WorldWideScience

Sample records for soil interpretive map

  1. 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...

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

    Science.gov (United States)

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

    2014-05-01

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

  3. 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.

  4. 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

  5. Progress towards GlobalSoilMap.net soil database of Denmark

    DEFF Research Database (Denmark)

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

    2012-01-01

    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...... 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....

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

    OpenAIRE

    A. Jafari; Norair Toomanian; R. Taghizadeh Mehrjerdi

    2016-01-01

    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 relationshi...

  7. 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

    Chaharmahal-Va- Bakhtiari province. Materials and Methods: The soils in the study area have been formed on Quaternary shale and foliated clayey limestone deposits. Irrigated crops such as wheat, barley and alfalfa are the main land uses in the area. According to the semi-detailed soil survey, 120 pedons with approximate distance of 750 m were excavated and described according to the “field book for describing and sampling soils”. Soil samples were taken from different genetic horizons and soil physicochemical properties were determined. Based on the pedons description and soil analytical data, pedons were classified according to the Soil Taxonomy (ST up to subgroup level. Using aerial photo interpretation, geology map, google earth image and field observations primary soil map was created. With considering the taxonomic level, the representative pedons were determined and soil map was prepared. Multinomial logistic regression was used to predict soil classes at great group and subgroup levels. The map units that have the highest frequency were selected as indicator to calculate diversity indices in the conventional soil map at each taxonomic level. The selected map units were overlay to digital soil map and further diversity indices were calculated. Diversity indices including the Shannon’s diversity, evenness and richness index. In order to know whether the means of Shannon’s diversity for two approaches are significantly different, means comparison was done. Results and Discussion: The results confirmed that the Shannon's diversity index was higher in the digital soil map than the conventional soil map for most soil map units. At great group and subgroup levels, a significant difference was observed for the Shannon's diversity index at 0.05 and 0.001 probability levels, respectively. Comparing the conventional and the digital soil maps showed the numbers of soil map units with significant difference regarding the Shannon's diversity index decreased from great group

  8. 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

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

    Science.gov (United States)

    Brown, David J.

    2015-04-01

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

  10. 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

  11. Interpretation of soil-type maps of forestry in terms of terrestrial gamma-ray dose rate

    International Nuclear Information System (INIS)

    Kopp, D.; Hannemann, M.

    1984-01-01

    Measurements have been performed in the lowlands of the G.D.R. to determine the activity concentration of 40 K, 226 Ra and 232 Th in soil as well as the terrestrial γ-ray dose rate at the soil surface and 1 m above. The results demonstrate that the dose rate due to terrestrial radiation can be assessed by means of forest site maps indicating the potassium content of the various soils. Two examples were presented to explain the approach. (author)

  12. 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

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

    Science.gov (United States)

    Dietrich, Peter; Werban, Ulrike; Sauer, Uta

    2010-05-01

    High-resolution soil property maps are one major prerequisite for the specific protection of soil functions and restoration of degraded soils as well as sustainable land use, water and environmental management. To generate such maps the combination of digital soil mapping approaches and remote as well as proximal soil sensing techniques is most promising. However, a feasible and reliable combination of these technologies for the investigation of large areas (e.g. catchments and landscapes) and the assessment of soil degradation threats is missing. Furthermore, there is insufficient dissemination of knowledge on digital soil mapping and proximal soil sensing in the scientific community, to relevant authorities as well as prospective users. As one consequence there is inadequate standardization of techniques. At the poster we present the EU collaborative project iSOIL within the 7th framework program of the European Commission. iSOIL focuses on improving fast and reliable mapping methods of soil properties, soil functions and soil degradation risks. This requires the improvement and integration of advanced soil sampling approaches, geophysical and spectroscopic measuring techniques, as well as pedometric and pedophysical approaches. The focus of the iSOIL project is to develop new and to improve existing strategies and innovative methods for generating accurate, high resolution soil property maps. At the same time the developments will reduce costs compared to traditional soil mapping. ISOIL tackles the challenges by the integration of three major components: (i)high resolution, non-destructive geophysical (e.g. Electromagnetic Induction EMI; Ground Penetrating Radar, GPR; magnetics, seismics) and spectroscopic (e.g., Near Surface Infrared, NIR) methods, (ii)Concepts of Digital Soil Mapping (DSM) and pedometrics as well as (iii)optimized soil sampling with respect to profound soil scientific and (geo)statistical strategies. A special focus of iSOIL lies on the

  14. Decoding implicit information from the soil map of Belgium and implications for spatial modelling and soil classification

    Science.gov (United States)

    Dondeyne, Stefaan; Legrain, Xavier; Colinet, Gilles; Van Ranst, Eric; Deckers, Jozef

    2014-05-01

    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. Soil surveyors were classifying soils in the field according to physical and morphogenetic characteristics such as texture, drainage class and profile development. Mapping units are defined as a combination of these characteristics but to which modifiers can be added such as parent material, stoniness or depth to substrata. Interpretation of the map towards predicting soil properties seems straight forward. Consequently, since the soil map has been digitized, it has been used for e.g. hydrological modelling or for estimating soil organic carbon content at sub-national and national level. Besides the explicit information provided by the legend, a wealth of implicit information is embedded in the map. Based on three cases, we illustrate that by decoding this information, properties pertaining to soil drainage or soil organic carbon content can be assessed more accurately. First, the presence/absence of fragipans affects the soil hydraulic conductivity. Although a dedicated symbol exits for fragipans (suffix "...m"), it is only used explicitly in areas where fragipans are not all that common. In the Belgian Ardennes, where fragipans are common, their occurrence is implicitly implied for various soil types mentioned in explanatory booklets. Second, whenever seasonal or permanent perched water tables were observed, these were indicated by drainage class ".h." or ".i.", respectively. Stagnic properties have been under reported as typical stagnic mottling - i.e. when the surface of soil peds are lighter and/or paler than the more reddish interior - were not distinguished from mottling due to groundwater gley. Still, by combining information on topography and the occurrence of substratum layers, stagnic properties can be inferred. Thirdly, soils with deep anthropogenic enriched organic matter

  15. ERTS-1 imagery interpretation techniques in the Tennessee Valley. [land use and soil mapping

    Science.gov (United States)

    Bodenheimer, R. E. (Principal Investigator)

    1974-01-01

    The author has identified the following significant results. The feasibility of delineating major soil associations and land uses through computerized analyses is discussed. Useful and potential applications in detecting landscape change and land use mapping are described. Recommendations for improving the data processing effort in a multidisciplinary program are presented.

  16. Soil-geographical regionalization as a basis for digital soil mapping: Karelia case study

    Science.gov (United States)

    Krasilnikov, P.; Sidorova, V.; Dubrovina, I.

    2010-12-01

    Recent development of digital soil mapping (DSM) allowed improving significantly the quality of soil maps. We tried to make a set of empirical models for the territory of Karelia, a republic at the North-East of the European territory of Russian Federation. This territory was selected for the pilot study for DSM for two reasons. First, the soils of the region are mainly monogenetic; thus, the effect of paleogeographic environment on recent soils is reduced. Second, the territory was poorly mapped because of low agricultural development: only 1.8% of the total area of the republic is used for agriculture and has large-scale soil maps. The rest of the territory has only small-scale soil maps, compiled basing on the general geographic concepts rather than on field surveys. Thus, the only solution for soil inventory was the predictive digital mapping. The absence of large-scaled soil maps did not allow data mining from previous soil surveys, and only empirical models could be applied. For regionalization purposes, we accepted the division into Northern and Southern Karelia, proposed in the general scheme of soil regionalization of Russia; boundaries between the regions were somewhat modified. Within each region, we specified from 15 (Northern Karelia) to 32 (Southern Karelia) individual soilscapes and proposed soil-topographic and soil-lithological relationships for every soilscape. Further field verification is needed to adjust the models.

  17. 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

  18. Using Vegetation Maps to Provide Information on Soil Distribution

    Science.gov (United States)

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

    2016-04-01

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

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

    African Journals Online (AJOL)

    2014-03-03

    Mar 3, 2014 ... a digital soil mapping (DSM) approach to soil mapping can speed up the mapping process and thereby extend soil map use in the field of ... This research uses an expert-knowledge DSM approach to create a soil map for Stevenson Hamilton .... the different bands of the Landsat and SPOT 5 images.

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

    African Journals Online (AJOL)

    The use of a digital soil mapping (DSM) approach to soil mapping can speed up the mapping process and thereby extend soil map use in the field of hydrology. This research uses an expert-knowledge DSM approach to create a soil map for Stevenson Hamilton Research Supersite within the Kruger National Park, South ...

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

    International Nuclear Information System (INIS)

    Olson, G.L.; Lee, R.D.; Jeppesen, D.J.

    1995-01-01

    This report discusses the production of a revised version of the general soil map of the 2304-km 2 (890-mi 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

  2. 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.

  3. 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.

  4. Digital soil mapping with limited data

    NARCIS (Netherlands)

    Hartemink, A.E.; McBratney, A.B.; Lourdes Mendonça-Santos, de M.

    2008-01-01

    There has been considerable expansion in the use of digital soil mapping technologies and development of methodologies that improve digital soil mapping at all scales and levels of resolution. These developments have occurred in all parts of the world in the past few years and also in countries

  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. A Brief History of Soil Mapping and Classification in the USA

    Science.gov (United States)

    Brevik, Eric C.; Hartemink, Alfred E.

    2014-05-01

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

  7. Preliminary soil-slip susceptibility maps, southwestern California

    Science.gov (United States)

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

    2003-01-01

    This group of maps shows relative susceptibility of hill slopes to the initiation sites of rainfall-triggered soil slip-debris flows in southwestern California. As such, the maps offer a partial answer to one part of the three parts necessary to predict the soil-slip/debris-flow process. A complete prediction of the process would include assessments of “where”, “when”, and “how big”. These maps empirically show part of the “where” of prediction (i.e., relative susceptibility to sites of initiation of the soil slips) but do not attempt to show the extent of run out of the resultant debris flows. Some information pertinent to “when” the process might begin is developed. “When” is determined mostly by dynamic factors such as rainfall rate and duration, for which local variations are not amenable to long-term prediction. “When” information is not provided on the maps but is described later in this narrative. The prediction of “how big” is addressed indirectly by restricting the maps to a single type of landslide process—soil slip-debris flows. The susceptibility maps were created through an iterative process from two kinds of information. First, locations of sites of past soil slips were obtained from inventory maps of past events. Aerial photographs, taken during six rainy seasons that produced abundant soil slips, were used as the basis for soil slip-debris flow inventory. Second, digital elevation models (DEM) of the areas that were inventoried were used to analyze the spatial characteristics of soil slip locations. These data were supplemented by observations made on the ground. Certain physical attributes of the locations of the soil-slip debris flows were found to be important and others were not. The most important attribute was the mapped bedrock formation at the site of initiation of the soil slip. However, because the soil slips occur in surficial materials overlying the bedrocks units, the bedrock formation can only serve as

  8. 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.

  9. Towards quantitative usage of EMI-data for Digital Soil Mapping

    Science.gov (United States)

    Nüsch, A.-K.; Wunderlich, T.; Kathage, S.; Werban, U.; Dietrich, P.

    2009-04-01

    As formulated in the Thematic Strategy for Soil Protection prepared by the European Commission soil degradation is a serious problem in Europe. The degradation is driven or exacerbated by human activity and has a direct impact on water and air quality, biodiversity, climate and human life-quality. High-resolution soil property maps are one major prerequisite for the specific protection of soil function and restoration of degraded soils as well as sustainable land use, water and environmental management. However, the currently available techniques for (digital) soil mapping still have deficiencies in terms of reliability and precision, the feasibility of investigation of large areas (e.g. catchments and landscapes) and the assessment of soil degradation threats at this scale. The focus of the iSOIL (Interactions between soil related science - Linking geophysics, soil science and digital soil mapping) project is on improving fast and reliable mapping of soil properties, soil functions and soil degradation threats. This requires the improvement as well as integration of geophysical and spectroscopic measurement techniques in combination with advanced soil sampling approaches, pedometrical and pedophysical approaches. Many commercially available geophysical sensors and equipment (EMI, DC, gamma-spectroscopy, magnetics) are ready to use for measurements of different parameters. Data collection with individual sensors is well developed and numerously described. However comparability of data of different sensor types as well as reproducibility of data is not self-evident. In particular handling of sensors has to be carried out accurately, e.g. consistent calibration. Soil parameters will be derived from geophysical properties to create comprehensive soil maps. Therefore one prerequisite is the comparison of different geophysical properties not only qualitative but also quantitative. At least reproducibility is one of the most important conditions for monitoring tasks. The

  10. Using Cognitive Mapping to Represent and Share Users’ Interpretations of Technology

    DEFF Research Database (Denmark)

    Kjærgaard, Annemette Leonhardt; Jensen, Tina Blegind

    2014-01-01

    be elicited, and only a few studies suggest methods for doing so. In this article we address this opportunity by advancing cognitive mapping as a well-established method to systematically inquire into people’s interpretations of technology. We show how cognitive maps can serve as visual means......An assumption implied by much of the literature in information systems (IS) research is that people’s interpretations of technology influence the way in which technology gets adapted in organizations. Despite this acknowledgment, little insight is provided for how these interpretations can...... of representation of these interpretations and discuss how the maps can be used to facilitate individual reflection and collective negotiation of technology adaptation. We illustrate the use of the cognitive mapping method with a case example of the introduction of an electronic patient record (EPR) system...

  11. 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

  12. Soil-Gas Radon Anomaly Map of an Unknown Fault Zone Area, Chiang Mai, Northern Thailand

    Science.gov (United States)

    Udphuay, S.; Kaweewong, C.; Imurai, W.; Pondthai, P.

    2015-12-01

    Soil-gas radon concentration anomaly map was constructed to help detect an unknown subsurface fault location in San Sai District, Chiang Mai Province, Northern Thailand where a 5.1-magnitude earthquake took place in December 2006. It was suspected that this earthquake may have been associated with an unrecognized active fault in the area. In this study, soil-gas samples were collected from eighty-four measuring stations covering an area of approximately 50 km2. Radon in soil-gas samples was quantified using Scintrex Radon Detector, RDA-200. The samplings were conducted twice: during December 2014-January 2015 and March 2015-April 2015. The soil-gas radon map obtained from this study reveals linear NNW-SSE trend of high concentration. This anomaly corresponds to the direction of the prospective fault system interpreted from satellite images. The findings from this study support the existence of this unknown fault system. However a more detailed investigation should be conducted in order to confirm its geometry, orientation and lateral extent.

  13. 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

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

    Science.gov (United States)

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

    2018-01-01

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

  15. Soil property maps of Africa at 250 m resolution

    Science.gov (United States)

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

    2015-04-01

    Vast areas of arable land in sub-Saharan Africa suffer from low soil fertility and physical soil constraints, and significant amounts of nutrients are lost yearly due to unsustainable soil management practices. At the same time it is expected that agriculture in Africa must intensify to meet the growing demand for food and fiber the next decades. Protection and sustainable management of Africa's soil resources is crucial to achieve this. In this context, comprehensive, accurate and up-to-date soil information is an essential input to any agricultural or environmental management or policy and decision-making model. In Africa, detailed soil information has been fragmented and limited to specific zones of interest for decades. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. AfSIS builds on recent advances in digital soil mapping, infrared spectroscopy, remote sensing, (geo)statistics, and integrated soil fertility management to improve the way soils are evaluated, mapped, and monitored. Over the period 2008-2014, the AfSIS project has compiled two soil profile data sets (about 28,000 unique locations): the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site (new soil samples) database -- the two data sets represent the most comprehensive soil sample database of the African continent to date. In addition a large set of high-resolution environmental data layers (covariates) was assembled. The point data were used in the AfSIS project to generate a set of maps of key soil properties for the African continent at 250 m spatial resolution: sand, silt and clay fractions, bulk density, organic carbon, total nitrogen, pH, cation-exchange capacity, exchangeable bases (Ca, K, Mg, Na), exchangeable acidity, and Al content. These properties were mapped for six depth intervals up to 2 m: 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm. Random forests modelling was used to

  16. 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.

  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. 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.

  19. 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.

  20. Evaluation of Electromagnetic Induction to Characterize and Map Sodium-Affected Soils in the Northern Great Plains of the United States

    Science.gov (United States)

    Brevik, E. C.; Heilig, J.; Kempenich, J.; Doolittle, J.; Ulmer, M.

    2012-04-01

    Sodium-affected soils (SAS) cover over 4 million hectares in the Northern Great Plains of the United States. Improving the classification, interpretation, and mapping of SAS is a major goal of the United States Department of Agriculture-Natural Resource Conservation Service (USDA-NRCS) as Northern Great Plains soil surveys are updated. Apparent electrical conductivity (ECa) as measured with ground conductivity meters has shown promise for mapping SAS, however, this use of this geophysical tool needs additional evaluation. This study used an EM-38 MK2-2 meter (Geonics Limited, Mississauga, Ontario), a Trimble AgGPS 114 L-band DGPS (Trimble, Sunnyvale, CA) and the RTmap38MK2 program (Geomar Software, Inc., Mississauga, Ontario) on an Allegro CX field computer (Juniper Systems, North Logan, UT) to collect, observe, and interpret ECa data in the field. The ECa map generated on-site was then used to guide collection of soil samples for soil characterization and to evaluate the influence of soil properties in SAS on ECa as measured with the EM-38MK2-2. Stochastic models contained in the ESAP software package were used to estimate the SAR and salinity levels from the measured ECa data in 30 cm depth intervals to a depth of 90 cm and for the bulk soil (0 to 90 cm). This technique showed promise, with meaningful spatial patterns apparent in the ECa data. However, many of the stochastic models used for salinity and SAR for individual depth intervals and for the bulk soil had low R-squared values. At both sites, significant variability in soil clay and water contents along with a small number of soil samples taken to calibrate the ECa values to soil properties likely contributed to these low R-squared values.

  1. 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.

  2. 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 ...

  3. 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

    implementation generally improved the algorithm’s ability to predict the correct soil class. The implementation of soil-landscape relationships and area-proportional sampling generally increased the calculation time, while the random forest implementation reduced the calculation time. In the most successful......Detailed soil information is often needed to support agricultural practices, environmental protection and policy decisions. Several digital approaches can be used to map soil properties based on field observations. When soil observations are sparse or missing, an alternative approach...... is to disaggregate existing conventional soil maps. At present, the DSMART algorithm represents the most sophisticated approach for disaggregating conventional soil maps (Odgers et al., 2014). The algorithm relies on classification trees trained from resampled points, which are assigned classes according...

  4. Accounting for access costs in validation of soil maps

    NARCIS (Netherlands)

    Yang, Lin; Brus, Dick J.; Zhu, A.X.; Li, Xinming; Shi, Jingjing

    2018-01-01

    The quality of soil maps can best be estimated by collecting additional data at locations selected by probability sampling. These data can be used in design-based estimation of map quality measures such as the population mean of the squared prediction errors (MSE) for continuous soil maps and

  5. Spectral signature selection for mapping unvegetated soils

    Science.gov (United States)

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

    1975-01-01

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

  6. A GIS-based fuzzy classification for mapping the agricultural soils for N-fertilizers use.

    Science.gov (United States)

    Assimakopoulos, J H; Kalivas, D P; Kollias, V J

    2003-06-20

    Special attention should be paid to the choice of the proper N-fertilizer, in order to avoid a further acidification and degradation of acid soils and at the same time to improve nitrogen use efficiency and to limit the nitrate pollution of the ground waters. Therefore, the risk of leaching of the fertilizer and of the acidification of the soils must be considered prior to any N-fertilizer application. The application of N-fertilizers to the soil requires a good knowledge of the soil-fertilizer relationship, which those who are planning the fertilization policy and/or applying it might not have. In this study, a fuzzy classification methodology is presented for mapping the agricultural soils according to the kind and the rate of application of N-fertilizer that should be used. The values of pH, clay, sand and carbonates soil variables are estimated at each point of an area by applying geostatistical techniques. Using the pH values three fuzzy sets: "no-risk-acidification"; "low-risk-acidification"; and "high-risk-acidification" are produced and the memberships of each point to the three sets are estimated. Additionally, from the clay and sand values the membership grade to the fuzzy set "risk-of-leaching" is calculated. The parameters and their values, which are used for the construction of the fuzzy sets, are based on the literature, the existing knowledge and the experimentation, of the soil-fertilizer relationships and provide a consistent mechanism for mapping the soils according to the type of N-fertilizers that should be applied and the rate of applications. The maps produced can easily be interpreted and used by non-experts in the application of the fertilization policy at national, local and farm level. The methodology is presented through a case study using data from the Amfilochia area, west Greece.

  7. Small scale digital soil mapping in Southeastern Kenya

    NARCIS (Netherlands)

    Mora Vallejo, A.P.; Claessens, L.; Stoorvogel, J.J.; Heuvelink, G.B.M.

    2008-01-01

    Digital soil mapping techniques appear to be an interesting alternative for traditional soil survey techniques. However, most applications deal with (semi-)detailed soil surveys where soil variability is determined by a limited number of soil forming factors. The question that remains is whether

  8. 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 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.

  9. Interpretation of soil-to-plant transfer on the basis of soil solution chemical composition

    International Nuclear Information System (INIS)

    Lembrechts, J.F.; Van Loon, L.R.; Van Ginkel, J.H.; Desmet, G.M.

    1988-01-01

    Soil-to-plant translocation of a radionuclide depends on its availability on the one hand and on the efficiency of the uptake process on the other. Criticism on the use of transfer coefficients for the description of translocation mainly concerns the fact that the complex variety of processes, a.o. dependent on plant characteristics and soil type and treatment, is integrated in a single ratio. For the interpretation of the effect of counter-measures the static transfer coefficient proved to be hard to handle and knowledge of the separate underlying processes and their time dependence showed to be indispensible. Based upon translocation experiments with technetium, cobalt, strontium and zinc transfer was shown to be primarily related to the concentration of the plant available fraction in the soil solution as well as to the soil solution chemistry in general. The transfer factor of the first three elements expressed in the basis of soil solution activity (ml/g), was observed to decrease when the nutrient content of the soil solution -- reflected by its conductivity -- increased. The characteristics of the soil matrix (solid phase) furthermore showed to be of secondary importance for the explanation of the observed accumulation. Since the interstitial soil liquid phase mediates between solid phase and plant root, reliable interpretations of soil-to-plant transfer might as a rule be based on a separate study of the effect of soil properties on availability on the one hand of the uptake from nutrient solutions on the other

  10. Mapping wind erosion hazard in Australia using MODIS-derived ground cover, soil moisture and climate data

    International Nuclear Information System (INIS)

    Yang, X; Leys, J

    2014-01-01

    This paper describes spatial modeling methods to identify wind erosion hazard (WEH) areas across Australia using the recently available time-series products of satellite-derived ground cover, soil moisture and wind speed. We implemented the approach and data sets in a geographic information system to produce WEH maps for Australia at 500 m ground resolution on a monthly basis for the recent thirteen year period (2000–2012). These maps reveal the significant wind erosion hazard areas and their dynamic tendencies at paddock and regional scales. Dust measurements from the DustWatch network were used to validate the model and interpret the dust source areas. The modeled hazard areas and changes were compared with results from a rule-set approach and the Computational Environmental Management System (CEMSYS) model. The study demonstrates that the time series products of ground cover, soil moisture and wind speed can be jointly used to identify landscape erodibility and to map seasonal changes of wind erosion hazard across Australia. The time series wind erosion hazard maps provide detailed and useful information to assist in better targeting areas for investments and continuous monitoring, evaluation and reporting that will lead to reduced wind erosion and improved soil condition

  11. 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

  12. Interpreting map art with a perspective learned from J.M. Blaut

    Science.gov (United States)

    Varanka, D.

    2006-01-01

    Map art has been mentioned only briefly in geographic or cartographic literature, and has been analyzed almost entirely at the interpretive level. This paper attempts to define and evaluate the cartographic value of contemporary map-like art by placing the body of work as a whole in the theoretical concepts proposed by J.M. Blaut and his colleagues about mapping as a cognitive and cultural universal. This paper discusses how map art resembles mapping characteristics similar to those observed empirically in very young children as described in the publications of Blaut and others. The theory proposes that these early mapping skills are later structured and refined by their social context and practice. Diverse cultural contexts account for the varieties, types, and degrees of mapping behavior documented with time and geographic place. The dynamics of early mapping are compared to mapping techniques employed by artists. The discipline of fine art serves as the context surrounding map artists and their work. My visual analysis, research about the art and the artists, and interviews with artists and curators form the basis of my interpretation of these works within varied and multiple contexts of late 20th century map art.

  13. 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.

  14. Uncertainty indication in soil function maps - transparent and easy-to-use information to support sustainable use of soil resources

    Science.gov (United States)

    Greiner, Lucie; Nussbaum, Madlene; Papritz, Andreas; Zimmermann, Stephan; Gubler, Andreas; Grêt-Regamey, Adrienne; Keller, Armin

    2018-05-01

    Spatial information on soil function fulfillment (SFF) is increasingly being used to inform decision-making in spatial planning programs to support sustainable use of soil resources. Soil function maps visualize soils abilities to fulfill their functions, e.g., regulating water and nutrient flows, providing habitats, and supporting biomass production based on soil properties. Such information must be reliable for informed and transparent decision-making in spatial planning programs. In this study, we add to the transparency of soil function maps by (1) indicating uncertainties arising from the prediction of soil properties generated by digital soil mapping (DSM) that are used for soil function assessment (SFA) and (2) showing the response of different SFA methods to the propagation of uncertainties through the assessment. For a study area of 170 km2 in the Swiss Plateau, we map 10 static soil sub-functions for agricultural soils for a spatial resolution of 20 × 20 m together with their uncertainties. Mapping the 10 soil sub-functions using simple ordinal assessment scales reveals pronounced spatial patterns with a high variability of SFF scores across the region, linked to the inherent properties of the soils and terrain attributes and climate conditions. Uncertainties in soil properties propagated through SFA methods generally lead to substantial uncertainty in the mapped soil sub-functions. We propose two types of uncertainty maps that can be readily understood by stakeholders. Cumulative distribution functions of SFF scores indicate that SFA methods respond differently to the propagated uncertainty of soil properties. Even where methods are comparable on the level of complexity and assessment scale, their comparability in view of uncertainty propagation might be different. We conclude that comparable uncertainty indications in soil function maps are relevant to enable informed and transparent decisions on the sustainable use of soil resources.

  15. 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

  16. 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.

  17. Digital Mapping of Soil Drainage Classes Using Multitemporal RADARSAT-1 and ASTER Images and Soil Survey Data

    Directory of Open Access Journals (Sweden)

    Mohamed Abou Niang

    2012-01-01

    Full Text Available Discriminant analysis classification (DAC and decision tree classifiers (DTC were used for digital mapping of soil drainage in the Bras-d’Henri watershed (QC, Canada using earth observation data (RADARSAT-1 and ASTER and soil survey dataset. Firstly, a forward stepwise selection was applied to each land use type identified by ASTER image in order to derive an optimal subset of soil drainage class predictors. The classification models were then applied to these subsets for each land use and merged to obtain a digital soil drainage map for the whole watershed. The DTC method provided better classification accuracies (29 to 92% than the DAC method (33 to 79% according to the land use type. A similarity measure (S was used to compare the best digital soil drainage map (DTC to the conventional soil drainage map. Medium to high similarities (0.6≤S<0.9 were observed for 83% (187 km2 of the study area while 3% of the study area showed very good agreement (S≥0.9. Few soil polygons showed very weak similarities (S<0.3. This study demonstrates the efficiency of combining radar and optical remote sensing data with a representative soil dataset for producing digital maps of soil drainage.

