WorldWideScience

Sample records for provisional soil map

  1. INTERACTIVE NAME PLACEMENT FOR PROVISIONAL MAPS.

    Science.gov (United States)

    Goldberg, Jeffrey L.; Miller, Thomas C.

    1983-01-01

    Computer generation and placement of map type has been refined into a production mode at Mid-Continent Mapping Center (MCMC) for USGS 1:24,000- and 1:25,000-scale Provisional maps. The map collar program is written in FORTRAN using batch processing that allows the program to work in the background.

  2. Mapping specific soil functions based on digital soil property maps

    Science.gov (United States)

    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

  3. A PROVISIONAL TRANSCRIPT MAP OF THE SPINAL MUSCULAR-ATROPHY (SMA) CRITICAL REGION

    NARCIS (Netherlands)

    VANDERSTEEGE, G; DRAAIJERS, TG; GROOTSCHOLTEN, PM; OSINGA, J; ANZEVINO, R; VELONA, [No Value; DENDUNNEN, JT; SCHEFFER, H; BRAHE, C; VANOMMEN, GJB; BUYS, CHCM

    1995-01-01

    YACs from the region containing the spinal muscular atrophy (SMA) locus at 5q12 have been used as probes in a direct screening of cDNA libraries to isolate 8 cDNAs, mapped to different YAC fragments. Three clones showed complete identity to the genes for cyclin B1 (CCNB1), the p44 subunit of the

  4. Innovative methods for soil parent material mapping

    OpenAIRE

    Farewell, Timothy S.

    2010-01-01

    Soil parent material exerts a fundamental control on many environmental processes. Nevertheless, resulting from the separate mapping programmes of the geological and soil surveys, parent material is currently poorly mapped in the United Kingdom. This research develops and tests four methods of predicting soil parent material using three study areas in England. The qualities of desirable parent material maps were stated, and then used to create new map value metrics to assess th...

  5. Digital soil mapping from conventional field soil observations

    OpenAIRE

    J. Balkovič; Rampasekova, Z.; Hutar, V.; Sobocka, J.; Skalsky, R

    2013-01-01

    We tested the performance of a formalized digital soil mapping (DSM) approach comprising fuzzy k-means (FKM) classification and regression-kriging to produce soil type maps from a fine-scale soil observation network in Risnovce, Slovakia. We examine whether the soil profile descriptions collected merely by field methods fit into the statistical DSM tools and if they provide pedologically meaningful results for an erosion-affected area. Soil texture, colour, carbonates, stoniness and genetic q...

  6. Soil studies. Soil inventory studies: mapping and description

    Energy Technology Data Exchange (ETDEWEB)

    Olgeirson, E.R.

    1979-01-01

    Soils on the Geokinetic Oil Shale Project site in Uintah County, Utah are described, classified and mapped. This interim report contains baseline information for soil series. Preliminary identification was made using black and white aerial photography and later verified in the field. Soil units are classified according to the USDA soil nomenclature. (DMC)

  7. Pedometric mapping of soil organic matter using a soil map with quantified uncertainty

    NARCIS (Netherlands)

    Kempen, B.; Heuvelink, G.B.M.; Brus, D.J.; Stoorvogel, J.J.

    2010-01-01

    This paper compares three models that use soil type information from point observations and a soil map to map the topsoil organic matter content for the province of Drenthe in the Netherlands. The models differ in how the information on soil type is obtained: model 1 uses soil type as depicted on

  8. Sampling for validation of digital soil maps

    NARCIS (Netherlands)

    Brus, D.J.; Kempen, B.; Heuvelink, G.B.M.

    2011-01-01

    The increase in digital soil mapping around the world means that appropriate and efficient sampling strategies are needed for validation. Data used for calibrating a digital soil mapping model typically are non-random samples. In such a case we recommend collection of additional independent data and

  9. Spectroscopy-supported digital soil mapping

    NARCIS (Netherlands)

    Mulder, V.L.

    2013-01-01

    Global environmental changes have resulted in changes in key ecosystem services that soils provide. It is necessary to have up to date soil information on regional and global scales to ensure that these services continue to be provided. As a result, Digital Soil Mapping (DSM) research priorities are

  10. 498 GIS-BASED PRODUCTION OF DIGITAL SOIL MAP FOR ...

    African Journals Online (AJOL)

    Osondu

    Key words: Soil, Soil maps, Digital soil map, GIS, Soil Database, Soil thematic maps, Query. Introduction. Soil, a valuable natural resource has been fundamental to human existence and can be said to play a part across the range of human activities such as housing, industrialization, economic activities, mining, fishery, and.

  11. Digital Soil Mapping - A platform for enhancing soil learning

    Science.gov (United States)

    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.

  12. Northern Circumpolar Soils Map, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of a circumpolar map of dominant soil characteristics, with a scale of 1:10,000,000, covering the United States, Canada, Greenland, Iceland,...

  13. Case studies: Soil mapping using multiple methods

    Science.gov (United States)

    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

  14. SOIL SALINITY MAPPING USING MULTITEMPORAL LANDSAT DATA

    Directory of Open Access Journals (Sweden)

    A. Azabdaftari

    2016-06-01

    Full Text Available Soil salinity is one of the most important problems affecting many areas of the world. Saline soils present in agricultural areas reduce the annual yields of most crops. This research deals with the soil salinity mapping of Seyhan plate of Adana district in Turkey from the years 2009 to 2010, using remote sensing technology. In the analysis, multitemporal data acquired from LANDSAT 7-ETM+ satellite in four different dates (19 April 2009, 12 October 2009, 21 March 2010, 31 October 2010 are used. As a first step, preprocessing of Landsat images is applied. Several salinity indices such as NDSI (Normalized Difference Salinity Index, BI (Brightness Index and SI (Salinity Index are used besides some vegetation indices such as NDVI (Normalized Difference Vegetation Index, RVI (Ratio Vegetation Index, SAVI (Soil Adjusted Vegetation Index and EVI (Enhamced Vegetation Index for the soil salinity mapping of the study area. The field’s electrical conductivity (EC measurements done in 2009 and 2010, are used as a ground truth data for the correlation analysis with the original band values and different index image bands values. In the correlation analysis, two regression models, the simple linear regression (SLR and multiple linear regression (MLR are considered. According to the highest correlation obtained, the 21st March, 2010 dataset is chosen for production of the soil salinity map in the area. Finally, the efficiency of the remote sensing technology in the soil salinity mapping is outlined.

  15. Soil resilience mapping in selective wetlands, West Suez Canal, Egypt

    OpenAIRE

    W.A. Abdel Kawy; Abdel-Aziz Belal

    2011-01-01

    The aims of this study are: (1) producing a geometrically corrected physiographic-soil map scale 1:50,000 reduced to the attached map; (2) detecting some soil characteristics as (effective soil depth, salinity and alkalinity) of the investigated area during the last 28 years to produce the soil resilience maps. To fulfill the first aim, eight soil profiles were selected from 30 profiles to represent the different mapping units. Morphological description was carried out and soil samples wer...

  16. GlobalSoilMap for Soil Organic Carbon Mapping and as a Basis for Global Modeling

    NARCIS (Netherlands)

    Arrouays, D.; Minasny, B.; McBratney, A.; Grundy, Mike; McKenzie, Neil; Thompson, James; Gimona, Alessandro; Hong, Suk Young; Smith, Scott; Hartemink, A.E.; Chen, Songchao; Martin, Manuel P.; Mulder, V.L.; Richer-de-Forges, A.C.; Odeh, Inakwu; Padarian, José; Lelyk, Glenn; Poggio, Laura; Savin, Igor; Stolbovoy, Vladimir; Leenaars, J.G.B.; Heuvelink, G.B.M.; Montanarella, Luca; Panagos, P.; Hempel, Jon

    2017-01-01

    The demand for information on functional soil properties is high and has increased over time. This is especially true for soil organic carbon (SOC) in the framework of food security and climate change. The GlobalSoilMap consortium was established in response to such a soaring demand for

  17. Landform segmentation for digital soil mapping

    Science.gov (United States)

    Gruber, Fabian E.; Baruck, Jasmin; Rutzinger, Martin; Geitner, Clemens

    2014-05-01

    Knowledge of the spatial distribution of soil is the basis for many agri- and silvicultural applications and provides information about ecological soil functions. Especially in mountain regions slow and often disturbed soil formation leads to shallow soil depths and a high soil vulnerability considering for instance soil erosion and human modification. The project 'ReBo - Terrain Classification of Airborne Laser Scanning (ALS) Data to Support Digital Soil Mapping', funded by the Autonomous Province of Bolzano - South Tyrol, aims to increase the availability of such information by combining geomorphometric analysis and field survey. The proposed digital soil mapping strategy is making use of a geographic object-based analysis (GEOBIA) approach considering the strong relation between soil formation and surrounding geomorphological settings. The first analysis step is the terrain segmentation using a high resolution ALS digital terrain model (DTM) with regard to geomorphological features. This study investigates the applicability of the GRASS GIS extension r.geomorphons for landform segmentation in the GEOBIA digital soil mapping approach. The module r.geomorphons (Jasiewicz and Stepinski, 2013) applies a pattern recognition method based on the visibility neighborhood of the focus pixel. The input parameter search radius (L) represents the maximum distance for line-of-sight calculation, splitting landforms into components if a landform is larger than L. The module yields, along with the unclassified results, a map containing the landform elements flat, peak, ridge, shoulder, slope, spur, hollow, foot slope, valley and pit. As soil formation and hence soil units (i.e. classes or soil communities) are often related to one or more specific landform elements (or parts of them) it is investigated to what extent there is a correlation between the landforms identified by r.geomorphons and mapped soil units. Due to the hitherto lack of detailed soil information in South Tyrol

  18. Continuous Mapping of Soil pH Using Digital Soil Mapping Approach in Europe

    Directory of Open Access Journals (Sweden)

    Ciro Gardi

    2012-07-01

    Full Text Available Soil pH is one of the most important chemical parameters of soil, playing an essential role on the agricultural production and on the distribution of plants and soil biota communities. It is the expression of soil genesis that in turns is a function of soil forming factors and influences all the chemical, physical and biological processes that occur in the soil. Thus it shapes the entire soil ecosystem. Due to any of the above reasons, mapping of soil pH becomes very important to provide harmonised soil pH data to policy makers, public bodies and researchers. In order to obtain a continuous mapping of soil pH for Europe, adopting the digital soil mapping approach, a set of continuously distribute covariates, highly correlated with pH, were selected. The estimate of soil pH was realized using a regression procedure, coupled with the kriging of the residuals. More than 30.000 points on top soil pH (CaCl2 were used, and 27 covariates were tested as predictors. The similar approach was already applied with 12.333 samples to produce a pH map of Europe using European Soil Profile Data in 2008 which compiles several databases from 11 different sources (Reuter et al. 2008. Our study was conducted to update the previous data and maps based on LUCAS (EUROSTAT - Land Use/Cover Area frame statistical Survey, BIOSOIL (Hiederer and Durrant, 2010 and merged database which was used to produce previous soil pH map of Europe (Reuter et al. 2008. We used a compilation of more than 30.000 soil pH measurements from 13 different sources to create a continuous map of soil pH across Europe using a geostatistical approach based on regression-kriging. Regression was based on the use of 27 covariates in the form of raster maps at 1km resolution to explain the differences in the distribution of soil pH in CaCl2 and we added the kriged map of the residuals from the regression model.

  19. Soil moisture mapping for aquarius

    Science.gov (United States)

    Aquarius is the first satellite to provide both passive and active L-band observations of the Earth. In addition, the instruments on Satelite de Aplicaciones Cientificas-D (SAC-D) provide complementary information for analysis and retrieval algorithms. Our research focuses on the retrieval of soil m...

  20. Mapping Soil Organic Matter with Hyperspectral Imaging

    Science.gov (United States)

    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

  1. Provisional maps of thermal areas in Yellowstone National Park, based on satellite thermal infrared imaging and field observations

    Science.gov (United States)

    Vaughan, R. Greg; Heasler, Henry; Jaworowski, Cheryl; Lowenstern, Jacob B.; Keszthelyi, Laszlo P.

    2014-01-01

    Maps that define the current distribution of geothermally heated ground are useful toward setting a baseline for thermal activity to better detect and understand future anomalous hydrothermal and (or) volcanic activity. Monitoring changes in the dynamic thermal areas also supports decisions regarding the development of Yellowstone National Park infrastructure, preservation and protection of park resources, and ensuring visitor safety. Because of the challenges associated with field-based monitoring of a large, complex geothermal system that is spread out over a large and remote area, satellite-based thermal infrared images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to map the location and spatial extent of active thermal areas, to generate thermal anomaly maps, and to quantify the radiative component of the total geothermal heat flux. ASTER thermal infrared data acquired during winter nights were used to minimize the contribution of solar heating of the surface. The ASTER thermal infrared mapping results were compared to maps of thermal areas based on field investigations and high-resolution aerial photos. Field validation of the ASTER thermal mapping is an ongoing task. The purpose of this report is to make available ASTER-based maps of Yellowstone’s thermal areas. We include an appendix containing the names and characteristics of Yellowstone’s thermal areas, georeferenced TIFF files containing ASTER thermal imagery, and several spatial data sets in Esri shapefile format.

  2. Digital Soil Mapping – A platform for enhancing soil learning.

    Science.gov (United States)

    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...

  3. Digital soil map of the Ussuri River basin

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  5. Soil map density and a nation's wealth and income

    NARCIS (Netherlands)

    Hartemink, A.E.

    2008-01-01

    Little effort has been made to link soil mapping and soil data density to a nation’s welfare. Soil map density in 31 European countries and 44 low and middle income countries is linked to Gross Domestic Product (GDP) per capita and the number of soil scientists per country.

  6. Progress towards GlobalSoilMap.net soil database of Denmark

    DEFF Research Database (Denmark)

    Adhikari, Kabindra; Bou Kheir, Rania; Greve, Mogens Humlekrog

    2012-01-01

    presents recent advancements in Digital Soil Mapping (DSM) activities in Denmark with an example of soil clay mapping using regression-based DSM techniques. Several environmental covariates were used to build regression rules and national scale soil prediction was made at 30 m resolution. Spatial...... content mapping, the plans for future soil mapping activities in support to GlobalSoilMap.net project initiatives are also included in this paper. Our study thought to enrich and update Danish soil database and Soil information system with new fine resolution soil property maps.......Denmark is an agriculture-based country where intensive mechanized cultivation has been practiced continuously for years leading to serious threats to the soils. Proper use and management of Danish soil resources, modeling and soil research activities need very detailed soil information. This study...

  7. Soil and Terrain Database for Malawi (ver. 1.0) (SOTER_Malawi)

    NARCIS (Netherlands)

    Kempen, B.

    2014-01-01

    The Soil and Terrain database for Malawi (version 1.0), at scale 1:1 million, was compiled based on the soil map of Malawi at scale 1:250,000 (compiled by the Land Resources Evaluation Project) that was complemented with soil boundary information from the provisional soil map at scale 1:1 million.

  8. Disaggregation of Soil Map Units for Improved Ecological Site Mapping in Rangelands

    Science.gov (United States)

    Rangeland soils are often mapped with soil map units consisting of associations, complexes, and undifferentiated groups composed of varied soil components. Because different components may be related to different ecological sites, the unmapped heterogeneity within map units limits the potential uses...

  9. Neighborhood size of training data influences soil map disaggregation

    Science.gov (United States)

    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 ...

  10. Digital soil mapping: bridging research, environmental application, and operation

    NARCIS (Netherlands)

    Boettinger, J.L.; Howell, D.W.; Moore, A.M.; Hartemink, A.E.; Kienast-Brown, S.

    2010-01-01

    Digital Soil Mapping is the creation and the population of a geographically referenced soil database. It is generated at a given resolution by using field and laboratory observation methods coupled with environmental data through quantitative relationships. Digital soil mapping is advancing on

  11. Creating a conceptual hydrological soil response map for the ...

    African Journals Online (AJOL)

    2014-03-03

    Mar 3, 2014 ... The soil water regime is a defining ecosystem service, directly influencing vegetation and animal distribution. Therefore ... These observations were used to determine soil distribution rules, from which the soil map was created in SoLIM. The map was .... Determining characteristics. CHSRU. Sodic site.

  12. Digital soil mapping: strategy for data pre-processing

    Directory of Open Access Journals (Sweden)

    Alexandre ten Caten

    2012-08-01

    Full Text Available The region of greatest variability on soil maps is along the edge of their polygons, causing disagreement among pedologists about the appropriate description of soil classes at these locations. The objective of this work was to propose a strategy for data pre-processing applied to digital soil mapping (DSM. Soil polygons on a training map were shrunk by 100 and 160 m. This strategy prevented the use of covariates located near the edge of the soil classes for the Decision Tree (DT models. Three DT models derived from eight predictive covariates, related to relief and organism factors sampled on the original polygons of a soil map and on polygons shrunk by 100 and 160 m were used to predict soil classes. The DT model derived from observations 160 m away from the edge of the polygons on the original map is less complex and has a better predictive performance.

  13. NACP MsTMIP: Unified North American Soil Map

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set provides soil maps for the United States (US) (including Alaska), Canada, Mexico, and a part of Guatemala. The map information content...

  14. NACP MsTMIP: Unified North American Soil Map

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides soil maps for the United States (US) (including Alaska), Canada, Mexico, and a part of Guatemala. The map information content includes maximum...

  15. Downscaling Digital Soil Organic Carbon Map

    Directory of Open Access Journals (Sweden)

    shahrokh fatehi

    2017-02-01

    Full Text Available Introduction: Spatial scale is a major concept in many sciences concerned with human activities and physical, chemical and biological processes occurring at the earth’s surface. Many environmental problems such as the impact of climate change on ecosystems, food, water and soil security requires not only an understanding of how processes operates at different scales and how they can be linked across scales but also gathering more information at finer spatial resolution. This paper presents results of different downscaling techniques taking soil organic matter data as one of the main and basic environmental piece of information in Mereksubcatchment (covered about 24000 ha located in Kermanshah province. Techniques include direct model and point sampling under generalized linear model, regression tree and artificial neural networks. Model performances with respect to different indices were compared. Materials and Methods: legacy soil data is used in this research, 320 observation points were randomly selected. Soil samples were collected from 0-30 cm of the soil surface layer in 2008 year. After preliminary data processing and point pattern analysis, spatial structure information of organic carbon determined using variography. Then, the support point data were converted to block support of 50 m by using block ordinary kriging. Covariates obtained from three resources including digital elevation model, TM Landsat imagery and legacy polygon maps. 23 relief parameters were derived from digital elevation model with 10m × 10m grid-cell resolution. Environmental information obtained from Landsat imagery included, clay index, normalized difference vegetation index, grain size index. The image data were re-sampled from its original spatial resolution of 30*30m to resolution of 10m*10m. Geomorphology, lithology and land use maps were also included in modelling process as categorical auxiliary variables. All auxiliary variables aggregated to 50*50 grid

  16. Saline soils spectral library as a tool for digital soil mapping

    Science.gov (United States)

    Bas, María Victoria; Meléndez-Pastor, Ignacio; Navarro-Pedreño, José; Gómez, Ignacio; Mataix-Solera, Jorge; Hernández, Encarni

    2013-04-01

    Soil information is needed at regional to global scales for proper land management. Soil scientist has been historically interested in mapping soil classes and properties to represent and explore the spatial distribution of soil characteristics. Fortunately, soil mapping came into the digital era decades ago, enabling the dissemination of computationally intensive techniques (e.g., geostatistics). Digital soil mapping is moving forward in recent decades. Digital soil mapping has evolved from "traditional" studies that employed a set of soils to build soil maps, to more recent approaches that exploit the increasing computing facilities to combine soil databases with ancillary data such as digital elevation models, remote sensing imagery and proximal sensing datasets. The inclusion of VNIR spectroscopy in digital soil mapping approaches is an outstanding research field. VNIR spectroscopy has largely been employed to quantify soil properties with proximal sensor and remote sensor (i.e., imaging spectroscopy). One of the traditional problems in soil mapping is the time needed to compile a soil database large enough to allow for mapping with robustness. Therefore there is a growing interest in using the less time consuming, immutability of the sample and increasing accuracy of soil spectroscopy to obtain accurate enough soil maps but with lower data requirements. This research trend is particularly interesting for the study of highly dynamic soil processes for which is necessary to know the spatial and temporal changes of certain properties for a correct soil assessment. The objective of this work was the study of soil salinity which is a dynamic property responding to seasonal (i.e., vertical upwelling) and inter-annual (i.e., salinization) changes. Soil salinity is a major constraint for agriculture by limiting or excluding certain crops. Thus, a continuous monitoring of soil salinity is needed to select the most suitable crops and to prevent future salinization

  17. Soil properties mapping with the DIGISOIL multi-sensor system

    Science.gov (United States)

    Grandjean, G.

    2012-04-01

    The multidisciplinary DIGISOIL project aimed to integrate and improve in situ and proximal measurement technologies for the assessment of soil properties and soil degradation indicators, going from the sensing technologies to their integration and their application in (digital) soil mapping (DSM). In order to assess and prevent soil degradation and to benefit from the different ecological, economical and historical functions of the soil in a sustainable way, high resolution and quantitative maps of soil properties are needed. The core objective of the project is to explore and exploit new capabilities of advanced geophysical technologies for answering this societal demand. To this aim, DIGISOIL addresses four issues covering technological, soil science and economic aspects: (i) the validation of geophysical (in situ, proximal and airborne) technologies and integrated pedo-geophysical inversion techniques (mechanistic data fusion) (ii) the relation between the geophysical parameters and the soil properties, (iii) the integration of the derived soil properties for mapping soil functions and soil threats, (iv) the pre-evaluation, standardisation and sub-industrialization of the proposed methodologies, including technical and economical studies related to the societal demand. With respect to these issues, the DIGISOIL project allows to develop, test and validate the most relevant geophysical technologies for mapping soil properties. The system was tested on different field tests, and validated the proposed technologies and solutions for each of the identified methods: geoelectric, GPR, EMI, seismics, magnetic and hyperspectral. After data acquisition systems, sensor geometry, and advanced data processing techniques have been developed and validated, we present now the solutions for going from geophysical data to soil properties maps. For two test sites, located respectively in Luxembourg (LU) and Mugello (IT) a set of soil properties maps have been produced. They give

  18. Uncertainty quantification of soil property maps with statistical expert elicitation

    NARCIS (Netherlands)

    Truong, N.P.; Heuvelink, G.B.M.

    2013-01-01

    Accuracy assessment and uncertainty analyses are key to the quality of data and data analysis in a wide array of scientific disciplines. For soil science, it is important to quantify the accuracy of soil maps that are used in environmental and agro-ecological studies and decision making. Many soil

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

    Science.gov (United States)

    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

  20. Predictive soil mapping in southern Arizona's basin and range

    Science.gov (United States)

    Levi, Matthew Robert

    A fundamental knowledge gap in understanding land-atmosphere interactions is accurate, high-resolution soil properties. Remote sensing and spatial modeling techniques can bridge the gap between site-specific soil properties and landscape variability, thereby improving predictions of soil attributes. Three studies were completed to advance soil prediction models in semiarid areas. The first study developed a soil pre-mapping technique using automated image segmentation that utilized soil-landscape relationships and surface reflectance to produce an effective map unit design in a 160,000 ha soil survey area. Overall classification accuracy of soil taxonomic units at the suborder was 58 % after including soil temperature regime. Physical soil properties were not significantly different for individual transects; however, properties were significantly different between soil pre-map units when soils from the entire study area were compared. Other studies used a raster approach to predict physical soil properties at a 5 m spatial resolution for a 6,265 ha area using digital soil mapping. The second study utilized remotely-sensed auxiliary data to develop a sampling design and compared three geostatistical techniques for predicting surface soil properties. Ordinary kriging had the smallest prediction error; however, regression kriging preserved landscape features present in the study area and demonstrated the potential of this technique for quantifying variability of soil components within soil map units. The third study applied quantitative data from soil prediction models in study 2 and additional models of subsurface properties to a pedotransfer function for predicting hydraulic soil parameters at the landscape scale. Saturated hydraulic conductivity and water retention parameters were used to predict water residence times for loss to gravity and evapotranspiration across the landscape. High water residence time for gravitational water corresponded to both low drainage

  1. An on-the-go-soil sampler for an automated soil nitrate mapping system

    NARCIS (Netherlands)

    Sibley, K.J.; Adsett, J.F.; Struik, P.C.

    2008-01-01

    An automated on-the-go soil sampler was developed as part of a soil nitrate mapping system that collects data for precisely analyzing small-scale variation in soil NO3-N. An essential requirement of the sampler is the ability to reliably collect a soil sample of known "weight" (mass). It was

  2. Regional validation of a high-resolution digital soil map using soil profile attributes

    Science.gov (United States)

    Digital soil mapping (DSM) for precision agriculture (PA) management is aimed at developing models that predict soil properties or classes using legacy soil data, sensors, and environmental covariates. The utility of DSM for PA centers on its ability to provide soil information to optimize crop yiel...

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

    Science.gov (United States)

    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

  4. Development of predictive mapping techniques for soil survey and salinity mapping

    Science.gov (United States)

    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.

  5. Physico-empirical approach for mapping soil hydraulic behaviour

    Directory of Open Access Journals (Sweden)

    G. D'Urso

    1997-01-01

    Full Text Available Abstract: Pedo-transfer functions are largely used in soil hydraulic characterisation of large areas. The use of physico-empirical approaches for the derivation of soil hydraulic parameters from disturbed samples data can be greatly enhanced if a characterisation performed on undisturbed cores of the same type of soil is available. In this study, an experimental procedure for deriving maps of soil hydraulic behaviour is discussed with reference to its application in an irrigation district (30 km2 in southern Italy. The main steps of the proposed procedure are: i the precise identification of soil hydraulic functions from undisturbed sampling of main horizons in representative profiles for each soil map unit; ii the determination of pore-size distribution curves from larger disturbed sampling data sets within the same soil map unit. iii the calibration of physical-empirical methods for retrieving soil hydraulic parameters from particle-size data and undisturbed soil sample analysis; iv the definition of functional hydraulic properties from water balance output; and v the delimitation of soil hydraulic map units based on functional properties.

  6. Predicting and mapping soil available water capacity in Korea.

    Science.gov (United States)

    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.

  7. Predicting and mapping soil available water capacity in Korea

    Directory of Open Access Journals (Sweden)

    Suk Young Hong

    2013-04-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

  9. Soil Moisture Mapping from ASAR Imagery of the Mulargia basin

    Science.gov (United States)

    Fois, L.; Montaldo, N.

    2016-12-01

    The state of the soil moisture is a key variable controlling surface water and energy balances. High resolution data of the ASAR (advanced synthetic aperture radar) sensor aboard European Space Agency's Envisat satellite offers the opportunity for monitoring surface soil moisture at high resolution (up to 30 m), which is suitable for distributed mapping within the small scales of typical Mediterranean basins. These basins are characterized by strong topography and high spatial variability of physiographic properties, and only high spatial resolution satellite images allow to estimate adequately soil moisture spatial variability. ASAR-based soil moisture mapping of the Mulargia basin (area of about 65 sq.km) are collected for 2003-2006 years. In Mediterranean basins, such as the Mulargia basin, characterized by water-limited conditions, even though there is no universal relationship between vegetation and soil patterns in water-limited conditions some relationship between soil water storage capacity and vegetation type and density can be found: for instance, typically an increase of woody vegetation dimension and canopy density when moving from uplands of a hillslope (with thin coarse textured soils) to alluvial fans (with deep soils of finer texture). We investigated the relationships between soil moisture spatial variability, soil depth and vegetation distribution, which impact strongly soil, vegetation and atmosphere interactions. For the case study ASAR products at single and double polarization are tested and validated. For validating radar soil moisture estimates, spatially distributed soil moisture ground-truth data have also been collected over the whole basin through the TDR technique and the gravimetric method, in days with available radar images. Results shows: 1) the high resolution ASAR imagery accuracy for producing maps of surface soil moisture patterns at the catchment scale and their reliability for different seasons (wet vs dry), and 2) a

  10. Evaluating the new soil erosion map of Hungary

    Science.gov (United States)

    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.

  11. Sensing and 3D Mapping of Soil Compaction.

    Science.gov (United States)

    Tekin, Yücel; Kul, Basri; Okursoy, Rasim

    2008-05-26

    Soil compaction is an important physical limiting factor for the root growth and plant emergence and is one of the major causes for reduced crop yield worldwide. The objective of this study was to generate 2D/3D soil compaction maps for different depth layers of the soil. To do so, a soil penetrometer was designed, which was mounted on the three-point hitch of an agricultural tractor, consisting of a mechanical system, data acquisition system (DAS), and 2D/3D imaging and analysis software. The system was successfully tested in field conditions, measuring soil penetration resistances as a function of depth from 0 to 40 cm at 1 cm intervals. The software allows user to either tabulate the measured quantities or generate maps as soon as data collection has been terminated. The system may also incorporate GPS data to create geo-referenced soil maps. The software enables the user to graph penetration resistances at a specified coordinate. Alternately, soil compaction maps could be generated using data collected from multiple coordinates. The data could be automatically stratified to determine soil compaction distribution at different layers of 5, 10,.…, 40 cm depths. It was concluded that the system tested in this study could be used to assess the soil compaction at topsoil and the randomly distributed hardpan formations just below the common tillage depths, enabling visualization of spatial variability through the imaging software.

  12. Comparing the Ability of Conventional and Digital Soil Maps to Explain Soil Variability using Diversity Indices

    Directory of Open Access Journals (Sweden)

    zohreh mosleh

    2017-06-01

    Full Text Available Introduction: Effective and sustainable soil management requires knowledge about the spatial patterns of soil variation and soil surveys are important and useful sources of data that can be used. Prior knowledge about the spatial distribution of the soils is the first essential step for this aim but this requires the collection of large amounts of soil information. However, the conventional soil surveys are usually not useful for providing quantitative information about the spatial distribution of soil properties that are used in many environmental studies. Recently, by the rapid development of the computers and technology together with the availability of new types of remote sensing data and digital elevation models (DEMs, digital and quantitative approaches have been developed. These new techniques relies on finding the relationships between soil properties or classes and the auxiliary information that explain the soil forming factors or processes and finally predict soil patterns on the landscape. Different types of the machine learning approaches have been applied for digital soil mapping of soil classes, such as the logistic and multinomial logistic regressions, neural networks and classification trees. In reality, soils are physical outcomes of the interactions happening among the geology, climate, hydrology and geomorphic processes. Diversity is a way of measuring soil variation. Ibanez (9 first introduced ecological diversity indices as measures of diversity. Application of the diversity indices in soil science have considerably increased in recent years. Taxonomic diversity has been evaluated in the most previous researches whereas comparing the ability of different soil mapping approaches based on these indices was rarely considered. Therefore, the main objective of this study was to compare the ability of the conventional and digital soil maps to explain the soil variability using diversity indices in the Shahrekord plain of

  13. Predictive spatial modelling for mapping soil salinity at continental scale

    Science.gov (United States)

    Bui, Elisabeth; Wilford, John; de Caritat, Patrice

    2017-04-01

    Soil salinity is a serious limitation to agriculture and one of the main causes of land degradation. Soil is considered saline if its electrical conductivity (EC) is > 4 dS/m. Maps of saline soil distribution are essential for appropriate land development. Previous attempts to map soil salinity over extensive areas have relied on satellite imagery, aerial electromagnetic (EM) and/or proximally sensed EM data; other environmental (climate, topographic, geologic or soil) datasets are generally not used. Having successfully modelled and mapped calcium carbonate distribution over the 0-80 cm depth in Australian soils using machine learning with point samples from the National Geochemical Survey of Australia (NGSA), we took a similar approach to map soil salinity at 90-m resolution over the continent. The input data were the EC1:5 measurements on the learning software 'Cubist' (www.rulequest.com) was used as the inference engine for the modelling, a 90:10 training:test set data split was used to validate results, and 100 randomly sampled trees were built using the training data. The results were good with an average internal correlation (r) of 0.88 between predicted and measured logEC1:5 (training data), an average external correlation of 0.48 (test subset), and a Lin's concordance correlation coefficient (which evaluates the 1:1 fit) of 0.61. Therefore, the rules derived were mapped and the mean prediction for each 90-m pixel was used for the final logEC1:5 map. This is the most detailed picture of soil salinity over Australia since the 2001 National Land and Water Resources Audit and is generally consistent with it. Our map will be useful as a baseline salinity map circa 2008, when the NGSA samples were collected, for future State of the Environment reports.

  14. Digital soil mapping of a soil classes map at 1:50,000 scale in the Doubs department, France

    Science.gov (United States)

    Lehmann, Sebastien; Eimberck, Micheline; Martin, Manuel P.; Arrouays, Dominique

    2013-04-01

    Recent advances in segmentation processing and in classification using boosted regression trees provide new prospects for predictive digital soil mapping. The availability of numerous soil data through the French soil database Donesol, and easy to access environmental co-variates (DEM and derivatives, geological maps, land cover maps...) makes it possible to produce a predicted soil type map, at a scale of about 1:50,000, validated by point data in the area of Vercel (Jura, France). On this area, the approach we detail here led to mapping a surface only ¼ of which was previously mapped. 2348 point data scattered over the whole territory were used to calibrate and validate the model. First, we produced a predictive map from point data. Half of these data were used to calibrate a model using boosted regression trees. The remaining half were used for validation. We tested 8 iterations using data integrating increasingly large spatial domains. The derivates from the DEM were averaged using circular windows of growing size (diameters from 30 to 1800 m). The resulting map was affected by some noise that we removed, using a filter based on the dominant classes, in order to obtain a map with clear, abrupt limits. Secondly, we used the same approach taking the soil units as calibration data (using a buffer around the limits in order to get "pure" pixels). Finally, the soil surveyor expertise was used to produce a synthesis of these two predictions to obtain a chloropleth map of soil units. The time saved by this approach, in comparison to a classical one, is estimated to be about 70-80 days for 36,000 ha. DSM alone is not sufficient, knowledge of the terrain and external validation remain essential.

  15. Construction of maps for soil recycling in regional infrastructural works integrating soil-quality laws

    NARCIS (Netherlands)

    Lienen, van F.; Frapporti, G.; Stein, A.

    2000-01-01

    A soil-quality map is at present an important tool to integrate laws on soil quality with regional infrastructural works. Basic data are commonly available, but soil quality is an indicator that has to be derived from these data, including site-specific environmental standards.We propose three

  16. Considerations for applying digital soil mapping to ecological sites

    Science.gov (United States)

    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...

  17. Field guide for mapping post-fire soil burn severity

    Science.gov (United States)

    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...

  18. Mapping forest soil organic matter on New Jersey's coastal plain

    Science.gov (United States)

    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...

  19. Soil fertility assessment and mapping of spatial variability at ...

    African Journals Online (AJOL)

    Information on soil fertility assessment and mapping of arable land helps to design appropriate soil fertility management practices. Experiment was conducted at ... Exchangeable Ca and Mg ranged from 9.25 (LU 4) to 23.35 cmol (+) kg-1 (LU 2) and 2.76 (LU 5) to 8.50 cmol (+) kg-1 (LU 3), respectively. The highest (76.86%) ...

  20. LARGE-SCALE INDICATIVE MAPPING OF SOIL RUNOFF

    Directory of Open Access Journals (Sweden)

    E. Panidi

    2017-11-01

    Full Text Available In our study we estimate relationships between quantitative parameters of relief, soil runoff regime, and spatial distribution of radioactive pollutants in the soil. The study is conducted on the test arable area located in basin of the upper Oka River (Orel region, Russia. Previously we collected rich amount of soil samples, which make it possible to investigate redistribution of the Chernobyl-origin cesium-137 in soil material and as a consequence the soil runoff magnitude at sampling points. Currently we are describing and discussing the technique applied to large-scale mapping of the soil runoff. The technique is based upon the cesium-137 radioactivity measurement in the different relief structures. Key stages are the allocation of the places for soil sampling points (we used very high resolution space imagery as a supporting data; soil samples collection and analysis; calibration of the mathematical model (using the estimated background value of the cesium-137 radioactivity; and automated compilation of the map (predictive map of the studied territory (digital elevation model is used for this purpose, and cesium-137 radioactivity can be predicted using quantitative parameters of the relief. The maps can be used as a support data for precision agriculture and for recultivation or melioration purposes.

  1. Do more detailed environmental covariates deliver more accurate soil maps?

    NARCIS (Netherlands)

    Samuel Rosa, A.; Heuvelink, G.B.M.; Vasques, G.M.; Anjos, L.H.C.

    2015-01-01

    In this study we evaluated whether investing in more spatially detailed environmental covariates improves the accuracy of digital soil maps. We used a case study from Southern Brazil to map clay content (CLAY), organic carbon content (SOC), and effective cation exchange capacity (ECEC) of the

  2. The status of soil mapping for the Idaho National Engineering Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Olson, G.L.; Lee, R.D. [Idaho National Engineering Lab., Idaho Falls, ID (United States); Jeppesen, D.J. [Department of Interior, Idaho Falls, ID (United States)

    1995-01-01

    This report discusses the production of a revised version of the general soil map of the 2304-km{sup 2} (890-mi{sup 2}) Idaho National Engineering Laboratory (INEL) site in southeastern Idaho and the production of a geographic information system (GIS) soil map and supporting database. The revised general soil map replaces an INEL soil map produced in 1978 and incorporates the most current information on INEL soils. The general soil map delineates large soil associations based on National Resources Conservation Services [formerly the Soil Conservation Service (SCS)] principles of soil mapping. The GIS map incorporates detailed information that could not be presented on the general soil map and is linked to a database that contains the soil map unit descriptions, surficial geology codes, and other pertinent information.

  3. Functional digital soil mapping for the prediction of available water capacity in Nigeria using legacy data

    NARCIS (Netherlands)

    Ugbaje, S.U.; Reuter, H.I.

    2013-01-01

    Soil information, particularly water storage capacity, is of utmost importance for assessing and managing land resources for sustainable land management. We investigated using digital soil mapping (DSM) and digital soil functional mapping (DSFM) procedures to predict available water capacity (AWC)

  4. Predictive mapping of the acidifying potential for acid sulfate soils

    DEFF Research Database (Denmark)

    Boman, A; Beucher, Amélie; Mattbäck, S

    Developing methods for the predictive mapping of the potential environmental impact from acid sulfate soils is important because recent studies (e.g. Mattbäck et al., under revision) have shown that the environmental hazards (e.g. leaching of acidity) related to acid sulfate soils vary depending...... on their texture (clay, silt, sand etc.). Moreover, acidity correlates, not only with the sulfur content, but also with the electrical conductivity (EC) measured after incubation. Electromagnetic induction (EMI) data collected from an EM38 proximal sensor also enabled the detailed mapping of acid sulfate soils...... over a field (Huang et al., 2014).This study aims at assessing the use of EMI data for the predictive mapping of the acidifying potential in an acid sulfate soil area in western Finland. Different supervised classification modelling techniques, such as Artificial Neural Networks (Beucher et al., 2015...

  5. Digital Soil Map of the World

    NARCIS (Netherlands)

    Sanchez, P.A.; Ahamed, S.; Carré, F.; Hartemink, A.E.; Hempel, J.; Huising, J.; Lagacherie, P.; McBratney, A.B.; McKenzie, N.G.; Lourdes Mendonça-Santos, de M.; Minasny, B.; Montanarella, L.; Okoth, P.; Palm, C.A.; Sachs, J.D.; Shepherd, K.D.; Vägen, T.; Vanlauwe, B.; Walsh, M.G.; Winowiecki, L.A.; Zhang, G.L.

    2009-01-01

    Soils are increasingly recognized as major contributors to ecosystem services such as food production and climate regulation (1, 2), and demand for up-to-date and relevant soil information is soaring. But communicating such information among diverse audiences remains challenging because of

  6. Creating soil moisture maps based on radar satellite imagery

    Science.gov (United States)

    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.

  7. Refining a reconnaissance soil map by calibrating regression models with data from the same map (Normandy, France)

    NARCIS (Netherlands)

    Collard, F.; Kempen, B.; Heuvelink, G.B.M.; Sabi, N.P.A.; Richer de Forge, A.C.; Lehmann, S.; Nehlig, P.; Arrouays, D.

    2014-01-01

    Reconnaissance soil maps at 1:250,000 scale are the most detailed source of soil information for large parts of France. For many environmental applications, however, the level of detail and accuracy of these maps is insufficient. Funds are lacking to refine and update these maps by traditional soil

  8. Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils

    Directory of Open Access Journals (Sweden)

    Marcelo Rodrigo Alves

    2015-10-01

    Full Text Available ABSTRACT In recent years, geotechnologies as remote and proximal sensing and attributes derived from digital terrain elevation models indicated to be very useful for the description of soil variability. However, these information sources are rarely used together. Therefore, a methodology for assessing and specialize soil classes using the information obtained from remote/proximal sensing, GIS and technical knowledge has been applied and evaluated. Two areas of study, in the State of São Paulo, Brazil, totaling approximately 28.000 ha were used for this work. First, in an area (area 1, conventional pedological mapping was done and from the soil classes found patterns were obtained with the following information: a spectral information (forms of features and absorption intensity of spectral curves with 350 wavelengths -2,500 nm of soil samples collected at specific points in the area (according to each soil type; b obtaining equations for determining chemical and physical properties of the soil from the relationship between the results obtained in the laboratory by the conventional method, the levels of chemical and physical attributes with the spectral data; c supervised classification of Landsat TM 5 images, in order to detect changes in the size of the soil particles (soil texture; d relationship between classes relief soils and attributes. Subsequently, the obtained patterns were applied in area 2 obtain pedological classification of soils, but in GIS (ArcGIS. Finally, we developed a conventional pedological mapping in area 2 to which was compared with a digital map, ie the one obtained only with pre certain standards. The proposed methodology had a 79 % accuracy in the first categorical level of Soil Classification System, 60 % accuracy in the second category level and became less useful in the categorical level 3 (37 % accuracy.

  9. An assessment of the accuracy of soil map of Kwara state, Nigeria ...

    African Journals Online (AJOL)

    An assessment of the accuracy of soil map of Kwara state, Nigeria. ... Nigerian Journal of Soil Science ... within and among the three major soil mapping units delineated in Kwara State, on the Federal Department of Agricultural Land Resources (FDALR) soil map of Nigeria was examined using some statistical measures.

  10. Bayesian Maximum Entropy prediction of soil categories using a traditional soil map as soft information.

    NARCIS (Netherlands)

    Brus, D.J.; Bogaert, P.; Heuvelink, G.B.M.

    2008-01-01

    Bayesian Maximum Entropy was used to estimate the probabilities of occurrence of soil categories in the Netherlands, and to simulate realizations from the associated multi-point pdf. Besides the hard observations (H) of the categories at 8369 locations, the soil map of the Netherlands 1:50 000 was

  11. Large-extent digital soil mapping approaches for total soil depth

    Science.gov (United States)

    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

  12. Combining Proximal and Penetrating Soil Electrical Conductivity Sensors for High Resolution Digital Soil Mapping

    Science.gov (United States)

    Proximal ground conductivity sensors produce high spatial resolution maps that integrate the bulk electrical conductivity (ECa) of the soil profile. Variability in conductivity maps must either be inverted to profile conductivity, or be directly calibrated to profile properties for meaningful interp...

  13. Application of Remote Sensing for Mapping Soil Organic Matter Content

    Directory of Open Access Journals (Sweden)

    Bangun Muljo Sukojo

    2010-10-01

    Full Text Available Information organic content is important in monitoring and managing the environment as well as doing agricultural production activities. This research tried to map soil organic content in Malang using remote sensing technology. The research uses 6 bands of data captured by Landsat TM (Thematic Mapper satellite (band 1, 2, 3, 4, 5, 7. The research focuses on pixels having Normalized Difference Soil Index (NDSI more than 0.3. Ground-truth data were collected by analysing organic content of soil samples using Black-Walkey method. The result of analysis shows that digital number of original satellite image can be used to predict soil organic matter content. The implementation of regression equation in predicting soil organic content shows that 63.18% of research area contains of organic in a moderate category.

  14. Wind erosion on heavy-textured soils: calculation and mapping

    Directory of Open Access Journals (Sweden)

    Jana Kozlovsky Dufková

    2011-01-01

    Full Text Available The equation that expresses the influence of factors affecting soil aggregates breakdown, and thus wind erosion, originated from the results of laboratory simulations of soil aggregates breakdown due to low temperatures treatment, field measurements of air temperature and soil moisture, and statistical evaluation of gained outcomes. All the analyses, whether field or laboratory, were realized on three different soils from three different localities of the Bílé Karpaty Mountains foothills – Ostrožská Nová Ves, Blatnice pod Svatým Antonínkem, and Suchá Loz. The statistically significant factors, influencing the soil aggregates breakdown, were determined using multiple regression analysis and stepwise regression. Soil moisture content at time of freezing was the most significant factor affecting soil aggregates breakdown, content of soil particles < 0.01 mm was the least significant one. Based on the results of laboratory and field research there was created a map of heavy-textured soils that are vulnerable to wind erosion.

  15. SoilGrids1km — Global Soil Information Based on Automated Mapping

    Science.gov (United States)

    Hengl, Tomislav; de Jesus, Jorge Mendes; MacMillan, Robert A.; Batjes, Niels H.; Heuvelink, Gerard B. M.; Ribeiro, Eloi; Samuel-Rosa, Alessandro; Kempen, Bas; Leenaars, Johan G. B.; Walsh, Markus G.; Gonzalez, Maria Ruiperez

    2014-01-01

    Background Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. Methodology/Principal Findings We present SoilGrids1km — a global 3D soil information system at 1 km resolution — containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kg−1), soil pH, sand, silt and clay fractions (%), bulk density (kg m−3), cation-exchange capacity (cmol+/kg), coarse fragments (%), soil organic carbon stock (t ha−1), depth to bedrock (cm), World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles), and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images), lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database). Prediction accuracies assessed using 5–fold cross-validation were between 23–51%. Conclusions/Significance SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1) weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2) difficulty to obtain covariates that capture soil forming factors, (3) low sampling density and spatial clustering of soil profile locations. However, as the Soil

  16. SoilGrids1km--global soil information based on automated mapping.

    Directory of Open Access Journals (Sweden)

    Tomislav Hengl

    Full Text Available BACKGROUND: Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. METHODOLOGY/PRINCIPAL FINDINGS: We present SoilGrids1km--a global 3D soil information system at 1 km resolution--containing spatial predictions for a selection of soil properties (at six standard depths: soil organic carbon (g kg-1, soil pH, sand, silt and clay fractions (%, bulk density (kg m-3, cation-exchange capacity (cmol+/kg, coarse fragments (%, soil organic carbon stock (t ha-1, depth to bedrock (cm, World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles, and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images, lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database. Prediction accuracies assessed using 5-fold cross-validation were between 23-51%. CONCLUSIONS/SIGNIFICANCE: SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1 weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2 difficulty to obtain covariates that capture soil forming factors, (3 low sampling density and spatial clustering of soil profile locations. However, as the SoilGrids system is

  17. Mapping Soil Erosion in a Quaternary Catchment in Eastern Cape ...

    African Journals Online (AJOL)

    Temp

    2017-04-06

    Apr 6, 2017 ... Mapping Soil Erosion in a Quaternary Catchment in Eastern Cape. Using Geographic Information System and Remote Sensing. Kwanele Phinziª ⃰, Njoya Silas Ngetarª. ªSchool of Agricultural, Earth and Environmental Sciences, Discipline of Geography, University of. KwaZulu-Natal, Durban, South Africa.

  18. Weed Mapping with Co-Kriging Using Soil Properties

    DEFF Research Database (Denmark)

    Heisel, Torben; Ersbøll, Annette Kjær; Andreasen, Christian

    1999-01-01

    Our aim is to build reliable weed maps to control weeds in patches. Weed sampling is time consuming but there are some shortcuts. If an intensively sampled variable (e.g. soil property) can be used to improve estimation of a sparsely sampled variable (e.g. weed distribution), one can reduce weed...

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

    Science.gov (United States)

    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.

  20. A new approach of mapping soils in the Alps - Challenges of deriving soil information and creating soil maps for sustainable land use. An example from South Tyrol (Italy)

    Science.gov (United States)

    Baruck, Jasmin; Gruber, Fabian E.; Geitner, Clemens

    2015-04-01

    Nowadays sustainable land use management is gaining importance because intensive land use leads to increasing soil degradation. Especially in mountainous regions like the Alps sustainable land use management is important, as topography limits land use. Therefore, a database containing detailed information of soil characteristics is required. However, information of soil properties is far from being comprehensive. The project "ReBo - Terrain classification based on airborne laser scanning data to support soil mapping in the Alps", founded by the Autonomous Province of Bolzano, aims at developing a methodical framework of how to obtain soil data. The approach combines geomorphometric analysis and soil mapping to generate modern soil maps at medium-scale in a time and cost efficient way. In this study the open source GRASS GIS extension module r.geomorphon (Jasciewicz and Stepinski, 2013) is used to derive topographically homogeneous landform units out of high resolution DTMs on scale 1:5.000. Furthermore, for terrain segmentation and classification we additionally use medium-scale data sets (geology, parent material, land use etc.). As the Alps are characterized by a great variety of topography, parent material, wide range of moisture regimes etc. getting reliable soil data is difficult. Additionally, geomorphic activity (debris flow, landslide etc.) leads to natural disturbances. Thus, soil properties are highly diverse and largely scale dependent. Furthermore, getting soil information of anthropogenically influenced soils is an added challenge. Due to intensive cultivation techniques the natural link between the soil forming factors is often repealed. In South Tyrol we find the largest pome producing area in Europe. Normally, the annual precipitation is not enough for intensive orcharding. Thus, irrigation strategies are in use. However, as knowledge about the small scaled heterogeneous soil properties is mostly lacking, overwatering and modifications of the

  1. Development and mapping of seleniferous soils in northwestern India.

    Science.gov (United States)

    Dhillon, Karaj S; Dhillon, Surjit K

    2014-03-01

    Periodic surveys were undertaken to identify and characterize Se-contaminated soils in northwestern India. Total Se content varied from 0.023 to 4.91mgkg(-1) in 0-15cm surface soil and 0.64-515.0mgkg(-1) in samples of vegetation. Selenium-contaminated land occupying an area of 865ha was classified into different categories based on total Se content of soils as moderately contaminated (0.5-2.0mg Sekg(-1)) and highly contaminated (>2.0mg Sekg(-1)). The normal soils contained soil map was prepared using village level cadastral maps. Se-contaminated soils were silty loam to silty clay loam in texture and tested pH 7.9-8.8, electrical conductivity 0.3-0.7dSm(-1), calcium carbonate 0.1-4.1% and organic carbon 0.4-1.0%. Selenium was present throughout the soil profile up to 2m depth; 0-15cm surface soil layer contained 1.5 to 6.0 times more Se than in subsurface layers. Selenium content in rock samples collected from lower and upper Shiwalik sub-Himalayan ranges varied from 1864 to 2754 and 11 to 847μgkg(-1), respectively. The sediments transported through seasonal rivulets linking the Shiwalik ranges to affected sites contained 0.57-2.89mg Sekg(-1). The underground water containing 2.5-69.5μg SeL(-1) used for irrigating transplanted rice grown in Se-contaminated area resulted in a net Se addition in soil up to 881gha(-1)y(-1); possibly further aggravating the Se-toxicity problem. Presence of substantial amount of Se in rock samples and sediments of seasonal rivulets suggests that Se-rich materials are being transported from Shiwalik hills and deposited in regions where seasonal rivulets end up. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. The effectiveness of digital soil mapping to predict soil properties over low-relief areas.

