolution of 5.6 miles (9 kilometers). The data gap is due to turning the instruments on and off during testing. http://photojournal.jpl.nasa.gov/catalog/PIA19337

Risk of nitrate in groundwaters of the United States - A national perspective

USGS Publications Warehouse

Nolan, B.T.; Ruddy, B.C.; Hitt, K.J.; Helsel, D.R.

1997-01-01

Nitrate contamination of groundwater occurs in predictable patterns, based on findings of the U.S. Geological Survey's (USGS) National Water Quality Assessment (NAWQA) Program. The NAWQA Program was begun in 1991 to describe the quality of the Nation's water resources, using nationally consistent methods. Variables affecting nitrate concentration in groundwater were grouped as 'input' factors (population density end the amount of nitrogen contributed by fertilizer, manure, and atmospheric sources) and 'aquifer vulnerability' factors (soil drainage characteristic and the ratio of woodland acres to cropland acres in agricultural areas) and compiled in a national map that shows patterns of risk for nitrate contamination of groundwater. Areas with high nitrogen input, well-drained soils, and low woodland to cropland ratio have the highest potential for contamination of shallow groundwater by nitrate. Groundwater nitrate data collected through 1992 from wells less than 100 ft deep generally verified the risk patterns shown on the national map. Median nitrate concentration was 0.2 mg/L in wells representing the low-risk group, and the maximum contaminant level (MCL) was exceeded in 3% of the wells. In contrast, median nitrate concentration was 4.8 mg/L in wells representing the high-risk group, and the MCL was exceeded in 25% of the wells.Nitrate contamination of groundwater occurs in predictable patterns, based on findings of the U.S. Geological Survey's (USGS) National Water Quality Assessment (NAWQA) Program. The NAWQA Program was begun in 1991 to describe the quality of the Nation's water resources, using nationally consistent methods. Variables affecting nitrate concentration in groundwater were grouped as `input' factors (population density and the amount of nitrogen contributed by fertilizer, manure, and atmospheric sources) and `aquifer vulnerability' factors (soil drainage characteristic and the ratio of woodland acres to cropland acres in agricultural areas) and compiled in a national map that shows patterns of risk for nitrate contamination of groundwater. Areas with high nitrogen input, well-drained soils, and low woodland to cropland ratio have the highest potential for contamination of shallow groundwater by nitrate. Groundwater nitrate data collected through 1992 from wells less than 100 ft deep generally verified the risk patterns shown on the national map. Median nitrate concentration was 0.2 mg/L in wells representing the low-risk group, and the maximum contaminant level (MCL) was exceeded in 3% of the wells. In contrast, median nitrate concentration was 4.8 mg/L in wells representing the high-risk group, and the MCL was exceeded in 25% of the wells.

Gemas: issues from the comparison of aqua regia and X-ray fluorescence results

NASA Astrophysics Data System (ADS)

Dinelli, Enrico; Birke, Manfred; Reimann, Clemens; Demetriades, Alecos; DeVivo, Benedetto; Flight, Dee; Ladenberger, Anna; Albanese, Stefano; Cicchella, Domenico; Lima, Annamaria

2014-05-01

The comparison of analytical results from aqua regia (AR) and X-ray fluorescence spectroscopy (XRF) can provide information on soil processes controlling the element distribution. The GEMAS (GEochemical Mapping of Agricultural and grazing land Soils) agricultural soil database is used for this comparison. Analyses for the same suite of elements and parameters were carried out in the same laboratory under strict quality control procedures. Sample preparation has been conducted at the laboratory of the The comparison of analytical results from aqua regia (AR) and X-ray fluorescence spectroscopy (XRF) can provide information on soil processes controlling the element distribution in soil. The GEMAS (GEochemical Mapping of Agricultural and grazing land Soils) agricultural soil database, consisting of 2 x ca. 2100 samples spread evenly over 33 European countries, is used for this comparison. Analyses for the same suite of elements and parameters were carried out in the same laboratory under strict quality control procedures. Sample preparation has been conducted at the laboratory of the Geological Survey of the Slovak Republic, AR analyses were carried out at ACME Labs, and XRF analyses at the Federal Institute for Geosciences and Natural Resources, Germany Element recovery by AR is very different, ranging from <1% (e.g. Na, Zr) to > 80% (e.g. Mn, P, Co). Recovery is controlled by mineralogy of the parent material, but geographic and climatic factors and the weathering history of the soils are also important. Nonetheless, even the very low recovery elements show wide ranges of variation and spatial patterns that are affected by other factors than soil parent material. For many elements soil pH have a clear influence on AR extractability: under acidic soil conditions almost all elements tend to be leached and their extractability is generally low. It progressively increases with increasing pH and is highest in the pH range 7-8. Critical is the clay content of the soil that almost for all elements correspond to higher extractability with increasing clay abundance. Also other factors such as organic matter content of soil, Fe and Mn occurrence are important for certain elements or in selected areas. This work illustrates that there are significant differences in the extractability of elements from soils and addresses important influencing factors related to soil properties, geology, climate.

Mapping of topsoil organic carbon in agro-ecosystems of a flat terrain area (Lombardy) by means of legacy soil data, climatic data and NDVI time series predictors with machine learning methods

NASA Astrophysics Data System (ADS)

Schillaci, Calogero; Saia, Sergio; Braun, Andreas; Acutis, Marco

2017-04-01

Topsoil organic carbon plays an important role in the agricultural yield, yield potential, and to deliver many ecosystem services, such as the potential to reduce greenhouse gas (GHG) emission from soil. In particular, SOC content sturdily affects soil properties, thus the precision of its estimation can support broad-scale agricultural and environmental management policy. Soils in temperate agro-ecosystem are generally highly productive and cropland occupies about 60% of their surface (Ramankutty et al 2008). In such contexts, lands is frequently subjected to SOC degrading operations, mostly ploughing, with drawbacks on soil fertility and erosion. In temperate agro-ecosystems, a strong role in SOC maintenance can be played by manure and residues inputs after husbandry and related activities and return of plant biomass to the soil (Acutis et al 2014). In this perspective, soil management can have a major role in SOC spatial distribution to maintain soil fertility and ecosystem services in a target area. Due to the considerable importance of SOC on both agronomical and ecological aspects of the agro-ecosystems, regional soil surveys over the years frequently take into account the measurement of SOC concentration and often stock. In the present study, we integrated a highly detailed legacy SOC dataset with climatic data and RS data to produce a reliable SOC maps from a farm to a district scale. In particular, the Normalized Difference Vegetation Index (NDVI)was used after the computation of its average value in a given pixel derived from several approximately cloud-free images. The input dataset was made of about 3000 Ap horizons implemented of SOC concentration, texture, bulk density and metadata. Climatic data (Worldclim), soil type (from the pedological map 1:250000 WRB), and a time series NDVI were applied. The NDVI data were derived from a set of Landsat 5 scenes (path 193, row 28,29) whereas the path 194, (row 28 and 29) contributes for less than one fourth of the study area. The use of machine learning approach for the generation of a SOC map of the flat terrain agricultural topsoil of Lombardy using the regional soil database relies on two assumptions: (1) the slow change in the content of the stabilised soil organic matter (SOM) fraction, which is almost everywhere the most represented SOM fraction; and (2) the intrinsic low erosion rates due to the low mean slope. In particular, NDVI, which is related land cover and to the amount of biomass returned the soil, can have drawbacks when applied in cultivated fields. These drawbacks mainly concern the variability on crop biomass within and across the year. Notwithstanding, this issue makes NDVI very suitable for differentiating contrasting land use (e.g. field crops vs. orchards) when computed from images captured in particular crop cycle moments (e.g. in summer). However, the same issue reduces NDVI suitability to estimate the amount of biomass within each land use or when aiming at highly detailed resolution. Different grade of cloud cover were admitted to construct the average NDVI. Boosted regression trees were used to reveal the effect of each spatial covariate in predicting the SOC content. Preliminary results highlighted that the integration of the soil pedological classification and the mean NDVI improved the pixel classification in SOC classes according to crop type and management. As expected, climatic gradient played an important role in SOC modelling but did not affect the spatial resolution of the final map. In conclusion, SOC estimate strongly depends on sample density and homogeneity of distribution and the environmental heterogeneity. The lack of the strong topographical traits in flat terrain areas represents a challenge for soil mapping. In such conditions, the computation of a reliable biomass-related RS trait such as the mean NDVI can increase the prediction ability of the models and reduce the mapping biases. References Acutis, M., Alfieri, L., Giussani, A., Provolo, G., Di Guardo, A., Colombini, S., Bertoncini, G.,Castelnuovo, M., Sali, G., Moschini, M., Sanna, M., Perego, A., Carozzi, M., Chiodini, M.E., Fumagalli, M., 2014. ValorE: An integrated and GIS-based decision support system for livestock manure management in the Lombardy region (northern Italy). Land use policy 41, 149-162. doi:10.1016/j.landusepol.2014.05.007 Ramankutty, N., A. T. Evan, C. Monfreda, and J. A. Foley (2008), Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cycles , 22, GB1003, doi:10.1029/2007GB002952.

Topsoil moisture mapping using geostatistical techniques under different Mediterranean climatic conditions.

PubMed

Martínez-Murillo, J F; Hueso-González, P; Ruiz-Sinoga, J D

2017-10-01

Soil mapping has been considered as an important factor in the widening of Soil Science and giving response to many different environmental questions. Geostatistical techniques, through kriging and co-kriging techniques, have made possible to improve the understanding of eco-geomorphologic variables, e.g., soil moisture. This study is focused on mapping of topsoil moisture using geostatistical techniques under different Mediterranean climatic conditions (humid, dry and semiarid) in three small watersheds and considering topography and soil properties as key factors. A Digital Elevation Model (DEM) with a resolution of 1×1m was derived from a topographical survey as well as soils were sampled to analyzed soil properties controlling topsoil moisture, which was measured during 4-years. Afterwards, some topography attributes were derived from the DEM, the soil properties analyzed in laboratory, and the topsoil moisture was modeled for the entire watersheds applying three geostatistical techniques: i) ordinary kriging; ii) co-kriging considering as co-variate topography attributes; and iii) co-kriging ta considering as co-variates topography attributes and gravel content. The results indicated topsoil moisture was more accurately mapped in the dry and semiarid watersheds when co-kriging procedure was performed. The study is a contribution to improve the efficiency and accuracy of studies about the Mediterranean eco-geomorphologic system and soil hydrology in field conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

A study of the utilization of ERTS-1 data from the Wabash River Basin. [soil mapping, crop identification, water resources

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1973-01-01

The author has identified the following significant results. In soil association mapping, computerized analysis of ERTS-1 MSS data has yielded images which will prove useful in the ongoing Cooperative Soil Survey program, involving the Soil Conservation Service of USDA and other state and local agencies. In the present mode of operation, a soil survey for a county may take up to 5 years to be completed. Results indicate that a great deal of soils information can be extracted from ERTS-1 data by computer analysis. This information is expected to be very valuable in the premapping conference phase of a soil survey, resulting in more efficient field operations during the actual mapping. In the earth surface features mapping effort it was found that temporal data improved the classification accuracy of forest classification in Tippecanoe County, Indiana. In water resources study a severe scanner look angle effect was observed in the aircraft scanner data of a test lake which was not present in ERTS-1 data of the same site. This effect was greatly accentuated by surface roughness caused by strong winds. Quantitative evaluation of urban features classification in ERTS-1 data was obtained. An 87.1% test accuracy was obtained for eight categories in Marion County, Indiana.

Evaluation of the spatial variability of soil water content at the spatial resolution of SMAP data products : case studies in Italy and Morocco

NASA Astrophysics Data System (ADS)

Menenti, Massimo; Akdim, Nadia; Alfieri, Silvia Maria; Labbassi, Kamal; De Lorenzi, Francesca; Bonfante, Antonello; Basile, Angelo

2014-05-01

Frequent and contiguous observations of soil water content such as the ones to be provided by SMAP are potentially useful to improve distributed models of soil water balance. This requires matching of observations and model estimates provided both sample spatial patterns consistently. The spatial resolution of SMAP soil water content data products ranges from 3 km X 3 km to 40 km X 40 km. Even the highest spatial resolution may not be sufficient to capture the spatial variability due to terrain, soil properties and precipitation. We have evaluated the SMAP spatial resolution against spatial variability of soil water content in two Mediterranean landscapes: a hilly area dominated by vineyards and olive orchards in Central Italy and a large irrigation schemes (Doukkala) in Morocco. The "Valle Telesina" is a 20,000 ha complex landscape located in South Italy in the Campania region, which has a complex geology and geomorphology and it is characterised by an E-W elongated graben where the Calore river flows. The main crops are grapevine (6,448 ha) and olive (3,390 ha). Soil information was mainly derived from an existing soil map at 1:50 000 scale (Terribile et al., 1996). The area includes 47 SMUs (Soil Mapping Units) and about 60 soil typological units (STUs). (Bonfante et al., 2011). In Doukkala, the soil water retention and unsaturated capillary conductivity were estimated from grain size distribution of a number of samples (22 pilot points, each one sampled in 3 horizons of 20cm), and combined with a soil map. The land use classification was carried out using a NDVI time series at high spatial resolution (Landsat TM and SPOT HRV). We have calculated soil water content for each soil unit in each area in response to several climate cases generating daily maps of soil water content at different depths. To reproduce spatial sampling by SMAP we have filtered these spatial patterns by calculating box averages with grid sizes of 1 km X 1 km and 5 km X 5 km. We have repeated this procedure for soil water content in the 0 to 5 cm and 0 to 10 cm depths. For each case we have compared the variance of filtered soil water content with the expected accuracy of SMAP soil water content. The two areas are very different as regards morphology and soil formation. The Valle Telesina is characterized by a very significant variability of soil hydrological properties leading to complex patterns in soil water content. Contrariwise, the soil properties estimated for all soil mapping units in the Dhoukkala collapse into just two pairs of water retention and hydraulic conductivity characteristics, leading to smoother patterns of soil water content.

[Effects of soil data and map scale on assessment of total phosphorus storage in upland soils.

PubMed

Li, Heng Rong; Zhang, Li Ming; Li, Xiao di; Yu, Dong Sheng; Shi, Xue Zheng; Xing, Shi He; Chen, Han Yue

2016-06-01

Accurate assessment of total phosphorus storage in farmland soils is of great significance to sustainable agricultural and non-point source pollution control. However, previous studies haven't considered the estimation errors from mapping scales and various databases with different sources of soil profile data. In this study, a total of 393×10 4 hm 2 of upland in the 29 counties (or cities) of North Jiangsu was cited as a case for study. Analysis was performed of how the four sources of soil profile data, namely, "Soils of County", "Soils of Prefecture", "Soils of Province" and "Soils of China", and the six scales, i.e. 1:50000, 1:250000, 1:500000, 1:1000000, 1:4000000 and1:10000000, used in the 24 soil databases established for the four soil journals, affected assessment of soil total phosphorus. Compared with the most detailed 1:50000 soil database established with 983 upland soil profiles, relative deviation of the estimates of soil total phosphorus density (STPD) and soil total phosphorus storage (STPS) from the other soil databases varied from 4.8% to 48.9% and from 1.6% to 48.4%, respectively. The estimated STPD and STPS based on the 1:50000 database of "Soils of County" and most of the estimates based on the databases of each scale in "Soils of County" and "Soils of Prefecture" were different, with the significance levels of P＜0.001 or P＜0.05. Extremely significant differences (P＜0.001) existed between the estimates based on the 1:50000 database of "Soils of County" and the estimates based on the databases of each scale in "Soils of Province" and "Soils of China". This study demonstrated the significance of appropriate soil data sources and appropriate mapping scales in estimating STPS.

Geochemical baseline studies of soil in Finland

NASA Astrophysics Data System (ADS)

Pihlaja, Jouni

2017-04-01

The soil element concentrations regionally vary a lot in Finland. Mostly this is caused by the different bedrock types, which are reflected in the soil qualities. Geological Survey of Finland (GTK) is carrying out geochemical baseline studies in Finland. In the previous phase, the research is focusing on urban areas and mine environments. The information can, for example, be used to determine the need for soil remediation, to assess environmental impacts or to measure the natural state of soil in industrial areas or mine districts. The field work is done by taking soil samples, typically at depth between 0-10 cm. Sampling sites are chosen to represent the most vulnerable areas when thinking of human impacts by possible toxic soil element contents: playgrounds, day-care centers, schools, parks and residential areas. In the mine districts the samples are taken from the areas locating outside the airborne dust effected areas. Element contents of the soil samples are then analyzed with ICP-AES and ICP-MS, Hg with CV-AAS. The results of the geochemical baseline studies are published in the Finnish national geochemical baseline database (TAPIR). The geochemical baseline map service is free for all users via internet browser. Through this map service it is possible to calculate regional soil baseline values using geochemical data stored in the map service database. Baseline data for 17 elements in total is provided in the map service and it can be viewed on the GTK's web pages (http://gtkdata.gtk.fi/Tapir/indexEN.html).

Using Remote Sensing Platforms to Estimate Near-Surface Soil Properties

NASA Technical Reports Server (NTRS)

Sullivan, D. G.; Shaw, J. N.; Rickman, D.; Mask, P. L.; Wersinger, J. M.; Luvall, J.

2003-01-01

Evaluation of near-surface soil properties via remote sensing (RS) could facilitate soil survey mapping, erosion prediction, fertilization regimes, and allocation of agrochemicals. The objective of this study was to evaluate the relationship between soil spectral signature and near surface soil properties in conventionally managed row crop systems. High resolution RS data were acquired over bare fields in the Coastal Plain, Appalachian Plateau, and Ridge and Valley provinces of Alabama using the Airborne Terrestrial Applications Sensor (ATLAS) multispectral scanner. Soils ranged from sandy Kandiudults to fine textured Rhodudults. Surface soil samples (0-1 cm) were collected from 163 sampling points for soil water content, soil organic carbon (SOC), particle size distribution (PSD), and citrate dithionite extractable iron (Fed) content. Surface roughness, soil water content, and crusting were also measured at sampling. Results showed RS data acquired from lands with less than 4 % surface soil water content best approximated near-surface soil properties at the Coastal Plain site where loamy sand textured surfaces were predominant. Utilizing a combination of band ratios in stepwise regression, Fed (r2 = 0.61), SOC (r2 = 0.36), sand (r2 = 0.52), and clay (r2 = 0.76) were related to RS data at the Coastal Plain site. In contrast, the more clayey Ridge and Valley soils had r-squares of 0.50, 0.36, 0.17, and 0.57. for Fed, SOC, sand and clay, respectively. Use of estimated eEmissivity did not generally improve estimates of near-surface soil attributes.

Agricultural land cover mapping in the context of a geographically referenced digital information system. [Carroll, Macon, and Gentry Counties, Missouri

NASA Technical Reports Server (NTRS)

Stoner, E. R.

1982-01-01

The introduction of soil map information to the land cover mapping process can improve discrimination of land cover types and reduce confusion among crop types that may be caused by soil-specific management practices and background reflectance characteristics. Multiple dates of LANDSAT MSS digital were analyzed for three study areas in northern Missouri to produce cover types for major agricultural land cover classes. Digital data bases were then developed by adding ancillary data such as digitized soil and transportation network information to the LANDSAT-derived cover type map. Procedures were developed to manipulate the data base parameters to extract information applicable to user requirements. An agricultural information system combining such data can be used to determine the productive capacity of land to grow crops, fertilizer needs, chemical weed control rates, irrigation suitability, and trafficability of soil for planting.

Ecosystem Services in Agricultural Landscapes: A Spatially Explicit Approach to Support Sustainable Soil Management

PubMed Central

Crossman, Neville D.; MacEwan, Richard J.; Wallace, D. Dugal; Bennett, Lauren T.