  18. 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

  19. Uncertainty indication in soil function maps – transparent and easy-to-use information to support sustainable use of soil resources

    Directory of Open Access Journals (Sweden)

    L. Greiner

    2018-05-01

    Full Text Available Spatial information on soil function fulfillment (SFF is increasingly being used to inform decision-making in spatial planning programs to support sustainable use of soil resources. Soil function maps visualize soils abilities to fulfill their functions, e.g., regulating water and nutrient flows, providing habitats, and supporting biomass production based on soil properties. Such information must be reliable for informed and transparent decision-making in spatial planning programs. In this study, we add to the transparency of soil function maps by (1 indicating uncertainties arising from the prediction of soil properties generated by digital soil mapping (DSM that are used for soil function assessment (SFA and (2 showing the response of different SFA methods to the propagation of uncertainties through the assessment. For a study area of 170 km2 in the Swiss Plateau, we map 10 static soil sub-functions for agricultural soils for a spatial resolution of 20 × 20 m together with their uncertainties. Mapping the 10 soil sub-functions using simple ordinal assessment scales reveals pronounced spatial patterns with a high variability of SFF scores across the region, linked to the inherent properties of the soils and terrain attributes and climate conditions. Uncertainties in soil properties propagated through SFA methods generally lead to substantial uncertainty in the mapped soil sub-functions. We propose two types of uncertainty maps that can be readily understood by stakeholders. Cumulative distribution functions of SFF scores indicate that SFA methods respond differently to the propagated uncertainty of soil properties. Even where methods are comparable on the level of complexity and assessment scale, their comparability in view of uncertainty propagation might be different. We conclude that comparable uncertainty indications in soil function maps are relevant to enable informed and transparent decisions on the sustainable use of soil

  20. 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

    Soil mapping in Denmark has a long history and a series of soil maps based on conventional mapping approaches have been produced. In this study, a national soil map of Denmark was constructed based on the FAO–Unesco Revised Legend 1990 using digital soil mapping techniques, existing soil profile......) 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...

  1. Soil Functional Mapping: A Geospatial Framework for Scaling Soil Carbon Cycling

    Science.gov (United States)

    Lawrence, C. R.

    2017-12-01

    Climate change is dramatically altering biogeochemical cycles in most terrestrial ecosystems, particularly the cycles of water and carbon (C). These changes will affect myriad ecosystem processes of importance, including plant productivity, C exports to aquatic systems, and terrestrial C storage. Soil C storage represents a critical feedback to climate change as soils store more C than the atmosphere and aboveground plant biomass combined. While we know plant and soil C cycling are strongly coupled with soil moisture, substantial unknowns remain regarding how these relationships can be scaled up from soil profiles to ecosystems. This greatly limits our ability to build a process-based understanding of the controls on and consequences of climate change at regional scales. In an effort to address this limitation we: (1) describe an approach to classifying soils that is based on underlying differences in soil functional characteristics and (2) examine the utility of this approach as a scaling tool that honors the underlying soil processes. First, geospatial datasets are analyzed in the context of our current understanding of soil C and water cycling in order to predict soil functional units that can be mapped at the scale of ecosystems or watersheds. Next, the integrity of each soil functional unit is evaluated using available soil C data and mapping units are refined as needed. Finally, targeted sampling is conducted to further differentiate functional units or fill in any data gaps that are identified. Completion of this workflow provides new geospatial datasets that are based on specific soil functions, in this case the coupling of soil C and water cycling, and are well suited for integration with regional-scale soil models. Preliminary results from this effort highlight the advantages of a scaling approach that balances theory, measurement, and modeling.

  2. 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

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

    DEFF Research Database (Denmark)

    Dewitte, Olivier; Jones, Arwyn; Spaargaren, Otto

    2013-01-01

    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...... with no information, soil patterns, river and drainage networks, and dynamic features such as sand dunes, water bodies and coastlines. In comparison to the initial map derived from HWSD, the new map represents a correction of 13% of the soil data for the continent. The map is available for downloading. (C) 2013......, 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...

  5. 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...

  6. 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...

  7. A comparison between probability and information measures of uncertainty in a simulated soil map and the economic value of imperfect soil information.

    Science.gov (United States)

    Lark, R. Murray

    2014-05-01

    Conventionally the uncertainty of a conventional soil map has been expressed in terms of the mean purity of its map units: the probability that the soil profile class examined at a site would be found to correspond to the eponymous class of the simple map unit that is delineated there (Burrough et al, 1971). This measure of uncertainty has an intuitive meaning and is used for quality control in soil survey contracts (Western, 1978). However, it may be of limited value to the manager or policy maker who wants to decide whether the map provides a basis for decision making, and whether the cost of producing a better map would be justified. In this study I extend a published analysis of the economic implications of uncertainty in a soil map (Giasson et al., 2000). A decision analysis was developed to assess the economic value of imperfect soil map information for agricultural land use planning. Random error matrices for the soil map units were then generated, subject to constraints which ensure consistency with fixed frequencies of the different soil classes. For each error matrix the mean map unit purity was computed, and the value of the implied imperfect soil information was computed by the decision analysis. An alternative measure of the uncertainty in a soil map was considered. This is the mean soil map information which is the difference between the information content of a soil observation, at a random location in the region, and the information content of a soil observation given that the map unit is known. I examined the relationship between the value of imperfect soil information and the purity and information measures of map uncertainty. In both cases there was considerable variation in the economic value of possible maps with fixed values of the uncertainty measure. However, the correlation was somewhat stronger with the information measure, and there was a clear upper bound on the value of an imperfect soil map when the mean information takes some

  8. The role of soil quality maps in the reuse of lightly contaminated soil

    OpenAIRE

    Lamé, F.P.J.; Leenaers, H.; Zegwaard, J.

    2000-01-01

    In 1999 the Dutch government agreed on a new policy regarding the reuse of lightly contaminated soil. From now on, lightly contaminated soil may be reused under conditions of soil-quality management. The municipal authorities supervise the reuse under this new regime. Two basic criteria need to be met before reuse of lightly contaminated soil is allowed. Firstly, the quality of the soil has to be characterised on a soil quality map. Secondly, the soil that will be reused has to be of the same...

  9. Combining hyperspectral imagery and legacy measured soil profiles to map subsurface soil properties in a Mediterranean area (Cap-Bon, Tunisia)

    Science.gov (United States)

    Lagacherie, Philippe; Sneep, Anne-Ruth; Gomez, Cécile

    2013-04-01

    Previous studies have demonstrated that Visible Near InfraRed (Vis-NIR) Hyperspectral imagery is a cost-efficient way for mapping soil properties at fine resolutions (~5m) over large areas. However, such mapping is only feasible for soil surface since the effective penetration depths of optical sensors do not exceed several millimetres. This study aimed to extend the use of Vis-NIR hyperspectral imagery to the mapping of subsurface properties at three intervals of depth (15-30 cm, 30-60 cm and 60-100 cm) as specified by the GlobalSoilMap project. To avoid additional data collection, our basic idea was to develop an original Digital Soil Mapping approach that combines the digital maps of surface soil properties obtained from Vis-NIR hyperspectral imagery with legacy soil profiles of the region and with easily available images of DEM-derived parameters. The study was conducted in a pedologically-contrasted 300km² cultivated area located in the Cap Bon region (Northern Tunisia). AISA-Dual Vis-NIR hyperspectral airborne data were acquired over the studied area with a fine spatial resolution (5 m) and fine spectral resolution (260 spectral bands from 450 to 2500nm). Vegetated surfaces were masked to conserve only bare soil surface which represented around 50% of the study area. Three soil surface properties (clay and sand contents, Cation Exchange Capacity) were successfully mapped over the bare soils, from these data using Partial Least Square Regression models (R2 > 0.7). We used as additional data a set of images of landscape covariates derived from a 30 meter DEM and a local database of 152 legacy soil profiles from which soil properties values at the required intervals of depths were computed using an equal-area-spline algorithm. Our Digital Soil Mapping approach followed two steps: i) the development of surface-subsurface functions - linear models and random forests - that estimates subsurface property values from surface ones and landscape covariates and that

  10. An interpretation map: Finding paths to reading processes | Green ...

    African Journals Online (AJOL)

    An interpretation map: Finding paths to reading processes. ... and for itself and that reading happens to the text as some extrinsic and contingent event. – Paul Ricoeur. A consideration of ... AJOL African Journals Online. HOW TO USE AJOL.

  11. Evaluation of urban soils. Subproject 4: Bonding of heavy metals in technological soils - mapping of urban soils for the city of Rostock. Final report

    International Nuclear Information System (INIS)

    Kretschmer, H.; Coburger, E.; Kahle, P.; Neumann, A.; Surkus, A.

    1995-01-01

    Within the framework of the project a conceptional soil map for the urban area of Rostock was drawn up. The starting point was formed by the collection and analysis of available information. The following maps were digitised with the help of the geographical information system Arc/Info: Soil estimation, middle scaled map of agricultural sites, geology, maps of bogs and forest sites, map of the bog-depth sourrounding the river Warnow by Geinitz from 1887. To characterise the influence by man information about impermeable covered areas, actual land use, thrown up areas and disposal sites as well as war-destroyed sites were digitally used. Till the beginning of this project no information about impermeable covered areas and about the actual land use were available. That's why these two maps were created within the framework of the project on the base of topographical maps, aerial photographs and results of on-site-captures. Afterwards the thematic layers were overlapped. The general conceptional map for the urban area of Rostock was created out of the three separate conceptional maps about groundwater-influence, natural soil inventory and man-influence. Soil societies were assigned to the units of this general conceptional map. At the end 35 units were given for Rostock. Detailed mappings were taken on areas of the following kinds of use: Living areas, city centre, gardens, parks, graveyards, industrial and military sites. 26 main profiles were described and soil-physically and soil-chemically examined. The total contents of the heavy metals Zn, Cu, Pb and Cd were determined for the horizons of the main profiles. The subproject of Rostock is also concerned with investigations on the heavy metals (hM) Cu, Pb, Cd, Zn and Ni in technological substrates (tS) from Kiel, Eckernfoerde, Halle and Rostock (11 main soil profiles). (orig./SR) [de

  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. Combining land use data acquired from Landsat with soil map data

    Science.gov (United States)

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

    1981-01-01

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

  14. Quantitative map interpretation in regional planning surveys. | J.A. ...

    African Journals Online (AJOL)

    A procedure followed for the quantitative interpretation of maps compiled for regional planning purposes of the Upper Orange catchment-basin is presented. The analyses provided useful figures concerning the distribution of dominant vegetation components and their association with relevant habitat factors. Keywords: ...

  15. Soil mapping and modelling for evaluation of the effects of historical and present-day soil erosion

    Science.gov (United States)

    Smetanova, Anna; Szwarczewski, Piotr

    2016-04-01

    The loess hilly lands in Danube Lowland are characterized by patchy soil-scape. The soil erosion processes uncover the subsurface, bright loess horizon, while non-eroded and colluvial soils are of the dark colour, in the chernozem area. With the modernisation of agriculture since the 1950's and in the process of collectivization, when small fields were merged into bigger, the soil degradation progressed. However, the analysis of historical sources and sediment archives showed the proofs of historical soil erosion. The objective of this study is to map the soil erosion patterns in connection of both pre- and post-collectivization landscape and to understand the accordingly developed soil erosion patterns. The combined methods of soil mapping and soil erosion modelling were applied in the part of the Trnavska pahorkatina Hilly Land in Danube Lowland. The detailed soil mapping in a zero-order catchment (0.28 km²) uncovered the removal of surface soil horizon of 0.6m or more, while the colluvial soils were about 1.1m deep. The soil properties and dating helped to describe the original soil profile in the valley bottom, and reconstruct the history of soil erosion in the catchment. The soil erosion model was applied using the reconstructed land use patterns in order to understand the effect of recent and historical soil erosion in the lowland landscape. This work was supported by the Slovak Research and Development Agency under the contract ESF-EC-0006-07 and APVV-0625-11; Anna Smetanová has received the support of the AgreenSkills fellowship (under grant agreement n°267196).

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

    DEFF Research Database (Denmark)

    Beucher, Amélie; Boman, A; Mattbäck, S

    impact through the resulting corrosion of concrete and steel infrastructures, or their poor geotechnical qualities. Therefore, mapping acid sulfate soil occurrence constitutes a key step to target the strategic areas for subsequent environmental risk management and mitigation. Conventional mapping (i...... obtained from a EM38 proximal sensor enabled the refined mapping of acid sulfate soils over a field (Huang et al. 2014). The present study aims at developing an efficient and reliable method for the detailed predictive mapping of acid sulfate soil occurrence in a field located in western Finland. Different...

  17. 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

  18. 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.

  19. 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...

  20. 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.

  1. The Use of Electromagnetic Induction Techniques for Soil Mapping

    Science.gov (United States)

    Brevik, Eric C.; Doolittle, Jim

    2015-04-01

    Soils have high natural spatial variability. This has been recognized for a long time, and many methods of mapping that spatial variability have been investigated. One technique that has received considerable attention over the last ~30 years is electromagnetic induction (EMI). Particularly when coupled with modern GPS and GIS systems, EMI techniques have allowed the rapid and relatively inexpensive collection of large spatially-related data sets that can be correlated to soil properties that either directly or indirectly influence electrical conductance in the soil. Soil electrical conductivity is directly controlled by soil water content, soluble salt content, clay content and mineralogy, and temperature. A wide range of indirect controls have been identified, such as soil organic matter content and bulk density; both influence water relationships in the soil. EMI techniques work best in areas where there are large changes in one soil property that influences soil electrical conductance, and don't work as well when soil properties that influence electrical conductance are largely homogenous. This presentation will present examples of situations where EMI techniques were successful as well as a couple of examples of situations where EMI was not so useful in mapping the spatial variability of soil properties. Reasons for both the successes and failures will be discussed.

  2. One perspective on spatial variability in geologic mapping

    Science.gov (United States)

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

    1991-01-01

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

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

    Science.gov (United States)

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

    2016-12-15

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

  4. Lineament interpretation. Short review and methodology

    Energy Technology Data Exchange (ETDEWEB)

    Tiren, Sven (GEOSIGMA AB (Sweden))

    2010-11-15

    The ground comprises the solid and continuous surface of the Earth. The crystalline crust, i.e. bedrock, is exposed or covered with sediments and vegetation. The morphology of the ground surface is influenced by a combination of tectonometamorphic- magmatic processes (building up) and denudation/erosion processes (tearing down). Landforms are related to these processes and the character of the bedrock (lithologies and structures), and the distribution of soil or other unconsolidated, superficial material. By using remote-sensing techniques applied for structural analysis of the ground surface, it is possible to map features in the terrain that are related to bedrock structures provided that the topography of the bedrock surface is not totally concealed below a cover of soil or other loose material. Even though the sedimentary cover is relatively thick it may be distorted and the ground surface displaced by late faulting in the basement rock. Studies of the relation between structures in the bedrock and the topography started more than 150 years ago. Hobbs (1903, 1912) introduced the fundamental concept of 'lineaments' and described them as 'significant lines in the Earth's face' and later he concluded that they are 'lines in the landscape which reveal the hidden architecture of the basement'. When airborne geophysical measurements started approximately fifty years ago such data were used to compliment the topographical interpretation of basement structures. Source data for studies of lineaments consist of information on the topography (e.g. topographical maps, aerial photos, elevation data, multi-spectral sensing, laser, radar and thermography) and geophysical data (e.g. airborne geophysical data comprising magnetic, electromagnetic, radiation measurements, and gravimetric measurements). The outcome of a lineament study depends on the terrain in the investigated area, the source data, the approach and systematic performance in the

  5. Lineament interpretation. Short review and methodology

    International Nuclear Information System (INIS)

    Tiren, Sven

    2010-11-01

    The ground comprises the solid and continuous surface of the Earth. The crystalline crust, i.e. bedrock, is exposed or covered with sediments and vegetation. The morphology of the ground surface is influenced by a combination of tectonometamorphic- magmatic processes (building up) and denudation/erosion processes (tearing down). Landforms are related to these processes and the character of the bedrock (lithologies and structures), and the distribution of soil or other unconsolidated, superficial material. By using remote-sensing techniques applied for structural analysis of the ground surface, it is possible to map features in the terrain that are related to bedrock structures provided that the topography of the bedrock surface is not totally concealed below a cover of soil or other loose material. Even though the sedimentary cover is relatively thick it may be distorted and the ground surface displaced by late faulting in the basement rock. Studies of the relation between structures in the bedrock and the topography started more than 150 years ago. Hobbs (1903, 1912) introduced the fundamental concept of 'lineaments' and described them as 'significant lines in the Earth's face' and later he concluded that they are 'lines in the landscape which reveal the hidden architecture of the basement'. When airborne geophysical measurements started approximately fifty years ago such data were used to compliment the topographical interpretation of basement structures. Source data for studies of lineaments consist of information on the topography (e.g. topographical maps, aerial photos, elevation data, multi-spectral sensing, laser, radar and thermography) and geophysical data (e.g. airborne geophysical data comprising magnetic, electromagnetic, radiation measurements, and gravimetric measurements). The outcome of a lineament study depends on the terrain in the investigated area, the source data, the approach and systematic performance in the interpretation, and the skill of

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

    Science.gov (United States)

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

    2016-04-01

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

  7. Accuracy assessment of vegetation community maps generated by aerial photography interpretation: perspective from the tropical savanna, Australia

    Science.gov (United States)

    Lewis, Donna L.; Phinn, Stuart

    2011-01-01

    Aerial photography interpretation is the most common mapping technique in the world. However, unlike an algorithm-based classification of satellite imagery, accuracy of aerial photography interpretation generated maps is rarely assessed. Vegetation communities covering an area of 530 km2 on Bullo River Station, Northern Territory, Australia, were mapped using an interpretation of 1:50,000 color aerial photography. Manual stereoscopic line-work was delineated at 1:10,000 and thematic maps generated at 1:25,000 and 1:100,000. Multivariate and intuitive analysis techniques were employed to identify 22 vegetation communities within the study area. The accuracy assessment was based on 50% of a field dataset collected over a 4 year period (2006 to 2009) and the remaining 50% of sites were used for map attribution. The overall accuracy and Kappa coefficient for both thematic maps was 66.67% and 0.63, respectively, calculated from standard error matrices. Our findings highlight the need for appropriate scales of mapping and accuracy assessment of aerial photography interpretation generated vegetation community maps.

  8. 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.

  9. 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.

  10. Semi-automated landform classification for hazard mapping of soil liquefaction by earthquake

    Science.gov (United States)

    Nakano, Takayuki

    2018-05-01

    Soil liquefaction damages were caused by huge earthquake in Japan, and the similar damages are concerned in near future huge earthquake. On the other hand, a preparation of soil liquefaction risk map (soil liquefaction hazard map) is impeded by the difficulty of evaluation of soil liquefaction risk. Generally, relative soil liquefaction risk should be able to be evaluated from landform classification data by using experimental rule based on the relationship between extent of soil liquefaction damage and landform classification items associated with past earthquake. Therefore, I rearranged the relationship between landform classification items and soil liquefaction risk intelligibly in order to enable the evaluation of soil liquefaction risk based on landform classification data appropriately and efficiently. And I developed a new method of generating landform classification data of 50-m grid size from existing landform classification data of 250-m grid size by using digital elevation model (DEM) data and multi-band satellite image data in order to evaluate soil liquefaction risk in detail spatially. It is expected that the products of this study contribute to efficient producing of soil liquefaction hazard map by local government.

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

    Science.gov (United States)

    Norman, Laura

    2004-01-01

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

  12. MAPPING OF SOIL DEGRADATION POTENCY IN PADDY FIELD WONOGIRI, INDONESIA

    Directory of Open Access Journals (Sweden)

    Mujiyo

    2016-06-01

    Full Text Available Sustainability of paddy field becomes the main concern as the media of biomass production, thus it is needed a datum and information about land characteristics to find out its degradation. Mapping of soil degradation potency in paddy field is an identification of initial soil condition to discover the land degradation potency. Mapping was done by overlaying map of soil, slope, rainfall and land use with standard procedures to obtain its value and status of soil degradation potency. Area mapping is an effective land for biomass production (natural forest, mixed farm, savanna, paddy field, shrub and dry field with approximately 43,291.00 hectares (ha in Sidoharjo, Girimarto, Jatipurno, Jatisrono, Jatiroto, Tirtomoyo, Nguntoronadi and Ngadirojo District. The result shows that soil degradation potency (SDP in Districts of Sidoharjo, Girimarto, Jatipurno, Jatisrono, Jatiroto, Tirtomoyo, Nguntoronadi and Ngadirojo are very low, low (DP II 20,702.47 ha (47.82%, moderate (DP III 15,823.80 ha (36,55% and high (DP IV 6,764.73 ha (15.63%. Paddy field covered 22,036.26 ha or about 50.90% of all area as effective biomass production, its SDP considers as low (DP II 16,021.04 ha (37.01% and moderate (DP III 6,015.22 ha (13,89%. Paddy field has a low SDP because it is commonly lies on flat area and conservation method by the farmer is maintaining the paddy bund and terrace. This study needs an advanced study to identify actual SDP through detail verification in the field, and also support by soil sample analysis in the laboratory.

  13. 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.

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

    DEFF Research Database (Denmark)

    Beucher, Amélie; Boman, A; Mattbäck, S

    impact through the resulting corrosion of concrete and steel infrastructures, or their poor geotechnical qualities.Mapping acid sulfate soil occurrence thus constitutes a key step to target the strategic areas for subsequent environmental risk management and mitigation. Conventional mapping (i.e. soil...

  15. A new look at soil phenoforms – Definition, identification, mapping

    NARCIS (Netherlands)

    Rossiter, David; Bouma, J.

    2018-01-01

    The soil genoform vs. soil phenoform distinction was suggested twenty years ago by Droogers and Bouma to recognize management-induced differences among pedons with the same long-term pedogenesis and included in the same soil map unit, these changes being sufficient to cause

  16. Constellation Map: Downstream visualization and interpretation of gene set enrichment results [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Yan Tan

    2015-06-01

    Full Text Available Summary: Gene set enrichment analysis (GSEA approaches are widely used to identify coordinately regulated genes associated with phenotypes of interest. Here, we present Constellation Map, a tool to visualize and interpret the results when enrichment analyses yield a long list of significantly enriched gene sets. Constellation Map identifies commonalities that explain the enrichment of multiple top-scoring gene sets and maps the relationships between them. Constellation Map can help investigators take full advantage of GSEA and facilitates the biological interpretation of enrichment results. Availability: Constellation Map is freely available as a GenePattern module at http://www.genepattern.org.

  17. 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

  18. 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

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

    Indian Academy of Sciences (India)

    unscientific management practices followed in the hilly regions. .... country. In the absence of large scale or detail map, researcher use the small scale of soil map prepared ..... tural development. .... mapping: An introductory perspective; Dev.

  20. 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...... the storehouse of existing legacy soils data along with geographic information and a range of covariates. A range of modeling techniques is used dependant on the complexity of the background soil survey information. The key soil properties that would be most useful to the modeling community and other users are...... of soil property values throughout the depth of each profile. Maps have been produced at the country level in the Australia, Canada, Denmark, Nigeria, South Korea and the US and work is on-going in many other parts of the world....

  1. 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

  2. 3D-Digital soil property mapping by geoadditive models

    Science.gov (United States)

    Papritz, Andreas

    2016-04-01

    In many digital soil mapping (DSM) applications, soil properties must be predicted not only for a single but for multiple soil depth intervals. In the GlobalSoilMap project, as an example, predictions are computed for the 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, 100-200 cm depth intervals (Arrouays et al., 2014). Legacy soil data are often used for DSM. It is common for such datasets that soil properties were measured for soil horizons or for layers at varying soil depth and with non-constant thickness (support). This poses problems for DSM: One strategy is to harmonize the soil data to common depth prior to the analyses (e.g. Bishop et al., 1999) and conduct the statistical analyses for each depth interval independently. The disadvantage of this approach is that the predictions for different depths are computed independently from each other so that the predicted depth profiles may be unrealistic. Furthermore, the error induced by the harmonization to common depth is ignored in this approach (Orton et al. 2016). A better strategy is therefore to process all soil data jointly without prior harmonization by a 3D-analysis that takes soil depth and geographical position explicitly into account. Usually, the non-constant support of the data is then ignored, but Orton et al. (2016) presented recently a geostatistical approach that accounts for non-constant support of soil data and relies on restricted maximum likelihood estimation (REML) of a linear geostatistical model with a separable, heteroscedastic, zonal anisotropic auto-covariance function and area-to-point kriging (Kyriakidis, 2004.) Although this model is theoretically coherent and elegant, estimating its many parameters by REML and selecting covariates for the spatial mean function is a formidable task. A simpler approach might be to use geoadditive models (Kammann and Wand, 2003; Wand, 2003) for 3D-analyses of soil data. geoAM extend the scope of the linear model with spatially correlated errors to

  3. 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

    Full Text Available Soil functions and their impact on health, economy, and the environment are evident at the macro scale but determined at the micro scale, based on interactions between soil micro-architecture and the transport and transformation processes occurring in the soil infrastructure comprising pore and particle networks and at their interfaces. Soil structure formation and its resilience to disturbance are highly dynamic features affected by management (energy input, moisture (matric potential, and solids composition and complexation (organic matter and clay interactions. In this paper we review and put into perspective preliminary results of the newly started research program "Soil-it-is" on functional soil architecture. To identify and quantify biophysical constraints on soil structure changes and resilience, we claim that new approaches are needed to better interpret processes and parameters measured at the bulk soil scale and their links to the seemingly chaotic soil inner space behavior at the micro scale. As a first step, we revisit the soil matrix (solids phase and pore system (water and air phases, constituting the complementary and interactive networks of soil infrastructure. For a field-pair with contrasting soil management, we suggest new ways of data analysis on measured soil-gas transport parameters at different moisture conditions to evaluate controls of soil matrix and pore network formation. Results imply that some soils form sponge-like pore networks (mostly healthy soils in terms of agricultural and environmental functions, while other soils form pipe-like structures (agriculturally poorly functioning soils, with the difference related to both complexation of organic matter and degradation of soil structure. The recently presented Dexter et al. (2008 threshold (ratio of clay to organic carbon of 10 kg kg−1 is found to be a promising constraint for a soil's ability to maintain or regenerate functional structure. Next

  4. 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 ...

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

    Science.gov (United States)

    Westin, F. C.

    1974-01-01

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

  6. A soil map of a large watershed in China: applying digital soil mapping in a data sparse region

    Science.gov (United States)

    Barthold, F.; Blank, B.; Wiesmeier, M.; Breuer, L.; Frede, H.-G.

    2009-04-01

    Prediction of soil classes in data sparse regions is a major research challenge. With the advent of machine learning the possibilities to spatially predict soil classes have increased tremendously and given birth to new possibilities in soil mapping. Digital soil mapping is a research field that has been established during the last decades and has been accepted widely. We now need to develop tools to reduce the uncertainty in soil predictions. This is especially challenging in data sparse regions. One approach to do this is to implement soil taxonomic distance as a classification error criterion in classification and regression trees (CART) as suggested by Minasny et al. (Geoderma 142 (2007) 285-293). This approach assumes that the classification error should be larger between soils that are more dissimilar, i.e. differ in a larger number of soil properties, and smaller between more similar soils. Our study area is the Xilin River Basin, which is located in central Inner Mongolia in China. It is characterized by semi arid climate conditions and is representative for the natural occurring steppe ecosystem. The study area comprises 3600 km2. We applied a random, stratified sampling design after McKenzie and Ryan (Geoderma 89 (1999) 67-94) with landuse and topography as stratifying variables. We defined 10 sampling classes, from each class 14 replicates were randomly drawn and sampled. The dataset was split into 100 soil profiles for training and 40 soil profiles for validation. We then applied classification and regression trees (CART) to quantify the relationships between soil classes and environmental covariates. The classification tree explained 75.5% of the variance with land use and geology as most important predictor variables. Among the 8 soil classes that we predicted, the Kastanozems cover most of the area. They are predominantly found in steppe areas. However, even some of the soils at sand dune sites, which were thought to show only little soil formation

  7. Mapping Soil Carbon in the Yukon Kuskokwim River Delta Alaska

    Science.gov (United States)

    Natali, S.; Fiske, G.; Schade, J. D.; Mann, P. J.; Holmes, R. M.; Ludwig, S.; Melton, S.; Sae-lim, N.; Jardine, L. E.; Navarro-Perez, E.