    Science.gov (United States)

    Mosleh, Zohreh; Salehi, Mohammad Hassan; Jafari, Azam; Borujeni, Isa Esfandiarpoor; Mehnatkesh, Abdolmohammad

    2016-03-01

    This study investigates the ability of different digital soil mapping (DSM) approaches to predict some of physical and chemical topsoil properties in the Shahrekord plain of Chaharmahal-Va-Bakhtiari province, Iran. According to a semi-detailed soil survey, 120 soil samples were collected from 0 to 30 cm depth with approximate distance of 750 m. Particle size distribution, coarse fragments (CFs), electrical conductivity (EC), pH, organic carbon (OC), and calcium carbonate equivalent (CCE) were determined. Four machine learning techniques, namely, artificial neural networks (ANNs), boosted regression tree (BRT), generalized linear model (GLM), and multiple linear regression (MLR), were used to identify the relationship between soil properties and auxiliary information (terrain attributes, remote sensing indices, geology map, existing soil map, and geomorphology map). Root-mean-square error (RMSE) and mean error (ME) were considered to determine the performance of the models. Among the studied models, GLM showed the highest performance to predict pH, EC, clay, silt, sand, and CCE, whereas the best model is not necessarily able to make accurate estimation. According to RMSE%, DSM has a good efficiency to predict soil properties with low and moderate variabilities. Terrain attributes were the main predictors among different studied auxiliary information. The accuracy of the estimations with more observations is recommended to give a better understanding about the performance of DSM approach over low-relief areas.

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

    Science.gov (United States)

    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

  4. Towards decadal soil salinity mapping using Landsat time series data

    Science.gov (United States)

    Fan, Xingwang; Weng, Yongling; Tao, Jinmei

    2016-10-01

    Salinization is one of the major soil problems around the world. However, decadal variation in soil salinization has not yet been extensively reported. This study exploited thirty years (1985-2015) of Landsat sensor data, including Landsat-4/5 TM (Thematic Mapper), Landsat-7 ETM+ (Enhanced Thematic Mapper Plus) and Landsat-8 OLI (Operational Land Imager), for monitoring soil salinity of the Yellow River Delta, China. The data were initially corrected for atmospheric effects, and then matched the spectral bands of EO-1 (Earth Observing One) ALI (Advanced Land Imager). Subsequently, soil salinity maps were derived with a previously developed PLSR (Partial Least Square Regression) model. On intra-annual scale, the retrievals showed that soil salinity increased in February, stabilized in March, and decreased in April. On inter-annual scale, soil salinity decreased within 1985-2000 (-0.74 g kg-1/10a, p salinity retrieval, and further the understanding of soil salinization development over the Yellow River Delta.

  5. Mapping soil magnetic susceptibility and mineralogy in Ukraine

    Science.gov (United States)

    Menshov, Oleksandr; Pereira, Paulo; Kruglov, Oleksandr; Sukhorada, Anatoliy

    2017-04-01

    Soil suatainable planning is fundamental for agricultural areas. Soil mapping and modeling are increasingly used in agricultural areas in the entire world (Brevik et al., 2016). They are beneficial to land managers, to reduce soil degradation, increase soil productivity and their restoration. Magnetic susceptibility (MS) methods are low cost and accurate for the developing maps of agricultural areas.. The objective of this work is to identify the minerals responsible for MS increase in soils from the two study areas in Poltava and Kharkiv region. The thermomagnetic analyses were conducted using the KLY-4 with an oven apparatus. The hysteresis parameters were measured with the Rotating Magnetometer at the Geophysical Centre Dourbes, Belgium. The results showed that all of samples from Kharkiv area and the majortity of the samples collected in Poltava area represent the pseudo single domain (PSD) zone particles in Day plot. According to Hanesch et al. (2006), the transformation of goethite, ferrihydrite or hematite to a stronger ferrimagnetic phase like magnetite or maghemite is common in strongly magnetic soils with high values of organic carbon content. In our case of thermomagnetic study, the first peak on the heating curve near 260 ˚C indicates the presence of ferrihydrite which gradually transforms into maghemite (Jordanova et al., 2013). A further decrease in the MS identified on the heating curve may be related to the transformation of the maghemite to hematite. A second MS peak on the heating curve near 530 ˚C and the ultimate loss of magnetic susceptibility near 580 ˚C were caused by the reduction of hematite to magnetite. The shape of the thermomagnetic curves suggests the presence of single domain (SD) particles at room temperature and their transformation to a superparamagnetic (SP) state under heating. Magnetic mineralogical analyses suggest the presence of highly magnetic minerals like magnetite and maghemite as well as slightly magnetic goethite

  6. How to map soil carbon stocks in highly urbanized regions?

    Science.gov (United States)

    Vasenev, V. I.; Stoorvogel, J. J.

    2012-04-01

    Soil organic carbon (SOC) is the largest carbon stock in terrestrial ecosystems and the capacity for carbon sequestration is a widely accepted soil function. For land-use planning and decision making the regional analysis of SOC stocks and their spatial variability is an important and challenging task that receives increasing attention. Quite a few studies focus on mapping the carbon stocks in natural and agricultural areas using digital soil mapping (DSM) techniques. Although urban areas remain almost neglected. The urban environment provides a number of specific features and processes that influence soil formation and functioning: soil sealing, functional zoning and settlement history. This not only results in a considerable urban SOC (especially in the subsoil), but also results in a unique spatial variability of SOC stocks at short distance. In contrast to the often gradual changes in natural areas, urban soils may exhibit abrupt changes due to the anthropogenic influence. Thus implementation of standard DSM methodology will result in extremely high nuggets and correspondingly low prediction accuracy. Besides, traditional regression kriging, widely-used for the case when legacy data is lacking, is often based on the correlation between SOC and dominating soil forming factors (climate, relief, parent material and vegetation). Although in urban conditions, anthropogenic influence itself turns out to be a predominant soil-forming factor. The spatial heterogeneity of urban soil carbon stocks is further complicated by a specific profile distribution with possible second SOC maximum, referred to cultural layer. Importance of urban SOC as well as specifics of urban environment requires for a specific approach to map urban SOC as part of regional analysis. 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

  7. Sequential provisional implant prosthodontics therapy.

    Science.gov (United States)

    Zinner, Ira D; Markovits, Stanley; Jansen, Curtis E; Reid, Patrick E; Schnader, Yale E; Shapiro, Herbert J

    2012-01-01

    The fabrication and long-term use of first- and second-stage provisional implant prostheses is critical to create a favorable prognosis for function and esthetics of a fixed-implant supported prosthesis. The fixed metal and acrylic resin cemented first-stage prosthesis, as reviewed in Part I, is needed for prevention of adjacent and opposing tooth movement, pressure on the implant site as well as protection to avoid micromovement of the freshly placed implant body. The second-stage prosthesis, reviewed in Part II, should be used following implant uncovering and abutment installation. The patient wears this provisional prosthesis until maturation of the bone and healing of soft tissues. The second-stage provisional prosthesis is also a fail-safe mechanism for possible early implant failures and also can be used with late failures and/or for the necessity to repair the definitive prosthesis. In addition, the screw-retained provisional prosthesis is used if and when an implant requires removal or other implants are to be placed as in a sequential approach. The creation and use of both first- and second-stage provisional prostheses involve a restorative dentist, dental technician, surgeon, and patient to work as a team. If the dentist alone cannot do diagnosis and treatment planning, surgery, and laboratory techniques, he or she needs help by employing the expertise of a surgeon and a laboratory technician. This team approach is essential for optimum results.

  8. Comparison between detailed digital and conventional soil maps of an area with complex geology

    Directory of Open Access Journals (Sweden)

    Osmar Bazaglia Filho

    2013-10-01

    Full Text Available Since different pedologists will draw different soil maps of a same area, it is important to compare the differences between mapping by specialists and mapping techniques, as for example currently intensively discussed Digital Soil Mapping. Four detailed soil maps (scale 1:10.000 of a 182-ha sugarcane farm in the county of Rafard, São Paulo State, Brazil, were compared. The area has a large variation of soil formation factors. The maps were drawn independently by four soil scientists and compared with a fifth map obtained by a digital soil mapping technique. All pedologists were given the same set of information. As many field expeditions and soil pits as required by each surveyor were provided to define the mapping units (MUs. For the Digital Soil Map (DSM, spectral data were extracted from Landsat 5 Thematic Mapper (TM imagery as well as six terrain attributes from the topographic map of the area. These data were summarized by principal component analysis to generate the map designs of groups through Fuzzy K-means clustering. Field observations were made to identify the soils in the MUs and classify them according to the Brazilian Soil Classification System (BSCS. To compare the conventional and digital (DSM soil maps, they were crossed pairwise to generate confusion matrices that were mapped. The categorical analysis at each classification level of the BSCS showed that the agreement between the maps decreased towards the lower levels of classification and the great influence of the surveyor on both the mapping and definition of MUs in the soil map. The average correspondence between the conventional and DSM maps was similar. Therefore, the method used to obtain the DSM yielded similar results to those obtained by the conventional technique, while providing additional information about the landscape of each soil, useful for applications in future surveys of similar areas.

  9. Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe.

    Science.gov (United States)

    Aksoy, Ece; Yigini, Yusuf; Montanarella, Luca

    2016-01-01

    Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because of playing key roles in the functions of both natural ecosystems and agricultural systems. There are several studies in the literature with the aim of finding the best method to assess and map the distribution of SOC content for Europe. Therefore this study aims searching for another aspect of this issue by looking to the performances of using aggregated soil samples coming from different studies and land-uses. The total number of the soil samples in this study was 23,835 and they're collected from the "Land Use/Cover Area frame Statistical Survey" (LUCAS) Project (samples from agricultural soil), BioSoil Project (samples from forest soil), and "Soil Transformations in European Catchments" (SoilTrEC) Project (samples from local soil data coming from six different critical zone observatories (CZOs) in Europe). Moreover, 15 spatial indicators (slope, aspect, elevation, compound topographic index (CTI), CORINE land-cover classification, parent material, texture, world reference base (WRB) soil classification, geological formations, annual average temperature, min-max temperature, total precipitation and average precipitation (for years 1960-1990 and 2000-2010)) were used as auxiliary variables in this prediction. One of the most popular geostatistical techniques, Regression-Kriging (RK), was applied to build the model and assess the distribution of SOC. This study showed that, even though RK method was appropriate for successful SOC mapping, using combined databases was not helpful to increase the statistical significance of the method results for assessing the SOC distribution. According to our results; SOC variation was mainly affected by elevation, slope, CTI, average temperature, average and total precipitation, texture, WRB and CORINE variables for Europe scale in our model. Moreover, the highest average SOC contents were found in the wetland areas; agricultural

  10. Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe.

    Directory of Open Access Journals (Sweden)

    Ece Aksoy

    Full Text Available Accuracy in assessing the distribution of soil organic carbon (SOC is an important issue because of playing key roles in the functions of both natural ecosystems and agricultural systems. There are several studies in the literature with the aim of finding the best method to assess and map the distribution of SOC content for Europe. Therefore this study aims searching for another aspect of this issue by looking to the performances of using aggregated soil samples coming from different studies and land-uses. The total number of the soil samples in this study was 23,835 and they're collected from the "Land Use/Cover Area frame Statistical Survey" (LUCAS Project (samples from agricultural soil, BioSoil Project (samples from forest soil, and "Soil Transformations in European Catchments" (SoilTrEC Project (samples from local soil data coming from six different critical zone observatories (CZOs in Europe. Moreover, 15 spatial indicators (slope, aspect, elevation, compound topographic index (CTI, CORINE land-cover classification, parent material, texture, world reference base (WRB soil classification, geological formations, annual average temperature, min-max temperature, total precipitation and average precipitation (for years 1960-1990 and 2000-2010 were used as auxiliary variables in this prediction. One of the most popular geostatistical techniques, Regression-Kriging (RK, was applied to build the model and assess the distribution of SOC. This study showed that, even though RK method was appropriate for successful SOC mapping, using combined databases was not helpful to increase the statistical significance of the method results for assessing the SOC distribution. According to our results; SOC variation was mainly affected by elevation, slope, CTI, average temperature, average and total precipitation, texture, WRB and CORINE variables for Europe scale in our model. Moreover, the highest average SOC contents were found in the wetland areas

  11. Application of mobile gamma-ray spectrometry for soil mapping

    Science.gov (United States)

    Werban, Ulrike; Lein, Claudia; Pohle, Marco; Dietrich, Peter

    2017-04-01

    Gamma-ray measurements have a long tradition for geological surveys and deposit exploration using airborne and borehole logging systems. For these applications, the relationships between the measured physical parameter - the concentration of natural gamma emitters 40K, 238U and 232Th - and geological origin or sedimentary developments are well described. Thus, Gamma-ray spectrometry seems a useful tool for carrying out spatial mapping of physical parameters related to soil properties. The isotope concentration in soils depends on different soil parameters (e.g. geochemical composition, grain size fractions), which are a result of source rock properties and processes during soil geneses. There is a rising interest in the method for application in Digital Soil Mapping or as input data for environmental, ecological or hydrological modelling, e.g. as indicator for clay content. However, the gamma-ray measurement is influenced by endogenous factors and processes like soil moisture variation, erosion and deposition of material or cultivation. We will present results from a time series of car borne gamma-ray measurements to observe heterogeneity of soil on a floodplain area in Central Germany. The study area is characterised by high variations in grain size distribution and occurrence of flooding events. For the survey, we used a 4 l NaI(Tl) detector with GPS connection mounted on a sledge, which is towed across the field sites by a four-wheel-vehicle. The comparison of data from different dates shows similar structures with small variation between the data ranges and shape of structures. We will present our experiences concerning the application of gamma-ray measurements under variable field conditions and their impacts on data quality.

  12. Seeing the soil through the net: an eye-opener on the soil map of the Flemish region (Belgium)

    Science.gov (United States)

    Dondeyne, Stefaan; Vanierschot, Laura; Langohr, Roger; Van Ranst, Eric; Deckers, Jozef; Oorts, Katrien

    2017-04-01

    A systematic soil survey of Belgium was conducted from 1948 to 1991. Field surveys were done at the detailed scale of 1:5000 with the final maps published at a 1:20,000 scale. The legend of these detailed soil maps (scale 1:20,000) has been converted to the 3rd edition of the international soil classification system 'World Reference Base for Soil Resources' (WRB). Over the last years, the government of the Flemish region made great efforts to make these maps, along with other environmental data, available to the general audience through the internet. The soil maps are widely used and consulted by researchers, teachers, land-use planners, environmental consultancy agencies and archaeologists. The maps can be downloaded and consulted in the viewer 'Visual Soil Explorer' ('Bodemverkenner'). To increase the legibility of the maps, we assembled a collection of photographs from soil profiles representing 923 soil types and 413 photos of related landscape settings. By clicking on a specific location in the 'Visual Soil Explorer', pictures of the corresponding soil type and landscape appear in a pop-up window, with a brief explanation about the soil properties. The collection of photographs of soil profiles cover almost 80% of the total area of the Flemish region, and include the 100 most common soil types. Our own teaching experience shows that these information layers are particular valuable for teaching soil geography and earth sciences in general. Overall, such visual information layers should contribute to a better interpretation of the soil maps and legacy soil data by serving as an eye-opener on the soil map to the wider community.

  13. GlobalSoilMap.net – a new digital soil map of the world

    NARCIS (Netherlands)

    Hartemink, A.E.; Hempel, J.; Lagacherie, P.; McBratney, A.B.; MacMillan, R.A.; Montanarella, L.; Sanchez, P.A.; Walsh, M.; Zhang, G.L.

    2010-01-01

    Knowledge of the world soil resources is fragmented and dated. There is a need for accurate, up-to-date and spatially referenced soil information as frequently expressed by the modelling community, farmers and land users, and policy and decision makers. This need coincides with an enormous leap in

  14. Soil Fertility Map for Food Legumes Production Areas in China.

    Science.gov (United States)

    Li, Ling; Yang, Tao; Redden, Robert; He, Weifeng; Zong, Xuxiao

    2016-05-23

    Given the limited resources of fossil energy, and the environmental risks of excess fertilizer on crops, it is time to reappraise the potential role of food legume biological nitrogen fixation (BNF) as sources of nitrogen for cropping systems in China. 150 soil samples across 17 provinces and 2 municipalities of China were collected and analyzed. A distribution map of the soil fertilities and their patterns of distribution was constructed. The pH results indicated that soils were neutral to slightly alkaline overall. The soil organic matter (SOM) and the available nitrogen (AN) content were relatively low, while the available phosphorus (AP) and available potassium (AK) contents were from moderate to high. Production areas of food legumes (faba bean, pea, adzuki bean, mung bean and common bean) were clearly separated into 4 soil fertility type clusters. In addition, regions with SOM, AN, AP and AK deficiency, high acidity and high alkalinity were listed as target areas for further soil improvement. The potential was considered for biological nitrogen fixation to substitute for the application of mineral nitrogen fertiliser.

  15. Soil Fertility Map for Food Legumes Production Areas in China

    Science.gov (United States)

    Li, Ling; Yang, Tao; Redden, Robert; He, Weifeng; Zong, Xuxiao

    2016-05-01

    Given the limited resources of fossil energy, and the environmental risks of excess fertilizer on crops, it is time to reappraise the potential role of food legume biological nitrogen fixation (BNF) as sources of nitrogen for cropping systems in China. 150 soil samples across 17 provinces and 2 municipalities of China were collected and analyzed. A distribution map of the soil fertilities and their patterns of distribution was constructed. The pH results indicated that soils were neutral to slightly alkaline overall. The soil organic matter (SOM) and the available nitrogen (AN) content were relatively low, while the available phosphorus (AP) and available potassium (AK) contents were from moderate to high. Production areas of food legumes (faba bean, pea, adzuki bean, mung bean and common bean) were clearly separated into 4 soil fertility type clusters. In addition, regions with SOM, AN, AP and AK deficiency, high acidity and high alkalinity were listed as target areas for further soil improvement. The potential was considered for biological nitrogen fixation to substitute for the application of mineral nitrogen fertiliser.

  16. Improvements on mapping soil liquefaction at a regional scale

    Science.gov (United States)

    Zhu, Jing

    Earthquake induced soil liquefaction is an important secondary hazard during earthquakes and can lead to significant damage to infrastructure. Mapping liquefaction hazard is important in both planning for earthquake events and guiding relief efforts by positioning resources once the events have occurred. This dissertation addresses two aspects of liquefaction hazard mapping at a regional scale including 1) predictive liquefaction hazard mapping and 2) post-liquefaction cataloging. First, current predictive hazard liquefaction mapping relies on detailed geologic maps and geotechnical data, which are not always available in at-risk regions. This dissertation improves the predictive liquefaction hazard mapping by the development and validation of geospatial liquefaction models (Chapter 2 and 3) that predict liquefaction extent and are appropriate for global application. The geospatial liquefaction models are developed using logistic regression from a liquefaction database consisting of the data from 27 earthquake events from six countries. The model that performs best over the entire dataset includes peak ground velocity (PGV), VS30, distance to river, distance to coast, and precipitation. The model that performs best over the noncoastal dataset includes PGV, VS30, water table depth, distance to water body, and precipitation. Second, post-earthquake liquefaction cataloging historically relies on field investigation that is often limited by time and expense, and therefore results in limited and incomplete liquefaction inventories. This dissertation improves the post-earthquake cataloging by the development and validation of a remote sensing-based method that can be quickly applied over a broad region after an earthquake and provide a detailed map of liquefaction surface effects (Chapter 4). Our method uses the optical satellite images before and after an earthquake event from the WorldView-2 satellite with 2 m spatial resolution and eight spectral bands. Our method

  17. Mapping uranium concentration in soil: Belgian experience towards a European map.

    Science.gov (United States)

    Cinelli, Giorgia; Tondeur, Francois; Dehandschutter, Boris; Bossew, Peter; Tollefsen, Tore; De Cort, Marc

    2017-01-01

    A map of uranium concentration in soil has been planned for the European Atlas of Natural Radiation. This Atlas is being developed by the Radioactivity Environmental Monitoring (REM) group of the Joint Research Centre (JRC) of the European Commission. The great interest in uranium compared to other terrestrial radionuclides stems from the fact that radon (222Rn) is in the decay chain of uranium (238U) and that public exposure to natural ionizing radiation is largely due to indoor radon. With several different databases available, including data (albeit not calibrated) from an airborne survey, Belgium is a favourable case for exploring the methodology of uranium mapping. A harmonized database of uranium in soil was built by merging radiological (not airborne) and geochemical data. Using this harmonized database it was possible to calibrate the data from the airborne survey. Several methods were used to perform spatial interpolation and to smooth the data: moving average without constraint, by soil class and by geological unit. When using the harmonized database, it is first necessary to evaluate the uranium concentration in areas without data or with an insufficient number of data points. Overall, there is a reasonable agreement between the maps on a 1 km × 1 km grid obtained with the two datasets (airborne U and harmonized soil U) with all the methods. The agreement is better when the maps are reduced to a 10 km × 10 km grid; the latter could be used for the European map of uranium concentration in soil. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  18. Mapping soil heterogeneity using RapidEye satellite images

    Science.gov (United States)

    Piccard, Isabelle; Eerens, Herman; Dong, Qinghan; Gobin, Anne; Goffart, Jean-Pierre; Curnel, Yannick; Planchon, Viviane

    2016-04-01

    In the frame of BELCAM, a project funded by the Belgian Science Policy Office (BELSPO), researchers from UCL, ULg, CRA-W and VITO aim to set up a collaborative system to develop and deliver relevant information for agricultural monitoring in Belgium. The main objective is to develop remote sensing methods and processing chains able to ingest crowd sourcing data, provided by farmers or associated partners, and to deliver in return relevant and up-to-date information for crop monitoring at the field and district level based on Sentinel-1 and -2 satellite imagery. One of the developments within BELCAM concerns an automatic procedure to detect soil heterogeneity within a parcel using optical high resolution images. Such heterogeneity maps can be used to adjust farming practices according to the detected heterogeneity. This heterogeneity may for instance be caused by differences in mineral composition of the soil, organic matter content, soil moisture or soil texture. Local differences in plant growth may be indicative for differences in soil characteristics. As such remote sensing derived vegetation indices may be used to reveal soil heterogeneity. VITO started to delineate homogeneous zones within parcels by analyzing a series of RapidEye images acquired in 2015 (as a precursor for Sentinel-2). Both unsupervised classification (ISODATA, K-means) and segmentation techniques were tested. Heterogeneity maps were generated from images acquired at different moments during the season (13 May, 30 June, 17 July, 31 August, 11 September and 1 November 2015). Tests were performed using blue, green, red, red edge and NIR reflectances separately and using derived indices such as NDVI, fAPAR, CIrededge, NDRE2. The results for selected winter wheat, maize and potato fields were evaluated together with experts from the collaborating agricultural research centers. For a few fields UAV images and/or yield measurements were available for comparison.

  19. Utilizing soil polypedons to improve model performance for digital soil mapping

    Science.gov (United States)

    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...

  20. Digital Mapping of Soil Texture Using Regression Tree and Artificial Neural Network in Bijar, Kurdistan

    OpenAIRE

    kamal nabiollahi; ahmad haidari; rohollah taghizade mehrjardi

    2015-01-01

    Soil texture is an important soil physical property that governs most physical, chemical, biological, and hydrological processes in soils. Detailed information on soil texture variability is crucial for proper crop and land management and environmental studies. Therefore, at present research, 103 soil profiles were dogged and then sampled in order to prepare digital map of soil texture in Bijar, Kurdistan. Auxiliary data used in this study to represent predictive soil forming factors were ter...

  1. Mapping soils in two watersheds using legacy data and extrapolation for similar surrounding areas

    Directory of Open Access Journals (Sweden)

    Marcelo Henrique Procópio Pelegrino

    Full Text Available ABSTRACT Existing soil maps (legacy data associated with digital mapping techniques are alternatives to obtain information at lower costs, however, tests are required to do it more efficiently. This study had as objectives to compare different methods to extract information from detailed scale soil maps using decision trees for mapping soil classes at two watersheds in Minas Gerais, validate these maps in the field and use the best method to extrapolate information to larger areas, also validating these maps of larger areas. Detailed soil maps of Vista Bela creek (VBW and Marcela creek (MCW watersheds were used as source of information. Seven methods to extract information from maps were compared: the whole polygon, eliminating 20 and 40 m from the polygon boundaries, and with buffers around the sampled points with radii of 25 m, 50 m, 75 m, and 100 m. The Classification and Regression Trees (CART algorithm was employed to create decision trees and enable creation of soil maps. Accuracy was assessed through overall accuracy and kappa index. The best method was used to extrapolate information to larger areas and maps were validated. The best methods for VCW and MCW were, respectively, eliminating 20 m from polygon edges and buffer of 25 m of radii from points. Maps for larger areas were obtained using these methods. Removing uncertainty areas from legacy soil maps contribute to better modeling and prediction of soil classes. Information generated in this work allowed for validated extrapolation of soil maps for regions surrounding the watersheds.

  2. Mapping the Soil Texture in the Heihe River Basin Based on Fuzzy Logic and Data Fusion

    Directory of Open Access Journals (Sweden)

    Ling Lu

    2017-07-01

    Full Text Available Mapping soil texture in a river basin is critically important for eco-hydrological studies and water resource management at the watershed scale. However, due to the scarcity of in situ observation of soil texture, it is very difficult to map the soil texture in high resolution using traditional methods. Here, we used an integrated method based on fuzzy logic theory and data fusion to map the soil texture in the Heihe River basin in an arid region of Northwest China, by combining in situ soil texture measurement data, environmental factors, a previous soil texture map, and other thematic maps. Considering the different landscape characteristics over the whole Heihe River basin, different mapping schemes have been used to extract the soil texture in the upstream, middle, and downstream areas of the Heihe River basin, respectively. The validation results indicate that the soil texture map achieved an accuracy of 69% for test data from the midstream area of the Heihe River basin, which represents a much higher accuracy than that of another existing soil map in the Heihe River basin. In addition, compared with the time-consuming and expensive traditional soil mapping method, this new method could ensure greater efficiency and a better representation of the explicitly spatial distribution of soil texture and can, therefore, satisfy the requirements of regional modeling.

  3. Soil organic carbon mapping of partially vegetated agricultural fields with imaging spectroscopy

    NARCIS (Netherlands)

    Bartholomeus, H.; Kooistra, L.; Stevens, A.; Leeuwen, van M.; Wesemael, van B.; Ben-Dor, E.; Tychon, B.

    2011-01-01

    Soil Organic Carbon (SOC) is one of the key soil properties, but the large spatial variation makes continuous mapping a complex task. Imaging spectroscopy has proven to be an useful technique for mapping of soil properties, but the applicability decreases rapidly when fields are partially covered

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

    Science.gov (United States)

    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...

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

    Science.gov (United States)

    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...

  6. Mapping soil resistance under different soil water content conditions using indicator kriging

    Science.gov (United States)

    Miras-Avalos, J. M.; Bonnin-Acosta, J.; Sande-Fouz, P.; Pereira-Lanças, K.; Paz-Gonzalez, A.

    2009-04-01

    In many agricultural problems, it is of interest to map the zones where the variable under study shows the probability of being greater than a threshold value. Soil resistances higher than 2 MPa might difficult the establishment of cultures; therefore, further management or tillage techniques should be undertaken. The aim of this work was to map soil resistance using geostatistical techniques, therefore, an analysis of the spatial distribution of soil compaction and the influence of soil water content on the resistance to penetration was carried out. The studied clay-textured soil was managed under no-tillage practices. Soil resistance was described by the cone index which was obtained using a penetrometer. This attribute was assessed at 5 different depths, i.e. 0-10 cm, 10-20 cm, 20-30 cm, 30-40 cm and deeper than 40 cm, whereas soil water content was described at 0-20 cm and 20-40 cm. In the end, 73 data points were surveyed. Soil water conditions varied during the five different samplings. Statistical analysis showed that datasets followed a normal distribution, therefore, no transformation was required. Studied attributes showed low and non-significant correlation coefficients which impeded the application of cross-variogram and cokriging techniques. Because of the limited number of measured data, only the omnidirectional semivariogram was computed, and hence the spatial variability is assumed to be identical in all directions. Spatial dependence was observed in 33 out of 35 data series, both for cone index and soil water content. Fitted theoretical structures corresponded to exponential models in 20 cases, 10 Gaussian models and 3 spherical models. Nugget effect varied from 0 to 44.4 depending on the dataset and spatial dependence maximum range was 90 m. A strong spatial dependence was observed in 18 of the data sets whereas only 2 showed a weak autocorrelation. Taking into account the 2 MPa threshold, indicator kriging was used to map the soil resistance

  7. Soil map disaggregation improved by soil-landscape relationships, area-proportional sampling and random forest implementation

    DEFF Research Database (Denmark)

    Møller, Anders Bjørn; Malone, Brendan P.; Odgers, Nathan

    algorithm were evaluated. The resulting maps were validated on 777 soil profiles situated in a grid covering Denmark. The experiments showed that the results obtained with Jacobsen’s map were more accurate than the results obtained with the CEC map, despite a nominally coarser scale of 1:2,000,000 vs. 1...... of European Communities (CEC, 1985) respectively, both using the FAO 1974 classification. Furthermore, the effects of implementing soil-landscape relationships, using area proportional sampling instead of per polygon sampling, and replacing the default C5.0 classification tree algorithm with a random forest......:1,000,000. This finding is probably related to the fact that Jacobsen’s map was more detailed with a larger number of polygons, soil map units and soil types, despite its coarser scale. The results showed that the implementation of soil-landscape relationships, area-proportional sampling and the random forest...

  8. GIS and geotechnical mapping of expansive soil in Toshka region

    Directory of Open Access Journals (Sweden)

    Mary Labib

    2013-09-01

    Full Text Available This paper presents the results of a subsurface site investigation that was performed to characterize different soil and rock formations along Sheikh Zayed canal with particular emphasis on the swelling characteristics of the clays in that area. Site-specific empirical correlations were developed to predict the clay swelling potential and pressure from simple and economic laboratory test results. The data were input into a Geographic Information System (GIS framework to provide interactive maps that show the spatial distribution of the variables and identify their characteristics. These maps are then used to easily identify the values of swelling pressure/potential at various locations. This research provides a tool that is based on simple index tests that can be used to provide data that otherwise would require elaborate and costly investigations; the GIS framework allows storing, retrieving and updating these data easily to assist taking supported decisions dynamically.

  9. Converting the legend of the Soil Map of Belgium into the World Reference Base for Soil Resources: Strenght and constraints of using WRB as a map legend

    OpenAIRE

    Dondeyne, Stefaan; Bouhon, Antoine; Legrain, Xavier

    2012-01-01

    Within the European Union, there is a general interest to prepare joint soil maps at a 1:250000 scale in order to harmonise agricultural and environmental policies. The World Reference Base for Soil Resources (WRB) has been adopted as the common soil classification system within the EU. As soil surveys in most member states were conducted independently, the challenge is now to convert the national legends into a common WRB legend. Based on our experiences from converting the le...

  10. Validating a high-resolution digital soil map for precision agriculture across multiple fields

    Science.gov (United States)

    Digital soil mapping (DSM) for precision agriculture (PA) management is aimed at developing models that predict soil properties or classes using legacy soil data, sensors, and environmental covariates. The utility of DSM for PA is based on its ability to provide useful spatial soil information for o...

  11. LBA-ECO CD-06 Soil Classification Map, Ji-Parana River Basin, Rondonia, Brazil

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides a digital map of soil orders for the Ji-Parana River Basin, in the state of Rondonia, Brazil (Western Amazonia). Soil orders were manually...

  12. LBA-ECO CD-06 Soil Classification Map, Ji-Parana River Basin, Rondonia, Brazil

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set provides a digital map of soil orders for the Ji-Parana River Basin, in the state of Rondonia, Brazil (Western Amazonia). Soil orders were...

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

    Science.gov (United States)

    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

  14. Mapping the Soil Texture in the Heihe River Basin Based on Fuzzy Logic and Data Fusion

    OpenAIRE

    Ling Lu; Chao Liu; Xin Li; Youhua Ran

    2017-01-01

    Mapping soil texture in a river basin is critically important for eco-hydrological studies and water resource management at the watershed scale. However, due to the scarcity of in situ observation of soil texture, it is very difficult to map the soil texture in high resolution using traditional methods. Here, we used an integrated method based on fuzzy logic theory and data fusion to map the soil texture in the Heihe River basin in an arid region of Northwest China, by combining in situ soil ...

  15. Use of pedological maps in the identification of sensitivity of soils to acidic deposition: application to Brazilian soils

    Directory of Open Access Journals (Sweden)

    Melfi Adolpho J.

    2004-01-01

    Full Text Available The pedogeochemical maps present the spatial distribution of soils according to crystalochemical parameters (clay fraction and physic-chemical aspects of the sorting complex (CEC and BS. These maps are adequate tool for environmental studies and particularly, for the analysis of the terrestrial ecosystem sensibility to acidic deposition. The pedogeochemical maps of the Brazilian soils, elaborated using FAO SoilWorld Map, allowed establishing the soil distribution according to 5 classes of vulnerability to acidic deposition, as defined by Stockholm Environmental Institute (SEI. From these maps, it is observed that about 50% of the Brazilian soils are high vulnerable to acidic deposition and can be included within the most sensitive class. This group is formed by well-developed and mature soils, constituted by clay minerals of kaolinite type associated with variable amount of gibbsite. About 8% of the soils can be considered as the least sensitive class. They correspond to Topomorphic Vertisols (Vertissolo, Embrapa 1999, Planosols (Planossolo, Embrapa 1999 and saline soils. Finally, the remaining soils represent the balanced media that dominate the northeastern semiarid zones and the south and northeastern subtropical zones.

  16. Automated soil resources mapping based on decision tree and Bayesian predictive modeling.

    Science.gov (United States)

    Zhou, Bin; Zhang, Xin-Gang; Wang, Ren-Chao

    2004-07-01

    This article presents two approaches for automated building of knowledge bases of soil resources mapping. These methods used decision tree and Bayesian predictive modeling, respectively to generate knowledge from training data. With these methods, building a knowledge base for automated soil mapping is easier than using the conventional knowledge acquisition approach. The knowledge bases built by these two methods were used by the knowledge classifier for soil type classification of the Longyou area, Zhejiang Province, China using TM bi-temporal imageries and GIS data. To evaluate the performance of the resultant knowledge bases, the classification results were compared to existing soil map based on field survey. The accuracy assessment and analysis of the resultant soil maps suggested that the knowledge bases built by these two methods were of good quality for mapping distribution model of soil classes over the study area.

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

    Science.gov (United States)

    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

  18. MODIFICATIONS ON THE SOILS MAP OF VINGA PLAIN DUE TO THE APPLICATION OF THE ROMANIAN SYSTEM OF SOIL TAXONOMY (RSST

    Directory of Open Access Journals (Sweden)

    C. Grigoras

    2005-10-01

    Full Text Available The Vinga Plain, a unit of the Banato – Crişane Plain, is a piedmont terrace plain covered by a thick layer of loess and loess-like deposits. The soil cover belongs to seven classes and many soil types and sub-types. The utilization of the Romanian System of Soil Taxonomy new criteria of classification brought to the modification of most of the soils names, to the change of certain soils from one class to another or to the appearance of new types and subtypes. The modifications on the soils map are more important than these modifications. Here, some soil units were included in other units (the former alluvial gleyic soils are now to be found in the Fluvisols class or there appeared new units due to the separation of new soil types and sub-types (the former units of the illuvial clay chernozems were sheared between argic chernozems and argic phaeozems.

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

    Science.gov (United States)

    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

  20. Potential and limitations of using soil mapping information to understand landscape hydrology

    Directory of Open Access Journals (Sweden)

    F. Terribile

    2011-12-01

    Full Text Available This paper addresses the following points: how can whole soil data from normally available soil mapping databases (both conventional and those integrated by digital soil mapping procedures be usefully employed in hydrology? Answering this question requires a detailed knowledge of the quality and quantity of information embedded in and behind a soil map.

    To this end a description of the process of drafting soil maps was prepared (which is included in Appendix A of this paper. Then a detailed screening of content and availability of soil maps and database was performed, with the objective of an analytical evaluation of the potential and the limitations of soil data obtained through soil surveys and soil mapping. Then we reclassified the soil features according to their direct, indirect or low hydrologic relevance. During this phase, we also included information regarding whether this data was obtained by qualitative, semi-quantitative or quantitative methods. The analysis was performed according to two main points of concern: (i the hydrological interpretation of the soil data and (ii the quality of the estimate or measurement of the soil feature.

    The interaction between pedology and hydrology processes representation was developed through the following Italian case studies with different hydropedological inputs: (i comparative land evaluation models, by means of an exhaustive itinerary from simple to complex modelling applications depending on soil data availability, (ii mapping of soil hydrological behaviour for irrigation management at the district scale, where the main hydropedological input was the application of calibrated pedo-transfer functions and the Hydrological Function Unit concept, and (iii flood event simulation in an ungauged basin, with the functional aggregation of different soil units for a simplified soil pattern.

    In conclusion, we show that special care is required in handling data from soil

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

    Science.gov (United States)

    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.

  2. COMBINING PROXIMAL AND PENETRATING CONDUCTIVITY SENSORS FOR HIGH RESOLUTION SOIL MAPPING

    Science.gov (United States)

    Proximal ground conductivity sensors produce a high spatial resolution map that integrates the bulk electrical conductivity (ECa) of the soil profile. Variability in the conductivity map must either be inverted to estimate profile conductivity, or be directly calibrated to soil profile properties fo...

  3. Mapping natural radioactivity of soils in the eastern Canary Islands.

    Science.gov (United States)

    Arnedo, M A; Rubiano, J G; Alonso, H; Tejera, A; González, A; González, J; Gil, J M; Rodríguez, R; Martel, P; Bolivar, J P

    2017-01-01

    The Canary Islands archipielago (Spain) comprises seven main volcanic islands and several islets that form a chain extending for around 500 km across the eastern Atlantic, between latitudes 27°N and 30°N, with its eastern edge only 100 km from the NW African coast. The administrative province of Las Palmas comprises the three eastern Canary Islands (Lanzarote, Fuerteventura and Gran Canaria). An extensive study of terrestrial gamma dose rates in surface soils has been carried out to cover the entire territory of the province (4093 km2). The average outdoor gamma dose rate in air at 1 m above ground is 73 nGyh-1 at Gran Canaria, 32 nGyh-1 at Fuerteventura, and 25 nGyh-1 at Lanzarote. To complete the radiological characterization of this volcanic area, 350 soil samples at 0-5 cm depth were collected to cover all the geologic typologies of the islands. These samples were measured using high resolution gamma spectrometry to determine the activity concentrations of 226Ra, 232Th and 40K. The average values obtained were 25.2 Bq/kg, 28.9 Bq/kg, and 384.4 Bq/kg, respectively. Maps of terrestrial gamma activity, effective dose, and activity concentrations of 226Ra, 232Th and 40K for the region have been developed through the use of geostatistical interpolation techniques. These maps are in accord with the geology of the islands. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Probability mapping of iron pan presence in sandy podzols in South-West France, using digital soil mapping.

    NARCIS (Netherlands)

    Richer-de-Forges, Anne C.; Saby, Nicolas P.A.; Mulder, V.L.; Larochea, B.; Arrouaysa, B.; Arrouaysa, D.

    2017-01-01

    This work evaluated two different digital soil mapping methods for mapping the presence of iron pans in South-West France. The presence of iron pans limit rooting depth, thereby affecting available water content for plants and increasing vulnerability of trees to storms. In some cases, it may also

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

    Science.gov (United States)

    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.

  6. Validating a digital soil map with corn yield data for precision agriculture decision support

    Science.gov (United States)

    Variability in soil and landscape characteristics is known to challenge producers in implementing site-specific crop management strategies in precision agriculture (PA). There are growing numbers of digital soil mapping (DSM) procedures that build upon traditional soil survey information by employin...

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

    Science.gov (United States)

    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.

  8. GIS-based production of digital soil map for Nigeria | Nkwunonwo ...

    African Journals Online (AJOL)

    Soil, a valuable natural resource can be said to play a part across the range of human existence and its knowledge is fundamental to its utilization and management. Soil maps provide a means of gaining understanding about the soil, but limitations in accuracy, revision and mode of presentation– relating to graphics or ...

  9. Supplementing predictive mapping of acid sulfate soil occurrence with Vis-NIR spectroscopy

    DEFF Research Database (Denmark)

    Beucher, Amélie; Peng, Yi; Knadel, Maria

    . Recently, a digital soil mapping approach was assessed to create a predictive map for potential acid sulfate soil occurrence in the wetlands of Jutland (c. 6500 km2; Beucher et al., 2016). An Artificial Neural Networks method was applied using 8000 soil observations and 16 environmental variables...... diagnostic features for hydroxides, clay minerals, iron oxides and iron sulfates which are typically present in acid sulfate soils (Shi et al., 2014). Soil spectroscopy may thus efficiently supplement the mapping of acid sulfate soil occurrence. The present study aims at predicting acid sulfate soil...... instrument (Peng et al., 2015). The spectral data were summarized using principal component analysis (PCA). The first two principal components (PC) explained 99% of the variability in the spectra. Kriging was applied to upgrade PC scores information from point to image scale for further use within the acid...

  10. Updating the 1:50,000 Dutch soil map using legacy soil data: A multinomial logistic regression approach

    NARCIS (Netherlands)

    Kempen, B.; Brus, D.J.; Heuvelink, G.B.M.; Stoorvogel, J.J.

    2009-01-01

    The 1:50,000 national soil survey of the Netherlands, completed in the early 1990s after more than three decades of mapping, is gradually becoming outdated. Large-scale changes in land and water management that took place after the field surveys have had a great impact on the soil. Especially

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

    Science.gov (United States)

    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...

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

    Science.gov (United States)

    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

  13. Soil erodibility mapping using three approaches in the Tangiers province –Northern Morocco

    Directory of Open Access Journals (Sweden)

    Hamza Iaaich

    2016-09-01

    Full Text Available Soil erodibility is a key factor in assessing soil loss rates. In fact, soil loss is the most occurring land degradation form in Morocco, affecting rural and urban vulnerable areas. This work deals with large scale mapping of soil erodibility using three mapping approaches: (i the CORINE approach developed for Europe by the JRC; (ii the UNEP/FAO approach developed within the frame of the United Nations Environmental Program for the Mediterranean area; (iii the Universal Soil Loss Equation (USLE K factor. Our study zone is the province of Tangiers, North-West of Morocco. For each approach, we mapped and analyzed different erodibility factors in terms of parent material, topography and soil attributes. The thematic maps were then integrated using a Geographic Information System to elaborate a soil erodibility map for each of the three approaches. Finally, the validity of each approach was checked in the field, focusing on highly eroded areas, by confronting the estimated soil erodibility and the erosion state as observed in the field. We used three statistical indicators for validation: overall accuracy, weighted Kappa factor and omission/commission errors. We found that the UNEP/FAO approach, based principally on lithofacies and topography as mapping inputs, is the most adapted for the case of our study zone, followed by the CORINE approach. The USLE K factor underestimated the soil erodibility, especially for highly eroded areas.

  14. Test of Regional Calibrations for a NIRS Soil Mapping System

    Science.gov (United States)

    Near infrared spectroscopy (NIRS) is an effective technique for simultaneously measuring several soil properties including soil organic carbon, total nitrogen, moisture, and cation exchange capacity. However, developing robust calibration models for predicting soil properties from spectral measureme...

  15. Evaluation of automated global mapping of Reference Soil Groups of WRB2015

    Science.gov (United States)

    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

  16. Understanding Americans: a focus on the transition from traditional to digital soil mapping

    Science.gov (United States)

    Miller, Bradley; Brevik, Eric; Fenton, Thomas; Homburg, Jeffrey

    2017-04-01

    The USA has had arguably the strongest and certainly the most extensive soil mapping program in the world. Yet many of the developments in digital soil mapping (DSM) occurred outside the USA from the late 1970s through the 1990s. This presentation attempts to explore why the USA has differed from many of the international trends in DSM. Much of the work on DSM in the USA has focused on the extraction of expert knowledge to formulate spatial prediction models for soil classes. Although DSM approaches are quickly evolving in American academia, the adoption of DSM methods have been slow and cautious in the National Cooperative Soil Survey (NCSS) mapping efforts. The great majority of soil maps available in the USA are digitized maps that were originally produced by traditional methods with some manual updating. Work attempting to implement more DSM techniques in the NCSS has been underway in select areas of California, Minnesota, Utah, Texas, and Wyoming. However, the only official NCSS product considered to be fully DSM-based thus far is in Essex County, Vermont. It is noteworthy that the Essex County Soil Survey map is still heavily dependent upon expert knowledge. Why the attachment to expert knowledge as opposed to data mining techniques for identifying new patterns in soil variability? We argue that this is because of the exceptional soil maps that were produced for the USA using traditional methods. Despite the limitations of traditional methods, it is difficult to improve upon the amount of field investigation and verification done to create the existing NCSS maps. Along with that comes a deep attachment to soil series as map units and all the data associated with those soil series.

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

    Science.gov (United States)

    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.

  18. Soil type mapping using the generalised linear geostatistical model: A case study in a Dutch cultivated peatland

    NARCIS (Netherlands)

    Kempen, B.; Brus, D.J.; Heuvelink, G.B.M.

    2012-01-01

    We present the generalised linear geostatistical model (GLGM) for soil type mapping and investigate if spatial prediction with this model results in a soil map of greater accuracy than a map obtained using a non-spatial model, i.e. a model that ignores spatial dependence in the soil type variable.

  19. 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.

    Science.gov (United States)

    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.

  20. Mapping acid sulfate soils in Denmark using legacy data and LiDAR-based derivatives

    DEFF Research Database (Denmark)

    Beucher, A; Adhikari, K; Breuning-Madsen, Henrik

    2017-01-01

    drainage of areas classified as potential a.s. soilswithout prior permission fromenvironmental authorities. Themapping of these soils was first conducted in the 1980’s.Wetlands, inwhich Danish potential a.s. soils mostly occur,were targeted and the soilswere surveyed through conventional mapping...... of environmental variables. The overall prediction accuracy based on a 30% hold-back validation data reached 70%. Furthermore, the conventional map indicated 32% of the study area (c. 2100 km2) as having a high frequency for potential a.s. soils while the digital map displayed about 46% (c. 3000 km2) as high......Leaching large amounts of acidity and metals into recipient watercourses and estuaries, acid sulfate (a.s.) soils constitute a substantial environmental issue worldwide. Mapping of these soils enables measures to be taken to prevent pollution in high risk areas. In Denmark, legislation prohibits...

  1. Soil mapping and classification: a case study in the Tigray Region, Ethiopia

    Directory of Open Access Journals (Sweden)

    Ahmed Harb Rabia

    2013-06-01

    Full Text Available Soil map is one of the basic tools in any agricultural development planning and generating a digital one is even more effective and more productive for natural resources evaluation. Moreover, remote sensing and GIS have added to soil classification different concept and enforcement. The study aim was to produce digital soil maps for the study area following different classification systems (ST and WRB and to define the spatial distribution and characteristics all the soil classes in the study area, which will be indispensable for future development planning. This work has been done as a part of the 29th Course Professional Master in IAO institution, Florence, Italy. The study area was Kilte Awulaelo district in Tigray region, Ethiopia, Which is characterized by different topographies and geomorphologies with different agro ecological conditions. Eleven main soil groups and sixty soil types were identified in the study area. The main soil groups are: Leptosols, Vertisols, Fluvisols, Stagnosols, Kastanozems, Phaeozems, Calcisols, Luvisols, Arenosols, Cambisols and Regosols.  Regosols and Cambisols are the dominant soils in the study area which is characteristic soils of rainfed agriculture and land affected by erosion. Using spatial distribution map of each soil group was very helpful to connect soil characteristics with soil forming factors. Lastly, GIS and remote sensing were very effective tools in this study and gave higher value for the final study results.

  2. Soil mapping and classification in the Alps: Current state and future challenges

    Science.gov (United States)

    Baruck, Jasmin; Gruber, Fabian; Geitner, Clemens

    2014-05-01

    Soil is an essential, non-renewable resource, which fundamentally needs sustainable management. Soils in mountain regions like the Alps have a diverse small-scale distribution and they are characterized by a slow soil development and multilayer profiles. This is mainly caused by high process dynamics and harsh climate conditions. Therefore, soils are particularly vulnerable and require a sustainable management approach. Furthermore, the global change, especially the climate and land use change, leads to new demands on the soil. Thus, high-resolution spatial informations on soil properties are required to protect this resource and to consider its properties in spatial planning and decision making. In the Alpine region soil maps are mostly confined to small (mostly agriculture) areas. Especially, in higher altitudes of the Alps pedologic research and data collection are lacking. However, nowadays and in the future systematic soil mapping works are and will be no longer applied. Another methodical problem arises because each Alpine country has its own national soil mapping and classification system which are not adapted to Alpine areas. Therefore, appropriate methods of working practices for the Alpine region are mostly missing. The central aim of the research project "ReBo - Terrain Classification based on airborne laser scanning data to support soil mapping in the Alps", founded by the Autonomous Province of Bolzano - South Tyrol, is to develop and verify a concept, which allows the collection of soil data through an optimized interaction of soil mapping and geomorphometric analysis. The test sites are located in South Tyrol (Italy). The workflow shall minimise the required pedologic field work and shall provide a reliable strategy for transferring punctual soil informations into spatial soil maps. However, for a detailed analysis a systematic pedologic field work is still indispensable. As in the Alps reliable soil mapping and classification standards are lacking

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

    Science.gov (United States)

    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

  4. Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

    Directory of Open Access Journals (Sweden)

    Waldir de Carvalho Junior

    2014-06-01

    Full Text Available Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR and geostatistical (ordinary kriging and co-kriging. The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap. Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI, soil wetness index (SWI, normalized difference vegetation index (NDVI, and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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 (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

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

    Directory of Open Access Journals (Sweden)

    De-Cai Wang

    Full Text Available 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.

  8. Constructing a Soil Class Map of Denmark based on the FAO Legend Using Digital Techniques

    DEFF Research Database (Denmark)

    Adhikari, Kabindra; Minasny, Budiman; Greve, Mette Balslev

    2014-01-01

    on sandy parent material, whereas eastern Denmark mostly contained Luvisols developed on loamy basal till. The occurrence of the predicted soil groups was assigned using several variables, of the most important was clay content in the topsoil and subsoil, elevation, geology and landscape type. The overall......) confirmed that the output is reliable and can be used in various soil and environmental studies without major difficulties. This study also verified the importance of GlobalSoilMap products and a priori pedological information that improved prediction performance and quality of the new FAO soil map...