2014-01-01

Soil degradation has been associated with a lack of adequate consideration of soil ecosystem services. We demonstrate a broadly applicable method for mapping changes in the supply of two priority soil ecosystem services to support decisions about sustainable land-use configurations. We used a landscape-scale study area of 302 km2 in northern Victoria, south-eastern Australia, which has been cleared for intensive agriculture. Indicators representing priority soil services (soil carbon sequestration and soil water storage) were quantified and mapped under both a current and a future 25-year land-use scenario (the latter including a greater diversity of land uses and increased perennial crops and irrigation). We combined diverse methods, including soil analysis using mid-infrared spectroscopy, soil biophysical modelling, and geostatistical interpolation. Our analysis suggests that the future land-use scenario would increase the landscape-level supply of both services over 25 years. Soil organic carbon content and water storage to 30 cm depth were predicted to increase by about 11% and 22%, respectively. Our service maps revealed the locations of hotspots, as well as potential trade-offs in service supply under new land-use configurations. The study highlights the need to consider diverse land uses in sustainable management of soil services in changing agricultural landscapes. PMID:24616632

Ecosystem services in agricultural landscapes: a spatially explicit approach to support sustainable soil management.

PubMed

Forouzangohar, Mohsen; Crossman, Neville D; MacEwan, Richard J; Wallace, D Dugal; Bennett, Lauren T

2014-01-01

Soil degradation has been associated with a lack of adequate consideration of soil ecosystem services. We demonstrate a broadly applicable method for mapping changes in the supply of two priority soil ecosystem services to support decisions about sustainable land-use configurations. We used a landscape-scale study area of 302 km(2) in northern Victoria, south-eastern Australia, which has been cleared for intensive agriculture. Indicators representing priority soil services (soil carbon sequestration and soil water storage) were quantified and mapped under both a current and a future 25-year land-use scenario (the latter including a greater diversity of land uses and increased perennial crops and irrigation). We combined diverse methods, including soil analysis using mid-infrared spectroscopy, soil biophysical modelling, and geostatistical interpolation. Our analysis suggests that the future land-use scenario would increase the landscape-level supply of both services over 25 years. Soil organic carbon content and water storage to 30 cm depth were predicted to increase by about 11% and 22%, respectively. Our service maps revealed the locations of hotspots, as well as potential trade-offs in service supply under new land-use configurations. The study highlights the need to consider diverse land uses in sustainable management of soil services in changing agricultural landscapes.

[Agricultural soil contamination from As and Cd and its responses to landscape heterogeneity at multiple scales in Guangzhou, China].

PubMed

Xu, Hui Qiu; Huang, Yin Hua; Wu, Zhi Feng; Cheng, Jiong; Li, Cheng

2016-10-01

Based on 641 agricultural top soil samples (0-20 cm) and land use map in 2005 of Guangzhou, we used single-factor pollution indices and Pearson/Spearman correlation and partial redundancy analyses and quantified the soil contamination with As and Cd and their relationships with landscape heterogeneity at three grid scales of 2 km×2 km, 5 km×5 km, and 10 km×10 km as well as the determinant landscape heterogeneity factors at a certain grid scale. 5.3% and 7.2% of soil samples were contaminated with As and Cd, respectively. At the three scales, the agricultural soil As and Cd contamination were generally significantly correlated with parent materials' composition, river/road density and landscape patterns of several land use types, indicating the parent materials, sewage irrigation and human activities (e.g., industrial and traffic activities, and the additions of pesticides and fertilizers) were possibly the main input pathways of trace metals. Three subsets of landscape heterogeneity variables (i.e., parent materials, distance-density variables, and landscape patterns) could explain 12.7%-42.9% of the variation of soil contamination with As and Cd, of which the explanatory power increased with the grid scale and the determinant factors varied with scales. Parent materials had higher contribution to the variations of soil contamination at the 2 and 10 km grid scales, while the contributions of landscape patterns and distance-density variables generally increased with the grid scale. Adjusting the distribution of cropland and optimizing the landscape pattern of land use types are important ways to reduce soil contamination at local scales, which urban planners and decision makers should pay more attention to.

Mapping soil landscape as spatial continua: The Neural Network Approach

NASA Astrophysics Data System (ADS)

Zhu, A.-Xing

2000-03-01

A neural network approach was developed to populate a soil similarity model that was designed to represent soil landscape as spatial continua for hydroecological modeling at watersheds of mesoscale size. The approach employs multilayer feed forward neural networks. The input to the network was data on a set of soil formative environmental factors; the output from the network was a set of similarity values to a set of prescribed soil classes. The network was trained using a conjugate gradient algorithm in combination with a simulated annealing technique to learn the relationships between a set of prescribed soils and their environmental factors. Once trained, the network was used to compute for every location in an area the similarity values of the soil to the set of prescribed soil classes. The similarity values were then used to produce detailed soil spatial information. The approach also included a Geographic Information System procedure for selecting representative training and testing samples and a process of determining the network internal structure. The approach was applied to soil mapping in a watershed, the Lubrecht Experimental Forest, in western Montana. The case study showed that the soil spatial information derived using the neural network approach reveals much greater spatial detail and has a higher quality than that derived from the conventional soil map. Implications of this detailed soil spatial information for hydroecological modeling at the watershed scale are also discussed.

Regional modeling of wind erosion in the North West and South West of Iran

NASA Astrophysics Data System (ADS)

Mirmousavi, S. H.

2016-08-01

About two-thirds of the Iran's area is located in the arid and semiarid region. Lack of soil moisture and vegetation is poor in most areas can lead to soil erosion caused by wind. So that the annual suffered severe damage to large areas of rich soils. Modeling studies of wind erosion in Iran is very low and incomplete. Therefore, this study aimed to wind erosion modeling, taking into three factors: wind speed, vegetation and soil types have been done. Wind erosion sensitivity was modeled using the key factors of soil sensitivity, vegetation cover and wind erodibility as proxies. These factors were first estimated separately by factor sensitivity maps and later combined by fuzzy logic into a regional-scale wind erosion sensitivity map. Large areas were evaluated by using publicly available datasets of remotely sensed vegetation information, soil maps and meteorological data on wind speed. The resulting estimates were verified by field studies and examining the economic losses from wind erosion as compensated by the state insurance company. The spatial resolution of the resulting sensitivity map is suitable for regional applications, as identifying sensitive areas is the foundation for diverse land development control measures and implementing management activities.

Assessment of physical and chemical indicators of sandy soil quality for sustainable crop production

NASA Astrophysics Data System (ADS)

Lipiec, Jerzy; Usowicz, Boguslaw

2017-04-01

Sandy soils are used in agriculture in many regions of the world. The share of sandy soils in Poland is about 55%. The aim of this study was to assess spatial variability of soil physical and chemical properties affecting soil quality and crop yields in the scale of field (40 x 600 m) during three years of different weather conditions. The experimental field was located on the post glacial and acidified sandy deposits of low productivity (Szaniawy, Podlasie Region, Poland). Physical soil quality indicators included: content of sand, silt, clay and water, bulk density and those chemical: organic carbon, cation exchange capacity, acidity (pH). Measurements of the most soil properties were done at spring and summer each year in topsoil and subsoil layer in 150 points. Crop yields were evaluated in places close to measuring points of the soil properties. Basic statistics including mean, standard deviation, skewness, kurtosis minimal, maximal and correlations between the soil properties and crop yields were calculated. Analysis of spatial dependence and distribution for each property was performed using geostatistical methods. Mathematical functions were fitted to the experimentally derived semivariograms that were used for mapping the soil properties and crop yield by kriging. The results showed that the largest variations had clay content (CV 67%) and the lowest: sand content (5%). The crop yield was most negatively correlated with sand content and most positively with soil water content and cation exchange capacity. In general the exponential semivariogram models fairly good matched to empirical data. The range of semivariogram models of the measured indicators varied from 14 m to 250 m indicate high and moderate spatial variability. The values of the nugget-to-sill+nugget ratios showed that most of the soil properties and crop yields exhibited strong and moderate spatial dependency. The kriging maps allowed identification of low yielding sub-field areas that correspond with low soil organic carbon and cation exchange capacity and high content of sand. These areas are considered as management zones to improve crop productivity and soil properties responsible for soil quality and functions. We conclude that soil organic carbon, cation exchange capacity and pH should be included as indicators of soil quality in sandy soils. The study was funded by HORIZON 2020, European Commission, Programme H2020-SFS-2015-2: Soil Care for profitable and sustainable crop production in Europe, project No. 677407 (SoilCare, 2016-2021).

Suitability aero-geophysical methods for generating conceptual soil maps and their use in the modeling of process-related susceptibility maps

NASA Astrophysics Data System (ADS)

Tilch, Nils; Römer, Alexander; Jochum, Birgit; Schattauer, Ingrid

2014-05-01

In the past years, several times large-scale disasters occurred in Austria, which were characterized not only by flooding, but also by numerous shallow landslides and debris flows. Therefore, for the purpose of risk prevention, national and regional authorities also require more objective and realistic maps with information about spatially variable susceptibility of the geosphere for hazard-relevant gravitational mass movements. There are many and various proven methods and models (e.g. neural networks, logistic regression, heuristic methods) available to create such process-related (e.g. flat gravitational mass movements in soil) suszeptibility maps. But numerous national and international studies show a dependence of the suitability of a method on the quality of process data and parameter maps (f.e. Tilch & Schwarz 2011, Schwarz & Tilch 2011). In this case, it is important that also maps with detailed and process-oriented information on the process-relevant geosphere will be considered. One major disadvantage is that only occasionally area-wide process-relevant information exists. Similarly, in Austria often only soil maps for treeless areas are available. However, in almost all previous studies, randomly existing geological and geotechnical maps were used, which often have been specially adapted to the issues and objectives. This is one reason why very often conceptual soil maps must be derived from geological maps with only hard rock information, which often have a rather low quality. Based on these maps, for example, adjacent areas of different geological composition and process-relevant physical properties are razor sharp delineated, which in nature appears quite rarly. In order to obtain more realistic information about the spatial variability of the process-relevant geosphere (soil cover) and its physical properties, aerogeophysical measurements (electromagnetic, radiometric), carried out by helicopter, from different regions of Austria were interpreted. Previous studies show that, especially with radiometric measurements, the two-dimensional spatial variability of the nature of the process-relevant soil, close to the surface can be determined. In addition, the electromagnetic measurements are more important to obtain three-dimensional information of the deeper geological conditions and to improve the area-specific geological knowledge and understanding. The validation of these measurements is done with terrestrial geoelectrical measurements. So both aspects, radiometric and electromagnetic measurements, are important and subsequently, interpretation of the geophysical results can be used as the parameter maps in the modeling of more realistic susceptibility maps with respect to various processes. Within this presentation, results of geophysical measurements, the outcome and the derived parameter maps, as well as first process-oriented susceptibility maps in terms of gravitational soil mass movements will be presented. As an example results which were obtained with a heuristic method in an area in Vorarlberg (Western Austria) will be shown. References: Schwarz, L. & Tilch, N. (2011): Why are good process data so important for the modelling of landslide susceptibility maps?- EGU-Postersession "Landslide hazard and risk assessment, and landslide management" (NH 3.6), Vienna. [http://www.geologie.ac.at/fileadmin/user_upload/dokumente/pdf/poster/poster_2011_egu_schwarz_tilch_1.pdf] Tilch, N. & Schwarz, L. (2011): Spatial and scale-dependent variability in data quality and their influence on susceptibility maps for gravitational mass movements in soil, modelled by heuristic method.- EGU-Postersession "Landslide hazard and risk assessment, and landslide management" (NH 3.6); Vienna. [http://www.geologie.ac.at/fileadmin/user_upload/dokumente/pdf/poster/poster_2011_egu_tilch_schwarz.pdf

Soil functional types: surveying the biophysical dimensions of soil security

NASA Astrophysics Data System (ADS)

Cécillon, Lauric; Barré, Pierre

2015-04-01

Soil is a natural capital that can deliver key ecosystem services (ES) to humans through the realization of a series of soil processes controlling ecosystem functioning. Soil is also a diverse and endangered natural resource. A huge pedodiversity has been described at all scales, which is strongly altered by global change. The multidimensional concept soil security, encompassing biophysical, economic, social, policy and legal frameworks of soils has recently been proposed, recognizing the role of soils in global environmental sustainability challenges. The biophysical dimensions of soil security focus on the functionality of a given soil that can be viewed as the combination of its capability and its condition [1]. Indeed, all soils are not equal in term of functionality. They show different processes, provide different ES to humans and respond specifically to global change. Knowledge of soil functionality in space and time is thus a crucial step towards the achievement soil security. All soil classification systems incorporate some functional information, but soil taxonomy alone cannot fully describe the functioning, limitations, resistance and resilience of soils. Droogers and Bouma [2] introduced functional variants (phenoforms) for each soil type (genoform) so as to fit more closely to soil functionality. However, different genoforms can have the same functionality. As stated by McBratney and colleagues [1], there is a great need of an agreed methodology for defining the reference state of soil functionality. Here, we propose soil functional types (SFT) as a relevant classification system for the biophysical dimensions of soil security. Following the definition of plant functional types widely used in ecology, we define a soil functional type as "a set of soil taxons or phenoforms sharing similar processes (e.g. soil respiration), similar effects on ecosystem functioning (e.g. primary productivity) and similar responses to global change (land-use, management or climate) for a particular soil-provided ecosystem service (e.g. climate regulation)". One SFT can thus include several soil types having the same functionality for a particular soil-provided ES. Another consequence is that SFT maps for two different ES may not superimpose over the same area, since some soils may fall in the same SFT for a service and in different SFT for another one. Soil functional types could be assessed and monitored in space and time by a combination of soil functional traits that correspond to inherent and manageable properties of soils. Their metrology would involve either classic (pedological observations) or advanced (molecular ecology, spectrometry, geophysics) tools. SFT could be studied and mapped at all scales, depending on the purpose of the soil security assessment (e.g. global climate modeling, land planning and management, biodiversity conservation). Overall, research is needed to find a pathway from soil pedological maps to SFT maps which would yield important benefits towards the assessment and monitoring of soil security. Indeed, this methodology would allow (i) reducing the spatial uncertainty on the assessment of ES; (ii) identifying and mapping multifunctional soils, which may be the most important soil resource to preserve. References [1] McBratney et al., 2014. Geoderma 213:203-213. [2] Droogers P, Bouma J, 1997. SSSAJ 61:1704-1710.

Soil classification based on cone penetration test (CPT) data in Western Central Java

NASA Astrophysics Data System (ADS)

Apriyono, Arwan; Yanto, Santoso, Purwanto Bekti; Sumiyanto

2018-03-01

This study presents a modified friction ratio range for soil classification i.e. gravel, sand, silt & clay and peat, using CPT data in Western Central Java. The CPT data was obtained solely from Soil Mechanic Laboratory of Jenderal Soedirman University that covers more than 300 sites within the study area. About 197 data were produced from data filtering process. IDW method was employed to interpolated friction ratio values in a regular grid point for soil classification map generation. Soil classification map was generated and presented using QGIS software. In addition, soil classification map with respect to modified friction ratio range was validated using 10% of total measurements. The result shows that silt and clay dominate soil type in the study area, which is in agreement with two popular methods namely Begemann and Vos. However, the modified friction ratio range produces 85% similarity with laboratory measurements whereby Begemann and Vos method yields 70% similarity. In addition, modified friction ratio range can effectively distinguish fine and coarse grains, thus useful for soil classification and subsequently for landslide analysis. Therefore, modified friction ratio range proposed in this study can be used to identify soil type for mountainous tropical region.

Effects of long-term soil and crop management on soil hydraulic properties for claypan soils

USDA-ARS?s Scientific Manuscript database

Regional and national soil maps have been developed along with associated soil property databases to assist users in making land management decisions based on soil characteristics. These soil properties include average values from soil characterization for each soil series. In reality, these propert...

Map of surficial deposits and materials in the eastern and central United States (east of 102 degrees West longitude)

USGS Publications Warehouse

Fullerton, David S.; Bush, Charles A.; Pennell, Jean N.

2003-01-01

This data set contains surficial geologic units in the Eastern and Central United States, as well as a glacial limit line showing the position of maximum glacial advance during various geologic time periods. The geologic units represent surficial deposits and other surface materials that accumulated or formed during the past 2+ million years, such as soils, alluvium, and glacial deposits. These surface materials are referred to collectively by many geologists as regolith, the mantle of fragmented and generally unconsolidated material that overlies the bedrock foundation of a continent. This data set and the printed map produced from it, U.S. Geological Survey (USGS) Geologic Investigation Series I-2789, were based on 31 published maps in the USGS's Quaternary Geologic Atlas of the United States map series (USGS Miscellaneous Investigations Series I-1420). The data were compiled at 1:1,000,000 scale, to be viewed as a digital map at 1:2,000,000 nominal scale and to be printed as a conventional paper map at 1:2,500,000 scale.

Analysis of heavy metal sources in soil using kriging interpolation on principal components.

PubMed

Ha, Hoehun; Olson, James R; Bian, Ling; Rogerson, Peter A

2014-05-06

Anniston, Alabama has a long history of operation of foundries and other heavy industry. We assessed the extent of heavy metal contamination in soils by determining the concentrations of 11 heavy metals (Pb, As, Cd, Cr, Co, Cu, Mn, Hg, Ni, V, and Zn) based on 2046 soil samples collected from 595 industrial and residential sites. Principal Component Analysis (PCA) was adopted to characterize the distribution of heavy metals in soil in this region. In addition, a geostatistical technique (kriging) was used to create regional distribution maps for the interpolation of nonpoint sources of heavy metal contamination using geographical information system (GIS) techniques. There were significant differences found between sampling zones in the concentrations of heavy metals, with the exception of the levels of Ni. Three main components explaining the heavy metal variability in soils were identified. The results suggest that Pb, Cd, Cu, and Zn were associated with anthropogenic activities, such as the operations of some foundries and major railroads, which released these heavy metals, whereas the presence of Co, Mn, and V were controlled by natural sources, such as soil texture, pedogenesis, and soil hydrology. In general terms, the soil levels of heavy metals analyzed in this study were higher than those reported in previous studies in other industrial and residential communities.

Estimating vegetation vulnerability to detect areas prone to land degradation in the Mediterranean basin

NASA Astrophysics Data System (ADS)

Imbrenda, Vito; Coluzzi, Rosa; D'Emilio, Mariagrazia; Lanfredi, Maria; Simoniello, Tiziana

2013-04-01

Vegetation is one of the key components to study land degradation vulnerability because of the complex interactions and feedbacks that link it to soil. In the Mediterranean region, degradation phenomena are due to a mix of predisposing factors (thin soil horizons, low soil organic matter, increasing aridity, etc.) and bad management practices (overgrazing, deforestation, intensification of agriculture, tourism development). In particular, in areas threatened by degradation processes but still covered by vegetation, large scale soil condition evaluation is a hard task and the detection of stressed vegetation can be useful to identify on-going soil degradation phenomena and to reduce their impacts through interventions for recovery/rehabilitation. In this context the use of satellite time series can increase the efficacy and completeness of the land degradation assessment, providing precious information to understand vegetation dynamics. In order to estimate vulnerability levels in Basilicata (a Mediterranean region of Southern Italy) in the framework of PRO-LAND project (PO-FESR Basilicata 2007-2013), we crossed information on potential vegetation vulnerability with information on photosynthetic activity dynamics. Potential vegetation vulnerability represents the vulnerability related to the type of present cover in terms of fire risk, erosion protection, drought resistance and plant cover distribution. It was derived from an updated land cover map by separately analyzing each factor, and then by combining them to obtain concise information on the possible degradation exposure. The analysis of photosynthetic activity dynamics provides information on the status of vegetation, that is fundamental to discriminate the different vulnerability levels within the same land cover, i.e. the same potential vulnerability. For such a purpose, we analyzed a time series (2000-2010) of a satellite vegetation index (MODIS NDVI) with 250m resolution, available as 16-day composite from the NASA LP DAAC dataset. Vegetation activity trends were estimated and then normalized to the starting conditions to obtain the percentage variation (NDVI-PV) for the considered period. Information on the potential vulnerability and vegetation activity dynamics were classified into indexes and combined to obtain the final map of the actual vegetation vulnerability and to identify on-going degradation phenomena and priority sites within areas already compromised. As for the investigated area, this map shows a composite picture in which only a few values of high vulnerability are scattered along areas where medium-high vulnerability values generally prevail. Here, we singled out two kind of areas: one largely devoted to intensive agriculture, and other one mostly characterized by bare soils and sparse vegetation. On the contrary, a large part of natural and seminatural vegetation located along the Apennine chain does not show critical vulnerability values. By comparing the vegetation vulnerability map with the vulnerability map due to anthropic factors (pressure induced by agricultural and grazing activities, estimated by indicators derived from census data), we found correlation, confirming the anthropogenic cause of vulnerability and therefore the major role held by soil management in areas mainly devoted to intensive farming.