    2017-12-01

    Arctic river deltas are hotspots for carbon storage, occupying 10% of carbon stored in arctic permafrost. The Yukon Kuskokwim (YK) Delta, Alaska is located in the lower latitudinal range of the northern permafrost region in an area of relatively warm permafrost that is particularly vulnerable to warming climate. Active layer depths range from 50 cm on peat plateaus to >100 cm in wetland and aquatic ecosystems. The size of the soil organic carbon pool and vulnerability of the carbon in the YK Delta is a major unknown and is critically important as climate warming and increasing fire frequency may make this carbon vulnerable to transport to aquatic and marine systems and the atmosphere. To characterize the size and distribution of soil carbon pools in the YK Delta, we mapped the land cover of a 1910 km2 watershed located in a region of the YK Delta that was impacted by fire in 2015. The map product was the result of an unsupervised classification using the Weka K Means clustering algorithm implemented in Google's Earth Engine. Inputs to the classification were Worldview2 resolution optical imagery (1m), Arctic DEM (5m), and Sentinel 2 level 1C multispectral imagery, including NDVI, (10 m). We collected 100 soil cores (0-30 cm) from sites of different land cover and landscape position, including moist and dry peat plateaus, high and low intensity burned plateaus, fens, and drained lakes; 13 lake sediment cores (0-50 cm); and 20 surface permafrost cores (to 100 cm) from burned and unburned peat plateaus. Active layer and permafrost soils were analyzed for organic matter content, soil moisture content, and carbon and nitrogen pools (30 and 100 cm). Soil carbon content varied across the landscape; average carbon content values for lake sediments were 12% (5- 17% range), fens 26% (9-44%), unburned peat plateaus 41% (34-44%), burned peat plateaus 19% (7-34%). These values will be used to estimate soil carbon pools, which will be applied to the spatial extent of each

  8. Use of Landsat data in soil and agricultural land use studies

    Science.gov (United States)

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

    1980-01-01

    This paper describes how the synoptic, multispectral, and temporal characteristics of Landsat can be used to locate Soil Association boundaries. Then, using these techniques we describe how a low intensity soil survey was conducted and how some interpretive maps were developed from this. Finally, we describe how soil suitability and land use interpretations were made to aid in defining Agrophysical units used in crop inventories.

  9. 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

  10. 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

  11. Soil Salinity Mapping in Everglades National Park Using Remote Sensing Techniques

    Science.gov (United States)

    Su, H.; Khadim, F. K.; Blankenship, J.; Sobhan, K.

    2017-12-01

    The South Florida Everglades is a vast subtropical wetland with a globally unique hydrology and ecology, and it is designated as an International Biosphere Reserve and a Wetland of International Importance. Everglades National Park (ENP) is a hydro-ecologically enriched wetland with varying salinity contents, which is a concern for terrestrial ecosystem balance and sustainability. As such, in this study, time series soil salinity mapping was carried out for the ENP area. The mapping first entailed a maximum likelihood classification of seven land cover classes for the ENP area—namely mangrove forest, mangrove scrub, low-density forest, sawgrass, prairies and marshes, barren lands with woodland hammock and water—for the years 1996, 2000, 2006, 2010 and 2015. The classifications for 1996-2010 yielded accuracies of 82%-94%, and the 2015 classification was supported through ground truthing. Afterwards, electric conductivity (EC) tolerance thresholds for each vegetation class were established,which yielded soil salinity maps comprising four soil salinity classes—i.e., the non- (EC = 0 2 dS/m), low- (EC = 2 4 dS/m), moderate- (EC = 4 8 dS/m) and high-saline (EC = >8 dS/m) areas. The soil salinity maps visualized the spatial distribution of soil salinity with no significant temporal variations. The innovative approach of "land cover identification to salinity estimation" used in the study is pragmatic and application oriented, and the study upshots are also useful, considering the diversifying ecological context of the ENP area.

  12. 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 techn...... the prediction in OKst compared with that in OK, whereas RT showed the lowest performance of all (R2 = 0.52; RMSE = 0.52; and RPD = 1.17). We found RKrr to be an effective prediction method and recommend this method for any future soil mapping activities in Denmark....... technique at a given site has always been a major issue in all soil mapping applications. We studied the prediction performance of ordinary kriging (OK), stratified OK (OKst), regression trees (RT), and rule-based regression kriging (RKrr) for digital mapping of soil clay content at 30.4-m grid size using 6...

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

    Science.gov (United States)

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

    1974-01-01

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

  14. Morphological Interpretation of Reflectance Spectrum (MIRS using libraries looking towards soil classification

    Directory of Open Access Journals (Sweden)

    José Alexandre Melo Demattê

    2014-12-01

    Full Text Available The search for tools to perform soil surveying faster and cheaper has led to the development of technological innovations such as remote sensing (RS and the so-called spectral libraries in recent years. However, there are no studies which collate all the RS background to demonstrate how to use this technology for soil classification. The present study aims to describe a simple method of how to classify soils by the morphology of spectra associated with a quantitative view (400-2,500 nm. For this, we constructed three spectral libraries: (i one for quantitative model performance; (ii a second to function as the spectral patterns; and (iii a third to serve as a validation stage. All samples had their chemical and granulometric attributes determined by laboratory analysis and prediction models were created based on soil spectra. The system is based on seven steps summarized as follows: i interpretation of the spectral curve intensity; ii observation of the general shape of curves; iii evaluation of absorption features; iv comparison of spectral curves between the same profile horizons; v quantification of soil attributes by spectral library models; vi comparison of a pre-existent spectral library with unknown profile spectra; vii most probable soil classification. A soil cannot be classified from one spectral curve alone. The behavior between the horizons of a profile, however, was correlated with its classification. In fact, the validation showed 85 % accuracy between the Morphological Interpretation of Reflectance Spectrum (MIRS method and the traditional classification, showing the importance and potential of a combination of descriptive and quantitative evaluations.

  15. 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.

  16. 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.

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

    Science.gov (United States)

    Ilieva, Diliana; Malinov, Ilia

    2014-05-01

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

  18. The evolution of mapping habitat for northern spotted owls (Strix occidentalis caurina): A comparison of photo-interpreted, Landsat-based, and lidar-based habitat maps

    Science.gov (United States)

    Ackers, Steven H.; Davis, Raymond J.; Olsen, K.; Dugger, Catherine

    2015-01-01

    Wildlife habitat mapping has evolved at a rapid pace over the last few decades. Beginning with simple, often subjective, hand-drawn maps, habitat mapping now involves complex species distribution models (SDMs) using mapped predictor variables derived from remotely sensed data. For species that inhabit large geographic areas, remote sensing technology is often essential for producing range wide maps. Habitat monitoring for northern spotted owls (Strix occidentalis caurina), whose geographic covers about 23 million ha, is based on SDMs that use Landsat Thematic Mapper imagery to create forest vegetation data layers using gradient nearest neighbor (GNN) methods. Vegetation data layers derived from GNN are modeled relationships between forest inventory plot data, climate and topographic data, and the spectral signatures acquired by the satellite. When used as predictor variables for SDMs, there is some transference of the GNN modeling error to the final habitat map.Recent increases in the use of light detection and ranging (lidar) data, coupled with the need to produce spatially accurate and detailed forest vegetation maps have spurred interest in its use for SDMs and habitat mapping. Instead of modeling predictor variables from remotely sensed spectral data, lidar provides direct measurements of vegetation height for use in SDMs. We expect a SDM habitat map produced from directly measured predictor variables to be more accurate than one produced from modeled predictors.We used maximum entropy (Maxent) SDM modeling software to compare predictive performance and estimates of habitat area between Landsat-based and lidar-based northern spotted owl SDMs and habitat maps. We explored the differences and similarities between these maps, and to a pre-existing aerial photo-interpreted habitat map produced by local wildlife biologists. The lidar-based map had the highest predictive performance based on 10 bootstrapped replicate models (AUC = 0.809 ± 0.011), but the

  19. 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.

  20. 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)

  1. Soil-Web: An online soil survey for California, Arizona, and Nevada

    Science.gov (United States)

    Beaudette, D. E.; O'Geen, A. T.

    2009-10-01

    Digital soil survey products represent one of the largest and most comprehensive inventories of soils information currently available. The complex structure of these databases, intensive use of codes and scientific jargon make it difficult for non-specialists to utilize digital soil survey resources. A project was initiated to construct a web-based interface to digital soil survey products (STATSGO and SSURGO) for California, Arizona, and Nevada that would be accessible to the general public. A collection of mature, open source applications (including Mapserver, PostGIS and Apache Web Server) were used as a framework to support data storage, querying, map composition, data presentation, and contextual links to related materials. Application logic was written in the PHP language to "glue" together the many components of an online soil survey. A comprehensive website ( http://casoilresource.lawr.ucdavis.edu/map) was created to facilitate access to digital soil survey databases through several interfaces including: interactive map, Google Earth and HTTP-based application programming interface (API). Each soil polygon is linked to a map unit summary page, which includes links to soil component summary pages. The most commonly used soil properties, land interpretations and ratings are presented. Graphical and tabular summaries of soil profile information are dynamically created, and aid with rapid assessment of key soil properties. Quick links to official series descriptions (OSD) and other such information are presented. All terminology is linked back to the USDA-NRCS Soil Survey Handbook which contains extended definitions. The Google Earth interface to Soil-Web can be used to explore soils information in three dimensions. A flexible web API was implemented to allow advanced users of soils information to access our website via simple web page requests. Soil-Web has been successfully used in soil science curriculum, outreach activities, and current research projects

  2. Mapping soil erosion risk in Serra de Grândola (Portugal)

    Science.gov (United States)

    Neto Paixão, H. M.; Granja Martins, F. M.; Zavala, L. M.; Jordán, A.; Bellinfante, N.

    2012-04-01

    Geomorphological processes can pose environmental risks to people and economical activities. Information and a better knowledge of the genesis of these processes is important for environmental planning, since it allows to model, quantify and classify risks, what can mitigate the threats. The objective of this research is to assess the soil erosion risk in Serra de Grândola, which is a north-south oriented mountain ridge with an altitude of 383 m, located in southwest of Alentejo (southern Portugal). The study area is 675 km2, including the councils of Grândola, Santiago do Cacém and Sines. The process for mapping of erosive status was based on the guidelines for measuring and mapping the processes of erosion of coastal areas of the Mediterranean proposed by PAP/RAC (1997), developed and later modified by other authors in different areas. This method is based on the application of a geographic information system that integrates different types of spatial information inserted into a digital terrain model and in their derivative models. Erosive status are classified using information from soil erodibility, slope, land use and vegetation cover. The rainfall erosivity map was obtained using the modified Fournier index, calculated from the mean monthly rainfall, as recorded in 30 meteorological stations with influence in the study area. Finally, the soil erosion risk map was designed by ovelaying the erosive status map and the rainfall erosivity map.

  3. Soil pH Mapping with an On-The-Go Sensor

    OpenAIRE

    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 ManagerTM, 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 ManagerTM under ...

  4. 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

  5. Mapping Agricultural Frozen Soil on the Watershed Scale Using Remote Sensing Data

    International Nuclear Information System (INIS)

    Khaldoune, J; Bernier, M; Van Bochove, E; Nolin, M.C

    2011-01-01

    This paper presents an empirical model for classifying frozen/unfrozen soils in the entire Bras d Henri River watershed (167 km 2 ) near Quebec City (Quebec, Canada). It was developed to produce frozen soil maps under snow cover using RADARSAT-1 fine mode images and in situ data during three winters. Twelve RADARSAT-1 images were analyzed from fall 2003 to spring 2006 to discern the intra- and inter annual variability of frozen soil characteristics. Regression models were developed for each soil group (parent material-drainage-soil type) and land cover to establish a threshold for frozen soil from the backscattering coefficients (HH polarization). Tilled fields showed higher backscattering signal (+3 db) than the untilled fields. The overall classification accuracy was 87% for frozen soils and 94% for unfrozen soils. With respect to land use, that is, tilled versus untilled fields, an overall accuracy of 89% was obtained for the tilled fields and 92% for the untilled fields. Results show that this new mapping approach using RADARSAT-1 images can provide estimates of surface soil status (frozen/unfrozen) at the watershed scale in agricultural areas.

  6. Use of Airborne Hyperspectral Imagery to Map Soil Properties in Tilled Agricultural Fields

    International Nuclear Information System (INIS)

    Hively, W.D; McCarty, G.W; Reeves, J.B; Lang, M.W; Oesterling, R.A; Delwiche, S.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 R 2 >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 x 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.

  7. 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.

  8. Continuous soil maps - a fuzzy set approach to bridge the gap between aggregation levels of process and distribution models

    NARCIS (Netherlands)

    Gruijter, de J.J.; Walvoort, D.J.J.; Gaans, van P.F.M.

    1997-01-01

    Soil maps as multi-purpose models of spatial soil distribution have a much higher level of aggregation (map units) than the models of soil processes and land-use effects that need input from soil maps. This mismatch between aggregation levels is particularly detrimental in the context of precision

  9. Do We Need a New Definition of Soil?

    Science.gov (United States)

    Arnold, Richard W.; Brevik, Eric C.

    2014-05-01

    Effective communication is really desirable to better relate with politicians, an interested lay public, and others not involved in soil science. Soil survey programs are intended to help people understand how soils function in their landscapes to make ecosystems operate better without damaging the environment and to indicate different kinds of suitability for various purposes. The properties of soils as recognized, described, and mapped at detailed scales form the basis for developing diagnostics for a systematic taxonomy that enables scientists to interact with other. In the USA mapping done at scales of 1:15,840± made it possible to define and use so-called "soil series", initially as soil map units, but later as central concepts of a set of soils which could be segregated using phases to indicate important features, primarily for farming. Detailed soil surveys published using a standard format helps maintain uniformity across the country. Soil series are recognized as the basic units of soils within the evolving hierarchical soil taxonomy and diagnostic properties are defined, measured and used to update and modify the scientific classification. Concepts like soil quality and soil function are considered to be "attributes" and not basic properties of soils. They are the collective interpretation of the combination of properties thought to be relevant for communicating important aspects of using, managing, restoring, and protecting the lands of any locality, region, or country. A famous example in the US was the land capability system with classes and subclasses of suitability for agricultural land uses. An updated soil survey in California contains over 500 pages providing details about classes of 30 different functional soil classifications for 155 map units. Over the years soil extension agents were the interpreters of the science to the lay folks and could help them form mental pictures of soils and soil landscapes locally They were the early leaders of

  10. 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.

  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. 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

  13. 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

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

    DEFF Research Database (Denmark)

    Beucher, Amélie; Adhikari, Kabindra; 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....... In this study, a probability map for potential a.s. soil occurrence was constructed for thewetlands located in Jutland, Denmark (c. 6500 km2), using the digital soilmapping (DSM) approach. Among the variety of available DSM techniques, artificial neural networks (ANNs) were selected. More than 8000 existing...... 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...

  15. Alternate data sources for soil surveys on rangeland

    Science.gov (United States)

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

    1983-01-01

    Soil information is an essential theme in a digital information base for land management and resource monitoring, but public land management agencies seldom have detailed soil maps available for all of the area under their administration. Most of these agencies conduct soil surveys on a scheduled basis, but escalating costs and declining budgets are reducing the number of surveys that can be scheduled. Digital elevation and satellite spectral data are available or are obtainable for all areas in the continental United States and may be used as an aid to produce soils data. A study was conducted in the Grass Creek Resource Area in north-central Wyoming to assess the utility of incorporating digital elevation and Landsat data into an information base for soil survey and to evaluate the usefulness of these data as an input to an order-three soil survey. Slope-interval maps were produced from digital elevation data and topographic maps of three 7.5-minute quadrangle areas. These slope-interval maps were then overlaid on orthophotoquadrangles and used to produce photo-interpreted physiographic maps. These physiographic maps were digitized into a data base and used with Landsat multispectral scanner data to produce tabular summaries that describe each map polygon in terms of physiographic unit, slope, aspect, elevation, area, and spectral values. A good

  16. 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.

  17. 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

  18. Agroclimatic mapping of maize crop based on soil physical properties

    International Nuclear Information System (INIS)

    Dourado Neto, Durval; Sparovek, G.; Reichardt, K.; Timm, Luiz Carlos; Nielsen, D.R.

    2004-01-01

    With the purpose of estimating water deficit to forecast yield knowing productivity (potential yield), the water balance is useful tool to recommend maize exploration and to define the sowing date. The computation can be done for each region with the objective of mapping maize grain yield based on agro-climatic data and soil physical properties. Based on agro-climatic data, air temperature and solar radiation, a model was built to estimate the corn grain productivity (the energy conversion results in dry mass production). The carbon dioxide (CO 2 ) fixation by plants is related to gross carbohydrate (CH 2 O) production and solar radiation. The CO 2 assimilation by C4 plants depends on the photosynthetic active radiation and temperature. From agro-climatic data and soil physical properties, a map with region identification can be built for solar radiation, air temperature, rainfall, maize grain productivity and yield, potential and real evapo-transpiration and water deficit. The map allows to identify the agro-climatic and the soil physical restrictions. This procedure can be used in different spatial (farm to State) and temporal (daily to monthly data) scales. The statistical analysis allows to compare estimated and observed values in different situations to validate the model and to verify which scale is more appropriate

  19. 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.

  20. 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.

  1. 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...

  2. 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

  3. 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

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

    Science.gov (United States)

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

    2018-02-01

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

  5. 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...

  6. Mapping The Temporal and Spatial Variability of Soil Moisture Content Using Proximal Soil Sensing

    Science.gov (United States)

    Virgawati, S.; Mawardi, M.; Sutiarso, L.; Shibusawa, S.; Segah, H.; Kodaira, M.

    2018-05-01

    In studies related to soil optical properties, it has been proven that visual and NIR soil spectral response can predict soil moisture content (SMC) using proper data analysis techniques. SMC is one of the most important soil properties influencing most physical, chemical, and biological soil processes. The problem is how to provide reliable, fast and inexpensive information of SMC in the subsurface from numerous soil samples and repeated measurement. The use of spectroscopy technology has emerged as a rapid and low-cost tool for extensive investigation of soil properties. The objective of this research was to develop calibration models based on laboratory Vis-NIR spectroscopy to estimate the SMC at four different growth stages of the soybean crop in Yogyakarta Province. An ASD Field-spectrophotoradiometer was used to measure the reflectance of soil samples. The partial least square regression (PLSR) was performed to establish the relationship between the SMC with Vis-NIR soil reflectance spectra. The selected calibration model was used to predict the new samples of SMC. The temporal and spatial variability of SMC was performed in digital maps. The results revealed that the calibration model was excellent for SMC prediction. Vis-NIR spectroscopy was a reliable tool for the prediction of SMC.

  7. 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

  8. 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

    Soil texture which is spatially variable in nature, is an important soil physical property that governs most physical, chemical, biological, and hydrological processes in soils. Detailed information on soil texture variability both in vertical and lateral dimensions is crucial for proper crop...... and land management and environmental studies, especially in Denmark where mechanized agriculture covers two thirds of the land area. We modeled the continuous depth function of texture distribution from 1958 Danish soil profiles (up to a 2-m depth) using equal-area quadratic splines and predicted clay......, 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...

  9. Mapping of depleted uranium with in situ spectrometry and soil samples

    International Nuclear Information System (INIS)

    Shebell, P.; Reginatto, M.; Monetti, M.; Faller, S.; Davis, L.

    1999-01-01

    Depleted uranium (DU) has been developed in the past two decades as a highly effective material for armor penetrating rounds and vehicle shielding. There is now a growing interest in the defense community to determine the presence and extent of DU contamination quickly and with a minimum amount of intrusive sampling. We report on a new approach using deconvolution techniques to quantitatively map DU contamination in surface soil. This approach combines data from soil samples with data from in situ gamma-ray spectrometry measurements to produce an accurate and detailed map of DU contamination. Results of a field survey at the Aberdeen Proving Ground are presented. (author)

  10. 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

  11. 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

  12. Self Organizing Maps to efficiently cluster and functionally interpret protein conformational ensembles

    Directory of Open Access Journals (Sweden)

    Fabio Stella

    2013-09-01

    Full Text Available An approach that combines Self-Organizing maps, hierarchical clustering and network components is presented, aimed at comparing protein conformational ensembles obtained from multiple Molecular Dynamic simulations. As a first result the original ensembles can be summarized by using only the representative conformations of the clusters obtained. In addition the network components analysis allows to discover and interpret the dynamic behavior of the conformations won by each neuron. The results showed the ability of this approach to efficiently derive a functional interpretation of the protein dynamics described by the original conformational ensemble, highlighting its potential as a support for protein engineering.

  13. Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects.

    Science.gov (United States)

    Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea

    2016-01-01

    Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Application of a very detailed soil survey method in viticultural zoning in Catalonia, Spain

    Directory of Open Access Journals (Sweden)

    Josep Miquel Ubalde

    2009-06-01

    Significance and impact of study: This study showed how very detailed soil maps, which can be difficult to interpret and put into practice, can be valorised as viticultural zoning maps by means of a simple methodology.

  19. 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

  20. 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.

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

    Science.gov (United States)

    Liu, Mingyue; Du, Baojia; Zhang, Bai

    2018-01-01

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

  2. 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

  3. Soil Erosion Risk Map based on irregularity of the vegetative activity

    Science.gov (United States)

    Saa-Requejo, Antonio; Tarquis, Ana Maria; Martín-Sotoca, Juan J.; Valencia, Jose L.; Gobin, Anne; Rodriguez-Sinobas, Leonor

    2016-04-01

    Because of the difficulties to build on both daily rainfall and base shorter time, we explored the possibilities of building indexes based on land cover, which also provide us the opportunity to evaluate their evolution over time. We consider the Fournier index (Fournier, 1960) which is used to assess the rainfall erosivity based on monthly rainfall, alternatively to use of the rainfall intensity in time bases under one hour (eg., van der Knijff et al., 1999; Shamshad et al, 2008). This index can also be interpreted as an index of irregularity and representing a ratio between maximum monthly precipitation and annual rainfall. We propose to calculate this irregularity in terms of irregularity of the vegetative activity. This activity is related to precipitation, but also with the availability of water in the soil reservoir and land use. Therefore, we propose a kind of Fournier index on the effective use of water, which is also closely related to variations in infiltration. Higher is the presence of vegetation higher is the effective use of water. For this "modified Fourier index" we used the NDVI (Normalized Difference Vegetation Index) as index of available vegetative activity, which is widely reported in the literature (Jensen, 2000). Initial calculations have been done with MODIS 500 x 500 m satellite data. The selected area was Cega-Eresma-Adaja subbasin during the period from 2009 to 2012. We selected 8 days composite images product. The calculation of the valid values to eliminate areas with clouds or snow is performed according to the criteria of Martinez Sotoca (2014), ie with a Saturation (based on HSL color model) greater or equal to 0.15. Then, an average of these values was estimated to represent each month of the year. The results are very interesting when we compare Modified Fournier Index on NDVIs with the map of potential soil loss. We have found surprisingly similar patterns and practical equivalence between several classes. Therefore, the Modified

  4. Infra Red Aerial Photograph Interpretation for Soil Erosion at Wuryantoro, Wonogiri

    Directory of Open Access Journals (Sweden)

    S Suharjo

    2016-07-01

    Full Text Available Collecting data of soil erosion hazard terrestrially needs much time, high cost, and large energy. Therefore it is needed appropriate technology in addition to terrestrially decreasing necessity of time, cost and energy. Aerial photograph is picture of earth surface, which shape and place similar to condition on earth surface. Using aerial photograph in this research is expected to be able to take account for erosion factors. This research is conducted in Kecamatan Wuryantoro Kabupaten Wonogiri. Research method that used is aerial photograph interpretation with land unit approach. Amounts of soil lost are approached with USLE formula. Aerial photograph that used in this research is aerial photograph coloured infrared with 1:10.000 in scale and 1991 in year of taking photography. The result shows that using aerial photograph is very useful in supporting soil erosion rate calculation. Erosion rate at research area is 0.0968 ton/ha/year to 100.4344 ton/ha/year. This number is included in class of light erosion hazard (

  5. The UK Soil Observatory (UKSO) and mySoil app: crowdsourcing and disseminating soil information.

    Science.gov (United States)

    Robinson, David; Bell, Patrick; Emmett, Bridget; Panagos, Panos; Lawley, Russell; Shelley, Wayne

    2017-04-01

    Digital technologies in terms of web based data portals and mobiles apps offer a new way to provide both information to the public, and to engage the public in becoming involved in contributing to the effort of collecting data through crowdsourcing. We are part of the Landpotential.org consortium which is a global partnership committed to developing and supporting the adoption of freely available technology and tools for sustainable land use management, monitoring, and connecting people across the globe. The mySoil app was launched in 2012 and is an example of a free mobile application downloadable from iTunes and Google Play. It serves as a gateway tool to raise interest in, and awareness of, soils. It currently has over 50,000 dedicated users and has crowd sourced more than 4000 data records. Recent developments have expanded the coverage of mySoil from the United Kingdom to Europe, introduced a new user interface and provided language capability, while the UKSO displays the crowd-sourced records from across the globe. We are now trying to identify which industry, education and citizen sectors are using these platforms and how they can be improved. Please help us by providing feedback or taking the survey on the UKSO website. www.UKSO.org The UKSO is a collaboration between major UK soil-data holders to provide maps, spatial data and real-time temporal data from observing platforms such as the UK soil moisture network. Both UKSO and mySoil have crowdsourcing capability and are slowly building global citizen science maps of soil properties such as pH and texture. Whilst these data can't replace professional monitoring data, the information they provide both stimulates public interest and can act as 'soft data' that can help support the interpretation of monitoring data, or guide future monitoring, identifying areas that don't correspond with current analysis. In addition, soft data can be used to map soils with machine learning approaches, such as SoilGrids.

  6. 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.

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

    Science.gov (United States)

    Loonstra, Eddie; van Egmond, Fenny

    2010-05-01

    The Mole is a passive gamma ray soil sensor system. It is designed for the mobile collection of radioactive energy stemming from soil. As the system is passive, it only measures energy that reaches the surface of soil. In general, this energy comes from upto 30 to 40 cm deep, which can be considered topsoil. The gathered energy spectra are logged every second, are processed with the method of Full Spectrum Analysis. This method uses all available spectral data and processes it with a Chi square optimalisation using a set of standard spectra into individual nuclide point data. A standard spectrum is the measured full spectrum of a specific detector derived when exposed to 1 Bq/kg of a nuclide. With this method the outcome of the surveys become quantitative.The outcome of a field survey with the Mole results in a data file containing point information of position, Total Counts and the decay products of 232Th, 238U, 40K and 137Cs. Five elements are therefor available for the modelling of soil properties. There are several ways for the modelling of soil properties with sensor derived gamma ray data. The Mole generates ratio scale output. For modelling a quantitative deterministic approach is used based on sample locations. This process is called fingerprinting. Fingerprinting is a comparison of the concentration of the radioactive trace elements and the lab results (pH, clay content, etc.) by regression analysis. This results in a mathematical formula describing the relationship between a dependent and independent property. The results of the sensor readings are interpolated into a nuclide map with GIS software. With the derived formula a soil property map is composed. The principle of fingerprinting can be applied on large geographical areas for physical soil properties such as clay, loam or sand (50 micron), grain size and organic matter. Collected sample data of previous field surveys within the same region can be used for the prediction of soil properties elsewhere

  8. 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.

  9. Interpreting predictive maps of disease: highlighting the pitfalls of distribution models in epidemiology

    Directory of Open Access Journals (Sweden)

    Nicola A. Wardrop

    2014-11-01

    Full Text Available The application of spatial modelling to epidemiology has increased significantly over the past decade, delivering enhanced understanding of the environmental and climatic factors affecting disease distributions and providing spatially continuous representations of disease risk (predictive maps. These outputs provide significant information for disease control programmes, allowing spatial targeting and tailored interventions. However, several factors (e.g. sampling protocols or temporal disease spread can influence predictive mapping outputs. This paper proposes a conceptual framework which defines several scenarios and their potential impact on resulting predictive outputs, using simulated data to provide an exemplar. It is vital that researchers recognise these scenarios and their influence on predictive models and their outputs, as a failure to do so may lead to inaccurate interpretation of predictive maps. As long as these considerations are kept in mind, predictive mapping will continue to contribute significantly to epidemiological research and disease control planning.

  10. Hydropodelogy From the Pedon to the Landscape: Challenges and Accomplishments in the National Cooperative Soil Survey

    Science.gov (United States)

    Hammer, D.; Richardson, J.; Hempel, J.; Market, P.