  9. A preliminary bioavailable strontium isotope soil map of Europe.

    Science.gov (United States)

    Hoogewerff, Jurian; Reimann, Clemens; Ueckermann, Henriette; Frei, Robert; Frei, Karin; van Aswegen, Thalita; Stirling, Claudine; Reid, Malcolm; Clayton, Aaron; Gemas Project Team

    2017-04-01

    The GEMAS project collected samples from grazing land (n=2118, 0-20cm depth) and agricultural soil (n=2211, 0-10cm depth) at a scale of 1 site/2500km2 in most of Europe1. Elemental analysis using different extractions (Aqua Regia and MMI), whole soil XRF data and Q-ICPMS lead isotope data have been published1. Here we report high-precision 87Sr/86Sr results for the first 1000+ samples. To best represent Sr in plants and animals an ammonium nitrate soil extraction was chosen2. Samples were measured in three laboratories and shared QC samples demonstrated the robustness of the complete extraction and measurement protocol. Observed 87Sr/86Sr values range from 0.7038 to 0.7597 with the majority of samples centring about the median of 0.7092. Spatial interpolation of the data shows some major trends over Europe with high 87Sr/86Sr in known old intrusive terrains in Scandinavia, Iberia and the Alps. To improve the spatial resolution we investigated relations between measured 87Sr/86Sr values and other parameters for which higher spatial density (interpolated) data exists in geological and lithological databases like IGME50003 and GLiM4. For each sampling site matching geological age data and lithology were obtained by overlaying sampling locations on the IGME5000 and GLiM maps and extracting age and lithology information. All statistical and geospatial manipulations were performed using the R statistical package. Overall the 87Sr/86Sr values show a moderate correlation (Pearson R=0.54) with age but demonstrate varying homogeneity in different lithological units. Within the GEMAS dataset the strontium isotope ratios correlate most strongly with the lead isotope results,206Pb/208Pb (R=0.56) indicating a combined age and "crustalinity" effect. Whole soil Rb (XRF) is slightly higher correlated (R=0.26) with 87Sr/86Sr than extracted Rb (AR) at R=0.12 indicating some influence of the long term Rb signal in the soil parent material. Sodium is the highest correlated whole soil

  10. Applying Nitrogen Site-Specifically Using Soil Electrical Conductivity Maps and Precision Agriculture Technology

    Directory of Open Access Journals (Sweden)

    E.D. Lund

    2001-01-01

    Full Text Available Soil texture varies significantly within many agricultural fields. The physical properties of soil, such as soil texture, have a direct effect on water holding capacity, cation exchange capacity, crop yield, production capability, and nitrogen (N loss variations within a field. In short, mobile nutrients are used, lost, and stored differently as soil textures vary. A uniform application of N to varying soils results in a wide range of N availability to the crop. N applied in excess of crop usage results in a waste of the grower’s input expense, a potential negative effect on the environment, and in some crops a reduction of crop quality, yield, and harvestability. Inadequate N levels represent a lost opportunity for crop yield and profit. The global positioning system (GPS-referenced mapping of bulk soil electrical conductivity (EC has been shown to serve as an effective proxy for soil texture and other soil properties. Soils with a high clay content conduct more electricity than coarser textured soils, which results in higher EC values. This paper will describe the EC mapping process and provide case studies of site-specific N applications based on EC maps. Results of these case studies suggest that N can be managed site-specifically using a variety of management practices, including soil sampling, variable yield goals, and cropping history.

  11. Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management.

    Science.gov (United States)

    Erskine, Robert H; Sherrod, Lucretia A; Green, Timothy R

    2017-09-12

    Spatial patterns of soil erosion and deposition can be inferred from differences in ground elevation mapped at appropriate time increments. Such changes in elevation are related to changes in near-surface soil carbonate (CaCO3) profiles. The objective is to describe a simple conceptual model and detailed protocol for repeatable field and laboratory measurements of these quantities. Here, accurate elevation is measured using a ground-based differential global positioning system (GPS); other data acquisition methods could be applied to the same basic method. Soil samples are collected from prescribed depth intervals and analyzed in the lab using an efficient and precise modified pressure-calcimeter method for quantitative analysis of inorganic carbon concentration. Standard statistical methods are applied to point data, and representative results show significant correlations between changes in soil surface layer CaCO3 and changes in elevation consistent with the conceptual model; CaCO3 generally decreased in depositional areas and increased in erosional areas. Maps are derived from point measurements of elevation and soil CaCO3 to aid analyses. A map of erosional and depositional patterns at the study site, a rain-fed winter wheat field cropped in alternating wheat-fallow strips, shows the interacting effects of water and wind erosion affected by management and topography. Alternative sampling methods and depth intervals are discussed and recommended for future work relating soil erosion and deposition to soil CaCO3.

  12. 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

    Science.gov (United States)

    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

  13. MAPSS: Mapped Atmosphere-Plant-Soil System Model, Version 1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: MAPSS (Mapped Atmosphere-Plant-Soil System) is a landscape to global vegetation distribution model that was developed to simulate the potential biosphere...

  14. LBA-ECO LC-08 Soil, Vegetation, and Land Cover Maps for Brazil and South America

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides (1) soil maps for Brazil that are digital versions of the MAPA DE SOLOS DO BRASIL (EMBRAPA, 1981) classified at three levels of detail,...

  15. MAPSS: Mapped Atmosphere-Plant-Soil System Model, Version 1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — MAPSS (Mapped Atmosphere-Plant-Soil System) is a landscape to global vegetation distribution model that was developed to simulate the potential biosphere impacts and...

  16. Mapping soil carbon stocks of Central Africa using SOTER

    NARCIS (Netherlands)

    Batjes, N.H.

    2008-01-01

    Little is known about the soil carbon stocks of Central Africa although such baseline data are needed for research and policy development on soil carbon changes. Estimates are presented based on a 1:2 million scale soil and terrain (SOTER) database for Burundi, the Democratic Republic of Congo, and

  17. Creating a conceptual hydrological soil response map for the ...

    African Journals Online (AJOL)

    The soil water regime is a defining ecosystem service, directly influencing vegetation and animal distribution. Therefore the understanding of hydrological processes is a vital building block in managing natural ecosystems. Soils contain morphological indicators of the water flow paths and rates in the soil profile, which are ...

  18. Creating a conceptual hydrological soil response map for the ...

    African Journals Online (AJOL)

    2014-03-03

    Mar 3, 2014 ... The soil water regime is a defining ecosystem service, directly influencing vegetation and animal distribution. Therefore the understanding of hydrological processes is a vital building block in managing natural ecosystems. Soils contain morphological indicators of the water flow paths and rates in the soil ...

  19. VSRR Provisional Drug Overdose Death Counts

    Data.gov (United States)

    U.S. Department of Health & Human Services — This data contains provisional counts for drug overdose deaths based on a current flow of mortality data in the National Vital Statistics System. National...

  20. Digital Mapping of Soil Texture Using Regression Tree and Artificial Neural Network in Bijar, Kurdistan

    Directory of Open Access Journals (Sweden)

    kamal nabiollahi

    2015-06-01

    Full Text Available Soil texture is an important soil physical property that governs most physical, chemical, biological, and hydrological processes in soils. Detailed information on soil texture variability is crucial for proper crop and land management and environmental studies. Therefore, at present research, 103 soil profiles were dogged and then sampled in order to prepare digital map of soil texture in Bijar, Kurdistan. Auxiliary data used in this study to represent predictive soil forming factors were terrain attributes, Landsat 7 ETM+ data and a geomorphologic surfaces map. To make a relationship between the soil data set (i.e. Clay, sand and silt and auxiliary data, regression tree (RT and artificial neural network (ANN were applied. Results showed that the RT had the higher accuracy than ANN for spatial prediction of three parameters. For the clay fraction, determination of coefficient (R2 and root mean square root (RMSE calculated for two models were 0.46, 0.81 and 17.10, 12.50, based on validation data set (20%. Our results showed some auxiliary variables had more influence on predictive soil class model which included: geomorphology map, wetness index, multi-resolution index of valley bottom flatness, elevation, slope length, and B3. In general, results showed that decision tree models had higher accuracy than ANN models and also their results are more convenient for interpretation. Therefore, it is suggested using of decision tree models for spatial prediction of soil properties in future studies.

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

    Science.gov (United States)

    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

  2. Detailed predictive mapping of acid sulfate soil occurrence using electromagnetic induction data

    DEFF Research Database (Denmark)

    Beucher, Amélie; Boman, A; Mattbäck, S

    Acid sulfate soils are often called the nastiest soils in the world (Dent & Pons, 1995). Releasing a toxic combination of acidity and metals into the recipient watercourses and estuaries, these soils represent a crucial environmental problem. Moreover, these soils can have a considerable economic......).Since acid sulfate soils contain large amounts of soluble salts, they yield strong electromagnetic (EM) anomalies, appearing as diffuse and round-shaped high electrical conductivity (EC) areas. EM induction data collected from an EM38 proximal sensor hence enabled the refined mapping of acid sulfate...

  3. Detection of terrain indices related to soil salinity and mapping salt-affected soils using remote sensing and geostatistical techniques.

    Science.gov (United States)

    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.

  4. The potential of gamma-ray spectrometry as supplementary information for mapping central European soils

    Science.gov (United States)

    Schuler, U.; Bock, M.; Baritz, R.; Willer, J.; Pickert, E.; Kardel, K.; Herrmann, L.

    2012-04-01

    Permanently updated soil maps are needed inter alia for the prediction of landslide hazards, flooding and drought effects, land degradation monitoring, and precision farming. Since comprehensive and intensive field mapping is not affordable, alternative mapping approaches are required. A promising tool, with quite unrecognised potential for modern soil science is gamma-ray spectrometry. As the radioelements potassium, thorium and uranium respond differently to soil forming processes, it should be possible to infer from their concentration on weathering status, and after calibration on soil properties and types. This paper aims to investigate the potential of airborne gamma spectrometry for mapping of central European soils and soil properties. The study was conducted for a test site in Southern Saxony, Germany, 140*85 km wide, representing diverse soil landscapes. Seven different petrographic training and validation areas were chosen each. To assess the potential of gamma-ray spectrometry as additional data layer, predictions were carried out (i) with and (ii) without radiometric data. The outputs were compared with independent soil information of the validation areas. Both prediction runs used the following predictors: elevation, slope, curvature, planform curvature, profile curvature, terrain ruggedness index, relative altitude, vertical distance above drainage network, wetness index, and convergence index. As additional predictor parent material derived from a reclassification of the official geological map (1:1M scale) was used. As radiometric properties potassium, thorium and uranium were used. The radiometric raster datasets were generated by universal kriging using relative altitude as covariate. Training and validation datasets were selected from a comprehensive dataset representing more than 14.000 point data. Point data include soil types and substrates, and for more than 800 sites soil profiles with analysed texture, pH, exchangeable cations, nutrients

  5. Increasing Efficiency of Soil Fertility Map for Rice Cultivation Using Fuzzy Logic, AHP and GIS

    Directory of Open Access Journals (Sweden)

    javad seyedmohammadi

    2017-02-01

    Full Text Available Introduction: With regard to increasing population of country, need to high agricultural production is essential. The most suitable method for this issue is high production per area unit. Preparation much food and other environmental resources with conservation of biotic resources for futures will be possible only with optimum exploitation of soil. Among effective factors for the most production balanced addition of fertilizers increases production of crops higher than the others. With attention to this topic, determination of soil fertility degree is essential tobetter use of fertilizers and right exploitation of soils. Using fuzzy logic and Analytic Hierarchy Process (AHP could be useful in accurate determination of soil fertility degree. Materials and Methods: The study area (at the east of Rasht city is located between 49° 31' to 49° 45' E longitude and 37° 7' to 37° 27' N latitude in north of Guilan Province, northern Iran, in the southern coast of the Caspian sea. 117 soil samples were derived from0-30 cm depth in the study area. Air-dried soil samples were crushed and passed through a 2mm sieve. Available phosphorus, potassium and organic carbon were determined by sodium bicarbonate, normal ammonium acetate and corrected walkly-black method, respectively. In the first stage, the interpolation of data was done by kriging method in GIS context. Then S-shape membership function was defined for each parameter and prepared fuzzy map. After determination of membership function weight parameters maps were determined using AHP technique and finally soil fertility map was prepared with overlaying of weighted fuzzy maps. Relative variance and correlation coefficient criteria used tocontrol groups separation accuracy in fuzzy fertility map. Results and Discussion: With regard to minimum amounts of parameters looks some lands of study area had fertility difficulty. Therefore, soil fertility map of study area distinct these lands and present soil

  6. Harmonisation of the soil map of Africa at the continental scale

    DEFF Research Database (Denmark)

    Dewitte, Olivier; Jones, Arwyn; Spaargaren, Otto

    2013-01-01

    -class map are presented, the basic information being derived from the Harmonized World Soil Database (HWSD). We show how the original data were updated and modified according to the World Reference Base for Soil Resources classification system. The corrections concerned boundary issues, areas......In the context of major global environmental challenges such as food security, climate change, fresh water scarcity and biodiversity loss, the protection and the sustainable management of soil resources in Africa are of paramount importance. To raise the awareness of the general public......, stakeholders, policy makers and the science community to the importance of soil in Africa, the Joint Research Centre of the European Commission has produced the Soil Atlas of Africa. To that end, a new harmonised soil map at the continental scale has been produced. The steps of the construction of the new area...

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

    Science.gov (United States)

    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...

  8. Instance selection in digital soil mapping: a study case in Rio Grande do Sul, Brazil

    Directory of Open Access Journals (Sweden)

    Elvio Giasson

    2015-09-01

    Full Text Available A critical issue in digital soil mapping (DSM is the selection of data sampling method for model training. One emerging approach applies instance selection to reduce the size of the dataset by drawing only relevant samples in order to obtain a representative subset that is still large enough to preserve relevant information, but small enough to be easily handled by learning algorithms. Although there are suggestions to distribute data sampling as a function of the soil map unit (MU boundaries location, there are still contradictions among research recommendations for locating samples either closer or more distant from soil MU boundaries. A study was conducted to evaluate instance selection methods based on spatially-explicit data collection using location in relation to soil MU boundaries as the main criterion. Decision tree analysis was performed for modeling digital soil class mapping using two different sampling schemes: a selecting sampling points located outside buffers near soil MU boundaries, and b selecting sampling points located within buffers near soil MU boundaries. Data was prepared for generating classification trees to include only data points located within or outside buffers with widths of 60, 120, 240, 360, 480, and 600m near MU boundaries. Instance selection methods using both spatial selection of methods was effective for reduced size of the dataset used for calibrating classification tree models, but failed to provide advantages to digital soil mapping because of potential reduction in the accuracy of classification tree models.

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

    Science.gov (United States)

    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

  10. Assessment of acid sulfate soil mapping utilizing chemical indicators in recipient waters

    Directory of Open Access Journals (Sweden)

    Beucher, A.

    2015-06-01

    Full Text Available In Finland, poor water quality and associated ecological damage in the coastal streams related to land use on acid sulfate (a.s. soils has been drawing a considerable amount of attention since the 1950’s. These soils originate from sulfide-bearing marine sediments mostly occurring in the coastal areas located below the highest shoreline of the former Litorina Sea. Of the many previous studies carried out on soil or water data, quite few gathered both and their geographic extent was relatively limited. This study aimed at assessing a.s. soil probability maps using two chemical indicators measured in the recipient waters (i.e. sulfate content and sulfate/chloride ratio for 24 catchments along the Finnish coast. All the available data was compiled for these catchments, which were surveyed using different methods (i.e. conventional mapping and two spatial modeling techniques: fuzzy logic and artificial neural networks. High sulfate contents and sulfate/ chloride ratios measured in these rivers were controlled by a.s. soils in the corresponding catchments. The extent of the most probable areas for a.s. soils in the surveyed catchments correlated with the two chemical indicators measured in the recipient waters, suggesting that the probability maps created with different methods are reliable and comparable. The use of a.s. soil related chemical indicators in water, thus, constitutes a complementary, independent and straightforward tool to assess a.s. soil probability maps.

  11. High-resolution hydraulic parameter maps for surface soils in tropical South America

    Science.gov (United States)

    Marthews, T. R.; Quesada, C. A.; Galbraith, D. R.; Malhi, Y.; Mullins, C. E.; Hodnett, M. G.; Dharssi, I.

    2014-05-01

    Modern land surface model simulations capture soil profile water movement through the use of soil hydraulics sub-models, but good hydraulic parameterisations are often lacking, especially in the tropics. We present much-improved gridded data sets of hydraulic parameters for surface soil for the critical area of tropical South America, describing soil profile water movement across the region to 30 cm depth. Optimal hydraulic parameter values are given for the Brooks and Corey, Campbell, van Genuchten-Mualem and van Genuchten-Burdine soil hydraulic models, which are widely used hydraulic sub-models in land surface models. This has been possible through interpolating soil measurements from several sources through the SOTERLAC soil and terrain data base and using the most recent pedotransfer functions (PTFs) derived for South American soils. All soil parameter data layers are provided at 15 arcsec resolution and available for download, this being 20x higher resolution than the best comparable parameter maps available to date. Specific examples are given of the use of PTFs and the importance highlighted of using PTFs that have been locally parameterised and that are not just based on soil texture. We discuss current developments in soil hydraulic modelling and how high-resolution parameter maps such as these can improve the simulation of vegetation development and productivity in land surface models.

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

    Science.gov (United States)

    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

  13. GEOSTATISTICAL BASED SUSCEPTIBILITY MAPPING OF SOIL EROSION AND OPTIMIZATION OF ITS CAUSATIVE FACTORS: A CONCEPTUAL FRAMEWORK

    Directory of Open Access Journals (Sweden)

    ABDULKADIR T. SHOLAGBERU

    2017-11-01

    Full Text Available Soil erosion hazard is the second biggest environmental challenges after population growth causing land degradation, desertification and water deterioration. Its impacts on watersheds include loss of soil nutrients, reduced reservoir capacity through siltation which may lead to flood risk, landslide, high water turbidity, etc. These problems become more pronounced in human altered mountainous areas through intensive agricultural activities, deforestation and increased urbanization among others. However, due to challenging nature of soil erosion management, there is great interest in assessing its spatial distribution and susceptibility levels. This study is thus intend to review the recent literatures and develop a novel framework for soil erosion susceptibility mapping using geostatistical based support vector machine (SVM, remote sensing and GIS techniques. The conceptual framework is to bridge the identified knowledge gaps in the area of causative factors’ (CFs selection. In this research, RUSLE model, field studies and the existing soil erosion maps for the study area will be integrated for the development of inventory map. Spatial data such as Landsat 8, digital soil and geological maps, digital elevation model and hydrological data shall be processed for the extraction of erosion CFs. GISbased SVM techniques will be adopted for the establishment of spatial relationships between soil erosion and its CFs, and subsequently for the development of erosion susceptibility maps. The results of this study include evaluation of predictive capability of GIS-based SVM in soil erosion mapping and identification of the most influential CFs for erosion susceptibility assessment. This study will serve as a guide to watershed planners and to alleviate soil erosion challenges and its related hazards.

  14. A GIS based method for soil mapping in Sardinia, Italy: a geomatic approach.

    Science.gov (United States)

    Vacca, A; Loddo, S; Melis, M T; Funedda, A; Puddu, R; Verona, M; Fanni, S; Fantola, F; Madrau, S; Marrone, V A; Serra, G; Tore, C; Manca, D; Pasci, S; Puddu, M R; Schirru, P

    2014-06-01

    A new project was recently initiated for the realization of the "Land Unit and Soil Capability Map of Sardinia" at a scale of 1:50,000 to support land use planning. In this study, we outline the general structure of the project and the methods used in the activities that have been thus far conducted. A GIS approach was used. We used the soil-landscape paradigm for the prediction of soil classes and their spatial distribution or the prediction of soil properties based on landscape features. The work is divided into two main phases. In the first phase, the available digital data on land cover, geology and topography were processed and classified according to their influence on weathering processes and soil properties. The methods used in the interpretation are based on consolidated and generalized knowledge about the influence of geology, topography and land cover on soil properties. The existing soil data (areal and point data) were collected, reviewed, validated and standardized according to international and national guidelines. Point data considered to be usable were input into a specific database created for the project. Using expert interpretation, all digital data were merged to produce a first draft of the Land Unit Map. During the second phase, this map will be implemented with the existing soil data and verified in the field if also needed with new soil data collection, and the final Land Unit Map will be produced. The Land Unit and Soil Capability Map will be produced by classifying the land units using a reference matching table of land capability classes created for this project. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. The Unified North American Soil Map and its implication on the soil organic carbon stock in North America

    Directory of Open Access Journals (Sweden)

    S. Liu

    2013-05-01

    Full Text Available The Unified North American Soil Map (UNASM was developed to provide more accurate regional soil information for terrestrial biosphere modeling. The UNASM combines information from state-of-the-art US STATSGO2 and Soil Landscape of Canada (SLCs databases. The area not covered by these datasets is filled by using the Harmonized World Soil Database version 1.21 (HWSD1.21. The UNASM contains maximum soil depth derived from the data source as well as seven soil attributes (including sand, silt, and clay content, gravel content, organic carbon content, pH, and bulk density for the topsoil layer (0–30 cm and the subsoil layer (30–100 cm, respectively, of the spatial resolution of 0.25 degrees in latitude and longitude. There are pronounced differences in the spatial distributions of soil properties and soil organic carbon between UNASM and HWSD, but the UNASM overall provides more detailed and higher-quality information particularly in Alaska and central Canada. To provide more accurate and up-to-date estimate of soil organic carbon stock in North America, we incorporated Northern Circumpolar Soil Carbon Database (NCSCD into the UNASM. The estimate of total soil organic carbon mass in the upper 100 cm soil profile based on the improved UNASM is 365.96 Pg, of which 23.1% is under trees, 14.1% is in shrubland, and 4.6% is in grassland and cropland. This UNASM data will provide a resource for use in terrestrial ecosystem modeling both for input of soil characteristics and for benchmarking model output.

  16. Soil Organic Carbon Mapping by Geostatistics in Europe Scale

    Science.gov (United States)

    Aksoy, E.; Panagos, P.; Montanarella, L.

    2013-12-01

    Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because SOC is an important soil component that plays key roles in the functions of both natural ecosystems and agricultural systems. The SOC content varies from place to place and it is strongly related with climate variables (temperature and rainfall), terrain features, soil texture, parent material, vegetation, land-use types, and human management (management and degradation) at different spatial scales. Geostatistical techniques allow for the prediction of soil properties using soil information and environmental covariates. In this study, assessment of SOC distribution has been predicted with Regression-Kriging method in Europe scale. In this prediction, combination of the soil samples which were collected from the LUCAS (European Land Use/Cover Area frame statistical Survey) & BioSoil Projects, with local soil data which were collected from six different CZOs in Europe and ten spatial predictors (slope, aspect, elevation, CTI, CORINE land-cover classification, parent material, texture, WRB soil classification, annual average temperature and precipitation) were used. Significant correlation between the covariates and the organic carbon dependent variable was found. Moreover, investigating the contribution of local dataset in watershed scale into regional dataset in European scale was an important challenge.

  17. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions

    Science.gov (United States)

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

    2015-01-01

    80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. Over the period 2008–2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management—organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na). We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15–75% in Root Mean Squared Error (RMSE) across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols) help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring pedological

  18. Remote sensing is a viable tool for mapping soil salinity in agricultural lands

    Directory of Open Access Journals (Sweden)

    Elia Scudiero

    2017-04-01

    Full Text Available Soil salinity negatively impacts the productivity and profitability of western San Joaquin Valley (WSJV farmland. Many factors, including drought, climate change, reduced water allocations, and land-use changes could worsen salinity conditions there, and in other agricultural lands in the state. Mapping soil salinity at regional and state levels is essential for identifying drivers and trends in agricultural soil salinity, and for developing mitigation strategies, but traditional soil sampling for salinity does not allow for accurate large-scale mapping. We tested remote-sensing modeling to map root zone soil salinity for farmland in the WSJV. According to our map, 0.78 million acres are salt affected (i.e., ECe > 4 dS/m, which represents 45% of the mapped farmland; 30% of that acreage is strongly or extremely saline. Independent validations of the remote-sensing estimations indicated acceptable to excellent correspondences, except in areas of low salinity and high soil heterogeneity. Remote sensing is a viable tool for helping landowners make decisions about land use and also for helping water districts and state agencies develop salinity mitigation strategies.

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

    Science.gov (United States)

    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

  20. Quaternary Glacial Mapping in Western Wisconsin Using Soil Survey Information

    Science.gov (United States)

    Oehlke, Betsy M.; Dolliver, Holly A. S.

    2011-01-01

    The majority of soils in the western Wisconsin have developed from glacial sediments deposited during the Quaternary Period (2.6 million years before present). In many regions, multiple advances and retreats have left a complex landscape of diverse glacial sediments and landforms. The soils that have developed on these deposits reflect the nature…

  1. Understanding Variations of Soil Mapping Units and Associated Data for Forensic Science.

    Science.gov (United States)

    Suarez, Melissa D; Southard, Randal J; Parikh, Sanjai J

    2015-07-01

    Soil samples have potential to be useful in forensic investigations, but their utility may be limited due to the inherent variability of soil properties, the wide array of analytical methods, and complexity of data analysis. This study examined the differentiation of similar soils based on both gross (texture, color, mineralogy) and explicit soil properties (elemental composition, cation exchange, Fe-oxyhydroxides). Soils were collected from Fallbrook and adjacent map units from Riverside and San Diego Counties in California. Samples were characterized using multiple techniques, including chemical extracts, X-ray diffraction (XRD), and Fourier transform infrared spectroscopy. Results were analyzed using multiple analytical approaches to compare counties and land uses. Some analyses (XRD, extractions) were better at distinguishing among samples than others (color, texture). Ratios of rare earth elements were particularly useful for distinguishing samples between counties. This potential to "fingerprint" soils illustrates the usefulness of a comprehensive soil database for criminal investigators. © 2015 American Academy of Forensic Sciences.

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

    Science.gov (United States)

    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

  3. First results of the DIGISOIL multi-sensor system for mapping soil properties

    Science.gov (United States)

    Grandjean, G.

    2009-04-01

    The purposes of the multidisciplinary DIGISOIL project are the integration and improvement of in situ and proximal measurement technologies for the assessment of soil properties and soil degradation indicators, going from the sensing technologies to their integration and their application in (digital) soil mapping (DSM). In order to assess and prevent soil degradation and to benefit from the different ecological, economical and historical functions of the soil in a sustainable way, high resolution and accurate maps of soil properties are needed. The core objective of the project is to explore and exploit new capabilities of advanced geophysical technologies for answering this societal demand. To this aim, DIGISOIL addresses four issues covering technological, soil science and economic aspects (Figure 1): (i) the validation of geophysical (in situ, proximal and airborne) technologies and integrated pedo-geophysical inversion techniques (mechanistic data fusion) (ii) the relation between the geophysical parameters and the soil properties, (iii) the integration of the derived soil properties for mapping soil functions and soil threats, (iv) the evaluation, standardisation and sub-industrialization of the proposed methodologies, including technical and economical studies. With respect to these issues, the preliminary tasks of the DIGISOIL project were to develop, test and validate the most relevant geophysical technologies for mapping soil properties. The different field tests, realized at this time, allow focusing on technological suitable solutions for each of identified methods: geoelectric, GPR, seismics, magnetic and hyperspectral. Data acquisition systems, sensor geometry, data processing are thus presented and discussed in the perspectives of producing information layers for Digital Soil Mapping. Next tasks will be dedicated to (i) establish correlations between the measured geophysical measurements and the soil properties involved in soil functions / threats

  4. Mapping soil degradation by topsoil grain size using MODIS data

    OpenAIRE

    XIAO, Jieying; SHEN, Yanjun; TATEISHI, Ryutaro

    2005-01-01

    [ABSTRACT] MODIS BRDF reflectance data at the end of April 2004 was selected to make a desertification map base on topsoil grain size by using Gain Size Index at arid and semiarid Asia. After data processing, GSI was applied into desertification mapping, and we find that high GSI area distributed at the desert and its’ marginal area, degraded grassland, desert steppe. The desertification map was output according to the correlation between GSI and grain size distribution, the classification of...

  5. Digital Mapping of Soil Organic Carbon Contents and Stocks in Denmark

    DEFF Research Database (Denmark)

    Adhikari, Kabindra; Hartemink, Alfred E.; Minasny, Budiman

    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...... of 20 g kg21 was reported for 025 cm soil, whereas there was on average 2.2 g SOC kg21 at 602100 cm depth. For SOC and bulk density prediction precision decreased with soil depth, and a standard error of 2.8 g kg21 was found at 602100 cm soil depth. Average SOC stock for 0230 cm was 72 t ha21...

  6. Mapping Soil Surface Macropores Using Infrared Thermography: An Exploratory Laboratory Study

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  8. Soil resilience mapping in selective wetlands, West Suez Canal, Egypt

    Directory of Open Access Journals (Sweden)

    W.A. Abdel Kawy

    2011-12-01

    The human action on soil resilience could be recognized through the man-action as good and proper land management, introducing proper land modern irrigation and drainage styles, in addition to adequate fertilizing programs.

  9. Spatial pattern of soil and soybean crop: an assessment using digital mapping techniques

    Science.gov (United States)

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

    2017-04-01

    The aim of this study was to analyze the relationships among spatial patterns of soil properties and soybean crop. The study was carried out in three provinces of Argentina: (i) Buenos Aires (BA), (ii) Entre Rios (ER) and (iii) Cordoba (COR). In each province, 2 agricultural fields were selected. Ancillary information related to soil forming factors in each field was gathered, for example apparent electrical conductivity (ECa), NDVI and yield maps. We used principal component spatial analysis (MULTISPATI-PCA) to delimit zones for soil type by field. To zonal validation, 4 sampling sites were located in which we collected soil samples, grain yield and soybean crop quality. Random Forest (RF) was used to determine the importance of soil properties over soybean crop properties. For comparing soil properties in each zone between fields, a mix lineal model and ANOVA were adjusted. Our results suggest that MULTISPATI-PCA was efficient to delimit zones for soil type. Relationships between soil properties and crop yield were examined and understood. However, it did not occur with crop quality patterns. Topography did not prove to be an accurate indicator of spatial pattern relations of soil properties and crop, whereas ECa, yield maps and NDVI proved to be effective indicators. Grains m-2 and NDVI were affected homogeneously and were showed spatial correspondence according to soil limitations. Percentage of protein did not show spatial correspondence with delimitated zones in saline soils, particularly in ER. In such fields, Om and pH were important for percentage of protein. It was evidenced that a direct relation exists between complex relationship of soil and crop properties and soil degradation.

  10. Soil Infrastructure, Interfaces & Translocation Processes in Inner Space ("Soil-it-is": towards a road map for the constraints and crossroads of soil architecture and biophysical processes

    Directory of Open Access Journals (Sweden)

    L. W. de Jonge

    2009-08-01

    , we show the Dexter et al. (2008 threshold may also apply to hydrological and physical-chemical interface phenomena including soil-water repellency and sorption of volatile organic vapors (gas-water-solids interfaces as well as polycyclic aromatic hydrocarbons (water-solids interfaces. However, data for differently-managed soils imply that energy input, soil-moisture status, and vegetation (quality of eluded organic matter may be equally important constraints together with the complexation and degradation of organic carbon in deciding functional soil architecture and interface processes. Finally, we envision a road map to soil inner space where we search for the main controls of particle and pore network changes and structure build-up and resilience at each crossroad of biophysical parameters, where, for example, complexation between organic matter and clay, and moisture-induced changes from hydrophilic to hydrophobic surface conditions can play a role. We hypothesize that each crossroad (e.g. between organic carbon/clay ratio and matric potential may control how soil self-organization will manifest itself at a given time as affected by gradients in energy and moisture from soil use and climate. The road map may serve as inspiration for renewed and multi-disciplinary focus on functional soil architecture.

  11. Compilation of functional soil maps for the support of spatial planning and land management in Hungary

    Science.gov (United States)

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

    2015-04-01

    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. Delineation of Areas with Excellent Productivity in the framework of the National Regional Development Plan or delimitation of Areas with Natural Constraints in Hungary according to the common European biophysical criteria are primary issues in national level spatial planning. 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 also incorporated in spatial planning. All these challenges require adequate, preferably timely and spatially detailed knowledge of the soil cover. For the satisfaction of these demands the soil conditions of Hungary have been digitally mapped based on the most detailed, available recent and legacy soil data, applying proper DSM techniques. Various soil related information were mapped in three distinct approaches: (i) basic soil properties determining agri-environmental conditions (e.g.: soil type according to the Hungarian genetic classification, rootable depth, sand, silt and clay content by soil layers, pH, OM and carbonate content for the plough layer); (ii) biophysical criteria of natural handicaps (e.g.: poor drainage, unfavourable texture and stoniness, shallow rooting depth, poor chemical properties and soil moisture balance) defined by common European system and (iii) agro-meteorologically modelled yield values for different crops, meteorological

  12. The fixed/detachable implant provisional prosthesis.

    Science.gov (United States)

    Cibirka, R M; Linebaugh, M L

    1997-06-01

    Interim modification and management of a complete denture following surgical uncovering of dental implants can be time-intensive and may fail to provide adequate patient benefit until the definitive prosthesis can be completed. Inadequate interim management can result in functional and tissue difficulties. Modification of the conventional complete denture to a fixed/detachable provisional prosthesis in a one-stage procedure provides the patient an opportunity to experience a fixed prosthesis. The incorporation of fixed, provisional cylinders to the existing denture base using autopolymerizing acrylic resin with a closed-mouth technique is described. The peripheral regions are reduced and the distal extension shortened to resemble a fixed/detachable prosthesis. This conversion technique can provide patient satisfaction and comfort until delivery of the definitive prosthesis. Esthetic concerns, home care problems, or patient difficulties with the provisional prosthesis can be rectified in the final prosthesis.

  13. Geomorpho-edaphic mapping of Atécuaro catchment (Michoacan, Mexico) and indigenous soil classification

    Science.gov (United States)

    Alanís González, N.; Alcalá de Jesús, M.; Arellano Reyes, A.; Jordán, A.; Zavala, L. M.

    2012-04-01

    The needs of management and conservation of land involve the study of natural resources and their internal relationships. Over time, these resources, including soil, have been used in an uncontrolled manner, resulting in species extinction and environmental degradation processes. The main reason for this in developing areas is the lack of soil and geomorphological information for an adequate land use planning. Often, ethnopedological knowledge and the inclusion of indigenous communities as beneficiaries of the agricultural technology are indispensable premises to make a better use of soil. A geomorphology and soil survey was conducted in the Atécuaro catchment (4591 ha), in the municipality of Morelia (Michoacan, Mexico). The Atécuaro catchment is located in the Mil Cumbres area, and is characterized by an irregular relief and a diversity of landforms and substrates (andesite, rhyolite, basalt, tuff and Quaternary sediments). The main land uses are oak and pine forest, shrubland, grassland and dryland farming. Results of the soil survey and the analysis of geoforms were studied and incorporated in a geographycal information system. Preliminary geoform and soil units maps were overlapped in order to get a map of geomorpho-edaphic units. Up to 30 different geomorpho-edaphic units were classified. Finally, map units were correlated with local indigenous soil classification.

  14. Sampling and Mapping Soil Erosion Cover Factor for Fort Richardson, Alaska. Integrating Stratification and an Up-Scaling Method

    National Research Council Canada - National Science Library

    Wang, Guangxing; Gertner, George; Anderson, Alan B; Howard, Heidi

    2006-01-01

    When a ground and vegetation cover factor related to soil erosion is mapped with the aid of remotely sensed data, a cost-efficient sample design to collect ground data and obtain an accurate map is required...

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

    Science.gov (United States)

    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

  16. Digital Mapping of Toxic Metals in Qatari Soils Using Remote Sensing and Ancillary Data

    DEFF Research Database (Denmark)

    Peng, Yi; Bou Kheir, Rania; Adhikari, Kabindra

    2016-01-01

    After decades of mining and industrialization in Qatar, it is important to estimate their impact on soil pollution with toxic metals. The study utilized 300 topsoil (0–30 cm) samples, multi-spectral images (Landsat 8), spectral indices and environmental variables to model and map the spatial...... distribution of arsenic (As), chromium (Cr), nickel (Ni), copper (Cu), lead (Pb) and zinc (Zn) in Qatari soils. The prediction model used condition-based rules generated in the Cubist tool. In terms of R2 and the ratio of performance to interquartile distance (RPIQ), the models showed good predictive...... metals’ monitoring in arid soils, due to the climate and the vegetation cover during this season. Topsoil maps of the six toxic metals were generated. The maps can be used to prioritize the choice of remediation measures and can be applied to other arid areas of similar environmental...

  17. Potential of hyperspectral remote sensing for field scale soil mapping and precision agriculture applications

    Directory of Open Access Journals (Sweden)

    Raffaele Casa

    2012-10-01

    Full Text Available Mapping within-field variation in soil properties opens up the possibility of employing variable agronomic management and precision farming technologies with potential environmental and economic benefits. However, the excessive cost of systematic direct soil sampling severely constrains the practical feasibility of site specific management based on soil variability information. Remote sensing offers a cost effective and efficient means for gathering a great deal of information on soil properties. The aim of the present work was to assess the potential of satellite hyperspectral imagery for the mapping of soil properties and the tilled layer of agricultural fields, in the context of precision agriculture applications. CHRIS-PROBA satellite images were acquired over two bare soil fields and their capability to provide estimates of soil texture and soil organic matter (SOM at the field scale was assessed. Partial least squares regression (PLSR models were developed on datasets spatially independent from those used for validation. Clay and sand could be estimated with intermediate accuracy, with values of RPD (ratio of performance to deviation higher than 1.4. Root mean squared error (RMSE values of 3.7 and 5.2 were obtained for clay in the two fields respectively. SOM estimates were not satisfactory, probably because of the limited range of spatial variation in the studied fields. Maps of uniform soil zones were obtained from measured and estimates soil texture data by means of fuzzy c-means classification. The resulting maps were then used for the parameterization of a simple water balance model, i.e. CropWat8.0, in order to simulate and compare uniform and variable-rate irrigation strategies. Simulation results suggest that site-specific irrigation allows to reduce significantly water losses by deep percolation, which occur when irrigation scheduling and volumes are calculated on the basis of average field soil properties. The present paper

  18. Mapping of soil erosion using remotely sensed data in Zombodze South, Swaziland

    Science.gov (United States)

    Manyatsi, Absalom M.; Ntshangase, Nomndeni

    Zombodze South is situated in the southern part of Swaziland. It has visible signs of soil erosion. However like many parts of the country, soil erosion has not been mapped. The area lacks soil conservation measures. The objective of the study was to map the spatial distribution of soil erosion, and to determine the perception of community members on soil erosion problems. IDRISI for Windows was used to produce 20 clusters from Landsat ETM data for January 1999. The clusters were allocated to five land cover classes based on a combination of use of “scatterplots” and NDVI values. Gullies were identified on digital aerial photos of the area, and digitized. Other land features such as settlements, roads and rivers were also digitized. A structured questionnaire was administered to 40 homesteads that were randomly selected from the 234 homesteads in the community to collect information on perception of communities on soil erosion, as well as their involvement in controlling soil erosion. About 4% of the area was eroded, with another 38% having very sparse vegetation cover. Gully erosion was prevalent in the southern part of the area. The limited soil erosion conservation measures in the area were undertaken by local school children as part of their school projects. The control measures suggested by members of the community included planting trees and grasses along the gullies, fencing of gullies and construction of check dams.

  19. Using proximal soil sensors and fuzzy classification for mapping Amazonian Dark Earths

    Directory of Open Access Journals (Sweden)

    Mats Söderström

    2013-12-01

    Full Text Available We tested if hand-carried field proximal soil sensing (PSS can be used to map the distribution of anthropogenic Amazonian Dark Earths (ADE. ADE soils are rich in archaeological artefacts, nutrients, organic matter and carbon in the very stable form of pyrogenic carbon, also referred to as black carbon or biochar. To test the capacity of PSS to detect signature ADE properties we measured electrical conductivity (ECa, magnetic susceptibility (MSa and gamma ray data by transect sampling and compared these readings, using fuzzy classification, with datasets on chemical soil properties from a 28 ha large study area located on the Belterra Plateau of the Lower Amazon in northern Brazil. Results indicate that ECa and MSa measurements were good indicators of ADE signatures, but that the gamma radiation sensor was less useful in the deeply weathered soils. PSS and fuzzy classification can be used for rapid field mapping of ADE for both agricultural and archaeological purposes.

  20. A 30 meter soil properties map of the contiguous United States for use in remote sensing and land surface models

    Science.gov (United States)

    Chaney, N.; Morgan, C.; McBratney, A.; Wood, E. F.; Yimam, Y.

    2016-12-01

    Soil moisture plays a critical role in the terrestrial water, energy, and biogeochemical cycles. For this reason, numerical weather prediction, global circulation models, and hydrologic monitoring systems increasingly emphasize modeling soil moisture and assimilating soil moisture remote sensing products. In both cases, the prescribed soil hydraulic properties play a pivotal role in accurately describing the soil moisture state. However, an accurate characterization of soil hydraulic properties remains a persistent challenge—existing continental soil databases are too coarse and outdated for contemporary applications. To address this challenge, we have developed the Probabilistic Remapping of SSURGO database (POLARIS); a new soil database that covers the contiguous United States (CONUS) at a 30-meter spatial resolution. POLARIS was constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm to remap the rich yet incomplete Soil Survey Geographic (SSURGO) database to create spatially complete probabilistic soil series maps over CONUS (Chaney et al., 2016). These maps are then combined with the vertical profile information of each soil series to create the corresponding maps of soil hydraulic properties and their associated uncertainties. The mapped soil hydraulic properties include soil texture, saturated hydraulic conductivity, porosity, field capacity, and wilting point. POLARIS provides a breakthrough in soil information. To illustrate this database's potential, we will both explore the database at multiple spatial scales and discuss recent land surface modeling results that have used POLARIS to simulate soil moisture at a 30-meter spatial resolution over CONUS between 2004 and 2014. We will discuss the added benefit of using POLARIS and the opportunity it presents to improve the characterization of soil hydraulic properties in land surface models and soil moisture remote sensing. References

  1. 14 CFR 121.207 - Provisionally certificated airplanes: Operating limitations.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Provisionally certificated airplanes... AND OPERATIONS OPERATING REQUIREMENTS: DOMESTIC, FLAG, AND SUPPLEMENTAL OPERATIONS Airplane Performance Operating Limitations § 121.207 Provisionally certificated airplanes: Operating limitations. In...

  2. VSRR - Provisional monthly number of live births by state

    Data.gov (United States)

    U.S. Department of Health & Human Services — https://www.cdc.gov/nchs/products/vsrr/provisional-tables.htm Monthly provisional counts of births are provided by state of residence (50 states, District of...

  3. VSRR - Provisional monthly number of deaths by state

    Data.gov (United States)

    U.S. Department of Health & Human Services — https://www.cdc.gov/nchs/products/vsrr/provisional-tables.htm Monthly provisional counts of deaths and infant deaths are provided by state of residence (50 states,...

  4. Bacterial adhesion of porphyromonas gingivalis on provisional fixed prosthetic materials

    Directory of Open Access Journals (Sweden)

    Mustafa Zortuk

    2010-01-01

    Conclusion : The quantity of bacterial adhesion and surface roughness differed among the assessed provisional fixed prosthodontic materials. The light-polymerized provisional material Revotek LC had rougher surface and more bacterial adhesion compared with the others.

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

    Directory of Open Access Journals (Sweden)

    Jean François Desprats

    2007-10-01

    Full Text Available Soil moisture is a key parameter in different environmental applications, suchas hydrology and natural risk assessment. In this paper, surface soil moisture mappingwas carried out over a basin in France using satellite synthetic aperture radar (SARimages acquired in 2006 and 2007 by C-band (5.3 GHz sensors. The comparisonbetween soil moisture estimated from SAR data and in situ measurements shows goodagreement, with a mapping accuracy better than 3%. This result shows that themonitoring of soil moisture from SAR images is possible in operational phase. Moreover,moistures simulated by the operational Météo-France ISBA soil-vegetation-atmospheretransfer model in the SIM-Safran-ISBA-Modcou chain were compared to radar moistureestimates to validate its pertinence. The difference between ISBA simulations and radarestimates fluctuates between 0.4 and 10% (RMSE. The comparison between ISBA andgravimetric 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 estimatedfrom 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.

  6. Three-Dimensional Mapping of Soil Organic Carbon by Combining Kriging Method with Profile Depth Function

    OpenAIRE

    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 ...

  7. SOIL SURVEY AND MAPPING USING QGIS IN THE SPECIFIC METHODOLOGICAL CONTEXT OF ROMANIA

    Directory of Open Access Journals (Sweden)

    Bogdan Rosca

    2013-07-01

    Full Text Available The purpose of this paper is to describe the use of QGIS as tool for soil survey and mapping in Romanian methodological context and to analyze the efficiency of Open Source tools in this matter. Beginning with integrating data from various sources (GPS points, analog and digital maps, analytical soil data, etc, continuing with editing and spatial analysis and finishing with map production, we have used QGIS and it's add-ons in every stage of the soil survey and mapping process following, as much as possible, standard procedures specified by methodology. Also we have searched for optimal solution in order to solve specific problems that may occur such as the type of topology for digitization (when the surveyor need to create data from scratch, how to integrate various databases, specific queries, etc. In conclusion QGIS, with his vast array of tools, can successfully be used in soil survey and for map production according to standards required by Romanian methodology. It can be implemented also very easily with minimum effort both technical and financial.

  8. Mapping Soil Erosion in a Quaternary Catchment in Eastern Cape ...

    African Journals Online (AJOL)

    Temp

    2017-04-06

    Apr 6, 2017 ... widely used Universal Soil Loss Equation (USLE) developed by Wischmeier and Smith (1965). The ... In this paper, satellite image-derived NDVI, SAVI, and SARVI are considered mainly because they are ... The image data used in this study include Landsat8 Operational Land Imager (OLI) and Satellites.

  9. Mapping soil erosion in a quaternary catchment in Eastern Cape ...

    African Journals Online (AJOL)

    In South Africa, soil erosion is considered as an environmental and social problem with serious financial implications particularly in some rural areas where this geomorphological phenomenon is widespread. An example is the Umzimvubu Local Municipality, where most households are strongly reliant on agriculture for ...

  10. GlobalSoilMap and Global Carbon Predictions

    DEFF Research Database (Denmark)

    Hempel, Jonathan; McBratney, Alex B.; Arrouays, Dominique

    consistently produced soil property information at 100 m resolution across the world. This information will aid in solving some of the key environment and societal issues of the day, including food security, global climate change land degradation and carbon sequestration. Data would be produced using mostly...

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

    Science.gov (United States)

    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

  12. Variability of apparently homogeneous soilscapes in São Paulo state, Brazil: II. quality of soil maps

    Directory of Open Access Journals (Sweden)

    M. van Den Berg

    2000-06-01

    Full Text Available The quality of semi-detailed (scale 1:100.000 soil maps and the utility of a taxonomically based legend were assessed by studying 33 apparently homogeneous fields with strongly weathered soils in two regions in São Paulo State: Araras and Assis. An independent data set of 395 auger sites was used to determine purity of soil mapping units and analysis of variance within and between mapping units and soil classification units. Twenty three soil profiles were studied in detail. The studied soil maps have a high purity for some legend criteria, such as B horizon type (> 90% and soil texture class (> 80%. The purity for the "trophic character" (eutrophic, dystrophic, allic was only 55% in Assis. It was 88% in Araras, where many soil units had been mapped as associations. In both regions, the base status of clay-textured soils was generally better than suggested by the maps. Analysis of variance showed that mapping was successful for "durable" soil characteristics such as clay content (> 80% of variance explained and cation exchange capacity (≥ 50% of variance explained of 0-20 and 60-80 cm layers. For soil characteristics that are easily modified by management, such as base saturation of the 0-20 cm layer, the maps had explained very little ( 100 m; (b taking advantage of correlations between easily measured soil characteristics and chemical soil properties and, (c unbending the link between legend criteria and a taxonomic system. The maps are well suited to obtain an impression of land suitability for high-input farming. Additional field work and data on former land use/management are necessary for the evaluation of chemical properties of surface horizons.

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

    Science.gov (United States)

    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.

  14. Mapping soil salinity in irrigated land using optical remote sensing data

    Directory of Open Access Journals (Sweden)

    Rachid Lhissoui

    2014-04-01

    Full Text Available Soil salinity caused by natural or human-induced processes is certainly a severe environmental problem that already affects 400 million hectares and seriously threatens an equivalent surface. Salinization causes negative effects on the ground; it affects agricultural production, infrastructure, water resources and biodiversity. In semi-arid and arid areas, 21% of irrigated lands suffer from waterlogging, salinity and/or sodicity that reduce their yields. 77 million hectares are saline soils induced by human activity, including 58% in the irrigated areas. In the irrigated perimeter of Tadla plain (central Morocco, the increased use of saline groundwater and surface water, coupled with agricultural intensification leads to the deterioration of soil quality. Experimental methods for monitoring soil salinity by direct measurements in situ are very demanding of time and resources, and also very limited in terms of spatial coverage. Several studies have described the usefulness of remote sensing for mapping salinity by its synoptic coverage and the sensitivity of the electromagnetic signal to surface soil parameters. In this study, we used an image of the TM Landsat sensor and field measurements of electrical conductivity (EC, the correlation between the image data and field measurements allowed us to develop a semi-empirical model allowing the mapping of soil salinity in the irrigated perimeter of Tadla plain. The validation of this model by the ground truth provides a correlation coefficient r² = 0.90. Map obtained from this model allows the identification of different salinization classes in the study area.

  15. Predictive mapping of soil properties at high resolution by component wise gradient boosting

    Science.gov (United States)

    Nussbaum, Madlene; Papritz, Andreas; Fraefel, Marielle; Baltensweiler, Andri; Keller, Armin

    2015-04-01

    Accurate spatial information on soils is crucial for sustainable usage of the resource soil. Spatial planning, agriculture, forestry or natural hazards management need high resolution maps of potentials of soils for particular functions (e. g. water storage, nutrient supply). Soil functions are derived from basic soil properties like soil organic carbon or soil texture. For many regions precise maps of basic soil properties are missing. Hence, as a prerequisite for digital soil function mapping, maps of soil properties must be created with the desired resolution. A wide range of statistical approaches (linear and additive models, external drift kriging, Random Forest) were used for this in the past. When numerous environmental covariates (e. g. hyper-spectral remote sensing data) are available the selection of the model with best predictive power is challenging. Besides the issue of covariate selection, one should allow for non-linear effects of covariates on soil properties. To handle these difficulties we used a gradient boosting approach that included besides categorical covariates linear and smooth non-linear terms of continuous covariates as base learners. Residual auto-correlation and non-stationary relationships were modeled by smooth spatial surfaces. Gradient boosting of this flavor selects relevant covariates in a slow learning procedure and inherently models non-linear dependencies on covariates during the fitting process. The restriction to linear and smoothing spline base learners retains the interpretability of the fitted predictive models. The number of boosting iterations is the main tuning parameter and was determined by tenfold cross validation. To explore the feasibility of the gradient boosting approach we mapped pH of forest topsoils in Canton of Zurich, Switzerland, at high (50 m) spatial resolution. Legacy pH measurements were available from 1200 sites in the in the forests of Canton of Zurich. Gradient boosting selected a sparse model with

  16. Generalized provisional seed zones for native plants

    Science.gov (United States)

    Andrew D. Bower; J. Bradley St.Clair; Vicky. Erickson

    2014-01-01

    Deploying well-adapted and ecologically appropriate plant materials is a core component of successful restoration projects. We have developed generalized provisional seed zones that can be applied to any plant species in the United States to help guide seed movement. These seed zones are based on the intersection of high-resolution climatic data for winter minimum...

  17. VSRR - Quarterly provisional estimates for infant mortality

    Data.gov (United States)

    U.S. Department of Health & Human Services — Provisional estimates of infant mortality (deaths of infants under 1 year per 1,000 live births), neonatal mortality (deaths of infants aged 0-27 days per 1,000 live...