Predictable bacterial composition and hydrocarbon degradation in Arctic soils following diesel and nutrient disturbance

PubMed Central

Bell, Terrence H; Yergeau, Etienne; Maynard, Christine; Juck, David; Whyte, Lyle G; Greer, Charles W

2013-01-01

Increased exploration and exploitation of resources in the Arctic is leading to a higher risk of petroleum contamination. A number of Arctic microorganisms can use petroleum for growth-supporting carbon and energy, but traditional approaches for stimulating these microorganisms (for example, nutrient addition) have varied in effectiveness between sites. Consistent environmental controls on microbial community response to disturbance from petroleum contaminants and nutrient amendments across Arctic soils have not been identified, nor is it known whether specific taxa are universally associated with efficient bioremediation. In this study, we contaminated 18 Arctic soils with diesel and treated subsamples of each with monoammonium phosphate (MAP), which has successfully stimulated degradation in some contaminated Arctic soils. Bacterial community composition of uncontaminated, diesel-contaminated and diesel+MAP soils was assessed through multiplexed 16S (ribosomal RNA) rRNA gene sequencing on an Ion Torrent Personal Genome Machine, while hydrocarbon degradation was measured by gas chromatography analysis. Diversity of 16S rRNA gene sequences was reduced by diesel, and more so by the combination of diesel and MAP. Actinobacteria dominated uncontaminated soils with <10% organic matter, while Proteobacteria dominated higher-organic matter soils, and this pattern was exaggerated following disturbance. Degradation with and without MAP was predictable by initial bacterial diversity and the abundance of specific assemblages of Betaproteobacteria, respectively. High Betaproteobacteria abundance was positively correlated with high diesel degradation in MAP-treated soils, suggesting this may be an important group to stimulate. The predictability with which bacterial communities respond to these disturbances suggests that costly and time-consuming contaminated site assessments may not be necessary in the future. PMID:23389106

Digital soil mapping using remote sensing indices, terrain attributes, and vegetation features in the rangelands of northeastern Iran.

PubMed

Mahmoudabadi, Ebrahim; Karimi, Alireza; Haghnia, Gholam Hosain; Sepehr, Adel

2017-09-11

Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R 2 RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.

Evaluation of Electromagnetic Induction to Characterize and Map Sodium-Affected Soils in the Northern Great Plains of the United States

NASA Astrophysics Data System (ADS)

Brevik, E. C.; Heilig, J.; Kempenich, J.; Doolittle, J.; Ulmer, M.

2012-04-01

Sodium-affected soils (SAS) cover over 4 million hectares in the Northern Great Plains of the United States. Improving the classification, interpretation, and mapping of SAS is a major goal of the United States Department of Agriculture-Natural Resource Conservation Service (USDA-NRCS) as Northern Great Plains soil surveys are updated. Apparent electrical conductivity (ECa) as measured with ground conductivity meters has shown promise for mapping SAS, however, this use of this geophysical tool needs additional evaluation. This study used an EM-38 MK2-2 meter (Geonics Limited, Mississauga, Ontario), a Trimble AgGPS 114 L-band DGPS (Trimble, Sunnyvale, CA) and the RTmap38MK2 program (Geomar Software, Inc., Mississauga, Ontario) on an Allegro CX field computer (Juniper Systems, North Logan, UT) to collect, observe, and interpret ECa data in the field. The ECa map generated on-site was then used to guide collection of soil samples for soil characterization and to evaluate the influence of soil properties in SAS on ECa as measured with the EM-38MK2-2. Stochastic models contained in the ESAP software package were used to estimate the SAR and salinity levels from the measured ECa data in 30 cm depth intervals to a depth of 90 cm and for the bulk soil (0 to 90 cm). This technique showed promise, with meaningful spatial patterns apparent in the ECa data. However, many of the stochastic models used for salinity and SAR for individual depth intervals and for the bulk soil had low R-squared values. At both sites, significant variability in soil clay and water contents along with a small number of soil samples taken to calibrate the ECa values to soil properties likely contributed to these low R-squared values.

7 CFR 12.22 - Highly erodible field determination criteria.

Code of Federal Regulations, 2014 CFR

2014-01-01

... percent or more of the total field acreage is identified as soil map units which are highly erodible; or (2) 50 or more acres in such field are identified as soil map units which are highly erodible. (b...

7 CFR 12.22 - Highly erodible field determination criteria.

Code of Federal Regulations, 2013 CFR

2013-01-01

... percent or more of the total field acreage is identified as soil map units which are highly erodible; or (2) 50 or more acres in such field are identified as soil map units which are highly erodible. (b...

7 CFR 12.22 - Highly erodible field determination criteria.

Code of Federal Regulations, 2011 CFR

2011-01-01

... percent or more of the total field acreage is identified as soil map units which are highly erodible; or (2) 50 or more acres in such field are identified as soil map units which are highly erodible. (b...

7 CFR 12.22 - Highly erodible field determination criteria.

Code of Federal Regulations, 2012 CFR

2012-01-01

... percent or more of the total field acreage is identified as soil map units which are highly erodible; or (2) 50 or more acres in such field are identified as soil map units which are highly erodible. (b...

The agricultural features of Nizhegorodskaya gubernia (province) in the XIX century

NASA Astrophysics Data System (ADS)

Kirillova, Vasilisa

2017-04-01

One of the main conditions for the sustainable development of any country is the food security of the population, based on the development of agriculture. This condition can be realized through the efficient use of the productive capacity of agriculture, and above all natural resources. From 1882 to 1887 in the Nizhegorodskaya gubernia (province) complex physiographic (landscape) researches were conducted by V.V. Dokuchaev and his followers. This investigation was focused on studying the relationship between the soils and the environment, having no parallel either in Russia or abroad, and received evaluation of the soils was the first experience of such a scale and nature. Reports of the expedition were presented in 14 volumes on the natural science of the study, and 11 volumes of economic statistics. Natural science volume includes descriptions of irrigation and hydrography, geology, soil and vegetation in uezds (districts). Economic volume represent a set of common data on the situation of the peasant economy, they contain information about the number of arable land, including fertilized, hayfields, forests, manure stocks, livestock, harvest volumes, proportions of cultivated crops. The aim of this research was to study the list and structure of crops cultivated in the Nizhegorodskaya gubernia in the XIX century and their compliance with the soil and climatic conditions. From the materials of the expedition reports for the eight districts of the Nizhegorodskaya gubernia was compiled a list of crops and crop area information which was introduced in the GIS (MapInfo). Geographic information systems were used to visualize the collected material in the form of maps, cartograms and charts. For the conformity assessment of soil and climatic conditions of the studied area of selected crops a map "Agricultural zoning of Russia for optimal crop growing" by I.I. Karmanov and D.S. Bulgakov (National Soil Atlas, 2011) was applied. According to this map the Nizhegorodskaya gubernia is located in three agro-climatic areas: (№9) European Southern taiga, sod-podzolic (humus soils of Opol'e), rye, barley, oat, potato and forage (corn silage), (number 11) North-steppe (ETP), gray forest soils with patches of chernozems, winter-wheat-rye, barley, oat, potato with corn silage, (№12) forest-steppe (ETP), leached and podzolized chernozems with gray forest soils , winter-wheat-rye, barley, oat, potato with sugar beet and corn for silage. Analysis of digitized information on cultivated crops of Nizhegorodskaya gubernia in the XIX century and agro-climatic characteristics of areas has shown that the list of selected crops in general corresponds to the recommendations by present-day scientists, but has its own characteristics. In reporting materials there is no information about the cultivation of crops such as winter wheat, sugar beet and corn. Potatoes and barley are cultivated in small quantities, their place is taken lentil, millet and spelt, which in today's recommendations are not mentioned.

Do We Need a New Definition of Soil?

NASA Astrophysics Data System (ADS)

Arnold, Richard W.; Brevik, Eric C.

2014-05-01

Effective communication is really desirable to better relate with politicians, an interested lay public, and others not involved in soil science. Soil survey programs are intended to help people understand how soils function in their landscapes to make ecosystems operate better without damaging the environment and to indicate different kinds of suitability for various purposes. The properties of soils as recognized, described, and mapped at detailed scales form the basis for developing diagnostics for a systematic taxonomy that enables scientists to interact with other. In the USA mapping done at scales of 1:15,840± made it possible to define and use so-called "soil series", initially as soil map units, but later as central concepts of a set of soils which could be segregated using phases to indicate important features, primarily for farming. Detailed soil surveys published using a standard format helps maintain uniformity across the country. Soil series are recognized as the basic units of soils within the evolving hierarchical soil taxonomy and diagnostic properties are defined, measured and used to update and modify the scientific classification. Concepts like soil quality and soil function are considered to be "attributes" and not basic properties of soils. They are the collective interpretation of the combination of properties thought to be relevant for communicating important aspects of using, managing, restoring, and protecting the lands of any locality, region, or country. A famous example in the US was the land capability system with classes and subclasses of suitability for agricultural land uses. An updated soil survey in California contains over 500 pages providing details about classes of 30 different functional soil classifications for 155 map units. Over the years soil extension agents were the interpreters of the science to the lay folks and could help them form mental pictures of soils and soil landscapes locally They were the early leaders of what we think of as "field guides to natural resources" such as trees, flowers, birds, and so forth. There were not such books to identify soils but the basics have always been there waiting for proper attention, preparation, and use. At smaller scales the map units are always combinations of the basic units, and now it is possible to use some higher category classes to indicate the central concepts of larger areas. Every year soil scientists around the world observe and describe features and properties of soils in landscapes that are getting more attention than previously. Soil genesis studies help us to better understand the complexity of landscape and soil evolution. Often they indicate that current soils are commonly being formed from parts of previous soils. We do not need a new definition of soil. We do need to work on developing and testing complete interpretive classifications of soils to better meet the needs of societies today. This means "soil quality", "soil functions", and other attributes of soils require more attention, now and in the near future to permit politicians and lay publics to better understand the significance of soils to the future of civilization. "After all is said and done, more is said than done" Aesop, Greek storyteller

Near-Surface Geophysical Mapping of the Hydrological Response to an Intense Rainfall Event at the Field Scale

NASA Astrophysics Data System (ADS)

Martínez, G.; Vanderlinden, K.; Giraldez, J. V.; Espejo, A. J.; Muriel, J. L.

2009-12-01

Soil moisture plays an important role in a wide variety of biogeochemical fluxes in the soil-plant-atmosphere system and governs the (eco)hydrological response of a catchment to an external forcing such as rainfall. Near-surface electromagnetic induction (EMI) sensors that measure the soil apparent electrical conductivity (ECa) provide a fast and non-invasive means for characterizing this response at the field or catchment scale through high-resolution time-lapse mapping. Here we show how ECa maps, obtained before and after an intense rainfall event of 125 mm h-1, elucidate differences in soil moisture patterns and hydrologic response of an experimental field as a consequence of differed soil management. The dryland field (Vertisol) was located in SW Spain and cropped with a typical wheat-sunflower-legume rotation. Both, near-surface and subsurface ECa (ECas and ECad, respectively), were measured using the EM38-DD EMI sensor in a mobile configuration. Raw ECa measurements and Mean Relative Differences (MRD) provided information on soil moisture patterns while time-lapse maps were used to evaluate the hydrologic response of the field. ECa maps of the field, measured before and after the rainfall event showed similar patterns. The field depressions where most of water and sediments accumulated had the highest ECa and MRD values. The SE-oriented soil, which was deeper and more exposed to sun and wind, showed the lowest ECa and MRD. The largest differences raised in the central part of the field where a high ECa and MRD area appeared after the rainfall event as a consequence of the smaller soil depth and a possible subsurface flux concentration. Time-lapse maps of both ECa and MRD were also similar. The direct drill plots showed higher increments of ECa and MRD as a result of the smaller runoff production. Time-lapse ECa increments showed a bimodal distribution differentiating clearly the direct drill from the conventional and minimum tillage plots. However this kind of distribution could not be shown using MRD differences since they come from standardized distributions. Field-extend time-lapse ECa maps can provide useful images of the hydrological response of agricultural fields which can be used to evaluate different soil management strategies or to aid the assessment of biogeochemical fluxes at the field scale.

Soil magnetic susceptibility: A quantitative proxy of soil drainage for use in ecological restoration

USGS Publications Warehouse

Grimley, D.A.; Wang, J.-S.; Liebert, D.A.; Dawson, J.O.

2008-01-01

Flooded, saturated, or poorly drained soils are commonly anaerobic, leading to microbially induced magnetite/maghemite dissolution and decreased soil magnetic susceptibility (MS). Thus, MS is considerably higher in well-drained soils (MS typically 40-80 ?? 10-5 standard international [SI]) compared to poorly drained soils (MS typically 10-25 ?? 10-5 SI) in Illinois, other soil-forming factors being equal. Following calibration to standard soil probings, MS values can be used to rapidly and precisely delineate hydric from nonhydric soils in areas with relatively uniform parent material. Furthermore, soil MS has a moderate to strong association with individual tree species' distribution across soil moisture regimes, correlating inversely with independently reported rankings of a tree species' flood tolerance. Soil MS mapping can thus provide a simple, rapid, and quantitative means for precisely guiding reforestation with respect to plant species' adaptations to soil drainage classes. For instance, in native woodlands of east-central Illinois, Quercus alba , Prunus serotina, and Liriodendron tulipifera predominantly occur in moderately well-drained soils (MS 40-60 ?? 10-5 SI), whereas Acer saccharinum, Carya laciniosa, and Fraxinus pennsylvanica predominantly occur in poorly drained soils (MS <20 ?? 10-5 SI). Using a similar method, an MS contour map was used to guide restoration of mesic, wet mesic, and wet prairie species to pre-settlement distributions at Meadowbrook Park (Urbana, IL, U.S.A.). Through use of soil MS maps calibrated to soil drainage class and native vegetation occurrence, restoration efforts can be conducted more successfully and species distributions more accurately reconstructed at the microecosystem level. ?? 2008 Society for Ecological Restoration International.

Mapping Soil Surface Macropores Using Infrared Thermography: An Exploratory Laboratory Study

PubMed Central

de Lima, João L. M. P.; Abrantes, João R. C. B.; Silva, Valdemir P.; de Lima, M. Isabel P.; Montenegro, Abelardo A. A.

2014-01-01

Macropores and water flow in soils and substrates are complex and are related to topics like preferential flow, nonequilibrium flow, and dual-continuum. Hence, the quantification of the number of macropores and the determination of their geometry are expected to provide a better understanding on the effects of pores on the soil's physical and hydraulic properties. This exploratory study aimed at evaluating the potential of using infrared thermography for mapping macroporosity at the soil surface and estimating the number and size of such macropores. The presented technique was applied to a small scale study (laboratory soil flume). PMID:25371915

Application of Thermal Infrared Remote Sensing for Quantitative Evaluation of Crop Characteristics

NASA Technical Reports Server (NTRS)

Shaw, J.; Luvall, J.; Rickman, D.; Mask, P.; Wersinger, J.; Sullivan, D.; Arnold, James E. (Technical Monitor)

2002-01-01

Evidence suggests that thermal infrared emittance (TIR) at the field-scale is largely a function of the integrated crop/soil moisture continuum. Because soil moisture dynamics largely determine crop yields in non-irrigated farming (85 % of Alabama farms are non-irrigated), TIR may be an effective method of mapping within field crop yield variability, and possibly, absolute yields. The ability to map yield variability at juvenile growth stages can lead to improved soil fertility and pest management, as well as facilitating the development of economic forecasting. Researchers at GHCC/MSFC/NASA and Auburn University are currently investigating the role of TIR in site-specific agriculture. Site-specific agriculture (SSA), or precision farming, is a method of crop production in which zones and soils within a field are delineated and managed according to their unique properties. The goal of SSA is to improve farm profits and reduce environmental impacts through targeted agrochemical applications. The foundation of SSA depends upon the spatial and temporal characterization of soil and crop properties through the creation of management zones. Management zones can be delineated using: 1) remote sensing (RS) data, 2) conventional soil testing and soil mapping, and 3) yield mapping. Portions of this research have concentrated on using remote sensing data to map yield variability in corn (Zea mays L.) and soybean (Glycine max L.) crops. Remote sensing data have been collected for several fields in the Tennessee Valley region at various crop growth stages during the last four growing seasons. Preliminary results of this study will be presented.

Soil depth mapping using seismic surface waves: Evaluation on eroded loess covered hillslopes

NASA Astrophysics Data System (ADS)

Bernardie, Severine; Samyn, Kevin; Cerdan, Olivier; Grandjean, Gilles

2010-05-01

The purposes of the multidisciplinary DIGISOIL project are the integration and improvement of in situ and proximal technologies for the assessment of soil properties and soil degradation indicators. Foreseen developments concern sensor technologies, data processing and their integration to applications of (digital) soil mapping (DSM). Among available techniques, the seismic one is, in this study, particularly tested for characterising soil vulnerability to erosion. The spectral analysis of surface waves (SASW) method is an in situ seismic technique used for evaluation of the stiffnesses (G) and associated depth in layered systems. A profile of Rayleigh wave velocity versus frequency, i.e., the dispersion curve, is calculated from each recorded seismogram before to be inverted to obtain the vertical profile of shear wave velocity Vs. Then, the soil stiffness can easily be calculated from the shear velocity if the material density is estimated, and the soil stiffness as a function of depth can be obtained. This last information can be a good indicator to identify the soil bedrock limit. SASW measurements adapted to soil characterisation is proposed in the DIGISOIL project, as it produces in an easy and quick way a 2D map of the soil. This system was tested for the digital mapping of the depth of loamy material in a catchment of the European loess belt. The validation of this methodology has been performed with the realisation of several acquisitions along the seismic profiles: - Several boreholes were drilled until the bedrock, permitting to get the geological features of the soil and the depth of the bedrock; - Several laboratory measurements of various parameters were done on samples taken from the boreholes at various depths, such as dry density, solid density, and water content; - Dynamic penetration tests were also conducted along the seismic profile, until the bedrock is attained. Some empirical correlations between the parameters measured with laboratory tests, the qc obtained from the dynamic penetration tests and the Vs acquired from the SASW measurements permit to assess the accuracy of the procedure and to evaluate its limitations. The depth to bedrock determined by this procedure can then be combined with the soil erosion susceptibility to produce a risk map. This methodology will help to target measures within areas that show a reduced soil depth associated with a high soil erosion susceptibility.

Factors influencing in situ gamma-ray measurements

NASA Astrophysics Data System (ADS)

Loonstra, E. H.; van Egmond, F. M.