    2005-12-01

    American pedology has focused on the National Cooperative Soil Survey. Primary responsibility rests with the U.S. Department of Agriculture. The primary goals, are legislatively mandated, are to map the country's soils, make interpretations, provide information to clients, maintain and market the soil survey. The first goal is near completion and focus is shifting to the other three. Concomitantly, American pedological science is being impacted by several conditions: technological advances; land use changes at unprecedented scales and magnitudes; a burgeoning population increasingly "separated" from the land; and a major emphasis in universities upon biological ("life") sciences at the DNA scale - as if soil, nutrients and water are not life essentials. Effects of the Flood of 1993 and Hurricane Katrina suggest that humans do not understand earth/climate interactions, particularly climatic extremes. Pedologists know the focus on soil classification and mapping was at the expense of understanding processes. Hydropedology is a holistic approach to understanding soil and geomorphic process in order to predict the impacts of perturbations. Water movement on and in the soil is the primary mechanism of distributing and altering sediments and chemicals (pedogenesis), and depends for its success upon understanding that the soil profile is the record of developmental history at that landscape site. Hydropedologists believe soil scientists can use pedons (point data) from appropriate locations from flownets in complex landscapes to extrapolate processes. This is the "pedotransfer function" concept. Technological advances are coupled with the existing soil survey information to create important soil-landscape interpretations at a variety of scales. Early results have been very successful. Quantification of soil systems can be classified broadly into three categories; hard data, soft data and tacit knowledge. "Hard data" are measured numbers, and include such attributes as p

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

    DEFF Research Database (Denmark)

    Beucher, Amélie; Peng, Yi; Knadel, Maria

    , including geology, landscape type and terrain parameters. Visible-Near-Infrared (Vis-NIR) spectroscopy constitutes a rapid and cheap alternative to soil analysis, and was successfully utilized for the prediction of soil chemical, physical and biological properties. In particular, the Vis-NIR spectra contain......Releasing acidity and metals into watercourses, acid sulfate soils represent a critical environmental problem worldwide. Identifying the spatial distribution of these soils enables to target the strategic areas for risk management. In Denmark, the occurrence of acid sulfate soils was first studied...... during the 1980’s through conventional mapping (i.e. soil sampling and the subsequent determination of pH at the time of sampling and after incubation, the pyrite content and the acid-neutralizing capacity). Since acid sulfate soils mostly occur in wetlands, the survey specifically targeted these areas...

  12. The history of soil erosion: Interpreting historical sources, buried soils and colluvial sediments as archives of past soil erosion and human-environment interactions in the Longue Durée

    Science.gov (United States)

    Dotterweich, Markus

    2015-04-01

    Soil erosion threatens the environment and the sustainability of agricultural practices since the earliest societies started modifying their natural environment in the Neolithic. Almost all farming-based cultures in the world, from large civilizations to peasant groups on little islands, have suffered from soil erosion by water. The amounts of soil erosion varied largely through time and space, and extreme events have left a wide variety of imprints on the landscape over millennia. Eroded hillslopes and gullies, deposited sediments in sinks like lakes, footslopes, valleys, floodplains, and river deltas are geomorphic legacies that have been linked to changes in land use and climate by many studies during the last decades. However, a standardized analysis and interpretation of these geomorphic legacies is problematic because of the variety of methodological approaches and the nonlinearity between soil erosion, climate, and land use. Cascading effects, land use structures, soil management, soil conservation strategies, and long-term system changes have produced different signals over time. Historical records are crucial and an invaluable source to provide alternative proxies about soil erosion in the past. Direct observations of individual soil erosion events may restrict the deposition of a distinct sediment package to a certain time span. They also expand the range of alternative interpretations, particularly with respect to the long-term effects of soil erosion to ecosystem services and socioeconomic processes. However, historical records also need critical analyses regarding their origin, intention, and quality. They were often created in the context of personal interests or political issues rather than being based on scientific facts; and it is often unclear if they represent certain events, narratives, or vague assumptions. This presentation will present and discuss examples of geomorphic evidences and historical records of past soil erosion for the deciphering

  13. Soil process-oriented modelling of within-field variability based on high-resolution 3D soil type distribution maps.

    Science.gov (United States)

    Bönecke, Eric; Lück, Erika; Gründling, Ralf; Rühlmann, Jörg; Franko, Uwe

    2016-04-01

    Today, the knowledge of within-field variability is essential for numerous purposes, including practical issues, such as precision and sustainable soil management. Therefore, process-oriented soil models have been applied for a considerable time to answer question of spatial soil nutrient and water dynamics, although, they can only be as consistent as their variation and resolution of soil input data. Traditional approaches, describe distribution of soil types, soil texture or other soil properties for greater soil units through generalised point information, e.g. from classical soil survey maps. Those simplifications are known to be afflicted with large uncertainties. Varying soil, crop or yield conditions are detected even within such homogenised soil units. However, recent advances of non-invasive soil survey and on-the-go monitoring techniques, made it possible to obtain vertical and horizontal dense information (3D) about various soil properties, particularly soil texture distribution which serves as an essential soil key variable affecting various other soil properties. Thus, in this study we based our simulations on detailed 3D soil type distribution (STD) maps (4x4 m) to adjacently built-up sufficient informative soil profiles including various soil physical and chemical properties. Our estimates of spatial STD are based on high-resolution lateral and vertical changes of electrical resistivity (ER), detected by a relatively new multi-sensor on-the-go ER monitoring device. We performed an algorithm including fuzzy-c-mean (FCM) logic and traditional soil classification to estimate STD from those inverted and layer-wise available ER data. STD is then used as key input parameter for our carbon, nitrogen and water transport model. We identified Pedological horizon depths and inferred hydrological soil variables (field capacity, permanent wilting point) from pedotransferfunctions (PTF) for each horizon. Furthermore, the spatial distribution of soil organic carbon

  14. Soil map, area and volume calculations in Orrmyrberget catchment basin at Gideaa, Northern Sweden

    International Nuclear Information System (INIS)

    Ittner, T.; Tammela, P.T.; Gustafsson, E.

    1991-06-01

    Fallout studies in the Gideaa study site after the Chernobyl fallout in 1986, has come to the point that a more exact surface mapping of the studied catchment basin is needed. This surface mapping is mainly made for area calculations of different soil types within the study site. The mapping focus on the surface, as the study concerns fallout redistribution and it is extended to also include materials down to a depth of 0.5 meter. Volume calculations are made for the various soil materials within the top 0.5 m. These volume and area calculations will then be used in the modelling of the migration and redistribution of the fallout radionuclides within the studied catchment basin. (au)

  15. Spatial soil information in South Africa: Situational analysis, limitations and challenges

    Directory of Open Access Journals (Sweden)

    Garry Paterson

    2015-05-01

    Full Text Available Soil information is vital for a range of purposes; however, soils vary greatly over short distances, making accurate soil data difficult to obtain. Soil surveys were first carried out in the 1920s, and the first national soil map was produced in 1940. Several regional studies were done in the 1960s, with the national Land Type Survey completed in 2002. Subsequently, the transfer of soil data to digital format has allowed a wide range of interpretations, but many data are still not freely available as they are held by a number of different bodies. The need for soil data is rapidly expanding to a range of fields, including health, food security, hydrological modelling and climate change. Fortunately, advances have been made in fields such as digital soil mapping, which enables the soil surveyors to address the need. The South African Soil Science fraternity will have to adapt to the changing environment in order to comply with the growing demands for data. At a recent Soil Information Workshop, soil scientists from government, academia and industry met to concentrate efforts in meeting the current and future soil data needs. The priorities identified included: interdisciplinary collaboration; expansion of the current national soil database with advanced data acquisition, manipulation, interpretation and countrywide dissemination facilities; and policy and human capital development in newly emerging soil science and environmental fields. It is hoped that soil information can play a critical role in the establishment of a national Natural Agricultural Information System.

  16. Water deficit mapping of soils in Southern and Insular Italy

    Energy Technology Data Exchange (ETDEWEB)

    Ciavatta, C; Vianello, G

    1987-03-01

    Cross-elaboration of climatic, pedological and vegetational factors allows the water balance of soils to be defined. The data obtained are of particular interest not only for the primary sector, but also for the economy as a whole since the availability of such information is necessary for the correct and rational use of water resources. The application of a methodology, which takes into account the previously mentioned factors, led to the realization of a map showing the overall, annual and monthly water deficit of the soils in Southern Italy, Sicily and Sardinia.

  17. 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

  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. 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

  20. Gamma-ray remote sensing of soil properties in a forested area near Batlow, NSW

    International Nuclear Information System (INIS)

    Bierwirth, P.N.; Aspin, S.J.; Ryan, P.J.; McKenzie, N.J.

    1998-01-01

    In forested and agricultural areas, reflective remote sensing methods are of limited utility for soil studies due to the variable effects of vegetation. Airborne gamma-ray remote sensing is presented here as a useful technique for soils. Short wavelength gamma-rays are detected from the upper 0.30-0.45 m of the soil . They are emitted from radioactive elements in the soil and largely pass through vegetation cover. In this paper, images of gamma parent elements (K, Th and U) are presented and element associations with soil properties and vegetation are analysed for a forested area near Batlow, NSW. Effects of vegetation are evident in gamma-ray data and in Landsat TM along powerlines and in clearings. A technique for removing this effect in the gamma-ray data is demonstrated. Detailed soil and rock chemistry together with ground gamma-spectrometer measurements were collected to support the interpretation and analysis of the image data. The work focuses mainly on the variation of soil properties within areas mapped as granodiorite lithology. Many areas of deep red soils are accurately mapped by the radiometric K data. The precise origin of these soils is not clear and their parent materials may include contributions from aeolian deposition, in situ weathering of granodiorite, and remnant basalt. . In areas of granodiorite, K patterns are interpreted to be a function of the degree of mineral weathering and can be related to soil depth and erosion status. This study demonstrates the effectiveness of gamma-ray remote sensing for directly mapping soil units and properties (authors). Copyright (1998) Remote Sensing and Photogrammetry Association of Australasia Ltd

  1. 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 ...

  2. Joint Interpretation of Bathymetric and Gravity Anomaly Maps Using Cross and Dot-Products.

    Science.gov (United States)

    Jilinski, Pavel; Fontes, Sergio Luiz

    2010-05-01

    0.1 Summary We present the results of joint map interpretation technique based on cross and dot-products applied to bathymetric and gravity anomaly gradients maps. According to the theory (Gallardo, Meju, 2004) joint interpretation of different gradient characteristics help to localize and empathize patterns unseen on one image interpretation and gives information about the correlation of different spatial data. Values of angles between gradients and their cross and dot-product were used. This technique helps to map unseen relations between bathymetric and gravity anomaly maps if they are analyzed separately. According to the method applied for the southern segment of Eastern-Brazilian coast bathymetrical and gravity anomaly gradients indicates a strong source-effect relation between them. The details of the method and the obtained results are discussed. 0.2 Introduction We applied this method to investigate the correlation between bathymetric and gravity anomalies at the southern segment of the Eastern-Brazilian coast. Gridded satellite global marine gravity data and bathymetrical data were used. The studied area is located at the Eastern- Brazilian coast between the 20° W and 30° W meridians and 15° S and 25° S parallels. The volcanic events responsible for the uncommon width of the continental shelf at the Abrolhos bank also were responsible for the formation of the Abrolhos islands and seamounts including the major Vitoria-Trindade chain. According to the literature this volcanic structures are expected to have a corresponding gravity anomaly (McKenzie, 1976, Zembruscki, S.G. 1979). The main objective of this study is to develop and test joint image interpretation method to compare spatial data and analyze its relations. 0.3 Theory and Method 0.3.1 Data sources The bathymetrical satellite data were derived bathymetry 2-minute grid of the ETOPO2v2 obtained from NOAA's National Geophysical Data Center (http://www.ngdc.noaa.gov). The satellite marine gravity 1

  3. 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

    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...

  4. Social-Ecological Patterns of Soil Heavy Metals Based on a Self-Organizing Map (SOM: A Case Study in Beijing, China

    Directory of Open Access Journals (Sweden)

    Binwu Wang

    2014-03-01

    Full Text Available The regional management of trace elements in soils requires understanding the interaction between the natural system and human socio-economic activities. In this study, a social-ecological patterns of heavy metals (SEPHM approach was proposed to identify the heavy metal concentration patterns and processes in different ecoregions of Beijing (China based on a self-organizing map (SOM. Potential ecological risk index (RI values of Cr, Ni, Zn, Hg, Cu, As, Cd and Pb were calculated for 1,018 surface soil samples. These data were averaged in accordance with 253 communities and/or towns, and compared with demographic, agriculture structure, geomorphology, climate, land use/cover, and soil-forming parent material to discover the SEPHM. Multivariate statistical techniques were further applied to interpret the control factors of each SEPHM. SOM application clustered the 253 towns into nine groups on the map size of 12 × 7 plane (quantization error 1.809; topographic error, 0.0079. The distribution characteristics and Spearman rank correlation coefficients of RIs were strongly associated with the population density, vegetation index, industrial and mining land percent and road density. The RIs were relatively high in which towns in a highly urbanized area with large human population density exist, while low RIs occurred in mountainous and high vegetation cover areas. The resulting dataset identifies the SEPHM of Beijing and links the apparent results of RIs to driving factors, thus serving as an excellent data source to inform policy makers for legislative and land management actions.

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

    Science.gov (United States)

    Samson, S. A.

    1985-01-01

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

  6. Pilot study of the application of Tellus airborne radiometric and soil geochemical data for radon mapping

    Energy Technology Data Exchange (ETDEWEB)

    Appleton, J.D. [British Geological Survey, Kingsley Dunham Centre, Keyworth, Nottingham NG12 5GG (United Kingdom)], E-mail: jda@bgs.ac.uk; Miles, J.C.H.; Green, B.M.R. [Health Protection Agency (HPA) - Radiation Protection Division, Chilton, Didcot, Oxon OX11 0RQ (United Kingdom); Larmour, R. [Environment and Heritage Service, Department of the Environment, Belfast BT7 2JA (United Kingdom)

    2008-10-15

    The scope for using Tellus Project airborne gamma-ray spectrometer and soil geochemical data to predict the probability of houses in Northern Ireland having high indoor radon concentrations is evaluated, in a pilot study in the southeast of the province, by comparing these data statistically with in-house radon measurements. There is generally good agreement between radon maps modelled from the airborne radiometric and soil geochemical data using multivariate linear regression analysis and conventional radon maps which depend solely on geological and indoor radon data. The radon maps based on the Tellus Project data identify some additional areas where the radon risk appears to be relatively high compared with the conventional radon maps. One of the ways of validating radon maps modelled on the Tellus Project data will be to carry out additional indoor measurements in these areas.

  7. Interpreting, measuring, and modeling soil respiration

    Science.gov (United States)

    Michael G. Ryan; Beverly E. Law

    2005-01-01

    This paper reviews the role of soil respiration in determining ecosystem carbon balance, and the conceptual basis for measuring and modeling soil respiration. We developed it to provide background and context for this special issue on soil respiration and to synthesize the presentations and discussions at the workshop. Soil respiration is the largest component of...

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

    Directory of Open Access Journals (Sweden)

    Jangwon Suh

    2016-12-01

    Full Text Available 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.

  9. Digital Soil Mapping Using Landscape Stratification for Arid Rangelands in the Eastern Great Basin, Central Utah

    OpenAIRE

    Fonnesbeck, Brook B.

    2015-01-01

    Digital soil mapping typically involves inputs of digital elevation models, remotely sensed imagery, and other spatially explicit digital data as environmental covariates to predict soil classes and attributes over a landscape using statistical models. Digital imagery from Landsat 5, a digital elevation model, and a digital geology map were used as environmental covariates in a 67,000-ha study area of the Great Basin west of Fillmore, UT. A “pre-map” was created for selecting sampling locatio...

  10. Segmentation of singularity maps in the context of soil porosity

    Science.gov (United States)

    Martin-Sotoca, Juan J.; Saa-Requejo, Antonio; Grau, Juan; Tarquis, Ana M.

    2016-04-01

    Geochemical exploration have found with increasingly interests and benefits of using fractal (power-law) models to characterize geochemical distribution, including concentration-area (C-A) model (Cheng et al., 1994; Cheng, 2012) and concentration-volume (C-V) model (Afzal et al., 2011) just to name a few examples. These methods are 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. Recently, the "Singularity-CA" method has been applied to binarize 2D grayscale Computed Tomography (CT) soil images (Martin-Sotoca et al, 2015). Unlike image segmentation based on global thresholding methods, the "Singularity-CA" method allows to quantify the local scaling property of the grayscale value map in the space domain and determinate the intensity of local singularities. It can be used as a high-pass-filter technique to enhance high frequency patterns usually regarded as anomalies when applied to maps. In this work we will put special attention on how to select the singularity thresholds in the C-A plot to segment the image. We will compare two methods: 1) cross point of linear regressions and 2) Wavelets Transform Modulus Maxima (WTMM) singularity function detection. REFERENCES Cheng, Q., Agterberg, F. P. and Ballantyne, S. B. (1994). The separation of geochemical anomalies from background by fractal methods. Journal of Geochemical Exploration, 51, 109-130. Cheng, Q. (2012). Singularity theory and methods for mapping geochemical anomalies caused by buried sources and for predicting undiscovered mineral deposits in covered areas. Journal of Geochemical Exploration, 122, 55-70. Afzal, P., Fadakar Alghalandis, Y., Khakzad, A., Moarefvand, P. and Rashidnejad Omran, N. (2011) Delineation of mineralization zones in

  11. Psychometric aspects of item mapping for criterion-referenced interpretation and bookmark standard setting.

    Science.gov (United States)

    Huynh, Huynh

    2010-01-01

    Locating an item on an achievement continuum (item mapping) is well-established in technical work for educational/psychological assessment. Applications of item mapping may be found in criterion-referenced (CR) testing (or scale anchoring, Beaton and Allen, 1992; Huynh, 1994, 1998a, 2000a, 2000b, 2006), computer-assisted testing, test form assembly, and in standard setting methods based on ordered test booklets. These methods include the bookmark standard setting originally used for the CTB/TerraNova tests (Lewis, Mitzel, Green, and Patz, 1999), the item descriptor process (Ferrara, Perie, and Johnson, 2002) and a similar process described by Wang (2003) for multiple-choice licensure and certification examinations. While item response theory (IRT) models such as the Rasch and two-parameter logistic (2PL) models traditionally place a binary item at its location, Huynh has argued in the cited papers that such mapping may not be appropriate in selecting items for CR interpretation and scale anchoring.

  12. Mapping and predictive variations of soil bacterial richness across France.

    Science.gov (United States)

    Terrat, Sébastien; Horrigue, Walid; Dequiedt, Samuel; Saby, Nicolas P A; Lelièvre, Mélanie; Nowak, Virginie; Tripied, Julie; Régnier, Tiffanie; Jolivet, Claudy; Arrouays, Dominique; Wincker, Patrick; Cruaud, Corinne; Karimi, Battle; Bispo, Antonio; Maron, Pierre Alain; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

    2017-01-01

    Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition.

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

    International Nuclear Information System (INIS)

    Baptista, G.M.M.; Meneses, P.R.; Correa, R.S.; Dos Santos, P.F.; Correa, R.S.; Jose, S.; Dos Santos, P.F.; Netto, M.

    2011-01-01

    The purpose of this study was to test the feasibility of applying AVIRIS sensor (Airborne Visible/Infra Red Imaging Spectrometer) for mapping and quantifying mineralogical components of three Brazilian soils, a reddish Oxisol in Sao Joao D'Alianca area (SJA) and a dark reddish brown Oxisol and Ultisol in Niquelandia (NIQ) counties, Goias 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.

  14. Soil Carbon Mapping in Low Relief Areas with Combined Land Use Types and Percentages

    Science.gov (United States)

    Liu, Y. L.; Wu, Z. H.; Chen, Y. Y.; Wang, B. Z.

    2018-05-01

    Accurate mapping of soil carbon in low relief areas is of great challenge because of the defect of conventional "soil-landscape" model. Efforts have been made to integrate the land use information in the modelling and mapping of soil organic carbon (SOC), in which the spatial context was ignored. With 256 topsoil samples collected from Jianghan Plain, we aim to (i) explore the land-use dependency of SOC via one-way ANOVA; (ii) investigate the "spillover effect" of land use on SOC content; (iii) examine the feasibility of land use types and percentages (obtained with a 200-meter buffer) for soil mapping via regression Kriging (RK) models. Results showed that the SOC of paddy fields was higher than that of woodlands and irrigated lands. The land use type could explain 20.5 % variation of the SOC, and the value increased to 24.7 % when the land use percentages were considered. SOC was positively correlated with the percentage of water area and irrigation canals. Further research indicated that SOC of irrigated lands was significantly correlated with the percentage of water area and irrigation canals, while paddy fields and woodlands did not show similar trends. RK model that combined land use types and percentages outperformed the other models with the lowest values of RMSEC (5.644 g/kg) and RMSEP (6.229 g/kg), and the highest R2C (0.193) and R2P (0.197). In conclusions, land use types and percentages serve as efficient indicators for the SOC mapping in plain areas. Additionally, irrigation facilities contributed to the farmland SOC sequestration especially in irrigated lands.

  15. Influence of management history and landscape variables on soil organic carbon and soil redistribution

    Science.gov (United States)

    Venteris, E.R.; McCarty, G.W.; Ritchie, J.C.; Gish, T.

    2004-01-01

    Controlled studies to investigate the interaction between crop growth, soil properties, hydrology, and management practices are common in agronomy. These sites (much as with real world farmland) often have complex management histories and topographic variability that must be considered. In 1993 an interdisiplinary study was started for a 20-ha site in Beltsville, MD. Soil cores (271) were collected in 1999 in a 30-m grid (with 5-m nesting) and analyzed as part of the site characterization. Soil organic carbon (SOC) and 137Cesium (137Cs) were measured. Analysis of aerial photography from 1992 and of farm management records revealed that part of the site had been maintained as a swine pasture and the other portion as cropped land. Soil properties, particularly soil redistribution and SOC, show large differences in mean values between the two areas. Mass C is 0.8 kg m -2 greater in the pasture area than in the cropped portion. The pasture area is primarily a deposition site, whereas the crop area is dominated by erosion. Management influence is suggested, but topographic variability confounds interpretation. Soil organic carbon is spatially structured, with a regionalized variable of 120 m. 137Cs activity lacks spatial structure, suggesting disturbance of the profile by animal activity and past structures such as swine shelters and roads. Neither SOC nor 137Cs were strongly correlated to terrain parameters, crop yields, or a seasonal soil moisture index predicted from crop yields. SOC and 137Cs were weakly correlated (r2 ???0.2, F-test P-value 0.001), suggesting that soil transport controls, in part, SOC distribution. The study illustrates the importance of past site history when interpreting the landscape distribution of soil properties, especially those strongly influenced by human activity. Confounding variables, complex soil hydrology, and incomplete documentation of land use history make definitive interpretations of the processes behind the spatial distributions

  16. Mapping of Cu and Pb Contaminations in Soil Using Combined Geochemistry, Topography, and Remote Sensing: A Case Study in the Le’an River Floodplain, China

    Directory of Open Access Journals (Sweden)

    Yin Gao

    2012-05-01

    Full Text Available Heavy metal pollution in soil is becoming a widely concerning environmental problem in China. The aim of this study is to integrate multiple sources of data, namely total Cu and Pb contents, digital elevation model (DEM data, remote sensing image and interpreted land-use data, for mapping the spatial distribution of total Cu and Pb contamination in top soil along the Le’an River and its branches. Combined with geographical analyses and watershed delineation, the source and transportation route of pollutants are identified. Regions at high risk of Cu or Pb pollution are suggested. Results reveal that topography is the major factor that controls the spatial distribution of Cu and Pb. Watershed delineation shows evidence that the streamflow resulting from rainfall is the major carrier of metal pollutants.

  17. `VIS/NIR mapping of TOC and extent of organic soils in the Nørre Å valley

    Science.gov (United States)

    Knadel, M.; Greve, M. H.; Thomsen, A.

    2009-04-01

    Organic soils represent a substantial pool of carbon in Denmark. The need for carbon stock assessment calls for more rapid and effective mapping methods to be developed. The aim of this study was to compare traditional soil mapping with maps produced from the results of a mobile VIS/NIR system and to evaluate the ability to estimate TOC and map the area of organic soils. The Veris mobile VIS/NIR spectroscopy system was compared to traditional manual sampling. The system is developed for in-situ near surface measurements of soil carbon content. It measures diffuse reflectance in the 350 nm-2200 nm region. The system consists of two spectrophotometers mounted on a toolbar and pulled by a tractor. Optical measurements are made through a sapphire window at the bottom of the shank. The shank was pulled at a depth of 5-7 cm at a speed of 4-5 km/hr. 20-25 spectra per second with 8 nm resolution were acquired by the spectrometers. Measurements were made on 10-12 m spaced transects. The system also acquired soil electrical conductivity (EC) for two soil depths: shallow EC-SH (0- 31 cm) and deep conductivity EC-DP (0- 91 cm). The conductivity was recorded together with GPS coordinates and spectral data for further construction of the calibration models. Two maps of organic soils in the Nørre Å valley (Central Jutland) were generated: (i) based on a conventional 25 m grid with 162 sampling points and laboratory analysis of TOC, (ii) based on in-situ VIS/NIR measurements supported by chemometrics. Before regression analysis, spectral information was compressed by calculating principal components. The outliers were determined by a mahalanobis distance equation and removed. Clustering using a fuzzy c- means algorithm was conducted. Within each cluster a location with the minimal spatial variability was selected. A map of 15 representative sample locations was proposed. The interpolation of the spectra into a single spectrum was performed using a Gaussian kernel weighting

  18. 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...

  19. Application of airborne gamma-ray spectrometry in soil/regolith mapping and applied geomorphology

    International Nuclear Information System (INIS)

    Wilford, J.R.; Bierwirth, P.N.; Craig, M.A.

    1997-01-01

    Gamma-ray spectrometric surveys are an important source of information for soil, regolith and geomorphological studies, as demonstrated by the interpretation of airborne surveys in Western Australia, central New South Wales and north Queensland. Gamma-rays emitted from the ground surface relate to the primary mineralogy and geochemistry of the bedrock, and the secondary weathered materials. Weathering modifies the distribution and concentration of radioelements from the original bedrock source. Once the radioelement response of bedrock and weathered materials is understood, the gamma-ray data can provide information on geomorphic processes and soil/regolith properties, including their mineralogy, texture, chemistry and style of weathering. This information can contribute significantly to an understanding of the weathering and geomorphic history of a region and, therefore, has the potential to be used in developing more effective land-management strategies and refining geochemical models in support of mineral exploration. Gamma-ray imagery is enhanced when combined with Landsat TM bands and digital elevation models (DEM). This synergy enables geochemical information derived from the gamma-ray data to be interpreted within a geomorphic framework. Draping gamma-ray images over DEMs as 3D landscape perspective views aids interpretation and allows the interpreter to visualise complex relationships between the gamma-ray response and landform features. 44 refs.,1 tab., 11 figs

  20. 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.

  1. Generating a Danish raster-based topsoil property map combining choropleth maps and point information

    DEFF Research Database (Denmark)

    Greve, Mogens H.; Greve, Mette B.; Bøcher, Peder K.

    2007-01-01

    The Danish environmental authorities have posed a soil type dependent restriction on the application of nitrogen. The official Danish soil map is a choropleth topsoil map classifying the agricultural land into eight classes. The use of the soil map has shown that the maps have serious...... classification flaws. The objective of this work is to compile a continuous national topsoil texture map to replace the old topsoil map. Approximately 45,000 point samples were interpolated using ordinary kriging in 250 m x 250 m cells. To reduce variability and to obtain more homogeneous strata, the samples...... were stratified according to landscape types. Five new soil texture maps were compiled; one for each of the five textural classes, and a new categorical soil type map was compiled using the old classification system. Both the old choropleth map and the new continuous soil maps were compared to 354...