  18. Digital Mapping of Soil Organic Carbon Contents and Stocks in Denmark

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  20. Geoinformation Mapping of the Soil Erosion in Russian Middle Volga Region river basins

    Science.gov (United States)

    Yermolaev, Oleg

    2017-04-01

    The major purpose of this study was to analyze spatial patterns of soil erosion on agricultural lands in the Middle Volga region. In such a case the level of generalization of the maps has been specified. The cartographic geoinformation method was used. The intensity of erosional processes on slopes in the Russian Middle Volga region is very high; this region is often called the "erosional pole" of the East European Plain. Plain territory and fertile soils of this region have always been attractive for people and favored the extensive agricultural development of the territory. Large-scale deforestation and soil plowing in place of former forests have led to the development of agrogenic erosion, the formation of gullies, and the accelerated soil loss exceeding the natural (geological) rate of soil loss by several orders of magnitude. The results of a medium-scale geoinformation mapping of the soil erosion on an area of about 150000 km2 in the Middle Volga region are analyzed using the catchment-based approach. A quantitative index of the development of soil erosion on the agricultural lands is suggested. It reflects the intensity of soil erosion on slopes within the river catchments. An integral index of the intensity of soil erosion from agricultural land on slopes of particular catchments has been suggested. A computer-based vector map of the boundaries more than 3000 elementary catchments has been developed. It represents the territorial units for the analysis of soil erosion. Archive materials from the former institutes for land survey have been used to compile a series of the maps of soil erosion in river catchments on a scale of 1:200000. The maximum development of soil erosion on agricultural lands in the Middle Volga region is typical of the subzone of broadleaved forests. To the north and to the south of this subzone, the intensity and extent of soil water erosion decrease. In the northern direction, this decrease is mainly due to lower agricultural loads

  1. Comparing Kriging and Regression Approaches for Mapping Soil Clay Content in a diverse Danish Landscape

    DEFF Research Database (Denmark)

    Adhikari, Kabindra; Bou Kheir, Rania; Greve, Mette Balslev

    2013-01-01

    Information on the spatial variability of soil texture including soil clay content in a landscape is very important for agricultural and environmental use. Different prediction techniques are available to assess and map spatial variability of soil properties, but selecting the most suitable......, and residual prediction deviation (RPD) for comparison. Among all the prediction methods, the highest R2 (i.e., 0.74) and lowest RMSE (i.e., 0.28) were associated with the RKrr model, which also had an RPD value of 2.2, confirming RKrr as the best prediction method. Stratification of samples slightly improved...

  2. Postfire soil burn severity mapping with hyperspectral image unmixing

    Science.gov (United States)

    Peter R. Robichaud; Sarah A. Lewis; Denise Y. M. Laes; Andrew T. Hudak; Raymond F. Kokaly; Joseph A. Zamudio

    2007-01-01

    Burn severity is mapped after wildfires to evaluate immediate and long-term fire effects on the landscape. Remotely sensed hyperspectral imagery has the potential to provide important information about fine-scale ground cover components that are indicative of burn severity after large wildland fires. Airborne hyperspectral imagery and ground data were collected after...

  3. Deriving soil function maps to assess related ecosystem services using imaging spectroscopy in the Lyss agricultural area, Switzerland

    Science.gov (United States)

    Diek, Sanne; de Jong, Rogier; Braun, Daniela; Böhler, Jonas; Schaepman, Michael

    2014-05-01

    Soils play an important role in the benefits offered by ecosystems services. In densely populated Switzerland soils are a scarce resource, with high pressure on services ranging from urban expansion to over-utilization. Key change drivers include erosion, soil degradation, land management change and (chemical) pollution, which should be taken into consideration. Therefore there is an emerging need for an integrated, sustainable and efficient system assessing the management of soil and land as a resource. The use of remote sensing can offer spatio-temporal and quantitative information of extended areas. In particular imaging spectroscopy has shown to perfectly complement existing sampling schemes as secondary information for digital soil mapping. Although only the upper-most layer of soil interacts with light when using reflectance spectroscopy, it still can offer valuable information that can be utilized by farmers and decision makers. Fully processed airborne imaging spectrometer data from APEX as well as land cover classification for the agricultural area in Lyss were available. Based on several spectral analysis methods we derived multiple soil properties, including soil organic matter, soil texture, and mineralogy; complemented by vegetation parameters, including leaf area index, chlorophyll content, pigment distribution, and water content. The surface variables were retrieved using a combination of index-based and physically-based retrievals. Soil properties in partly to fully vegetated areas were interpolated using regression kriging based methods. This allowed the continuous assessment of potential soil functions as well as non-contiguous maps of abundances of combined soil and vegetation parameters. Based on a simple regression model we could make a rough estimate of ecosystem services. This provided the opportunity to look at the differences between the interpolated soil function maps and the non-contiguous (but combined) vegetation and soil function maps

  4. Soil gas radon assessment and development of a radon risk map in Bolsena, Central Italy.

    Science.gov (United States)

    Cinelli, G; Tositti, L; Capaccioni, B; Brattich, E; Mostacci, D

    2015-04-01

    Vulsini Volcanic district in Northern Latium (Central Italy) is characterized by high natural radiation background resulting from the high concentrations of uranium, thorium and potassium in the volcanic products. In order to estimate the radon radiation risk, a series of soil gas radon measurements were carried out in Bolsena, the principal urban settlement in this area NE of Rome. Soil gas radon concentration ranges between 7 and 176 kBq/m(3) indicating a large degree of variability in the NORM content and behavior of the parent soil material related in particular to the occurrence of two different lithologies. Soil gas radon mapping confirmed the existence of two different areas: one along the shoreline of the Bolsena lake, characterized by low soil radon level, due to a prevailing alluvial lithology; another close to the Bolsena village with high soil radon level due to the presence of the high radioactive volcanic rocks of the Vulsini volcanic district. Radon risk assessment, based on soil gas radon and permeability data, results in a map where the alluvial area is characterized by a probability to be an area with high Radon Index lower than 20 %, while probabilities higher than 30 % and also above 50 % are found close to the Bolsena village.

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

    Science.gov (United States)

    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.

  6. 3D modelling of soil texture: mapping and incertitude estimation in centre-France

    Science.gov (United States)

    Ciampalini, Rossano; Martin, Manuel P.; Saby, Nicolas P. A.; Richer de Forges, Anne C.; Nehlig, Pierre; Martelet, Guillaume; Arrouays, Dominique

    2014-05-01

    Soil texture is an important component of all soil physical-chemical processes. The spatial variability of soil texture plays a crucial role in the evaluation and modelling of all distributed processes. The object of this study is to determine the spatial variation of soil granulometric fractions (i.e., clay, silt, sand) in the region "Centre" of France in relation to the main controlling factors, and to create extended maps of these properties following GlobalSoilMap specifications. For this purpose we used 2487 soil profiles of the French soil database (IGCS - Inventory Management and Soil Conservation) and continuum depth values of the properties within the soil profiles have been calculated with a quadratic splines methodology optimising the spline parameters in each soil profile. We used environmental covariates to predict soil properties within the region at depth intervals 0-5, 5-15, 15-30, 30-60, 60-100, and 100-200 cm. Concerning environmental covariates, we used SRTM and ASTER DEM with 90m and 30m resolution, respectively, to generate terrain parameters and topographic indexes. Other covariates we used are Gamma Ray maps, Corine land cover, available geological and soil maps of the region at scales 1M, 250k and 50k. Soil texture is modeled with the application of the compositional data analysis theory namely, alr-transform (Aitchison, 1986) which considers in statistical calculation the complementary dependence between the different granulometric classes (i.e. 100% constraint). The prediction models of the alr-transformed variables have been developed with the use of boosting regression trees (BRT), then, using a LMM - Linear Mixed Model - that separates a fixed effect from a random effect related to the continuous spatially correlated variation of the property. In this case, the LMM is applied to the two co-regionalized properties (clay and sand alr-transforms). Model uncertainty mapping represents a practical way to describe efficiency and limits of

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

    Science.gov (United States)

    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

  8. Mapping soil moisture and surface heat fluxes by assimilating GOES land surface temperature and SMAP soil moisture data

    Science.gov (United States)

    Lu, Yang; Steele-Dunne, Susan C.; van de Giesen, Nick

    2017-04-01

    This study is focused on estimating soil moisture and sensible/latent heat fluxes by assimilating remotely-sensed land surface temperature (LST) and soil moisture data. Surface heat fluxes interact with the overlying atmosphere, and play a crucial role in the water and energy cycles. However, they cannot be directly measured using remote sensing. It has been demonstrated that LST time series contain information about the surface energy balance, and that assimilating soil moisture further improves the estimation by putting more constraints on the energy partitioning. In previous studies, two controlling factors were estimated: (1) a monthly constant bulk heat transfer coefficient (CHN) that scales the sum of surface heat fluxes, and (2) an evaporative fraction (EF) which governs the energy partitioning and stays quasi-constant during the near-peak hours. Considering the fact that CHN is not constant especially in the growing season, here CHN is assumed a function of leaf area index (LAI). LST data from GOES (Geostationary Operational Environmental Satellites) and soil moisture data from SMAP (Soil Moisture Active Passive) are both assimilated into a simply heat and water transfer model to update LST, soil moisture, CHN and EF , and to map surface heat fluxes over a study area in central US. A hybrid data assimilation strategy is necessary because SMAP data are available every 2-3 days, while GOES LST data are provided every hour. In this study, LST data are assimilated using an adaptive particle batch smoother (APBS) and soil moisture is periodically updated using a particle filter (PF). Results show that soil moisture is greatly improved, and that EF estimates are restored very well after assimilation. As forcing data are provided by remote sensing or reanalysis products to minimize the dependence on ground measurements, this methodology can be easily applied in other regions with limited data.

  9. Simulation of soil moisture and evapotranspiration in a soil profile during the 1999 MAP-Riviera Campaign

    Directory of Open Access Journals (Sweden)

    M. Zappa

    2003-01-01

    Full Text Available Detailed plot-scale observations of basic hydrometeorological variables represent valuable data for assessing the quality of the soil moisture module and evapotranspiration scheme in hydrological models. This study presents the validation of soil moisture and evapotranspiration (ET simulation during the special observing period (R-SOP of the Riviera Project (July–November 1999, a sub-project of the Mesoscale Alpine Programme (MAP. The location investigated was a sandy soil plot at the edge of a corn field. The hydrological model PREVAH was driven using three meteorological data sets: hourly data from an experimental tower in the Riviera Valley (southern Switzerland, hourly data interpolated for the Riviera site during the R-SOP period from permanent automatic stations (MeteoSwiss network and interpolated daily data (1980–2000. The quality of the interpolated meteorological data was evaluated with respect to data collected at an experimental tower. The interpolated data proved fairly representative for the location under investigation. The hydrological simulations were compared with recorded observations of soil moisture and latent heat flux (LE. The simulation of soil moisture was accurate in case of all three meteorological data sets. The results of ET simulations with three simple parameterisations showed high correlation to LE derived using the Bowen ratio and measured through eddy correlation. The quantitative agreement between observed and simulated LE was poorer because of the presence of a fully developed wind valley system during periods of good weather. This wind system claims part of the available energy and therefore reduces the amount of energy available for LE. The 21-year simulation at daily time step shows that the R-SOP period in 1999 was warm and wet compared to the last 21 years. Keywords: MAP-Riviera Project, soil moisture, evapotranspiration, hydrological modelling, model evaluation

  10. Global map of soil roughness using L-band SMOS data

    Science.gov (United States)

    Parrens, Marie; Wigneron, Jean-Pierre; Richaume, Philippe; Al-Bitar, Ahmad; Mialon, Arnaud; Wang, Shu; Fernandez-Moran, Roberto; Al-Yaari, Amen; Kerr, Yann

    2015-04-01

    Since 2010, soil moisture (SM) has been mapped over the Earth by the Soil Moisture and Ocean Salinity (SMOS) satellite. This mission is the first one to monitor SM over land using passive L-band radiometry technique. At this frequency the signal depends on SM and vegetation but is significantly affected by surface soil roughness. Quantifying the surface soil roughness on ground surface emissivity is a key issue to improve the quality of passive microwave large-scale SM products. The core of the SMOS algorithm permitting to provide SM operational data is the inversion of the L-band Microwave Emission of Biosphere (L-MEB) model that is the result of an extensive review of the current knowledge of the microwave emission. In this model, surface soil roughness is modeled with empirical parameters (Qr , Hr , Nrp , with p = H or V polarizations). These parameters have been estimated by numerous studies but only at local scale using in situ measurements or airborne campaigns. However, these local estimations are not representative at large scale and they are not consistent with the actual surface roughness conditions, especially in agricultural areas and can lead to important errors in the SM retrievals. In this study, a method has been developed to obtain the first global map of the roughness parameter, by combining the vegetation and soil roughness into one parameter, referred to as TR. SM and TR were retrieved globally using the SMOS L3 brigthness temperature and the forward emission model L-MEB for 2011. The effect of vegetation and roughness can be separated in TR using the LAI MODIS data to account for the vegetation. This map could lead to improve soil moisture retrievals for present and future microwave remote sensing missions such as SMOS and the Soil Moisture Active Passive (SMAP).

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

    Directory of Open Access Journals (Sweden)

    M. Nussbaum

    2018-01-01

    Full Text Available 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

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  14. Quantifying soil and critical zone variability in a forested catchment through digital soil mapping

    Science.gov (United States)

    Quantifying catchment scale soil property variation yields insights into critical zone evolution and function. The objective of this study was to quantify and predict the spatial distribution of soil properties within a high elevation forested catchment in southern AZ, USA using a combined set of di...

  15. Assessment and field-scale mapping of soil quality properties of a saline-sodic soil

    NARCIS (Netherlands)

    Corwin, D.L.; Kaffka, S.R.; Hopmans, J.W.; Mori, Y.; Groenigen, van J.W.; Kessel, van C.; Lesch, S.M.; Oster, J.S.

    2003-01-01

    Salt-affected soils could produce useful forages when irrigated with saline drainage water. To assess the productive potential and sustainability of using drainage water for forage production, a saline-sodic site (32.4 ha) in California's San Joaquin Valley was characterized for soil quality. The

  16. Digital Mapping of Toxic Metals in Qatari Soils Using Remote Sensing and Ancillary Data

    DEFF Research Database (Denmark)

    Peng, Yi; Bou Kheir, Rania; Adhikari, Kabindra

    2016-01-01

    After decades of mining and industrialization in Qatar, it is important to estimate their impact on soil pollution with toxic metals. The study utilized 300 topsoil (0–30 cm) samples, multi-spectral images (Landsat 8), spectral indices and environmental variables to model and map the spatial...

  17. USCS and the USDA Soil Classification System: Development of a Mapping Scheme

    Science.gov (United States)

    2015-03-01

    Development of a Mapping Scheme Co ld R eg io ns R es ea rc h an d En gi ne er in g La bo ra to ry Rubén A. García-Gaines and Susan...important to human daily living. A variety of disciplines ( geology , agriculture, engineering, etc.) require a sys- tematic categorization of soil, detailing

  18. Spectral analysis of charcoal on soils: Implications for wildland fire severity mapping methods

    Science.gov (United States)

    Alistair M. S. Smith; Jan U. H. Eitel; Andrew T. Hudak

    2010-01-01

    Recent studies in the Western United States have supported climate scenarios that predict a higher occurrence of large and severe wildfires. Knowledge of the severity is important to infer long-term biogeochemical, ecological, and societal impacts, but understanding the sensitivity of any severity mapping method to variations in soil type and increasing charcoal (char...

  19. The use of remote sensing in soil and terrain mapping: Review

    NARCIS (Netherlands)

    Mulder, V.L.; Bruin, de S.; Schaepman, M.E.; Mayr, T.

    2011-01-01

    This article reviews the use of optical and microwave remote sensing data for soil and terrain mapping with emphasis on applications at regional and coarser scales. Remote sensing is expected to offer possibilities for improving incomplete spatial and thematic coverage of current regional and global

  20. An assessment of the accuracy of soil map of Kwara state, Nigeria ...

    African Journals Online (AJOL)

    The variability of particle size fraction, pH, organic matter, total nitrogen, available phosphorus, exchangeable Ca, Mg, Na, exchangeable acidity, effective cation exchange capacity (CEC), base saturation, extractable Fe, Mn and Zn contents within and among the three major soil mapping units delineated in Kwara State, ...

  1. Mapping soil moisture across an irrigated field using electromagnetic conductivity imaging

    Science.gov (United States)

    The ability to measure and map volumetric soil water theta quickly and accurately is important in irrigated agriculture. However, the traditional approach of using thermogravimetric moisture (w) and converting this to theta using measurements of bulk density (theta – cm3/cm3) is laborious and time c...

  2. Using ERS-2 and ALOS PALSAR images for soil moisture and inundation mapping in Cyprus

    Science.gov (United States)

    Alexakis, Dimitrios D.; Agapiou, Athos; Themistocleous, Kyriacos; Retalis, Adrianos; Hadjimitsis, Diofantos G.

    2013-08-01

    Floods are among the most frequent and costly natural disasters in terms of human and economic loss and are considered to be a weather-related natural disaster. This study strives to highlight the potential of active remote sensing imagery in flood inundation monitoring and mapping in a catchment area in Cyprus (Yialias river). GeoEye-1 and ASTER images were employed to create updated Land use /Land cover maps of the study area. Following, the application of fully polarimetric (ALOS PALSAR) and dual polarimetric (ERS - 2) Synthetic Aperture Radar (SAR) data for soil moisture and inundation mapping is presented. For this purpose 2 ALOS PALSAR images and 3 ERS-2 images were acquired. This study offers an integrated methodology by the use of multi-angle radar images to estimate roughness and soil moisture without the use of ancillary field data such as field measurements. The relationship between soil moisture and backscattering coefficient was thoroughly studied and linear regression models were developed to predict future flood inundation events. Multi-temporal FCC images, classification, image fusion, moisture indices, texture and PCA analysis were employed to assist soil moisture mapping. Certain land cover classes were characterized as flood prone areas according to statistics of their signal response. The results will be incorporated in an integrated flood risk assessment model of Yialias catchment area.

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

    Science.gov (United States)

    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.

  4. GIS-based soil liquefaction susceptibility map of Mumbai city for earthquake events

    Science.gov (United States)

    Mhaske, Sumedh Yamaji; Choudhury, Deepankar

    2010-03-01

    The problem of liquefaction of soil during seismic event is one of the important topics in the field of Geotechnical Earthquake Engineering. Liquefaction of soil is generally occurs in loose cohesionless saturated soil when pore water pressure increases suddenly due to induced ground motion and shear strength of soil decreases to zero and leading the structure situated above to undergo a large settlement, or failure. The failures took place due to liquefaction induced soil movement spread over few square km area continuously. Hence this is a problem where spatial variation involves and to represent this spatial variation Geographic Information System (GIS) is very useful in decision making about the area subjected to liquefaction. In this paper, GIS software GRAM++ is used to prepare soil liquefaction susceptibility map for entire Mumbai city in India by marking three zones viz. critically liquefiable soil, moderately liquefiable soil and non liquefiable soil. Extensive field borehole test data for groundwater depth, standard penetration test (SPT) blow counts, dry density, wet density and specific gravity, etc. have been collected from different parts of Mumbai. Simplified procedure of Youd et al. (2001) is used for calculation of factor of safety against soil liquefaction potential. Mumbai city and suburban area are formed by reclaiming lands around seven islands since 1865 till current date and still it is progressing in the area such as Navi Mumbai and beyond Borivali to Mira road suburban area. The factors of safety against soil liquefaction were determined for earthquake moment magnitude ranging from Mw = 5.0 to 7.5. It is found that the areas like Borivali, Malad, Dahisar, Bhandup may prone to liquefaction for earthquake moment magnitude ranging from Mw = 5.0 to 7.5. The liquefaction susceptibility maps were created by using GRAM++ by showing the areas where the factor of safety against the soil liquefaction is less than one. Proposed liquefaction

  5. Method for the Preparation of Hazard Map in Urban Area Using Soil Depth and Groundwater Level

    Science.gov (United States)

    Kim, Sung-Wook; Choi, Eun-Kyeong; Cho, Jin Woo; Lee, Ju-Hyoung

    2017-04-01

    The hazard maps for predicting collapse on natural slopes consists of a combination of topographic, hydrological, and geological factors. Topographic factors are extracted from DEM, including aspect, slope, curvature, and topographic index. Hydrological factors, such as distance to drainage, drainage density, stream-power index, and wetness index are most important factors for slope instability. However, most of the urban areas are located on the plains and it is difficult to apply the hazard map using the topography and hydrological factors. In order to evaluate the risk of collapse of flat and low slope areas, soil depth and groundwater level data were collected and used as a factor for interpretation. In addition, the reliability of the hazard map was compared with the disaster history of the study area (Gangnam-gu and Yeouido district). In the disaster map of the disaster prevention agency, the urban area was mostly classified as the stable area and did not reflect the collapse history. Soil depth, drainage conditions and groundwater level obtained from boreholes were added as input data of hazard map, and disaster vulnerability increased at the location where the actual collapse points. In the study area where damage occurred, the moderate and low grades of the vulnerability of previous hazard map were 12% and 88%, respectively. While, the improved map showed 2% high grade, moderate grade 29%, low grade 66% and very low grade 2%. These results were similar to actual damage. Keywords: hazard map, urban area, soil depth, ground water level Acknowledgement This research was supported by a Grant from a Strategic Research Project (Horizontal Drilling and Stabilization Technologies for Urban Search and Rescue (US&R) Operation) funded by the Korea Institute of Civil Engineering and Building Technology.

  6. Improving the performance of digital soil maps by the application of remotely sensed data used in terroir mapping - case study of the Tokaj wine region

    Science.gov (United States)

    Takács, Katalin; Laborczi, Annamária; Lukácsy, György; Pásztor, László

    2015-04-01

    The aim of the soil mapping is to explore and visualize the spatial extension and variability of the thematic knowledge about soils. Soil maps are thematic maps, which can present information about the primary or derivative soil characteristics, soil classes and knowledge about the processes, function and services of the soils. The method for information obtaining about soils is sampling which results only point data and should be spatially extended by a properly chosen process. The digital soil mapping (DSM) method uses environmental auxiliary variables for the spatial extension. These variables should be in direct or indirect relation with the target soil characteristic and should provide full coverage for the target area. Environmental variables can be derived from digital elevation models, land cover data or satellite images which can be obtained most efficiently with remote sensing methods. The soil-landscape relation can be modelled by geostatistical and data mining methods based the soil data and auxiliary variables. The study area is Tokaj wine region (approximately 400 km2) which is located in Northeast-Hungary, in Tokaj Mountains. Soil data is available for 200 sampling points. The terrain variables - such as elevation, slope, aspect and other derivatives - are derived from a relatively high resolution digital elevation model (DEM; 1 m), that was generated by LiDAR. The other environmental variables - such as land cover, NDVI - are prepared based on Landsat images which are acquired at different seasons in line with vegetation phenology and soil coverage. The target maps are prepared by digital soil mapping methods. For the analysis of the relationship between soil sampling data and the auxiliary variables different geostatistical methods are used to choose the most appropriate environmental variables for the spatial modelling. The spatial extension of point data are performed by interpolation methods. For summarizing the main aim of this study is to test

  7. Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

    Directory of Open Access Journals (Sweden)

    César da Silva Chagas

    2013-04-01

    Full Text Available Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI, derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs was greater than of the classic Maximum Likelihood Classifier (MLC. Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 % was superior to the MLC map (57.94 %. The main errors when using the two classifiers were caused by: a the geological heterogeneity of the area coupled with problems related to the geological map; b the depth of lithic contact and/or rock exposure, and c problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

  8. Mapping spatial variability of soil salinity in a coastal paddy field based on electromagnetic sensors.

    Science.gov (United States)

    Guo, Yan; Huang, Jingyi; Shi, Zhou; Li, Hongyi

    2015-01-01

    In coastal China, there is an urgent need to increase land area for agricultural production and urban development, where there is a rapid growing population. One solution is land reclamation from coastal tidelands, but soil salinization is problematic. As such, it is very important to characterize and map the within-field variability of soil salinity in space and time. Conventional methods are often time-consuming, expensive, labor-intensive, and unpractical. Fortunately, proximal sensing has become an important technology in characterizing within-field spatial variability. In this study, we employed the EM38 to study spatial variability of soil salinity in a coastal paddy field. Significant correlation relationship between ECa and EC1:5 (i.e. r >0.9) allowed us to use EM38 data to characterize the spatial variability of soil salinity. Geostatistical methods were used to determine the horizontal spatio-temporal variability of soil salinity over three consecutive years. The study found that the distribution of salinity was heterogeneous and the leaching of salts was more significant in the edges of the study field. By inverting the EM38 data using a Quasi-3D inversion algorithm, the vertical spatio-temporal variability of soil salinity was determined and the leaching of salts over time was easily identified. The methodology of this study can be used as guidance for researchers interested in understanding soil salinity development as well as land managers aiming for effective soil salinity monitoring and management practices. In order to better characterize the variations in soil salinity to a deeper soil profile, the deeper mode of EM38 (i.e., EM38v) as well as other EMI instruments (e.g. DUALEM-421) can be incorporated to conduct Quasi-3D inversions for deeper soil profiles.

  9. Mapping spatial variability of soil salinity in a coastal paddy field based on electromagnetic sensors.

    Directory of Open Access Journals (Sweden)

    Yan Guo

    Full Text Available In coastal China, there is an urgent need to increase land area for agricultural production and urban development, where there is a rapid growing population. One solution is land reclamation from coastal tidelands, but soil salinization is problematic. As such, it is very important to characterize and map the within-field variability of soil salinity in space and time. Conventional methods are often time-consuming, expensive, labor-intensive, and unpractical. Fortunately, proximal sensing has become an important technology in characterizing within-field spatial variability. In this study, we employed the EM38 to study spatial variability of soil salinity in a coastal paddy field. Significant correlation relationship between ECa and EC1:5 (i.e. r >0.9 allowed us to use EM38 data to characterize the spatial variability of soil salinity. Geostatistical methods were used to determine the horizontal spatio-temporal variability of soil salinity over three consecutive years. The study found that the distribution of salinity was heterogeneous and the leaching of salts was more significant in the edges of the study field. By inverting the EM38 data using a Quasi-3D inversion algorithm, the vertical spatio-temporal variability of soil salinity was determined and the leaching of salts over time was easily identified. The methodology of this study can be used as guidance for researchers interested in understanding soil salinity development as well as land managers aiming for effective soil salinity monitoring and management practices. In order to better characterize the variations in soil salinity to a deeper soil profile, the deeper mode of EM38 (i.e., EM38v as well as other EMI instruments (e.g. DUALEM-421 can be incorporated to conduct Quasi-3D inversions for deeper soil profiles.

  10. A new detailed map of total phosphorus stocks in Australian soil.

    Science.gov (United States)

    Viscarra Rossel, Raphael A; Bui, Elisabeth N

    2016-01-15

    Accurate data are needed to effectively monitor environmental condition, and develop sound policies to plan for the future. Globally, current estimates of soil total phosphorus (P) stocks are very uncertain because they are derived from sparse data, with large gaps over many areas of the Earth. Here, we derive spatially explicit estimates, and their uncertainty, of the distribution and stock of total P in Australian soil. Data from several sources were harmonized to produce the most comprehensive inventory of total P in soil of the continent. They were used to produce fine spatial resolution continental maps of total P in six depth layers by combining the bootstrap, a decision tree with piecewise regression on environmental variables and geostatistical modelling of residuals. Values of percent total P were predicted at the nodes of a 3-arcsecond (approximately 90 m) grid and mapped together with their uncertainties. We combined these predictions with those for bulk density and mapped the total soil P stock in the 0-30 cm layer over the whole of Australia. The average amount of P in Australian topsoil is estimated to be 0.98 t ha(-1) with 90% confidence limits of 0.2 and 4.2 t ha(-1). The total stock of P in the 0-30 cm layer of soil for the continent is 0.91 Gt with 90% confidence limits of 0.19 and 3.9 Gt. The estimates are the most reliable approximation of the stock of total P in Australian soil to date. They could help improve ecological models, guide the formulation of policy around food and water security, biodiversity and conservation, inform future sampling for inventory, guide the design of monitoring networks, and provide a benchmark against which to assess the impact of changes in land cover, land use and management and climate on soil P stocks and water quality in Australia. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

  11. Remote Sensing Soil Salinity Map for the San Joaquin Vally, California

    Science.gov (United States)

    Scudiero, E.; Skaggs, T. H.; Anderson, R. G.; Corwin, D. L.

    2015-12-01

    Soil salinization is a major natural hazard to worldwide agriculture. We present a remote imagery approach that maps salinity within a range (i.e., salinities less than 20 dS m-1, when measured as the electrical conductivity of the soil saturation extract), accuracy, and resolution most relevant to agriculture. A case study is presented for the western San Joaquin Valley (WSJV), California, USA (~870,000 ha of farmland) using multi-year Landsat 7 ETM+ canopy reflectance and the Canopy Response Salinity Index (CRSI). Highly detailed salinity maps for 22 fields (542 ha) established from apparent soil electrical conductivity directed sampling were used as ground-truth (sampled in 2013), totaling over 5000 pixels (30×30 m) with salinity values in the range of 0 to 35.2 dS m-1. Multi-year maximum values of CRSI were used to model soil salinity. In addition, soil type, elevation, meteorological data, and crop type were evaluated as covariates. The fitted model (R2=0.73) was validated: i) with a spatial k-folds (i.e., leave-one-field-out) cross-validation (R2=0.61), ii) versus salinity data from three independent fields (sampled in 2013 and 2014), and iii) by determining the accuracy of the qualitative classification of white crusted land as extremely-saline soils. The effect of land use change is evaluated over 2396 ha in the Broadview Water District from a comparison of salinity mapped in 1991 with salinity predicted in 2013 from the fitted model. From 1991 to 2013 salinity increased significantly over the selected study site, bringing attention to potential negative effects on soil quality of shifting from irrigated agriculture to fallow-land. This is cause for concern since over the 3 years of California's drought (2010-2013) the fallow land in the WSJV increased from 12.7% to 21.6%, due to drastic reduction in water allocations to farmers.

  12. Visible-near infrared spectroscopy as a tool to improve mapping of soil properties

    Science.gov (United States)

    Evgrafova, Alevtina; Kühnel, Anna; Bogner, Christina; Haase, Ina; Shibistova, Olga; Guggenberger, Georg; Tananaev, Nikita; Sauheitl, Leopold; Spielvogel, Sandra

    2017-04-01

    Spectroscopic measurements, which are non-destructive, precise and rapid, can be used to predict soil properties and help estimate the spatial variability of soil properties at the pedon scale. These estimations are required for quantifying soil properties with higher precision, identifying the changes in soil properties and ecosystem response to climate change as well as increasing the estimation accuracy of soil-related models. Our objectives were to (i) predict soil properties for nested samples (n = 296) using the laboratory-based visible-near infrared (vis-NIR) spectra of air-dried (sieved through a 2-mm sieve and ground with an agate mortar prior to the elemental analysis. The soil organic carbon and total nitrogen concentrations (in %) were determined using a dry combustion method on the Vario EL cube analyzer (Elementar Analysensysteme GmbH, Germany). Inorganic C was removed from the mineral soil samples with pH values higher than 7 prior to the elemental analysis using the volatilization method (HCl, 6 hours). The pH of soil samples was measured in 0.01 M CaCl2 using a 1:2 soil:solution ratio. However, for soil sample with a high in organic matter content, a 1:10 ratio was applied. We also measured oxalate and dithionite extracted iron, aluminum and manganese oxides and hydroxides using inductively coupled plasma optical emission spectroscopy (Varian Vista MPX ICP-OES, Agilent Technologies, USA). We predicted the above-mentioned soil properties for all nested samples using partial least squares regression, which was performed using R program. We can conclude that vis-NIR spectroscopy can be used effectively in order to describe, estimate and further map the spatial patterns of soil properties using geostatistical methods. This research could also help to improve the global soil spectral library taking into account that only few previous applications of vis-NIR spectroscopy were conducted on permafrost-affected soils of Northern Siberia. Keywords: Visible

  13. Digital mapping of soil related common European biophysical criteria used for the identification of Less Favoured Areas in Hungary

    Science.gov (United States)

    Pásztor, László; Szabó, József; Bakacsi, Zsófia

    2010-05-01

    One of the main objectives of the EU's Common Agricultural Policy is to encourage maintaining agricultural production in less favoured areas (LFA) in order to sustain agricultural production and use natural resources, in such a way to secure both stable production and income to farmers and to protect the environment. LFA assignment has both ecological and severe economical aspects. Recently the delimitation of LFAs is suggested to be carried out by using common biophysical diagnostic criteria on low soil productivity and poor climate conditions all over Europe. The criterion system was elaborated by JRC and its operational implementation comes under member state competence. This process requires the existence of an adequate national spatial soil information system with appropriate data structure and spatial resolution as well as a proper methodology for its analysis. Hungary possesses an appropriate nationwide, 1:25,000 scale legacy data set originating from the national soil mapping project, which was initiated and led by Kreybig. This national survey was based on field and laboratory soil analyses and at the same time serving practical purposes. Its objective was the preparation of a map series which gives an insight to the geographical site and extent of soil conditions and soil properties for the production directing authorities, agricultural policy-makers, farmers, and the research institutes related to production problems. The similarity between the objectives of the old national mapping and those of the present European activities is remarkable. In the fifties, when the survey was completed, Hungary was the first in the world to have 1:25,000 scale soil information for the whole country. Overall chemical and physical soil properties of the soil root zone featuring soil patches were identified for croplands. Three characteristics were attributed to soil mapping units and displayed on the maps; further soil properties were determined and measured in soil

  14. Evaluation of freely available ancillary data used for detailed soil mapping in Brazil

    Science.gov (United States)

    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

  15. Digital soil mapping at pilot sites in the northwest coast of Egypt: A multinomial logistic regression approach

    Directory of Open Access Journals (Sweden)

    Fawzy Hassan Abdel-Kader

    2011-06-01

    Full Text Available The study examines a digital soil mapping approach for the production of soil maps by using multinomial logistic regression on soil and terrain information at pilot sites in the Northwestern Coastal region of Egypt. The aim is to reproduce the original map and predict soil distribution in the adherent landscape. Reference soil maps produced by conventional methods at Omayed and Nagamish areas were used. Spectral and terrain parameters were calculated and logit models of the soil classes were developed. Predicted soil classes’ maps were produced. Software’s IDRISI/SAGA/SATISTCA/SPSS were used. The terrain and spectral parameters were found to be significantly influential and the selection of the land surfaces predictors was satisfactory. The McFadden pseudo R-squares ranged from 0.473 to 0.496. The most significant terrain parameters influencing the spatial distribution of the soil classes were elevation, valley depth, multiresolution ridgetop flatness index, multiresolution valley-bottom flatness index, and SAGA wetness index. However, the most influential spectral parameters are the first two principal components of the six Landsat Enhanced Thematic Mapper bands. The overall accuracy of the predicted soil maps ranged from 72% to 74% with a Kappa Index ranging from 0.62 to 0.64. The developed probability models were successfully used to predict the spatial distribution of the soil mapping units at pixel resolutions of 28.5 m × 28.5 m and 90 m × 90 m at adjacent unvisited areas at Matrouh and Alamin. The developed methodology could contribute to the allocation and to the soil digital mapping and management of new expansion sites in remote desert areas of Egypt.

  16. Three-Dimensional Mapping of Soil Organic Carbon by Combining Kriging Method with Profile Depth Function.

    Science.gov (United States)

    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.

  17. Three-Dimensional Mapping of Soil Organic Carbon by Combining Kriging Method with Profile Depth Function.

    Directory of Open Access Journals (Sweden)

    Chong Chen

    Full Text Available 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.

  18. Digital Mapping of Toxic Metals in Qatari Soils Using Remote Sensing and Ancillary Data

    Directory of Open Access Journals (Sweden)

    Yi Peng

    2016-12-01

    Full Text Available After decades of mining and industrialization in Qatar, it is important to estimate their impact on soil pollution with toxic metals. The study utilized 300 topsoil (0–30 cm samples, multi-spectral images (Landsat 8, spectral indices and environmental variables to model and map the spatial distribution of arsenic (As, chromium (Cr, nickel (Ni, copper (Cu, lead (Pb and zinc (Zn in Qatari soils. The prediction model used condition-based rules generated in the Cubist tool. In terms of R2 and the ratio of performance to interquartile distance (RPIQ, the models showed good predictive capabilities for all elements. Of all of the prediction results, Cu had the highest R2 = 0.74, followed by As > Pb > Cr > Zn > Ni. This study found that all of the models only chose images from January and February as predictors, which indicates that images from these two months are important for soil toxic metals’ monitoring in arid soils, due to the climate and the vegetation cover during this season. Topsoil maps of the six toxic metals were generated. The maps can be used to prioritize the choice of remediation measures and can be applied to other arid areas of similar environmental/socio-economic conditions and pollution causes.

  19. Louisiana State Soil Geographic, General Soil Map, Geographic NAD83, NWRC (1998) [statsgo_soils_NWRC_1998

    Data.gov (United States)

    Louisiana Geographic Information Center — This data set contains vector line map information. The vector data contain selected base categories of geographic features, and characteristics of these features,...

  20. Probability maps as a way to communicate uncertainty in soil texture classes at landscape scale

    Science.gov (United States)

    Rawlins, Barry; Lark, Murray

    2014-05-01

    Soil texture is critical for a range of functions and degradation threats including soil carbon cycling, hydrology and erosion. The texture of a soil at a point in the landscape is often expressed as a class in a soil texture triangle. The boundaries between these classes are based on the proportions of sand, silt and clay-sized particles. Soils are typically attributed to a single class, without considering the uncertainty associated with class membership. We demonstrate an approach for communicating uncertainty in spatial prediction of soil texture classes using a database of 2600 measurements of particle size distribution across part of England. A subset of these measurements included repeated analyses of separate aliquots from the same sample from which we could compute uncertainties associated with analytical and subsampling variance to include in our uncertainty analysis. After appropriate transformation for compositional variables, the spatial variation of the soil particle size classes was modelled geostatistically using robust variogram estimators to produce a validated linear model of coregionalization. This was then used to predict the composition of topsoil at the nodes of a fine grid. The predictions were backtransformed to the original scales of measurement by a Monte Carlo integration over the prediction distribution on the transformed scale. This approach allowed the probability to be computed for each class in the soil texture classification, at each node on the grid. The probability of each class, and derived information such as the class of maximum probability could therefore be mapped. We validated the predictions at a set of randomly sampled locations. We consider this technique has the potential to improve the communication of uncertainty associated with the application of soil texture classifications in soil science.

  1. Soil magnetic susceptibility mapping as a pollution and provenance tool: an example from southern New Zealand

    Science.gov (United States)

    Martin, A. P.; Ohneiser, C.; Turnbull, R. E.; Strong, D. T.; Demler, S.

    2018-02-01

    The presence or absence, degree and variation of heavy metal contamination in New Zealand soils is a matter of ongoing debate as it affects soil quality, agriculture and human health. In many instances, however, the soil heavy metal concentration data do not exist to answer these questions and the debate is ongoing. To address this, magnetic susceptibility (a common proxy for heavy metal contamination) values were measured in topsoil (0-30 cm) and subsoil (50-70 cm) at grid sites spaced at 8 km intervals across ca. 20 000 km2 of southern New Zealand. Samples were measured for both mass- and volume-specific magnetic susceptibility, with results being strongly, positively correlated. Three different methods of determining anomalies were applied to the data including the topsoil-subsoil difference method, Tukey boxplot method and geoaccumulation index method, with each method filtering out progressively more anomalies. Additional soil magnetic (hysteresis, isothermal remanence and thermomagnetic) measurements were made on a select subset of samples from anomalous sites. Magnetite is the dominant remanence carrying mineral, and magnetic susceptibility is governed by that minerals concentration in soils, rather than mineral type. All except two anomalous sites have a dominant geogenic source (cf. anthropogenic). By proxy, heavy metal contamination in southern New Zealand soils is minimal, making them relatively pristine. The provenance of the magnetic minerals in the anomalous sites can be traced back to likely sources in outcrops of igneous rocks within the same catchment, terrane or rock type: a distance of <100 km but frequently <1 km. Soil provenance is a key step when mapping element or isotopic distribution, vectoring to mineralization or studying soil for agricultural suitability, water quality or environmental regulation. Measuring soil magnetic susceptibility is a useful, quick and inexpensive tool that usefully supplements soil geochemical data.

  2. 3D Digital Mapping of Soil Cation Exchange Capacity in Dorud, Lorestan Province

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    R. Taghizadeh Mehrjerdi

    2015-06-01

    Full Text Available There is an increasing demand for reliable large-scale soil datato meet the requirements of models for planning of land-usesystems, characterization of soil pollution, and prediction ofland degradation. Cation exchangecapacity (CEC is among the most important soil propertiesthat are required in soil databases. This paper applied a novel method for whole-soil profile predictions of CEC (to 1 m across Dorudlocated in LorestanProvince. At present research, we combined equal-area spline depth functions with digital soil mapping techniques to predict the vertical and lateral variations of CEC across the study area where limited soil information exists (103 soil profiles. To model the relationship between CEC and environmental factors (i.e. Representative soil forming factors, derived from a digital elevation model and Landsat imagery, a regression tree was applied. Results indicated that some auxiliary data had more influence on the prediction model (i.e. B3 and modified catchment area. Our results also confirmed the regression tree model predicted target variable at the five specific depths with coefficient of determination of 0.84, 0.84, 0.84, 0.66, 0.27 and root mean square of 1.75, 1.84, 1.84, 2.11, and 2.16, respectively. Results showed a reasonable R2 in first four depths ranged from 0.66 to 0.84; while, it decreases to 0.27 in the last depth. Our results also confirmed that the regression tree as a predictive model, digital soil mappingtechniqueand equal area splinesare powerful tools to predict lateral and vertical variation of CEC.

  3. Geochemical and mineralogical maps for soils of the conterminous United States

    Science.gov (United States)

    Smith, David B.; Cannon, William F.; Woodruff, Laurel G.; Solano, Federico; Ellefsen, Karl J.

    2014-01-01

    The U.S. Geological Survey began sampling in 2007 for a low-density (1 site per 1,600 square kilometers, 4,857 sites) geochemical and mineralogical survey of soils in the conterminous United States as part of the North American Soil Geochemical Landscapes Project. The sampling protocol for the national-scale survey included, at each site, a sample from a depth of 0 to 5 centimeters, a composite of the soil A horizon, and a deeper sample from the soil C horizon or, if the top of the C horizon was at a depth greater than 1 meter, a sample from a depth of approximately 80–100 centimeters. The mineralogical components in the samples from the soil A and C horizons were determined by a quantitative X-ray diffraction method using Rietveld refinement. Sampling in the conterminous United States was completed in 2010, with chemical and mineralogical analyses completed in May 2013. The resulting data set provides an estimate of the abundance and spatial distribution of chemical elements and minerals in soils of the conterminous United States and represents a baseline for soil geochemistry and mineralogy against which future changes may be recognized and quantified. This report releases geochemical and mineralogical maps along with a histogram, boxplot, and empirical cumulative distribution function plot for each element or mineral.

  4. Yield mapping, soil fertility and tree gaps in an orange orchard

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    José Paulo Molin

    2012-12-01

    Full Text Available The current high competition on Citrus industry demands from growers new management technologies for superior efficiency and sustainability. In this context, precision agriculture (PA has developed techniques based on yield mapping and management systems that recognize field spatial variability, which contribute to increase profitability of commercial crops. Because spatial variability is often not perceived the orange orchards are still managed as uniform and adoption of PA technology on citrus farms is low. Thus, the objective of the present study was to characterize the spatial variability of three factors: fruit yield, soil fertility and occurrence of plant gaps caused by either citrus blight or huanglongbing (HLB in a commercial Valencia orchard in Brotas, São Paulo State, Brazil. Data from volume, geographic coordinates and representative area of the bags used on harvest were recorded to generate yield points that were then interpolated to produce the yield map. Soil chemical characteristics were studied by analyzing samples collected along planting rows and inter-rows in 24 points distributed in the field. A map of density of tree gaps was produced by georeferencing individual gaps and later by counting the number of gaps within 500 m² cells. Data were submitted to statistical and geostatistical analyses. A t test was used to compare means of soil chemical characteristics between sampling regions. High variation on yield and density of tree gaps was observed from the maps. It was also demonstrated overlapping regions of high density of plant absence and low fruit yield. Soil fertility varied depending on the sampling region in the orchard. The spatial variability found on yield, soil fertility and on disease occurrence demonstrated the importance to adopt site specific nutrient management and disease control as tools to guarantee efficiency of fruit production.

  5. LBA-ECO TG-05 NPP, Carbon Pool, Soil Characteristics, Soil Gas Flux Maps of Brazil

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    National Aeronautics and Space Administration — This data set provides maps produced from model output data from the National Aeronautics and Space Administration-Carnegie Ames Stanford Approach (NASA-CASA) model...

  6. LBA-ECO TG-05 NPP, Carbon Pool, Soil Characteristics, Soil Gas Flux Maps of Brazil

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set provides maps produced from model output data from the National Aeronautics and Space Administration-Carnegie Ames Stanford Approach...

  7. Using Environmental Variables for Studying of the Quality of Sampling in Soil Mapping

    Directory of Open Access Journals (Sweden)

    A. Jafari

    2016-02-01

    Full Text Available Introduction: Methods of soil survey are generally empirical and based on the mental development of the surveyor, correlating soil with underlying geology, landforms, vegetation and air-photo interpretation. Since there are no statistical criteria for traditional soil sampling; this may lead to bias in the areas being sampled. In digital soil mapping, soil samples may be used to elaborate quantitative relationships or models between soil attributes and soil covariates. Because the relationships are based on the soil observations, the quality of the resulting soil map depends also on the soil observation quality. An appropriate sampling design for digital soil mapping depends on how much data is available and where the data is located. Some statistical methods have been developed for optimizing data sampling for soil surveys. Some of these methods deal with the use of ancillary information. The purpose of this study was to evaluate the quality of sampling of existing data. Materials and Methods: The study area is located in the central basin of the Iranian plateau (Figure 1. The geologic infrastructure of the area is mainly Cretaceous limestone, Mesozoic shale and sandstone. Air photo interpretation (API was used to differentiate geomorphic patterns based on their formation processes, general structure and morphometry. The patterns were differentiated through a nested geomorphic hierarchy (Fig. 2. A four-level geomorphic hierarchy is used to breakdown the complexity of different landscapes of the study area. In the lower level of the hierarchy, the geomorphic surfaces, which were formed by a unique process during a specific geologic time, were defined. A stratified sampling scheme was designed based on geomorphic mapping. In the stratified simple random sampling, the area was divided into sub-areas referred to as strata based on geomorphic surfaces, and within each stratum, sampling locations were randomly selected (Figure 2. This resulted in 191

  8. Multifractal and Singularity Maps of soil surface moisture distribution derived from 2D image analysis.

    Science.gov (United States)

    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

  9. Mapping Surface Soil Moisture With Synthetic Aperture Radar Data and Basin Indexes

    Science.gov (United States)

    Yilmaz, M.; Sorman, A.; Sorman, U.

    2008-12-01

    The soil moisture condition of a watershed plays a significant role in separation of infiltration and surface runoff, and hence is a key parameter for the majority of physical hydrological models. Due to the large difference in dielectric constants of dry soil and water, microwave remote sensing (particularly the commonly available synthetic aperture radar) is a potential tool for such studies. The main aim of this study is to compute a distributed soil moisture map of a catchment, which can be input to a hydrological model. For this purpose, nine field trips are performed and point surface soil moisture values are collected with a Time Domain Reflectometer. The field studies, which are carried out on a small catchment in western Anatolia, are planned to match radar image acquisitions and accomplished over a water year. First, the Dubois Model, a physical backscatter model is utilized in the reverse order to compute soil surface roughness values. This is accomplished for the field study dates which have two radar image acquisitions and with sparse vegetation cover. Then the first relationship of this study, between observed radar backscatter values and computed roughness values, is established with a correlation coefficient of 0.78. For bare soil surfaces, local incidence angle, soil moisture and roughness are the most dominant parameters effecting radar backscatter. After computing the incidence angle map of the study area, the second relationship, between observed radar backscatter values and the three governing parameters, is determined with a correlation coefficient of 0.87. The third and the last relationship of the study is estimated between the measured point soil moisture values and two basin indexes; topographic and solar radiation. In the last part of the study, the established three relationships, which are derived for point moisture measurements, are used to compute the soil moisture map of the whole catchment. This process is handled separately for the

  10. Landmarks of History of Soil Science in Sri Lanka

    Science.gov (United States)

    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

  11. Soil legacy data rescue via GlobalSoilMap and other international and national initiatives

    NARCIS (Netherlands)

    Arrouays, Dominique; Leenaars, Johan G.B.; Richer de Forges, Anne C.; Adhikari, Kabindra; Ballabio, Cristiano; Greve, Mogens H.; Grundy, Mike; Guerrero, Eliseo; Hempel, Jon; Hengl, Tom; Heuvelink, Gerard; Batjes, Niels; Carvalho Ribeiro, Eloi; Hartemink, Alfred; Okx, J.P.

    2017-01-01

    Legacy soil data have been produced over 70 years in nearly all countries of the world. Unfortunately, data, information and knowledge are still currently fragmented and at risk of getting lost if they remain in a paper format. To process this legacy data into consistent, spatially explicit and

  12. Compilation of a soil map for Nigeria: a nation-wide soil resource ...

    African Journals Online (AJOL)

    This paper presents the results of a nation-wide soil and land form inventory of Nigeria. The data compilation was conducted in the framework of two projects with the objective to calculate agricultural production potential under different input levels and assess the water erosion hazard. The information on spatial distribution ...

  13. The importance of magnetic methods for soil mapping and process modelling. Case study in Ukraine

    Science.gov (United States)

    Menshov, Oleksandr; Pereira, Paulo; Kruglov, Oleksandr; Sukhorada, Anatoliy

    2016-04-01

    The correct planning of agriculture areas is fundamental for a sustainable future in Ukraine. After the recent political problems in Ukraine, new challenges emerged regarding sustainability questions. At the same time the soil mapping and modelling are intensively developing all over the world (Pereira et al., 2015; Brevik et al., in press). Magnetic susceptibility (MS) methods are low cost and accurate for the developing maps of agricultural areas, fundamental for Ukrain's economy.This allow to colleact a great amount of soil data, usefull for a better understading of the spatial distribution of soil properties. Recently, this method have been applied in other works in Ukraine and elsewhere (Jordanova et al., 2011; Menshov et al., 2015). The objective of this work is to study the spatial distribution of MS and humus content on the topsoils (0-5 cm) in two different areas. The first is located in Poltava region and the second in Kharkiv region. The results showed that MS depends of soil type, topography and anthropogenic influence. For the interpretation of MS spatial distribution in top soil we consider the frequency and time after the last tillage, tilth depth, fertilizing, and the puddling regarding the vehicle model. On average the soil MS of the top soil of these two cases is about 30-70×10-8 m3/kg. In Poltava region not disturbed soil has on average MS values of 40-50×10-8 m3/kg, for Kharkiv region 50-60×10-8 m3/kg. The tilled soil of Poltava region has on average an MS of 60×10-8 m3/kg, and 70×10-8 m3/kg in Kharkiv region. MS is higher in non-tilled soils than in the tilled ones. The correlation between MS and soil humus content is very high ( up to 0.90) in both cases. Breivik, E., Baumgarten, A., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Jordán, A. Soil mapping, classification, and modelling: history and future directions. Geoderma (in press), doi:10.1016/j.geoderma.2015.05.017 Jordanova D., Jordanova N., Atanasova A., Tsacheva T., Petrov P

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

    Science.gov (United States)

    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

  15. A provisional fixed partial denture for an implant prosthesis.

    Science.gov (United States)

    Hansen, Paul A; Kim, Eunghwan

    2010-01-01

    This article presents a technique for fabricating an esthetic provisional restoration on multiple implants. Fabricating a provisional restoration allows the dentist to make a replica of the desired restoration. The incisal edge can be placed for esthetics and function in the new provisional restoration, allowing patients to evaluate comfort and test their ability to speak with the contour of the provisional restoration. Patients can evaluate both the ease of cleaning the restoration and how tissue esthetics can be duplicated to their satisfaction. By adding acrylic resin to or removing it from the provisional, the dentist can easily change the restoration until the patient is satisfied with the esthetic and functional result. This technique will allow the dentist to fabricate the provisional prosthesis quickly, while the patient is in the chair.