2009-04-01

Introduction In situ passive gamma-ray sensors are very well suitable for mapping physical soil properties. In order to make a qualitative sound soil map, high quality input parameters for calibration are required. This paper will focus on the factors that affect the output of in situ passive gamma-ray sensors, the primary source, soil, not taken into account. Factors The gamma-ray spectrum contains information of naturally occurring nuclides 40K, 238U and 232Th and man-made nuclides like 137Cs, as well as the total count rate. Factors that influence the concentration of these nuclides and the count rate can be classified in 3 categories. These are sensor design, environmental conditions and operational circumstances. Sensor design The main elements of an in situ gamma-ray sensor that influence the outcome and quality of the output are the crystal and the spectrum analysis method. Material and size of the crystal determine the energy resolution. Though widely used, NaI crystals are not the most efficient capturer of gamma radiation. Alternatives are BGO and CsI. BGO has a low peak resolution, which prohibits use in cases where man-made nuclides are subject of interest. The material is expensive and prone to temperature instability. CsI is robust compared to NaI and BGO. The density of CsI is higher than NaI, yielding better efficiency, especially for smaller crystal sizes. More volume results in higher energy efficiency. The reduction of the measured spectral information into concentration of radionuclides is mostly done using the Windows analysis method. In Windows, the activities of the nuclides are found by summing the intensities of the spectrum found in a certain interval surrounding a peak. A major flaw of the Windows method is the limited amount of spectral information that is incorporated into the analysis. Another weakness is the inherent use of ‘stripping factors' to account for contributions of radiation from nuclide A into the peak of nuclide B. This can be overcome using Full Spectrum Analysis (FSA). This method incorporates virtually all data present in the measured gamma spectrum. In FSA, a Chi-squared algorithm is used to fit a set of "Standard Spectra" to the measured spectrum. The uncertainty in the FSA method is at least a factor 2 lower compared to the Windows method. Environmental conditions Environmental conditions can influence the signal output and therefore the quality. In general, the density of the medium through which gamma-radiation travels determines the interaction of the radiation with matter and thus affects the sensor readings. Excluding soil as being the source; water is the most important external factor in this respect. The amount of water in soil will affect the signal. In general, energy loss occurs as water content in soil increases. As a result, the nuclide concentrations will be lower. Monte Carlo simulations show a difference of 16% in nuclide concentration for completely dry and fully saturated sandy soils. Another water related issue is rainfall. With rain radon gas, a product of 238U, will precipitate. This causes spectral noise effects. Snow and fog have the same effect to a minor degree. Another aspect is the openness of soil. From experience we know that the concentration of 40K differs if soil is tilled. Finally, on earth there is always radioactive noise present from the galaxy. The "Standard Spectra" used in the FSA method can take noise and geometric effects into account. Operational circumstances During a survey an operator should be aware of the effects of driving speed and measurement height. In general, a larger crystal has better energy efficiency and is therefore more suitable for high speed. E.g. a 70 x 150 mm CsI crystal provides qualitative satisfactory output for soil mapping up to 10 km/hr. Sample locations, however, are best measured during a longer period (3 to 5 minutes). The measurement height affects the measurement resolution; the lower the sensor, the smaller the measured area. In addition, Monte Carlo simulations show that the mass of the survey vehicle has to be taken into account. A large tractor e.g. can lead to spectral shape disruptions of 5 to 10%. Conclusion Several factors can effect the measured concentrations of radioactive nuclides. Potential users should take mentioned factors into account in respect to their needs when building and applying gamma-ray sensors. For purposes of soil mapping the use of FSA method is preferred, as it incorporates several disturbing factors. This allows the user to create a consistent dataset which will lead to a better understanding of the relation between nuclide concentrations and physical soil properties.

Effects of Long-term Soil and Crop Management on Soil Hydraulic Properties for Claypan Soils

USDA-ARS?s Scientific Manuscript database

Regional and national soil maps and associated databases of soil properties have been developed to help land managers make decisions based on soil characteristics. Hydrologic modelers also utilize soil hydraulic properties provided in these databases, in which soil characterization is based on avera...

Validating a spatially distributed hydrological model with soil morphology data

NASA Astrophysics Data System (ADS)

Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.

2013-10-01

Spatially distributed hydrological models are popular tools in hydrology and they are claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time-series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for the transport of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography. Around 40% of the catchment area are artificially drained. We measured weather data, discharge and groundwater levels in 11 piezometers for 1.5 yr. For broadening the spatially distributed data sets that can be used for model calibration and validation, we translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. We used redox-morphology signs for these estimates. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to the groundwater levels in the piezometers and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the accuracy of the groundwater level predictions was not high enough to be used for the prediction of saturated areas. The groundwater level dynamics were not adequately reproduced and the predicted spatial patterns of soil saturation did not correspond to the patterns estimated from the soil map. Our results indicate that an accurate prediction of the groundwater level dynamics of the shallow groundwater in our catchment that is subject to artificial drainage would require a more complex model. Especially high spatial resolution and very detailed process representations at the boundary between the unsaturated and the saturated zone are expected to be crucial. The data needed for such a detailed model are not generally available. The high computational demand and the complex model setup would require more resources than the direct identification of saturated areas in the field. This severely hampers the practical use of such models despite their usefulness for scientific purposes.

The application of remote sensing technology to the solution of problems in the management of resources in Indiana

NASA Technical Reports Server (NTRS)

Weismiller, R. A. (Principal Investigator); Mroczynski, R. P.

1977-01-01

The author has identified the following significant results. The Lydich quadrangle area was successfully classified into seven cover types: (1) trees, (2) poorly drained soil and water, (3) pasture land, (4) well drained brown soil, (5) moderately well drained dark brown soil, (6) moderately drained soil, and (7) medium to poorly drained soil. Measurements of the percent of mapping unit represented by a named soil series range from 44 to 55 percent. If the class identified as vegetation is combined with the named unit, the range increases from 54 to 64 percent. The Xenia mapping unit was the only unit represented by less than 50 percent of the named unit. Results from the intensive tent moth study in Owensburg and Williams were interpreted from 70 mm color infrared and visually transferred to maps. A correction factor was necessary, because the date the sample photography was taken was a month later than the intensive site data (CF x acres defoliated in each level = expanded defoliated acres).

The Soil Moisture Active and Passive Mission (SMAP): Science and Applications

NASA Technical Reports Server (NTRS)

Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni

2009-01-01

The Soil Moisture Active and Passive mission (SMAP) will provide global maps of soil moisture content and surface freeze/thaw state. Global measurements of these variables are critical for terrestrial water and carbon cycle applications. The SMAP observatory consists of two multipolarization L-band sensors, a radar and radiometer, that share a deployable-mesh reflector antenna. The combined observations from the two sensors will allow accurate estimation of soil moisture at hydrometeorological (10 km) and hydroclimatological (40 km) spatial scales. The rotating antenna configuration provides conical scans of the Earth surface at a constant look angle. The wide-swath (1000 km) measurements will allow global mapping of soil moisture and its freeze/thaw state with 2-3 days revisit. Freeze/thaw in boreal latitudes will be mapped using the radar at 3 km resolution with 1-2 days revisit. The synergy of active and passive observations enables measurements of soil moisture and freeze/thaw state with unprecedented resolution, sensitivity, area coverage and revisit.

NASA Soil Moisture Mission Produces First Global Radar Map

NASA Image and Video Library

2015-04-21

With its antenna now spinning at full speed, NASA new Soil Moisture Active Passive SMAP observatory has successfully re-tested its science instruments and generated its first global maps, a key step to beginning routine science operations in May, 2015

NASA Soil Moisture Mission Produces First Global Radiometer Map

NASA Image and Video Library

2015-04-21

With its antenna now spinning at full speed, NASA new Soil Moisture Active Passive SMAP observatory has successfully re-tested its science instruments and generated its first global maps, a key step to beginning routine science operations in May, 2015

Remote sensing of soils, land forms, and land use in the northern Great Plains in preparation for ERTS applications

NASA Technical Reports Server (NTRS)

Frazee, C. J.; Westin, F. C.; Gropper, J.; Myers, V. I.

1972-01-01

Research to determine the optimum time or season for obtaining imagery to identify and map soil limitations was conducted in the proposed Oahe irrigation project area in South Dakota. The optimum time for securing photographs or imagery is when the soil surface patterns are most apparent. For cultivated areas similar to the study area, May is the optimum time. The density slicing analysis of the May image provided additional and more accurate information than did the existing soil map. The soil boundaries were more accurately located. The use of a density analysis system for an operational soil survey has not been tested, but is obviously dependent upon securing excellent photographs for interpretation. The colors or densities of photographs will have to be corrected for sun angle effects, vignetting effects, and processing to have maximum effectiveness for mapping soil limitations. Rangeland sites were established in Bennett County, South Dakota to determine the usefulness of ERTS imagery. Imagery from these areas was interpreted for land use and drainage patterns.

Case studies: Soil mapping using multiple methods

NASA Astrophysics Data System (ADS)

Petersen, Hauke; Wunderlich, Tina; Hagrey, Said A. Al; Rabbel, Wolfgang; Stümpel, Harald

2010-05-01

Soil is a non-renewable resource with fundamental functions like filtering (e.g. water), storing (e.g. carbon), transforming (e.g. nutrients) and buffering (e.g. contamination). Degradation of soils is meanwhile not only to scientists a well known fact, also decision makers in politics have accepted this as a serious problem for several environmental aspects. National and international authorities have already worked out preservation and restoration strategies for soil degradation, though it is still work of active research how to put these strategies into real practice. But common to all strategies the description of soil state and dynamics is required as a base step. This includes collecting information from soils with methods ranging from direct soil sampling to remote applications. In an intermediate scale mobile geophysical methods are applied with the advantage of fast working progress but disadvantage of site specific calibration and interpretation issues. In the framework of the iSOIL project we present here some case studies for soil mapping performed using multiple geophysical methods. We will present examples of combined field measurements with EMI-, GPR-, magnetic and gammaspectrometric techniques carried out with the mobile multi-sensor-system of Kiel University (GER). Depending on soil type and actual environmental conditions, different methods show a different quality of information. With application of diverse methods we want to figure out, which methods or combination of methods will give the most reliable information concerning soil state and properties. To investigate the influence of varying material we performed mapping campaigns on field sites with sandy, loamy and loessy soils. Classification of measured or derived attributes show not only the lateral variability but also gives hints to a variation in the vertical distribution of soil material. For all soils of course soil water content can be a critical factor concerning a succesful application of geophysical methods, e.g. GPR on wet loessy soils will result in a high attenuation of signals. Furthermore, with this knowledge we support the development of geophysical pedo-transfer-functions, i.e. the link between geophysical to soil parameters, which is active researched in another work package of the iSOIL project. Acknowledgement: iSOIL-Interactions between soil related sciences - Linking geophysics, soil science and digital soil mapping is a Collaborative Project (Grant Agreement number 211386) co-funded by the Research DG of the European Commission within the RTD activities of the FP7 Thematic Priority Environment.

Remotely sensed soil moisture input to a hydrologic model

NASA Technical Reports Server (NTRS)

Engman, E. T.; Kustas, W. P.; Wang, J. R.

1989-01-01

The possibility of using detailed spatial soil moisture maps as input to a runoff model was investigated. The water balance of a small drainage basin was simulated using a simple storage model. Aircraft microwave measurements of soil moisture were used to construct two-dimensional maps of the spatial distribution of the soil moisture. Data from overflights on different dates provided the temporal changes resulting from soil drainage and evapotranspiration. The study site and data collection are described, and the soil measurement data are given. The model selection is discussed, and the simulation results are summarized. It is concluded that a time series of soil moisture is a valuable new type of data for verifying model performance and for updating and correcting simulated streamflow.

Potential Electrokinetic Remediation Technologies of Laboratory Scale into Field Application- Methodology Overview

NASA Astrophysics Data System (ADS)

Ayuni Suied, Anis; Tajudin, Saiful Azhar Ahmad; Nizam Zakaria, Muhammad; Madun, Aziman

2018-04-01

Heavy metal in soil possesses high contribution towards soil contamination which causes to unbalance ecosystem. There are many ways and procedures to make the electrokinetic remediation (EKR) method to be efficient, effective, and potential as a low cost soil treatment. Electrode compartment for electrolyte is expected to treat the contaminated soil through electromigration and enhance metal ions movement. The electrokinetic is applicable for many approaches such as electrokinetic remediation (EKR), electrokinetic stabilization (EKS), electrokinetic bioremediation and many more. This paper presents a critical review on comparison of laboratory scale between EKR, EKS and EK bioremediation treatment by removing the heavy metal contaminants. It is expected to propose one framework of contaminated soil mapping. Electrical Resistivity Method (ERM) is one of famous indirect geophysical tools for surface mapping and subsurface profiling. Hence, ERM is used to mapping the migration of heavy metal ions by electrokinetic.

Predicting large wildfires across western North America by modeling seasonal variation in soil water balance.

PubMed

Waring, Richard H; Coops, Nicholas C

A lengthening of the fire season, coupled with higher temperatures, increases the probability of fires throughout much of western North America. Although regional variation in the frequency of fires is well established, attempts to predict the occurrence of fire at a spatial resolution <10 km 2 have generally been unsuccessful. We hypothesized that predictions of fires might be improved if depletion of soil water reserves were coupled more directly to maximum leaf area index (LAI max ) and stomatal behavior. In an earlier publication, we used LAI max and a process-based forest growth model to derive and map the maximum available soil water storage capacity (ASW max ) of forested lands in western North America at l km resolution. To map large fires, we used data products acquired from NASA's Moderate Resolution Imaging Spectroradiometers (MODIS) over the period 2000-2009. To establish general relationships that incorporate the major biophysical processes that control evaporation and transpiration as well as the flammability of live and dead trees, we constructed a decision tree model (DT). We analyzed seasonal variation in the relative availability of soil water ( fASW ) for the years 2001, 2004, and 2007, representing respectively, low, moderate, and high rankings of areas burned. For these selected years, the DT predicted where forest fires >1 km occurred and did not occur at ~100,000 randomly located pixels with an average accuracy of 69 %. Extended over the decade, the area predicted burnt varied by as much as 50 %. The DT identified four seasonal combinations, most of which included exhaustion of ASW during the summer as critical; two combinations involving antecedent conditions the previous spring or fall accounted for 86 % of the predicted fires. The approach introduced in this paper can help identify forested areas where management efforts to reduce fire hazards might prove most beneficial.

Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

USGS Publications Warehouse

Wang, A.; Moore, J.C.; Cui, Xingquan; Ji, D.; Li, Q.; Zhang, N.; Wang, C.; Zhang, S.; Lawrence, D.M.; McGuire, A.D.; Zhang, W.; Delire, C.; Koven, C.; Saito, K.; MacDougall, A.; Burke, E.; Decharme, B.

2016-01-01

 We perform a land-surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies among six modern stand-alone land-surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by five different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99 to 135  ×  104 km2) between the two diagnostic methods based on air temperature which are also consistent with the observation-based estimate of actual permafrost area (101  × 104 km2). However the uncertainty (1 to 128  ×  104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on the TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air-temperature-based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification, vegetation types and snow cover. Models are particularly poor at simulating permafrost distribution using the definition that soil temperature remains at or below 0 °C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land-surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in future permafrost distribution can be made for the Tibetan Plateau.

Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

NASA Astrophysics Data System (ADS)

Wang, W.; Rinke, A.; Moore, J. C.; Cui, X.; Ji, D.; Li, Q.; Zhang, N.; Wang, C.; Zhang, S.; Lawrence, D. M.; McGuire, A. D.; Zhang, W.; Delire, C.; Koven, C.; Saito, K.; MacDougall, A.; Burke, E.; Decharme, B.

2016-02-01

We perform a land-surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies among six modern stand-alone land-surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by five different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99 to 135 × 104 km2) between the two diagnostic methods based on air temperature which are also consistent with the observation-based estimate of actual permafrost area (101 × 104 km2). However the uncertainty (1 to 128 × 104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on the TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air-temperature-based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification, vegetation types and snow cover. Models are particularly poor at simulating permafrost distribution using the definition that soil temperature remains at or below 0 °C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land-surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in future permafrost distribution can be made for the Tibetan Plateau.

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

Scaling up from field to region for wind erosion prediction using a field-scale wind erosion model and GIS

USGS Publications Warehouse

Zobeck, T.M.; Parker, N.C.; Haskell, S.; Guoding, K.

2000-01-01

Factors that affect wind erosion such as surface vegetative and other cover, soil properties and surface roughness usually change spatially and temporally at the field-scale to produce important field-scale variations in wind erosion. Accurate estimation of wind erosion when scaling up from fields to regions, while maintaining meaningful field-scale process details, remains a challenge. The objectives of this study were to evaluate the feasibility of using a field-scale wind erosion model with a geographic information system (GIS) to scale up to regional levels and to quantify the differences in wind erosion estimates produced by different scales of soil mapping used as a data layer in the model. A GIS was used in combination with the revised wind erosion equation (RWEQ), a field-scale wind erosion model, to estimate wind erosion for two 50 km2 areas. Landsat Thematic Mapper satellite imagery from 1993 with 30 m resolution was used as a base map. The GIS database layers included land use, soils, and other features such as roads. The major land use was agricultural fields. Data on 1993 crop management for selected fields of each crop type were collected from local government agency offices and used to 'train' the computer to classify land areas by crop and type of irrigation (agroecosystem) using commercially available software. The land area of the agricultural land uses was overestimated by 6.5% in one region (Lubbock County, TX, USA) and underestimated by about 21% in an adjacent region (Terry County, TX, USA). The total estimated wind erosion potential for Terry County was about four times that estimated for adjacent Lubbock County. The difference in potential erosion among the counties was attributed to regional differences in surface soil texture. In a comparison of different soil map scales in Terry County, the generalised soil map had over 20% more of the land area and over 15% greater erosion potential in loamy sand soils than did the detailed soil map. As a result, the wind erosion potential determined using the generalised soil map Was about 26% greater than the erosion potential estimated by using the detailed soil map in Terry County. This study demonstrates the feasibility of scaling up from fields to regions to estimate wind erosion potential by coupling a field-scale wind erosion model with GIS and identifies possible sources of error with this approach.

An assessment of gas emanation hazard using a geographic information system and geostatistics.

PubMed

Astorri, F; Beaubien, S E; Ciotoli, G; Lombardi, S

2002-03-01

This paper describes the use of geostatistical analysis and GIS techniques to assess gas emanation hazards. The Mt. Vulsini volcanic district was selected for this study because of the wide range of natural phenomena locally present that affect gas migration in the near surface. In addition, soil gas samples that were collected in this area should allow for a calibration between the generated risk/hazard models and the measured distribution of toxic gas species at surface. The approach used during this study consisted of three general stages. First data were digitally organized into thematic layers, then software functions in the GIS program "ArcView" were used to compare and correlate these various layers, and then finally the produced "potential-risk" map was compared with radon soil gas data in order to validate the model and/or to select zones for further, more-detailed soil gas investigations.

Evaluating the role of soil variability on groundwater pollution and recharge at regional scale by integrating a process-based vadose zone model in a stochastic approach

NASA Astrophysics Data System (ADS)

Coppola, Antonio; Comegna, Alessandro; Dragonetti, Giovanna; Lamaddalena, Nicola; Zdruli, Pandi

2013-04-01

Interpreting and predicting the evolution of water resources and soils at regional scale are continuing challenges for natural scientists. Examples include non-point source (NPS) pollution of soil and surface and subsurface water from agricultural chemicals and pathogens, as well as overexploitation of groundwater resources. The presence and build up of NPS pollutants may be harmful for both soil and groundwater resources. The accumulation of salts and trace elements in soils can significantly impact crop productivity, while loading of salts, nitrates, trace elements and pesticides into groundwater supplies can deteriorate a source of drinking and irrigation water. Consequently, predicting the spatial distribution and fate of NPS pollutants in soils at applicative scales is now considered crucial for maintaining the fragile balance between crop productivity and the negative environmental impacts of NPS pollutants, which is a basis of sustainable agriculture. Soil scientists and hydrologists are regularly asked to assist state agencies to understand these critical environmental issues. The most frequent inquiries are related to the development of mathematical models needed for analyzing the impacts of alternative land-use and best management use and management of soil and water resources. Different modelling solutions exist, mainly differing on the role of the vadose zone and its horizontal and vertical variability in the predictive models. The vadose zone (the region from the soil surface to the groundwater surface) is a complex physical, chemical and biological ecosystem that controls the passage of NPS pollutants from the soil surface where they have been deposited or accumulated due to agricultural activities, to groundwater. Physically based distributed hydrological models require the internal variability of the vadose zone be explored at a variety of scales. The equations describing fluxes and storage of water and solutes in the unsaturated zone used in these modelling approaches have been developed at small space scales. Their extension to the applicative macroscale of the regional model is not a simple task mainly because of the heterogeneity of vadose zone properties, as well as of non-linearity of hydrological processes. Besides, one of the problems when applying distributed models is that spatial and temporal scales for data to be used as input in the models vary on a wide range of scales and are not always consistent with the model structure. Under these conditions, a strictly deterministic response to questions about the fate of a pollutant in the soil is impossible. At best, one may answer "this is the average behaviour within this uncertainty band". Consequently, the extension of these equations to account for regional-scale processes requires the uncertainties of the outputs be taken into account if the pollution vulnerability maps that may be drawn are to be used as agricultural management tools. A map generated without a corresponding map of associated uncertainties has no real utility. The stochastic stream tube approach is a frequently used to the water flux and solute transport through the vadose zone at applicative scales. This approach considers the field soil as an ensemble of parallel and statistically independent tubes, assuming only vertical flow. The stream tubes approach is generally used in a probabilistic framework. Each stream tube defines local flow properties that are assumed to vary randomly between the different stream tubes. Thus, the approach allows average water and solute behaviour be described, along with the associated uncertainty bands. These stream tubes are usually considered to have parameters that are vertically homogeneous. This would be justified by the large difference between the horizontal and vertical extent of the spatial applicative scale. Vertical is generally overlooked. Obviously, all the model outputs are conditioned by this assumption. The latter, in turn, is more dictated by the lack of information on vertical variability of soil properties. It is our opinion that, with sufficient information on soil horizonation and with an appropriate horizontal resolution, it may be demonstrated that model outputs may be largely sensitive to the vertical variability of stream tubes, even at applicative scales. Horizon differentiation is one of the main observations made by pedologists while describing soils and most analytical data are given according to soil horizons. Over the last decades, soil horizonation has been subjected to regular monitoring for mapping soil variation at regional scales. Accordingly, this study mainly aims to developing a regional-scale simulation approach for vadose zone flow and transport that use real soil profiles data based on information on vertical variability of soils. As to the methodology, the parallel column concept was applied to account for the effect of vertical heterogeneity on variability of water flow and solute transport in the vadose zone. Even if the stream tube approach was mainly introduced for (unrealistic) vertically homogeneous soils, we extended their use to real vertically variable soils. The approach relies on available datasets coming from different sources and offers quantitative answers to soil and groundwater vulnerability to non-point source of chemicals and pathogens at regional scale within a defined confidence interval. This result will be pursued through the design and building up of a spatial database containing 1). Detailed pedological information, 2). Hydrological properties mainly measured in the investigated area in different soil horizons, 3). Water table depth, 4). Spatially distributed climatic temporal series, and 5). Land use. The area of interest for the study is located in the sub-basin of Metaponto agricultural site, located in southern Basilicata Region in Italy, covering approximately 11,698 hectares, crossed by two main rivers, Sinni and Agri and from many secondary water bodies. Distributed output of soil pollutant leaching behaviour, with corresponding statistical uncertainties, will be provided and finally visualized in GIS maps. The example pollutants considered cover much of the practical pollution conditions one may found in the reality. Nevertheless, this regional- scale methodology may be applied to any specific pollutants for any soil, climatic and land use conditions. Also, as the approach is built on physically based equations, it may be extended to the predictions of any water and solute storage and fluxes (i.e., groundwater recharge) in the vadose zone. By integrating the scientific results with economic and political considerations, and with advanced information technologies, the NPS-pollution assessment may become a powerful decision support tool for guiding activities involving soil and groundwater resources and, more in general, for managing environmental resources.