  2. Convergence of soil nitrogen isotopes across global climate gradients

    Science.gov (United States)

    Craine, Joseph M.; Elmore, Andrew J.; Wang, Lixin; Augusto, Laurent; Baisden, W. Troy; Brookshire, E. N. J.; Cramer, Michael D.; Hasselquist, Niles J.; Hobbie, Erik A.; Kahmen, Ansgar; Koba, Keisuke; Kranabetter, J. Marty; Mack, Michelle C.; Marin-Spiotta, Erika; Mayor, Jordan R.; McLauchlan, Kendra K.; Michelsen, Anders; Nardoto, Gabriela B.; Oliveira, Rafael S.; Perakis, Steven S.; Peri, Pablo L.; Quesada, Carlos A.; Richter, Andreas; Schipper, Louis A.; Stevenson, Bryan A.; Turner, Benjamin L.; Viani, Ricardo A. G.; Wanek, Wolfgang; Zeller, Bernd

    2015-01-01

    Quantifying global patterns of terrestrial nitrogen (N) cycling is central to predicting future patterns of primary productivity, carbon sequestration, nutrient fluxes to aquatic systems, and climate forcing. With limited direct measures of soil N cycling at the global scale, syntheses of the 15 N: 14 N ratio of soil organic matter across climate gradients provide key insights into understanding global patterns of N cycling. In synthesizing data from over 6000 soil samples, we show strong global relationships among soil N isotopes, mean annual temperature (MAT), mean annual precipitation (MAP), and the concentrations of organic carbon and clay in soil. In both hot ecosystems and dry ecosystems, soil organic matter was more enriched in 15 N than in corresponding cold ecosystems or wet ecosystems. Below a MAT of 9.8°C, soil δ15N was invariant with MAT. At the global scale, soil organic C concentrations also declined with increasing MAT and decreasing MAP. After standardizing for variation among mineral soils in soil C and clay concentrations, soil δ15N showed no consistent trends across global climate and latitudinal gradients. Our analyses could place new constraints on interpretations of patterns of ecosystem N cycling and global budgets of gaseous N loss.

  3. Miocene Soil Database: Global paleosol and climate maps of the Middle Miocene Thermal Maximum

    Science.gov (United States)

    Metzger, C. A.

    2013-12-01

    Paleosols, which record past climatic, biologic, and atmospheric conditions, can be used as a proxy to understand ancient terrestrial landscapes, paleoclimate, and paleoenvironment. In addition, the middle Miocene thermal maximum (~16 Ma) provides an ancient analog for understanding the effects of current and future climate change on soil and ecosystem regimes, as it contains records of shifts similar in magnitude to expected global climate change. The Miocene Soil Database (MSDB) combines new paleosol data from Australia and Argentina with existing and previously uncollated paleosol data from the literature and the Paleobiology Database. These data (n = 507) were then used to derive a paleogeographic map of climatically significant soil types zones during the Middle Miocene. The location of each diagnostic paleosol type (Aridisol, Alfisol, Mollisol, Histosol, Oxisol, and Ultisol) was plotted and compared with the extent of these soil types in the modern environment. The middle Miocene soil map highlights the extension of tropical soils (Oxisols, Ultisols), accompanied by thermophilic flora and fauna, into northern and southern mid-latitudes. Peats, lignites, and Histosols of wetlands were also more abundant at higher latitudes, especially in the northern hemisphere, during the middle Miocene. The paleosol changes reflect that the Middle Miocene was a peak of global soil productivity and carbon sequestration, with replacement of unproductive Aridisols and Gelisols with more productive Oxisols, Alfisols, Mollisols and Histosols. With expansion to include additional data such as soil texture, moisture, or vegetation type, the MSDB has the potential to provide an important dataset for computer models of Miocene climate shifts as well as future land use considerations of soils in times of global change.

  4. 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.

  5. A calculation method of available soil water content : application to viticultural terroirs mapping of the Loire valley

    Directory of Open Access Journals (Sweden)

    Etienne Goulet

    2004-12-01

    Full Text Available Vine water supply is one of the most important elements in the determination of grape composition and wine quality. Water supply conditions are in relation with available soil water content, therefore this one has to be determined when vineyard terroir mapping is undertaken. The available soil water content depends on soil factors like water content at field capacity, water content at the permanent wilting point, apparent density and rooting depth. The aim of this study is to seek the relationship between these factors and a simple soil characteristic such as texture which could be easily measurable in routine cartography. Study area is located in the Loire valley, in two different geological regions. First results indicate that it is possible to determine available soil water content from clay percentage, then from soil texture. These results also show that available soil water content algorithms differ with geological properties. This calculation can be used at each auger boring and results can be spatialised within a Geographical Information System that allows the production of available water content maps.

  6. Mapping and predictive variations of soil bacterial richness across France.

    Directory of Open Access Journals (Sweden)

    Sébastien Terrat

    Full Text Available Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i to describe the bacterial taxonomic richness variations across France, ii to identify the ecological processes (i.e. selection by the environment and dispersal limitation influencing this distribution, and iii to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS, which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance, the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively, and the land use (1.4%. Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56 and provides a reference value for a given pedoclimatic condition.

  7. 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...... sampling. The geostatistical estimation method co-kriging uses two or more sampled variables, which are correlated, to improve the estimation of one of the variables at locations where it was not sampled. We did an experiment on a 2.1 ha winter wheat field to compare co-kriging using soil properties......, with kriging based only on one variable. The results showed that co-kriging Lamium spp. from 96 0.25m2 sample plots ha-1 with silt content improved the prediction variance by 11% compared to kriging. With 51 or 18 sample plots ha-1 the prediction variance was improved by 21 and 15%....

  8. Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models.

    Science.gov (United States)

    Scholte, Ronaldo G C; Schur, Nadine; Bavia, Maria E; Carvalho, Edgar M; Chammartin, Frédérique; Utzinger, Jürg; Vounatsou, Penelope

    2013-11-01

    Soil-transmitted helminths (Ascaris lumbricoides, Trichuris trichiura and hookworm) negatively impact the health and wellbeing of hundreds of millions of people, particularly in tropical and subtropical countries, including Brazil. Reliable maps of the spatial distribution and estimates of the number of infected people are required for the control and eventual elimination of soil-transmitted helminthiasis. We used advanced Bayesian geostatistical modelling, coupled with geographical information systems and remote sensing to visualize the distribution of the three soil-transmitted helminth species in Brazil. Remotely sensed climatic and environmental data, along with socioeconomic variables from readily available databases were employed as predictors. Our models provided mean prevalence estimates for A. lumbricoides, T. trichiura and hookworm of 15.6%, 10.1% and 2.5%, respectively. By considering infection risk and population numbers at the unit of the municipality, we estimate that 29.7 million Brazilians are infected with A. lumbricoides, 19.2 million with T. trichiura and 4.7 million with hookworm. Our model-based maps identified important risk factors related to the transmission of soiltransmitted helminths and confirm that environmental variables are closely associated with indices of poverty. Our smoothed risk maps, including uncertainty, highlight areas where soil-transmitted helminthiasis control interventions are most urgently required, namely in the North and along most of the coastal areas of Brazil. We believe that our predictive risk maps are useful for disease control managers for prioritising control interventions and for providing a tool for more efficient surveillance-response mechanisms.

  9. Interpretation of fingerprint image quality features extracted by self-organizing maps

    Science.gov (United States)

    Danov, Ivan; Olsen, Martin A.; Busch, Christoph

    2014-05-01

    Accurate prediction of fingerprint quality is of significant importance to any fingerprint-based biometric system. Ensuring high quality samples for both probe and reference can substantially improve the system's performance by lowering false non-matches, thus allowing finer adjustment of the decision threshold of the biometric system. Furthermore, the increasing usage of biometrics in mobile contexts demands development of lightweight methods for operational environment. A novel two-tier computationally efficient approach was recently proposed based on modelling block-wise fingerprint image data using Self-Organizing Map (SOM) to extract specific ridge pattern features, which are then used as an input to a Random Forests (RF) classifier trained to predict the quality score of a propagated sample. This paper conducts an investigative comparative analysis on a publicly available dataset for the improvement of the two-tier approach by proposing additionally three feature interpretation methods, based respectively on SOM, Generative Topographic Mapping and RF. The analysis shows that two of the proposed methods produce promising results on the given dataset.

  10. 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

  11. A diagnostic algorithm to optimize data collection and interpretation of Ripple Maps in atrial tachycardias.

    Science.gov (United States)

    Koa-Wing, Michael; Nakagawa, Hiroshi; Luther, Vishal; Jamil-Copley, Shahnaz; Linton, Nick; Sandler, Belinda; Qureshi, Norman; Peters, Nicholas S; Davies, D Wyn; Francis, Darrel P; Jackman, Warren; Kanagaratnam, Prapa

    2015-11-15

    Ripple Mapping (RM) is designed to overcome the limitations of existing isochronal 3D mapping systems by representing the intracardiac electrogram as a dynamic bar on a surface bipolar voltage map that changes in height according to the electrogram voltage-time relationship, relative to a fiduciary point. We tested the hypothesis that standard approaches to atrial tachycardia CARTO™ activation maps were inadequate for RM creation and interpretation. From the results, we aimed to develop an algorithm to optimize RMs for future prospective testing on a clinical RM platform. CARTO-XP™ activation maps from atrial tachycardia ablations were reviewed by two blinded assessors on an off-line RM workstation. Ripple Maps were graded according to a diagnostic confidence scale (Grade I - high confidence with clear pattern of activation through to Grade IV - non-diagnostic). The RM-based diagnoses were corroborated against the clinical diagnoses. 43 RMs from 14 patients were classified as Grade I (5 [11.5%]); Grade II (17 [39.5%]); Grade III (9 [21%]) and Grade IV (12 [28%]). Causes of low gradings/errors included the following: insufficient chamber point density; window-of-interestRipple Maps in atrial tachycardias. This algorithm requires prospective testing on a real-time clinical platform. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  12. Land use, forest density, soil mapping, erosion, drainage, salinity limitations

    Science.gov (United States)

    Yassoglou, N. J. (Principal Investigator)

    1973-01-01

    The author has identified the following significant results. The results of analyses show that it is possible to obtain information of practical significance as follows: (1) A quick and accurate estimate of the proper use of the valuable land can be made on the basis of temporal and spectral characteristics of the land features. (2) A rather accurate delineation of the major forest formations in the test areas was achieved on the basis of spatial and spectral characteristics of the studied areas. The forest stands were separated into two density classes; dense forest, and broken forest. On the basis of ERTS-1 data and the existing ground truth information a rather accurate mapping of the major vegetational forms of the mountain ranges can be made. (3) Major soil formations are mapable from ERTS-1 data: recent alluvial soils; soil on quarternary deposits; severely eroded soil and lithosol; and wet soils. (4) An estimation of cost benefits cannot be made accurately at this stage of the investigation. However, a rough estimate of the ratio of the cost for obtaining the same amount information from ERTS-1 data and from conventional operations would be approximately 1:6 to 1:10, in favor of the ERTS-1.

  13. Density fractionation of forest soils: methodological questions and interpretation of incubation results and turnover time in an ecosystem context

    Science.gov (United States)

    Susan E. Crow; Christopher W. Swanston; Kate Lajtha; J. Renee Brooks; Heath Keirstead

    2007-01-01

    Soil organic matter (SOM) is often separated by physical means to simplify a complex matrix into discrete fractions. A frequent approach to isolating two or more fractions is based on differing particle densities and uses a high density liquid such as sodium polytungstate (SPT). Soil density fractions are often interpreted as organic matter pools with different carbon...

  14. Soil monitoring as a part of environment monitoring in Slovakia

    International Nuclear Information System (INIS)

    Kobza, J.

    1997-01-01

    In frame of Soil monitoring system it is going about a lot of methods in advance as follows: methods of soil monitoring sites selection and soil monitoring network construction, as well; methods of soil survey and soil sampling; analytical methods (indicating of chemical, agrochemical and physical properties); soil database and methods of evaluation and interpretation of measured results. The monitoring network was constructed on the base of ecological principles - including the monitoring of all soil types and subtypes, various climatic and emission regions as well as relatively clean regions, lowland and highland. Soil monitoring network in forest land is regular (8 x 8 km) with regard to International monitoring system in Forestry. The soil monitoring network in Slovakia consist of 650 monitoring sites (312 sites in farming land and 338 sites in forest land). In addition soil monitoring network includes also 21 monitoring sites. All monitoring sites are geodesically located and reported on the map at a scale of 1:5000. There are the methods concerning the important soil parameters indication with regard to main soil degradation processes a s follows: soil contamination (heavy metals and organic contaminants); soil acidification; soil salinity; soil erosion (deluometrically by the Cs-137 and remote sensing methods); soil compaction; soil fertility and protection. Analytical control system was elaborated according to Good Laboratory Practice. Evaluation of soil monitoring network results is not simple because it depends on various monitored parameters, on aim of evaluation as well as on the scale of landscape which is object for evaluation. There are used the modern statistical methods in monitoring system which can be: universal; disjunctive; simulated. Used statistical methods are significant for interpretation of measured results as follows: trends in landscape; anisotropy; comparison. The evaluation and interpretation way is very significant with regard not

  15. Retrieval and Mapping of Heavy Metal Concentration in Soil Using Time Series Landsat 8 Imagery

    Science.gov (United States)

    Fang, Y.; Xu, L.; Peng, J.; Wang, H.; Wong, A.; Clausi, D. A.

    2018-04-01

    Heavy metal pollution is a critical global environmental problem which has always been a concern. Traditional approach to obtain heavy metal concentration relying on field sampling and lab testing is expensive and time consuming. Although many related studies use spectrometers data to build relational model between heavy metal concentration and spectra information, and then use the model to perform prediction using the hyperspectral imagery, this manner can hardly quickly and accurately map soil metal concentration of an area due to the discrepancies between spectrometers data and remote sensing imagery. Taking the advantage of easy accessibility of Landsat 8 data, this study utilizes Landsat 8 imagery to retrieve soil Cu concentration and mapping its distribution in the study area. To enlarge the spectral information for more accurate retrieval and mapping, 11 single date Landsat 8 imagery from 2013-2017 are selected to form a time series imagery. Three regression methods, partial least square regression (PLSR), artificial neural network (ANN) and support vector regression (SVR) are used to model construction. By comparing these models unbiasedly, the best model are selected to mapping Cu concentration distribution. The produced distribution map shows a good spatial autocorrelation and consistency with the mining area locations.

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

    Directory of Open Access Journals (Sweden)

    Tomislav Hengl

    Full Text Available 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

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

    Science.gov (United States)

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

    2013-04-01

    There is a heap of evidences that demands on soil related information have been significant worldwide and it is still increasing. Soil maps were typically used for long time to satisfy these demands. By the spread of GI technology, spatial soil information systems (SSIS) and digital soil mapping (DSM) took the role of traditional soil maps. Due to the relatively high costs of data collection, new conventional soil surveys and inventories are getting less and less frequent, which fact valorises legacy soil information and the systems which are serving the their digitally processed version. The existing data contain a wealth of information that can be exploited by proper methodology. Not only the degree of current needs for soil information has changed but also its nature. Traditionally the agricultural functions of soils were focussed on, which was also reflected in the methodology of data collection and mapping. Recently the multifunctionality of soils is getting to gain more and more ground; consequently information related to additional functions of soils becomes identically important. The new types of information requirements however cannot be fulfilled generally with new data collections at least not on such a level as it was done in the frame of traditional soil surveys. Soil monitoring systems have been established for the collection of recent information on the various elements of the DPSIR (Driving Forces-Pressures-State-Impacts-Responses) framework, but the primary goal of these systems has not been mapping by all means. And definitely this is the case concerning the two recently working Hungarian soil monitoring systems. In Hungary, presently soil data requirements are fulfilled with the recently available datasets either by their direct usage or after certain specific and generally fortuitous, thematic and/or spatial inference. Due to the more and more frequently emerging discrepancies between the available and the expected data, there might be notable

  18. The Unified North American Soil Map and Its Implication on the Soil Organic Carbon Stock in North America

    Science.gov (United States)

    Wei, Y.; Liu, S.; Huntzinger, D. N.; Michalak, A. M.; Post, W. M.; Cook, R. B.; Schaefer, K. M.; Thornton, M.

    2014-12-01

    The Unified North American Soil Map (UNASM) was developed by Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) 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 has been provided as a resource for use in terrestrial ecosystem modeling of MsTMIP both for input of soil characteristics and for benchmarking model output.

  19. Mapping of Rill Erosion of Arable Soils Based on Unmanned Aerial Vehicles Survey

    Science.gov (United States)

    Kashtanov, A. N.; Vernyuk, Yu. I.; Savin, I. Yu.; Shchepot'ev, V. V.; Dokukin, P. A.; Sharychev, D. V.; Li, K. A.

    2018-04-01

    Possibilities of using data obtained from unmanned aerial vehicles for detection and mapping of rill erosion on arable lands are analyzed. Identification and mapping of rill erosion was performed on a key plot with a predominance of arable gray forest soils (Greyzemic Phaeozems) under winter wheat in Tula oblast. This plot was surveyed from different heights and in different periods to determine the reliability of identification of rill erosion on the basis of automated procedures in a GIS. It was found that, despite changes in the pattern of rills during the warm season, only one survey during this season is sufficient for adequate assessment of the area of eroded soils. According to our data, the most reliable identification of rill erosion is based on the aerial survey from the height of 50 m above the soil surface. When the height of the flight is more than 200 m, erosional rills virtually escape identification. The efficiency of identification depends on the type of crops, their status, and time of the survey. The surveys of bare soil surface in periods with maximum possible interval from the previous rain or snowmelt season are most efficient. The results of our study can be used in the systems of remote sensing monitoring of erosional processes on arable fields. Application of multiand hyperspectral cameras can improve the efficiency of monitoring.

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. Mapping of soil erosion and redistribution on two agricultural areas in Czech Republic by using of magnetic parameters.

    Science.gov (United States)

    Kapicka, Ales; Stejskalova, Sarka; Grison, Hana; Petrovsky, Eduard; Jaksik, Ondrej; Kodesova, Radka

    2015-04-01

    Soil erosion is one of the major concerns in sustainability of agricultural systems in different areas. Therefore there is a need to develop suitable innovative indirect methods of soil survey. One of this methods is based on well established differentiation in magnetic signature with depth in soil profile. Magnetic method can be applied in the field as well as in the laboratory on collected soil samples. The aim of this study is to evaluate suitability of magnetic method to assess soil degradation and construct maps of cumulative soil loss due to erosion at two morphologically diverse areas with different soil types. Dominant soil unit in the first locality (Brumovice) is chernozem, which is gradually degraded on slopes to regosols. In the second site (Vidim), the dominant soil unit is luvisol, gradualy transformed to regosol due to erosion. Field measurements of magnetic susceptibility were carried out on regular grid, resulting in 101 data points in Brumovice and 65 in Vidim locality. Mass specific magnetic susceptibility χ and its frequency dependence χFD was used to estimate the significance of SP ferrimagnetic particles of pedogenic origin in top soil horizons. Strong correlation was found between the volume magnetic susceptibility (field measurement) and mass- specific magnetic susceptibility measured in the laboratory (Kapicka et al 2013). Values of magnetic susceptibility are spatially distributed depending on terrain position. Higher values were measured at the flat parts (where the original topsoil horizon remained). The lowest values magnetic susceptibility were obtained on the steep valley sides. Here the original topsoil was eroded and mixed by tillage with the soil substrate (loess). Positive correlation between the organic carbon content and volume magnetic susceptibility (R2= 0.89) was found for chernozem area. The differences between the values of susceptibility in the undisturbed soil profile and the magnetic signal after uniform mixing of the

  5. 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.

  6. 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.

  7. Geologic map of the Basque-Cantabrian Basin and a new tectonic interpretation of the Basque Arc

    Science.gov (United States)

    Ábalos, B.

    2016-11-01

    A new printable 1/200.000 bedrock geological map of the onshore Basque-Cantabrian Basin is presented, aimed to contribute to future geologic developments in the central segment of the Pyrenean-Cantabrian Alpine orogenic system. It is accompanied in separate appendixes by a historic report on the precedent geological maps and by a compilation above 350 bibliographic citations of maps and academic reports (usually overlooked or ignored) that are central to this contribution. Structural scrutiny of the map permits to propose a new tectonic interpretation of the Basque Arc, implementing previously published partial reconstructions. It is presented as a printable 1/400.000 tectonic map. The Basque Arc consists of various thrust slices that can expose at the surface basement rocks (Palaeozoic to Lower Triassic) and their sedimentary cover (uppermost Triassic to Tertiary), from which they are detached by intervening (Upper Triassic) evaporites and associated rocks. The slice-bounding thrusts are in most cases reactivated normal faults active during Meso-Cenozoic sedimentation that can be readily related to basement discontinuities generated during the Hercynian orogeny.

  8. 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.

  9. High-resolution Mapping of Permafrost and Soil Freeze/thaw Dynamics in the Tibetan Plateau Based on Multi-sensor Satellite Observations

    Science.gov (United States)

    Zhang, W.; Yi, Y.; Yang, K.; Kimball, J. S.

    2016-12-01

    The Tibetan Plateau (TP) is underlain by the world's largest extent of alpine permafrost ( 2.5×106 km2), dominated by sporadic and discontinuous permafrost with strong sensitivity to climate warming. Detailed permafrost distributions and patterns in most of the TP region are still unknown due to extremely sparse in-situ observations in this region characterized by heterogeneous land cover and large temporal dynamics in surface soil moisture conditions. Therefore, satellite-based temperature and moisture observations are essential for high-resolution mapping of permafrost distribution and soil active layer changes in the TP region. In this study, we quantify the TP regional permafrost distribution at 1-km resolution using a detailed satellite data-driven soil thermal process model (GIPL2). The soil thermal model is calibrated and validated using in-situ soil temperature/moisture observations from the CAMP/Tibet field campaign (9 sites: 0-300 cm soil depth sampling from 1997-2007), a multi-scale soil moisture and temperature monitoring network in the central TP (CTP-SMTMN, 57 sites: 5-40 cm, 2010-2014) and across the whole plateau (China Meteorology Administration, 98 sites: 0-320 cm, 2000-2015). Our preliminary results using the CAMP/Tibet and CTP-SMTMN network observations indicate strong controls of surface thermal and soil moisture conditions on soil freeze/thaw dynamics, which vary greatly with underlying topography, soil texture and vegetation cover. For regional mapping of soil freeze/thaw and permafrost dynamics, we use the most recent soil moisture retrievals from the NASA SMAP (Soil Moisture Active Passive) sensor to account for the effects of temporal soil moisture dynamics on soil thermal heat transfer, with surface thermal conditions defined by MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature records. Our study provides the first 1-km map of spatial patterns and recent changes of permafrost conditions in the TP.

  10. Functional interpretation of representative soil spatial-temporal variability at the Central region of European territory of Russia

    Science.gov (United States)

    Vasenev, I.

    2012-04-01

    The essential spatial and temporal variability is mutual feature for most natural and man-changed soils at the Central region of European territory of Russia. The original spatial heterogeneity of forest and forest-steppe soils has been further complicated by a specific land-use history and different-direction soil successions due to environmental changes and human impacts. For demand-driven land-use planning and decision making the quantitative analysis, modeling and functional-ecological interpretation of representative soil cover patterns spatial variability is an important and challenging task that receives increasing attention from scientific society, private companies, governmental and environmental bodies. On basis of long-term different-scale soil mapping, key plot investigation, land quality and land-use evaluation, soil forming and degradation processes modeling, functional-ecological typology of the zonal set of elementary soil cover patterns (ESCP) has been done in representative natural and man transformed ecosystems of the forest, forest-steppe and steppe zones at the Central region of European territory of Russia (ETR). The validation and ranging of the limiting factors of functional quality and ecological state have been made for dominating and most dynamical components of ESCP regional-typological forms - with application of local GIS, traditional regression kriging and correlation tree models. Development, zonal-regional differentiation and verification of the basic set of criteria and algorithms for logically formalized distinguishing of the most "stable" & "hot" areas in soil cover patterns make it possible for quantitative assessment of dominating in them elementary landscape, soil-forming and degradation processes. The received data essentially expand known ranges of the soil forming processes (SFP) rate «in situ». In case of mature forests mutual for them the windthrow impacts and lateral processes make SFPs more active and complex both in

  11. 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.

  12. 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 solid-state 13C nuclear magnetic resonance (NMR) spectroscopy, giving the three OC pools, particulate organic carbon (POC), humic organic carbon (HOC) and resistant organic carbon (ROC; charcoal or char-carbon). 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, POC, HOC and ROC at the continental scale. In this presentation I will describe how we made the maps and how we use them to assess the vulnerability of soil organic C to for instance climate change.

  13. Soil moisture mapping at Bubnow Wetland using L-band radiometer (ELBARA III)

    Science.gov (United States)

    Łukowski, Mateusz; Schwank, Mike; Szlązak, Radosław; Wiesmann, Andreas; Marczewski, Wojciech; Usowicz, Bogusław; Usowicz, Jerzy; Rojek, Edyta; Werner, Charles

    2016-04-01

    The study of soil moisture is a scientific challenge. Not only because of large diversity of soils and differences in their water content, but also due to the difficulty of measuring, especially in large scale. On this field of interest several methods to determine the content of water in soil exists. The basic and referential is gravimetric method, which is accurate, but suitable only for small spatial scales and time-consuming. Indirect methods are faster, but need to be validated, for example those based on dielectric properties of materials (e.g. time domain reflectometry - TDR) or made from distance (remote), like brightness temperature measurements. Remote sensing of soil moisture can be performed locally (from towers, drones, planes etc.) or globally (satellites). These techniques can complement and help to verify different models and assumptions. In our studies, we applied spatial statistics to local soil moisture mapping using ELBARA III (ESA L-band radiometer, 1.4 GHz) mounted on tower (6.5 meter height). Our measurements were carried out in natural Bubnow Wetland, near Polesie National Park (Eastern Poland), during spring time. This test-site had been selected because it is representative for one of the biggest wetlands in Europe (1400 km2), called "Western Polesie", localized in Ukraine, Poland and Belarus. We have investigated Bubnow for almost decade, using meteorological and soil moisture stations, conducting campaigns of hand-held measurements and collecting soil samples. Now, due to the possibility of rotation at different incidence angles (as in previous ELBARA systems) and the new azimuth tracking capabilities, we obtained brightness temperature data not only at different distances from the tower, but also around it, in footprints containing different vegetation and soil types. During experiment we collected data at area about 450 m2 by rotating ELBARA's antenna 5-175° in horizontal and 30-70° in vertical plane. This type of approach allows

  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. Soil geohazard mapping for improved asset management of UK local roads

    Science.gov (United States)

    Pritchard, O. G.; Hallett, S. H.; Farewell, T. S.

    2015-09-01

    Unclassified roads comprise 60 % of the road network in the United Kingdom (UK). The resilience of this locally important network is declining. It is considered by the Institution of Civil Engineers to be "at risk" and is ranked 26th in the world. Many factors contribute to the degradation and ultimate failure of particular road sections. However, several UK local authorities have identified that in drought conditions, road sections founded upon shrink-swell susceptible clay soils undergo significant deterioration compared with sections on non-susceptible soils. This arises from the local road network having little, if any, structural foundations. Consequently, droughts in East Anglia have resulted in millions of pounds of damage, leading authorities to seek emergency governmental funding. This paper assesses the use of soil-related geohazard assessments in providing soil-informed maintenance strategies for the asset management of the locally important road network of the UK. A case study draws upon the UK administrative county of Lincolnshire, where road assessment data have been analysed against mapped clay-subsidence risk. This reveals a statistically significant relationship between road condition and susceptible clay soils. Furthermore, incorporation of UKCP09 future climate projections within the geohazard models has highlighted roads likely to be at future risk of clay-related subsidence.