  16. Mapping and determinism of soil microbial community distribution across an agricultural landscape.

    Science.gov (United States)

    Constancias, Florentin; Terrat, Sébastien; Saby, Nicolas P A; Horrigue, Walid; Villerd, Jean; Guillemin, Jean-Philippe; Biju-Duval, Luc; Nowak, Virginie; Dequiedt, Samuel; Ranjard, Lionel; Chemidlin Prévost-Bouré, Nicolas

    2015-06-01

    Despite the relevance of landscape, regarding the spatial patterning of microbial communities and the relative influence of environmental parameters versus human activities, few investigations have been conducted at this scale. Here, we used a systematic grid to characterize the distribution of soil microbial communities at 278 sites across a monitored agricultural landscape of 13 km². Molecular microbial biomass was estimated by soil DNA recovery and bacterial diversity by 16S rRNA gene pyrosequencing. Geostatistics provided the first maps of microbial community at this scale and revealed a heterogeneous but spatially structured distribution of microbial biomass and diversity with patches of several hundreds of meters. Variance partitioning revealed that both microbial abundance and bacterial diversity distribution were highly dependent of soil properties and land use (total variance explained ranged between 55% and 78%). Microbial biomass and bacterial richness distributions were mainly explained by soil pH and texture whereas bacterial evenness distribution was mainly related to land management. Bacterial diversity (richness, evenness, and Shannon index) was positively influenced by cropping intensity and especially by soil tillage, resulting in spots of low microbial diversity in soils under forest management. Spatial descriptors also explained a small but significant portion of the microbial distribution suggesting that landscape configuration also shapes microbial biomass and bacterial diversity. © 2015 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

  17. Soil pH mapping with an on-the-go sensor.

    Science.gov (United States)

    Schirrmann, Michael; Gebbers, Robin; Kramer, Eckart; Seidel, Jan

    2011-01-01

    Soil pH is a key parameter for crop productivity, therefore, its spatial variation should be adequately addressed to improve precision management decisions. Recently, the Veris pH Manager™, a sensor for high-resolution mapping of soil pH at the field scale, has been made commercially available in the US. While driving over the field, soil pH is measured on-the-go directly within the soil by ion selective antimony electrodes. The aim of this study was to evaluate the Veris pH Manager™ under farming conditions in Germany. Sensor readings were compared with data obtained by standard protocols of soil pH assessment. Experiments took place under different scenarios: (a) controlled tests in the lab, (b) semicontrolled test on transects in a stop-and-go mode, and (c) tests under practical conditions in the field with the sensor working in its typical on-the-go mode. Accuracy issues, problems, options, and potential benefits of the Veris pH Manager™ were addressed. The tests demonstrated a high degree of linearity between standard laboratory values and sensor readings. Under practical conditions in the field (scenario c), the measure of fit (r(2)) for the regression between the on-the-go measurements and the reference data was 0.71, 0.63, and 0.84, respectively. Field-specific calibration was necessary to reduce systematic errors. Accuracy of the on-the-go maps was considerably higher compared with the pH maps obtained by following the standard protocols, and the error in calculating lime requirements was reduced by about one half. However, the system showed some weaknesses due to blockage by residual straw and weed roots. If these problems were solved, the on-the-go sensor investigated here could be an efficient alternative to standard sampling protocols as a basis for liming in Germany.

  18. Efficient mapping of agricultural soils using a novel electromagnetic measurement system

    Science.gov (United States)

    Trinks, Immo; Pregesbauer, Michael

    2016-04-01

    "Despite all our accomplishments, we owe our existence to a six-inch layer of topsoil and the fact that it rains." - Paul Harvey. Despite the fact, that a farmers most precious good is the soil that he or she cultivates, in most cases actually very little is known about the soils that are being farmed. Agricultural soils are under constant threat through erosion, depletion, pollution and other degrading processes, in particular when considering intensive industrial scale farming. The capability of soils to retain water and soil moisture is of vital importance for their agricultural potential. Detailed knowledge of the physical properties of soils, their types and texture, water content and the depth of the agricultural layer would be of great importance for resource-efficient tillage with sub-area dependent variable depth, and the targeted intelligent application of fertilizers or irrigation. Precision farming, which has seen increasing popularity in the USA as well as Australia, is still in its infancy in Europe. Traditional near-surface geophysical prospection systems for agricultural soil mapping have either been based on earth resistance measurements using electrode-disks that require soil contact, with inherent issues, or electromagnetic induction (EMI) measurements conducted with EMI devices mounted in non-metallic sledges towed several metres behind survey vehicles across the fields. Every farmer passes over the fields several times during each growing season, working the soil and treating the crops. Therefore a novel user-friendly measurement system, the "Topsoil Mapper" (TSM) has been developed, which enables the farmer to simultaneously acquire soil conductivity information and derived soil parameters while anyway passing over the fields using different agricultural implements. The measurement principle of the TSM is electromagnetic induction using a multi-coil array to acquire conductivity information along a vertical profile down to approximately 1.1 m

  19. Soil zymography - A novel technique for mapping enzyme activity in the rhizosphere

    Science.gov (United States)

    Spohn, Marie

    2014-05-01

    The effect plant roots on microbial activity in soil at the millimeter scale is poorly understood. One reason for this is that spatially explicit methods for the study of microbial activity in soil are limited. Here we present a quantitative in situ technique for mapping the distribution of exoenzymes in soil along with some results about the effects of roots on exoenzyme activity in soil. In the first study we showed that both acid and alkaline phosphatase activity were up to 5.4-times larger in the rhizosphere of Lupinus albus than in the bulk soil. While acid phosphatase activity (produced by roots and microorganisms) was closely associated with roots, alkaline phosphatase activity (produced only by microorganisms) was more widely distributed, leading to a 2.5-times larger area of activity of alkaline than of acid phosphatase. These results indicate a spatial differentiation of different ecophysiological groups of organic phosphorus mineralizing organisms in the rhizosphere which might alleviate a potential competition for phosphorus between them. In a second study cellulase, chitinase and phosphatase activities were analyzed in the presence of living Lupinus polyphyllus roots and dead/dying roots (in the same soils 10, 20 and 30 days after cutting the L. polyphyllus shoots). The activity of all three enzymes was 9.0 to 13.9-times higher at the living roots compared to the bulk soil. Microhotspots of cellulase, chitinase and phosphatase activity in the soil were found up to 60 mm away from the living roots. 10 days after shoot cutting, the areas of high activities of cellulase and phosphatase activity were extend up to 55 mm away from the next root, while the extension of the area of chitinase activity did not change significantly. At the root, cellulase and chitinase activity increased first at the root tips after shoot cutting and showed maximal activity 20 days after shoot cutting. The number and activity of microhotspots of chitinase activity was maximal 10

  20. High-Resolution 3-D Mapping of Soil Texture in Denmark

    DEFF Research Database (Denmark)

    Adhikari, Kabindra; Bou Kheir, Rania; Greve, Mette Balslev

    2013-01-01

    , silt, fine sand, and coarse sand content at six standard soil depths of GlobalSoilMap project (0–5, 5–15, 15–30, 30–60, 60–100, and 100–200 cm) via regression rules using the Cubist data mining tool. Seventeen environmental variables were used as predictors and their strength of prediction was also...... calculated. For example, in the prediction of silt content at 0 to 5 cm depth, factors that registered a higher level of importance included the soil map scored (90%), landscape types (54%), and landuse (27%), while factors with lower scores were direct insolation (17%) and slope aspect (14%). Model...... validation (20% of the data selected randomly) showed a higher prediction performance in the upper depth intervals but increasing prediction error in the lower depth intervals (e.g., R2 = 0.54, RMSE = 33.7 g kg−1 for silt 0–5 cm and R2 = 0.29, RMSE = 38.8 g kg−1 from 100–200 cm). Danish soils have a high...

  1. Fixed and removable provisional options for patients undergoing implant treatment.

    Science.gov (United States)

    Cho, Sang-Choon; Shetty, Saphal; Froum, Stuart; Elian, Nicolas; Tarnow, Dennis

    2007-11-01

    The provisional phase of treatment can be the most challenging aspect of implant dentistry. The techniques available today include removable, tooth-supported, and implant-retained provisional restorations. The selection of the type of provisional prosthesis should be based on esthetic demands, functional requirements, duration, and ease of fabrication. This article includes a review of 118 articles from peer-reviewed journals published in English from January 1986 to February 2007. This review was performed using MEDLINE. The indications, advantages, and disadvantages of the various provisional restorations are discussed.

  2. Digital soil mapping in assessment of land suitability for organic farming

    Science.gov (United States)

    Ghambashidze, Giorgi; Kentchiashvili, Naira; Tarkhnishvili, Maia; Jolokhava, Tamar; Meskhi, Tea

    2017-04-01

    Digital soil mapping (DSM) is a fast-developing sub discipline of soil science which gets more importance along with increased availability of spatial data. DSM is based on three main components: the input in the form of field and laboratory observational methods, the process used in terms of spatial and non-spatial soil inference systems, and the output in the form of spatial soil information systems, which includes outputs in the form of rasters of prediction along with the uncertainty of prediction. Georgia is one of the countries who are under the way of spatial data infrastructure development, which includes soil related spatial data also. Therefore, it is important to demonstrate the capacity of DSM technics for planning and decision making process, in which assessment of land suitability is a major interest for those willing to grow agricultural crops. In that term land suitability assessment for establishing organic farms is in high demand as market for organically produced commodities is still increasing. It is the first attempt in Georgia to use DSM to predict areas with potential for organic farming development. Current approach is based on risk assessment of soil pollution with toxic elements (As, Hg, Pb, Cd, Cr) and prediction of bio-availability of those elements to plants on example of the region of Western Georgia, where detailed soil survey was conducted and spatial database of soil was created. The results of the study show the advantages of DSM at early stage assessment and depending on availability and quality of the input data, it can achieve acceptable accuracy.

  3. Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping.

    Science.gov (United States)

    Hamalainen, Sampsa; Geng, Xiaoyuan; He, Juanxia

    2017-04-01

    Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping. Sampsa Hamalainen, Xiaoyuan Geng, and Juanxia, He. AAFC - Agriculture and Agr-Food Canada, Ottawa, Canada. The Latin Hypercube Sampling (LHS) approach to assist with Digital Soil Mapping has been developed for some time now, however the purpose of this work was to complement LHS with use of multiple spatial resolutions of covariate datasets and variability in the range of sampling points produced. This allowed for specific sets of LHS points to be produced to fulfil the needs of various partners from multiple projects working in the Ontario and Prince Edward Island provinces of Canada. Secondary soil and environmental attributes are critical inputs that are required in the development of sampling points by LHS. These include a required Digital Elevation Model (DEM) and subsequent covariate datasets produced as a result of a Digital Terrain Analysis performed on the DEM. These additional covariates often include but are not limited to Topographic Wetness Index (TWI), Length-Slope (LS) Factor, and Slope which are continuous data. The range of specific points created in LHS included 50 - 200 depending on the size of the watershed and more importantly the number of soil types found within. The spatial resolution of covariates included within the work ranged from 5 - 30 m. The iterations within the LHS sampling were run at an optimal level so the LHS model provided a good spatial representation of the environmental attributes within the watershed. Also, additional covariates were included in the Latin Hypercube Sampling approach which is categorical in nature such as external Surficial Geology data. Some initial results of the work include using a 1000 iteration variable within the LHS model. 1000 iterations was consistently a reasonable value used to produce sampling points that provided a good spatial representation of the environmental

  4. Mapping soil particle-size fractions: A comparison of compositional kriging and log-ratio kriging

    Science.gov (United States)

    Wang, Zong; Shi, Wenjiao

    2017-03-01

    Soil particle-size fractions (psf) as basic physical variables need to be accurately predicted for regional hydrological, ecological, geological, agricultural and environmental studies frequently. Some methods had been proposed to interpolate the spatial distributions of soil psf, but the performance of compositional kriging and different log-ratio kriging methods is still unclear. Four log-ratio transformations, including additive log-ratio (alr), centered log-ratio (clr), isometric log-ratio (ilr), and symmetry log-ratio (slr), combined with ordinary kriging (log-ratio kriging: alr_OK, clr_OK, ilr_OK and slr_OK) were selected to be compared with compositional kriging (CK) for the spatial prediction of soil psf in Tianlaochi of Heihe River Basin, China. Root mean squared error (RMSE), Aitchison's distance (AD), standardized residual sum of squares (STRESS) and right ratio of the predicted soil texture types (RR) were chosen to evaluate the accuracy for different interpolators. The results showed that CK had a better accuracy than the four log-ratio kriging methods. The RMSE (sand, 9.27%; silt, 7.67%; clay, 4.17%), AD (0.45), STRESS (0.60) of CK were the lowest and the RR (58.65%) was the highest in the five interpolators. The clr_OK achieved relatively better performance than the other log-ratio kriging methods. In addition, CK presented reasonable and smooth transition on mapping soil psf according to the environmental factors. The study gives insights for mapping soil psf accurately by comparing different methods for compositional data interpolation. Further researches of methods combined with ancillary variables are needed to be implemented to improve the interpolation performance.

  5. Gemas: Geochemical mapping of the agricultural and grasing land soils of Europe

    Science.gov (United States)

    Reimann, Clemens; Fabian, Karl; Birke, Manfred; Demetriades, Alecos; Matschullat, Jörg; Gemas Project Team

    2017-04-01

    Geochemical Mapping of Agricultural and grazing land Soil (GEMAS) is a cooperative project between the Geochemistry Expert Group of EuroGeoSurveys and Eurometaux. During 2008 and until early 2009, a total of 2108 samples of agricultural (ploughed land, 0-20 cm, Ap-samples) and 2023 samples of grazing land (0-10 cm, Gr samples)) soil were collected at a density of 1 site/2500 km2 each from 33 European countries, covering an area of 5,600,000 km2. All samples were analysed for 52 chemical elements following an aqua regia extraction, 42 elements by XRF (total), and soil properties, like CEC, TOC, pH (CaCl2), following tight external quality control procedures. In addition, the Ap soil samples were analysed for 57 elements in a mobile metal ion (MMI®) extraction, Pb isotopes, magnetic susceptibility and total C, N and S. The results demonstrate that robust geochemical maps of Europe can be constructed based on low density sampling, the two independent sample materials, Ap and Gr, show very comparable distribution patterns across Europe. At the European scale, element distribution patterns are governed by natural processes, most often a combination of geology and climate. The geochemical maps reflect most of the known metal mining districts in Europe. In addition, a number of new anomalies emerge that may indicate mineral potential. The size of some anomalies is such that they can only be detected when mapping at the continental scale. For some elements completely new geological settings are detected. An anthropogenic impact at a much more local scale is discernible in the immediate vicinity of some major European cities (e.g., London, Paris) and some metal smelters. The impact of agriculture is visible for Cu (vineyard soils) and for some further elements only in the mobile metal ion (MMI) extraction. For several trace elements deficiency issues are a larger threat to plant, animal and finally human health at the European scale than toxicity. Taking the famous step

  6. Soils, To update the existing STATSGO soils map for the State by clipping the map to the state boundary, and editing and labeling polygons which have changed., Published in 1998, 1:24000 (1in=2000ft) scale, Louisiana State University (LSU).

    Data.gov (United States)

    NSGIC Education | GIS Inventory — Soils dataset current as of 1998. To update the existing STATSGO soils map for the State by clipping the map to the state boundary, and editing and labeling polygons...

  7. UAV MULTISPECTRAL SURVEY TO MAP SOIL AND CROP FOR PRECISION FARMING APPLICATIONS

    Directory of Open Access Journals (Sweden)

    G. Sona

    2016-06-01

    Full Text Available New sensors mounted on UAV and optimal procedures for survey, data acquisition and analysis are continuously developed and tested for applications in precision farming. Procedures to integrate multispectral aerial data about soil and crop and ground-based proximal geophysical data are a recent research topic aimed to delineate homogeneous zones for the management of agricultural inputs (i.e., water, nutrients. Multispectral and multitemporal orthomosaics were produced over a test field (a 100 m x 200 m plot within a maize field, to map vegetation and soil indices, as well as crop heights, with suitable ground resolution. UAV flights were performed in two moments during the crop season, before sowing on bare soil, and just before flowering when maize was nearly at the maximum height. Two cameras, for color (RGB and false color (NIR-RG images, were used. The images were processed in Agisoft Photoscan to produce Digital Surface Model (DSM of bare soil and crop, and multispectral orthophotos. To overcome some difficulties in the automatic searching of matching points for the block adjustment of the crop image, also the scientific software developed by Politecnico of Milan was used to enhance images orientation. Surveys and image processing are described, as well as results about classification of multispectral-multitemporal orthophotos and soil indices.

  8. Uav Multispectral Survey to Map Soil and Crop for Precision Farming Applications

    Science.gov (United States)

    Sonaa, Giovanna; Passoni, Daniele; Pinto, Livio; Pagliari, Diana; Masseroni, Daniele; Ortuani, Bianca; Facchi, Arianna

    2016-06-01

    New sensors mounted on UAV and optimal procedures for survey, data acquisition and analysis are continuously developed and tested for applications in precision farming. Procedures to integrate multispectral aerial data about soil and crop and ground-based proximal geophysical data are a recent research topic aimed to delineate homogeneous zones for the management of agricultural inputs (i.e., water, nutrients). Multispectral and multitemporal orthomosaics were produced over a test field (a 100 m x 200 m plot within a maize field), to map vegetation and soil indices, as well as crop heights, with suitable ground resolution. UAV flights were performed in two moments during the crop season, before sowing on bare soil, and just before flowering when maize was nearly at the maximum height. Two cameras, for color (RGB) and false color (NIR-RG) images, were used. The images were processed in Agisoft Photoscan to produce Digital Surface Model (DSM) of bare soil and crop, and multispectral orthophotos. To overcome some difficulties in the automatic searching of matching points for the block adjustment of the crop image, also the scientific software developed by Politecnico of Milan was used to enhance images orientation. Surveys and image processing are described, as well as results about classification of multispectral-multitemporal orthophotos and soil indices.

  9. Integrating legacy soil information in a Digital Soil Mapping approach based on a modified conditioned Latin Hypercube Sampling design

    Science.gov (United States)

    Stumpf, Felix; Schmidt, Karsten; Behrens, Thorsten; Schoenbrodt-Stitt, Sarah; Scholten, Thomas

    2014-05-01

    One crucial component of a Digital Soil Mapping (DSM) framework is outlined by geo-referenced soil observations. Nevertheless, highly informative legacy soil information, acquired by traditional soil surveys, is often neglected due to lacking accordance with specific statistical DSM designs. The focus of this study is to integrate legacy data into a state-of-the-art DSM approach, based on a modified conditioned Latin Hypercube Sampling (cLHS) design and Random Forest. Furthermore, by means of the cLHS modification the scope of actually unique cLHS sampling locations is widened in order to compensate limited accessability in the field. As well, the maximally stratified cLHS design is not diluted by the modification. Exemplarily the target variables of the modelling are represented by sand and clay fractions. The study site is a small mountainous hydrological catchment of 4.2 km² in the reservoir of the Three Gorges Dam in Central China. The modification is accomplished by demarcating the histogram borders of each cLHS stratum, which are based on the multivariate cLHS feature space. Thereby, all potential sample locations per stratum are identified. This provides a possibility to integrate legacy data samples that match one of the newly created sample locations, and flexibility with respect to field accessibility. Consequently, six legacy data samples, taken from a total sample size of n = 30 were integrated into the sampling design and for all strata several potential sample locations are identified. The comparability of the modified and standard cLHS data sets is approved by (i) identifying their feature space coverage with respect to the cLHS stratifying variables, and (ii) by assessing the Random Forest accuracy estimates.

  10. Heavy Metals in the Environment : Mapping the Probability of Exceeding Critical Thresholds for Cadmium Concentrations in Soils in the Netherlands

    NARCIS (Netherlands)

    Brus, D.J.; Gruijter, de J.J.; Walvoort, D.J.J.; Vries, de F.

    2002-01-01

    Received for publication April 24, 2001. The probability of exceeding critical thresholds of Cd concentrations in the soil was mapped at a national scale. The critical thresholds in soil were based on food quality criteria for Cd in crops or in organs of cattle (Bos taurus), and were calculated by

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

    Science.gov (United States)

    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...visibility. • Empirical relations tuned using 1960’s to 1980’s military vehicles. • NRMM may not be accurate for new military vehicles: oversized wheels

  12. Multitemporal mapping of peri-urban carbon stocks and soil sealing from satellite data.

    Science.gov (United States)

    Villa, Paolo; Malucelli, Francesco; Scalenghe, Riccardo

    2018-01-15

    Peri-urbanisation is the expansion of compact urban areas towards low-density settlements. This phenomenon directly challenges the agricultural landscape multifunctionality, including its carbon (C) storage capacity. Using satellite data, we mapped peri-urban C stocks in soil and built-up surfaces over three areas from 1993 to 2014 in the Emilia-Romagna region, Italy: a thinly populated area around Piacenza, an intermediate-density area covering the Reggio Emilia-Modena conurbation and a densely anthropized area developing along the coast of Rimini. Satellite-derived maps enabled the quantitative analysis of spatial and temporal features of urban growth and soil sealing, expressed as the ratio between C in built-up land and organic C in soils (Cc/Co). The three areas show substantial differences in C stock balance and soil sealing evolution. In Piacenza (Cc/Co=0.07 in 1993), although questioned by late industrial expansion and connected residential sprawl (Cc/Co growth by 38%), most of the new urbanisation spared the best rural soils. The Reggio Emilia-Modena conurbation, driven by the polycentricism of the area and the heterogeneity of economic sectors (Cc/Co rising from 0.08 to 0.14 from 1993 to 2014), balances sprawl and densification. Rimini, severely sealed since the 1960s (Cc/Co=0.23 in 1993), densifies its existing settlements and develops an industrial expansion of the hinterland, with Cc/Co growth accelerating from +15% before 2003 to +36% for the last decade. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Mapping Soil hydrologic features in a semi-arid irrigated area in Spain

    Science.gov (United States)

    Jiménez-Aguirre, M.° Teresa; Isidoro, Daniel; Usón, Asunción

    2016-04-01

    The lack of soil information is a managerial problem in irrigated areas in Spain. The Violada Irrigation District (VID; 5234 ha) is a gypsic, semi-arid region in the Middle Ebro River Basin, northeast Spain. VID is under irrigation since the 1940's. The implementation of the flood irrigation system gave rise to waterlogging problems, solved along the years with the installation of an artificial drainage network. Aggregated water balances have been performed in VID since the early 1980's considering average soil properties and aggregated irrigation data for the calculations (crop evapotranspiration, canal seepage, and soil drainage). In 2008-2009, 91% of the VID was modernized to sprinkler irrigation. This new system provides detailed irrigation management information that together with detailed soil information would allow for disaggregated water balances for a better understanding of the system. Our goal was to draw a semi-detailed soil map of VID presenting the main soil characteristics related to irrigation management. A second step of the work was to set up pedotransfer functions (PTF) to estimate the water content and saturated hydraulic conductivity (Ks) from easily measurable parameters. Thirty four pits were opened, described and sampled for chemical and physical properties. Thirty three additional auger holes were sampled for water holding capacity (WHC; down to 60 cm), helping to draw the soil units boundaries. And 15 Ks tests (inverse auger hole method) were made. The WHC was determined as the difference between the field capacity (FC) and wilting point (WP) measured in samples dried at 40°C during 5 days. The comparison with old values dried at 105°C for 2 days highlighted the importance of the method when gypsum is present in order to avoid water removal from gypsum molecules. The soil map was drawn down to family level. Thirteen soil units were defined by the combination of five subgroups [Typic Calcixerept (A), Petrocalcic Calcixerept (B), Gypsic

  14. Digital Soil Mapping in the Absence of Field Training Data: A Case Study Using Terrain Attributes and Semiautomated Soil Signature Derivation to Distinguish Ecological Potential

    Directory of Open Access Journals (Sweden)

    Dawn M. Browning

    2011-01-01

    Full Text Available Spatially explicit data for soil properties governing plant water availability are needed to understand mechanisms influencing plant species distributions and predict plant responses to changing climate. This is especially important for arid and semiarid regions. Spatial data representing surrogates for soil forming factors are becoming widely available (e.g., spectral and terrain layers. However, field-based training data remain a limiting factor, particularly across remote and extensive drylands. We present a method to map soils with Landsat ETM+ imagery and high-resolution (5 m terrain (IFSAR data based on statistical properties of the input data layers that do not rely on field training data. We then characterize soil classes mapped using this semiautomated technique. The method distinguished spectrally distinct soil classes that differed in subsurface rather than surface properties. Field evaluations of the soil classification in conjunction with analysis of long-term vegetation dynamics indicate the approach was successful in mapping areas with similar soil properties and ecological potential.

  15. MISTRALE: Soil moisture mapping service based on a UAV-embedded GNSS-Reflectometry sensor

    Science.gov (United States)

    Van de Vyvere, Laura; Desenfans, Olivier

    2016-04-01

    Around 70 percent of worldwide freshwater is used by agriculture. To be able to feed an additional 2 billion people by 2030, water demand is expected to increase tremendously in the next decades. Farmers are challenged to produce "more crop per drop". In order to optimize water resource management, it is crucial to improve soil moisture situation awareness, which implies both a better temporal and spatial resolution. To this end, the objective of the MISTRALE project (Monitoring soIl moiSture and waTeR-flooded Areas for agricuLture and Environment) is to provide UAV-based soil moisture maps that could complement satellite-based and field measurements. In addition to helping farmers make more efficient decisions about where and when to irrigate, MISTRALE moisture maps are an invaluable tool for risk management and damage evaluation, as they provide highly relevant information for wetland and flood-prone area monitoring. In order to measure soil water content, a prototype of a new sensor, called GNSS-Reflectometry (GNSS-R), is being developed in MISTRALE. This approach consists in comparing the direct signal, i.e. the signal travelling directly from satellite to receiver (in this case, embedded in the UAV), with its ground-reflected equivalent. Since soil dielectric properties vary with moisture content, the reflected signal's peak power is affected by soil moisture, unlike the direct one. In order to mitigate the effect of soil surface roughness on measurements, both left-hand and right-hand circular polarization reflected signals have to be recorded and processed. When it comes to soil moisture, using GNSS signals instead of traditional visible/NIR imagery has many advantages: it is operational under cloud cover, during the night, and also under vegetation (bushes, grass, trees). In addition, compared to microwaves, GNSS signal (which lies in L-band, between 1.4 and 1.8 GHz) is less influenced by variation on thermal background. GNSS frequencies are then ideal

  16. A coherent geostatistical approach for combining choropleth map and field data in the spatial interpolation of soil properties.

    Science.gov (United States)

    Goovaerts, P

    2011-06-01

    Information available for mapping continuous soil attributes often includes point field data and choropleth maps (e.g. soil or geological maps) that model the spatial distribution of soil attributes as the juxtaposition of polygons (areas) with constant values. This paper presents two approaches to incorporate both point and areal data in the spatial interpolation of continuous soil attributes. In the first instance, area-to-point kriging is used to map the variability within soil units while ensuring the coherence of the prediction so that the average of disaggregated estimates is equal to the original areal datum. The resulting estimates are then used as local means in residual kriging. The second approach proceeds in one step and capitalizes on: 1) a general formulation of kriging that allows the combination of both point and areal data through the use of area-to-area, area-to-point, and point-to-point covariances in the kriging system, 2) the availability of GIS to discretize polygons of irregular shape and size, and 3) knowledge of the point-support variogram model that can be inferred directly from point measurements, thereby eliminating the need for deconvolution procedures. The two approaches are illustrated using the geological map and heavy metal concentrations recorded in the topsoil of the Swiss Jura. Sensitivity analysis indicates that the new procedures improve prediction over ordinary kriging and traditional residual kriging based on the assumption that the local mean is constant within each mapping unit.

  17. 2012 Provisional classification criteria for polymyalgia rheumatica

    DEFF Research Database (Denmark)

    Dasgupta, Bhaskar; Cimmino, Marco A; Kremers, Hilal Maradit

    2012-01-01

    % and specificity to 81%. According to these provisional classification criteria, patients ≥50 years old presenting with bilateral shoulder pain, not better explained by an alternative pathology, can be classified as having PMR in the presence of morning stiffness >45 minutes, elevated C-reactive protein and......The objective of this study was to develop European League Against Rheumatism/American College of Rheumatology classification criteria for polymyalgia rheumatica (PMR). Candidate criteria were evaluated in a 6-month prospective cohort study of 125 patients with new-onset PMR and 169 non......-PMR comparison subjects with conditions mimicking PMR. A scoring algorithm was developed based on morning stiffness >45 minutes (2 points), hip pain/limited range of motion (1 point), absence of rheumatoid factor and/or anti-citrullinated protein antibody (2 points), and absence of peripheral joint pain (1 point...

  18. Mapping of Soil Saturated Hydraulic Conductivity in Navroud-Assalem Watershed in Guilan Province

    Directory of Open Access Journals (Sweden)

    M.R. Khaledian

    2016-02-01

    Full Text Available Introduction: With increasing awareness of human beings towards the environment, researchers pay more attention to process and redistribution of water flow and solute transport in the soil and groundwater. Moreover, determination of soil hydraulic conductivity is necessary to determine the runoff from basins. Water movement within the unsaturated zone is often described by the formulae proposed by Richards. To solve this equation, initial and boundary conditions of the hydraulic conductivity and the soil water pressure should be determined as functions of soil water content. Beerkan method was developed to identify retention and hydraulic conductivity curves. In this method, van Gunechten with Burdine condition and Brooks and Corey equations were used to describe water retention and hydraulic conductivity curves. Recognition of the spatial pattern of studied parameter using semivariogram and then preparing zoning map with interpolation methods such as IDW and kriging can help us in relevant watershed management. The aim of this study was to spatial analyze of saturated hydraulic conductivity from 50 infiltration tests at watershed scale using Beerkan method and then preparing zoning map for the Navroud watershed. Materials and Methods: Navroud-Assalem watershed with an area of about 307 km2 is located in the west part of Guilan province, within the city of Talesh. Of the total watershed area of Navroud, about 41 km2 is plains and the rest of it is about 266 km2, corresponding to the mountainous area. The study area includes an area with a height above 130 m. In order to complete the database of the studied watershed the present study was designed to assess soil saturated hydraulic conductivity. In this study, a 2×2 km network was designed in Navroud watershed with a surface area of 307 km2, and then infiltration tests were carried out in each node using single ring of Beerkan. Beerkan method derives shape parameters from particle

  19. Predicting weed migration from soil and climate maps. [Centaurea maculosa Lam

    Energy Technology Data Exchange (ETDEWEB)

    Chicoine, T.K.; Fay, P.K.; Nielsen, G.A.

    1985-01-01

    Soil characteristics, elevation, annual precipitation, potential evapotranspiration, length of frost-free season, and mean maximum July temperature were estimated for 116 established infestations of spotted knapweed (Centaurea maculosa Lam. number/sup 3/ CENMA) in Montana using basic land resource maps. Areas potentially vulnerable to invasion by the plant were delineated on the basis of representative edaphic and climatic characteristics. No single environmental variable was an effective predictor of sites vulnerable to invasion by spotted knapweed. Only a combination of variables was effective, indicating that the factors that regulate adaptability of this plant are complex. This technique provides a first approximation map of the regions most similar environmentally to infested sites and; therefore, most vulnerable to further invasion. This weed migration prediction technique shows promise for predicting suitable habitats of other invader species. 6 references, 4 figures, 1 table.

  20. High Resolution Mapping of Soils and Landforms for the Desert Renewable Energy Conservation Plan (DRECP)

    Science.gov (United States)

    Potter, Christopher S.; Li, Shuang

    2014-01-01

    The Desert Renewable Energy Conservation Plan (DRECP), a major component of California's renewable energy planning efforts, is intended to provide effective protection and conservation of desert ecosystems, while allowing for the sensible development of renewable energy projects. This NASA mapping report was developed to support the DRECP and the Bureau of Land Management (BLM). We outline in this document remote sensing image processing methods to deliver new maps of biological soils crusts, sand dune movements, desert pavements, and sub-surface water sources across the DRECP area. We focused data processing first on the largely unmapped areas most likely to be used for energy developments, such as those within Renewable Energy Study Areas (RESA) and Solar Energy Zones (SEZs). We used imagery (multispectral and radar) mainly from the years 2009-2011.

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

    Science.gov (United States)

    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

  2. Suitability aero-geophysical methods for generating conceptual soil maps and their use in the modeling of process-related susceptibility maps

    Science.gov (United States)

    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

  3. The methods of geomorphometry and digital soil mapping for assessing spatial variability in the properties of agrogray soils on a slope

    Science.gov (United States)

    Gopp, N. V.; Nechaeva, T. V.; Savenkov, O. A.; Smirnova, N. V.; Smirnov, V. V.

    2017-01-01

    The relationships between the morphometric parameters (MPs) of topography calculated on the basis of digital elevation model (ASTER GDEM, 30 m) and the properties of the plow layer of agrogray soils on a slope were analyzed. The contribution of MPs to the spatial variability of the soil moisture reached 42%; to the content of physical clay (exchangeable potassium, 45%; to the content of exchangeable calcium, 67%; to the content of exchangeable magnesium, 40%; and to the soil pH, 42%. A comparative analysis of the plow layer within the eluvial and transitional parts of the slope was performed with the use of geomorphometric methods and digital soil mapping. The regression analysis showed statistically significant correlations between the properties of the plow layer and the MPs describing surface runoff, geometric forms of surface, and the soil temperature regime.

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

    Science.gov (United States)

    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

  5. Soil salinity mapping and hydrological drought indices assessment in arid environments based on remote sensing techniques

    Science.gov (United States)

    Elhag, Mohamed; Bahrawi, Jarbou A.

    2017-03-01

    Vegetation indices are mostly described as crop water derivatives. The normalized difference vegetation index (NDVI) is one of the oldest remote sensing applications that is widely used to evaluate crop vigor directly and crop water relationships indirectly. Recently, several NDVI derivatives were exclusively used to assess crop water relationships. Four hydrological drought indices are examined in the current research study. The water supply vegetation index (WSVI), the soil-adjusted vegetation index (SAVI), the moisture stress index (MSI) and the normalized difference infrared index (NDII) are implemented in the current study as an indirect tool to map the effect of different soil salinity levels on crop water stress in arid environments. In arid environments, such as Saudi Arabia, water resources are under pressure, especially groundwater levels. Groundwater wells are rapidly depleted due to the heavy abstraction of the reserved water. Heavy abstractions of groundwater, which exceed crop water requirements in most of the cases, are powered by high evaporation rates in the designated study area because of the long days of extremely hot summer. Landsat 8 OLI data were extensively used in the current research to obtain several vegetation indices in response to soil salinity in Wadi ad-Dawasir. Principal component analyses (PCA) and artificial neural network (ANN) analyses are complementary tools used to understand the regression pattern of the hydrological drought indices in the designated study area.

  6. The use of the soil map of Belgium in the assessment of landslide risk

    Directory of Open Access Journals (Sweden)

    Closson D.

    1999-01-01

    Full Text Available The analysis is based on a report from the Laboratory of Geomorphology and Remote sensing of the University of Liege concerning Mont-de-l'Enclus hill (Province of Hainaut, 20 kilometers north of the city of Tournai. After a landslide in a street of the hill, the regional administration ordered, in 1998, a detailed study of the hillside (7 square kilometres. The report is in three parts. The first one analyses the influence of human settlement on the landslide hazards. The second one studies all the environmental components in relation to the landslides. Finally, a synthesis map gathers the most important conclusions drawn from the first two parts. The Belgian soil map is very useful when combined with geological and geomorphological data. This is called geo-morpho-pedologic approach. Analysis and comparison have been made with the geographical information system Arc/Info-Arcview. The landslide of the ""rue du Renard"" is located at the interface between discontinuous layers of clay (5 to 15 meters and sand. Geology gives us a global evaluation of the layer of clay responsible for the landslide. Geomorphology increases the accuracy of location for the clay layer through several elements of the landscape such as superficial landslides, water seepage, concavities and convexities. Pedology matches up previous information through different kinds of data such as texture, ""natural soil drainage"", soil profile and derived series. The geo-morpho-pedological approach is not always effective in foreseeing a landslide phenomenon such as in the case studied. The report from the Laboratoire de Geomorphologie et Teledetection (remote sensing indicates, however, that the methodology gave better results than the geotechnical approach in this particular case, and it was also less expensive. The geotechnical approach had either not worked, or was too difficult to use because of the geological conditions (lateral variation of clay fades, absence of outcrops.

  7. The potential of UAS imagery for soil mapping at the agricultural plot scale

    Science.gov (United States)

    Gilliot, Jean-Marc; Michelin, Joël; Becu, Maxime; Cissé, Moustapha; Hadjar, Dalila; Vaudour, Emmanuelle

    2017-04-01

    Soil mapping is expensive and time consuming. Airborne and satellite remote sensing data have already been used to predict some soil properties but now Unmanned Aerial Systems (UAS) allow to do many images acquisitions in various field conditions in favour of developing methods for better prediction models construction. This study propose an operational method for spatial prediction of soil properties (organic carbon, clay) at the scale of the agricultural plot by using UAS imagery. An agricultural plot of 28 ha, located in the western region of Paris France, was studied from March to May 2016. An area of 3.6 ha was delimited within the plot and a total of 16 flights were completed. The UAS platforms used were the eBee fixed wing provided by Sensefly® flying at an altitude from 60m to 130m and the iris+ 3DR® Quadcopter (from 30m to 100m). Two multispectral visible near-infrared cameras were used: the AirInov® MultiSPEC 4C® and the Micasense® RedEdge®. 42 ground control points (GCP) were sampled within the 3.6 ha plot. A centimetric Trimble Geo 7x DGPS was used to determine precise GCP positions. On each GCP the soil horizons were described and the top soil were sampled for standard physico-chemical analysis. Ground spectral measurements with a Spectral Evolution® SR-3500 spectroradiometer were made synchronously with the drone flights. 22 additional GCP were placed around the 3.6 ha area in order to realize a precise georeferencing. The multispectral mosaics were calculated using the Agisoft Photoscan® software and all mapping processings were done with the ESRI ArcGIS® 10.3 software. The soil properties were estimated by partial least squares regression (PLSR) between the laboratory analyses and the multispectral information of the UAS images, with the PLS package of the R software. The objective was to establish a model that would achieve an acceptable prediction quality using minimum number of points. For this, we tested 5 models with a decreasing

  8. Digital soil mapping using remote sensing indices, terrain attributes, and vegetation features in the rangelands of northeastern Iran.

    Science.gov (United States)

    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.

  9. MAPPING REMOVAL SWELLING CLAY SOILS IN THE AURES (N’GAOUS ALGERIA

    Directory of Open Access Journals (Sweden)

    Rahmani MOUNA

    2016-09-01

    Full Text Available The shrinkage and swelling phenomena of certain clay soils cause differential settlement manifested by disorders that affect mainly the individual frame. The objective of this research was to create a map related to these phenomena especially in the area of Algeria N’gaous (figure 1. The approach of the study is primarily based firstly on the interpretation of a geological map at a scale 1 : 50 000 and on the other part from existing literature and observations on a synthesis of a large number of geotechnical information to determine susceptibility to the phenomenon of clay or marl formations. This approach consisted in the establishment of a synthetic departmental mapping of these formations that have been identified from a hierarchy as to their susceptibility according to the shrinkage and swelling phenomenon. This classification was established on the basis of three quantifiable main features: the dominant lithology of formations, the mineralogical composition of their clay fraction (proportion of swelling minerals and geotechnical behavior (primarily assessed from the blue value and the plasticity index.

  10. VSRR - Quarterly provisional estimates for selected birth indicators

    Data.gov (United States)

    U.S. Department of Health & Human Services — Provisional estimates of selected reproductive indicators. Estimates are presented for: general fertility rates, age-specific birth rates, total and low risk...

  11. VSRR - Quarterly provisional estimates for selected indicators of mortality

    Data.gov (United States)

    U.S. Department of Health & Human Services — Provisional estimates of death rates. Estimates are presented for each of the 15 leading causes of death plus estimates for deaths attributed to drug overdose, falls...

  12. POLARIS: A 30-meter probabilistic soil series map of the contiguous United States

    Science.gov (United States)

    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.

  13. Comparison of different landform classification methods for digital landform and soil mapping of the Iranian loess plateau

    Science.gov (United States)

    Hoffmeister, Dirk; Kramm, Tanja; Curdt, Constanze; Maleki, Sedigheh; Khormali, Farhad; Kehl, Martin

    2016-04-01

    The Iranian loess plateau is covered by loess deposits, up to 70 m thick. Tectonic uplift triggered deep erosion and valley incision into the loess and underlying marine deposits. Soil development strongly relates to the aspect of these incised slopes, because on northern slopes vegetation protects the soil surface against erosion and facilitates formation and preservation of a Cambisol, whereas on south-facing slopes soils were probably eroded and weakly developed Entisols formed. While the whole area is intensively stocked with sheep and goat, rain-fed cropping of winter wheat is practiced on the valley floors. Most time of the year, the soil surface is unprotected against rainfall, which is one of the factors promoting soil erosion and serious flooding. However, little information is available on soil distribution, plant cover and the geomorphological evolution of the plateau, as well as on potentials and problems in land use. Thus, digital landform and soil mapping is needed. As a requirement of digital landform and soil mapping, four different landform classification methods were compared and evaluated. These geomorphometric classifications were run on two different scales. On the whole area an ASTER GDEM and SRTM dataset (30 m pixel resolution) was used. Likewise, two high-resolution digital elevation models were derived from Pléiades satellite stereo-imagery (58%. For the 30 m resolution datasets is the achieved accuracy approximately 40%, as several small scale features are not recognizable in this resolution. Thus, for an accurate differentiation between different important landform types, high-resolution datasets are necessary for this strongly shaped area. One major problem of this approach are the different classes derived by each method and the various class annotations. The result of this evaluation will be regarded for the derivation of landform and soil maps.

  14. Mapping soil erosion hotspots and assessing the potential impacts of land management practices in the highlands of Ethiopia

    Science.gov (United States)

    Tamene, Lulseged; Adimassu, Zenebe; Ellison, James; Yaekob, Tesfaye; Woldearegay, Kifle; Mekonnen, Kindu; Thorne, Peter; Le, Quang Bao

    2017-09-01

    An enormous effort is underway in Ethiopia to address soil erosion and restore overall land productivity. Modelling and participatory approaches can be used to delineate erosion hotspots, plan site- and context-specific interventions and assess their impacts. In this study, we employed a modelling interface developed based on the Revised Universal Soil Loss Equation adjusted by the sediment delivery ratio to map the spatial distribution of net soil loss and identify priority areas of intervention. Using the modelling interface, we also simulated the potential impacts of different soil and water conservation measures in reducing net soil loss. Model predictions showed that net soil loss in the study area ranges between 0.4 and 88 t ha- 1 yr- 1 with an average of 12 t ha- 1 yr- 1. The dominant soil erosion hotspots were associated with steep slopes, gullies, communal grazing and cultivated areas. The average soil loss observed in this study is higher than the tolerable soil loss rate estimated for the highland of Ethiopia. The scenario analysis results showed that targeting hotspot areas where soil loss exceeds 10 t ha- 1 yr- 1 could reduce net soil loss to the tolerable limit (< 2 t ha- 1 yr- 1). The spatial distribution of soil loss and the sediment yield reduction potential of different options provided essential information to guide prioritization and targeting. In addition, the results can help promoting awareness within the local community of the severity of the soil erosion problem and the potential of management interventions. Future work should include cost-benefit and tradeoff analyses of the various management options for achieving a given level of erosion reduction.

  15. Comparative study of interpolation methods for mapping soil pH in the apple orchards of Murree, Pakistan

    Directory of Open Access Journals (Sweden)

    Humair Ahmed

    2017-05-01

    Full Text Available Soil pH is considered as a core indicator for nutrient bioavailability. Prevailing alkaline pH due to calcareousness in Pakistan is considered as one of the limiting factor for nutrient availability to plants. Exploring the spatial variability of soil variables serves as scientific basis for the generation of soil management strategies. Selection of best interpolation method to predict the soil properties at un-sampled locations is an important issue in the site specific investigations. This article evaluates Inverse distance weighting, global and local polynomial interpolation, radial basis function and kriging to determine the optimal interpolation method for mapping soil pH. Performance of the interpolation methods was analyzed using soil test (pH data from 180 surface soil samples collected from 30 representative orchards grown in tehsil Murree. For inverse distance weighting, powers of 1, 2 and 3 were used and the number of neighbors for all methods ranged from 15 to 25. The conclusion of our study suggested that increased power of inverse distance weighting resulted in an increase in the prediction accuracy. Local polynomial interpolation method was more suitable as compared to global polynomial interpolation. Radial basis function with regularized and spline tension gave equivalent prediction accuracy. Higher errors (mean and mean absolute errors were observed in case of ordinary kriging as compared to other interpolation methods. Digital maps generated by the higher powers of inverse distance weighting, local polynomial interpolation, and radial basis function were of higher accuracy.

  16. Modeling and Mapping of Soil Salinity with Reflectance Spectroscopy and Landsat Data Using Two Quantitative Methods (PLSR and MARS

    Directory of Open Access Journals (Sweden)

    Said Nawar

    2014-11-01

    Full Text Available The monitoring of soil salinity levels is necessary for the prevention and mitigation of land degradation in arid environments. To assess the potential of remote sensing in estimating and mapping soil salinity in the El-Tina Plain, Sinai, Egypt, two predictive models were constructed based on the measured soil electrical conductivity (ECe and laboratory soil reflectance spectra resampled to Landsat sensor’s resolution. The models used were partial least squares regression (PLSR and multivariate adaptive regression splines (MARS. The results indicated that a good prediction of the soil salinity can be made based on the MARS model (R2 = 0.73, RMSE = 6.53, and ratio of performance to deviation (RPD = 1.96, which performed better than the PLSR model (R2 = 0.70, RMSE = 6.95, and RPD = 1.82. The models were subsequently applied on a pixel-by-pixel basis to the reflectance values derived from two Landsat images (2006 and 2012 to generate quantitative maps of the soil salinity. The resulting maps were validated successfully for 37 and 26 sampling points for 2006 and 2012, respectively, with R2 = 0.72 and 0.74 for 2006 and 2012, respectively, for the MARS model, and R2 = 0.71 and 0.73 for 2006 and 2012, respectively, for the PLSR model. The results indicated that MARS is a more suitable technique than PLSR for the estimation and mapping of soil salinity, especially in areas with high levels of salinity. The method developed in this paper can be used for other satellite data, like those provided by Landsat 8, and can be applied in other arid and semi-arid environments.

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

    Science.gov (United States)

    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.

  18. EXTRAPOLATING THE SUITABILITY OF SOILS AS NATURAL REACTORS USING AN EXISTING SOIL MAP: APPLICATION OF PEDOTRANSFER FUNCTIONS, SPATIAL INTEGRATION AND VALIDATION PROCEDURES

    Directory of Open Access Journals (Sweden)

    Yameli Guadalupe Aguilar Duarte

    2011-04-01

    Full Text Available The aim of this study was the spatial identification of the suitability of soils as reactors in the treatment of swine wastewater in the Mexican state of Yucatan, as well as the development of a map with validation procedures. Pedotransfer functions were applied to the existing soils database. A methodological approach was adopted that allowed the spatialization of pedotransfer function data points. A map of the suitability of soil associations as reactors was produced, as well as a map of the level of accuracy of the associations using numerical classification technique, such as discriminant analysis. Soils with the highest suitability indices were found to be Vertisols, Stagnosols, Nitisols and Luvisols. Some 83.9% of the area of Yucatan is marginally suitable for the reception of swine wastewater, 6.5% is moderately suitable, while 6% is suitable. The percentages of the spatial accuracy of the pedotransfer functions range from 62% to 95% with an overall value of 71.5%. The methodological approach proved to be practical, accurate and inexpensive.

  19. Soil Moisture Mapping in an Arid Area Using a Land Unit Area (LUA Sampling Approach and Geostatistical Interpolation Techniques

    Directory of Open Access Journals (Sweden)

    Saeid Gharechelou

    2016-03-01

    Full Text Available Soil moisture (SM plays a key role in many environmental processes and has a high spatial and temporal variability. Collecting sample SM data through field surveys (e.g., for validation of remote sensing-derived products can be very expensive and time consuming if a study area is large, and producing accurate SM maps from the sample point data is a difficult task as well. In this study, geospatial processing techniques are used to combine several geo-environmental layers relevant to SM (soil, geology, rainfall, land cover, etc. into a land unit area (LUA map, which delineates regions with relatively homogeneous geological/geomorphological, land use/land cover, and climate characteristics. This LUA map is used to guide the collection of sample SM data in the field, and the field data is finally spatially interpolated to create a wall-to-wall map of SM in the study area (Garmsar, Iran. The main goal of this research is to create a SM map in an arid area, using a land unit area (LUA approach to obtain the most appropriate sample locations for collecting SM field data. Several environmental GIS layers, which have an impact on SM, were combined to generate a LUA map, and then field surveying was done in each class of the LUA map. A SM map was produced based on LUA, remote sensing data indexes, and spatial interpolation of the field survey sample data. The several interpolation methods (inverse distance weighting, kriging, and co-kriging were evaluated for generating SM maps from the sample data. The produced maps were compared to each other and validated using ground truth data. The results show that the LUA approach is a reasonable method to create the homogenous field to introduce a representative sample for field soil surveying. The geostatistical SM map achieved adequate accuracy; however, trend analysis and distribution of the soil sample point locations within the LUA types should be further investigated to achieve even better results. Co

  20. Identifying the role of historical anthropogenic activities on urban soils: geochemical impact and city scale mapping

    Science.gov (United States)

    Le Guern, Cecile; Baudouin, Vivien; Conil, Pierre

    2017-04-01

    , more than 1800 analyzed samples, almost 100 000 analyzed parameters). The potential quality of soil and subsoil was spatialized in 2D and 3D on the basis of anthropogenic deposits structure and typology as well as of the potential sources of contamination linked to former industrial activities. Volumes were also calculated to help the developer anticipating the management of excavated materials. Comparison with effective soil and subsoil quality (existing chemical data) shows fairly good anticipation of contamination problems, confirming the interest of spatializing the historical anthropogenic activities to anticipate the quality of urban soil and subsoil and guide city scale mapping. Urban geochemical compatibility levels will be used operationally to enhance the reuse of excavated materials. A better knowledge of soils and subsoils at depth is very useful to optimize urban redevelopment projects, anticipating contamination problems, and managing excavated materials (e.g. local reuse possibilities, disposal costs etc.). The potential economic, environmental and social consequences render it essential for urban sustainable development. 3D geochemical characterization of soil and subsoil for urban (re)development is an ambitious task. Rarely carried out until now, it needs improved development of acquisition, management, visualisation and use of data.