Soil erosion assessment and its correlation with landslide events using remote sensing data and GIS: a case study at Penang Island, Malaysia.

PubMed

Pradhan, Biswajeet; Chaudhari, Amruta; Adinarayana, J; Buchroithner, Manfred F

2012-01-01

In this paper, an attempt has been made to assess, prognosis and observe dynamism of soil erosion by universal soil loss equation (USLE) method at Penang Island, Malaysia. Multi-source (map-, space- and ground-based) datasets were used to obtain both static and dynamic factors of USLE, and an integrated analysis was carried out in raster format of GIS. A landslide location map was generated on the basis of image elements interpretation from aerial photos, satellite data and field observations and was used to validate soil erosion intensity in the study area. Further, a statistical-based frequency ratio analysis was carried out in the study area for correlation purposes. The results of the statistical correlation showed a satisfactory agreement between the prepared USLE-based soil erosion map and landslide events/locations, and are directly proportional to each other. Prognosis analysis on soil erosion helps the user agencies/decision makers to design proper conservation planning program to reduce soil erosion. Temporal statistics on soil erosion in these dynamic and rapid developments in Penang Island indicate the co-existence and balance of ecosystem.

Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.

2015-01-01

Accurately estimating aboveground vegetation biomass productivity is essential for local ecosystem assessment and best land management practice. Satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. A 250-m grassland biomass productivity map for the Greater Platte River Basin had been developed based on the relationship between Moderate Resolution Imaging Spectroradiometer (MODIS) GSN and Soil Survey Geographic (SSURGO) annual grassland productivity. However, the 250-m MODIS grassland biomass productivity map does not capture detailed ecological features (or patterns) and may result in only generalized estimation of the regional total productivity. Developing a high or moderate spatial resolution (e.g., 30-m) productivity map to better understand the regional detailed vegetation condition and ecosystem services is preferred. The 30-m Landsat data provide spatial detail for characterizing human-scale processes and have been successfully used for land cover and land change studies. The main goal of this study is to develop a 30-m grassland biomass productivity estimation map for central Nebraska, leveraging 250-m MODIS GSN and 30-m Landsat data. A rule-based piecewise regression GSN model based on MODIS and Landsat (r = 0.91) was developed, and a 30-m MODIS equivalent GSN map was generated. Finally, a 30-m grassland biomass productivity estimation map, which provides spatially detailed ecological features and conditions for central Nebraska, was produced. The resulting 30-m grassland productivity map was generally supported by the SSURGO biomass production map and will be useful for regional ecosystem study and local land management practices.

Digital Mapping of Soil Organic Carbon Contents and Stocks in Denmark

PubMed Central

Adhikari, Kabindra; Hartemink, Alfred E.; Minasny, Budiman; Bou Kheir, Rania; Greve, Mette B.; Greve, Mogens H.

2014-01-01

Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance inventories. For Denmark, we modeled the vertical distribution of soil organic carbon (SOC) and bulk density, and mapped its spatial distribution at five standard soil depth intervals (0−5, 5−15, 15−30, 30−60 and 60−100 cm) using 18 environmental variables as predictors. SOC distribution was influenced by precipitation, land use, soil type, wetland, elevation, wetness index, and multi-resolution index of valley bottom flatness. The highest average SOC content of 20 g kg−1 was reported for 0−5 cm soil, whereas there was on average 2.2 g SOC kg−1 at 60−100 cm depth. For SOC and bulk density prediction precision decreased with soil depth, and a standard error of 2.8 g kg−1 was found at 60−100 cm soil depth. Average SOC stock for 0−30 cm was 72 t ha−1 and in the top 1 m there was 120 t SOC ha−1. In total, the soils stored approximately 570 Tg C within the top 1 m. The soils under agriculture had the highest amount of carbon (444 Tg) followed by forest and semi-natural vegetation that contributed 11% of the total SOC stock. More than 60% of the total SOC stock was present in Podzols and Luvisols. Compared to previous estimates, our approach is more reliable as we adopted a robust quantification technique and mapped the spatial distribution of SOC stock and prediction uncertainty. The estimation was validated using common statistical indices and the data and high-resolution maps could be used for future soil carbon assessment and inventories. PMID:25137066

Digital mapping of soil organic carbon contents and stocks in Denmark.

PubMed

Adhikari, Kabindra; Hartemink, Alfred E; Minasny, Budiman; Bou Kheir, Rania; Greve, Mette B; Greve, Mogens H

2014-01-01

Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance inventories. For Denmark, we modeled the vertical distribution of soil organic carbon (SOC) and bulk density, and mapped its spatial distribution at five standard soil depth intervals (0-5, 5-15, 15-30, 30-60 and 60-100 cm) using 18 environmental variables as predictors. SOC distribution was influenced by precipitation, land use, soil type, wetland, elevation, wetness index, and multi-resolution index of valley bottom flatness. The highest average SOC content of 20 g kg(-1) was reported for 0-5 cm soil, whereas there was on average 2.2 g SOC kg(-1) at 60-100 cm depth. For SOC and bulk density prediction precision decreased with soil depth, and a standard error of 2.8 g kg(-1) was found at 60-100 cm soil depth. Average SOC stock for 0-30 cm was 72 t ha(-1) and in the top 1 m there was 120 t SOC ha(-1). In total, the soils stored approximately 570 Tg C within the top 1 m. The soils under agriculture had the highest amount of carbon (444 Tg) followed by forest and semi-natural vegetation that contributed 11% of the total SOC stock. More than 60% of the total SOC stock was present in Podzols and Luvisols. Compared to previous estimates, our approach is more reliable as we adopted a robust quantification technique and mapped the spatial distribution of SOC stock and prediction uncertainty. The estimation was validated using common statistical indices and the data and high-resolution maps could be used for future soil carbon assessment and inventories.

Dependence of the cyclization of branched tetraethers on soil moisture in alkaline soils from arid-subhumid China: implications for palaeorainfall reconstructions on the Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Wang, H.; Liu, W.; Zhang, C. L.

2014-12-01

The use of branched glycerol dialkyl glycerol tetraethers (bGDGTs) in loess-palaeosol sequences (LPSs) has shown promises in continental palaeotemperature reconstructions. Thus far, however, little is known about the effect of soil moisture on their distributions in the water-limited Chinese Loess Plateau (CLP). In this study, the relationships between environmental variables and the cyclization of branched tetraethers (CBT) were investigated in arid-subhumid China using 97 surface soils in the CLP and its vicinity, as well as 78 soils with pH > 7 which have been previously published. We find that CBT correlates best with soil water content (SWC) or mean annual precipitation (MAP) for the overall data set. This indicates that CBT is mainly controlled by soil moisture instead of soil pH in alkaline soils from arid-subhumid regions, where water availability is a limiting factor for the producers of bGDGTs. Therefore, we suggest that CBT can potentially be used as a palaeorainfall proxy on the alkaline CLP. According to the preliminary CBT-MAP relationship for modern CLP soils (CBT = -0.0021 × MAP + 1.7, n = 37, r = -0.93), palaeorainfall history was reconstructed from three LPSs (Yuanbao, Lantian, and Mangshan) with published bGDGT data spanning the past 70 ka. The CBT-derived MAP records of the three sites consistently show precession-driven variation resembling the monsoon record based on speleothem δ18O, supporting CBT as a reasonable proxy for palaeorainfall reconstruction in LPS. The direct application of CBT as a palaeorainfall proxy in corroboration with the bGDGT-based temperature proxy may enable us to further assess the temperature/hydrological association for palaeoclimate studies on the CLP.

Irrigation salinity hazard assessment and risk mapping in the lower Macintyre Valley, Australia.

PubMed

Huang, Jingyi; Prochazka, Melissa J; Triantafilis, John

2016-05-01

In the Murray-Darling Basin of Australia, secondary soil salinization occurs due to excessive deep drainage and the presence of shallow saline water tables. In order to understand the cause and best management, soil and vadose zone information is necessary. This type of information has been generated in the Toobeah district but owing to the state border an inconsistent methodology was used. This has led to much confusion from stakeholders who are unable to understand the ambiguity of the results in terms of final overall risk of salinization. In this research, a digital soil mapping method that employs various ancillary data is presented. Firstly, an electromagnetic induction survey using a Geonics EM34 and EM38 was used to characterise soil and vadose zone stratigraphy. From the apparent electrical conductivity (ECa) collected, soil sampling locations were selected and with laboratory analysis carried out to determine average (2-12m) clay and EC of a saturated soil-paste extract (ECe). EM34 ECa, land surface parameters derived from a digital elevation model and measured soil data were used to establish multiple linear regression models, which allowed for mapping of various hazard factors, including clay and ECe. EM38 ECa data were calibrated to deep drainage obtained from Salt and Leaching Fraction (SaLF) modelling of soil data. Expert knowledge and indicator kriging were used to determine critical values where the salinity hazard factors were likely to contribute to a shallow saline water table (i.e., clay ≤35%; ECe>2.5dS/m, and deep drainage >100mm/year). This information was combined to produce an overall salinity risk map for the Toobeah district using indicator kriging. The risk map shows potential salinization areas and where detailed information is required and where targeted research can be conducted to monitor soil conditions and water table heights and determine best management strategies. Copyright © 2016 Elsevier B.V. All rights reserved.

Integrating proximal soil sensing techniques and terrain indexes to generate 3D maps of soil restrictive layers in the Palouse region, Washington, USA

NASA Astrophysics Data System (ADS)

Poggio, Matteo; Brown, David J.; Gasch, Caley K.; Brooks, Erin S.; Yourek, Matt A.

2015-04-01

In the Palouse region of eastern Washington and northern Idaho (USA), spatially discontinuous restrictive layers impede rooting growth and water infiltration. Consequently, accurate maps showing the depth and spatial extent of these restrictive layers are essential for watershed hydrologic modeling appropriate for precision agriculture. In this presentation, we report on the use of a Visible and Near-Infrared (VisNIR) penetrometer fore optic to construct detailed maps of three wheat fields in the Palouse region. The VisNIR penetrometer was used to deliver in situ soil reflectance to an Analytical Spectral Devices (ASD, Boulder, CO, USA) spectrometer and simultaneously acquire insertion force. With a hydraulic push-type soil coring systems for insertion (e.g. Giddings), we collected soil spectra and insertion force data along 41m x 41m grid points (2 fields) and 50m x 50m grid points (1 field) to ≈80cm depth, in addition to interrogation points at 36 representative instrumented locations per field. At each of the 36 instrumented locations, two soil cores were extracted for laboratory determination of clay content and bulk density. We developed calibration models of soil clay content and bulk density with spectra and insertion force collected in situ, using partial least squares regression 2 (PLSR2). Applying spline functions, we delineated clay and bulk density profiles at each points (grid and 24 locations). The soil profiles were then used as inputs in a regression-kriging model with terrain indexes and ECa data (derived from an EM38 field survey, Geonics, Mississauga, Ontario, Canada) as covariates to generate 3D soil maps. Preliminary results show that the VisNIR penetrometer can capture the spatial patterns of restrictive layers. Work is ongoing to evaluate the prediction accuracy of penetrometer-derived 3D clay content and restriction layer maps.

Soil Salinity Mapping in Everglades National Park Using Remote Sensing Techniques

NASA Astrophysics Data System (ADS)

Su, H.; Khadim, F. K.; Blankenship, J.; Sobhan, K.

2017-12-01

The South Florida Everglades is a vast subtropical wetland with a globally unique hydrology and ecology, and it is designated as an International Biosphere Reserve and a Wetland of International Importance. Everglades National Park (ENP) is a hydro-ecologically enriched wetland with varying salinity contents, which is a concern for terrestrial ecosystem balance and sustainability. As such, in this study, time series soil salinity mapping was carried out for the ENP area. The mapping first entailed a maximum likelihood classification of seven land cover classes for the ENP area—namely mangrove forest, mangrove scrub, low-density forest, sawgrass, prairies and marshes, barren lands with woodland hammock and water—for the years 1996, 2000, 2006, 2010 and 2015. The classifications for 1996-2010 yielded accuracies of 82%-94%, and the 2015 classification was supported through ground truthing. Afterwards, electric conductivity (EC) tolerance thresholds for each vegetation class were established,which yielded soil salinity maps comprising four soil salinity classes—i.e., the non- (EC = 0 2 dS/m), low- (EC = 2 4 dS/m), moderate- (EC = 4 8 dS/m) and high-saline (EC = >8 dS/m) areas. The soil salinity maps visualized the spatial distribution of soil salinity with no significant temporal variations. The innovative approach of "land cover identification to salinity estimation" used in the study is pragmatic and application oriented, and the study upshots are also useful, considering the diversifying ecological context of the ENP area.

Simulating climate change impact on soil erosion using RUSLE model - A case study in a watershed of mid-Himalayan landscape

NASA Astrophysics Data System (ADS)

Gupta, Surya; Kumar, Suresh

2017-06-01

Climate change, particularly due to the changed precipitation trend, can have a severe impact on soil erosion. The effect is more pronounced on the higher slopes of the Himalayan region. The goal of this study was to estimate the impact of climate change on soil erosion in a watershed of the Himalayan region using RUSLE model. The GCM (general circulation model) derived emission scenarios (HadCM3 A2a and B2a SRES) were used for climate projection. The statistical downscaling model (SDSM) was used to downscale the precipitation for three future periods, 2011-2040, 2041-2070, and 2071-2099, at large scale. Rainfall erosivity ( R) was calculated for future periods using the SDSM downscaled precipitation data. ASTER digital elevation model (DEM) and Indian Remote Sensing data - IRS LISS IV satellite data were used to generate the spatial input parameters required by RUSLE model. A digital soil-landscape map was prepared to generate spatially distributed soil erodibility ( K) factor map of the watershed. Topographic factors, slope length ( L) and steepness ( S) were derived from DEM. Normalised difference vegetation index (NDVI) derived from the satellite data was used to represent spatial variation vegetation density and condition under various land use/land cover. This variation was used to represent spatial vegetation cover factor. Analysis revealed that the average annual soil loss may increase by 28.38, 25.64 and 20.33% in the 2020s, 2050s and 2080s, respectively under A2 scenario, while under B2 scenario, it may increase by 27.06, 25.31 and 23.38% in the 2020s, 2050s and 2080s, respectively, from the base period (1985-2013). The study provides a comprehensive understanding of the possible future scenario of soil erosion in the mid-Himalaya for scientists and policy makers.

SOIL Geo-Wiki: A tool for improving soil information

NASA Astrophysics Data System (ADS)

Skalský, Rastislav; Balkovic, Juraj; Fritz, Steffen; See, Linda; van der Velde, Marijn; Obersteiner, Michael

2014-05-01

Crowdsourcing is increasingly being used as a way of collecting data for scientific research, e.g. species identification, classification of galaxies and unravelling of protein structures. The WorldSoilProfiles.org database at ISRIC is a global collection of soil profiles, which have been 'crowdsourced' from experts. This system, however, requires contributors to have a priori knowledge about soils. Yet many soil parameters can be observed in the field without specific knowledge or equipment such as stone content, soil depth or color. By crowdsourcing this information over thousands of locations, the uncertainty in current soil datasets could be radically reduced, particularly in areas currently without information or where multiple interpretations are possible from different existing soil maps. Improved information on soils could benefit many research fields and applications. Better soil data could enhance assessments of soil ecosystem services (e.g. soil carbon storage) and facilitate improved process-based ecosystem modeling from local to global scales. Geo-Wiki is a crowdsourcing tool that was developed at IIASA for land cover validation using satellite imagery. Several branches are now available focused on specific aspects of land cover validation, e.g. validating cropland extent or urbanized areas. Geo-Wiki Pictures is a smart phone application for collecting land cover related information on the ground. The extension of Geo-Wiki to a mobile environment provides a tool for experts in land cover validation but is also a way of reaching the general public in the validation of land cover. Here we propose a Soil Geo-Wiki tool that builds on the existing functionality of the Geo-Wiki application, which will be largely designed for the collection and sharing of soil information. Two distinct applications are envisaged: an expert-oriented application mainly for scientific purposes, which will use soil science related language (e.g. WRB or any other global reference soil classification system) and allow experts to upload and share scientifically rigorous soil data; and an application oriented towards the general public, which will be more focused on describing well observed, individual soil properties using simplified classification keys. The latter application will avoid the use of soil science related terminology and focus on the most useful soil parameters such as soil surface features, stone content, soil texture, soil plasticity, calcium carbonate presence, soil color, soil pH, soil repellency, and soil depth. Collection of soil and landscape pictures will also be supported in Soil Geo-Wiki to allow for comprehensive data collection while simultaneously allowing for quality checking by experts.

Soil Fertility Evaluation and Land Management of Dryland Farming at Tegallalang Sub-District, Gianyar Regency, Bali, Indonesia

NASA Astrophysics Data System (ADS)

Sardiana, I. K.; Susila, D.; Supadma, A. A.; Saifulloh, M.

2017-12-01

The landuse of Tegallalang Subdistrict is dominated by dryland farming. The practice of cultivation on agricultural dryland that ignores the carrying capacity of the environment can lead to land degradation that makes the land vulnerable to the deterioration of soil fertility. Soil fertility evaluation and land management of dryland farming in Tegallalang Sub-district, Gianyar Regency were aimed at (1) identifying the soil fertility and it’s respective limiting factors, (2) mapping the soil fertility using Geographic Information Systems (GIS) and (3) developing land management for dryland farming in Tegallalang Sub-district. This research implementing explora-tory method which followed by laboratory analysis. Soil samples were taken on each homogene-ous land units which developed by overlay of slope, soil type, and land use maps. The following soil fertility were measured, such as CEC, base saturation, P2O5, K- Total and C-Organic. The values of soil fertility were mapping using QGIS 2.18.7 and refer to land management evaluation. The results showed that the soil fertility in the research area considered high, and low level. The High soil fertility presents on land units at the flat to undulating slope with different land management systems (fertilizer, without fertilizer, soil tillage and without soil tillage). The low soil fertility includes land units that present on steep slope, and without land managements. The limiting factors of soil fertility were texture, C-Organic, CEC, P2O5, and K- total. It was recommended to applying organic fertilizer, Phonska, and dolomite on the farming area.