  16. Mapping of soil organic carbon stocks for spatially explicit assessments of climate change mitigation potential

    International Nuclear Information System (INIS)

    Vågen, Tor-Gunnar; Winowiecki, Leigh A

    2013-01-01

    Current methods for assessing soil organic carbon (SOC) stocks are generally not well suited for understanding variations in SOC stocks in landscapes. This is due to the tedious and time-consuming nature of the sampling methods most commonly used to collect bulk density cores, which limits repeatability across large areas, particularly where information is needed on the spatial dynamics of SOC stocks at scales relevant to management and for spatially explicit targeting of climate change mitigation options. In the current study, approaches were explored for (i) field-based estimates of SOC stocks and (ii) mapping of SOC stocks at moderate to high resolution on the basis of data from four widely contrasting ecosystems in East Africa. Estimated SOC stocks for 0–30 cm depth varied both within and between sites, with site averages ranging from 2 to 8 kg m −2 . The differences in SOC stocks were determined in part by rainfall, but more importantly by sand content. Results also indicate that managing soil erosion is a key strategy for reducing SOC loss and hence in mitigation of climate change in these landscapes. Further, maps were developed on the basis of satellite image reflectance data with multiple R-squared values of 0.65 for the independent validation data set, showing variations in SOC stocks across these landscapes. These maps allow for spatially explicit targeting of potential climate change mitigation efforts through soil carbon sequestration, which is one option for climate change mitigation and adaptation. Further, the maps can be used to monitor the impacts of such mitigation efforts over time. (letter)

  17. 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

    2018-07-15

    Efficient and effective modelling methods to assess soil organic carbon (SOC) stock are central in understanding the global carbon cycle and informing related land management decisions. However, mapping SOC stocks in semi-arid rangelands is challenging due to the lack of data and poor spatial coverage. The use of remote sensing data to provide an indirect measurement of SOC to inform digital soil mapping has the potential to provide more reliable and cost-effective estimates of SOC compared with field-based, direct measurement. Despite this potential, the role of remote sensing data in improving the knowledge of soil information in semi-arid rangelands has not been fully explored. This study firstly investigated the use of high spatial resolution satellite data (seasonal fractional cover data; SFC) together with elevation, lithology, climatic data and observed soil data to map the spatial distribution of SOC at two soil depths (0-5cm and 0-30cm) in semi-arid rangelands of eastern Australia. Overall, model performance statistics showed that random forest (RF) and boosted regression trees (BRT) models performed better than support vector machine (SVM). The models obtained moderate results with R 2 of 0.32 for SOC stock at 0-5cm and 0.44 at 0-30cm, RMSE of 3.51MgCha -1 at 0-5cm and 9.16MgCha -1 at 0-30cm without considering SFC covariates. In contrast, by including SFC, the model accuracy for predicting SOC stock improved by 7.4-12.7% at 0-5cm, and by 2.8-5.9% at 0-30cm, highlighting the importance of including SFC to enhance the performance of the three modelling techniques. Furthermore, our models produced a more accurate and higher resolution digital SOC stock map compared with other available mapping products for the region. The data and high-resolution maps from this study can be used for future soil carbon assessment and monitoring. Copyright © 2018 Elsevier B.V. All rights reserved.

  18. Large area mapping of soil moisture using the ESTAR passive microwave radiometer in Washita'92

    International Nuclear Information System (INIS)

    Jackson, T.J.; Le Vine, D.M.; Swift, C.T.; Schmugge, T.J.; Schiebe, F.R.

    1995-01-01

    Washita'92 was a large-scale study of remote sensing and hydrology conducted on the Little Washita watershed in southwest Oklahoma. Data collection during the experiment included passive microwave observations using an L-band electronically scanned thinned array radiometer (ESTAR) and surface soil moisture observations at sites distributed over the area. Data were collected on 8 days over a 9-day period in June 1992. The watershed was saturated with a great deal of standing water at the outset of the study. During the experiment there was no rainfall and surface soil moisture observations exhibited a drydown pattern over the period. Significant variations in the level and rate of change in surface soil moisture were noted over areas dominated by different soil textures. ESTAR data were processed to produce brightness temperature maps of a 740 sq. km. area on each of the 8 days. These data exhibited significant spatial and temporal patterns. Spatial patterns were clearly associated with soil textures and temporal patterns with drainage and evaporative processes. Relationships between the ground sampled soil moisture and the brightness temperatures were consistent with previous results. Spatial averaging of both variables was analyzed to study scaling of soil moisture over a mixed landscape. Results of these studies showed that a strong correlation is retained at these scales, suggesting that mapping surface moisture for large footprints may provide important information for regional studies. (author)

  19. Estimating surface soil erosion losses and mapping erosion risk for Yusufeli micro-catchment (Artvin

    Directory of Open Access Journals (Sweden)

    Mustafa Tüfekçioğlu

    2016-10-01

    Full Text Available Sheet erosion, one of the most important types of water erosion, takes place on the top soil as tiny soil layer movement that affects lake and stream ecosystem. This type of erosion is very important because the productive soil layer on the top soil can be lost in a very short period of time. The goal of this study was to quantify the amount of surface (sheet and rill soil erosion, and to identify areas under high erosion risk within the study area at Yusufeli province in Artvin by using RUSLE erosion methodology. As a result of the study it was found that the average annual potential soil loss by surface erosion was 3.6 ton ha-1yr-1. Additionally, the maps produced and conclusions reached by the study revealed that the areas of high erosion risk were identified spatially and measures to control erosion on some of these high risk areas can be possible with appropriate erosion control techniques.

  20. 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.

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

    Science.gov (United States)

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

    2016-04-01

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

  2. A Surface Soil Radioactivity Mapping Has Been Carried Out at Muria Peninsula, Central Java

    International Nuclear Information System (INIS)

    Soepradto-Tjokrokardono; Nasrun-Syamsul; Supardjo-AS; Djodi-R-Mappa; Kurnia-Setyawan W

    2004-01-01

    The air of this mapping is to gain exposure dose value of the soil surface of Muria Peninsula. Central Java, in the area of 75 km radius from Ujung Lemah Abang. Lemah Abang is the proposed site of the first indonesian nuclear Power Plant. A radioactivity data obtained in 1995/1996 to 1998/1999 researches has been used for input data. For further analysis, a conversation factor multiplication is applied. This conversation factor is obtained from linear regression equation of the relationship between radioactivity and exposure values gained from re-measured randomly 44 points which are representative for high, medium, and low radiation areas obtained in 1995/1996 to 1998/1999 activities and it taking soil samples. The conversation data result is being constructed of the Surface Exposure Dose Map of Muria Peninsula. Those data show that the exposure dose of northern slope of Muria Volcano is relatively higher than that of southern slope, it means be harmonizing to the soil sample radioactivity values. The maximum radioactivity value of the soil samples is 3,56.10 -2 Bq/gram (α radiation), 8,22.10 -1 Bq/gram (β radiation) and 6,20.10 -1 Bq/gram (γ radiation) and the minimum values are 4,44 10 -3 Bq/gram (α radiation), 1,50. 10 -1 Bq/gram (β radiation) and 4,09. 10 -2 Bq/gram (γ radiation). (author)

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

    Science.gov (United States)

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

    2016-12-15

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

  4. 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

  5. Preliminary geologic map of the Lathrop Wells volcanic center

    International Nuclear Information System (INIS)

    Crowe, B.; Harrington, C.; McFadden, L.; Perry, F.; Wells, S.; Turrin, B.; Champion, D.

    1988-12-01

    A preliminary geologic map has been compiled for the bedrock geology of the Lathrop Wells volcanic center. The map was completed through use of a combination of stereo photographic interpretation and field mapping on color aerial photographs. These photographs (scale 1:4000) were obtained from American Aerial Surveys, Inc. They were flown on August 18, 1987, at the request of the Yucca Mountain Project (then Nevada Nuclear Waste Storage Investigations). The photographs are the Lathrop Wells VC-Area 25 series, numbers 1--32. The original negatives for these photographs are on file with American Aerial Surveys, Inc. Copies of the negatives have been archived at the Los Alamos National Laboratory, Group N-5. The preliminary geologic map is a bedrock geologic map. It does not show alluvial deposits, eolian sands, or scoria fall deposits from the youngest eruptive events. The units will be compiled on separate maps when the geomorphic and soils studies are more advanced

  6. Spatial patterns of soil organic carbon stocks in Estonian arable soils

    Science.gov (United States)

    Suuster, Elsa; Astover, Alar; Kõlli, Raimo; Roostalu, Hugo; Reintam, Endla; Penu, Priit

    2010-05-01

    Soil organic carbon (SOC) determines ecosystem functions, influencing soil fertility, soil physical, chemical and biological properties and crop productivity. Therefore the spatial pattern of SOC stocks and its appropriate management is important at various scales. Due to climate change and the contribution of carbon store in the soils, the national estimates of soil carbon stocks should be determined. Estonian soils have been well studied and mapped at a scale 1:10,000. Previous studies have estimated SOC stocks based on combinations of large groups of Estonian soils and the mean values of the soil profile database, but were not embedded into the geo-referenced databases. These studies have estimated SOC stocks of Estonian arable soils 122.3 Tg. Despite of available soil maps and databases, this information is still very poorly used for spatial soil modelling. The aim of current study is to assess and model spatial pattern of SOC stocks of arable soils on a pilot area Tartu County (area 3089 sq km). Estonian digital soil map and soil monitoring databases are providing a good opportunity to assess SOC stocks at various scales. The qualitative nature of the initial data from a soil map prohibits any straightforward use in modelling. Thus we have used several databases to construct models and linkages between soil properties that can be integrated into soil map. First step was to reorganize the soil map database (44,046 mapping units) so it can be used as an input to modelling. Arable areas were distinguished by a field layer of Agricultural Registers and Information Board, which provides precise information of current land use as it is the basis of paying CAP subsidies. The estimates of SOC content were found by using the arable land evaluation database of Tartu from the Estonian Land Board (comprising 950 sq km and 31,226 fields), where each soil type was assessed separately and average SOC content grouped by texture was derived. SOC content of epipedon varies in

  7. Two Gonostomatid Ciliates from the Soil of Lombardia, Italy; including Note on the Soil Mapping Project.

    Science.gov (United States)

    Bharti, Daizy; Kumar, Santosh; La Terza, Antonietta

    2015-01-01

    Two gonostomatid ciliates, Gonostomum paronense n. sp. and G. strenuum, isolated from the soil sample of paddy field, Lombardia, Italy, were investigated using live observation and protargol impregnation. Gonostomum paronense n. sp. is mainly characterized by a tailed body, frontoventral cirri arranged in pairs, and presence of pretransverse and transverse cirri. Morphologically and morphometrically, the new species is similar to Gonostomum namibiense in having a tailed body and frontoventral cirral pairs; however, it differs mainly in the number of frontoventral cirral pairs (seven vs. three). Phylogenetic analyses based on the SSU rDNA sequences show that the new species is more closely related to G. namibiense than to G. strenuum, supporting the morphological classification based on the cirral pattern and the tailed body. However, due to the poor nodal support and absence of gene sequence of the type species Gonostomum, a more robust phylogeny of this group still remains unresolved. The biometric data of the Italian population of Gonostomum strenuum overlap with those from other known populations. Both species were collected from the industrial area of Parona, in the framework of the "Soil Mapping, Lombardia" project in which, for the first time in Italy, soil ciliates were used as bioindicators of soil quality. © 2015 The Author(s) Journal of Eukaryotic Microbiology © 2015 International Society of Protistologists.

  8. 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.

  9. 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

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

    Science.gov (United States)

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

    2018-01-01

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

  11. 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

  12. The Karakum and Kyzylkum sand seas dynamics; mapping and palaeoclimatic interpretations

    Science.gov (United States)

    Maman, Shimrit; Blumberg, Dan G.; Tsoar, Haim; Porat, Naomi

    2015-04-01

    Sand seas are large basins in deserts that are mantled by wind-swept sand and that exhibit varying degrees of vegetation cover. Wilson (1973) was the first to globally map and classify sand seas. Beyond Wilson's maps, however, little research has been published regarding the Karakum and Kyzylkum sand seas of Central Asia. Wilson's maps delineate active ergs from inactive ergs based solely on precipitation. His assumption of annual average rainfall as a factor determining mobility vs. stability of sand seas is too simplistic and does not take into consideration other factors such as biogenic soil crusts and wind power, both of which are known to have major effects on the dynamics of sand dunes. Literature related to mapping and classifying the Central Asian ergs by remote sensing or sand sea classification state (stable/active) is lacking. Moreover, the palaeoclimatic significance of dunes in Central Asia is difficult to assess, as there has been few studies of dune stratigraphy and numerical ages are lacking. Optically stimulated luminescence (OSL) is a firm optical dating method that is used to determine the elapsed time since quartz grains were last exposed to sunlight, thus, their burial. Yet, absolute ages indicating mobilization and stabilization of these sands, are still inadequately known and are here under discussion. The broad concern of this research was to determine the dynamics of the Central Asian sand seas and study the palaeoclimatic changes that brought to their stabilization. As there are no reliable maps or aeolian discussion of these sands, establishment of a digital data base was initially conducted, focusing on identifying and mapping these sand seas. The vast area and inaccessibility make traditional mapping methods virtually impossible. A variety of space-borne imagery both optical and radar, with varying spectral and spatial resolutions was used. These images provided the basis for mapping sand distribution, dune forms, and vegetation cover

  13. Mapping out Map Libraries

    Directory of Open Access Journals (Sweden)

    Ferjan Ormeling

    2008-09-01

    Full Text Available Discussing the requirements for map data quality, map users and their library/archives environment, the paper focuses on the metadata the user would need for a correct and efficient interpretation of the map data. For such a correct interpretation, knowledge of the rules and guidelines according to which the topographers/cartographers work (such as the kind of data categories to be collected, and the degree to which these rules and guidelines were indeed followed are essential. This is not only valid for the old maps stored in our libraries and archives, but perhaps even more so for the new digital files as the format in which we now have to access our geospatial data. As this would be too much to ask from map librarians/curators, some sort of web 2.0 environment is sought where comments about data quality, completeness and up-to-dateness from knowledgeable map users regarding the specific maps or map series studied can be collected and tagged to scanned versions of these maps on the web. In order not to be subject to the same disadvantages as Wikipedia, where the ‘communis opinio’ rather than scholarship, seems to be decisive, some checking by map curators of this tagged map use information would still be needed. Cooperation between map curators and the International Cartographic Association ( ICA map and spatial data use commission to this end is suggested.

  14. Model Interpretation of Topological Spatial Analysis for the Visually Impaired (Blind Implemented in Google Maps

    Directory of Open Access Journals (Sweden)

    Marcelo Franco Porto

    2013-06-01

    Full Text Available The technological innovations promote the availability of geographic information on the Internet through Web GIS such as Google Earth and Google Maps. These systems contribute to the teaching and diffusion of geographical knowledge that instigates the recognition of the space we live in, leading to the creation of a spatial identity. In these products available on the Web, the interpretation and analysis of spatial information gives priority to one of the human senses: vision. Due to the fact that this representation of information is transmitted visually (image and vectors, a portion of the population is excluded from part of this knowledge because categories of analysis of geographic data such as borders, territory, and space can only be understood by people who can see. This paper deals with the development of a model of interpretation of topological spatial analysis based on the synthesis of voice and sounds that can be used by the visually impaired (blind.The implementation of a prototype in Google Maps and the usability tests performed are also examined. For the development work it was necessary to define the model of topological spatial analysis, focusing on computational implementation, which allows users to interpret the spatial relationships of regions (countries, states and municipalities, recognizing its limits, neighborhoods and extension beyond their own spatial relationships . With this goal in mind, several interface and usability guidelines were drawn up to be used by the visually impaired (blind. We conducted a detailed study of the Google Maps API (Application Programming Interface, which was the environment selected for prototype development, and studied the information available for the users of that system. The prototype was developed based on the synthesis of voice and sounds that implement the proposed model in C # language and in .NET environment. To measure the efficiency and effectiveness of the prototype, usability

  15. 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.

  16. Interpreting diel hysteresis between soil respiration and temperature

    Science.gov (United States)

    C. Phillips; N. Nickerson; D. Risk; B.J. Bond

    2011-01-01

    Increasing use of automated soil respiration chambers in recent years has demonstrated complex diel relationships between soil respiration and temperature that are not apparent from less frequent measurements. Soil surface flux is often lagged from soil temperature by several hours, which results in semielliptical hysteresis loops when surface flux is plotted as a...

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

    Science.gov (United States)

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

    2018-01-01

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

  18. 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.

  19. Soil erosion assessment and its correlation with landslide events using remote sensing data and GIS: a case study at Penang Island, Malaysia.

    Science.gov (United States)

    Pradhan, Biswajeet; Chaudhari, Amruta; Adinarayana, J; Buchroithner, Manfred F

    2012-01-01

    In this paper, an attempt has been made to assess, prognosis and observe dynamism of soil erosion by universal soil loss equation (USLE) method at Penang Island, Malaysia. Multi-source (map-, space- and ground-based) datasets were used to obtain both static and dynamic factors of USLE, and an integrated analysis was carried out in raster format of GIS. A landslide location map was generated on the basis of image elements interpretation from aerial photos, satellite data and field observations and was used to validate soil erosion intensity in the study area. Further, a statistical-based frequency ratio analysis was carried out in the study area for correlation purposes. The results of the statistical correlation showed a satisfactory agreement between the prepared USLE-based soil erosion map and landslide events/locations, and are directly proportional to each other. Prognosis analysis on soil erosion helps the user agencies/decision makers to design proper conservation planning program to reduce soil erosion. Temporal statistics on soil erosion in these dynamic and rapid developments in Penang Island indicate the co-existence and balance of ecosystem.

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

    Science.gov (United States)

    Ramirez-Lopez, Leonardo; Alexandre Dematte, Jose

    2010-05-01

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

  1. 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...

  2. 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.

  3. 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

  4. Partial least squares methods for spectrally estimating lunar soil FeO abundance: A stratified approach to revealing nonlinear effect and qualitative interpretation

    Science.gov (United States)

    Li, Lin

    2008-12-01

    Partial least squares (PLS) regressions were applied to lunar highland and mare soil data characterized by the Lunar Soil Characterization Consortium (LSCC) for spectral estimation of the abundance of lunar soil chemical constituents FeO and Al2O3. The LSCC data set was split into a number of subsets including the total highland, Apollo 16, Apollo 14, and total mare soils, and then PLS was applied to each to investigate the effect of nonlinearity on the performance of the PLS method. The weight-loading vectors resulting from PLS were analyzed to identify mineral species responsible for spectral estimation of the soil chemicals. The results from PLS modeling indicate that the PLS performance depends on the correlation of constituents of interest to their major mineral carriers, and the Apollo 16 soils are responsible for the large errors of FeO and Al2O3 estimates when the soils were modeled along with other types of soils. These large errors are primarily attributed to the degraded correlation FeO to pyroxene for the relatively mature Apollo 16 soils as a result of space weathering and secondary to the interference of olivine. PLS consistently yields very accurate fits to the two soil chemicals when applied to mare soils. Although Al2O3 has no spectrally diagnostic characteristics, this chemical can be predicted for all subset data by PLS modeling at high accuracies because of its correlation to FeO. This correlation is reflected in the symmetry of the PLS weight-loading vectors for FeO and Al2O3, which prove to be very useful for qualitative interpretation of the PLS results. However, this qualitative interpretation of PLS modeling cannot be achieved using principal component regression loading vectors.

  5. Apparent soil electrical conductivity in two different soil types

    Directory of Open Access Journals (Sweden)

    Wilker Nunes Medeiros

    Full Text Available ABSTRACT Mapping the apparent soil electrical conductivity (ECa has become important for the characterization of the soil variability in precision agriculture systems. Could the ECa be used to locate the soil sampling points for mapping the chemical and physical soil attributes? The objective of this work was to examine the relations between ECa and soil attributes in two fields presenting different soil textures. In each field, 50 sampling points were chosen using a path that presented a high variability of ECa obtained from a preliminary ECa map. At each sampling point, the ECa was measured in soil depths of 0-20, 0-40 and 0-60 cm. In addition, at each point, soil samples were collected for the determination of physical and chemical attributes in the laboratory. The ECa data obtained for different soil depths was very similar. A large number of significant correlations between ECa and the soil attributes were found. In the sandy clay loam texture field there was no correlation between ECa and organic matter or between ECa and soil clay and sand content. However, a significant positive correlation was shown for the remaining phosphorus. In the sandy loam texture field the ECa had a significant positive correlation with clay content and a significant negative correlation with sand content. The results suggest that the mapping of apparent soil electrical conductivity does not replace traditional soil sampling, however, it can be used as information to delimit regions in a field that have similar soil attributes.

  6. Remote sensing data applied to the evaluation of soil erosion caused by land-use. Ribeirao Anhumas Basin Area: A case study. [Brazil

    Science.gov (United States)

    Dejesusparada, N. (Principal Investigator); Dosanjosferreirapinto, S.; Kux, H. J. H.

    1980-01-01

    Formerly covered by a tropical forest, the study area was deforested in the early 40's for coffee plantation and cattle raising, which caused intense gully erosion problems. To develop a method to analyze the relationship between land use and soil erosion, visual interpretations of aerial photographs (scale 1:25.000), MSS-LANDSAT imagery (scale 1:250,000), as well as automatic interpretation of computer compatible tapes by IMAGE-100 system were carried out. From visual interpretation the following data were obtained: land use and cover tapes, slope classes, ravine frequency, and a texture sketch map. During field work, soil samples were collected for texture and X-ray analysis. The texture sketch map indicate that the areas with higher slope angles have a higher susceptibilty to the development of gullies. Also, the over carriage of pastureland, together with very friable lithologies (mainly sandstone) occuring in that area, seem to be the main factors influencing the catastrophic extension of ravines in the study site.

  7. 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.

  8. Geologic Interpretation of Data Sets Collected by Planetary Analog Geology Traverses and by Standard Geologic Field Mapping. Part 1; A Comparison Study

    Science.gov (United States)

    Eppler, Dean B.; Bleacher, Jacob F.; Evans, Cynthia A.; Feng, Wanda; Gruener, John; Hurwitz, Debra M.; Skinner, J. A., Jr.; Whitson, Peggy; Janoiko, Barbara

    2013-01-01

    Geologic maps integrate the distributions, contacts, and compositions of rock and sediment bodies as a means to interpret local to regional formative histories. Applying terrestrial mapping techniques to other planets is challenging because data is collected primarily by orbiting instruments, with infrequent, spatiallylimited in situ human and robotic exploration. Although geologic maps developed using remote data sets and limited "Apollo-style" field access likely contain inaccuracies, the magnitude, type, and occurrence of these are only marginally understood. This project evaluates the interpretative and cartographic accuracy of both field- and remote-based mapping approaches by comparing two 1:24,000 scale geologic maps of the San Francisco Volcanic Field (SFVF), north-central Arizona. The first map is based on traditional field mapping techniques, while the second is based on remote data sets, augmented with limited field observations collected during NASA Desert Research & Technology Studies (RATS) 2010 exercises. The RATS mission used Apollo-style methods not only for pre-mission traverse planning but also to conduct geologic sampling as part of science operation tests. Cross-comparison demonstrates that the Apollo-style map identifies many of the same rock units and determines a similar broad history as the field-based map. However, field mapping techniques allow markedly improved discrimination of map units, particularly unconsolidated surficial deposits, and recognize a more complex eruptive history than was possible using Apollo-style data. Further, the distribution of unconsolidated surface units was more obvious in the remote sensing data to the field team after conducting the fieldwork. The study raises questions about the most effective approach to balancing mission costs with the rate of knowledge capture, suggesting that there is an inflection point in the "knowledge capture curve" beyond which additional resource investment yields progressively

  9. Can Process Understanding Help Elucidate The Structure Of The Critical Zone? Comparing Process-Based Soil Formation Models With Digital Soil Mapping.

    Science.gov (United States)

    Vanwalleghem, T.; Román, A.; Peña, A.; Laguna, A.; Giráldez, J. V.

    2017-12-01

    There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties in the critical zone. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of traditional digital soil mapping versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

  10. 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

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

    Science.gov (United States)

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

    2017-12-01

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

  12. Mapping earthworm communities in Europe

    DEFF Research Database (Denmark)

    Rutgers, Michiel; Orgiazzi, Alberto; Gardi, Ciro

    Existing data sets on earthworm communities in Europe were collected, harmonized, modelled and depicted on a soil biodiversity map of Europe. Digital Soil Mapping was applied using multiple regressions relating relatively low density earthworm community data to soil characteristics, land use...

  13. 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,

  14. Combination of geo- pedo- and technogenic magnetic and geochemical signals in soil profiles - Diversification and its interpretation: A new approach.

    Science.gov (United States)

    Szuszkiewicz, Marcin; Łukasik, Adam; Magiera, Tadeusz; Mendakiewicz, Maria

    2016-07-01

    Magnetic and geochemical parameters of soils are determined with respect to geology, pedogenesis and anthropopression. Depending on local conditions these factors affect magnetic and geochemical signals simultaneously or in various configurations. We examined four type of soils (Entic Podzol, Eutric Cambisol, Humic Cambisol and Dystric Cambisol) developed on various bedrock (the Tumlin Sandstone, basaltoid, amphibolite and serpentinite, respectively). Our primary aim was to characterize the origin and diversification of the magnetic and geochemical signal in soils in order to distinguish the most reliable methods for correct interpretation of measured parameters. Presented data include selected parameters, both magnetic (mass magnetic susceptibility - χ, frequency-dependent magnetic susceptibility - χfd and thermomagnetic susceptibility measurement - TSM), and geochemical (selected heavy metal contents: Co, Cr, Cu, Fe, Mn, Ni, Pb, Zn). Additionally, the enrichment factor (EF) and index of geoaccumulation (Igeo) were calculated. Our results suggest the following: (1) the χ/Fe ratio may be a reliable indicator for determining changes of magnetic signal origin in soil profiles; (2) magnetic and geochemical signals are simultaneously higher (the increment of χ and lead and zinc was noted) in topsoil horizons because of the deposition of technogenic magnetic particles (TMPs); (3) EF and Igeo evaluated for lead and zinc unambiguously showed anthropogenic influence in terms of increasing heavy metal contents in topsoil regardless of bedrock or soil type; (4) magnetic susceptibility measurements supported by TSM curves for soil samples of different genetic horizons are a helpful tool for interpreting the origin and nature of the mineral phases responsible for the changes of magnetic susceptibility values. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. 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 km 2 ). 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 226 Ra, 232 Th and 40 K. 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 226 Ra, 232 Th and 40 K 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.

  16. 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.

  17. Are catenas relevant to soil maps and pedology in Iowa in the twenty-first century?

    Science.gov (United States)

    Richter, Jennifer; Burras, C. Lee

    2014-05-01

    The modern intensity of agriculture brings to question whether anthropogenic impacts on soil profiles and catenas in agricultural areas are minor or dominant pedogenic influences. Answering this question is crucial to evaluating the modern relevance of historic soil maps, which use the traditional catena model as their foundation. This study quantifies the magnitude of change within the soil profile and across the landscape that result from decadal scale agriculture. Four benchmark catenas located on the Des Moines Lobe in Iowa, USA, were re-examined to determine the changes that occurred in the soils over the intervening years. The first site was initially studied by Walker and Ruhe in the mid 1960's. Burras and Scholtes initially examined the second catena in the early 1980's, while the remaining two catenas were first studied in the early 1990's by Steinwand and Fenton, and the late 1990's by Konen. Thus, the catenas were re-sampled for this study roughly 50, 30, 20, and 15 years, respectively, after the initial study. In this part of Iowa, continuous row crop agriculture (primarily Zea mays and Glycine max) and extensive subsurface drainage are very common. All study sites are closed-basin catenas located within 40 km of each other with a parent material of Late Wisconsinan glacial till. Soil cores to a depth of approximately two meters were taken with a truck mounted Giddings hydraulic soil sampler at 27 to 30 meter intervals along one transect for each of the four catenas, resulting in a total of forty-eight cores. The soil cores were then brought to the laboratory where soil descriptions and laboratory analyses are being completed. Soil descriptions include information about horizon type and depth, Munsell color, texture, rock fragments, structure, consistence, clay films, roots, pores, presence of carbonates, and redoximorphic features. Laboratory analyses include bulk density, particle size, total carbon and nitrogen content, cation exchange capacity

  18. 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

  19. Image Analysis for Facility Siting: a Comparison of Lowand High-altitude Image Interpretability for Land Use/land Cover Mapping

    Science.gov (United States)

    Borella, H. M.; Estes, J. E.; Ezra, C. E.; Scepan, J.; Tinney, L. R.

    1982-01-01

    For two test sites in Pennsylvania the interpretability of commercially acquired low-altitude and existing high-altitude aerial photography are documented in terms of time, costs, and accuracy for Anderson Level II land use/land cover mapping. Information extracted from the imagery is to be used in the evaluation process for siting energy facilities. Land use/land cover maps were drawn at 1:24,000 scale using commercially flown color infrared photography obtained from the United States Geological Surveys' EROS Data Center. Detailed accuracy assessment of the maps generated by manual image analysis was accomplished employing a stratified unaligned adequate class representation. Both 'area-weighted' and 'by-class' accuracies were documented and field-verified. A discrepancy map was also drawn to illustrate differences in classifications between the two map scales. Results show that the 1:24,000 scale map set was more accurate (99% to 94% area-weighted) than the 1:62,500 scale set, especially when sampled by class (96% to 66%). The 1:24,000 scale maps were also more time-consuming and costly to produce, due mainly to higher image acquisition costs.