  1. Digital mapping of topsoil organic carbon in Grand-Duchy of Luxembourg using a compilation of legacy soil data

    Science.gov (United States)

    Stevens, Antoine; Marx, Simone; van Wesemael, Bas

    2014-05-01

    Providing localized predictions (with uncertainties) of soil properties is needed to assist soil surveyors and land managers, and inform/assist the political debate with quantified estimates of the status and change of the soil resource. Such maps can be produced with data originating either from purpose-built soil monitoring networks (SMN) or from previous soil measurements exercises such as soil testing for farmers by commercial/institutional soil laboratories. Although SMN's are likely to provide better and less biased estimates of soil attributes because of their optimal sampling strategy, SMN's are costly to establish, maintain and re-visit. Data gathered from other sources, on the other hand, are often more numerous which might favor greater accuracy in a geostatistical context. Another advantage is that these data are often acquired continuously so that derived-maps can be rapidly and easily improved or updated with upcoming data. In this study, we produce a map of the topsoil Organic Carbon (OC) content of croplands, grasslands, vineyards and forest land of the Grand-Duchy of Luxembourg using more than 2000 samples analyzed for OC (by dry combustion) in 2012-2013 by an accredited soil laboratory in Luxembourg. To model OC content, this study relies on a set of spatial covariates with a resolution of 90 m, including elevation and its derivatives, land cover, soil texture, climate and livestock intensity. To avoid problems related to co-linearity in the independent variables, the covariates were transformed using Principal Component (PC) analysis, retaining PC components explaining more than 99% of the variation. Different prediction models were developed for each of the four land cover classes using either Generalized Additive Models (GAM) or Random Forest Kriging. For cropland soils, the model is characterized by a R2 = 0.75 and RMSE = 4 g C kg-1 and the variables used in the model are geographical coordinates and PC components related to elevation and

  2. Using Remote Sensing, Geomorphology, and Soils to Map Episodic Streams in Drylands

    Science.gov (United States)

    Thibodeaux-Yost, S. N. S.

    2016-12-01

    Millions of acres of public land in the California deserts are currently being evaluated and permitted for the construction of large-scale renewable energy projects. The absence of a standard method for identifying episodic streams in arid and semi-arid (dryland) regions is a source of conflict between project developers and the government agencies responsible for conserving natural resources and permitting renewable energy projects. There is a need for a consistent, efficient, and cost-effective dryland stream delineation protocol that accurately reflects the extent and distribution of active watercourses. This thesis evaluates the stream delineation method and results used by the developer for the proposed Ridgecrest Solar Power Project on the El Paso Fan, Ridgecrest, Kern County, California. This evaluation is then compared and contrasted with results achieved using remote sensing, geomorphology, soils, and GIS analysis to identify stream presence on the site. This study's results identified 105 acres of watercourse, a value 10 times greater than that originally identified by the project developer. In addition, the applied methods provide an ecohydrologic base map to better inform project siting and potential project impact mitigation opportunities. This study concludes that remote sensing, geomorphology, and dryland soils can be used to accurately and efficiently identify episodic stream activity and the extent of watercourses in dryland environments.

  3. Soil radioactivity levels, radiological maps and risk assessment for the state of Kuwait.

    Science.gov (United States)

    Alazemi, N; Bajoga, A D; Bradley, D A; Regan, P H; Shams, H

    2016-07-01

    An evaluation of the radioactivity levels associated with naturally occurring radioactive materials has been undertaken as part of a systematic study to provide a surface radiological map of the State of Kuwait. Soil samples from across Kuwait were collected, measured and analysed in the current work. These evaluations provided soil activity concentration levels for primordial radionuclides, specifically members of the (238)U and (232)Th decay chains and (40)K which. The (238)U and (232)Th chain radionuclides and (40)K activity concentration values ranged between 5.9 ↔ 32.3, 3.5 ↔ 27.3, and 74 ↔ 698 Bq/kg respectively. The evaluated average specific activity concentrations of (238)U, (232)Th and (40)K across all of the soil samples have mean values of 18, 15 and 385 Bq/kg respectively, all falling below the worldwide mean values of 35, 40 and 400 Bq/kg respectively. The radiological risk factors are associated with a mean of 33.16 ± 2.46 nG/h and 68.5 ± 5.09 Bq/kg for the external dose rate and Radium equivalent respectively. The measured annual dose rates for all samples gives rise to a mean value of 40.8 ± 3.0 μSv/y while the internal and internal hazard indices have been found to be 0.23 ± 0.02 and 0.19 ± 0.01 respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Mapping Depth to Argillic Horizon Using Electromagnetic Induction on Historically Farmed Soils within the Piedmont Region of the United States

    Science.gov (United States)

    Ryland, R.; Markewitz, D.; Thompson, A.

    2016-12-01

    Historic agricultural practices throughout the Piedmont region of the southeastern United States from 1820 to 1940 led to accelerated erosion. Practices, such as tilling, degraded soil quality altering hydrologic processes on the landscape by limiting infiltration and leading to overland flow and erosion. Erosion due to these practices has substantially redistributed sediment from upper to lower landscape positions, causing a change in the depth-to-argillic horizon along hillslopes. By mapping the depth to argillic horizon within watersheds that have a history of farming and watersheds with little evidence of agricultural disturbance, a better understanding of the effects of farming practices on erosion and sediment redistribution can be made. This study uses extensive soil sampling within historically farmed and unfarmed watersheds to map spatial variations in the depth to argillic horizon. In addition to sampling, Electro-magnetic Induction (EMI) is being tested and calibrated to clay content and other topographic characteristic (i.e. landscape position, aspect, percent slope) from which the depth to argillic horizon can be predicted. Current hillslope and watershed hydrologic models use characteristics from soil classification maps for parameterization, however, these soil maps may lack sufficient spatial detail and may not accurately represent landscapes that have been eroded from historical farming. The results from this study will improve understanding of previous erosion on sediment redistribution and will characterize the potential use of electromagnetic induction as an accurate and efficient means to predict the depth to the argillic horizon. This information will improve parameterization of hillslope and watershed hydrologic models.

  5. Soil organic carbon content assessment in a heterogeneous landscape: comparison of digital soil mapping and visible and near Infrared spectroscopy approaches

    Science.gov (United States)

    Michot, Didier; Fouad, Youssef; Pascal, Pichelin; Viaud, Valérie; Soltani, Inès; Walter, Christian

    2017-04-01

    This study aims are: i) to assess SOC content distribution according to the global soil map (GSM) project recommendations in a heterogeneous landscape ; ii) to compare the prediction performance of digital soil mapping (DSM) and visible-near infrared (Vis-NIR) spectroscopy approaches. The study area of 140 ha, located at Plancoët, surrounds the unique mineral spring water of Brittany (Western France). It's a hillock characterized by a heterogeneous landscape mosaic with different types of forest, permanent pastures and wetlands along a small coastal river. We acquired two independent datasets: j) 50 points selected using a conditioned Latin hypercube sampling (cLHS); jj) 254 points corresponding to the GSM grid. Soil samples were collected in three layers (0-5, 20-25 and 40-50cm) for both sampling strategies. SOC content was only measured in cLHS soil samples, while Vis-NIR spectra were measured on all the collected samples. For the DSM approach, a machine-learning algorithm (Cubist) was applied on the cLHS calibration data to build rule-based models linking soil carbon content in the different layers with environmental covariates, derived from digital elevation model, geological variables, land use data and existing large scale soil maps. For the spectroscopy approach, we used two calibration datasets: k) the local cLHS ; kk) a subset selected from the regional spectral database of Brittany after a PCA with a hierarchical clustering analysis and spiked by local cLHS spectra. The PLS regression algorithm with "leave-one-out" cross validation was performed for both calibration datasets. SOC contents for the 3 layers of the GSM grid were predicted using the different approaches and were compared with each other. Their prediction performance was evaluated by the following parameters: R2, RMSE and RPD. Both approaches led to satisfactory predictions for SOC content with an advantage for the spectral approach, particularly as regards the pertinence of the variation

  6. 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

    Science.gov (United States)

    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.

  7. From HYSOMA to ENSOMAP - A new open source tool for quantitative soil properties mapping based on hyperspectral imagery from airborne to spaceborne applications

    Science.gov (United States)

    Chabrillat, Sabine; Guillaso, Stephane; Rabe, Andreas; Foerster, Saskia; Guanter, Luis

    2016-04-01

    Soil spectroscopy from the visible-near infrared to the short wave infrared has been shown to be a proven method for the quantitative prediction of key soil surface properties in the laboratory, field, and up to airborne studies for exposed soils in appropriate surface conditions. With the upcoming launch of the next generation of spaceborne hyperspectral sensors within the next 3 to 5 years (EnMAP, HISUI, PRISMA, SHALOM), a great potential for the global mapping and monitoring of soil properties is appearing. This potential can be achieved only if adequate software tools are available, as shown by the increasing demand for the availability/accessibility of hyperspectral soil products from the geoscience community that have neither the capacity nor the expertise to deliver these soil products. In this context, recently many international efforts were tuned toward the development of robust and easy-to-access soil algorithms to allow non-remote sensing experts to obtain geoscience information based on non-expensive software packages where repeatability of the results is an important prerequisite. In particular, several algorithms for geological and mineral mapping were recently released such as the U.S. Geological Survey Processing Routines in IDL for Spectroscopic Measurements (PRISM) software, or the GFZ EnMAP Geological Mapper. For quantitative soil mapping and monitoring, the HYSOMA (Hyperspectral Soil Mapper) software interface was developed at GFZ under the EUFAR (www.eufar.net) and the EnMAP (www.enmap.org) programs. HYSOMA was specifically oriented toward digital soil mapping applications and has been distributed since 2012 for free as IDL plug-ins under the IDL-virtual machine at www.gfz-potsdam.de/hysoma under a close source license. The HYSOMA 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. With more than 100 users around the world

  8. A stratified two-stage sampling design for digital soil mapping in a Mediterranean basin

    Science.gov (United States)

    Blaschek, Michael; Duttmann, Rainer

    2015-04-01

    ESRI software (ArcGIS) extended by Hawth's Tools and later on its replacement the Geospatial Modelling Environment (GME). 88% of all desired points could actually be reached in the field and have been successfully sampled. Our results indicate that the sampled calibration and validation sets are representative for each other and could be successfully used as interpolation data for spatial prediction purposes. With respect to soil textural fractions, for instance, equal multivariate means and variance homogeneity were found for the two datasets as evidenced by significant (P > 0.05) Hotelling T²-test (2.3 with df1 = 3, df2 = 193) and Bartlett's test statistics (6.4 with df = 6). The multivariate prediction of clay, silt and sand content using a neural network residual cokriging approach reached an explained variance level of 56%, 47% and 63%. Thus, the presented case study is a successful example of considering readily available continuous information on soil forming factors such as geology and relief as stratifying variables for designing sampling schemes in digital soil mapping projects.

  9. Mapping soil erosion susceptibility using GIS techniques within the Danube floodplain, the Calafat - Turnu Măgurele sector (Romania

    Directory of Open Access Journals (Sweden)

    Ionuş Oana

    2013-01-01

    Full Text Available The Danube floodplain, the Calafat - Turnu Măgurele sector, through its main features (topographic and climatic characteristics, land use and soil type and human activities, constitutes an area exposed to soil erosion. The main objective of the present research is to map soil erosion susceptibility using the GIS techniques for the computation and representation of areas, which are exposed to soil erosion correlated with the field data for the validation. Analyzing the entire model, the relatively simple methodology, the database consistence, the comparability of the results with the existent soil erosion values at national and local scale, we can say that the model was applied with success in the studied area (areas and classes of water erosion susceptibility: very low, low, moderate, high - Ciupercenii Noi, Desa, Măceşu de Jos, Grojdibodu, Orlea, very high - Rast, Negoi, Catane, Bistreţ, Goicea; areas and classes of wind erosion susceptibility: very low, low, moderate - Ciupercenii Noi, Dăbuleni, Ianca, high - Calafat, Poiana Mare, Desa, Goicea, Piscu Vechi, very high - Poiana Mare, Rast, Negoi, Bistreţ, Gighera, Orlea. The soil erosion susceptibility map can be useful for planning erosion control measures and for selecting suitable sites for runoff plot experiments.

  10. Use of Imaging Spectroscopy for Mapping and Quantifying the Weathering Degree of Tropical Soils in Central Brazil

    Directory of Open Access Journals (Sweden)

    Gustavo M. M. Baptista

    2011-01-01

    Full Text Available The purpose of this study was to test the feasibility of applying AVIRIS sensor (Airborne Visible/InfraRed Imaging Spectrometer for mapping and quantifying mineralogical components of three Brazilian soils, a reddish Oxisol in São João D'Aliança area (SJA and a dark reddish brown Oxisol and Ultisol in Niquelândia (NIQ counties, Goiás State. The study applied the spectral index RCGb [kaolinite/(kaolinite + gibbsite ratio] and was based on spectral absorption features of these two minerals.The RCGb index was developed for the evaluation of weathering degrees of various Brazilian soils and was validated by the analysis of soil samples spectra imaged by AVIRIS and checked against laboratory mineralogical quantification (TGA:Thermal Gravimetric Analysis. Results showed to be possible mapping and quantifying the weathering degree of the studied soils and that the two selected areas presented different weathering degrees of their soils even for a same soil type.

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

    Directory of Open Access Journals (Sweden)

    Rongjiang Yao

    Full Text Available 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

  12. Digital soil mapping for the support of delineation of Areas Facing Natural Constraints defined by common European biophysical criteria

    Science.gov (United States)

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

    2016-04-01

    One of the main objectives of the EU's Common Agricultural Policy is to encourage maintaining agricultural production in Areas Facing Natural Constraints (ANC) in order to sustain agricultural production and use natural resources, in such a way to secure both stable production and income to farmers and to protect the environment. ANC assignment has both ecological and severe economical aspects. Recently the delimitation of ANCs is suggested to be carried out by using common biophysical diagnostic criteria on low soil productivity and poor climate conditions all over Europe. The criterion system was elaborated and has been repeatedly upgraded by JRC. The operational implementation is under member state competence. This process requires application of available soil databases and proper thematic and spatial inference methods. In our paper we present the inferences applied for the latest identification and delineation of areas with low soil productivity in Hungary according to JRC biophysical criteria related to soil: limited soil drainage, texture and stoniness (coarse texture, heavy clay, vertic properties), shallow rooting depth, chemical properties (salinity, sodicity, low pH). The compilation of target specific maps were based on the available legacy and recently collected data. In the present work three different data sources were used. The most relevant available data were queried from the datasets for each mapped criterion for either direct application or for the compilation a suitable, synthetic (non-measured) parameter. In some cases the values of the target variable originated from only one, in other cases from more databases. The reference dataset used in the mapping process was set up after substantial statistical analysis and filtering. It consisted of the values of the target variable attributed to the finally selected georeferenced locations. For spatial inference regression kriging was applied. Accuracy assessment was carried out by Leave One Out

  13. Mapping erosion prone areas in the Bouhamdane watershed (Algeria using the Revised Universal Soil Loss Equation through GIS

    Directory of Open Access Journals (Sweden)

    Bouguerra Hamza

    2017-03-01

    Full Text Available Soil erosion by water is a major problem that the Northern part of Algeria witnesses nowadays; it reduces: the productivity of agricultural areas due to the loss of lands, and leads to the loss of storage capacity in reservoirs, the deterioration of water quality etc. The aim of this study is to evaluate the soil losses due to water erosion, and to identify the sectors which are potentially sensitive to water erosion in the Bouhamdane watershed, that is located in the northeastern part of Algeria. To this end, the Revised Universal Soil Loss Equation (RUSLE was used. The application of this equation takes into account five parameters, namely the rainfall erosivity, topography, soil erodibility, vegetative cover and erosion control practices. The product of these parameters under GIS using the RUSLE mathematical equation has enabled evaluating an annual average erosion rate for the Bouhamdane watershed of 11.18 t·ha-1·y-1. Based on the estimates of soil loss in each grid cell, a soil erosion risk map with five risk classes was elaborated. The spatial distribution of risk classes was 16% very low, 41% low, 28% moderate, 12% high and 3% very high. Most areas showing high and very high erosion risk occurred in the lower Bouhamdane watershed around Hammam Debagh dam. These areas require adequate erosion control practices to be implemented on a priority basis in order to conserve soil resources and reduce siltation in the reservoir.

  14. Technology and the use of acrylics for provisional dentine protection.

    Science.gov (United States)

    Kapusevska, Biljana; Dereban, Nikola; Popovska, Mirjana; Nikolovska, Julijana; Radojkova Nikolovska, Vеrа; Zabokova Bilbilova, Efka; Mijoska, Aneta

    2013-01-01

    Acrylics are compounds polymerized from monomers of acrylic, metacrylic acid or acrylonitrates. The purpose of this paper is to present the technology and use of acrylics for provisional dentine protection in the practice of dental prosthodontics. For this reason, we followed 120 clinical cases from the everyday clinical practice, divided into 4 groups of 30 patients who needed prosthetic reconstruction. The first group included cases in which we applied celluloid crowns for dentine protection, for the second group we used acrylic teeth from a set of teeth for complete dentures; in the third and fourth groups the fabrication was done with the system of an impression matrix and the acrylic resin block technique respectively. In all the examined patients, the gingival index by Silness and Loe and the vitality of the dental pulp were verified clinically, after preparation and 8 days from the placement of the provisional crown. The value for dental sensitivity measured after preparation was 2.59, and 8 days after the placement of the provisional crown it bwas 3.1. From these results we can conclude that after the 8th day from the placement of the provisional crown, there was an adaptation period, characterized by a decrease in the painful sensations. The value of the Silness and Loe gingival index measured after the preparation was 1.34, and 8 days from the placement of the provisional crown was 0.94. The results inclined us to the fact that the provisional acrylic crowns facilitated the reparation of the periodontal tissue.

  15. A Rapid, Accurate, and Efficient Method to Map Heavy Metal-Contaminated Soils of Abandoned Mine Sites Using Converted Portable XRF Data and GIS.

    Science.gov (United States)

    Suh, Jangwon; Lee, Hyeongyu; Choi, Yosoon

    2016-12-01

    The use of portable X-ray fluorescence (PXRF) and inductively coupled plasma atomic emission spectrometry (ICP-AES) increases the rapidity and accuracy of soil contamination mapping, respectively. In practice, it is often necessary to repeat the soil contamination assessment and mapping procedure several times during soil management within a limited budget. In this study, we have developed a rapid, inexpensive, and accurate soil contamination mapping method using a PXRF data and geostatistical spatial interpolation. To obtain a large quantity of high quality data for interpolation, in situ PXRF data analyzed at 40 points were transformed to converted PXRF data using the correlation between PXRF and ICP-AES data. The method was applied to an abandoned mine site in Korea to generate a soil contamination map for copper and was validated for investigation speed and prediction accuracy. As a result, regions that required soil remediation were identified. Our method significantly shortened the time required for mapping compared to the conventional mapping method and provided copper concentration estimates with high accuracy similar to those measured by ICP-AES. Therefore, our method is an effective way of mapping soil contamination if we consistently construct a database based on the correlation between PXRF and ICP-AES data.

  16. 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

    Science.gov (United States)

    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.

  17. Proposal for a Spatial Organization Model in Soil Science (The Example of the European Communities Soil Map).

    Science.gov (United States)

    King, D.; And Others

    1994-01-01

    Discusses the computational problems of automating paper-based spatial information. A new relational structure for soil science information based on the main conceptual concepts used during conventional cartographic work is proposed. This model is a computerized framework for coherent description of the geographical variability of soils, combined…

  18. La ejecución provisional de las sentencias

    OpenAIRE

    Silva Álvarez,Óscar

    2008-01-01

    Dentro de la corriente reformista del proceso civil en Chile, un lugar importante debería estar ocupado por la figura de la ejecución provisional de las sentencias judiciales, como una manifestación del derecho a la tutela judicial efectiva y un instrumento para el acortamiento de los tiempos en el proceso. El presente artículo contiene un examen teórico a la figura de la ejecución provisional, y establece las reglas técnicas de su configuración legal. También analiza los aislados casos de ta...

  19. Mapping soil particle-size fractions using additive-log ratio transformation and proximally sensed ancillary data

    Science.gov (United States)

    Zare, Ehsan; Huang, Jingyi; Triantafilis, John

    2017-04-01

    Together the three particle size fractions (PSFs) of clay, silt, and sand are the most fundamental soil properties because of their relative abundance influences the physical, chemical and biological activities in soil. Therefore, there is an increasing need for high-resolution information on spatial distribution of soil texture. Unfortunately, determining PSFs requires a laboratory method which is time-consuming. One way to add value is to use digital soil mapping. Specifically, using mathematical models, such as multiple linear regression (MLR), to couple ancillary data to PSF data. However, this approach does not account for the special requirements of compositional data. Here we demonstrated how ancillary data can be coupled via MLR modelling to an additive log-ratio transformation (ALR) of the PSF to meet these requirements. We compared these two approaches (MLR vs. ALR-MLR). We also compared the use of different ancillary data including proximally sensed gamma-ray spectrometry (i.e. RS700), electromagnetic induction (i.e. DUALEM-421S) and elevation data. In addition, we tested how prediction might be improved by using ancillary data measured on transects (which simulated measurements made on 6.5 m transects) as compared to interpolation from transects spaced 13 m and 26 m apart. Although the ALR-MLR approach did not produce significantly better results, it generated predicted soil PSFs which summed to 100. We found that for predicting PSFs at various depths, all ancillary data was useful with elevation and gamma-ray slightly better for topsoil and elevation and EM data better for subsoil prediction. In addition, a reduced transect spacing (26 m) and sampling size (9-16) can be adopted for mapping soil PSFs and soil texture across the study field.

  20. Mapping the Risk of Soil-Transmitted Helminthic Infections in the Philippines.

    Directory of Open Access Journals (Sweden)

    Ricardo J Soares Magalhães

    Full Text Available In order to increase the efficient allocation of soil-transmitted helminth (STH disease control resources in the Philippines, we aimed to describe for the first time the spatial variation in the prevalence of A. lumbricoides, T. trichiura and hookworm across the country, quantify the association between the physical environment and spatial variation of STH infection and develop predictive risk maps for each infection.Data on STH infection from 35,573 individuals across the country were geolocated at the barangay level and included in the analysis. The analysis was stratified geographically in two major regions: 1 Luzon and the Visayas and 2 Mindanao. Bayesian geostatistical models of STH prevalence were developed, including age and sex of individuals and environmental variables (rainfall, land surface temperature and distance to inland water bodies as predictors, and diagnostic uncertainty was incorporated. The role of environmental variables was different between regions of the Philippines. This analysis revealed that while A. lumbricoides and T. trichiura infections were widespread and highly endemic, hookworm infections were more circumscribed to smaller foci in the Visayas and Mindanao.This analysis revealed significant spatial variation in STH infection prevalence within provinces of the Philippines. This suggests that a spatially targeted approach to STH interventions, including mass drug administration, is warranted. When financially possible, additional STH surveys should be prioritized to high-risk areas identified by our study in Luzon.

  1. Detailed predictive mapping of acid sulfate soil occurrence using electromagnetic induction data

    DEFF Research Database (Denmark)

    Beucher, Amélie; Boman, A; Mattbäck, S

    Acid sulfate soils are often called the nastiest soils in the world (Dent & Pons 1995). Releasing a toxic combination of acidity and metals into the recipient watercourses and estuaries, these soils represent a crucial environmental problem. Moreover, these soils can have a considerable economic.......e. soil sampling and subsequent pH measurements) has typically been used for acid sulfate soils. Nonetheless, spatial modelling techniques have recently been assessed, demonstrating promising results at catchment or regional extent (Beucher et al. 2014, 2015). Furthermore, electromagnetic induction data...... machine learning approaches will be assessed using soil and environmental data, in particular proximal sensing electromagnetic data collected from a DUALEM. The measurements of the apparent soil electrical conductivity can provide data on the spatial variation of soil salinity, which is associated...

  2. Soil organic carbon and particle sizes mapping using vis–NIR, EC and temperature mobile sensor platform

    DEFF Research Database (Denmark)

    Knadel, Maria; Thomsen, Anton Gårde; Schelde, Kirsten

    2015-01-01

    1 and Voulund2) in Denmark were mapped with the Veris mobile sensor platform (MSP). MSP collected simultaneously visible near infrared spectra (vis–NIR; 350–2200 nm), electrical conductivity (EC: shallow; 0–30 cm, deep; 0–90 cm), and temperature measurements. Fuzzy k-means clustering was applied...... predictive ability for SOC was obtained using a fusion of sensor data. The calibration models based on vis–NIR spectra and temperature resulted in RMSECV = 0.14% and R2 = 0.94 in Voulund1. In Voulund2, the combination of EC, temperature and spectral data generated a SOC model with RMSECV = 0.17% and R2 = 0...... and particle sizes are costly limiting the detailed characterization of soil spatial variability and fine resolution mapping. Mobile sensors provide an alternative approach to soil analysis. They offer densely spaced georeferenced data in a cost-effective manner. In this study, two agricultural fields (Voulund...

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

    Science.gov (United States)

    2016-08-04

    SOFT-SOIL TERRAIN MAPS USING PHYSICS -BASED SIMULATION Tamer Wasfy*, Paramsothy Jayakumar**, Dave Mechergui**, and Srinivas Sanikommu** *Advanced...relations used in NRMM. The objective of this paper is to present a high-fidelity physics -based approach to accurately and reliably predict the vehicle...as a high-fidelity multibody dynamics model which includes models of the various vehicle systems including chassis, wheels /tires, suspension system

  4. Occlusal wear of provisional implant-supported restorations

    NARCIS (Netherlands)

    Santing, Hendrik J.; Kleverlaan, Cornelis J.; Werner, Arie; Feilzer, Albert J.; Raghoebar, Gerry M.; Meijer, Henny J. A.

    BACKGROUND: Implant-supported provisional restorations should be resistant to occlusal wear. PURPOSE: The purpose of this laboratory study was to evaluate three-body wear of three indirect laboratory composite resins, five chair side bis-acryl resin-based materials, and two chair side

  5. Evaluation of Vertical Marginal Adaptation of Provisional Crowns by ...

    African Journals Online (AJOL)

    2018-01-30

    Jan 30, 2018 ... Department of Prosthetic Dental Sciences, College of Dentistry,. King Saud University, Riyadh, Kingdom of Saudi Arabia. E‑mail: malrifaiy@hotmail.com. How to cite this article: Al Rifaiy MQ. Evaluation of vertical marginal adaptation of provisional crowns by digital microscope. Niger J Clin Pract. 2017 ...

  6. Where can cone penetrometer technology be applied? Development of a map of Europe regarding the soil penetrability.

    Science.gov (United States)

    Fleischer, Matthias; van Ree, Derk; Leven, Carsten

    2014-01-01

    Over the past decades, significant efforts have been invested in the development of push-in technology for site characterization and monitoring for geotechnical and environmental purposes and have especially been undertaken in the Netherlands and Germany. These technologies provide the opportunity for faster, cheaper, and collection of more reliable subsurface data. However, to maximize the technology both from a development and implementation point of view, it is necessary to have an overview of the areas suitable for the application of this type of technology. Such an overview is missing and cannot simply be read from existing maps and material. This paper describes the development of a map showing the feasibility or applicability of Direct Push/Cone Penetrometer Technology (DPT/CPT) in Europe which depends on the subsurface and its extremely varying properties throughout Europe. Subsurface penetrability is dependent on a range of factors that have not been mapped directly or can easily be inferred from existing databases, especially the maximum depth reachable would be of interest. Among others, it mainly depends on the geology, the soil mechanical properties, the type of equipment used as well as soil-forming processes. This study starts by looking at different geological databases available at the European scale. Next, a scheme has been developed linking geological properties mapped to geotechnical properties to determine basic penetrability categories. From this, a map of soil penetrability is developed and presented. Validating the output by performing field tests was beyond the scope of this study, but for the country of the Netherlands, this map has been compared against a database containing actual cone penetrometer depth data to look for possible contradictory results that would negate the approach. The map for the largest part of Europe clearly shows that there is a much wider potential for the application of Direct Push Technology than is currently

  7. Effect of provisional cements on shear bond strength of porcelain laminate veneers.

    Science.gov (United States)

    Altintas, Subutay Han; Tak, Onjen; Secilmis, Asli; Usumez, Aslihan

    2011-08-01

    The purpose of this study was to evaluate the effect of three provisional cements and two cleaning techniques on the final bond strength of porcelain laminate veneers. The occlusal third of the crowns of forty molar teeth were sectioned and embedded in autopolymerizing acrylic resin. Dentin surfaces were polished and specimens were randomly divided into four groups (n=10). Provisional restorations were fabricated and two provisional restorations were cemented onto each tooth. Restorations were fixed with one of three different provisional cements: eugenol-free provisional cement (Cavex), calcium hydroxide (Dycal), and light-cured provisional cement (Tempond Clear). Provisional restorations were removed with either a dental explorer and air-water spray, or a cleaning bur (Opticlean). In the control group, provisional restorations were not used on the surfaces of specimens. IPS Empress 2 ceramic discs were luted with a dual-cured resin cement (Panavia F). Shear bond strength was measured using a universal testing machine. Data were statistically analyzed by ANOVA, Tukey's HSD and Dunnett tests. Surfaces were examined by scanning electronic microscopy. Significant differences were found between the control group and both the light-cured provisional cement groups and the eugenol-free provisional cement-cleaning bur group (Pprovisional cement showed the lowest bond strength values. Selection of the provisional cement is an important factor in the ultimate bond strength of the final restoration. Calcium hydroxide provisional cement and cleaning with a dental explorer are advisable.

  8. Comparison of crop stress and soil maps to enhance variable rate irrigation prescriptions

    Science.gov (United States)

    Soil textural variability within many irrigated fields diminishes the effectiveness of conventional irrigation management, and scheduling methods that assume uniform soil conditions may produce less than satisfactory results. Furthermore, benefits of variable-rate application of agrochemicals, seeds...

  9. Prediction interval evaluation in modelling of soil texture for regional mapping: methodology and a case study

    Science.gov (United States)

    Ciampalini, Rossano; Martin, Manuel; Saby, Nicolas P. A.; Richer de Forges, Anne C.; Nehlig, Pierre; Martelet, Guillaume; Arrouays, Dominique

    2015-04-01

    Model uncertainty mapping represents a practical way to describe efficiency and limits of models prediction and can be calculated using different techniques. The object of this study is to determine and apply a procedure for the prediction interval (PI) evaluation for extended maps of soil granulometric fractions (i.e. clay, silt, sand) in the region "Centre" of France. Among the various methodologies for PI determination, a recent approach is the use of a non-parametric procedure evaluating the prediction interval. The PI is defined as a conventional bound of the predicted values (i.e. 95th percentile) and can be calculated as follows. Assuming a relationship between the inputs of the model and the resulting prediction error (Shrestha et al., 2006, Malone et al., 2011), the input variables-space is classified into different clusters having similar errors with a fuzzy c-means clustering technique. Then, a prediction interval (PI) is calculated for each cluster on the basis of the associated empirical distributions of the errors and considering the degree of membership belonging to each cluster. A relationship between the input variables and the computed prediction intervals is founded using a modelling procedure (calibration), then; the relationship is applied to estimate the prediction interval for the out-of-sample data (validation) (e.g. Solomatine et al., 2008, 2009, Malone et al., 2011). This approach requires the assumption of a relationships between the input variables and the errors, and, obviously the relevancy and accuracy of such approach depends on the validity of the assumption. These assumptions have been accepted in all the studies quoted above. In this work we adopted a similar procedure to the third approach. Our hypothesis is, if a correspondence is supposed and identified between confidence interval and predictors (i.e., 2.5-97.5% values, respectively), a model between predictors and PI may be used to extrapolate it to the whole map. This

  10. Mapping soil deformation around plant roots using in vivo 4D X-ray Computed Tomography and Digital Volume Correlation.

    Science.gov (United States)

    Keyes, S D; Gillard, F; Soper, N; Mavrogordato, M N; Sinclair, I; Roose, T

    2016-06-14

    The mechanical impedance of soils inhibits the growth of plant roots, often being the most significant physical limitation to root system development. Non-invasive imaging techniques have recently been used to investigate the development of root system architecture over time, but the relationship with soil deformation is usually neglected. Correlative mapping approaches parameterised using 2D and 3D image data have recently gained prominence for quantifying physical deformation in composite materials including fibre-reinforced polymers and trabecular bone. Digital Image Correlation (DIC) and Digital Volume Correlation (DVC) are computational techniques which use the inherent material texture of surfaces and volumes, captured using imaging techniques, to map full-field deformation components in samples during physical loading. Here we develop an experimental assay and methodology for four-dimensional, in vivo X-ray Computed Tomography (XCT) and apply a Digital Volume Correlation (DVC) approach to the data to quantify deformation. The method is validated for a field-derived soil under conditions of uniaxial compression, and a calibration study is used to quantify thresholds of displacement and strain measurement. The validated and calibrated approach is then demonstrated for an in vivo test case in which an extending maize root in field-derived soil was imaged hourly using XCT over a growth period of 19h. This allowed full-field soil deformation data and 3D root tip dynamics to be quantified in parallel for the first time. This fusion of methods paves the way for comparative studies of contrasting soils and plant genotypes, improving our understanding of the fundamental mechanical processes which influence root system development. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Map of Natural (Landscape) and Permafrost Zones and the Net of Soil Temperature Meteorological Stations in Russia and Middle Asian Mountains, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set is a vector coverage of the Map of Natural Landscape and Permafrost Zones and the Net of Soil Temperature Meteorological Stations in Russia and Middle...

  12. Soils

    Science.gov (United States)

    Emily Moghaddas; Ken Hubbert

    2014-01-01

    When managing for resilient forests, each soil’s inherent capacity to resist and recover from changes in soil function should be evaluated relative to the anticipated extent and duration of soil disturbance. Application of several key principles will help ensure healthy, resilient soils: (1) minimize physical disturbance using guidelines tailored to specific soil types...

  13. Geospatial approach in mapping soil erodibility using CartoDEM – A ...

    Indian Academy of Sciences (India)

    Soil erodibility is one of the most important factors used in spatial soil erosion risk assessment. Soil information derived .... management. Availability of DEM at varying spa- tial resolution (10–90 m) facilitated the characteri- zation of terrain parameters at various scales. The ... is 805 ha. The climate is characterized as humid.

  14. Geospatial approach in mapping soil erodibility using CartoDEM–A ...

    Indian Academy of Sciences (India)

    Correlation analysis among K-factor and terrain parameters showed highest correlation of soil erodibilty with TWI (r 2 =0.561) followed by slope (r 2 = 0.33). A multiple linear regression model was developed to derive soil erodibilty using terrain parameters. A set of 20 soil sample points were used to assess the accuracy of ...

  15. Farmers' indicators for soil erosion mapping and crop yield estimation in central highlands of Kenya

    NARCIS (Netherlands)

    Okoba, B.O.

    2005-01-01

    The central highlands of Kenya is characterised by abundant rainfall and fertile volcanic soils that support agricultural activities but problems of soil erosion are widespread in the region. Past efforts to control the soil erosion problems were through application of regulations that enforced

  16. Physical characterization, spectral response and remotely sensed mapping of Mediterranean soil surface crusts

    NARCIS (Netherlands)

    Jong, S.M. de; Addink, E.A.; Duijsing, D.; Beek, L.P.H. van

    2011-01-01

    Soil surface crusting and sealing are frequent but unfavorable processes in Mediterranean areas. Soil crust and seals form on bare soil subject to high-intensity rainfall, resulting in a hard, impenetrable layer that impedes infiltration and hampers the germination and establishment of plants. The

  17. Baseline map of organic carbon in Australian soil to support national carbon accounting and monitoring under climate change.

    Science.gov (United States)

    Viscarra Rossel, Raphael A; Webster, Richard; Bui, Elisabeth N; Baldock, Jeff A

    2014-09-01

    We can effectively monitor soil condition-and develop sound policies to offset the emissions of greenhouse gases-only with accurate data from which to define baselines. Currently, estimates of soil organic C for countries or continents are either unavailable or largely uncertain because they are derived from sparse data, with large gaps over many areas of the Earth. Here, we derive spatially explicit estimates, and their uncertainty, of the distribution and stock of organic C in the soil of Australia. We assembled and harmonized data from several sources to produce the most comprehensive set of data on the current stock of organic C in soil of the continent. Using them, we have produced a fine spatial resolution baseline map of organic C at the continental scale. We describe how we made it by combining the bootstrap, a decision tree with piecewise regression on environmental variables and geostatistical modelling of residuals. Values of stock were predicted at the nodes of a 3-arc-sec (approximately 90 m) grid and mapped together with their uncertainties. We then calculated baselines of soil organic C storage over the whole of Australia, its states and territories, and regions that define bioclimatic zones, vegetation classes and land use. The average amount of organic C in Australian topsoil is estimated to be 29.7 t ha(-1) with 95% confidence limits of 22.6 and 37.9 t ha(-1) . The total stock of organic C in the 0-30 cm layer of soil for the continent is 24.97 Gt with 95% confidence limits of 19.04 and 31.83 Gt. This represents approximately 3.5% of the total stock in the upper 30 cm of soil worldwide. Australia occupies 5.2% of the global land area, so the total organic C stock of Australian soil makes an important contribution to the global carbon cycle, and it provides a significant potential for sequestration. As the most reliable approximation of the stock of organic C in Australian soil in 2010, our estimates have important applications. They could support

  18. Mapping of Bare Soil Surface Parameters (Moisture, Roughness, Texture) from one TerraSAR-X Radar Configuration

    Science.gov (United States)

    Zribi, Mehrez; Gorrab, Azza; Baghdadi, Nicolas; Chabaane, Zohra Lili

    2016-08-01

    In this paper, surface bare soil parameters (moisture, roughness and texture) mapping was carried out in central Tunisia (North Africa) using one TerraSAR-X radar configuration (one incidence angle, one polarization). Firstly, we analyzed statistically the relationships between TerraSAR-X backscattering signals function of soil moisture and different roughness parameters (the root mean square height Hrms, the Zs and the Zg parameters) at 36° and HH polarization. Results have shown a high sensitivity of real radar data to all soil parameters. Then, we proposed an algorithm combing the TerraSAR-X images with different continuous thetaprobe measurements for the retrieval of surface soil moisture. Empirical relationship was established between the mean moisture values retrieved from the SAR images and the percentage of clay over 36 test fields. Validation of the proposed approach was carried out over a second set of 34 fields, showing that highly accurate clay estimations can be achieved. Finally, for spatial and temporal surface roughness estimation, we proposed empirical relationships between radar and soil roughness parameters (Hrms and Zg parameters). The proposed model was calibrated over 39 test fields, and then validated over 40 other plots.

  19. Modeling and mapping of cadmium in soils based on qualitative and quantitative auxiliary variables in a cadmium contaminated area.

    Science.gov (United States)

    Cao, Shanshan; Lu, Anxiang; Wang, Jihua; Huo, Lili

    2017-02-15

    The aim of this study was to measure the improvement in mapping accuracy of spatial distribution of Cd in soils by using geostatistical methods combined with auxiliary factors, especially qualitative variables. Significant correlations between Cd content and correlation environment variables that are easy to obtain (such as topographic factors, distance to residential area, land use types and soil types) were analyzed systematically and quantitatively. Based on 398 samples collected from a Cd contaminated area (Hunan Province, China), we estimated the spatial distribution of Cd in soils by using spatial interpolation models, including ordinary kriging (OK), and regression kriging (RK) with each auxiliary variable, all quantitative variables (RKWQ) and all auxiliary variables (RKWA). Results showed that mapping with RK was more consistent with the sampling data of the spatial distribution of Cd in the study area than mapping with OK. The performance indicators (smaller mean error, mean absolute error, root mean squared error values and higher relative improvement of RK than OK) indicated that the introduction of auxiliary variables can improve the prediction accuracy of Cd in soils for which the spatial structure could not be well captured by point-based observation (nugget to sill ratio=0.76) and strong relationships existed between variables to be predicted and auxiliary variables. The comparison of RKWA with RKWQ further indicated that the introduction of qualitative variables improved the prediction accuracy, and even weakened the effects of quantitative factors. Furthermore, the significantly different relative improvement with similar R2 and varying spatial dependence showed that a reasonable choice of auxiliary variables and analysis of spatial structure of regression residuals are equally important to ensure accurate predictions. Copyright © 2016. Published by Elsevier B.V.

  20. The grey areas in soil pollution risk mapping : The distinction between cases of soil pollution and increased background levels

    NARCIS (Netherlands)

    Gaast, N. van der; Leenaers, H.; Zegwaard, J.

    1998-01-01

    The progress of soil clean up in the Netherlands is severely hindered by the lack of common agreement on how to describe the grey areas of increased background levels of pollutants. In this study practical methods are proposed in which background levels are described as distribution functions within

  1. Soil Organic Matter Map of Europe. Estimates of soil organic matter content of the topsoil of FAO-Unesco soil units

    NARCIS (Netherlands)

    Fraters B; Bouwman AF; Thewessen TJM

    1993-01-01

    One of the threats to groundwater is the leaching of pesticides. A major factor determining the migration of most pesticides in soil is their organic matter content. Using classification criteria, data on organic matter content in European and American soil profiles are described, and common

  2. Mapping soil organic carbon content and composition across Australia to assess vulnerability to climate change

    Science.gov (United States)

    Viscarra Rossel, R. A.

    2015-12-01

    We can effectively monitor soil condition—and develop sound policies to offset the emissions of greenhouse gases—only with accurate data from which to define baselines. Currently, estimates of soil organic C for countries or continents are either unavailable or largely uncertain because they are derived from sparse data, with large gaps over many areas of the Earth. Here, we derive spatially explicit estimates, and their uncertainty, of the distribution and stock of organic C content and composition in the soil of Australia. The composition of soil organic C may be characterized by chemical separation or physical fractionation based on either particle size or particle density (Skjemstad et al., 2004; Gregorich et al., 2006; Kelleher&Simpson, 2006; Zimmermann et al., 2007). In Australia, for example, Skjemstad et al. (2004) used physical separation of soil samples into 50-2000 and assess the vulnerability of soil organic C to for instance climate change.

  3. Mapping soil organic carbon stock in the area of Neamtu Catchment, Northeastern Romania

    Science.gov (United States)

    Breaban, Ana-Ioana; Bobric, Elena-Diana; Breaban, Iuliana-Gabriela; Rusu, Eugen

    2017-04-01

    The quantification of soil organic carbon stocks and its spatial extent is directly influenced by the land cover. The aim of the study is to quantify both the spatial distribution of soil organic carbon and stocks under different soil types and land uses in an area of 41.808,04 ha in northeastern part of Romania. It has been studied the evolution of carbon stocks over time, taking into account the change of land use between 1990-2012 under 5 classes: forests, pastures, arable land, orchard and built spaces. Common soils are Cambisols, Fluvisols, Phaezems, and Luvisols, forest being the predominant land use. The most important loss of soil organic carbon occurs as a result of changes in the supply of biomass supplying litter and therefore the process of bioaccumulation. The samples were collected from 100 representative soil profiles and analyzed with Analytik Jena multi N/C 2100 with HT 1300 solid module. Based on the soil organic carbon, C/N ratio and texture the values of those parameters varied from high values in Ao and Bv horizons to lower values in C horizon. In order to model soil organic carbon concentration were used different interpolation techniques (regression and ordinary -kriging, IDW) at different sampling densities for each depth to 100 cm, using a Gaussian approach to estimate the uncertainty. It is noticeable that soil organic carbon had a positive correlation with different types of land uses and a negative correlation with the elevation, being a decreasing trend of the carbon stocks sequestered in biomass, litter and soil. In the upper part of the profiles, the soil organic carbon stock considerably varied for forest land between 6.5-7.23 kg C/sqm) and agricultural land (3.67-4.65 kg C/sqm). The kriging regression evidenced a good variability of the calculated root mean square errors of the predicted soil organic carbon stocks.

  4. Mapping Historic Hookworm Disease Prevalence in the Southern Us, Comparing Percent Prevalence with Percent Soil Drainage Type Using GIS

    Directory of Open Access Journals (Sweden)

    Alice L. Anderson

    2011-01-01

    Full Text Available Mapping of Historic US Hookworm prevalence data from the Rockefeller Sanitary Commission (early 1900s using current GIS (Geographic Information System software (county shape files illustrates the extremely high prevalence of hookworm disease (Uncariasis in the Southeastern US at the time. Some counties in 7 states recorded 50% to 100% of the population with positive screens for hookworm in a monumental surveillance and treatment campaign. Narrative descriptions mentioned higher prevalence in “sand districts” vs. “clay districts”. In order to validate this description for historic data, further GIS databases (STATSGO were used to classify and quantify the % acreage in Eastern North Carolina falling into moderately- to well-drained soil types. These were then mapped and compared with the historic prevalence data. Most severely infested counties had at least 50% moderately to well-drained soil. Further analysis on soil data for other states with “coastal plains” could provide more background information on Environmental conditions for hookworm prevalence and distribution in US history. “Since history has no properly scientific value, its only purpose is educative. And if historians neglect to educate the public, if they fail to interest it intelligently in the past, then all their historical learning is valueless except in so far as it educates themselves”. Trevelyan, (1922.

  5. Advancing analysis of spatio-temporal variations of soil nutrients in the water level fluctuation zone of China's Three Gorges Reservoir using self-organizing map.

    Science.gov (United States)

    Ye, Chen; Li, Siyue; Yang, Yuyi; Shu, Xiao; Zhang, Jiaquan; Zhang, Quanfa

    2015-01-01

    The ~350 km2 water level fluctuation zone (WLFZ) in the Three Gorges Reservoir (TGR) of China, situated at the intersection of terrestrial and aquatic ecosystems, experiences a great hydrological change with prolonged winter inundation. Soil samples were collected in 12 sites pre- (September 2008) and post submergence (June 2009) in the WLFZ and analyzed for soil nutrients. Self-organizing map (SOM) and statistical analysis including multi-way ANOVA, paired-T test, and stepwise least squares multiple regression were employed to determine the spatio-temporal variations of soil nutrients in relation to submergence, and their correlations with soil physical characteristics. Results showed significant spatial variability in nutrients along ~600 km long shoreline of the TGR before and after submergence. There were higher contents of organic matter, total nitrogen (TN), and nitrate (NO3-) in the lower reach and total phosphorus (TP) in the upper reach that were primarily due to the spatial variations in soil particle size composition and anthropogenic activities. Submergence enhanced soil available potassium (K), while significantly decreased soil N, possibly due to the alterations of soil particle size composition and increase in soil pH. In addition, SOM analysis determined important roles of soil pH value, bulk density, soil particle size (i.e., silt and sand) and nutrients (TP, TK, and AK) on the spatial and temporal variations in soil quality. Our results suggest that urban sewage and agricultural runoffs are primary pollutants that affect soil nutrients in the WLFZ of TGR.

  6. Advancing Analysis of Spatio-Temporal Variations of Soil Nutrients in the Water Level Fluctuation Zone of China’s Three Gorges Reservoir Using Self-Organizing Map

    Science.gov (United States)

    Ye, Chen; Li, Siyue; Yang, Yuyi; Shu, Xiao; Zhang, Jiaquan; Zhang, Quanfa

    2015-01-01

    The ~350 km2 water level fluctuation zone (WLFZ) in the Three Gorges Reservoir (TGR) of China, situated at the intersection of terrestrial and aquatic ecosystems, experiences a great hydrological change with prolonged winter inundation. Soil samples were collected in 12 sites pre- (September 2008) and post submergence (June 2009) in the WLFZ and analyzed for soil nutrients. Self-organizing map (SOM) and statistical analysis including multi-way ANOVA, paired-T test, and stepwise least squares multiple regression were employed to determine the spatio-temporal variations of soil nutrients in relation to submergence, and their correlations with soil physical characteristics. Results showed significant spatial variability in nutrients along ~600 km long shoreline of the TGR before and after submergence. There were higher contents of organic matter, total nitrogen (TN), and nitrate (NO3-) in the lower reach and total phosphorus (TP) in the upper reach that were primarily due to the spatial variations in soil particle size composition and anthropogenic activities. Submergence enhanced soil available potassium (K), while significantly decreased soil N, possibly due to the alterations of soil particle size composition and increase in soil pH. In addition, SOM analysis determined important roles of soil pH value, bulk density, soil particle size (i.e., silt and sand) and nutrients (TP, TK, and AK) on the spatial and temporal variations in soil quality. Our results suggest that urban sewage and agricultural runoffs are primary pollutants that affect soil nutrients in the WLFZ of TGR. PMID:25789612

  7. Bacterial leakage of provisional restorative materials used in endodontics.

    Science.gov (United States)

    Hartwell, Gary R; Loucks, Carina A; Reavley, Brenton A

    2010-04-01

    To test the bacterial sealing ability of commonly used provisional endodontic restorative materials. This study investigated Cavit (3M ESPE), Ketac (3M ESPE), DuoTemp (Coltane/Whaledent), and a combination technique using Ketac and Cavit. One hundred molars were randomly selected and then mounted in an apparatus that isolated the crown portion of the tooth. Provisional restorative materials were placed in an open access following manufacturer guidelines. Streptococcus mutans was applied to the samples, and results were tabulated over the course of 4 weeks. Cavit and DuoTemp performed the best, and Ketac performed the worst. After 14 days, however, all materials leaked in over half of the samples. No material can be recommended as superior in providing a reliable seal after 14 days.

  8. Provisional Crown Dislodgement during Scuba Diving: A Case of Barotrauma

    OpenAIRE

    Meenal Nitin Gulve; Nitin Dilip Gulve

    2013-01-01

    Changes in ambient pressure, for example, during flying, diving, or hyperbaric oxygen therapy, can lead to barotrauma. Although it may seem that this issue was neglected in dental education and research in recent decades, familiarity with and understanding of these facts may be of importance for dental practitioners. We report the case of a patient who experienced barotrauma involving dislodgement of a provisional crown during scuba diving. Patients who are exposed to pressure changes as a pa...

  9. Immediately Loaded Intraorally Welded Complete-Arch Maxillary Provisional Prosthesis.

    Science.gov (United States)

    Albiero, Alberto Maria; Benato, Renato; Fincato, Andrea

    2015-01-01

    Guided implant surgery is not completely accurate when using computer-designed stereolithographic surgical guides. Complications are frequently reported when combining computer-guided flapless surgery with an immediately loaded prefabricated prosthesis. Achieving passive fit of a prefabricated prosthesis on the inserted implants the same day of the surgery can be difficult. The aim of this report is to show a new treatment approach to immediately loaded implants inserted with computer-guided surgery using an intraoral welded full-arch provisional prosthesis.

  10. In vitro color stability of provisional restorative materials

    Directory of Open Access Journals (Sweden)

    Hamid Jalali

    2012-01-01

    Aims: The purpose of this study was to investigate the effect of tea on provisional restorative materials. Setting and Design: This study was designed to measure the degree of color change of three acrylic resin provisional materials, before and after immersion in artificial saliva and artificial saliva-tea solution for 2 and 4 weeks. Materials and Methods : Three types of acrylic provisional materials (duralay, tempron, acropars TRP, were studied. Twenty disks (20±0.1 mm by 2±0.05 mm were fabricated from each material. Specimens were polished with acrylic bur using pumice and diamond polishing paste. Base line color was measured using a spectrophotometer. Ten disks were stored in artificial saliva and 10 were stored in a solution of artificial saliva and tea at room temperature. Color measurements were made after 2 and 4 weeks of immersion. Statistical analysis used: Differences in color changes were compared by two way ANOVA, across the six groups, followed by a Turkey-Kramer′s multiple comparison test. Results: For specimens immersed in artificial saliva, the color change of methyl methacrylate materials; duralay (ΔE=4.94 and tempron (ΔE=6.54, was significantly more than butyl methacrylate material; acropars (ΔE=4.10. After immersion in an artificial saliva- tea solution, tempron exhibited less color change (ΔE=8.50 compared to duralay (ΔE=10.93 and acropars (ΔE=15.64. Conclusion: Color stability of methyl methacrylate is higher than butyl methacrylates so if provisional materials are used for extended periods of time; tempron is preferred.