Surficial geologic map of the Heath-Northfield-Southwick-Hampden 24-quadrangle area in the Connecticut Valley region, west-central Massachusetts

USGS Publications Warehouse

Stone, Janet R.; DiGiacomo-Cohen, Mary L.

2010-01-01

The surficial geologic map layer shows the distribution of nonlithified earth materials at land surface in an area of 24 7.5-minute quadrangles (1,238 mi2 total) in west-central Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text, quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Surficial geologic map of the Norton-Manomet-Westport-Sconticut Neck 23-quadrangle area in southeast Massachusetts

USGS Publications Warehouse

Stone, Byron D.; Stone, Janet R.; DiGiacomo-Cohen, Mary L.; Kincare, Kevin A.

2012-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of 23 7.5-minute quadrangles (919 mi2 total) in southeastern Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Surficial geologic map of the Mount Grace-Ashburnham-Monson-Webster 24-quadrangle area in central Massachusetts

USGS Publications Warehouse

Stone, Janet R.

2013-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of 24 7.5-minute quadrangles (1,238 mi2 total) in central Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction-aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Residual effects of monoammonium phosphate, gypsum and elemental sulfur on cadmium phytoavailability and translocation from soil to wheat in an effluent irrigated field.

PubMed

Qayyum, Muhammad Farooq; Rehman, Muhammad Zia Ur; Ali, Shafaqat; Rizwan, Muhammad; Naeem, Asif; Maqsood, Muhammad Aamer; Khalid, Hinnan; Rinklebe, Jörg; Ok, Yong Sik

2017-05-01

Cadmium (Cd) accumulation in agricultural soils is one of the major threats to food security. The application of inorganic amendments such as mono-ammonium phosphate (MAP), gypsum and elemental sulfur (S) could alleviate the negative effects of Cd in crops. However, their long-term residual effects on decreasing Cd uptake in latter crops remain unclear. A field that had previously been applied with treatments including control and 0.2, 0.4 and 0.8% by weight of each MAP, gypsum and S, and grown with wheat and rice and thereafter wheat in the rotation was selected for this study. Wheat (Triticum aestivum L.) was grown in the same field as the third crop without further application of amendments to evaluate the residual effects of the amendments on Cd uptake by wheat. Plants were harvested at maturity and grain, and straw yield along with Cd concentration in soil, straw, and grains was determined. The addition of MAP and gypsum significantly increased wheat growth and yield and decreased Cd accumulation in straw and grains compared to control while the reverse was found in S application. Both MAP and gypsum decreased AB-DTPA extractable Cd in soil while S increased the bioavailable Cd in soil. Both MAP and gypsum increased the Cd immobilization in the soil and S decreased Cd immobilization in a dose-additive manner. We conclude that MAP and gypsum had a significant residual effect on decreasing Cd uptake in wheat. The cost-benefit ratio revealed that gypsum is an effective amendment for decreasing Cd concentration in plants. Copyright © 2017 Elsevier Ltd. All rights reserved.

Distribution of lithium in agricultural and grazing land soils at European continental scale (GEMAS project)

NASA Astrophysics Data System (ADS)

Negrel, Philippe; Reimann, Clemens; Ladenberger, Anna; Birke, Manfred

2017-04-01

The environmental chemistry of Li has received attention because Li has been shown to have numerous and important implications for human health and agriculture and the stable isotope composition of lithium is a powerful geochemical tool that provides quantitative information about Earth processes such as sediment recycling, global chemical weathering and its role in the carbon cycle, hydrothermal alteration, and groundwater evolution. However, the role of bedrock sources, weathering and climate changes in the repartition of Li at the continental scale has been scarcely investigated. Agricultural soil (Ap-horizon, 0-20 cm) and grazing land soil (Gr-horizon, 0-10 cm) samples were collected from a large part of Europe (33 countries, 5.6 million km2) as a part of the GEMAS (GEochemical Mapping of Agricultural and grazing land Soil) soil mapping project. GEMAS soil data have been used to provide a general view of element mobility and source rocks at the continental scale, either by reference to average crustal abundances or to normalized patterns of element mobility during weathering processes. The survey area includes a diverse group of soil parent materials with varying geological history, a wide range of climate zones and landscapes. The concentrations of Li in European soil were determined by ICP-MS after a hot aqua regia extraction, and their spatial distribution patterns generated by means of a GIS software. Due to the partial nature of the aqua regia extraction, the mean concentration of Li in the European agricultural soil (ca 11.4 mg/kg in Ap and Gr soils) is about four times lower than in the Earth's upper continental crust (UCC = 41 mg/kg). The combined plot histogram - density trace one- dimensional scattergram - boxplot of the aqua regia data displays the univariate data distribution of Li. The one-dimensional scattergram and boxplot highlight the existence of many outliers at the lower end of the Li distribution and very few at the upper end. Though the density trace, histogram and boxplot suggest a slight skew, the data distributions are still rather symmetrical in the log-scale. The median values of the Ap and Gr samples do overlap, demonstrating they are not statistically different at the 5 % significance level. The maps of Li in the aqua regia extraction show a distinct difference between northern Europe with predominantly low concentrations (median 6.4 mg/kg) and southern Europe with significantly higher values (median 15 mg/kg). The maximum extent of the last glaciation is visible as a discrete concentration break on the maps. The principal Li anomalies occur spatially associated with the granitic rocks and Li-pegmatites and their weathering products throughout Europe, e.g. in central Sweden (Central Scandinavian Clay Belt) and in the western part of the Alpine Region (higher Li concentrations). Even the new Li-deposit near Wolfsberg, Austria is marked by a clear anomaly. In southern Europe, high Li values occurring over limestone areas can be attributed to secondary Li enrichment during weathering controlled by climate (temperature and precipitation).

GEMAS - Tin and Tungsten: possible sources of enriched concentrations in soils in European countries

NASA Astrophysics Data System (ADS)

João Batista, Maria; Filipe, Augusto; Reimann, Clemens

2014-05-01

Tin and tungsten occur related with magmatic differentiation and can be installed in fissures and veins of magmatic rocks or in the neighbor metasediments. Generally, both elements have low chemical mobility in the superficial environment although effectively mobile in detrital media such as stream sediments and deposited in alluvial soils. The most important tin-tungsten deposits in Europe are in Variscides. From the northern Europe, 985 samples and from southern Europe 1123 samples were collected both in agricultural and grazing lands. Analysis were made of Sn , W, pH, TOC, SiO2 from the upper 20 and 10 cm of agricultural and grazing soils, respectively. The present study is part of the GEMAS project a joint project of European geochemical mapping between the EuroGeoSurvey Geochemical Expert Group and EuroMetaux. The results show that in general, at the European (continental) scale natural processes are dominant. It is clear the distinction between NE Europe and SW European tin and tungsten concentrations in soils. Tin geometric mean concentrations in the northern Europe is 0.57 mg kg-1 in agricultural soils and 0.62 mg kg-1 in grazing land; southern Europe 0.91 mg kg-1 in agricultural soils and 0.95 mg kg-1 in grazing land. Tungsten geometric mean concentrations in northern Europe is 0.067 mg kg-1 in agricultural soils and 0.073 mg kg-1 in grazing land and in southern Europe is 0.085 mg kg-1 in agricultural soils and 0.090 mg kg-1 in grazing land. Limit between north and south is the maximum extent of the last glaciation. Grazing land, undisturbed soils for a period of several years, have higher concentrations of Sn and W than agricultural soils which raises the question that if only natural processes are observed. Parent material seems to be the main source of Sn and W to soil. Sn-W rich Variscan granitic intrusions of Central Iberian Zone, Massif Central, Brittany, Cornwall and Bohemia are reflected in soil concentrations. TOC is higher in northern than in southern soils and SiO2 is higher in loess sediments region, in the North German-Poland basin and in the Paris basin. Organic matter may immobilise these metals and silica content influences metallic elements concentrations in soils. Natural processes of soil development, land management of agricultural soils and population density all together may be responsible for higher concentrations of W in the soils of Netherlands Germany, Belgium, Switzerland and northeast France which seems not related with Sn-W mineral provinces. Tin and tungsten are enriched in the Precambrian shields compared to the Caledonian shields soils in the northern countries, although in northern countries climatic conditions may play the most important role in these elements concentrations. Tin and tungsten and tin or tungsten alone or in association of precious metals, copper, uranium, niobium, beryllium, titanium altogether were extracted in 650 small or median size mines in Portugal. Except tin in Neves Corvo mine of the Iberian Pyrite Belt the rest of these mines occurred in the Variscides granitic intrusions region. Tin and tungsten concentrations are therefore well reflected in the northern Portugal soils. At the GEMAS density of sampling pollution and local natural phenomena are not reflected in mapping but this important province is well delimited.

Hydropodelogy From the Pedon to the Landscape: Challenges and Accomplishments in the National Cooperative Soil Survey

NASA Astrophysics Data System (ADS)

Hammer, D.; Richardson, J.; Hempel, J.; Market, P.

2005-12-01

American pedology has focused on the National Cooperative Soil Survey. Primary responsibility rests with the U.S. Department of Agriculture. The primary goals, are legislatively mandated, are to map the country's soils, make interpretations, provide information to clients, maintain and market the soil survey. The first goal is near completion and focus is shifting to the other three. Concomitantly, American pedological science is being impacted by several conditions: technological advances; land use changes at unprecedented scales and magnitudes; a burgeoning population increasingly "separated" from the land; and a major emphasis in universities upon biological ("life") sciences at the DNA scale - as if soil, nutrients and water are not life essentials. Effects of the Flood of 1993 and Hurricane Katrina suggest that humans do not understand earth/climate interactions, particularly climatic extremes. Pedologists know the focus on soil classification and mapping was at the expense of understanding processes. Hydropedology is a holistic approach to understanding soil and geomorphic process in order to predict the impacts of perturbations. Water movement on and in the soil is the primary mechanism of distributing and altering sediments and chemicals (pedogenesis), and depends for its success upon understanding that the soil profile is the record of developmental history at that landscape site. Hydropedologists believe soil scientists can use pedons (point data) from appropriate locations from flownets in complex landscapes to extrapolate processes. This is the "pedotransfer function" concept. Technological advances are coupled with the existing soil survey information to create important soil-landscape interpretations at a variety of scales. Early results have been very successful. Quantification of soil systems can be classified broadly into three categories; hard data, soft data and tacit knowledge. "Hard data" are measured numbers, and include such attributes as pH, texture, cation exchange capacity and event-specific rainfall. "Soft data" include soil maps, SSURGO data and climate maps. Soft data are combinations of observations, measurements and inferences that produce maps and models at various scales. "Tacit knowledge" is human understanding that results from focused experience within a system. A skilled soil scientist with tacit knowledge specific to a particular region can combination hard and soft data to develop important and useful interpretations and predictions. Illustrations from natural and urban settings will be provided. Soils and climate are temporally and spatially variable at all scales. Soil systems respond differently to different climates and perturbations. For example, the recent pluvial period in the Prairie Pothole region is changing surface soil sodium concentrations and locations and sizes of discharge wetlands. This is a relatively short-term response to a regional climate shift. Climatic shift in Oxisol landscapes will have little effect on soil cations. To optimize soil interpretations, focus must be on quantifying region-specific "dynamic" soil, geomorphic and climatic attributes. Recognizing these needs, the National Cooperative Soil Survey will develop regional watershed projects that focus on quantifying soil-water relationships that can be used at a variety of scales.

Towards quantitative usage of EMI-data for Digital Soil Mapping

NASA Astrophysics Data System (ADS)

Nüsch, A.-K.; Wunderlich, T.; Kathage, S.; Werban, U.; Dietrich, P.

2009-04-01

As formulated in the Thematic Strategy for Soil Protection prepared by the European Commission soil degradation is a serious problem in Europe. The degradation is driven or exacerbated by human activity and has a direct impact on water and air quality, biodiversity, climate and human life-quality. High-resolution soil property maps are one major prerequisite for the specific protection of soil function and restoration of degraded soils as well as sustainable land use, water and environmental management. However, the currently available techniques for (digital) soil mapping still have deficiencies in terms of reliability and precision, the feasibility of investigation of large areas (e.g. catchments and landscapes) and the assessment of soil degradation threats at this scale. The focus of the iSOIL (Interactions between soil related science - Linking geophysics, soil science and digital soil mapping) project is on improving fast and reliable mapping of soil properties, soil functions and soil degradation threats. This requires the improvement as well as integration of geophysical and spectroscopic measurement techniques in combination with advanced soil sampling approaches, pedometrical and pedophysical approaches. Many commercially available geophysical sensors and equipment (EMI, DC, gamma-spectroscopy, magnetics) are ready to use for measurements of different parameters. Data collection with individual sensors is well developed and numerously described. However comparability of data of different sensor types as well as reproducibility of data is not self-evident. In particular handling of sensors has to be carried out accurately, e.g. consistent calibration. Soil parameters will be derived from geophysical properties to create comprehensive soil maps. Therefore one prerequisite is the comparison of different geophysical properties not only qualitative but also quantitative. At least reproducibility is one of the most important conditions for monitoring tasks. The first parameter we focussed on is apparent electrical conductivity (ECa). It is an important geophysical properity in soil science since soil parameters (water content, etc.) can be deduced. Nowadays mobile geophysical platforms allow to survey large areas comprehensively in a short time period. These platforms have been equipped with EM38DD (Geonics) and Profiler EMP-400 (GSSI) - two different types of electromagnetic induction (EMI) instruments - within first iSOIL field campaign. While EM38DD measures in horizontal and vertical mode at the same time, Profiler measures three frequencies simultaneously and magnetic susceptibility additionally. Coil separation of the instruments is nearly the same, so penetration depth is similar. On the other hand, frequencies are arbitrary at Profiler but fixed at EM38DD. These differences in penetration depth have to taken into account. By our measurement we tested the comparability of the data to show differences between instruments of the same type (EM38DD-EM38DD) using different settings, and different types (EM38DD-Profiler). Moreover both sensors work in continuous as well in discontinuous mode. The results show that quality of data is comparable, but the quantities are varying. This has to be considered for further interpretations and monitoring. In the next steps we have to determine how to convert relative data into absolute data since ECa data from different locations are not comparable to each other in a quantitative way. In the talk we will give an introduction in the application of EMI for soil monitoring, followed by an overview about comparability and reproducibility of data.

Soil degradation level under particular annual rainfall at Jenawi District– Karanganyar, Indonesia

NASA Astrophysics Data System (ADS)

Herawati, A.; Suntoro; Widijanto, H.; Pusponegoro, I.; Sutopo, N. R.; Mujiyo

2018-03-01

The study of the climatic elements such as rainfall is vital for the sustainable development of agriculture at a region. The aims of the study were to evaluate the soil degradation based on the annual rainfall and to determine the key factors which responsible for the soil degradation at in Jenawi Sub-District. The mapping of soil degradation potency is an identification of initial soil condition to discover the potential of the land degradation. The mapping was done by overlaying the map of soil, slope, rainfall and land use with the standard procedures to obtain the value and status of Soil Degradation Potency (SDP). The result showed that SDP in Jenawi District categorized in very low (SDP I) 0.00 ha (0.00%); low (SDP II) 109.01 ha (2.57%); moderate (SDP III) 1,935.92 ha (45.63%); high (SDP IV) 1,959.54 ha (46.19%) and very high (SDP V) 238.08 ha (5.61%). The rainfall is the factor which has the strong correlation with the SDP (r = 0.65, P < 0.01, n = 306). The changes in the rainfall as the impact of climate change need to be anticipated to minimize soil degradation. The result can be adapted to the rainfall changes in various ways based on local soil-land characteristics.

Mapping soil erosion risk in Serra de Grândola (Portugal)

NASA Astrophysics Data System (ADS)

Neto Paixão, H. M.; Granja Martins, F. M.; Zavala, L. M.; Jordán, A.; Bellinfante, N.

2012-04-01

Geomorphological processes can pose environmental risks to people and economical activities. Information and a better knowledge of the genesis of these processes is important for environmental planning, since it allows to model, quantify and classify risks, what can mitigate the threats. The objective of this research is to assess the soil erosion risk in Serra de Grândola, which is a north-south oriented mountain ridge with an altitude of 383 m, located in southwest of Alentejo (southern Portugal). The study area is 675 km2, including the councils of Grândola, Santiago do Cacém and Sines. The process for mapping of erosive status was based on the guidelines for measuring and mapping the processes of erosion of coastal areas of the Mediterranean proposed by PAP/RAC (1997), developed and later modified by other authors in different areas. This method is based on the application of a geographic information system that integrates different types of spatial information inserted into a digital terrain model and in their derivative models. Erosive status are classified using information from soil erodibility, slope, land use and vegetation cover. The rainfall erosivity map was obtained using the modified Fournier index, calculated from the mean monthly rainfall, as recorded in 30 meteorological stations with influence in the study area. Finally, the soil erosion risk map was designed by ovelaying the erosive status map and the rainfall erosivity map.

When citizens and scientists work together : a french collaborative science network on earthworms communities distribution

NASA Astrophysics Data System (ADS)

Guernion, Muriel; Hoeffner, Kevin; Guillocheau, Sarah; Hotte, Hoël; Cylly, Daniel; Piron, Denis; Cluzeau, Daniel; Hervé, Morgane; Nicolai, Annegret; Pérès, Guénola

2017-04-01

Scientists have become more and more interested in earthworms because of their impact on soil functioning and their importance in provision of many ecosystem services. To improve the knowledge on soil biodiversity and integrate earthworms in soil quality diagnostics, it appeared necessary to gain a large amount of data on their distribution. The University of Rennes 1 developed since 2011 a collaborative science project called Observatoire Participatif des Vers de Terre (OPVT, participative earthworm observatory). It has several purposes : i) to offer a simple tool for soil biodiversity evaluation in natural and anthropic soils through earthworm assessment, ii) to offer trainings to farmers, territory managers, gardeners, pupils on soil ecology, iii) to build a database of reference values on earthworms in different habitats, iv) to propose a website (https://ecobiosoil.univ-rennes1.fr/OPVT_accueil.php) providing for example general scientific background (earthworm ecology and impacts of soil management), sampling protocols and online visualization of results (data processing and earthworms mapping). Up to now, more than 5000 plots have been prospected since the opening of the project in 2011., Initially available to anyone on a voluntary basis, this project is also used by the French Ministry of Agriculture to carry out a scientific survey throughout the French territory.

Soil Functional Mapping: A Geospatial Framework for Scaling Soil Carbon Cycling

NASA Astrophysics Data System (ADS)

Lawrence, C. R.

2017-12-01

Climate change is dramatically altering biogeochemical cycles in most terrestrial ecosystems, particularly the cycles of water and carbon (C). These changes will affect myriad ecosystem processes of importance, including plant productivity, C exports to aquatic systems, and terrestrial C storage. Soil C storage represents a critical feedback to climate change as soils store more C than the atmosphere and aboveground plant biomass combined. While we know plant and soil C cycling are strongly coupled with soil moisture, substantial unknowns remain regarding how these relationships can be scaled up from soil profiles to ecosystems. This greatly limits our ability to build a process-based understanding of the controls on and consequences of climate change at regional scales. In an effort to address this limitation we: (1) describe an approach to classifying soils that is based on underlying differences in soil functional characteristics and (2) examine the utility of this approach as a scaling tool that honors the underlying soil processes. First, geospatial datasets are analyzed in the context of our current understanding of soil C and water cycling in order to predict soil functional units that can be mapped at the scale of ecosystems or watersheds. Next, the integrity of each soil functional unit is evaluated using available soil C data and mapping units are refined as needed. Finally, targeted sampling is conducted to further differentiate functional units or fill in any data gaps that are identified. Completion of this workflow provides new geospatial datasets that are based on specific soil functions, in this case the coupling of soil C and water cycling, and are well suited for integration with regional-scale soil models. Preliminary results from this effort highlight the advantages of a scaling approach that balances theory, measurement, and modeling.