  20. Manifestation of a neuro-fuzzy model to produce landslide susceptibility map using remote sensing data derived parameters

    Science.gov (United States)

    Pradhan, Biswajeet; Lee, Saro; Buchroithner, Manfred

    Landslides are the most common natural hazards in Malaysia. Preparation of landslide suscep-tibility maps is important for engineering geologists and geomorphologists. However, due to complex nature of landslides, producing a reliable susceptibility map is not easy. In this study, a new attempt is tried to produce landslide susceptibility map of a part of Cameron Valley of Malaysia. This paper develops an adaptive neuro-fuzzy inference system (ANFIS) based on a geographic information system (GIS) environment for landslide susceptibility mapping. To ob-tain the neuro-fuzzy relations for producing the landslide susceptibility map, landslide locations were identified from interpretation of aerial photographs and high resolution satellite images, field surveys and historical inventory reports. Landslide conditioning factors such as slope, plan curvature, distance to drainage lines, soil texture, lithology, and distance to lineament were extracted from topographic, soil, and lineament maps. Landslide susceptible areas were analyzed by the ANFIS model and mapped using the conditioning factors. Furthermore, we applied various membership functions (MFs) and fuzzy relations to produce landslide suscep-tibility maps. The prediction performance of the susceptibility map is checked by considering actual landslides in the study area. Results show that, triangular, trapezoidal, and polynomial MFs were the best individual MFs for modelling landslide susceptibility maps (86

  1. Computer analysis to the geochemical interpretation of soil and stream sediment data in an area of Southern Uruguay

    International Nuclear Information System (INIS)

    Spangenberg, J.

    2010-01-01

    In southern Uruguay there are several known occurrences of base metal sulphide mineralization within an area of Precambrian volcanic sedimentary rocks. Regional geochemical stream sediment reconnaissance surveys revealed new polymetallic anomalies in the same stratigraphic zone. Geochemical interpretation of multi-element data from a soil and stream sediment survey carried out in one of these anomalous areas is presented.

  2. 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.

  3. 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

  4. How to interpret rheometry, an innovative technique in soil physicochemistry, correctly - explained by critical users

    Science.gov (United States)

    Holthusen, Dörthe; Paulus, Eloi; Pértile, Patricia; Reichert, José Miguel; José Reinert, Dalvan; Horn, Rainer

    2015-04-01

    scales. Transferability to field situations is given due to the character of the mechanic stress which equals those appearing e.g. under a tractor tire exerting vibrating, compressing and shearing forces. Unfortunately, the multiple results of this single test can impede the use of rheometry as their interpretation requires intensive data analysis. By pointing out the single results and their meaning for soil structure, we aim at facilitating the use of rheometry. We also suggest moderate alterations to take into account more strongly the vertical compression of soil for a more comprehensive implementation of a micro shear test. Additionally, we point out further uses of a rheometer in soil physics, which is the viscosity, i. e. the ability of a fluid to penetrate into a porous system and to be relocated within. Herewith, quite complex fluid characteristics, e.g. of animal manure, anaerobic digestates, but also pesticides in aqueous solution, root mucilage etc. can be determined and applied as improved, because more detailed, model parameters in soil water transport. As a conclusion, our contribution aims at further promoting a promising method for investigating the fundamentals of soil physics at the interface to soil chemistry.

  5. Interpretation, compilation and field verification procedures in the CARETS project

    Science.gov (United States)

    Alexander, Robert H.; De Forth, Peter W.; Fitzpatrick, Katherine A.; Lins, Harry F.; McGinty, Herbert K.

    1975-01-01

    The production of the CARETS map data base involved the development of a series of procedures for interpreting, compiling, and verifying data obtained from remote sensor sources. Level II land use mapping from high-altitude aircraft photography at a scale of 1:100,000 required production of a photomosaic mapping base for each of the 48, 50 x 50 km sheets, and the interpretation and coding of land use polygons on drafting film overlays. CARETS researchers also produced a series of 1970 to 1972 land use change overlays, using the 1970 land use maps and 1972 high-altitude aircraft photography. To enhance the value of the land use sheets, researchers compiled series of overlays showing cultural features, county boundaries and census tracts, surface geology, and drainage basins. In producing Level I land use maps from Landsat imagery, at a scale of 1:250,000, interpreters overlaid drafting film directly on Landsat color composite transparencies and interpreted on the film. They found that such interpretation involves pattern and spectral signature recognition. In studies using Landsat imagery, interpreters identified numerous areas of change but also identified extensive areas of "false change," where Landsat spectral signatures but not land use had changed.

  6. Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks

    Science.gov (United States)

    Miller, B. A.; Koszinski, S.; Wehrhan, M.; Sommer, M.

    2015-03-01

    The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which is to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m-2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.

  7. A WFS-SVM Model for Soil Salinity Mapping in Keriya Oasis, Northwestern China Using Polarimetric Decomposition and Fully PolSAR Data

    Directory of Open Access Journals (Sweden)

    Ilyas Nurmemet

    2018-04-01

    Full Text Available Timely monitoring and mapping of salt-affected areas are essential for the prevention of land degradation and sustainable soil management in arid and semi-arid regions. The main objective of this study was to develop Synthetic Aperture Radar (SAR polarimetry techniques for improved soil salinity mapping in the Keriya Oasis in the Xinjiang Uyghur Autonomous Region (Xinjiang, China, where salinized soil appears to be a major threat to local agricultural productivity. Multiple polarimetric target decomposition, optimal feature subset selection (wrapper feature selector, WFS, and support vector machine (SVM algorithms were used for optimal soil salinization classification using quad-polarized PALSAR-2 data. A threefold exercise was conducted. First, 16 polarimetric decomposition methods were implemented and a wide range of polarimetric parameters and SAR discriminators were derived in order to mine hidden information in PolSAR data. Second, the optimal polarimetric feature subset that constitutes 19 polarimetric elements was selected adopting the WFS approach; optimum classification parameters were identified, and the optimal SVM classification model was obtained by employing a cross-validation method. Third, the WFS-SVM classification model was constructed, optimized, and implemented based on the optimal match of polarimetric features and optimum classification parameters. Soils with different salinization degrees (i.e., highly, moderately and slightly salinized soils were extracted. Finally, classification results were compared with the Wishart supervised classification and conventional SVM classification to examine the performance of the proposed method for salinity mapping. Detailed field investigations and ground data were used for the validation of the adopted methods. The overall accuracy and kappa coefficient of the proposed WFS-SVM model were 87.57% and 0.85, respectively that were much higher than those obtained by the Wishart supervised

  8. 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...

  9. Radon flux maps for the Netherlands and Europe using terrestrial gamma radiation derived from soil radionuclides

    Science.gov (United States)

    Manohar, S. N.; Meijer, H. A. J.; Herber, M. A.

    2013-12-01

    Naturally occurring radioactive noble gas, radon (222Rn) is a valuable tracer to study atmospheric processes and to validate global chemical transport models. However, the use of radon as a proxy in atmospheric and climate research is limited by the uncertainties in the magnitude and distribution of the radon flux density over the Earth's surface. Terrestrial gamma radiation is a useful proxy for generating radon flux maps. A previously reported radon flux map of Europe used terrestrial gamma radiation extracted from automated radiation monitoring networks. This approach failed to account for the influence of local artificial radiation sources around the detector, leading to under/over estimation of the reported radon flux values at different locations. We present an alternative approach based on soil radionuclides which enables us to generate accurate radon flux maps with good confidence. Firstly, we present a detailed comparison between the terrestrial gamma radiation obtained from the National Radiation Monitoring network of the Netherlands and the terrestrial gamma radiation calculated from soil radionuclides. Extending further, we generated radon flux maps of the Netherlands and Europe using our proposed approach. The modelled flux values for the Netherlands agree reasonably well with the two observed direct radon flux measurements (within 2σ level). On the European scale, we find that the observed radon flux values are higher than our modelled values and we introduce a correction factor to account for this difference. Our approach discussed in this paper enables us to develop reliable and accurate radon flux maps in countries with little or no information on radon flux values.

  10. 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.

  11. Image analysis for facility siting: a comparison of low- and high-altitude image interpretability for land use/land cover mapping

    International Nuclear Information System (INIS)

    Borella, H.M.; Estes, J.E.; Ezra, C.E.; Scepan, J.; Tinney, L.R.

    1982-01-01

    For two test sites in Pennsylvania the interpretability of commercially acquired low-altitude and existing high-altitude aerial photography are documented in terms of time, costs, and accuracy for Anderson Level II land use/land cover mapping. Information extracted from the imagery is to be used in the evaluation process for siting energy facilities. Land use/land cover maps were drawn at 1:24,000 scale using commercially flown color infrared photography obtained from the United States Geological Surveys' EROS Data Center. Detailed accuracy assessment of the maps generated by manual image analysis was accomplished employing a stratified unaligned adequate class representation. Both are-weighted and by-class accuracies were documented and field-verified. A discrepancy map was also drawn to illustrate differences in classifications between the two map scales. Results show that the 1:24,000 scale map set was accurate (99% to 94% area-weighted) than the 1:62,500 scale set, especially when sampled by class (96% to 66%). The 1:24,000 scale maps were also more time-consuming and costly to produce, due mainly to higher image acquisition costs

  12. GEMAS: Unmixing magnetic properties of European agricultural soil

    Science.gov (United States)

    Fabian, Karl; Reimann, Clemens; Kuzina, Dilyara; Kosareva, Lina; Fattakhova, Leysan; Nurgaliev, Danis

    2016-04-01

    High resolution magnetic measurements provide new methods for world-wide characterization and monitoring of agricultural soil which is essential for quantifying geologic and human impact on the critical zone environment and consequences of climatic change, for planning economic and ecological land use, and for forensic applications. Hysteresis measurements of all Ap samples from the GEMAS survey yield a comprehensive overview of mineral magnetic properties in European agricultural soil on a continental scale. Low (460 Hz), and high frequency (4600 Hz) magnetic susceptibility k were measured using a Bartington MS2B sensor. Hysteresis properties were determined by a J-coercivity spectrometer, built at the paleomagnetic laboratory of Kazan University, providing for each sample a modified hysteresis loop, backfield curve, acquisition curve of isothermal remanent magnetization, and a viscous IRM decay spectrum. Each measurement set is obtained in a single run from zero field up to 1.5 T and back to -1.5 T. The resulting data are used to create the first continental-scale maps of magnetic soil parameters. Because the GEMAS geochemical atlas contains a comprehensive set of geochemical data for the same soil samples, the new data can be used to map magnetic parameters in relation to chemical and geological parameters. The data set also provides a unique opportunity to analyze the magnetic mineral fraction of the soil samples by unmixing their IRM acquisition curves. The endmember coefficients are interpreted by linear inversion for other magnetic, physical and chemical properties which results in an unprecedented and detailed view of the mineral magnetic composition of European agricultural soils.

  13. Soil Fertility Assessment and Mapping of Agricultural Research Station, Jaubari, Illam, Nepal

    Directory of Open Access Journals (Sweden)

    Dinesh Khadka

    2017-08-01

    Full Text Available Soil fertility evaluation is a prerequisite factor for sustainable planning of a particular region. Considering this, a study was conducted to determine the soil fertility status of the Agricultural Research Station, Jaubari, Illam, Nepal. In total, 78 soil samples were collected using soil sampling auger randomly from a depth of 0-20 cm. The texture, pH, OM, N, P2O5, K2O, Ca, Mg, S, B, Fe, Zn, Cu and Mn status of the samples were analyzed in the laboratory of Soil Science Division, Khumaltar by following standard analytical methods. The soil fertility maps of the observed parameters were prepared through Arc-GIS 10.1 software. The observed data revealed that soil was brown (10YR 4/3, dark grayish brown (10YR 4/2, dark yellowish brown (10YR 4/4 and yellowish brown (10YR 5/6 in colour, and the structure was granular. Similarly, the sand, silt and clay content were 53.84±1.06%, 34.34±0.83% and 11.82±0.47%, respectively and were indicated as sandy loam and loam in texture. The soil was very acidic (pH 3.85±0.04, and very low in available boron (0.26±0.06mg/kg and available sulphur (0.59±0.15mg/kg. The available calcium (188.7±31.30mg/kg, available magnesium (50.98±5.0mg/kg and available manganese (5.16±0.90mg/kg were low. Likewise, available potassium (110.91±7.30mg/kg, available zinc (1.19±0.31mg/kg and available copper (0.95±0.05mg/kg content were medium. Similarly, organic matter (7.88±0.32%, total nitrogen (0.27±0.01% and available phosphorus (36.53±5.66mg/kg were high, and available iron (39.5±2.17 mg/kg was very high.  International Journal of EnvironmentVolume-6, Issue-3, Jun-Aug 2017, page: 46-70

  14. Seismic Microzonation of Breginjski Kot (NW Slovenia) Based on Detailed Engineering Geological Mapping

    Science.gov (United States)

    2013-01-01

    Breginjski kot is among the most endangered seismic zones in Slovenia with the seismic hazard assessed to intensity IX MSK and the design ground acceleration of 0.250 g, both for 500-year return period. The most destructive was the 1976 Friuli Mw = 6.4 earthquake which had maximum intensity VIII-IX. Since the previous microzonation of the area was based solely on the basic geological map and did not include supplementary field research, we have performed a new soil classification of the area. First, a detailed engineering geological mapping in scale 1 : 5.000 was conducted. Mapped units were described in detail and some of them interpreted anew. Stiff sites are composed of hard to medium-hard rocks which were subjected to erosion mainly evoked by glacial and postglacial age. At that time a prominent topography was formed and different types of sediments were deposited in valleys by mass flows. A distinction between sediments and weathered rocks, their exact position, and thickness are of significant importance for microzonation. On the basis of geological mapping, a soil classification was carried out according to the Medvedev method (intensity increments) and the Eurocode 8 standard (soil factors) and two microzonation maps were prepared. The bulk of the studied area is covered by soft sediments and nine out of ten settlements are situated on them. The microzonation clearly points out the dependence of damage distribution in the case of 1976 Friuli earthquake to local site effects. PMID:24453884

  15. Estimating soil water-holding capacities by linking the Food and Agriculture Organization Soil map of the world with global pedon databases and continuous pedotransfer functions

    Science.gov (United States)

    Reynolds, C. A.; Jackson, T. J.; Rawls, W. J.

    2000-12-01

    Spatial soil water-holding capacities were estimated for the Food and Agriculture Organization (FAO) digital Soil Map of the World (SMW) by employing continuous pedotransfer functions (PTF) within global pedon databases and linking these results to the SMW. The procedure first estimated representative soil properties for the FAO soil units by statistical analyses and taxotransfer depth algorithms [Food and Agriculture Organization (FAO), 1996]. The representative soil properties estimated for two layers of depths (0-30 and 30-100 cm) included particle-size distribution, dominant soil texture, organic carbon content, coarse fragments, bulk density, and porosity. After representative soil properties for the FAO soil units were estimated, these values were substituted into three different pedotransfer functions (PTF) models by Rawls et al. [1982], Saxton et al. [1986], and Batjes [1996a]. The Saxton PTF model was finally selected to calculate available water content because it only required particle-size distribution data and results closely agreed with the Rawls and Batjes PTF models that used both particle-size distribution and organic matter data. Soil water-holding capacities were then estimated by multiplying the available water content by the soil layer thickness and integrating over an effective crop root depth of 1 m or less (i.e., encountered shallow impermeable layers) and another soil depth data layer of 2.5 m or less.

  16. 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.

    Directory of Open Access Journals (Sweden)

    Gerald Forkuor

    Full Text Available 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

  17. A methodology for small scale rural land use mapping in semi-arid developing countries using orbital imagery. Part 6: A low-cost method for land use mapping using simple visual techniques of interpretation. [Spain

    Science.gov (United States)

    Vangenderen, J. L. (Principal Investigator); Lock, B. F.

    1976-01-01

    The author has identified the following significant results. It was found that color composite transparencies and monocular magnification provided the best base for land use interpretation. New methods for determining optimum sample sizes and analyzing interpretation accuracy levels were developed. All stages of the methodology were assessed, in the operational sense, during the production of a 1:250,000 rural land use map of Murcia Province, Southeast Spain.

  18. 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).

  19. Environmental sensibility maps of pipelines rows; Mapas de sensibilidade ambiental para faixas de dutos terrestres

    Energy Technology Data Exchange (ETDEWEB)

    Oliveira, Wilson J. de [PETROBRAS Engenharia, Rio de Janeiro, RJ (Brazil). Engenharia de Avaliacao Ambiental IEGEN/EGE/EAMB; Ferreira Filho, Aluisio Teles; Ferreira, Vanderlei Cardoso [TRANSPETRO - PETROBRAS Transporte S.A., Rio de Janeiro, RJ (Brazil). SMS - Seguranca, Meio Ambiente e Saude; Braun, Oscar P.G.; Pereira, Junior, Edson Rodrigues [Geodatum, Rio de Janeiro, RJ (Brazil)

    2003-07-01

    To subsidize its contingency plans for oil leaks, TRANSPETRO, subsidiary of PETROBRAS, set up an internal program with a big extension to obtain Environmental Sensibility Maps over a strip of twenty kilometers of width along more than five thousand kilometers of pipelines. Due to the pioneer characteristic of these natural survey (thematic cartography) it was opted a first approach for integration of this information in 1:50.000 scale. Based on a Geographical Information System (GIS), it was opted the supervised geo processing resources, compiling, firstly, the elevation, soil and geological maps for generation of the physical environment vulnerability units. Using a combination by weight average, ten vulnerability units were generated and were improved through aggregation in five units to decrease the complexity of the representation in map. These classes represent the combinations of variables of the physical environment that can be recognized by theirs corresponding landscapes. Based on interpretation of orbital LANDSAT TM images, aided by verifications in aerial photograph and a systematic survey of notable points of environmental observation (PVAs) along the pipelines, it was elaborated a general map of soil use and vegetable coverage. The classes of this theme were combined with the classes of physical vulnerability environment to generate five classes of Environmental Sensibility (Environmental Sensibility Maps). Over this theme, were attributed the representations of the main types of vegetable coverage and occupation of the soil, as well as the fauna and the other social-economics aspects, obtaining therefore a map with all the essential controller information of the environmental protection measures. (author)

  20. New morphological mapping and interpretation of ejecta deposits from Orientale Basin on the Moon

    Science.gov (United States)

    Morse, Zachary R.; Osinski, Gordon R.; Tornabene, Livio L.

    2018-01-01

    Orientale Basin is one of the youngest and best-preserved multi-ring impact basins in the Solar System. The structure is ∼950 km across and is located on the western edge of the nearside of the Moon. The interior of the basin, which possesses three distinct rings and a post-impact mare fill, has been studied extensively using modern high-resolution datasets. Exterior to these rings, Orientale has an extensive ejecta blanket that extends out radially for at least 800 km from the basin rim in all directions and covers portions of both the nearside and farside of the Moon. These deposits, known as the Hevelius Formation, were first mapped using photographic data from the Lunar Orbiter IV probe. In this study, we map in detail the morphology of each distinct facies observed within the Orientale ejecta blanket using high resolution Lunar Reconnaissance Orbiter (LRO) Wide Angle Camera (WAC) and Narrow Angle Camera (NAC) images and Lunar Orbiter Laser Altimeter (LOLA) elevation data. We identified 5 unique facies within the ejecta blanket. Facies A is identified as a region of hummocky plains located in a low-lying topographic region between the Outer Rook and Cordillera rings. This facies is interpreted to be a mix of crater-derived impact melt and km-scale blocks of ballistic ejecta and host rock broken up during the modification stage and formation of the Cordillera ring. Facies B is an inner facies marked by radial grooves extending outward from the direction of the basin center. This facies is interpreted as the continuous ballistic ejecta blanket. Facies C consists of inner and outer groupings of flat smooth-surfaced deposits isolated in local topographic lows. Facies D displays characteristic sinuous ridges and lobate extensions. Facies C and D are interpreted to be impact melt-rich materials, which manifest as flows and ponds. Our observations suggest that these facies were emplaced subsequent to the ballistic ejecta blanket - most likely during the modification

  1. Mapping Urban Social Divisions

    Directory of Open Access Journals (Sweden)

    Susan Ball

    2010-05-01

    Full Text Available Against the background of increased levels of interest in space and images beyond the field of geography, this article (re- introduces earlier work on the semiotics of maps undertaken by geographers in the 1960s. The data limitations, purpose and cultural context in which a user interprets a map's codes and conventions are highlighted in this work, which remains relevant to the interpretation of maps—new and old—forty years later. By means of drawing on geography's contribution to the semiotics of maps, the article goes on to examine the concept of urban social divisions as represented in map images. Using a small number of map images, including two of the most widely known maps of urban social division in Europe and North America, the roles of context, data and purpose in the production and interpretation of maps are discussed. By presenting the examples chronologically the article shows that although advances in data collection and manipulation have allowed researchers to combine different social variables in maps of social division, and to interact with map images, work by geographers on the semiotics of maps is no less relevant today than when it was first proposed forty years ago. URN: urn:nbn:de:0114-fqs1002372

  2. Landslide susceptibility mapping using a neuro-fuzzy

    Science.gov (United States)

    Lee, S.; Choi, J.; Oh, H.

    2009-12-01

    This paper develops and applied an adaptive neuro-fuzzy inference system (ANFIS) based on a geographic information system (GIS) environment using landslide-related factors and location for landslide susceptibility mapping. A neuro-fuzzy system is based on a fuzzy system that is trained by a learning algorithm derived from the neural network theory. The learning procedure operates on local information, and causes only local modifications in the underlying fuzzy system. The study area, Boun, suffered much damage following heavy rain in 1998 and was selected as a suitable site for the evaluation of the frequency and distribution of landslides. Boun is located in the central part of Korea. Landslide-related factors such as slope, soil texture, wood type, lithology, and density of lineament were extracted from topographic, soil, forest, and lineament maps. Landslide locations were identified from interpretation of aerial photographs and field surveys. Landslide-susceptible areas were analyzed by the ANFIS method and mapped using occurrence factors. In particular, we applied various membership functions (MFs) and analysis results were verified using the landslide location data. The predictive maps using triangular, trapezoidal, and polynomial MFs were the best individual MFs for modeling landslide susceptibility maps (84.96% accuracy), proving that ANFIS could be very effective in modeling landslide susceptibility mapping. Various MFs were used in this study, and after verification, the difference in accuracy according to the MFs was small, between 84.81% and 84.96%. The difference was just 0.15% and therefore the choice of MFs was not important in the study. Also, compared with the likelihood ratio model, which showed 84.94%, the accuracy was similar. Thus, the ANFIS could be applied to other study areas with different data and other study methods such as cross-validation. The developed ANFIS learns the if-then rules between landslide-related factors and landslide

  3. Fracture mapping in clays: the design and application of a mobile gas geochemistry laboratory for the analysis of soil gases

    International Nuclear Information System (INIS)

    Gregory, R.G.

    1988-02-01

    Integrated soil gas analyses for helium, radon, carbon dioxide, oxygen and organic gases allow the accurate interpretation of soil gas signatures as indicators of underlying structure. The most important features observed in the patterns of soil gas behaviour are large variations over faults and fractures. Structures such as these provide channelways for fluid movement in the upper crust. The construction of a mobile gas geochemistry laboratory for the analysis of soil gases at field investigation sites, and the subsequent trials carried out to evaluate the laboratory, clearly show that the soil gas investigation technique is accurate and viable as an independent site investigation method for the study of fracturing and groundwater movement around potential waste repository sites. (author)

  4. Multi-temporal mapping of a large, slow-moving earth flow for kinematic interpretation

    Science.gov (United States)

    Guerriero, Luigi; Coe, Jeffrey A.; Revellino, Paola; Guadagno, Francesco M.

    2014-01-01

    Periodic movement of large, thick landslides on discrete basal surfaces produces modifications of the topographic surface, creates faults and folds, and influences the locations of springs, ponds, and streams (Baum, et al., 1993; Coe et al., 2009). The geometry of the basal-slip surface, which can be controlled by geological structures (e.g., fold axes, faults, etc.; Revellino et al., 2010; Grelle et al., 2011), and spatial variation in the rate of displacement, are responsible for differential deformation and kinematic segmentation of the landslide body. Thus, large landslides are often composed of several distinct kinematic elements. Each element represents a discrete kinematic domain within the main landslide that is broadly characterized by stretching (extension) of the upper part of the landslide and shortening (compression) near the landslide toe (Baum and Fleming, 1991; Guerriero et al., in review). On the basis of this knowledge, we used photo interpretive and GPS field mapping methods to map structures on the surface of the Montaguto earth flow in the Apennine Mountains of southern Italy at a scale of 1:6,000. (Guerriero et al., 2013a; Fig.1). The earth flow has been periodically active since at least 1954. The most extensive and destructive period of activity began on April 26, 2006, when an estimated 6 million m3 of material mobilized, covering and closing Italian National Road SS90, and damaging residential structures (Guerriero et al., 2013b). Our maps show the distribution and evolution of normal faults, thrust faults, strike-slip faults, flank ridges, and hydrological features at nine different dates (October, 1954; June, 1976; June, 1991; June, 2003; June, 2005; May, 2006; October, 2007; July, 2009; and March , 2010) between 1954 and 2010. Within the earth flow we recognized several kinematic elements and associated structures (Fig.2a). Within each kinematic element (e.g. the earth flow neck; Fig.2b), the flow velocity was highest in the middle, and

  5. High resolution Slovak Bouguer gravity anomaly map and its enhanced derivative transformations: new possibilities for interpretation of anomalous gravity fields

    Science.gov (United States)

    Pašteka, Roman; Zahorec, Pavol; Kušnirák, David; Bošanský, Marián; Papčo, Juraj; Szalaiová, Viktória; Krajňák, Martin; Ivan, Marušiak; Mikuška, Ján; Bielik, Miroslav

    2017-06-01

    The paper deals with the revision and enrichment of the present gravimetric database of the Slovak Republic. The output of this process is a new version of the complete Bouguer anomaly (CBA) field on our territory. Thanks to the taking into account of more accurate terrain corrections, this field has significantly higher quality and higher resolution capabilities. The excellent features of this map will allow us to re-evaluate and improve the qualitative interpretation of the gravity field when researching the structural and tectonic geology of the Western Carpathian lithosphere. In the contribution we also analyse the field of the new CBA based on the properties of various transformed fields - in particular the horizontal gradient, which by its local maximums defines important density boundaries in the lateral direction. All original and new transformed maps make a significant contribution to improving the geological interpretation of the CBA field. Except for the horizontal gradient field, we are also interested in a new special transformation of TDXAS, which excellently separates various detected anomalies of gravity field and improves their lateral delimitation.

  6. Soil functional types: surveying the biophysical dimensions of soil security

    Science.gov (United States)

    Cécillon, Lauric; Barré, Pierre

    2015-04-01

    climate) for a particular soil-provided ecosystem service (e.g. climate regulation)". One SFT can thus include several soil types having the same functionality for a particular soil-provided ES. Another consequence is that SFT maps for two different ES may not superimpose over the same area, since some soils may fall in the same SFT for a service and in different SFT for another one. Soil functional types could be assessed and monitored in space and time by a combination of soil functional traits that correspond to inherent and manageable properties of soils. Their metrology would involve either classic (pedological observations) or advanced (molecular ecology, spectrometry, geophysics) tools. SFT could be studied and mapped at all scales, depending on the purpose of the soil security assessment (e.g. global climate modeling, land planning and management, biodiversity conservation). Overall, research is needed to find a pathway from soil pedological maps to SFT maps which would yield important benefits towards the assessment and monitoring of soil security. Indeed, this methodology would allow (i) reducing the spatial uncertainty on the assessment of ES; (ii) identifying and mapping multifunctional soils, which may be the most important soil resource to preserve. References [1] McBratney et al., 2014. Geoderma 213:203-213. [2] Droogers P, Bouma J, 1997. SSSAJ 61:1704-1710.

  7. Mapping Erosion Risk in California's Rangelands Using the Universal Soil Loss Equation (USLE)

    Science.gov (United States)

    Salls, W. B.; O'Geen, T. T.