  11. Update to the legend of the reconnaissance soil map of Espírito Santo state and the implementation of Geobases interface for data usage in GIS

    Directory of Open Access Journals (Sweden)

    Alexson de Mello Cunha

    2016-12-01

    Full Text Available The objective of this study was the upgrade of soil mapping units defined in surveys published by the Radambrasil/ IBGE in 1983 and 1987, with the main focus on the clas - ses of soils. To accomplish this, data from representative soil profiles of those surveys were used to classify them in the current Brazilian Classification System. The mapping units which do not have representative profiles were updated based solely on the direct correlation between the denomination used in the old and current classification. This work has also updated the legend of the reconnaissance soil map. The layer of information related to soil, in shape format, containing an attribute table with data regarding mapping units and the respective updated legends (taxonomy, symbols and colors is currently available and can be downloaded by the general public using the Geobases browser. A specific geographic interface for the partners of Geobases dedicated to soil studies has also been created. This interface allows the analysis, acquisition and input of new data, which contributes to the non-duplication of efforts and financial resources on activities of surveying, registering and maintenance of geospatial database related to soils in the State

  12. School Water, Sanitation, and Hygiene, Soil-Transmitted Helminths, and Schistosomes: National Mapping in Ethiopia.

    Directory of Open Access Journals (Sweden)

    Jack E T Grimes

    2016-03-01

    Full Text Available It is thought that improving water, sanitation, and hygiene (WASH might reduce the transmission of schistosomes and soil-transmitted helminths, owing to their life cycles. However, few large-scale studies have yet assessed the real extent of associations between WASH and these parasites.In the 2013-2014 Ethiopian national mapping of infections with these parasites, school WASH was assessed alongside infection intensity in children, mostly between 10 and 15 years of age. Scores were constructed reflecting exposure to schistosomes arising from water collection for schools, from freshwater sources, and the adequacy of school sanitation and hygiene facilities. Kendall's τb was used to test the WASH scores against the school-level arithmetic mean intensity of infection with each parasite, in schools with at least one child positive for the parasite in question. WASH and parasitology data were available for 1,645 schools. More frequent collection of water for schools, from open freshwater sources was associated with statistically significantly higher Schistosoma mansoni infection intensity (Kendall's τb = 0.097, 95% confidence interval, CI: 0.011 to 0.18, better sanitation was associated with significantly lower Ascaris lumbricoides intensity (Kendall's τb = -0.067, 95% CI: -0.11 to -0.023 and borderline significant lower hookworm intensity (Kendall's τb = -0.039, 95% CI: -0.090 to 0.012, P = 0.067, and better hygiene was associated with significantly lower hookworm intensity (Kendall's τb = -0.076, 95% CI: -0.13 to -0.020. However, no significant differences were observed when comparing sanitation and infection with S. mansoni or Trichuris trichiura, or hygiene and infection with A. lumbricoides or T. trichiura.Improving school WASH may reduce transmission of these parasites. However, different forms of WASH appear to have different effects on infection with the various parasites, with our analysis finding the strongest associations between

  13. School Water, Sanitation, and Hygiene, Soil-Transmitted Helminths, and Schistosomes: National Mapping in Ethiopia.

    Science.gov (United States)

    Grimes, Jack E T; Tadesse, Gemechu; Mekete, Kalkidan; Wuletaw, Yonas; Gebretsadik, Abeba; French, Michael D; Harrison, Wendy E; Drake, Lesley J; Gardiner, Iain A; Yard, Elodie; Templeton, Michael R

    2016-03-01

    It is thought that improving water, sanitation, and hygiene (WASH) might reduce the transmission of schistosomes and soil-transmitted helminths, owing to their life cycles. However, few large-scale studies have yet assessed the real extent of associations between WASH and these parasites. In the 2013-2014 Ethiopian national mapping of infections with these parasites, school WASH was assessed alongside infection intensity in children, mostly between 10 and 15 years of age. Scores were constructed reflecting exposure to schistosomes arising from water collection for schools, from freshwater sources, and the adequacy of school sanitation and hygiene facilities. Kendall's τb was used to test the WASH scores against the school-level arithmetic mean intensity of infection with each parasite, in schools with at least one child positive for the parasite in question. WASH and parasitology data were available for 1,645 schools. More frequent collection of water for schools, from open freshwater sources was associated with statistically significantly higher Schistosoma mansoni infection intensity (Kendall's τb = 0.097, 95% confidence interval, CI: 0.011 to 0.18), better sanitation was associated with significantly lower Ascaris lumbricoides intensity (Kendall's τb = -0.067, 95% CI: -0.11 to -0.023) and borderline significant lower hookworm intensity (Kendall's τb = -0.039, 95% CI: -0.090 to 0.012, P = 0.067), and better hygiene was associated with significantly lower hookworm intensity (Kendall's τb = -0.076, 95% CI: -0.13 to -0.020). However, no significant differences were observed when comparing sanitation and infection with S. mansoni or Trichuris trichiura, or hygiene and infection with A. lumbricoides or T. trichiura. Improving school WASH may reduce transmission of these parasites. However, different forms of WASH appear to have different effects on infection with the various parasites, with our analysis finding the strongest associations between water and S

  14. Timing of erosion and satellite data: a multi-resolution approach to soil risk mapping

    NARCIS (Netherlands)

    Vrieling, A.; Jong, de S.M.; Sterk, G.; Rodrigues, S.C.

    2008-01-01

    Erosion reduces soil productivity and causes negative downstream impacts. Erosion processes occur on areas with erodible soils and sloping terrain when high-intensity rainfall coincides with limited vegetation cover. Timing of erosion events has implications on the selection of satellite imagery,

  15. Mapping Soil Physical Structure of Loamy Agricultural Fields for Assessing Localised Potential Leaching Risks

    DEFF Research Database (Denmark)

    Nørgaard, Trine; Vendelboe, Anders Lindblad; Olsen, Preben

    -facilitated transport plays an important role in the leaching of phosphorus and other strongly sorbing compounds. Interesting negative correlations was obtained between bulk density and the 5% tritium tracer arrival time, suggesting soil compaction level to be one of the controls for formation of functional macropore...... in Silstrup was evaluated based on soil texture, structural parameters, tritium breakthrough curves, and colloid- and phosphorus leaching to investigate the link between the leaching of pesticides such as TFMP and soil structure. Bulk soil was sampled from the A-horizon in a 15 x 15 m grid across the field......, and according to soil texture analyses the clay content was ranging from 14.2 to 18.9%, whereas the organic carbon (OC) content was ranging between 1.7 and 2.2%. Clay content increased to the North and OC content to the South. It was found that there is a risk for pronounced leaching to take place from...

  16. Mapping tillage operations over peri-urban croplands using a synchronous SPOT4/ASAR ENVISAT pair and soil roughness measurements

    Science.gov (United States)

    Vaudour, Emmanuelle; Baghdadi, Nicolas; Gilliot, Jean-Marc

    2014-05-01

    Tillage operations (TOs) affect nutrient uptake, carbon sequestration, water and CO2 exchanges in soil, and therefore impact soil ecology together with biophysical processes such as soil erosion, leaching, run-off and infiltration. They are critical for parameterizing complex dynamic models of carbon and nitrogen. This study done in the framework of the Prostock-Gessol3 project presents an approach for mapping TOs of bare agricultural fields over a peri-urban area characterized by conventional tillage system in the western suburbs of Paris (France), combining synchronous SPOT4 and ENVISAT/ASAR images (HH and HV polarizations). Spatial modeling relied on 57 reference within-field areas named 'reference zones' (RZs) homogeneous for their soil properties, constructed in the vicinity of 57 roughness measurement locations and spread across 20 agricultural fields for which TOs were known. Soil roughness expressed as the standard deviation of surface height (Hrms) was estimated on the ground with a fully automatic photogrammetric method based on the processing of a set of overlapping pictures taken from different viewpoints from a simple digital camera all around a rectangular frame. The relationship was studied between the mean backscattering coefficient of the ASAR image and Hrms choosing a limited set of 28 RZs, on which successive random selections of training/validating RZs were then performed; the remaining 29 RZs were kept for validating the final map results. Six supervised per-pixel classifiers were used in order to map 2 TOs classes (seedbed&harrowed and late winter plough) in addition to 4 landuse classes (forest, urban,crops and grass, water bodies): support vector machine with polynomial kernel (pSVM), SVM with radial basis kernel (rSVM), artificial neural network (ANN), Maximum Likelihood (ML), regression tree (RT), and random forests (RF). All 6 classifiers were implemented in a bootstrapping approach in order to assess the uncertainty of map results. The

  17. In-Field, In Situ, and In Vivo 3-Dimensional Elemental Mapping for Plant Tissue and Soil Analysis Using Laser-Induced Breakdown Spectroscopy

    Directory of Open Access Journals (Sweden)

    Chunjiang Zhao

    2016-10-01

    Full Text Available Sensing and mapping element distributions in plant tissues and its growth environment has great significance for understanding the uptake, transport, and accumulation of nutrients and harmful elements in plants, as well as for understanding interactions between plants and the environment. In this study, we developed a 3-dimensional elemental mapping system based on laser-induced breakdown spectroscopy that can be deployed in- field to directly measure the distribution of multiple elements in living plants as well as in the soil. Mapping is performed by a fast scanning laser, which ablates a micro volume of a sample to form a plasma. The presence and concentration of specific elements are calculated using the atomic, ionic, and molecular spectral characteristics of the plasma emission spectra. Furthermore, we mapped the pesticide residues in maize leaves after spraying to demonstrate the capacity of this method for trace elemental mapping. We also used the system to quantitatively detect the element concentrations in soil, which can be used to further understand the element transport between plants and soil. We demonstrate that this method has great potential for elemental mapping in plant tissues and soil with the advantages of 3-dimensional and multi-elemental mapping, in situ and in vivo measurement, flexible use, and low cost.

  18. Provisional implants for immediate restoration of partially edentulous jaws: a clinical study.

    Science.gov (United States)

    Krennmair, Gerald; Krainhöfner, Martin; Weinländer, Michael; Piehslinger, Eva

    2008-01-01

    The aim of this study was to evaluate the use of provisional implants, which can provide patients with provisional fixed partial dentures during the healing time of augmentation procedures and/or during the osseointegration period of definitive implants until delivery of the definitive prosthesis. Thirty-one patients were consecutively included in the study. Eighteen patients (group A, primary simultaneous group) were initially treated simultaneously with provisional and definitive implants and provided with 18 interim fixed partial dentures. Thirteen patients (group B) received provisional implants in a staggered procedure. In the first stage of group B patients (augmentation phase), provisional implants were placed to bridge the augmentation phase and for anchoring 13 interim fixed partial dentures. In the second stage (secondary simultaneous group), patients of group B received provisional implants to bridge the osseointegration phase for simultaneously placed definitive implants by further use of 13 interim fixed partial dentures. All patients were followed from provisional implant and definitive implant placement to delivery of the definitive prosthesis. Loss of provisional implants and interim fixed partial dentures was noted, and stability of provisional implants was evaluated using the Periotest device. The procedures of immediate rehabilitation with fixed partial dentures using provisional implants were subjectively rated by patients with regard to satisfaction, treatment period, and acceptance. In 31 patients, 44 provisional fixed partial dentures were supported by 98 provisional implants. No provisional implant loss in group A or group B-second stage was observed. Only 3 (3%) provisional implants were lost in group B-first stage during the augmentation phase. Incidence (90.8% versus 9.2%) and stability (Periotest values: 8.6 +/- 3.9 versus 4.8 +/- 2.7) of provisional implants differed significantly between maxilla and mandible (P fixed partial dentures

  19. Use of Imaging Spectroscopy for Mapping and Quantifying the Weathering Degree of Tropical Soils in Central Brazil

    OpenAIRE

    Baptista, Gustavo M. M.; Rodrigo S. Corrêa; Perseu F. dos Santos; José S. Madeira Netto; Meneses, Paulo R.

    2011-01-01

    The purpose of this study was to test the feasibility of applying AVIRIS sensor (Airborne Visible/InfraRed Imaging Spectrometer) for mapping and quantifying mineralogical components of three Brazilian soils, a reddish Oxisol in São João D'Aliança area (SJA) and a dark reddish brown Oxisol and Ultisol in Niquelândia (NIQ) counties, Goiás State. The study applied the spectral index RCGb [kaolinite/(kaolinite + gibbsite) ratio] and was based on spectral absorption features of these two minerals....

  20. Effect of Provisional Cements on Shear Bond Strength of Porcelain Laminate Veneers

    Science.gov (United States)

    Altintas, Subutay Han; Tak, Onjen; Secilmis, Asli; Usumez, Aslihan

    2011-01-01

    Objectives: The purpose of this study was to evaluate the effect of three provisional cements and two cleaning techniques on the final bond strength of porcelain laminate veneers. Methods: The occlusal third of the crowns of forty molar teeth were sectioned and embedded in autopolymerizing acrylic resin. Dentin surfaces were polished and specimens were randomly divided into four groups (n=10). Provisional restorations were fabricated and two provisional restorations were cemented onto each tooth. Restorations were fixed with one of three different provisional cements: eugenol-free provisional cement (Cavex), calcium hydroxide (Dycal), and light-cured provisional cement (Tempond Clear). Provisional restorations were removed with either a dental explorer and air-water spray, or a cleaning bur (Opticlean). In the control group, provisional restorations were not used on the surfaces of specimens. IPS Empress 2 ceramic discs were luted with a dual-cured resin cement (Panavia F). Shear bond strength was measured using a universal testing machine. Data were statistically analyzed by ANOVA, Tukey’s HSD and Dunnett tests. Surfaces were examined by scanning electronic microscopy. Results: Significant differences were found between the control group and both the light-cured provisional cement groups and the eugenol-free provisional cement-cleaning bur group (P<.05). Groups that had received light-cured provisional cement showed the lowest bond strength values. Conclusions: Selection of the provisional cement is an important factor in the ultimate bond strength of the final restoration. Calcium hydroxide provisional cement and cleaning with a dental explorer are advisable. PMID:21912495

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

    Science.gov (United States)

    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

  2. Mapping Soil Carbon from Cradle to Grave: 'Omic and Isotope Based Measurements of Root C Transformations

    Science.gov (United States)

    Pett-Ridge, J.; Nuccio, E. E.; Shi, S.; Neurath, R.; Brodie, E.; Zhou, J.; Lipton, M. S.; Herman, D.; Firestone, M.

    2014-12-01

    Carbon cycling in the rhizosphere is a nexus of biophysical interactions between plant roots, microorganisms, and the soil organo-mineral matrix. Plant roots are the primary inputs of soil organic C; the presence of roots significantly alters rates of organic matter mineralization by soil microbes. Our research on how roots influence decomposition of soil organic matter in both simplified and complex microcosms uses geochemical characterization, molecular microbiology, isotope tracing, 'omics and novel imaging approaches ('ChipSIP' and 'STXM-SIMS') to trace the fate of isotopically labelled root exudates and plant tissues. Our work seeks to understand the genomic basis for how organic C transformation and decomposition in soil is altered by interactions between plant roots and the soil microbial community (bacteria, archaea, fungi, microfauna). We hypothesize that root-exudate stimulation of soil microbial populations results in the altered expression of transcripts and proteins involved in decomposition of macromolecular C compounds. Using an isotope array that allows us to follow root C into bacterial, fungal, and microfaunal communities, we have tracked movement of 13C from labeled exudates and 15N from labeled root litter into the soil microbial community, and linked this data to 16S profiles and community gene transcripts. By integrating stable isotopes as tracers of natural resource utilization (i.e. root litter), and analysis of the functional properties of the communities that respond to those resources, we can identify the molecular pathways that are stimulated in the soil microbiome in response to root litter, living roots, and their interfaces.

  3. MAPPING SPATIAL MOISTURE CONTENT OF UNSATURATED AGRICULTURAL SOILS WITH GROUND-PENETRATING RADAR

    Directory of Open Access Journals (Sweden)

    O. Shamir

    2016-06-01

    Full Text Available Soil subsurface moisture content, especially in the root zone, is important for evaluation the influence of soil moisture to agricultural crops. Conservative monitoring by point-measurement methods is time-consuming and expensive. In this paper we represent an active remote-sensing tool for subsurface spatial imaging and analysis of electromagnetic physical properties, mostly water content, by ground-penetrating radar (GPR reflection. Combined with laboratory methods, this technique enables real-time and highly accurate evaluations of soils' physical qualities in the field. To calculate subsurface moisture content, a model based on the soil texture, porosity, saturation, organic matter and effective electrical conductivity is required. We developed an innovative method that make it possible measures spatial subsurface moisture content up to a depth of 1.5 m in agricultural soils and applied it to two different unsaturated soil types from agricultural fields in Israel: loess soil type (Calcic haploxeralf, common in rural areas of southern Israel with about 30% clay, 30% silt and 40% sand, and hamra soil type (Typic rhodoxeralf, common in rural areas of central Israel with about 10% clay, 5% silt and 85% sand. Combined field and laboratory measurements and model development gave efficient determinations of spatial moisture content in these fields. The environmentally friendly GPR system enabled non-destructive testing. The developed method for measuring moisture content in the laboratory enabled highly accurate interpretation and physical computing. Spatial soil moisture content to 1.5 m depth was determined with 1–5% accuracy, making our method useful for the design of irrigation plans for different interfaces.

  4. Using multi-temporal Sentinal-2 imagery for mapping Andean meadows and surface soil moisture in central Chile

    Science.gov (United States)

    Araya, Rocio; Fassnacht, Fabian E.; Lopatin, Javier; Hernández, H. Jaime

    2017-04-01

    In the Rio Maipo watershed, situated in central Chile, mining activities are the main factor impacting Andean meadows, through the consumption and exploitation of water and land. As wetlands are vulnerable and particularly susceptible to changes of water supply, alterations and modifications in the hydrological regime have direct effects on vegetation cover. In order to better understand this ecosystem, as well as for conservation planning and resource management, there is a strong need for spatially explicit and update wetland ecosystem assessment. However, there is a lack of baseline dataset and state of knowledge on these habitats. During the last decades remote sensing as evolve as an efficient tool for mapping and monitoring wetland ecosystems at different temporal and spatial scales. Accurate and up-to-date mapping and assessment of wetlands allows monitoring the changes in wetlands' vegetation due to natural and/or anthropogenic disturbances. New freely available spaceborne imagery, like Sentinel-2, supports long term monitoring on a high spatial resolution (10 m). The main aim of this work was to evaluate the potential of multi-temporal Sentinel-2 images in the detection and monitoring of water status of Andean meadows with anthropic disturbances. For these tasks we used bias support vector machines (BSVM), a one-class classifier to map and monitor meadow areas, and the support vector machines regression (SVMR) to estimate surface soil moisture (i.e. top 30 cm). BSVM produces probability maps of the class of interest, were only data of this class is needed as input of the model. One-class classifiers are well suited for situations where the numbers of the training samples from the class of interest is small and/or cover a small fraction of the area to be classified. We found that BSVM was capable to classify the meadow areas with an overall accuracy between 65% and 96%. Meanwhile, surface soil moisture prediction using SVMR reached r2 values between 0.2 and

  5. Global Gridded Soil Phosphorus Distribution Maps at 0.5-degree Resolution

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set provides estimates of different forms of naturally occurring soil phosphorus (P) including labile inorganic P, organic P, occluded P,...

  6. Global Gridded Soil Phosphorus Distribution Maps at 0.5-degree Resolution

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides estimates of different forms of naturally occurring soil phosphorus (P) including labile inorganic P, organic P, occluded P, secondary mineral...

  7. Indicative capacity of NDVI in predictive mapping of the properties of plow horizons of soils on slopes in the south of Western Siberia

    Science.gov (United States)

    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 (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.

  8. Mapping Soil Water-Holding Capacity Index to Evaluate the Effectiveness of Phytoremediation Protocols and ExposureRisk to Contaminated Soils in a National Interest Priority Site of the Campania Region (Southern Italy).

    Science.gov (United States)

    Romano, N.

    2015-12-01

    Soil moisture is an important state variable that influences water flow and solute transport in the soil-vegetation-atmosphere system, and plays a key role in securing agricultural ecosystem services for nutrition and food security. Especially when environmental studies should be carried out at relatively large spatial scales, there is a need to synthesize the complex interactions between soil, plant behavior, and local atmospheric conditions. Although it relies on the somewhat loosely defined concepts of "field capacity" and "wilting point", the soil water-holding capacity seems a suitable indicator to meet the above-mentioned requirement, yet easily understandable by the public and stakeholders. This parameter is employed in this work to evaluate the effectiveness of phytoremediation protocols funded by the EU-Life project EcoRemed and being implemented to remediate and restore contaminated agricultural soils of the National Interest Priority Site Litorale Domizio-Agro Aversano. The study area is located in the Campania Region (Southern Italy) and has an extent of about 200,000 hectares. A high-level spotted soil contamination is mostly due to the legal or outlaw industrial and municipal wastes, with hazardous consequences also on groundwater quality. With the availability of soil and land systems maps for this study area, disturbed and undisturbed soil samples were collected at two different soil depths to determine basic soil physico-chemical properties for the subsequent application of pedotransfer functions (PTFs). Soil water retention and hydraulic conductivity functions were determined for a number of soil cores, in the laboratory with the evaporation experiments, and used to calibrate the PTFs. Efficient mapping of the soil hydraulic properties benefitted greatly from the use of the PTFs and the physically-based scaling procedure developed by Nasta et al. (2013, WRR, 49:4219-4229).

  9. Modeling and Mapping Soil Moisture of Plateau Pasture Using RADARSAT-2 Imagery

    Directory of Open Access Journals (Sweden)

    Xun Chai

    2015-01-01

    Full Text Available Accurate soil moisture retrieval of a large area in high resolution is significant for plateau pasture. The object of this paper is to investigate the estimation of volumetric soil moisture in vegetated areas of plateau pasture using fully polarimetric C-band RADARSAT-2 SAR (Synthetic Aperture Radar images. Based on the water cloud model, Chen model, and Dubois model, we proposed two developed algorithms for soil moisture retrieval and validated their performance using experimental data. We eliminated the effect of vegetation cover by using the water cloud model and minimized the effect of soil surface roughness by solving the Dubois equations. Two experimental campaigns were conducted in the Qinghai Lake watershed, northeastern Tibetan Plateau in September 2012 and May 2013, respectively, with simultaneous satellite overpass. Compared with the developed Chen model, the predicted soil moisture given by the developed Dubois model agreed better with field measurements in terms of accuracy and stability. The RMSE, R2, and RPD value of the developed Dubois model were (5.4, 0.8, 1.6 and (3.05, 0.78, 1.74 for the two experiments, respectively. Validation results indicated that the developed Dubois model, needing a minimum of prior information, satisfied the requirement for soil moisture inversion in the study region.

  10. Generalized Soil Map of Europe ; aggregation of the FAO-Unesco soil units based on the characteristics determining the vulnerability to degradation processes

    NARCIS (Netherlands)

    Fraters B; LBG

    1996-01-01

    The FAO-Unesco soil units of Europe have been aggregated into categories of soils with similar soil characteristics (soil depth, stoniness, texture, acidity, etc.) which are of importance to the vulnerability of the soil to major degradation processes. The major soil degradation processes in Europe

  11. Mapping energy balance fluxes and root zone soil moisture in the White Volta Basin using optical imagery

    Science.gov (United States)

    Hendrickx, Jan M. H.; Hong, Sung-ho; Friesen, Jan; Compaore, Halidou; van de Giesen, Nick C.; Rodgers, Charles; Vlek, Paul L. G.

    2006-05-01

    Accurate information on the distribution of sensible and latent heat fluxes as well as soil moisture is critical for evaluation of background characteristics. Since these fluxes are subject to rapid changes in time and space, it is nearly impossible to determine their spatial and temporal distributions over large areas from ground measurements alone. Therefore, prediction from remote sensing images is very attractive as it enables extensive area coverage and a high repetition rate. In this study, the Surface Energy Balance Algorithm for Land as implemented at New Mexico Tech (SEBAL NM) is used to estimate sensible and latent heat fluxes in the White Volta Basin of Ghana, West Africa. The objectives are (i) to demonstrate a SEBAL NM application in a part of the world were ground measurements are very scarce and (ii) to compare evapotranspiration (ET) maps obtained from Landsat and MODIS imagery, respectively. The results of this study demonstrate that SEBAL NM can be applied for mapping sensible and latent heat fluxes as well as soil moisture over areas where few or no ground measurements are available using common satellite products (Landsat and MODIS).

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

    Science.gov (United States)

    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

  13. Multisensor On-The-Go Mapping of Soil Organic Carbon Content

    DEFF Research Database (Denmark)

    Knadel, Maria; Thomsen, Anton Gårde; Greve, Mogens Humlekrog

    2011-01-01

    of secondary information. An increased RPD value (2.3) was obtained for the sensor fusion measurements in comparison with those obtained using spectral data only (RPD = 1.9). The map based on MSP measurements detected more of the local SOC variation. High values for the error of prediction may have originated...... mapping SOC using a mobile sensor platform (MSP) and conventional grid sampling on a highly variable agricultural field in Denmark. Sixty-four samples collected on a 25-m grid were used to generate a reference map of SOC distribution using kriging. Mobile sensory data (visible–near infrared spectra......, electrical conductivity [EC], and temperature) obtained with a MSP were used to create a map of predicted C. To predict SOC, a calibration model was developed based on 15 representative samples. The best calibration model using a second Savitzky–Golay derivative on spectral data with EC as auxiliary data...

  14. Geochemical and mineralogical maps for soils of the conterminous United States

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Geochemical and mineralogical maps along with a histogram, boxplot, and empirical cumulative distribution function plot for each element or mineral whose data are...

  15. Effect of Provisional Cements on Shear Bond Strength of Porcelain Laminate Veneers

    OpenAIRE

    Altintas, Subutay Han; Tak, Onjen; Secilmis, Asli; Usumez, Aslihan

    2011-01-01

    Objectives: The purpose of this study was to evaluate the effect of three provisional cements and two cleaning techniques on the final bond strength of porcelain laminate veneers. Methods: The occlusal third of the crowns of forty molar teeth were sectioned and embedded in autopolymerizing acrylic resin. Dentin surfaces were polished and specimens were randomly divided into four groups (n=10). Provisional restorations were fabricated and two provisional restorations were cemented onto each to...

  16. Soil moisture assessed by digital mapping techniques and its field validation

    Directory of Open Access Journals (Sweden)

    Bruno Montoani Silva

    2014-04-01

    Full Text Available Digital techniques and tools can assist not only in the prediction of soil properties, such as soil moisture, but also in planning the use and management of areas for agriculture and, or, environmental purposes. In this sense, this work aimed to study wetness indexes methods, defining the spatial resolution and selecting the estimation method that best correlates with water content data measured in the field, evaluating even moisture at different soil depths and seasons. This study was developed in a landscape with strongly undulated relief and covered with Nitosols at the summit and upper middle third, and Argisols at the low middle third, ranging in altitude from 845 to 890 m, located in the southern state of Minas Gerais, Brazil. It were performed analyses of Pearson linear correlation between soil moisture determined in the field, at depths of 10, 20, 30, 40, 60 and 100 cm and the water storage in 0-100 cm depth, and the topographic and SAGA wetness indexes, TWI and SWI, respectively, obtained from digital elevation models at different spatial resolutions. In most studied conditions, the TWI with resolution of 10 m provided better results, particularly for the dry season. In this study, only the depth of 100 cm resulted in a significant and positive correlation, suggesting that the moisture levels are suitable for water dynamic studies in the subsurface, assisting in studies of hydrological dynamics and planning the soil use and management, especially for perennial plants with deeper root systems.

  17. Provisional drivers' perceptions of the impact of displaying P plates.

    Science.gov (United States)

    Bates, Lyndel; Scott-Parker, Bridie; Darvell, Millie; Watson, Barry

    2017-11-17

    P plates (or decals) identify a driver's license status to other road users. They are a compulsory part of the graduated driver licensing system in Queensland, Australia, for drivers on a P1 (provisional 1) or P2 (provisional 2) license. This study explored the perceptions of young drivers regarding the display of P plates (decals) in Queensland, Australia. In this study, 226 young drivers with a provisional (intermediate/restricted) license completed a 30-min online survey between October 2013 and June 2014. t Tests were used to compare the opinions of people who displayed their plates nearly always with those who displayed them less frequently. Participants approved of the requirement to display P plates with 69% of those on a P1 license and 79% on a P2 license supporting the condition to display P1 (red) plates. Participants on a P1 license (62%) and a P2 license (68%) also approved the requirement to display P2 (green) plates. However, young drivers also perceived that the display of P plates (measured from 1 = never to 5 = nearly all the time) enabled newly licensed drivers to be targeted by police and other drivers (those who do not always display P plates: M = 3.72, SD = 0.94; those who nearly always display P plates: M = 3.43, SD = 1.09). The study findings suggest that participants who nearly always display their P plates are more likely to report that having to display their plates resulted in them driving more carefully.

  18. Which persistent organic pollutants can we map in soil using a large spacing systematic soil monitoring design? A case study in Northern France.

    Science.gov (United States)

    Villanneau, Estelle J; Saby, Nicolas P A; Marchant, Ben P; Jolivet, Claudy C; Boulonne, Line; Caria, Giovanni; Barriuso, Enrique; Bispo, Antonio; Briand, Olivier; Arrouays, Dominique

    2011-09-01

    Persistent organic pollutants (POPs) impact upon human and animal health and the wider environment. It is important to determine where POPs are found and the spatial pattern of POP variation. The concentrations of 90 molecules which are members of four families of POPs and two families of herbicides were measured within a region of Northern France as part of the French National Soil Monitoring Network (RMQS: Réseau de Mesures de la Qualité des Sols). We also gather information on five covariates (elevation, soil organic carbon content, road density, land cover and population density) which might influence POP concentrations. The study region contains 105 RMQS observation sites arranged on a regular square grid with spacing of 16 km. The observations include hot-spots at sites of POP application, smaller concentrations where POPs have been dispersed and observations less than the limit of quantification (LOQ) where the soil has not been impacted by POPs. Fifty nine of the molecules were detected at less than 50 sites and hence the data were unsuitable for spatial analyses. We represent the variation of the remaining 31 molecules by various linear mixed models which can include fixed effects (i.e. linear relationships between the molecule concentrations and covariates) and spatially correlated random effects. The best model for each molecule is selected by the Akaike Information Criterion. For nine of the molecules, spatial correlation is evident and hence they can potentially be mapped. For four of these molecules, the spatial correlation cannot be wholly explained by fixed effects. It appears that these molecules have been transported away from their application sites and are now dispersed across the study region with the largest concentrations found in a heavily populated depression. More complicated statistical models and sampling designs are required to explain the distribution of the less dispersed molecules. Copyright © 2011 Elsevier B.V. All rights

  19. 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.

    Science.gov (United States)

    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

  20. Land cover mapping using lidar data and aerial image and soil fertility degradation assessment for rice production area in Quezon, Nueva Ecija, Philippines

    Science.gov (United States)

    Alberto, R. T.; Damian, G. B.; Camaso, E. E.; Isip, M. F.

    2017-09-01

    Land-cover maps were important for many scientific, ecological and land management purposes and during the last decades, rapid decrease of soil fertility was observed to be due to land use practices such as rice cultivation. High-precision land-cover maps are not yet available in the area which is important in an economy management. To assure accurate mapping of land cover to provide information, remote sensing is a very suitable tool to carry out this task and automatic land use and cover detection. The study did not only provide high precision land cover maps but it also provide estimates of rice production area that had undergone chemical degradation due to fertility decline. Land-cover were delineated and classified into pre-defined classes to achieve proper detection features. After generation of Land-cover map, of high intensity of rice cultivation, soil fertility degradation assessment in rice production area due to fertility decline was created to assess the impact of soils used in agricultural production. Using Simple spatial analysis functions and ArcGIS, the Land-cover map of Municipality of Quezon in Nueva Ecija, Philippines was overlaid to the fertility decline maps from Land Degradation Assessment Philippines- Bureau of Soils and Water Management (LADA-Philippines- BSWM) to determine the area of rice crops that were most likely where nitrogen, phosphorus, zinc and sulfur deficiencies were induced by high dosage of urea and imbalance N:P fertilization. The result found out that 80.00 % of fallow and 99.81% of rice production area has high soil fertility decline.

  1. Sediment source identification in a semiarid watershed at soil mapping unit scales

    Science.gov (United States)

    Selective erosion and transport of silt and clay-particles from watershed soil surfaces leads to enrichment of suspended sediments by size fractions that are the most effective scavengers of chemical pollutants. Thus, preferential transport of highly reactive size fractions represents a major proble...

  2. A new methodology for producing of risk maps of soil salinity, case ...

    African Journals Online (AJOL)

    The data for this study have been gathered from the records and reports published by the different departments of the Ministries of Agriculture and Energy and the Meteorological Organization of Iran. The present paper deals only with the intensities of hazards of soil salinity as a parameter for assessing the land degradation ...

  3. How to map soil organic carbon stocks in highly urbanized regions?

    NARCIS (Netherlands)

    Vasenev, V.I.; Stoorvogel, J.J.; Vasenev, I.I.; Valentini, R.

    2014-01-01

    Urbanization is among the most impetuous current land-use change trends, resulting in a permanently increasing role of urban ecosystems in regional and global environments. Urban soil organic carbon (SOC) is probably the least understood stocks because of the lack of appropriate methodology to

  4. Magnetic mapping of distribution of wood ash used for fertilization of forest soil

    Czech Academy of Sciences Publication Activity Database

    Petrovský, Eduard; Remeš, J.; Kapička, Aleš; Podrázský, V.; Grison, Hana; Borůvka, L.

    2018-01-01

    Roč. 626, June (2018), s. 228-234 ISSN 0048-9697 Institutional support: RVO:67985530 Keywords : forest soil * wood ash * fertilizing * tree plants * iron oxides * rock magnetism Subject RIV: DE - Earth Magnetism, Geodesy, Geography Impact factor: 4.900, year: 2016

  5. A new methodology for producing of risk maps of soil salinity, Case ...

    African Journals Online (AJOL)

    DR. MIKE HORSFALL

    have been gathered from the records and reports published by the different departments of the Ministries of Agriculture and. Energy and the Meteorological Organization of Iran. The present paper deals only with the intensities of hazards of soil salinity as a parameter for assessing the land degradation. The present paper ...

  6. Synergic Use of Sentinel-1 and Sentinel-2 Images for Operational Soil Moisture Mapping at High Spatial Resolution over Agricultural Areas

    Directory of Open Access Journals (Sweden)

    Mohammad El Hajj

    2017-12-01

    Full Text Available Soil moisture mapping at a high spatial resolution is very important for several applications in hydrology, agriculture and risk assessment. With the arrival of the free Sentinel data at high spatial and temporal resolutions, the development of soil moisture products that can better meet the needs of users is now possible. In this context, the main objective of the present paper is to develop an operational approach for soil moisture mapping in agricultural areas at a high spatial resolution over bare soils, as well as soils with vegetation cover. The developed approach is based on the synergic use of radar and optical data. A neural network technique was used to develop an operational method for soil moisture estimates. Three inversion SAR (Synthetic Aperture Radar configurations were tested: (1 VV polarization; (2 VH polarization; and (3 both VV and VH polarization, all in addition to the NDVI information extracted from optical images. Neural networks were developed and validated using synthetic and real databases. The results showed that the use of a priori information on the soil moisture condition increases the precision of the soil moisture estimates. The results showed that VV alone provides better accuracy on the soil moisture estimates than VH alone. In addition, the use of both VV and VH provides similar results, compared to VV alone. In conclusion, the soil moisture could be estimated in agricultural areas with an accuracy of approximately 5 vol % (volumetric unit expressed in percent. Better results were obtained for soil with a moderate surface roughness (for root mean surface height between 1 and 3 cm. The developed approach could be applied for agricultural plots with an NDVI lower than 0.75.

  7. Mapping earthworm communities in Europe

    NARCIS (Netherlands)

    Rutgers, M.; Orgiazzi, A.; Gardi, C.; Römbke, J.; Jansch, S.; Keith, A.; Neilson, R.; Boag, B.; Schmidt, O.; Murchie, A.K.; Blackshaw, R.P.; Pérès, G.; Cluzeau, D.; Guernion, M.; Briones, M.J.I.; Rodeiro, J.; Pineiro, R.; Diaz Cosin, D.J.; Sousa, J.P.; Suhadolc, M.; Kos, I.; Krogh, P.H.; Faber, J.H.; Mulder, C.; Bogte, J.J.; Wijnen, van H.J.; Schouten, A.J.; Zwart, de D.

    2016-01-01

    Existing data sets on earthworm communities in Europe were collected, harmonized, collated, modelled and depicted on a soil biodiversity map. Digital Soil Mapping was applied using multiple regressions relating relatively low density earthworm community data to soil characteristics, land use,

  8. Soil maps, field knowledge, forest inventory and Ecological-Economic Zoning as a basis for agricultural suitability of lands in Minas Gerais elaborated in GIS

    Directory of Open Access Journals (Sweden)

    Vladimir Antonio Silva

    2013-12-01

    Full Text Available Lands (broader concept than soils, including all elements of the environment: soils, geology, topography, climate, water resources, flora and fauna, and the effects of anthropogenic activities of the state of Minas Gerais are in different soil, climate and socio-economics conditions and suitability for the production of agricultural goods is therefore distinct and mapping of agricultural suitability of the state lands is crucial for planning guided sustainability. Geoprocessing uses geographic information treatment techniques and GIS allows to evaluate geographic phenomena and their interrelationships using digital maps. To evaluate the agricultural suitability of state lands, we used soil maps, field knowledge, forest inventories and databases related to Ecological-Economic Zoning (EEZ of Minas Gerais, to develop a map of land suitability in GIS. To do this, we have combined the maps of soil fertility, water stress, oxygen deficiency, vulnerability to erosion and impediments to mechanization. In terms of geographical expression, the main limiting factor of lands is soil fertility, followed by lack of water, impediments to mechanization and vulnerability to erosion. Regarding agricultural suitability, the group 2 (regular suitability for crops is the most comprehensive, representing 45.13% of the state. For management levels A and B, low and moderate technological level, respectively, the most expressive suitability class is the regular, followed by the restricted class and last, the adequate class, while for the management level C (high technological level the predominant class is the restricted. The predominant most intensive use type is for crops, whose area increases substantially with capital investment and technology (management levels B and C.

  9. Maps of critical loads and exceedance for sulfur and nitrogen to forest soils in Norway

    Energy Technology Data Exchange (ETDEWEB)

    Frogner, T.; Wright, R.F.; Cosby, B.J.; Esser, J.M.

    1994-12-31

    This report uses the dynamic MAGIC (Model of Acidification of Groundwater in Catchments) model to calculate critical loads of sulfur and nitrogen for forest soils in Norway. Inputs include soil survey data, atmospheric deposition data, forest productivity data, and surface water chemistry. Two scenarios for future sulfur deposition are used with two scenarios of nitrogen retention in catchments. The magnitude and patterns of calculated nitrogen critical loads and exceedance differ substantially depending on the scenario chosen for sulfur deposition and nitrogen retention. In the worst case, critical loads for N are low and exceeded in southernmost Norway. In the best case, critical loads for N are high and not exceeded. More information on the processes controlling N retention in forested ecosystems is of utmost importance for the specification of nitrogen critical loads. 25 refs., 14 figs., 1 table

  10. Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models

    DEFF Research Database (Denmark)

    Kheir, Rania Bou; Greve, Mogens Humlekrog; Bøcher, Peder Klith

    2010-01-01

    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...... 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...

  11. Remote Satellite Soil Moisture Mapping for the ERDC Countermine Simulation Test Bed

    Science.gov (United States)

    2010-03-01

    albedo , and NDVI. This objective serves to “proof the concept” of using the METRIC approach for operational army use in Afghanistan. 2. Install an...research results clearly demonstrate the great potential of optical imagery (Landsat, MODIS , GOES, METEOSAT, QUICKBIRD and other platforms) for reliably...14, 15, and 16). This is a consequence of not taking into account sufficiently the effect of albedo on the soil moisture prediction. On the sand

  12. Remote sensing for mapping soil moisture and drainage potential in semi-arid regions: Applications to the Campidano plain of Sardinia, Italy.

    Science.gov (United States)

    Filion, Rébecca; Bernier, Monique; Paniconi, Claudio; Chokmani, Karem; Melis, Massimo; Soddu, Antonino; Talazac, Manon; Lafortune, Francois-Xavier

    2016-02-01

    The aim of this study is to investigate the potential of radar (ENVISAT ASAR and RADARSAT-2) and LANDSAT data to generate reliable soil moisture maps to support water management and agricultural practice in Mediterranean regions, particularly during dry seasons. The study is based on extensive field surveys conducted from 2005 to 2009 in the Campidano plain of Sardinia, Italy. A total of 12 small bare soil fields were sampled for moisture, surface roughness, and texture values. From field scale analysis with ENVISAT ASAR (C-band, VV polarized, descending mode, incidence angle from 15.0° to 31.4°), an empirical model for estimating bare soil moisture was established, with a coefficient of determination (R(2)) of 0.85. LANDSAT TM5 images were also used for soil moisture estimation using the TVX slope (temperature/vegetation index), and in this case the best linear relationship had an R(2) of 0.81. A cross-validation on the two empirical models demonstrated the potential of C-band SAR data for estimation of surface moisture, with and R(2) of 0.76 (bias +0.3% and RMSE 7%) for ENVISAT ASAR and 0.54 (bias +1.3% and RMSE 5%) for LANDSAT TM5. The two models developed at plot level were then applied over the Campidano plain and assessed via multitemporal and spatial analyses, in the latter case against soil permeability data from a pedological map of Sardinia. Encouraging estimated soil moisture (ESM) maps were obtained for the SAR-based model, whereas the LANDSAT-based model would require a better field data set for validation, including ground data collected on vegetated fields. ESM maps showed sensitivity to soil drainage qualities or drainage potential, which could be useful in irrigation management and other agricultural applications. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Soils - Volusia County Soils (Polygons)

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Soils: 1:24000 SSURGO Map. Polygon boundaries of Soils in Volusia County, downloaded from SJRWMD and created by NRCS and SJRWMD. This data set is a digital version...

  14. Identification and Mapping of Soils, Vegetation, and Water Resources of Lynn County, Texas, by Computer Analysis of ERTS MSS Data

    Science.gov (United States)

    Baumgardner, M. F.; Kristof, S. J.; Henderson, J. A., Jr.

    1973-01-01

    Results of the analysis and interpretation of ERTS multispectral data obtained over Lynn County, Texas, are presented. The test site was chosen because it embodies a variety of problems associated with the development and management of agricultural resources in the Southern Great Plains. Lynn County is one of ten counties in a larger test site centering around Lubbock, Texas. The purpose of this study is to examine the utility of ERTS data in identifying, characterizing, and mapping soils, vegetation, and water resources in this semiarid region. Successful application of multispectral remote sensing and machine-processing techniques to arid and seminarid land-management problems will provide valuable new tools for the more than one-third of the world's lands lying in arid-semiarid regions.

  15. An algorithm for generating soil moisture and snow depth maps from microwave spaceborne radiometers: HydroAlgo

    Directory of Open Access Journals (Sweden)

    E. Santi

    2012-10-01

    Full Text Available A systematic and timely monitoring of land surface parameters that affect the hydrological cycle at local and global scales is of primary importance in obtaining a better understanding of geophysical processes and in managing environmental resources as well as natural disasters. Soil moisture and snow water equivalent are two quantities that play a major role in these applications. In this paper an algorithm for hydrological purposes (called hereinafter HydroAlgo, which is able to generate maps of snow depth (SD and soil moisture content (SMC from AMSR-E data, has been developed and implemented within the framework of the JAXA ADEOS-II/AMSR-E and GCOM/AMSR-2 programs, as well as of a project of the Italian Space Agency that is devoted to civil protection from floods and landslides. As auxiliary output, the algorithm also generates maps of vegetation biomass (VB. An initial phase of pre-processing includes the improvement of spatial resolution, as well as masking for urban areas, water bodies, and dense vegetation. The algorithm was then split into two branches, the first of which focused on the retrieval of SMC and the second, on SD. Both parameters were retrieved using Artificial Neural Network (ANN methods. The algorithm was calibrated using a wide set of experimental data collected on three sites: Mongolia and Australia (for SMC, and Siberia (for SD, integrated with model simulations. These results were then validated by comparing the algorithm outputs with experimental data collected on two additional sites: a part of a watershed in Northern Italy, and a large portion of Scandinavia. An additional test of the algorithm was also performed on a large scale, and included sites characterized by differing climatic and meteorological conditions.

  16. Workplace exposure to nanoparticles and the application of provisional nanoreference values in times of uncertain risks

    NARCIS (Netherlands)

    van Broekhuizen, P; van Broekhuizen, F.; Cornelissen, R.; Reijnders, L.

    2012-01-01

    Nano reference values (NRVs) for occupational use of nanomaterials were tested as provisional substitute for Occupational Exposure Limits (OELs). NRVs can be used as provisional limit values until Health-Based OELs or derived no-effect levels (DNEL) become available. NRVs were defined for 8 h

  17. Provisional Admission Practices: Blending Access and Support to Facilitate Student Success

    Science.gov (United States)

    Nichols, Andrew Howard; Clinedinst, Melissa

    2013-01-01

    This report examines provisional admission as an initiative that can expand four-year college access and success for students from economically disadvantaged backgrounds. Provisional admission policies and programs enable students to enroll at an institution under specific conditions. Students are often required to meet certain academic…

  18. 76 FR 61042 - Modification of Regulations Regarding the Practice of Accepting Bonds During the Provisional...

    Science.gov (United States)

    2011-10-03

    ... Practice of Accepting Bonds During the Provisional Measures Period in Antidumping and Countervailing Duty... importers directly responsible for the payment of AD and CVD duties. DATES: This Final Rule is effective... practice of accepting bonds during the provisional measures period in AD and CVD investigations. See...

  19. Fabrication of a screw-retained fixed provisional prosthesis supported by dental implants.

    Science.gov (United States)

    Kökat, Ali Murat; Akça, Kivanç

    2004-03-01

    Screw-retained provisional implant-supported prostheses may have advantages over cement-retained prostheses in certain situations. This article describes a technique for fabrication of screw-retained provisional acrylic resin implant-supported prostheses from the modified metal components provided with the implant.

  20. Indirect implant-supported fixed provisional restoration in the esthetic zone: fabrication technique and treatment workflow.

    Science.gov (United States)

    Shor, Alexander; Schuler, Ralf; Goto, Yoshihiro

    2008-01-01

    Treatment objectives of an implant-supported fixed provisional restoration include shaping/preservation of the gingival soft tissue contour, functional and esthetic substitution of the missing dentition during postsurgical healing, and definitive prosthesis fabrication stages. Fixed provisional restoration can also serve as an esthetic and functional blueprint in the fabrication of the definitive restoration. Despite its common use and important indications, limited information is available on the various aspects of the provisional fabrication and treatment. This article presents a production technique and treatment workflow of a laboratory-fabricated, screw-retained fixed provisional restoration. Provisional restoration is fabricated using layering technique and internal stain characterization. The soft tissue profile of the working cast is modified according to the coronal contour of the diagnostic wax-up. Upon delivery, the provisional contour is reevaluated and modified as necessary. The developed emergence profile of the provisional restoration is transferred to the master cast via customized impression copings. Laboratory-fabricated implant-supported provisional restorations allow the esthetic and functional substitution of the missing dentition and the shaping of the soft tissue profile, and can act as a blueprint in the fabrication of definitive restorations.

  1. 78 FR 36571 - North American Datum of 1983 (NAD 83) Outer Continental Shelf (OCS) Provisional Official...

    Science.gov (United States)

    2013-06-18

    ... Official Protraction Diagrams in the Pacific Ocean, Hawaiian Islands Description/Date NF04-08 (Kaua'i... with this publication two NAD 83-based OCS Provisional OPDs that represent the Island of Oahu and... Title 43, Code of Federal Regulations, has created provisional versions of the basic record used for the...

  2. Comparison of Three Supervised Learning Methods for Digital Soil Mapping: Application to a Complex Terrain in the Ecuadorian Andes

    Directory of Open Access Journals (Sweden)

    Martin Hitziger

    2014-01-01

    Full Text Available A digital soil mapping approach is applied to a complex, mountainous terrain in the Ecuadorian Andes. Relief features are derived from a digital elevation model and used as predictors for topsoil texture classes sand, silt, and clay. The performance of three statistical learning methods is compared: linear regression, random forest, and stochastic gradient boosting of regression trees. In linear regression, a stepwise backward variable selection procedure is applied and overfitting is controlled by minimizing Mallow’s Cp. For random forest and boosting, the effect of predictor selection and tuning procedures is assessed. 100-fold repetitions of a 5-fold cross-validation of the selected modelling procedures are employed for validation, uncertainty assessment, and method comparison. Absolute assessment of model performance is achieved by comparing the prediction error of the selected method and the mean. Boosting performs best, providing predictions that are reliably better than the mean. The median reduction of the root mean square error is around 5%. Elevation is the most important predictor. All models clearly distinguish ridges and slopes. The predicted texture patterns are interpreted as result of catena sequences (eluviation of fine particles on slope shoulders and landslides (mixing up mineral soil horizons on slopes.

  3. PALSAR Wide-Area Mapping of Borneo: Methodology and Map Validation

    NARCIS (Netherlands)

    Hoekman, D.H.; Vissers, M.A.M.; Wielaard, N.

    2010-01-01

    This paper describes the operational radar mapping processing chain developed and steps taken to produce a provisional wide-area PALSAR forest and land cover map covering Borneo for the year 2007, compliant with emerging international standards (CEOS guidelines, FAO LCCS). A Bayesian approach based

  4. Early versus delayed, provisional eptifibatide in acute coronary syndromes.

    Science.gov (United States)

    Giugliano, Robert P; White, Jennifer A; Bode, Christoph; Armstrong, Paul W; Montalescot, Gilles; Lewis, Basil S; van 't Hof, Arnoud; Berdan, Lisa G; Lee, Kerry L; Strony, John T; Hildemann, Steven; Veltri, Enrico; Van de Werf, Frans; Braunwald, Eugene; Harrington, Robert A; Califf, Robert M; Newby, L Kristin

    2009-05-21

    Glycoprotein IIb/IIIa inhibitors are indicated in patients with acute coronary syndromes who are undergoing an invasive procedure. The optimal timing of the initiation of such therapy is unknown. We compared a strategy of early, routine administration of eptifibatide with delayed, provisional administration in 9492 patients who had acute coronary syndromes without ST-segment elevation and who were assigned to an invasive strategy. Patients were randomly assigned to receive either early eptifibatide (two boluses, each containing 180 microg per kilogram of body weight, administered 10 minutes apart, and a standard infusion > or = 12 hours before angiography) or a matching placebo infusion with provisional use of eptifibatide after angiography (delayed eptifibatide). The primary efficacy end point was a composite of death, myocardial infarction, recurrent ischemia requiring urgent revascularization, or the occurrence of a thrombotic complication during percutaneous coronary intervention that required bolus therapy opposite to the initial study-group assignment ("thrombotic bailout") at 96 hours. The key secondary end point was a composite of death or myocardial infarction within the first 30 days. Key safety end points were bleeding and the need for transfusion within the first 120 hours after randomization. The primary end point occurred in 9.3% of patients in the early-eptifibatide group and in 10.0% in the delayed-eptifibatide group (odds ratio, 0.92; 95% confidence interval [CI], 0.80 to 1.06; P=0.23). At 30 days, the rate of death or myocardial infarction was 11.2% in the early-eptifibatide group, as compared with 12.3% in the delayed-eptifibatide group (odds ratio, 0.89; 95% CI, 0.79 to 1.01; P=0.08). Patients in the early-eptifibatide group had significantly higher rates of bleeding and red-cell transfusion. There was no significant difference between the two groups in rates of severe bleeding or nonhemorrhagic serious adverse events. In patients who had acute

  5. VSRR - Provisional monthly and 12-month ending number of live births, deaths and infant deaths: United States

    Data.gov (United States)

    U.S. Department of Health & Human Services — https://www.cdc.gov/nchs/products/vsrr/provisional-tables.htm Monthly and 12 month-ending provisional counts of births, deaths and infant deaths are provided for the...