Indicative capacity of NDVI in predictive mapping of the properties of plow horizons of soils on slopes in the south of Western Siberia

NASA Astrophysics Data System (ADS)

Gopp, N. V.; Nechaeva, T. V.; Savenkov, O. A.; Smirnova, N. V.; Smirnov, V. V.

2017-11-01

The informativeness of NDVI for predictive mapping of the physical and chemical properties of plow horizons of soils on different slope positions within the first (280-310 m a.s.l.) and second (240-280 m a.s.l.) altitudinal steps has been examined. This index is uninformative for mapping soil properties in small hollows, whose factual width is less than the Landsat image resolution (30 m). In regression models, NDVI index explains 52% of variance in the content of humus; 35 and 24% of variance in the contents of total and nitrate nitrogen; 19 and 29% of variance in the contents of total and available phosphorus; 25 and 50% of variance in the contents of exchangeable calcium and manganese; and 30 and 29% of variance in the contents of fine silt and soil water, respectively. On the basis of the models obtained, prognostic maps of the soil properties have been developed. Spatial distribution patterns of NDVI calculated from Landsat 8 images (30-m resolution) serve as the cartographic base and the main indicator of the soil properties. The NDVI values and the contents of humus, physical clay (<0.01 mm) and fine silt particles, total and nitrate nitrogen, total phosphorus, and exchangeable calcium and manganese in the soils of the first altitudinal step are higher than those in the soils of the second altitudinal step. An opposite tendency has been found for the available phosphorus content: in the soils of the second altitudinal step and the hollow, its content is higher than that in the soils of the first altitudinal step by 1.8 and 2.4 times, respectively. Differences in the pH of soil water suspensions, easily available phosphorus, and clay in the soils of the compared topographic positions (first and second altitudinal steps and the hollow) are statistically unreliable.

[Assessment of soil degradation in regions of nuclear power explosions at Semipalatinsk Nuclear Test Site].

PubMed

Evseeva, T I; Geras'kin, S A; Maĭstrenko, T A; Belykh, E S

2011-01-01

Degree of the soil cover degradation at the "Balapan" and "Experimental field" test sites was assessed based on Allium-test of soil toxicity results and international guidelines on radioactive restriction of solid materials (IAEA, 2004) and environment (Smith, 2005). Soil cover degradation maps of large-scale (1 : 25000) were made. The main part of the area mapped belongs to high-contaminated toxic degraded soil. A relationship between the soil toxicity and the total radionuclide activity concentrations was found to be described by power functions. When the calculated value (equal to 413-415 Bq/kg of air dry soil) increases, the soil becomes toxic for plants. This value is 7.8 times higher than the maximal value for background territories (53 Bq/kg) surrounding SNTS. Russian sanitary and hygienic guidelines (Radiation safety norms, 2009; Sanitary regulations of radioactive waste management, 2003) underestimate the degree of soil radioactive contamination for plants.

High resolution mapping of soil organic carbon stocks using remote sensing variables in the semi-arid rangelands of eastern Australia.

PubMed

Wang, Bin; Waters, Cathy; Orgill, Susan; Gray, Jonathan; Cowie, Annette; Clark, Anthony; Liu, De Li

2018-07-15

Efficient and effective modelling methods to assess soil organic carbon (SOC) stock are central in understanding the global carbon cycle and informing related land management decisions. However, mapping SOC stocks in semi-arid rangelands is challenging due to the lack of data and poor spatial coverage. The use of remote sensing data to provide an indirect measurement of SOC to inform digital soil mapping has the potential to provide more reliable and cost-effective estimates of SOC compared with field-based, direct measurement. Despite this potential, the role of remote sensing data in improving the knowledge of soil information in semi-arid rangelands has not been fully explored. This study firstly investigated the use of high spatial resolution satellite data (seasonal fractional cover data; SFC) together with elevation, lithology, climatic data and observed soil data to map the spatial distribution of SOC at two soil depths (0-5cm and 0-30cm) in semi-arid rangelands of eastern Australia. Overall, model performance statistics showed that random forest (RF) and boosted regression trees (BRT) models performed better than support vector machine (SVM). The models obtained moderate results with R 2 of 0.32 for SOC stock at 0-5cm and 0.44 at 0-30cm, RMSE of 3.51MgCha -1 at 0-5cm and 9.16MgCha -1 at 0-30cm without considering SFC covariates. In contrast, by including SFC, the model accuracy for predicting SOC stock improved by 7.4-12.7% at 0-5cm, and by 2.8-5.9% at 0-30cm, highlighting the importance of including SFC to enhance the performance of the three modelling techniques. Furthermore, our models produced a more accurate and higher resolution digital SOC stock map compared with other available mapping products for the region. The data and high-resolution maps from this study can be used for future soil carbon assessment and monitoring. Copyright © 2018 Elsevier B.V. All rights reserved.

Use of a flux-based field capacity criterion to identify effective hydraulic parameters of layered soil profiles subjected to synthetic drainage experiments

NASA Astrophysics Data System (ADS)

Nasta, Paolo; Romano, Nunzio

2016-01-01

This study explores the feasibility of identifying the effective soil hydraulic parameterization of a layered soil profile by using a conventional unsteady drainage experiment leading to field capacity. The flux-based field capacity criterion is attained by subjecting the soil profile to a synthetic drainage process implemented numerically in the Soil-Water-Atmosphere-Plant (SWAP) model. The effective hydraulic parameterization is associated to either aggregated or equivalent parameters, the former being determined by the geometrical scaling theory while the latter is obtained through the inverse modeling approach. Outcomes from both these methods depend on information that is sometimes difficult to retrieve at local scale and rather challenging or virtually impossible at larger scales. The only knowledge of topsoil hydraulic properties, for example, as retrieved by a near-surface field campaign or a data assimilation technique, is often exploited as a proxy to determine effective soil hydraulic parameterization at the largest spatial scales. Comparisons of the effective soil hydraulic characterization provided by these three methods are conducted by discussing the implications for their use and accounting for the trade-offs between required input information and model output reliability. To better highlight the epistemic errors associated to the different effective soil hydraulic properties and to provide some more practical guidance, the layered soil profiles are then grouped by using the FAO textural classes. For the moderately heterogeneous soil profiles available, all three approaches guarantee a general good predictability of the actual field capacity values and provide adequate identification of the effective hydraulic parameters. Conversely, worse performances are encountered for the highly variable vertical heterogeneity, especially when resorting to the "topsoil-only" information. In general, the best performances are guaranteed by the equivalent parameters, which might be considered a reference for comparisons with other techniques. As might be expected, the information content of the soil hydraulic properties pertaining only to the uppermost soil horizon is rather inefficient and also not capable to map out the hydrologic behavior of the real vertical soil heterogeneity since the drainage process is significantly affected by profile layering in almost all cases.

Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing

USGS Publications Warehouse

Kokaly, R.F.; Rockwell, B.W.; Haire, S.L.; King, T.V.V.

2007-01-01

Forest fires leave behind a changed ecosystem with a patchwork of surface cover that includes ash, charred organic matter, soils and soil minerals, and dead, damaged, and living vegetation. The distributions of these materials affect post-fire processes of erosion, nutrient cycling, and vegetation regrowth. We analyzed high spatial resolution (2.4??m pixel size) Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data collected over the Cerro Grande fire, to map post-fire surface cover into 10 classes, including ash, soil minerals, scorched conifer trees, and green vegetation. The Cerro Grande fire occurred near Los Alamos, New Mexico, in May 2000. The AVIRIS data were collected September 3, 2000. The surface cover map revealed complex patterns of ash, iron oxide minerals, and clay minerals in areas of complete combustion. Scorched conifer trees, which retained dry needles heated by the fire but not fully combusted by the flames, were found to cover much of the post-fire landscape. These scorched trees were found in narrow zones at the edges of completely burned areas. A surface cover map was also made using Landsat Enhanced Thematic Mapper plus (ETM+) data, collected September 5, 2000, and a maximum likelihood, supervised classification. When compared to AVIRIS, the Landsat classification grossly overestimated cover by dry conifer and ash classes and severely underestimated soil and green vegetation cover. In a comparison of AVIRIS surface cover to the Burned Area Emergency Rehabilitation (BAER) map of burn severity, the BAER high burn severity areas did not capture the variable patterns of post-fire surface cover by ash, soil, and scorched conifer trees seen in the AVIRIS map. The BAER map, derived from air photos, also did not capture the distribution of scorched trees that were observed in the AVIRIS map. Similarly, the moderate severity class of Landsat-derived burn severity maps generated from the differenced Normalized Burn Ratio (dNBR) calculation had low agreement with the AVIRIS classes of scorched conifer trees. Burn severity and surface cover images were found to contain complementary information, with the dNBR map presenting an image of degree of change caused by fire and the AVIRIS-derived map showing specific surface cover resulting from fire.

Comparing measured and modelled soil carbon: which site-specific variables are linked to high stability?

NASA Astrophysics Data System (ADS)

Robertson, Andy; Schipanski, Meagan; Ma, Liwang; Ahuja, Lajpat; McNamara, Niall; Smith, Pete; Davies, Christian

2016-04-01

Changes in soil carbon (C) stocks have been studied in depth over the last two decades, as net greenhouse gas (GHG) sinks are highlighted to be a partial solution to the causes of climate change. However, the stability of this soil C is often overlooked when measuring these changes. Ultimately a net sequestration in soils is far less beneficial if labile C is replacing more stable forms. To date there is no accepted framework for measuring soil C stability, and as a result there is considerable uncertainty associated with the simulated impacts of land management and land use change when using process-based systems models. However, a recent effort to equate measurable soil C fractions to model pools has generated data that help to assess the impacts of land management, and can ultimately help to reduce the uncertainty of model predictions. Our research compiles this existing fractionation data along with site metadata to create a simplistic statistical model able to quantify the relative importance of different site-specific conditions. Data was mined from 23 published studies and combined with original data to generate a dataset of 100+ land use change sites across Europe. For sites to be included they required soil C fractions isolated using the Zimmermann et al. (2007) method and specific site metadata (mean annual precipitation, MAP; mean annual temperature, MAT; soil pH; land use; altitude). Of the sites, 75% were used to develop a generalized linear mixed model (GLMM) to create coefficients where site parameters can be used to predict influence on the measured soil fraction C stocks. The remaining 25% of sites were used to evaluate uncertainty and validate this empirical model. Further, four of the aforementioned sites were used to simulate soil C dynamics using the RothC, DayCent and RZWQM2 models. A sensitivity analysis (4096 model runs for each variable applying Latin hypercube random sampling techniques) was then used to observe whether these models place as much weight on the same site parameters as the GLMM. Sites were spread across an extensive geographic area and encompassed a wide range of conditions (2% to 44% clay content; 0.9° C to 18° C MAT; 300mm to 1400mm MAP). Topsoil (30 cm) C stocks also varied considerably (29.0 to 115.9 t/ha) but the proportion deemed stable (mean residence time >10 years) was relatively consistent (72 ± 2 %). The GLMM approach suggested that an interaction of soil pH and historic land use explained the largest amount of variation seen in stable fraction C stocks, closely followed by MAT and MAP interactions. For all three systems models, the stable soil C pools were most sensitive to climatic variables and land use. However, RZWQM2 did indicate that soil characteristics (texture, pH) also had an influence on stable C pool dynamics. References 1 - Zimmermann et al., 2007. Measured soil organic matter fractions can be related to pools in the RothC model. European Journal of Soil Science, 58:658-667.

Groundwater Assessment Study for 50 Communities in Southeastern New Hampshire. Appendixes

DTIC Science & Technology

1980-09-01

U.S. Dept. of Agriculture, Soil Conservation Service, 1973. 3. Groundwater Favorability Map of the Salem -Plaistow Area, New Hampshire, by James M...QUADRANGLE LOCATION AQUIFER QUADRANGLE LOCATION At-i Haverhill (7.5’ series) Ex-i Exeter Salem Depot Ba-l Dover West Fr-l Haverhill (15’ series) Mt...Qenerall? are ice contact, Ki-l and Ne-2 are generally stratified sand and silt outwash tgpe deposits B. POTENTIAL 1. WIEGLE: ( Salem -Plaistow--defines

Direct Push Optical Screening Tool for High-Resolution, Real-Time Mapping of Chlorinated Solvent DNAPL Architecture

DTIC Science & Technology

2016-04-01

due to higher densities, lower viscosities , and increased weathering (mass depletion) of residual chlorinated solvent DNAPL compared to those other...demonstration area can be generally classified as stratified layers of fine sand and silt with few clay layers. A silt layer was penetrated consistently at...toxic and carcinogenic. Another potential issue evaluated was that in plastic soils (stiff clays for example) there is potential for the thickness of

POLARIS: A 30-meter probabilistic soil series map of the contiguous United States

USGS Publications Warehouse

Chaney, Nathaniel W; Wood, Eric F; McBratney, Alexander B; Hempel, Jonathan W; Nauman, Travis; Brungard, Colby W.; Odgers, Nathan P

2016-01-01

A new complete map of soil series probabilities has been produced for the contiguous United States at a 30 m spatial resolution. This innovative database, named POLARIS, is constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm (DSMART-HPC) to remap the Soil Survey Geographic (SSURGO) database. This 9 billion grid cell database is possible using available high performance computing resources. POLARIS provides a spatially continuous, internally consistent, quantitative prediction of soil series. It offers potential solutions to the primary weaknesses in SSURGO: 1) unmapped areas are gap-filled using survey data from the surrounding regions, 2) the artificial discontinuities at political boundaries are removed, and 3) the use of high resolution environmental covariate data leads to a spatial disaggregation of the coarse polygons. The geospatial environmental covariates that have the largest role in assembling POLARIS over the contiguous United States (CONUS) are fine-scale (30 m) elevation data and coarse-scale (~ 2 km) estimates of the geographic distribution of uranium, thorium, and potassium. A preliminary validation of POLARIS using the NRCS National Soil Information System (NASIS) database shows variable performance over CONUS. In general, the best performance is obtained at grid cells where DSMART-HPC is most able to reduce the chance of misclassification. The important role of environmental covariates in limiting prediction uncertainty suggests including additional covariates is pivotal to improving POLARIS' accuracy. This database has the potential to improve the modeling of biogeochemical, water, and energy cycles in environmental models; enhance availability of data for precision agriculture; and assist hydrologic monitoring and forecasting to ensure food and water security.

Soil erosion assessment using the Universal Soil Loss Equation (USLE) in a GIS framework: A case study of Zacatecas, México

NASA Astrophysics Data System (ADS)

Betanzos Arroyo, L. I.; Prol Ledesma, R. M.; da Silva Pinto da Rocha, F. J. P.

2014-12-01

The Universal Soil Loss Equation (USLE), which is considered to be a contemporary approach in soil loss assessment, was used to assess soil erosion hazard in the Zacatecas mining district. The purpose of this study is to produce erosion susceptibility maps for an area that is polluted with mining tailings which are susceptible to erosion and can disperse the particles that contain heavy metals and other toxic elements. USLE method is based in the estimation of soil loss per unit area and takes into account specific parameters such as precipitation data, topography, soil erodibility, erosivity and runoff. The R-factor (rainfall erosivity) was calculated from monthly and annual precipitation data. The K-factor (soil erodibility) was estimated using soil maps available from the CONABIO at a scale of 1:250000. The LS-factor (slope length and steepness) was determined from a 30-m digital elevation model. A raster-based Geographic Information System (GIS) was used to interactively calculate soil loss and map erosion hazard. The results show that estimated erosion rates ranged from 0 to 4770.48 t/ha year. Maximum proportion of the total area of the Zacatecas mining district have nil to very extremely slight erosion severity. Small areas in the central and south part of the study area shows the critical condition requiring sustainable land management.

The assessment of spatial distribution of soil salinity risk using neural network.

PubMed

Akramkhanov, Akmal; Vlek, Paul L G

2012-04-01

Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km(2)) results were used to upscale soil salinity to a district area (∼300 km(2)). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m(-1)). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70-90% of locations were correctly estimated.

Multifractal and Singularity Maps of soil surface moisture distribution derived from 2D image analysis.

NASA Astrophysics Data System (ADS)

Cumbrera, Ramiro; Millán, Humberto; Martín-Sotoca, Juan Jose; Pérez Soto, Luis; Sanchez, Maria Elena; Tarquis, Ana Maria

2016-04-01

Soil moisture distribution usually presents extreme variation at multiple spatial scales. Image analysis could be a useful tool for investigating these spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to describe the local scaling of apparent soil moisture distribution and (ii) to define apparent soil moisture patterns from vertical planes of Vertisol pit images. Two soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. One was excavated in April/2011 and the other pit was established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak™ digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ≈373 μm of the photographed soil pit. For more details see Cumbrera et al. (2012). Geochemical exploration have found with increasingly interests and benefits of using fractal (power-law) models to characterize geochemical distribution, using the concentration-area (C-A) model (Cheng et al., 1994; Cheng, 2012). This method is based on the singularity maps of a measure that at each point define areas with self-similar properties that are shown in power-law relationships in Concentration-Area plots (C-A method). The C-A method together with the singularity map ("Singularity-CA" method) define thresholds that can be applied to segment the map. We have applied it to each soil image. The results show that, in spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used to study the dynamical change of soil moisture sampling in agreement with previous results (Millán et al., 2016). REFERENCES Cheng, Q., Agterberg, F. P. and Ballantyne, S. B. (1994). The separation of geochemical anomalies from background by fractal methods. Journal of Geochemical Exploration, 51, 109-130. Cheng, Q. (2012). Singularity theory and methods for mapping geochemical anomalies caused by buried sources and for predicting undiscovered mineral deposits in covered areas. Journal of Geochemical Exploration, 122, 55-70. Cumbrera, R., Ana M. Tarquis, Gabriel Gascó, Humberto Millán (2012) Fractal scaling of apparent soil moisture estimated from vertical planes of Vertisol pit images. Journal of Hydrology (452-453), 205-212. Martin Sotoca; J.J. Antonio Saa-Requejo, Juan Grau and Ana M. Tarquis (2016). Segmentation of singularity maps in the context of soil porosity. Geophysical Research Abstracts, 18, EGU2016-11402. Millán, H., Cumbrera, R. and Ana M. Tarquis (2016) Multifractal and Levy-stable statistics of soil surface moisture distribution derived from 2D image analysis. Applied Mathematical Modelling, 40(3), 2384-2395.

SOIL RADON POTENTIAL MAPPLING OF TWELVE COUNTIES IN NORTH-CENTRAL FLORIDA

EPA Science Inventory

The report describes the approach, methods, and detailed data used to prepare soil radon potential maps of 12 counties in North-Central Florida. he maps were developed under the Florida Radon Research Program to provide a scientific basis for implementing radon-protective buildin...

Multidate, multisensor remote sensing reveals high density of carbon-rich mountain peatlands in the páramo of Ecuador.

PubMed

Hribljan, John A; Suarez, Esteban; Bourgeau-Chavez, Laura; Endres, Sarah; Lilleskov, Erik A; Chimbolema, Segundo; Wayson, Craig; Serocki, Eleanor; Chimner, Rodney A

2017-12-01

Tropical peatlands store a significant portion of the global soil carbon (C) pool. However, tropical mountain peatlands contain extensive peat soils that have yet to be mapped or included in global C estimates. This lack of data hinders our ability to inform policy and apply sustainable management practices to these peatlands that are experiencing unprecedented high rates of land use and land cover change. Rapid large-scale mapping activities are urgently needed to quantify tropical wetland extent and rate of degradation. We tested a combination of multidate, multisensor radar and optical imagery (Landsat TM/PALSAR/RADARSAT-1/TPI image stack) for detecting peatlands in a 2715 km 2 area in the high elevation mountains of the Ecuadorian páramo. The map was combined with an extensive soil coring data set to produce the first estimate of regional peatland soil C storage in the páramo. Our map displayed a high coverage of peatlands (614 km 2 ) containing an estimated 128.2 ± 9.1 Tg of peatland belowground soil C within the mapping area. Scaling-up to the country level, páramo peatlands likely represent less than 1% of the total land area of Ecuador but could contain as much as ~23% of the above- and belowground vegetation C stocks in Ecuadorian forests. These mapping approaches provide an essential methodological improvement applicable to mountain peatlands across the globe, facilitating mapping efforts in support of effective policy and sustainable management, including national and global C accounting and C management efforts. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Spatial analysis of plutonium-239 + 240 and Americium-241 in soils around Rocky Flats, Colorado

DOE Office of Scientific and Technical Information (OSTI.GOV)

Litaor, M.I.

1995-05-01

Plutonium and american contamination of soils around Rocky Flats, Colorado resulted from past outdoor storage practices. Four previous studies produce four different Pu isopleth maps. Spatial estimation techniques were not used in the construction of these maps and were also based on an extremely small number of soil samples. The purpose of this study was to elucidate the magnitude of Pu-239 + 240 and Am-241 dispersion in the soil environment east of Rocky Flats using robust spatial estimation techniques. Soils were sampled from 118 plots of 1.01 and 4.05 ha by compositing 25 evenly spaced samples in each plot frommore » the top 0.64 cm. Plutonium-239 + 240 activity ranged from 1.85 to 53 560 Bq/kg with a mean of 1924 Bq/kg and a standard deviation of 6327 Bq/kg. Americium-241 activity ranged from 0.18 to 9990 Bq/kg with a mean of 321 Bq/kg and a standard deviation of 1143 Bq/kg. Geostatistical techniques were used to model the spatial dependency and construct isopleth maps showing Pu-239 + 240 and Am-241 distribution. The isopleth configuration was consistent with the hypothesis that the dominant dispersal mechanism of Pu-239 + 240 was wind dispersion from west to east. The Pu-239 + 240 isopleth map proposed to this study differed significantly in the direction and distance of dispersal from the previously published maps. This ispleth map as well as the Am-241 map should be used as the primary data for future risk assessment associated with public exposure to Pu-239 + 240 and Am-241. 37 refs., 7 figs., 2 tabs.« less

Long-term comparison of Kuparuk Watershed active layer maps, northern Alaska, USA

NASA Astrophysics Data System (ADS)

Nyland, K. E.; Queen, C.; Nelson, F. E.; Shiklomanov, N. I.; Streletskiy, D. A.; Klene, A. E.

2017-12-01

The active layer, or the uppermost soil horizon that thaws seasonally, is among the most dynamic components of the permafrost system. Evaluation of the thickness and spatial variation of the active layer is critical to many components of Arctic research, including climatology, ecology, environmental monitoring, and engineering. In this study we mapped active-layer thickness (ALT) across the 22,278 sq. km Kuparuk River basin on Alaska's North Slope throughout the summer of 2016. The Kuparuk River extends from the Brooks Range through the Arctic Foothills and across the Arctic Coastal Plain physiographic provinces, and drains into the Beaufort Sea. Methodology followed procedures used to produce an ALT map of the basin in 1995 accounting for the effects of topography, vegetation, topoclimate, and soils, using the same spatial sampling scheme for direct ALT and temperature measurement at representative locations and relating these parameters to vegetation-soil associations. A simple semi-empirical engineering solution was used to estimate thaw rates for the different associations. An improved lapse-rate formulation and a higher-resolution DEM were used to relate temperature to elevation. Three ALT maps were generated for the 2016 summer, combining measured thaw depth, temperature records, the 25 m ArcticDEM, high resolution remote sensed data, empirical laps rates, and a topoclimatic index through the thaw solution. These maps were used to track the spatial progression of thaw through the 2016 summer season and estimate a total volume of thawed soil. Maps produced in this study were compared to the 1995 map to track areas of significant geographic changes in patterns of ALT and total volume of thawed soil.

Three-Dimensional Mapping of Soil Organic Carbon by Combining Kriging Method with Profile Depth Function.

PubMed

Chen, Chong; Hu, Kelin; Li, Hong; Yun, Anping; Li, Baoguo

2015-01-01

Understanding spatial variation of soil organic carbon (SOC) in three-dimensional direction is helpful for land use management. Due to the effect of profile depths and soil texture on vertical distribution of SOC, the stationary assumption for SOC cannot be met in the vertical direction. Therefore the three-dimensional (3D) ordinary kriging technique cannot be directly used to map the distribution of SOC at a regional scale. The objectives of this study were to map the 3D distribution of SOC at a regional scale by combining kriging method with the profile depth function of SOC (KPDF), and to explore the effects of soil texture and land use type on vertical distribution of SOC in a fluvial plain. A total of 605 samples were collected from 121 soil profiles (0.0 to 1.0 m, 0.20 m increment) in Quzhou County, China and SOC contents were determined for each soil sample. The KPDF method was used to obtain the 3D map of SOC at the county scale. The results showed that the exponential equation well described the vertical distribution of mean values of the SOC contents. The coefficients of determination, root mean squared error and mean prediction error between the measured and the predicted SOC contents were 0.52, 1.82 and -0.24 g kg(-1) respectively, suggesting that the KPDF method could be used to produce a 3D map of SOC content. The surface SOC contents were high in the mid-west and south regions, and low values lay in the southeast corner. The SOC contents showed significant positive correlations between the five different depths and the correlations of SOC contents were larger in adjacent layers than in non-adjacent layers. Soil texture and land use type had significant effects on the spatial distribution of SOC. The influence of land use type was more important than that of soil texture in the surface soil, and soil texture played a more important role in influencing the SOC levels for 0.2-0.4 m layer.

Three-Dimensional Mapping of Soil Organic Carbon by Combining Kriging Method with Profile Depth Function

PubMed Central

Chen, Chong; Hu, Kelin; Li, Hong; Yun, Anping; Li, Baoguo

2015-01-01

Understanding spatial variation of soil organic carbon (SOC) in three-dimensional direction is helpful for land use management. Due to the effect of profile depths and soil texture on vertical distribution of SOC, the stationary assumption for SOC cannot be met in the vertical direction. Therefore the three-dimensional (3D) ordinary kriging technique cannot be directly used to map the distribution of SOC at a regional scale. The objectives of this study were to map the 3D distribution of SOC at a regional scale by combining kriging method with the profile depth function of SOC (KPDF), and to explore the effects of soil texture and land use type on vertical distribution of SOC in a fluvial plain. A total of 605 samples were collected from 121 soil profiles (0.0 to 1.0 m, 0.20 m increment) in Quzhou County, China and SOC contents were determined for each soil sample. The KPDF method was used to obtain the 3D map of SOC at the county scale. The results showed that the exponential equation well described the vertical distribution of mean values of the SOC contents. The coefficients of determination, root mean squared error and mean prediction error between the measured and the predicted SOC contents were 0.52, 1.82 and -0.24 g kg-1 respectively, suggesting that the KPDF method could be used to produce a 3D map of SOC content. The surface SOC contents were high in the mid-west and south regions, and low values lay in the southeast corner. The SOC contents showed significant positive correlations between the five different depths and the correlations of SOC contents were larger in adjacent layers than in non-adjacent layers. Soil texture and land use type had significant effects on the spatial distribution of SOC. The influence of land use type was more important than that of soil texture in the surface soil, and soil texture played a more important role in influencing the SOC levels for 0.2-0.4 m layer. PMID:26047012

SoilInfo App: global soil information on your palm

NASA Astrophysics Data System (ADS)

Hengl, Tomislav; Mendes de Jesus, Jorge

2015-04-01

ISRIC ' World Soil Information has released in 2014 and app for mobile de- vices called 'SoilInfo' (http://soilinfo-app.org) and which aims at providing free access to the global soil data. SoilInfo App (available for Android v.4.0 Ice Cream Sandwhich or higher, and Apple v.6.x and v.7.x iOS) currently serves the Soil- Grids1km data ' a stack of soil property and class maps at six standard depths at a resolution of 1 km (30 arc second) predicted using automated geostatistical mapping and global soil data models. The list of served soil data includes: soil organic carbon (), soil pH, sand, silt and clay fractions (%), bulk density (kg/m3), cation exchange capacity of the fine earth fraction (cmol+/kg), coarse fragments (%), World Reference Base soil groups, and USDA Soil Taxonomy suborders (DOI: 10.1371/journal.pone.0105992). New soil properties and classes will be continuously added to the system. SoilGrids1km are available for download under a Creative Commons non-commercial license via http://soilgrids.org. They are also accessible via a Representational State Transfer API (http://rest.soilgrids.org) service. SoilInfo App mimics common weather apps, but is also largely inspired by the crowdsourcing systems such as the OpenStreetMap, Geo-wiki and similar. Two development aspects of the SoilInfo App and SoilGrids are constantly being worked on: Data quality in terms of accuracy of spatial predictions and derived information, and Data usability in terms of ease of access and ease of use (i.e. flexibility of the cyberinfrastructure / functionalities such as the REST SoilGrids API, SoilInfo App etc). The development focus in 2015 is on improving the thematic and spatial accuracy of SoilGrids predictions, primarily by using finer resolution covariates (250 m) and machine learning algorithms (such as random forests) to improve spatial predictions.

BOREAS TGB-12 Soil Carbon and Flux Data of NSA-MSA in Raster Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Knapp, David E. (Editor); Rapalee, Gloria; Davidson, Eric; Harden, Jennifer W.; Trumbore, Susan E.; Veldhuis, Hugo

2000-01-01

The BOREAS TGB-12 team made measurements of soil carbon inventories, carbon concentration in soil gases, and rates of soil respiration at several sites. This data set provides: (1) estimates of soil carbon stocks by horizon based on soil survey data and analyses of data from individual soil profiles; (2) estimates of soil carbon fluxes based on stocks, fire history, drain-age, and soil carbon inputs and decomposition constants based on field work using radiocarbon analyses; (3) fire history data estimating age ranges of time since last fire; and (4) a raster image and an associated soils table file from which area-weighted maps of soil carbon and fluxes and fire history may be generated. This data set was created from raster files, soil polygon data files, and detailed lab analysis of soils data that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. Also used were soils data from Susan Trumbore and Jennifer Harden (BOREAS TGB-12). The binary raster file covers a 733-km 2 area within the NSA-MSA.

SMAP Radiometer Captures Views of Global Soil Moisture

NASA Image and Video Library

2015-05-06

These maps of global soil moisture were created using data from the radiometer instrument on NASA Soil Moisture Active Passive SMAP observatory. Evident are regions of increased soil moisture and flooding during April, 2015.

High resolution regional soil carbon mapping in Madagascar : towards easy to update maps

NASA Astrophysics Data System (ADS)

Grinand, Clovis; Dessay, Nadine; Razafimbelo, Tantely; Razakamanarivo, Herintsitoaina; Albrecht, Alain; Vaudry, Romuald; Tiberghien, Matthieu; Rasamoelina, Maminiaina; Bernoux, Martial

2013-04-01

The soil organic carbon plays an important role in climate change regulation through carbon emissions and sequestration due to land use changes, notably tropical deforestation. Monitoring soil carbon emissions from shifting-cultivation requires to evaluate the amount of carbon stored at plot scale with a sufficient level of accuracy to be able to detect changes. The objective of this work was to map soil carbon stocks (30 cm and 100 cm depths) for different land use at regional scale using high resolution satellite dataset. The Andohahela National Parc and its surroundings (South-Est Madagascar) - a region with the largest deforestation rate in the country - was selected as a pilot area for the development of the methodology. A three steps approach was set up: (i) carbon inventory using mid infra-red spectroscopy and stock calculation, (ii) spatial data processing and (iii) modeling and mapping. Soil spectroscopy was successfully used for measuring organic carbon in this region. The results show that Random Forest was the inference model that produced the best estimates on calibration and validation datasets. By using a simple and robust method, we estimated uncertainty levels of of 35% and 43% for 30-cm and 100-cm carbon maps respectively. The approach developed in this study was based on open data and open source software that can be easily replicated to other regions and for other time periods using updated satellite images.

Distribution of heavy metals in agricultural soils near a petrochemical complex in Guangzhou, China.

PubMed

Li, Junhui; Lu, Ying; Yin, Wei; Gan, Haihua; Zhang, Chao; Deng, Xianglian; Lian, Jin

2009-06-01

The aim of the study was to investigate influence of an industrialized environment on the accumulation of heavy metals in agricultural soils. Seventy soil samples collected from surface layers (0-20 cm) and horizons of five selected pedons in the vicinity area of petrochemical complex in Guangzhou, China were analyzed for Zn, Cu, Pb, Cd, Hg and As concentrations, the horizontal and vertical variation of these metals were studied and geographic information system (GIS)-based mapping techniques were applied to generate spatial distribution maps. The mean concentrations of these heavy metals in the topsoils did not exceed the maximum allowable concentrations in agricultural soil of China with the exception of Hg. Significant differences between land-use types showed that Cu, Pb, Cd, Hg and As concentrations in topsoils were strongly influenced by agricultural practices and soil management. Within a radius of 1,300 m there were no marked decreasing trends for these element concentrations (except for Zn) with the increase of distance from the complex boundary, which reflected little influence of petroleum air emission on soil heavy metal accumulation. Concentrations of Zn, Cu, Pb, Cd, Hg and As in the five pedons, particularly in cultivated vegetable field and orchard, decreased with soil depth, indicating these elements mainly originated from anthropogenic sources. GIS mapping was a useful tool for evaluating spatial variability of heavy metals in the affected soil. The spatial distribution maps allowed the identification of hot-spot areas with high metal concentration. Effective measures should be taken to avoid or minimize heavy metal further contamination of soils and to remediate the contaminated areas in order to prevent pollutants affecting human health through agricultural products.

Mapping CO2 emission in highly urbanized region using standardized microbial respiration approach

NASA Astrophysics Data System (ADS)

Vasenev, V. I.; Stoorvogel, J. J.; Ananyeva, N. D.

2012-12-01

Urbanization is a major recent land-use change pathway. Land conversion to urban has a tremendous and still unclear effect on soil cover and functions. Urban soil can act as a carbon source, although its potential for CO2 emission is also very high. The main challenge in analysis and mapping soil organic carbon (SOC) in urban environment is its high spatial heterogeneity and temporal dynamics. The urban environment provides a number of specific features and processes that influence soil formation and functioning and results in a unique spatial variability of carbon stocks and fluxes at short distance. Soil sealing, functional zoning, settlement age and size are the predominant factors, distinguishing heterogeneity of urban soil carbon. The combination of these factors creates a great amount of contrast clusters with abrupt borders, which is very difficult to consider in regional assessment and mapping of SOC stocks and soil CO2 emission. Most of the existing approaches to measure CO2 emission in field conditions (eddy-covariance, soil chambers) are very sensitive to soil moisture and temperature conditions. They require long-term sampling set during the season in order to obtain relevant results. This makes them inapplicable for the analysis of CO2 emission spatial variability at the regional scale. Soil respiration (SR) measurement in standardized lab conditions enables to overcome this difficulty. SR is predominant outgoing carbon flux, including autotrophic respiration of plant roots and heterotrophic respiration of soil microorganisms. Microbiota is responsible for 50-80% of total soil carbon outflow. Microbial respiration (MR) approach provides an integral CO2 emission results, characterizing microbe CO2 production in optimal conditions and thus independent from initial difference in soil temperature and moisture. The current study aimed to combine digital soil mapping (DSM) techniques with standardized microbial respiration approach in order to analyse and map CO2 emission and its spatial variability in highly urbanized Moscow region. Moscow region with its variability of bioclimatic conditions and high urbanization level (10 % from the total area) was chosen as an interesting case study. Random soil sampling in different soil zones (4) and land-use types (3 non-urban and 3 urban) was organized in Moscow region in 2010-2011 (n=242). Both topsoil (0-10 cm) and subsoil (10-150 cm) were included. MR for each point was analysed using standardized microbial (basal) respiration approach, including the following stages: 1) air dried soil samples were moisturised up to 55% water content and preincubated (7 days, 22° C) in a plastic bag with air exchange; 2) soil MR (in μg CO2-C g-1) was measured as the rate of CO2 production (22° C, 24 h) after incubating 2g soil with 0.2 μl distilled water; 3) the MR results were used to estimate CO2 emission (kg C m-2 yr-1). Point MR and CO2 emission results obtained were extrapolated for the Moscow region area using regression model. As a result, two separate CO2 maps for topsoil and subsoil were created. High spatial variability was demonstrated especially for the urban areas. Thus standardized MR approach combined with DSM techniques provided a unique opportunity for spatial analysis of soil carbon temporal dynamics at the regional scale.

Soils of the Sylvania Wilderness-Recreation Area, western Upper Peninsula, Michigan.

Treesearch

James G. Bockheim; J.K. Jordan

2004-01-01

Characterizes 22 soil profiles in teh Sylvania Wilderness-Recreation Area on the Ottawa National Forest, including soil descriptions and laboratory data. A soil map at a scale of 1:24,000 is provided. The genesis of the soils is discussed.

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

Lots of legacy soil data are available, but which data do we need to collect for regional land use analysis?

NASA Astrophysics Data System (ADS)

Hendriks, Chantal; Stoorvogel, Jetse; Claessens, Lieven

2015-04-01

In the past, soil surveying techniques were mainly developed for qualitative regional land use analysis (RLUA) like land evaluation and land use planning. Conventional soil survey techniques usually describe soil types according to a soil classification scheme (e.g. Soil Taxonomy and World Reference Base). These soil surveys met the requirements of qualitative land evaluation and land use planning. However, during the last decades there is an increased need for quantitative RLUA resulting in an increased demand for quantitative soil data. The rapid developments in computing technology and the availability of auxiliary information (e.g. remote sensing and digital elevation models) allowed for the development of new soil surveying techniques like digital soil mapping. These new soil surveying techniques aim to produce continuous maps of quantitative functional soil properties. However, RLUA nowadays requires soil data that include a description of the spatial variability of the entire pedon in which correlations between soil properties are retained. Current surveying techniques do not fully fulfil these requirements resulting in a gap between the supply and demand of soil data in RLUA. The gap is caused by the fact that legacy soil data are collected for different purposes and inherently have different assumptions on e.g., soil variability. In this study, some of these assumptions are tested and verified using primary soil data collected during a recent field survey in Machakos and Makueni County (Kenya). Subsequently an ongoing RLUA, the Global Yield Gap Atlas (GYGA) project, is taken as a case study to evaluate the effect of different sources of soil data on the results of the RLUA. The results of the study show that various assumptions underlying the soil survey hamper the quality requirements of soil data for the specific objectives of the RLUA. To give a few examples: mapping soil properties individually ignores correlations between them, soil properties differed significantly between natural and agricultural land, discrete soil mapping units described by a representative soil profile showed internal variability. None of the legacy datasets fitted the requirements of the RLUA. However, resources to collect additional primary soil data are limited. Evaluating legacy data allows us to identify the soil data that we need to collect. Legacy data lack information on e.g. soil management and effective rooting depth, while these data are often required for RLUA. This results in the use of assumptions, estimations and simplifications in a RLUA. The choice of legacy data has a profound effect on the results of a RLUA. The GYGA case study shows for example that different sources of soil input data can lead to differences in simulated water-limited maize yields of up to 3 ton/ha.

Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Werban, Ulrike; Zacharias, Steffen; Pohle, Marco; Dietrich, Peter; Wollschläger, Ute

2017-01-01

Electromagnetic induction (EMI) measurements are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa). Although the use of non-invasive EMI for imaging spatial soil properties is very attractive, the dependence of ECa on several factors challenges any interpretation with respect to individual soil properties or states such as soil moisture (θ). The major aim of this study was to further investigate the potential of repeated EMI measurements to map θ, with particular focus on the temporal variability of the spatial patterns of ECa and θ. To this end, we compared repeated EMI measurements with high-resolution θ data from a wireless soil moisture and soil temperature monitoring network for an extensively managed hillslope area for which soil properties and θ dynamics are known. For the investigated site, (i) ECa showed small temporal variations whereas θ varied from very dry to almost saturation, (ii) temporal changes of the spatial pattern of ECa differed from those of the spatial pattern of θ, and (iii) the ECa-θ relationship varied with time. Results suggest that (i) depending upon site characteristics, stable soil properties can be the major control of ECa measured with EMI, and (ii) for soils with low clay content, the influence of θ on ECa may be confounded by changes of the electrical conductivity of the soil solution. Further, this study discusses the complex interplay between factors controlling ECa and θ, and the use of EMI-based ECa data with respect to hydrological applications.