  6. Mapping and modelling the geographical distribution of soil-transmitted helminthiases in Peninsular Malaysia: implications for control approaches

    Directory of Open Access Journals (Sweden)

    Romano Ngui

    2014-05-01

    Full Text Available Soil-transmitted helminth (STH infections in Malaysia are still highly prevalent, especially in rural and remote communities. Complete estimations of the total disease burden in the country has not been performed, since available data are not easily accessible in the public domain. The current study utilised geographical information system (GIS to collate and map the distribution of STH infections from available empirical survey data in Peninsular Malaysia, highlighting areas where information is lacking. The assembled database, comprising surveys conducted between 1970 and 2012 in 99 different locations, represents one of the most comprehensive compilations of STH infections in the country. It was found that the geographical distribution of STH varies considerably with no clear pattern across the surveyed locations. Our attempt to generate predictive risk maps of STH infections on the basis of ecological limits such as climate and other environmental factors shows that the prevalence of Ascaris lumbricoides is low along the western coast and the southern part of the country, whilst the prevalence is high in the central plains and in the North. In the present study, we demonstrate that GIS can play an important role in providing data for the implementation of sustainable and effective STH control programmes to policy-makers and authorities in charge.

  7. The global SMOS Level 3 daily soil moisture and brightness temperature maps

    Directory of Open Access Journals (Sweden)

    A. Al Bitar

    2017-06-01

    Full Text Available The objective of this paper is to present the multi-orbit (MO surface soil moisture (SM and angle-binned brightness temperature (TB products for the SMOS (Soil Moisture and Ocean Salinity mission based on a new multi-orbit algorithm. The Level 3 algorithm at CATDS (Centre Aval de Traitement des Données SMOS makes use of MO retrieval to enhance the robustness and quality of SM retrievals. The motivation of the approach is to make use of the longer temporal autocorrelation length of the vegetation optical depth (VOD compared to the corresponding SM autocorrelation in order to enhance the retrievals when an acquisition occurs at the border of the swath. The retrieval algorithm is implemented in a unique operational processor delivering multiple parameters (e.g. SM and VOD using multi-angular dual-polarisation TB from MO. A subsidiary angle-binned TB product is provided. In this study the Level 3 TB V310 product is showcased and compared to SMAP (Soil Moisture Active Passive TB. The Level 3 SM V300 product is compared to the single-orbit (SO retrievals from the Level 2 SM processor from ESA with aligned configuration. The advantages and drawbacks of the Level 3 SM product (L3SM are discussed. The comparison is done on a global scale between the two datasets and on the local scale with respect to in situ data from AMMA-CATCH and USDA ARS Watershed networks. The results obtained from the global analysis show that the MO implementation enhances the number of retrievals: up to 9 % over certain areas. The comparison with the in situ data shows that the increase in the number of retrievals does not come with a decrease in quality, but rather at the expense of an increased time lag in product availability from 6 h to 3.5 days, which can be a limiting factor for applications like flood forecast but reasonable for drought monitoring and climate change studies. The SMOS L3 soil moisture and L3 brightness temperature products are delivered using an

  8. The global SMOS Level 3 daily soil moisture and brightness temperature maps

    Science.gov (United States)

    Bitar, Ahmad Al; Mialon, Arnaud; Kerr, Yann H.; Cabot, François; Richaume, Philippe; Jacquette, Elsa; Quesney, Arnaud; Mahmoodi, Ali; Tarot, Stéphane; Parrens, Marie; Al-Yaari, Amen; Pellarin, Thierry; Rodriguez-Fernandez, Nemesio; Wigneron, Jean-Pierre

    2017-06-01

    The objective of this paper is to present the multi-orbit (MO) surface soil moisture (SM) and angle-binned brightness temperature (TB) products for the SMOS (Soil Moisture and Ocean Salinity) mission based on a new multi-orbit algorithm. The Level 3 algorithm at CATDS (Centre Aval de Traitement des Données SMOS) makes use of MO retrieval to enhance the robustness and quality of SM retrievals. The motivation of the approach is to make use of the longer temporal autocorrelation length of the vegetation optical depth (VOD) compared to the corresponding SM autocorrelation in order to enhance the retrievals when an acquisition occurs at the border of the swath. The retrieval algorithm is implemented in a unique operational processor delivering multiple parameters (e.g. SM and VOD) using multi-angular dual-polarisation TB from MO. A subsidiary angle-binned TB product is provided. In this study the Level 3 TB V310 product is showcased and compared to SMAP (Soil Moisture Active Passive) TB. The Level 3 SM V300 product is compared to the single-orbit (SO) retrievals from the Level 2 SM processor from ESA with aligned configuration. The advantages and drawbacks of the Level 3 SM product (L3SM) are discussed. The comparison is done on a global scale between the two datasets and on the local scale with respect to in situ data from AMMA-CATCH and USDA ARS Watershed networks. The results obtained from the global analysis show that the MO implementation enhances the number of retrievals: up to 9 % over certain areas. The comparison with the in situ data shows that the increase in the number of retrievals does not come with a decrease in quality, but rather at the expense of an increased time lag in product availability from 6 h to 3.5 days, which can be a limiting factor for applications like flood forecast but reasonable for drought monitoring and climate change studies. The SMOS L3 soil moisture and L3 brightness temperature products are delivered using an open licence and

  9. Self-organizing feature map (neural networks) as a tool to select the best indicator of road traffic pollution (soil, leaves or bark of Robinia pseudoacacia L.).

    Science.gov (United States)

    Samecka-Cymerman, A; Stankiewicz, A; Kolon, K; Kempers, A J

    2009-07-01

    Concentrations of the elements Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn were measured in the leaves and bark of Robinia pseudoacacia and the soil in which it grew, in the town of Oleśnica (SW Poland) and at a control site. We selected this town because emission from motor vehicles is practically the only source of air pollution, and it seemed interesting to evaluate its influence on soil and plants. The self-organizing feature map (SOFM) yielded distinct groups of soils and R. pseudoacacia leaves and bark, depending on traffic intensity. Only the map classifying bark samples identified an additional group of highly polluted sites along the main highway from Wrocław to Warszawa. The bark of R. pseudoacacia seems to be a better bioindicator of long-term cumulative traffic pollution in the investigated area, while leaves are good indicators of short-term seasonal accumulation trends.

  10. Genome-wide association mapping of acid soil resistance in barley (Hordeum vulgare L.

    Directory of Open Access Journals (Sweden)

    Gaofeng eZhou

    2016-03-01

    Full Text Available AbstractGenome-wide association studies (GWAS based on linkage disequilibrium (LD have been used to detect QTLs underlying complex traits in major crops. In this study, we collected 218 barley (Hordeum vulgare L. lines including wild barley and cultivated barley from China, Canada, Australia and Europe. A total of 408 polymorphic markers were used for population structure and LD analysis. GWAS for acid soil resistance were performed on the population using a general linkage model (GLM and a mixed linkage model (MLM, respectively. A total of 22 QTLs (quantitative trait loci were detected with the GLM and MLM analyses. Two QTLs, close to markers bPb-1959 (133.1 cM and bPb-8013 (86.7 cM, localized on chromosome 1H and 4H respectively, were consistently detected in two different trials with both the GLM and MLM analyses. Furthermore, bPb-8013, the closest marker to the major Al3+ resistance gene HvAACT1 in barley, was identified to be QTL5. The QTLs could be used in marker-assisted selection to identify and pyramid different loci for improved acid soil resistance in barley.

  11. Genome-Wide Association Mapping of Acid Soil Resistance in Barley (Hordeum vulgare L.)

    Science.gov (United States)

    Zhou, Gaofeng; Broughton, Sue; Zhang, Xiao-Qi; Ma, Yanling; Zhou, Meixue; Li, Chengdao

    2016-01-01

    Genome-wide association studies (GWAS) based on linkage disequilibrium (LD) have been used to detect QTLs underlying complex traits in major crops. In this study, we collected 218 barley (Hordeum vulgare L.) lines including wild barley and cultivated barley from China, Canada, Australia, and Europe. A total of 408 polymorphic markers were used for population structure and LD analysis. GWAS for acid soil resistance were performed on the population using a general linkage model (GLM) and a mixed linkage model (MLM), respectively. A total of 22 QTLs (quantitative trait loci) were detected with the GLM and MLM analyses. Two QTLs, close to markers bPb-1959 (133.1 cM) and bPb-8013 (86.7 cM), localized on chromosome 1H and 4H respectively, were consistently detected in two different trials with both the GLM and MLM analyses. Furthermore, bPb-8013, the closest marker to the major Al3+ resistance gene HvAACT1 in barley, was identified to be QTL5. The QTLs could be used in marker-assisted selection to identify and pyramid different loci for improved acid soil resistance in barley. PMID:27064793

  12. Provisional Crown Dislodgement during Scuba Diving: A Case of Barotrauma

    Directory of Open Access Journals (Sweden)

    Meenal Nitin Gulve

    2013-01-01

    Full Text Available Changes in ambient pressure, for example, during flying, diving, or hyperbaric oxygen therapy, can lead to barotrauma. Although it may seem that this issue was neglected in dental education and research in recent decades, familiarity with and understanding of these facts may be of importance for dental practitioners. We report the case of a patient who experienced barotrauma involving dislodgement of a provisional crown during scuba diving. Patients who are exposed to pressure changes as a part of their jobs or hobbies and their dentists should know the causes of barotrauma. In addition, the clinician must be aware of the possible influence of pressure changes on the retention of dental components.

  13. Mapping Soil Transmitted Helminths and Schistosomiasis under Uncertainty: A Systematic Review and Critical Appraisal of Evidence.

    Directory of Open Access Journals (Sweden)

    Andrea L Araujo Navas

    2016-12-01

    Full Text Available Spatial modelling of STH and schistosomiasis epidemiology is now commonplace. Spatial epidemiological studies help inform decisions regarding the number of people at risk as well as the geographic areas that need to be targeted with mass drug administration; however, limited attention has been given to propagated uncertainties, their interpretation, and consequences for the mapped values. Using currently published literature on the spatial epidemiology of helminth infections we identified: (1 the main uncertainty sources, their definition and quantification and (2 how uncertainty is informative for STH programme managers and scientists working in this domain.We performed a systematic literature search using the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA protocol. We searched Web of Knowledge and PubMed using a combination of uncertainty, geographic and disease terms. A total of 73 papers fulfilled the inclusion criteria for the systematic review. Only 9% of the studies did not address any element of uncertainty, while 91% of studies quantified uncertainty in the predicted morbidity indicators and 23% of studies mapped it. In addition, 57% of the studies quantified uncertainty in the regression coefficients but only 7% incorporated it in the regression response variable (morbidity indicator. Fifty percent of the studies discussed uncertainty in the covariates but did not quantify it. Uncertainty was mostly defined as precision, and quantified using credible intervals by means of Bayesian approaches.None of the studies considered adequately all sources of uncertainties. We highlighted the need for uncertainty in the morbidity indicator and predictor variable to be incorporated into the modelling framework. Study design and spatial support require further attention and uncertainty associated with Earth observation data should be quantified. Finally, more attention should be given to mapping and interpreting

  14. The eco-innovation of K-Chabazite zeolite application in high nitrate vulnerable soils: a mapping assessment

    Science.gov (United States)

    Blasi, Emanuele; Passeri, Nicolò; Martella, Angelo; Coltorti, Massimo; Faccini, Barbara; Di Giuseppe, Dario; Ferretti, Giacomo

    2015-04-01

    practice. This analysis has been set at regional scale through a GIS mapping framework to focus on the priority areas where the interventions on soil are suitable to preserve environmental functions and land quality, taking into account the environmental policy addresses and the Regional Rural Development Program.

  15. Predicting and Mapping Soil Carbon Using Visible Near Infrared Spectroscopy at Different Scales

    DEFF Research Database (Denmark)

    Deng, Fan

    , particularly useful for field applications and facilitates high sampling densities. The general aim of this thesis, as part of the research project “Temporal and spatial dynamics of soil organic carbon in cultivated landscapes” funded by the Danish Council for Independent Research, Technology and Production...... SOC contents were measured by dry combustion with one of three instruments: LECO CN-1000 furnace, LECO CN-2000 or Thermo Flash 2000 Organic Element Analyzer. Principal component analysis (PCA), partial least squares regression (PLSR) and regression rules were the multivariate data analysis methods....... Principal component analysis and PLSR were then applied for pattern recognition and building calibration models for each of the pretreatment techniques. The results of the validation process suggested that MSC preprocessing led to the best performing calibration model with the best predictive power among...

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

    Science.gov (United States)

    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

  17. Physiographic soil map delineation for the Nile alluvium and desert outskirts in middle Egypt using remote sensing data of EgyptSat-1

    Directory of Open Access Journals (Sweden)

    A.A. Afify

    2010-12-01

    Full Text Available The objectives of this study are to produce a physiographic soil map with correlated attributes to be a base for extra modifiers within the land information system. This integrated data will serve the purposes of land use planning, precision farming practices and to be applied in other areas using the extrapolation approach. The Satellite data of EgyptSat-1 were projected on an area of Middle Egypt that represents unique physiographic features over portions of Beni Suef, El Fayoum, Helwan, and October Provinces. The spectral signatures of the land patterns were delineated by the visual interpretation using the physiographic approach, while soil taxa were categorized according to the key of Soil Taxonomy (USDA, 2010, resulting in two landscape categories. The first category includes older and developed parent materials, covering the following units: (a Pediplains of residual soils over limestone parent rock, having soils of Lithic Haplocalcids, loamy skeletal. (b Terraced old alluvial plains represent the formerly deposited alluvium that preceded the recent one of the River Nile alluvium. They includes soils of Typic Calcigypsids, loamy skeletal and old alluvial plain but are currently managed under cultivation. The soils are dominated by Typic Haplocalcids, loamy skeletal. (c Wadis that were shaped by the paleodrainage erosion, are currently subjected to the seasonal flush flooding and are sparsely vegetated including soils of Typic Torrifluvents, lamy skeletal (calcareous; Typic Torriorthents, sandy skeletal, and Typic Torriorthents, sandy. (d Aeolian plain “partly cultivated” includes soils of Typic Torripsamments (calcareous. The second category is a recent River Nile alluvium that formed the following units: (a Terraced recent alluvial plain “cultivated” includes soils of Entic Calcitorrerts, fine and Typic Haplotorrerts fine. (b Recent flat alluvial plain includes soils of Typic Haplotorrerts, fine. (c Meandering belt is aligning

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

    Science.gov (United States)

    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.

  19. [Clinical evaluation of "All-on-Four" provisional prostheses reinforced with carbon fibers].

    Science.gov (United States)

    Li, Bei-bei; Lin, Ye; Cui, Hong-yan; Hao, Qiang; Xu, Jia-bin; Di, Ping

    2016-02-18

    To assess the clinical effects of carbon fiber reinforcement on the "All-on-Four" provisional prostheses. Provisional prostheses were divided into control group and carbon fiber reinforcing group according to whether carbon fiber reinforcement was used in the provisional prostheses base resin. In our study, a total of 60 patients (32 males and 28 females) with 71 provisional prostheses(28 maxilla and 43 mandible)were enrolled between April 2008 and December 2012 for control group; a total of 23 patients (13 males and 10 females) with 28 provisional prostheses (9 maxillas and 19 mandibles) were enrolled between January 2013 and March 2014 for carbon fiber reinforcing group. The information of provisional prostheses in the patients was recorded according to preoperative examination. We used the date of definitive prosthesis restoration as the cut-off point, observing whether fracture occurred on the provisional prostheses in the two groups. Additionally we observed whether fiber exposure occurred on the tissue surface of the provisional prostheses and caused mucosal irritation. The interface between the denture base resin and the fibers was examined using scanning electron microscopy (SEM). The age [(57.3 ± 10.1) years vs.(55.1 ± 11.4) years], gender (32 males and 28 females vs. 13 males and 10 females), maxilla and mandible distributions (28 maxillas and 43 mandibles vs. 9 maxillas and 19 mandibles), the number of extraction jaws (46 vs. 23), the average using time [(7.8 ± 1.3) months vs. (7.5 ± 1.1) months], and the opposing dentition distributions of provisional prostheses of the patients showed no significant differences between the control and reinforcing groups. There were 21(29.6%) fractures that occurred on the 71 provisional prostheses in the control group; there was no fracture that occurred on the 28 provisional prosthesesin the carbon fiber reinforcing group. The fracture rate of the carbon fiber reinforcing group was significantly lower than that of

  20. Soil Parameter Mapping and Ad Hoc Power Analysis to Increase Blocking Efficiency Prior to Establishing a Long-Term Field Experiment.

    Science.gov (United States)

    Collins, Doug; Benedict, Chris; Bary, Andy; Cogger, Craig

    2015-01-01

    The spatial heterogeneity of soil and weed populations poses a challenge to researchers. Unlike aboveground variability, below-ground variability is more difficult to discern without a strategic soil sampling pattern. While blocking is commonly used to control environmental variation, this strategy is rarely informed by data about current soil conditions. Fifty georeferenced sites were located in a 0.65 ha area prior to establishing a long-term field experiment. Soil organic matter (OM) and weed seed bank populations were analyzed at each site and the spatial structure was modeled with semivariograms and interpolated with kriging to map the surface. These maps were used to formulate three strategic blocking patterns and the efficiency of each pattern was compared to a completely randomized design and a west to east model not informed by soil variability. Compared to OM, weeds were more variable across the landscape and had a shorter range of autocorrelation, and models to increase blocking efficiency resulted in less increase in power. Weeds and OM were not correlated, so no model examined improved power equally for both parameters. Compared to the west to east blocking pattern, the final blocking pattern chosen resulted in a 7-fold increase in power for OM and a 36% increase in power for weeds.

  1. Soil Parameter Mapping and Ad Hoc Power Analysis to Increase Blocking Efficiency Prior to Establishing a Long-Term Field Experiment

    Science.gov (United States)

    Collins, Doug; Benedict, Chris; Bary, Andy; Cogger, Craig

    2015-01-01

    The spatial heterogeneity of soil and weed populations poses a challenge to researchers. Unlike aboveground variability, below-ground variability is more difficult to discern without a strategic soil sampling pattern. While blocking is commonly used to control environmental variation, this strategy is rarely informed by data about current soil conditions. Fifty georeferenced sites were located in a 0.65 ha area prior to establishing a long-term field experiment. Soil organic matter (OM) and weed seed bank populations were analyzed at each site and the spatial structure was modeled with semivariograms and interpolated with kriging to map the surface. These maps were used to formulate three strategic blocking patterns and the efficiency of each pattern was compared to a completely randomized design and a west to east model not informed by soil variability. Compared to OM, weeds were more variable across the landscape and had a shorter range of autocorrelation, and models to increase blocking efficiency resulted in less increase in power. Weeds and OM were not correlated, so no model examined improved power equally for both parameters. Compared to the west to east blocking pattern, the final blocking pattern chosen resulted in a 7-fold increase in power for OM and a 36% increase in power for weeds. PMID:26247056

  2. High resolution mapping of soil organic carbon stocks using remote sensing variables in the semi-arid rangelands of eastern Australia.

    Science.gov (United States)

    Wang, Bin; Waters, Cathy; Orgill, Susan; Gray, Jonathan; Cowie, Annette; Clark, Anthony; Liu, De Li

    2018-02-23

    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.

  3. Modeling and mapping of critical loads for heavy metals in Kunshan soil.

    Science.gov (United States)

    Wu, Shaohua; Shi, Yaxing; Zhou, Shenglu; Wang, Chunhui; Chen, Hao

    2016-11-01

    The assessment of critical loads of metals in soil can be used as an important tool for evaluation and for risk precaution of future inputs of metal in order to avoid the occurrence of heavy metal pollution and its long-term risks for people. In this study, critical loads of Cd, Cu, and Pb in farming and non-farming areas of Kunshan were calculated based on three main effects. Two of these effects, limit value of daily metals dose and different environmental water quality criteria are new ways to calculate the critical content of heavy metals. The mean value of critical loads decreased in the order Cu>Pb>Cd when calculated using mass balance effects, child health risk effects, and adult health risk effects. Critical loads were highest in the areas near construction land, areas of low critical load were scattered throughout the city. The areal proportion of critical load exceedance is greatest for Pb based on mass balance effects, followed by Cu based on water quality effects, and Cd based on mass balance effects. Exceedances only occurred in 6% and 3% of farming areas for water quality effects for Cd and Pb when compared critical load values to the input fluxes in the Yangtze River delta. However, for these metals, values were up to 83% and 100%, respectively, based on mass balance effects. Exceedances completely covered non-farming areas for each effect for Pb. Most exceedances occurred in the north and south of the city in non-farming areas. Spatially explicit critical loads of heavy metals based on the different effects can serve as a reference for controlling the emissions of heavy metals effectively and meeting the demands of different management objectives. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Geochemistry of soils along a transect from Central Mexico to the Pacific Coast: a pilot study for continental-scale geochemical mapping

    Science.gov (United States)

    Chiprés, J.A.; de la Calleja,; Tellez, J.I.; Jiménez, F.; Cruz, Carlos; Guerrero, E.G.; Castro, J.; Monroy, M.G.; Salinas, J.C.

    2009-01-01

    The Mexican Geological Survey (SGM), the National Institute of Statistics, Geography and Informatics (INEGI) and the Autonomous University of San Luis Potosi (UASLP) have established a multidisciplinary team with the objective of creating a national program of geochemical mapping of soils in Mexico. This is being done as part of the North American Soil Geochemical Landscapes Project in partnership with the US Geological Survey and the Geological Survey of Canada. As the first step, a pilot study was conducted over a transect that extends from the Mexico–US border near Ciudad Juarez in the north to the Pacific Ocean in the south. This pilot transect was conducted in two phases, and this paper presents results from the first phase, which sampled soils at about a 40-km spacing along a 730-km transect beginning in Central Mexico and ending at the Pacific Coast. Samples were collected from the A and C horizons at each site and 60 elements were analyzed. This pilot study demonstrates that geochemical mapping based on a 40-km spacing is adequate to identify broad-scale geochemical patterns. Geologic influence (i.e., soil parent material) was the most important factor influencing the distribution of elements along the transect, followed by the influence of regional mineralization. The study also showed that influence by human activities over the transect is minimal except possibly in large mining districts. A comparison of element abundance in the A horizon with the environmental soil guidelines in Mexico showed that the natural concentrations of the studied soils were lower than the established threshold for soil restoration with the exception of V and As. The former had a median value (75 mg/kg) approximately equal to the value established in Mexico for soil restoration in agricultural and residential lands (78 mg/kg), and the latter had three values higher than the 22 mg/kg threshold for soil restoration in agricultural and residential lands. These cases demonstrate

  5. Assessing and mapping the severity of soil erosion using the 30-m Landsat multispectral satellite data in the former South African homelands of Transkei

    Science.gov (United States)

    Seutloali, Khoboso E.; Dube, Timothy; Mutanga, Onisimo

    2017-08-01

    Soil erosion is increasingly recognised as the principal cause of land degradation, loss of agricultural land area and siltation of surrounding water waterbodies. Accurate and up-to-date soil erosion mapping is key in understanding its severity if these negative impacts are to be minimised and affected areas rehabilitated. The aim of this work was to map the severity of soil erosion, based on the 30-m Landsat series multispectral satellite data in the former South African homelands of Transkei between the year 1994 and 2010. Further, the study assessed if the observed soil erosion trends and morphology that existed in this area could be explained by biophysical factors (i.e. slope, stream erosivity, topographic wetness index) retrieved from the 30-m ASTER Digital Elevation Model (DEM). The results of this study indicate that the Transkei region experiences varying erosion levels from moderate to very severe. The large portion of the land area under the former homelands was largely affected by rill erosion with approximately 74% occurring in the year 1984 and 54% in 2010. The results also revealed specific thresholds of soil erosion drivers. These include steeper areas (≥30°), high stream power index greater than 2.0 (stream erosivity), relatively lower vegetation cover (≤15%) and low topographic wetness index (≤5%). The results of this work demonstrate the severity of soil erosion in the Southern African former homelands of Transkei for the year 1984 and 2010. Additionally, this work has demonstrated the significance of the 30-m Landsat multispectral sensor in examining soil erosion occurrence at a regional scale where in-depth field work still remains a challenging task.

  6. VSRR - State and National Provisional Counts for Live Births, Deaths, and Infant Deaths

    Data.gov (United States)

    U.S. Department of Health & Human Services — NOTES: Figures include all revisions received from the states and, therefore, may differ from those previously published. Data are provisional and are subject to...

  7. Using a fixed provisional prosthesis during post-extraction healing and implant placement.

    Science.gov (United States)

    McArdle, Barry F

    2006-03-01

    Most dental patients insist on the use of provisional prostheses throughout healing and osseointegration when replacing extracted teeth with implants in esthetically sensitive areas. Removable appliances of some kind are normally used for this purpose, but patients often consider them to be too cumbersome. This can lead to decreased case acceptance and compliance with the use of the provisional restoration, which can compromise the final result of treatment. Custom fixed solutions to this problem exist, but they tend to be more complicated, less practical, and more expensive than other options now available. The Monodont bridge, a new system of prefabricated components for the creation of provisional fixed partial dentures, can be more esthetic, more retentive, more functional, more cost-effective, and more universally applicable than any other available techniques. This can raise patient tolerance of provisional prostheses and thus increase case acceptance, while fostering a more predictable esthetic result with regard to soft tissue contours and emergence profile.

  8. A provisional gene regulatory atlas for mouse heart development.

    Science.gov (United States)

    Chen, Hailin; VanBuren, Vincent

    2014-01-01

    Congenital Heart Disease (CHD) is one of the most common birth defects. Elucidating the molecular mechanisms underlying normal cardiac development is an important step towards early identification of abnormalities during the developmental program and towards the creation of early intervention strategies. We developed a novel computational strategy for leveraging high-content data sets, including a large selection of microarray data associated with mouse cardiac development, mouse genome sequence, ChIP-seq data of selected mouse transcription factors and Y2H data of mouse protein-protein interactions, to infer the active transcriptional regulatory network of mouse cardiac development. We identified phase-specific expression activity for 765 overlapping gene co-expression modules that were defined for obtained cardiac lineage microarray data. For each co-expression module, we identified the phase of cardiac development where gene expression for that module was higher than other phases. Co-expression modules were found to be consistent with biological pathway knowledge in Wikipathways, and met expectations for enrichment of pathways involved in heart lineage development. Over 359,000 transcription factor-target relationships were inferred by analyzing the promoter sequences within each gene module for overrepresentation against the JASPAR database of Transcription Factor Binding Site (TFBS) motifs. The provisional regulatory network will provide a framework of studying the genetic basis of CHD.

  9. A provisional gene regulatory atlas for mouse heart development.

    Directory of Open Access Journals (Sweden)

    Hailin Chen

    Full Text Available Congenital Heart Disease (CHD is one of the most common birth defects. Elucidating the molecular mechanisms underlying normal cardiac development is an important step towards early identification of abnormalities during the developmental program and towards the creation of early intervention strategies. We developed a novel computational strategy for leveraging high-content data sets, including a large selection of microarray data associated with mouse cardiac development, mouse genome sequence, ChIP-seq data of selected mouse transcription factors and Y2H data of mouse protein-protein interactions, to infer the active transcriptional regulatory network of mouse cardiac development. We identified phase-specific expression activity for 765 overlapping gene co-expression modules that were defined for obtained cardiac lineage microarray data. For each co-expression module, we identified the phase of cardiac development where gene expression for that module was higher than other phases. Co-expression modules were found to be consistent with biological pathway knowledge in Wikipathways, and met expectations for enrichment of pathways involved in heart lineage development. Over 359,000 transcription factor-target relationships were inferred by analyzing the promoter sequences within each gene module for overrepresentation against the JASPAR database of Transcription Factor Binding Site (TFBS motifs. The provisional regulatory network will provide a framework of studying the genetic basis of CHD.

  10. Componentes principais como preditores no mapeamento digital de classes de solos Principal components as predictor variables in digital mapping of soil classes

    Directory of Open Access Journals (Sweden)

    Alexandre ten Caten

    2011-07-01

    Full Text Available Tecnologias disponíveis para a observação da Terra oferecem uma grande gama de informações sobre componentes ambientais que, por estarem relacionadas com a formação dos solos, podem ser usadas como variáveis preditoras no Mapeamento Digital de Solos (MDS. No entanto, modelos com um grande número de preditores, bem como a existência de multicolinearidade entre os dados, podem ser ineficazes no mapeamento de classes e propriedades do solo. O objetivo deste estudo foi empregar a Análise de Componentes Principais (ACP visando a selecionar e diminuir o número de preditores na regressão logística múltipla multinomial (RLMM utilizada no mapeamento de classes de solos. Nove covariáveis ambientais, ligadas ao fator de formação relevo, foram derivadas de um Modelo Digital de Elevação e denominadas variáveis originais, estas foram submetidas à ACP e transformadas em Componentes Principais (CP. As RLMM foram desenvolvidas utilizando-se atributos de terreno e as CP como variáveis explicativas. O mapa de solos gerado a partir de três CP (65,6% da variância original obteve um índice kappa de 37,3%, inferior aos 48,5% alcançado pelo mapa de solos gerado a partir de todas as nove variáveis originais.Available technologies for Earth observation offer a wide range of predictors relevant to Digital Soil Mapping (DSM. However, models with a large number of predictors, as well as, the existence of multicollinearity among the data, may be ineffective in the mapping of classes and soil properties. The aim of this study was to use the Principal Component Analysis (PCA to reduce the number of predictors in the multinomial logistic regression (MLR used in soil mapping. Nine environmental covariates, related to the relief factor of soil formation, were derived from a digital elevation model and named the original variables, which were submitted to PCA and transformed into principal components (PC. The MLR were developed using the terrain

  11. Health risk estimates for groundwater and soil contamination in the Slovak Republic: a convenient tool for identification and mapping of risk areas.

    Science.gov (United States)

    Fajčíková, K; Cvečková, V; Stewart, A; Rapant, S

    2014-10-01

    We undertook a quantitative estimation of health risks to residents living in the Slovak Republic and exposed to contaminated groundwater (ingestion by adult population) and/or soils (ingestion by adult and child population). Potential risk areas were mapped to give a visual presentation at basic administrative units of the country (municipalities, districts, regions) for easy discussion with policy and decision-makers. The health risk estimates were calculated by US EPA methods, applying threshold values for chronic risk and non-threshold values for cancer risk. The potential health risk was evaluated for As, Ba, Cd, Cu, F, Hg, Mn, NO3 (-), Pb, Sb, Se and Zn for groundwater and As, B, Ba, Be, Cd, Cu, F, Hg, Mn, Mo, Ni, Pb, Sb, Se and Zn for soils. An increased health risk was identified mainly in historical mining areas highly contaminated by geogenic-anthropogenic sources (ore deposit occurrence, mining, metallurgy). Arsenic and antimony were the most significant elements in relation to health risks from groundwater and soil contamination in the Slovak Republic contributing a significant part of total chronic risk levels. Health risk estimation for soil contamination has highlighted the significance of exposure through soil ingestion in children. Increased cancer risks from groundwater and soil contamination by arsenic were noted in several municipalities and districts throughout the country in areas with significantly high arsenic levels in the environment. This approach to health risk estimations and visualization represents a fast, clear and convenient tool for delineation of risk areas at national and local levels.

  12. Evaluation of Geostatistical Techniques for Mapping Spatial Distribution of Soil PH, Salinity and Plant Cover Affected by Environmental Factors in Southern Iran

    Directory of Open Access Journals (Sweden)

    Mohammad ZARE-MEHRJARDI

    2010-12-01

    Full Text Available The study presented in this paper attempts to evaluate some interpolation techniques for mapping spatial distribution of soil pH, salinity and plant cover in Hormozgan province, Iran. The relationships among environmental factors and distribution of vegetation types were also investigated. Plot sampling was applied in the study area. Landform parameters of each plot were recorded and canopy cover percentages of each species were measured while stoniness and browsing damage were estimated. Results indicated that there was a significant difference in vegetation cover for high and low slope steepness. Also, vegetation cover was greater than other cases in the mountains with calcareous lithology. In general, there were no significant relationships among vegetation cover and soil properties such as pH, EC, and texture. Other soil properties, such as soil depth and gravel percentage were significantly affected by vegetation cover. Moreover, the geostatistical results showed that kriging and cokriging methods were better than inverse distance weighting (IDW method for prediction of the spatial distribution of soil properties. Also, the results indicated that all the concerned soil and plant parameters were better determined by means of a cokriging method. Land elevation, which was highly correlated with studied parameters, was used as an auxiliary parameter.

  13. Effect of nightguard vital bleaching gel on the color stability of provisional restorative materials

    OpenAIRE

    Salwa Omar Bajunaid

    2016-01-01

    Purpose: To assess the hypothesis that there was no difference in effect of 10% and 15% tooth bleaching agents on color stability of materials used for provisional fixed dental prosthesis. Methodology: Fifteen samples from two materials used for provisional fixed dental prosthesis: methacrylate-based and composite-based materials and 15 preformed polycarbonate crowns soaked in bleaching gel or distilled water. Spectrophotometer recorded color of specimens at baseline, after 3, 7, and 14 d...

  14. Evaluation of surface physical properties of acrylic resins for provisional prosthesis

    OpenAIRE

    Sérgio Paulo Hilgenberg; Emigdio Enrique Orellana-Jimenez; Wilmer Fabian Sepúlveda-Navarro; Beatriz Elena Arana-Correa; Dario César Teixeira Alves; Nara Hellen Campanha

    2008-01-01

    Acrylic resins used for provisional prostheses should have satisfactory superficial characteristics in order to ensure gingival health and low bacterial attachment. The purpose of the present study was to evaluate the superficial roughness and contact angle after two types of polishing and the Vickers hardness of three acrylic resins (Duralay - G1, Dencrilay - G2, and Dencor - G3), all shade 66, indicated for provisional fixed prostheses. Five 20 x 3 ± 1 mm diameter discoid specimens were obt...

  15. In Vitro Fit and Cementation Resistance of Provisional Crowns for Single Implant-Supported Restorations

    OpenAIRE

    Moris,Izabela Cristina Maurício; Oliveira,Juliana Elias de; Faria,Adriana Cláudia Lapria; Ribeiro,Ricardo Faria; Rodrigues,Renata Cristina Silveira

    2015-01-01

    Abstract: This study aimed to verify marginal fit and the effect of cement film thickness standardization on retention of provisional crowns made with prefabricated acrylic cylinders on abutments, using two temporary luting agents subjected or not to mechanical cycling. Provisional crowns were made from bis-acryl (Luxatemp Fluorescence) or methyl methacrylate (Duralay) resins on acrylic cylinders and marginal fit and cement film thickness were evaluated. For retention evaluation, crowns were ...

  16. Mineração de dados para inferência de relações solo-paisagem em mapeamentos digitais de solo Data mining to infer soil-landscape relationships in digital soil mapping

    Directory of Open Access Journals (Sweden)

    Rafael Castro Crivelenti

    2009-12-01

    Full Text Available O objetivo deste trabalho foi desenvolver uma metodologia para mapeamento digital de solos na escala 1:100.000 com a aplicação de técnicas de mineração de dados a descritores de relevo e a dados de mapas geológico e pedológico preexistentes. Foi criada uma base de dados digitais a partir de cartas topográficas e temáticas, que permitiu elaboração do modelo digital de elevação (MDE da folha Dois Córregos, SP (escala 1:50.000. A partir do MDE, foram calculados os parâmetros geomorfométricos declividade, curvaturas em planta e perfil, área de contribuição e distância diagonal de drenagem. A matriz que associou esses dados georreferenciados foi analisada por meio de árvores de decisão, no ambiente de aprendizado de máquina Weka, o que gerou um modelo de predição de unidades de mapeamento de solos. A acurácia geral do modelo aumentou de 54 para 61% com a eliminação das classes com probabilidade nula de ocorrência. A associação da mineração de dados com sistemas de informações geográficas permite a elaboração de mapas digitais passíveis de uso em estudos que requeiram menor detalhamento que aqueles realizados com o mapa original.The objective of this work was to develop a methodology for digital soil mapping at a 1:100,000 scale by applying data mining techniques to preexisting relief descriptors and data from pedological and geological maps. A digital database was created from topographic and thematic maps, and allowed the generation of a digital elevation model (DEM of the Dois Córregos (SP, Brazil sheet (1:50,000 scale. The slope gradient, slope profile, contour profile, basin contributing area, and diagonal distance to drainage geomorphometric parameters were extracted from the DEM. The matrix which associated this georeferred data was analyzed by means of decision trees within the Weka machine-learning environment, and a model for soil mapping unit prediction was generated. The overall model accuracy

  17. Clinical evaluation of a visible light-cured indirect composite for long-term provisionalization.

    Science.gov (United States)

    Ewoldsen, Nels; Sundar, Veeraraghavan; Bennett, William; Kanya, Kevin; Magyar, Karl

    2008-01-01

    To clinically evaluate a visible light-cured (VLC) resin composite system for long-term provisional and esthetic diagnostic restorations, fabricated using indirect techniques. One-hundred and nine teeth were restored in 31 patients. Preoperational impressions were used to create VLC resin composite restorations (Radica) using indirect techniques. Restorations were relined as necessary and placed using various provisional cements at a follow-up appointment, subsequent to preparation of the teeth. Both fabricating laboratory technicians and placing dentists rated the restorations for acceptability in esthetics, marginal fit, occlusion, and functionality in various stages of provisionalization. All restorations (100%) were rated acceptable for esthetics prior to relining. After relining, a majority (93-100%) of restorations were rated acceptable in esthetic and functional criteria. At the placement of the permanent restoration, a majority (96-100%) of restorations were rated acceptable in esthetic and functional criteria. Terms of service ranged from two to seventy-six days. In combination with in vitro results, the clinical performance of the Radica VLC system for provisionalization and esthetic diagnostic restorations was judged to be acceptable. The system offers esthetics that are superior to conventional provisional restorations, and should be a valuable option to practitioners considering longer-term provisionalization in complex cases.

  18. Landslide susceptibility mapping using downscaled AMSR-E soil moisture: A case study from Cleveland Corral, California, US

    Science.gov (United States)

    As soil moisture increases, slope stability decreases. Remotely sensed soil moisture data can provide routine updates of slope conditions necessary for landslide predictions. For regional scale landslide investigations, only remote sensing methods have the spatial and temporal resolution required to...

  19. Mapping bare soil in South West Wales, UK, using high resolution colour infra-red aerial photography for water quality and flood risk management applications

    Science.gov (United States)

    Sykes, Helena; Neale, Simon; Coe, Sarah

    2016-04-01

    Natural Resources Wales is a UK government body responsible for environmental regulation, among other areas. River walks in Water Framework Directive (WFD) priority catchments in South West Wales, UK, identified soil entering water courses due to poaching and bank erosion, leading to deterioration in the water quality and jeopardising the water quality meeting legal minimum standards. Bare soil has also been shown to cause quicker and higher hydrograph peaks in rural catchments than if those areas were vegetated, which can lead to flooding of domestic properties during peak storm flows. The aim was to target farm visits by operational staff to advise on practices likely to improve water quality and to identify areas where soft engineering solutions such as revegetation could alleviate flood risk in rural areas. High resolution colour-infrared aerial photography, 25cm in the three colour bands and 50cm in the near infrared band, was used to map bare soil in seven catchments using supervised classification of a five band stack including the Normalised Difference Vegetation Index (NDVI). Mapping was combined with agricultural land use and field boundary data to filter out arable fields, which are supposed to bare soil for part of their cycle, and was very successful when compared to ground truthing, with the exception of silage fields which contained sparse, no or unproductive vegetation at the time the imagery was acquired leading to spectral similarity to bare soil. A raindrop trace model was used to show the path sediment from bare soil areas would take when moving through the catchment to a watercourse, with hedgerows inserted as barriers following our observations from ground truthing. The findings have been used to help farmers gain funding for improvements such as fencing to keep animals away from vulnerable river banks. These efficient and automated methods can be rolled out to more catchments in Wales and updated using aerial imagery acquired more recently to

  20. Molecular characterization of serologically atypical provisional serovars of Shigella isolates from Kolkata, India.

    Science.gov (United States)

    Dutta, Shanta; Jain, Priyanka; Nandy, Suman; Matsushita, Shigeru; Yoshida, Shin-ichi

    2014-12-01

    During 2000-2004, 13 Shigella strains that were untypable by commercially available antisera were isolated from children Shigella dysenteriae provisional serovar 204/96 (n = 3), Shigella dysenteriae provisional serovar E23507 (n = 1), Shigella dysenteriae provisional serovar I9809-73 (n = 1), Shigella dysenteriae provisional serovar 93-119 (n = 1), Shigella flexneri provisional serovar 88-893 (n = 6) and Shigella boydii provisional serovar E16553 (n = 1). In this study, characterization of those provisional serovars of Shigella was performed with respect to their antimicrobial resistance, plasmids, virulence genes and PFGE profiles. The drug resistant strains (n = 10) of Shigella identified in this study possessed various antibiotic resistance genetic markers like catA (for chloramphenicol resistance); tetA and tetB (for tetracycline resistance); dfrA1 and sul2 (for co-trimoxazole resistance); aadA1, strA and strB (for streptomycin resistance) and blaOXA-1 (for ampicillin resistance). Class 1 and/or class 2 integrons were present in eight resistant strains. Three study strains were pan-susceptible. A single mutation in the gyrA gene (serine to leucine at codon 83) was present in four quinolone resistant strains. The virulence gene ipaH (invasion plasmid antigen H) was uniformly present in all strains in this study, but the stx (Shiga toxin) and set1 (Shigella enterotoxin 1) genes were absent. Other virulence genes like ial (invasion associated locus) and sen (Shigella enterotoxin 2) were occasionally present. A large plasmid of 212 kb and of incompatibility type IncFIIA was present in the majority of the strains (n = 10) and diversity was noticed in the smaller plasmid profiles of these strains even within the same provisional serovars. PFGE profile analysis showed the presence of multiple unrelated clones among the isolates of provisional Shigella serovars. To the best of our knowledge, this is the first report on the phenotypic and

  1. Developing a provisional and national renal disease registry for Iran

    Directory of Open Access Journals (Sweden)

    Sima Ajami

    2015-01-01

    Full Text Available Background: Disease registry is a database that includes information about people suffering a special kind of disease. The aim of this study was to first identify and compare the National Renal Disease Registry (NRDR characteristics in some countries with Iran; and second, develop a provisional and NRDR for Iran. Materials and Methods: Retrieval of data of the NRDR was performed by scholars responsible in related agencies, including the Ministry of Health and Medical Education, Renal Disease charity, and data registries in the United States, United Kingdom, Malaysia, and Iran. This research was applied, and the study was descriptive-comparative. The study population consisted of the NRDR in selected countries in which data were collected by forms that were designed according to the study objectives. Sources of data were researchers, articles, books, journals, databases, websites, related documents, and people who are active in this regard, and related agencies, including the Ministry of Health and Medical Education, and patient support charity. The researchers collected data for each country based on the study objectives and then put them in comparative tables. Data were analyzed by descriptive, comparative, and theoretical methods. Results: Most of the renal transplant teams report their own results as a single center experiences. America and Britain have a preeminent national registry of renal disease compared to other countries. Conclusion: Given that control, prevention, and treatment of chronic renal diseases incur high expenses and the disease is one of leading mortality factors in Iran and across the world and since national registry system for chronic renal diseases can provide better tools and strategies to manage and evaluate patients′ characteristics as well as risk factors which eventually leads to making better decisions.

  2. Irrigation scenarios for artichokes and dry bean as a result of soil variability on the basis of resistivity mapping in southwest Italy

    Directory of Open Access Journals (Sweden)

    Alaa Aldin Alromeed

    2015-09-01

    Full Text Available This work aims at comparing irrigation strategies on the basis of deficit irrigation and soil spatial variability assessed through electrical resistivity mapping (ERM conducted by an automatic resistivity profiler on-the-go sensor. Profiles chosen along a range of soil electrical resistivity showed different soil properties linked to water holding capacity within a field, with total available water (TAW values of the coarser-textured zone corresponding to about 50% of TAW in the finertextured zone within the field. Multi-year weather data were obtained on a daily basis and scenarios were developed for climatic demand conditions representing dry average and wet years. The ISAREG water balance and irrigation scheduling model was afterwards applied to the different soil profiles and with different strategies for full and deficit irrigation, to compute water and irrigation requirements as well as related yield impacts of deficit irrigation for artichokes and dry beans. Deficit irrigation allowed calculated water savings up to about 50% for the winter crop and 33% for the summer crop with yield losses lower than 10%. Irrigation requirements within irrigation strategy were 10 to 44% different between profiles, and this indicates that soil visualization techniques such as ERM can be used for the identification of zones for site-specific irrigation management.

  3. Mapeamento digital de classes de solos: características da abordagem brasileira Digital soil mapping: characteristics of the brazilian approach

    Directory of Open Access Journals (Sweden)

    Alexandre ten Caten

    2012-11-01

    Full Text Available O solo é cada vez mais reconhecido como tendo um importante papel nos ecossistemas, assim como para a produção de alimentos e regulação do clima global. Por esse motivo, a demanda por informações relevantes e atualizadas em solos é crescente. Pesquisadores em ciência do solo estão sendo demandados a gerar informações em diferentes resoluções espaciais e com qualidade associada dentro do que está sendo chamado de Mapeamento Digital de Solos (MDS. Devido ao crescente número de trabalhos relacionados ao MDS, faz-se necessário reunir e discutir as principais características dos estudos relacionados ao mapeamento digital de classes de solos no Brasil, o que irá possibilitar uma perspectiva mais ampla dos caminhos, além de nortear trabalhos e demandas futuras. O mapeamento de classes de solos empregando técnicas de MDS é recente no país, com a primeira publicação em 2006. Entre as funções preditivas utilizadas, predomina o emprego da técnica de regressões logísticas. O fator de formação relevo foi empregado na totalidade dos estudos revisados. Quanto à avaliação da qualidade dos modelos preditivos, o emprego da matriz de erros e do índice kappa têm sido os procedimentos mais usuais. A consolidação dessa abordagem automatizada como ferramenta auxiliar ao mapeamento convencional passa pelo treinamento dos jovens pedólogos para a utilização de tecnologias da geoinformação e de ferramentas quantitativas dos aspectos de variabilidade do solo.Soil is increasingly being recognized as having an important role in ecosystems, as well as for food production and global climate regulation. For this reason, the demand for relevant and updated soil information is increasing. Soil science researchers are being demanded to produce information in different spatial resolutions with associated quality in what is being called Digital Soil Mapping (DSM. Due to an increasing number of papers related to the DSM in Brazil, it is

  4. A study on provisional cements, cementation techniques, and their effects on bonding of porcelain laminate veneers.

    Science.gov (United States)

    Vinod Kumar, G; Soorya Poduval, T; Bipin Reddy; Shesha Reddy, P

    2014-03-01

    Minimal tooth preparation is required for porcelain laminate veneers, but interim restorations are a must to protect their teeth against thermal insult, chemical irritation, and to provide aesthetics. Cement remaining after the removal of the provisional restoration can impair the etching quality of the tooth surface and fit and final bonding of the porcelain laminate veneer. This in vitro study examined the tooth surface for remaining debris of cement after removal of a provisional restoration. Determine the presence of cement debris on prepared tooth surface subsequent to the removal of provisional restoration. Determine the cement with the least residue following the cleansing procedures. Determine the effect of smear layer on the amount of residual luting cement. Eighty-four extracted natural anterior teeth were prepared for porcelain laminate veneers. For half of the teeth, the smear layer was removed before luting provisional restorations. Veneer provisional restorations were fabricated and luted to teeth with six bonding methods: varnish combined with glass ionomer cement (GIC), varnish combined with resin modified GIC, varnish, spot etching combined with dual-cure luting cement, adhesive combined with GIC, adhesive combined with resin modified GIC, and adhesive, spot etching combined with dual-cure luting cement. After removal of provisional restorations 1 week later, the tooth surface was examined for residual luting material with SEM. Traces of cement debris were found on all the prepared teeth surfaces for all six groups which were cemented with different methods. Cement debris was seen on teeth subsequent to the removal of provisional's. Dual-cure cement had the least residue following the cleansing procedures. Presence of smear layer had no statistical significance in comparison with cement residue. With the use of adhesive the cement debris was always found to be more than with the use of varnish. GIC showed maximum residual cement followed by dual-cure.

  5. Mapa digital de solos: uma proposta metodológica usando inferência fuzzy Digital soil map: a methodological proposal using fuzzy inference

    Directory of Open Access Journals (Sweden)

    Claudia C. Nolasco-Carvalho

    2009-02-01

    Full Text Available Elaborou-se um mapa digital de solos de uma área na região de Mucugê, BA, com o objetivo de avaliar o uso de geotecnologias na cartografia de solos. A metodologia desenvolvida a partir do modelo de inferência para solos - SoLIM , requer o conhecimento prévio da área por um especialista em mapeamento e está alicerçada na equação dos fatores de formação do solo e no modelo de distribuição dos solos na paisagem. Os dados, advindos do Modelo Digital do Terreno - MDT, da vegetação e da geologia, foram associados ao conhecimento do pedólogo e integrados em ambiente SIG (Sistema de Informações Geográficas sob inferência fuzzy. A modelagem por lógica fuzzy permitiu apontar as incertezas e transições da cobertura pedológica e gerou um mapa digital de solo que, quando comparado com o mapa convencional da área, mostrou menor generalização no domínio de espaços e parâmetros, ou seja, um refinamento da escala, porém a aplicabilidade da metodologia depende da validação de campo e da repetição em outras áreas.A digital soil map was elaborated for an area in the region of Mucugê-BA using data integration derived from a digital elevation model (DEM of the vegetation and geology that was associated with a soil scientist's knowledge and correlated in a GIS environment (Geography Information System under fuzzy inference, as a methodological proposal. The methodology was developed and based on the soil-land inference model - SoLIM, on the soil factor equation and the soil-landscape model. The fuzzy logic is able to simulate the uncertainty and transitions that often appear in pedologic systems. The results show that the methodology allows the generation of digital soil maps with increased scale and to reduce soil classe generalizations in the space and parameter domain. However, this methodology is very dependent upon the soil expert's knowledge and accuracy of the data base. To verify the applicability of the methodology the

  6. Effect of different provisional cement remnant cleaning procedures including Er:YAG laser on shear bond strength of ceramics

    OpenAIRE<