    2015-12-01

    Soil loss constitutes a multi-faceted problem for agriculture: in addition to reducing soil fertility and crop yield, it compromises downstream water quality. Sediment itself is a major issue for aquatic ecosystems, but also serves as a vector for transporting nutrients, pesticides, and pathogens. Rangelands are thought to be a contributor to water quality degradation in California, particularly in the northern Coast Range. Though total maximum daily loads (TMDLs) have been imposed in some watersheds, and countless rangeland water quality outreach activities have been conducted, the connection between grazing intensity recommendations and changes in water quality is poorly understood at the state level. This disconnect gives rise to poorly informed regulations and discourages adoption of best management practices by ranchers. By applying the Universal Soil Loss Equation (USLE) at a statewide scale, we highlighted areas most prone to erosion. We also investigated how two different grazing intensity scenarios affect modeled soil loss. Geospatial data layers representing the USLE parameters—rainfall erosivity, soil erodibility, slope length and steepness, and cover—were overlaid to model annual soil loss. Monitored suspended sediment data from a small North Coast watershed with grazing as the predominant land use was used to validate the model. Modeled soil loss values were nearly one order of magnitude higher than monitored values; average soil loss feeding the downstream-most site was modeled at 0.329 t ha-1 yr-1, whereas storm-derived sediment passing the site over two years was calculated to be 0.037 t ha-1 yr-1. This discrepancy may stem from the fact that the USLE models detached sediment, whereas stream monitoring reflects sediment detached and subsequently transported to the waterway. Preliminary findings from the statewide map support the concern that the North Coast is particularly at risk given its combination of intense rain, erodible soils, and

  8. Issues related to interpretation of space imagery

    Energy Technology Data Exchange (ETDEWEB)

    Alferenok, A V; Przhiyalgovskii, Ye S

    1981-01-01

    A method for interpreting remotely derived data of various generalization levels (e.g. the northern section of the Chu-Sarysuiskaya basin) that suggests use of a uniform legend for interpretation of maps.

  9. 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

  10. The value of soil respiration measurements for interpreting and modeling terrestrial carbon cycling

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, Claire L.; Bond-Lamberty, Ben; Desai, Ankur R.; Lavoie, Martin; Risk, Dave; Tang, Jianwu; Todd-Brown, Katherine; Vargas, Rodrigo

    2016-11-16

    A recent acceleration of model-data synthesis activities has leveraged many terrestrial carbon (C) datasets, but utilization of soil respiration (RS) data has not kept pace with other types such as eddy covariance (EC) fluxes and soil C stocks. Here we argue that RS data, including non-continuous measurements from survey sampling campaigns, have unrealized value and should be utilized more extensively and creatively in data synthesis and modeling activities. We identify three major challenges in interpreting RS data, and discuss opportunities to address them. The first challenge is that when RS is compared to ecosystem respiration (RECO) measured from EC towers, it is not uncommon to find substantial mismatch, indicating one or both flux methodologies are unreliable. We argue the most likely cause of mismatch is unreliable EC data, and there is an unrecognized opportunity to utilize RS for EC quality control. The second challenge is that RS integrates belowground heterotrophic (RH) and autotrophic (RA) activity, whereas modelers generally prefer partitioned fluxes, and few models include an explicit RS output. Opportunities exist to use the total RS flux for data assimilation and model benchmarking methods rather than less-certain partitioned fluxes. Pushing for more experiments that not only partition RS but also monitor the age of RA and RH, as well as for the development of belowground RA components in models, would allow for more direct comparison between measured and modeled values. The third challenge is that soil respiration is generally measured at a very different resolution than that needed for comparison to EC or ecosystem- to global-scale models. Measuring soil fluxes with finer spatial resolution and more extensive coverage, and downscaling EC fluxes to match the scale of RS, will improve chamber and tower comparisons. Opportunities also exist to estimate RH at regional scales by implementing decomposition functional types, akin to plant functional

  11. SoilInfo App: global soil information on your palm

    Science.gov (United States)

    Hengl, Tomislav; Mendes de Jesus, Jorge

    2015-04-01

    ISRIC ' World Soil Information has released in 2014 and app for mobile de- vices called 'SoilInfo' (http://soilinfo-app.org) and which aims at providing free access to the global soil data. SoilInfo App (available for Android v.4.0 Ice Cream Sandwhich or higher, and Apple v.6.x and v.7.x iOS) currently serves the Soil- Grids1km data ' a stack of soil property and class maps at six standard depths at a resolution of 1 km (30 arc second) predicted using automated geostatistical mapping and global soil data models. The list of served soil data includes: soil organic carbon (), soil pH, sand, silt and clay fractions (%), bulk density (kg/m3), cation exchange capacity of the fine earth fraction (cmol+/kg), coarse fragments (%), World Reference Base soil groups, and USDA Soil Taxonomy suborders (DOI: 10.1371/journal.pone.0105992). New soil properties and classes will be continuously added to the system. SoilGrids1km are available for download under a Creative Commons non-commercial license via http://soilgrids.org. They are also accessible via a Representational State Transfer API (http://rest.soilgrids.org) service. SoilInfo App mimics common weather apps, but is also largely inspired by the crowdsourcing systems such as the OpenStreetMap, Geo-wiki and similar. Two development aspects of the SoilInfo App and SoilGrids are constantly being worked on: Data quality in terms of accuracy of spatial predictions and derived information, and Data usability in terms of ease of access and ease of use (i.e. flexibility of the cyberinfrastructure / functionalities such as the REST SoilGrids API, SoilInfo App etc). The development focus in 2015 is on improving the thematic and spatial accuracy of SoilGrids predictions, primarily by using finer resolution covariates (250 m) and machine learning algorithms (such as random forests) to improve spatial predictions.

  12. Use of Microtremor Array Recordings for Mapping Subsurface Soil Structure, Singapore

    Science.gov (United States)

    Walling, M.

    2012-12-01

    Microtremor array recordings are carried out in Singapore, for different geology, to study the influence of each site in modeling the subsurface structure. The Spatial Autocorrelation (SPAC) method is utilized for the computation of the soil profiles. The array configuration of the recording consists of 7 seismometers, recording the vertical component of the ground motion, and the recording at each site is carried out for 30 minutes. The results from the analysis show that the soil structure modeled for the young alluvial of Kallang Formation (KF), in terms of shear wave velocity (Vs), gives a good correlation with borehole information, while for the older geological formation of Jurong Formation (JF) (sedimentary rock sequence) and Old Alluvial (OA) (dense alluvium formation), the correlation is not very clear due to the lack of impedance contrast. The older formation of Bukit Timah Granite (BTG) show contrasting results within the formation, with the northern BTG suggesting a low Vs upper layer of about 20m - 30m while the southern BTG reveals a dense formation. The discrepancy in the variation within BTG is confirmed from borehole data that reveals the northern BTG to have undergone intense weathering while the southern BTG have not undergone noticeable weathering. Few sites with bad recording quality could not resolve the soil structure. Microtremor array recording is good for mapping sites with soft soil formation and weathered rock formation but can be limited in the absence of subsurface velocity contrast and bad quality of microtremor records.; The correlation between the Vs30 estimated from SPAC method and borehole data for the four major geological formations of Singapore. The encircled sites are the sites with recording error.

  13. Comparison of soil thickness in a zero-order basin in the Oregon Coast Range using a soil probe and electrical resistivity tomography

    Science.gov (United States)

    Morse, Michael S.; Lu, Ning; Godt, Jonathan W.; Revil, André; Coe, Jeffrey A.

    2012-01-01

    Accurate estimation of the soil thickness distribution in steepland drainage basins is essential for understanding ecosystem and subsurface response to infiltration. One important aspect of this characterization is assessing the heavy and antecedent rainfall conditions that lead to shallow landsliding. In this paper, we investigate the direct current (DC) resistivity method as a tool for quickly estimating soil thickness over a steep (33–40°) zero-order basin in the Oregon Coast Range, a landslide prone region. Point measurements throughout the basin showed bedrock depths between 0.55 and 3.2 m. Resistivity of soil and bedrock samples collected from the site was measured for degrees of saturation between 40 and 92%. Resistivity of the soil was typically higher than that of the bedrock for degrees of saturation lower than 70%. Results from the laboratory measurements and point-depth measurements were used in a numerical model to evaluate the resistivity contrast at the soil-bedrock interface. A decreasing-with-depth resistivity contrast was apparent at the interface in the modeling results. At the field site, three transects were surveyed where coincident ground truth measurements of bedrock depth were available, to test the accuracy of the method. The same decreasing-with-depth resistivity trend that was apparent in the model was also present in the survey data. The resistivity contour of between 1,000 and 2,000 Ωm that marked the top of the contrast was our interpreted bedrock depth in the survey data. Kriged depth-to-bedrock maps were created from both the field-measured ground truth obtained with a soil probe and interpreted depths from the resistivity tomography, and these were compared for accuracy graphically. Depths were interpolated as far as 16.5 m laterally from the resistivity survey lines with root mean squared error (RMSE) = 27 cm between the measured and interpreted depth at those locations. Using several transects and analysis of the subsurface

  14. 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

  15. 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.

  16. 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.

  17. 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. PMID:26020969

  18. Farm scale application of EMI and FDR sensors to measuring and mapping soil water content

    Science.gov (United States)

    Rallo, Giovanni; Provenzano, Giuseppe

    2017-04-01

    Soil water content (SWC) controls most water exchange processes within and between the soil-plants-atmosphere continuum and can therefore be considered as a practical variable for irrigation farmer choices. A better knowledge of spatial SWC patterns could improve farmer's awareness about critical crop water status conditions and enhance their capacity to characterize their behavior at the field or farm scale. However, accurate soil moisture measurement across spatial and temporal scales is still a challenging task and, specifically at intermediate spatial (0.1-100 ha) and temporal (minutes to days) scales, a data gap remains that limits our understanding over reliability of the SWC spatial measurements and its practical applicability in irrigation scheduling. In this work we compare the integrated EM38 (Geonics Ltd. Canada) response, collected at different sensor positions above ground to that obtained by integrating the depth profile of volumetric SWC measured with Diviner 2000 (Sentek) in conjunction with the depth response function of the EM38 when operated in both horizontal and vertical dipole configurations. On a 1.0-ha Olive grove site in Sicliy (Italy), 200 data points were collected before and after irrigation or precipitation events following a systematic sampling grid with focused measurements around the tree. Inside two different zone of the field, characterized from different soil physical properties, two Diviner 2000 access tube (1.2 m) were installed and used for the EM38 calibration. After calibration, the work aimed to propose the combined use of the FDR and EMI sensors to measuring and mapping root zone soil water content. We found strong correlations (R2 = 0.66) between Diviner 2000 SWC averaged to a depth of 1.2 m and ECa from an EM38 held in the vertical mode above the soil surface. The site-specific relationship between FDR-based SWC and ECa was linear for the purposes of estimating SWC over the explored range of ECa monitored at field levels

  19. SOIL Geo-Wiki: A tool for improving soil information

    Science.gov (United States)

    Skalský, Rastislav; Balkovic, Juraj; Fritz, Steffen; See, Linda; van der Velde, Marijn; Obersteiner, Michael

    2014-05-01

    Crowdsourcing is increasingly being used as a way of collecting data for scientific research, e.g. species identification, classification of galaxies and unravelling of protein structures. The WorldSoilProfiles.org database at ISRIC is a global collection of soil profiles, which have been 'crowdsourced' from experts. This system, however, requires contributors to have a priori knowledge about soils. Yet many soil parameters can be observed in the field without specific knowledge or equipment such as stone content, soil depth or color. By crowdsourcing this information over thousands of locations, the uncertainty in current soil datasets could be radically reduced, particularly in areas currently without information or where multiple interpretations are possible from different existing soil maps. Improved information on soils could benefit many research fields and applications. Better soil data could enhance assessments of soil ecosystem services (e.g. soil carbon storage) and facilitate improved process-based ecosystem modeling from local to global scales. Geo-Wiki is a crowdsourcing tool that was developed at IIASA for land cover validation using satellite imagery. Several branches are now available focused on specific aspects of land cover validation, e.g. validating cropland extent or urbanized areas. Geo-Wiki Pictures is a smart phone application for collecting land cover related information on the ground. The extension of Geo-Wiki to a mobile environment provides a tool for experts in land cover validation but is also a way of reaching the general public in the validation of land cover. Here we propose a Soil Geo-Wiki tool that builds on the existing functionality of the Geo-Wiki application, which will be largely designed for the collection and sharing of soil information. Two distinct applications are envisaged: an expert-oriented application mainly for scientific purposes, which will use soil science related language (e.g. WRB or any other global reference

  20. Microwave radiometric measurements of soil moisture in Italy

    Directory of Open Access Journals (Sweden)

    G. Macelloni

    2003-01-01

    Full Text Available Within the framework of the MAP and RAPHAEL projects, airborne experimental campaigns were carried out by the IFAC group in 1999 and 2000, using a multifrequency microwave radiometer at L, C and X bands (1.4, 6.8 and 10 GHz. The aim of the experiments was to collect soil moisture and vegetation biomass information on agricultural areas to give reliable inputs to the hydrological models. It is well known that microwave emission from soil, mainly at L-band (1.4 GHz, is very well correlated to its moisture content. Two experimental areas in Italy were selected for this project: one was the Toce Valley, Domodossola, in 1999, and the other, the agricultural area of Cerbaia, close to Florence, where flights were performed in 2000. Measurements were carried out on bare soils, corn and wheat fields in different growth stages and on meadows. Ground data of soil moisture (SMC were collected by other research teams involved in the experiments. From the analysis of the data sets, it has been confirmed that L-band is well related to the SMC of a rather deep soil layer, whereas C-band is sensitive to the surface SMC and is more affected by the presence of surface roughness and vegetation, especially at high incidence angles. An algorithm for the retrieval of soil moisture, based on the sensitivity to moisture of the brightness temperature at C-band, has been tested using the collected data set. The results of the algorithm, which is able to correct for the effect of vegetation by means of the polarisation index at X-band, have been compared with soil moisture data measured on the ground. Finally, the sensitivity of emission at different frequencies to the soil moisture profile was investigated. Experimental data sets were interpreted by using the Integral Equation Model (IEM and the outputs of the model were used to train an artificial neural network to reproduce the soil moisture content at different depths. Keywords: microwave radiometry, soil moisture

  1. SoilGrids1km— global soil information based on automated mapping

    NARCIS (Netherlands)

    Hengl, T.; Mendes de Jesus, J.S.; Macmillan, R.A.; Batjes, N.H.; Heuvelink, G.B.M.; Carvalho Ribeiro, E.D.; Samuel Rosa, A.; Kempen, B.; Leenaars, J.G.B.; Walsh, M.G.; Ruiperez Gonzalez, M.

    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

  2. Pedodiversity and Its Significance in the Context of Modern Soil Geography

    Science.gov (United States)

    Krasilnikov, P. V.; Gerasimova, M. I.; Golovanov, D. L.; Konyushkova, M. V.; Sidorova, V. A.; Sorokin, A. S.

    2018-01-01

    Methodological basics of the study and quantitative assessment of pedodiversity are discussed. It is shown that the application of various indices and models of pedodiversity can be feasible for solving three major issues in pedology: a comparative geographical analysis of different territories, a comparative historical analysis of soil development in the course of landscape evolution, and the analysis of relationships between biodiversity and pedodiversity. Analogous geographic concepts of geodiversity and landscape diversity are also discussed. Certain limitations in the use of quantitative estimates of pedodiversity related to their linkage to the particular soil classification systems and with the initial soil maps are considered. Problems of the interpretation of the results of pedodiversity assessments are emphasized. It is shown that scientific explanations of biodiversity cannot be adequately applied in soil studies. Promising directions of further studies of pedodiversity are outlined. They include the assessment of the functional diversity of soils on the basis of data on their properties, integration with geostatistical methods of evaluation of soil variability, and assessment of pedodiversity on different scales.

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

    Science.gov (United States)

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

    2013-12-01

    Digital elevation models (DEMs) are the dominant input to spatially explicit digital soil mapping (DSM) efforts due to their increasing availability and the tight coupling between topography and soil variability. Accurate characterization of this coupling is dependent on DEM spatial resolution and soil sampling density, both of which may limit analyses. For example, DEM resolution may be too coarse to accurately reflect scale-dependent soil properties yet downscaling introduces artifactual uncertainty unrelated to deterministic or stochastic soil processes. We tackle these limitations through a DSM effort that couples moderately high density soil sampling with a very fine scale terrestrial lidar dataset (20 cm) implemented in a semiarid rolling hillslope domain where terrain variables change rapidly but smoothly over short distances. Our guiding hypothesis is that in this diffusion-dominated landscape, soil thickness is readily predicted by continuous terrain attributes coupled with catenary hillslope segmentation. We choose soil thickness as our keystone dependent variable for its geomorphic and hydrologic significance, and its tendency to be a primary input to synthetic ecosystem models. In defining catenary hillslope position we adapt a logical rule-set approach that parses common terrain derivatives of curvature and specific catchment area into discrete landform elements (LE). Variograms and curvature-area plots are used to distill domain-scale terrain thresholds from short range order noise characteristic of very fine-scale spatial data. The revealed spatial thresholds are used to condition LE rule-set inputs, rendering a catenary LE map that leverages the robustness of fine-scale terrain data to create a generalized interpretation of soil geomorphic domains. Preliminary regressions show that continuous terrain variables alone (curvature, specific catchment area) only partially explain soil thickness, and only in a subset of soils. For example, at spatial

  4. Interpreting Impoliteness: Interpreters’ Voices

    Directory of Open Access Journals (Sweden)

    Tatjana Radanović Felberg

    2017-11-01

    Full Text Available Interpreters in the public sector in Norway interpret in a variety of institutional encounters, and the interpreters evaluate the majority of these encounters as polite. However, some encounters are evaluated as impolite, and they pose challenges when it comes to interpreting impoliteness. This issue raises the question of whether interpreters should take a stance on their own evaluation of impoliteness and whether they should interfere in communication. In order to find out more about how interpreters cope with this challenge, in 2014 a survey was sent to all interpreters registered in the Norwegian Register of Interpreters. The survey data were analyzed within the theoretical framework of impoliteness theory using the notion of moral order as an explanatory tool in a close reading of interpreters’ answers. The analysis shows that interpreters reported using a variety of strategies for interpreting impoliteness, including omissions and downtoning. However, the interpreters also gave examples of individual strategies for coping with impoliteness, such as interrupting and postponing interpreting. These strategies border behavioral strategies and conflict with the Norwegian ethical guidelines for interpreting. In light of the ethical guidelines and actual practice, mapping and discussing different strategies used by interpreters might heighten interpreters’ and interpreter-users’ awareness of the role impoliteness can play in institutional interpreter– mediated encounters. 

  5. 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

  6. Mapping Soil Age at Continental Scales

    Science.gov (United States)

    Slessarev, E.; Feng, X.

    2017-12-01

    Soil age controls the balance between weathered and unweathered minerals in soil, and thus strongly influences many of the biological, geochemical, and hydrological functions of the critical zone. However, most quantitative models of soil development do not represent soil age. Instead, they rely on a steady-state assumption: physical erosion controls the residence time of unweathered minerals in soil, and thus fixes the chemical weathering rate. This assumption may hold true in mountainous landscapes, where physical erosion rates are high. However, the steady-state assumption may fail in low-relief landscapes, where physical erosion rates have been insufficient to remove unweathered minerals left by glaciation and dust deposition since the Last Glacial Maximum (LGM). To test the applicability of the steady-state assumption at continental scales, we developed an empirical predictor for physical erosion, and then simulated soil development since LGM with a numerical model. We calibrated the physical erosion predictor using a compilation of watershed-scale sediment yield data, and in-situ 10Be denudation measurements corrected for weathering by Zr/Ti mass-balance. Physical erosion rates can be predicted using a power-law function of local relief and peak ground acceleration, a proxy for tectonic activity. Coupling physical erosion rates with the numerical model reveals that extensive low-relief areas of North America may depart from steady-state because they were glaciated, or received high dust fluxes during LGM. These LGM legacy effects are reflected in topsoil Ca:Al and Quartz:Feldspar ratios derived from United States Geological Survey data, and in a global compilation of soil pH measurements. Our results quantitatively support the classic idea that soils in the mid-high latitudes of the Northern Hemisphere are "young", in the sense that they are undergoing transient response to LGM conditions. Where they occur, such departures from steady-state likely increase

  7. Forsmark site investigation. Interpretation of topographic lineaments 2002

    International Nuclear Information System (INIS)

    Isaksson, Hans

    2003-04-01

    SKB performs site investigations for localization of a deep repository for high level radioactive waste. The site investigations are performed in two municipalities; Oesthammar and Oskarshamn. The Forsmark investigation area is situated in Oesthammar, close to the Forsmark nuclear power plant. The purpose of interpretation of lineaments from topographic data is to identify linear features (lineaments), which may correspond to deformation zones in the bedrock. The data will be combined with interpretations of lineaments from airborne geophysical data in order to produce an integrated lineament interpretation for the Forsmark area. This integrated interpretation will be combined with geological data in order to establish a bedrock geological map of the Forsmark area. The area for the lineament interpretation is the same as that selected for the bedrock mapping activities during 2002, i.e. the land area around Forsmark

  8. The Interpretation of Urban Land Use Maps

    Science.gov (United States)

    Robinson, Roger J.

    1973-01-01

    Three steps in urban land use analysis, fieldwork mapping, processing of data, and classification and delimitation of zones in an urban area, are described. An appendix presents a classification of buildings by function. (KM)

  9. 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 (interventions. Future work should include cost-benefit and tradeoff analyses of the various management options for achieving a given level of erosion reduction.

  10. Modelling soil organic carbon concentration of mineral soils in arable lands using legacy soil data

    DEFF Research Database (Denmark)

    Suuster, E; Ritz, Christian; Roostalu, H

    2012-01-01

    is appropriate if the study design has a hierarchical structure as in our scenario. We used the Estonian National Soil Monitoring data on arable lands to predict SOC concentrations of mineral soils. Subsequently, the model with the best prediction accuracy was applied to the Estonian digital soil map...

  11. Mapping monthly rainfall erosivity in Europe.

    Science.gov (United States)

    Ballabio, Cristiano; Borrelli, Pasquale; Spinoni, Jonathan; Meusburger, Katrin; Michaelides, Silas; Beguería, Santiago; Klik, Andreas; Petan, Sašo; Janeček, Miloslav; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Tadić, Melita Perčec; Diodato, Nazzareno; Kostalova, Julia; Rousseva, Svetla; Banasik, Kazimierz; Alewell, Christine; Panagos, Panos

    2017-02-01

    Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315MJmmha -1 h -1 ) compared to winter (87MJmmha -1 h -1 ). The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R 2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be

  12. 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.

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

    Science.gov (United States)

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

    2017-12-01

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

  14. A global map of mangrove forest soil carbon at 30 m spatial resolution

    Science.gov (United States)

    Sanderman, Jonathan; Hengl, Tomislav; Fiske, Greg; Solvik, Kylen; Adame, Maria Fernanda; Benson, Lisa; Bukoski, Jacob J.; Carnell, Paul; Cifuentes-Jara, Miguel; Donato, Daniel; Duncan, Clare; Eid, Ebrahem M.; Ermgassen, Philine zu; Ewers Lewis, Carolyn J.; Macreadie, Peter I.; Glass, Leah; Gress, Selena; Jardine, Sunny L.; Jones, Trevor G.; Ndemem Nsombo, Eugéne; Mizanur Rahman, Md; Sanders, Christian J.; Spalding, Mark; Landis, Emily

    2018-05-01

    With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30 m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250 m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kg m‑3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha‑1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies.

  15. High-resolution, real-time mapping of surface soil moisture at the field scale using ground penetrating radar

    Science.gov (United States)

    Lambot, S.; Minet, J.; Slob, E.; Vereecken, H.; Vanclooster, M.

    2008-12-01

    Measuring soil surface water content is essential in hydrology and agriculture as this variable controls important key processes of the hydrological cycle such as infiltration, runoff, evaporation, and energy exchanges between the earth and the atmosphere. We present a ground-penetrating radar (GPR) method for automated, high-resolution, real-time mapping of soil surface dielectric permittivity and correlated water content at the field scale. Field scale characterization and monitoring is not only necessary for field scale management applications, but also for unravelling upscaling issues in hydrology and bridging the scale gap between local measurements and remote sensing. In particular, such methods are necessary to validate and improve remote sensing data products. The radar system consists of a vector network analyzer combined with an off-ground, ultra-wideband monostatic horn antenna, thereby setting up a continuous-wave steeped-frequency GPR. Radar signal analysis is based on three-dimensional electromagnetic inverse modelling. The forward model accounts for all antenna effects, antenna-soil interactions, and wave propagation in three-dimensional multilayered media. A fast procedure was developed to evaluate the involved Green's function, resulting from a singular, complex integral. Radar data inversion is focused on the surface reflection in the time domain. The method presents considerable advantages compared to the current surface characterization methods using GPR, namely, the ground wave and common reflection methods. Theoretical analyses were performed, dealing with the effects of electric conductivity on the surface reflection when non-negligible, and on near-surface layering, which may lead to unrealistic values for the surface dielectric permittivity if not properly accounted for. Inversion strategies are proposed. In particular the combination of GPR with electromagnetic induction data appears to be promising to deal with highly conductive soils

  16. Mapping Surface Heat Fluxes by Assimilating SMAP Soil Moisture and GOES Land Surface Temperature Data

    Science.gov (United States)

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

    2017-12-01

    Surface heat fluxes play a crucial role in the surface energy and water balance. In situ measurements are costly and difficult, and large-scale flux mapping is hindered by surface heterogeneity. Previous studies have demonstrated that surface heat fluxes can be estimated by assimilating land surface temperature (LST) and soil moisture to determine two key parameters: a neutral bulk heat transfer coefficient (CHN) and an evaporative fraction (EF). Here a methodology is proposed to estimate surface heat fluxes by assimilating Soil Moisture Active Passive (SMAP) soil moisture data and Geostationary Operational Environmental Satellite (GOES) LST data into a dual-source (DS) model using a hybrid particle assimilation strategy. SMAP soil moisture data are assimilated using a particle filter (PF), and GOES LST data are assimilated using an adaptive particle batch smoother (APBS) to account for the large gap in the spatial and temporal resolution. The methodology is implemented in an area in the U.S. Southern Great Plains. Assessment against in situ observations suggests that soil moisture and LST estimates are in better agreement with observations after assimilation. The RMSD for 30 min (daytime) flux estimates is reduced by 6.3% (8.7%) and 31.6% (37%) for H and LE on average. Comparison against a LST-only and a soil moisture-only assimilation case suggests that despite the coarse resolution, assimilating SMAP soil moisture data is not only beneficial but also crucial for successful and robust flux estimation, particularly when the uncertainties in the model estimates are large.

  17. Soil Fertility Assessment and Mapping of Regional Agricultural Research Station, Parwanipur, Bara, Nepal

    Directory of Open Access Journals (Sweden)

    Dinesh Khadka

    2018-05-01

    Full Text Available Soil fertility assessment is a key for sustainable planning of a particular area. Thus, the present study was conducted to assess the soil fertility status of the Regional Agricultural Research Station, Parwanipur, Bara, Nepal. The study area is situated at the latitude 27°4’40.9’’N and longitude 84°56’9.85”E at 75masl altitude. Altogether 76 soil samples were collected based on the variability of land at 0-20 cm depth. The texture, pH, OM, total N, available P2O5, K2O, Ca, Mg, S, B, Fe, Zn, Cu and Mn content in the samples were determined following standard analytical methods. Arc-GIS 10.1 was used for soil fertility mapping. The soil structure was angular blocky, and varied between grayish brown (10YR 5/2 and dark grayish brown (10YR 4/2 in color. The sand, silt and clay content were 24.41±0.59%, 54.57±0.44% and 21.03±0.32%, respectively and categorized as silt loam and loam in texture. The soil was moderately acidic in pH (5.67±0.09, low in organic matter (0.74±0.04% and available Sulphur (0.8± 0.1 ppm. The total nitrogen (0.06±0.001%, available boron (0.59±0.08ppm and available zinc (0.51±0.05ppm were low. Furthermore, available potassium (50.26±2.95ppm, available calcium (1674.6±46.3ppm and available magnesium (175.43± 8.93ppm were medium. Moreover, available copper (1.36±0.06 ppm and available manganese (16.52±1.12 ppm were high, while, available phosphorus (77.55±6.65 ppm and available iron (85.88±7.05 ppm were found high. It is expected that the present study would help to guide practices required for sustainable soil fertility management and developing future agricultural research strategy in the farm.

  18. Soil homogeneity evaluation by radionuclide tracer breakthrough curve interpretation

    International Nuclear Information System (INIS)

    Brenizer, J.S. Jr.; Jarrett, A.R.; Jester, W.A.

    1980-01-01

    Increasing concern about the environmental impact of hazardous waste disposal has made site evaluation and site selection difficult and expensive. Pollutants, assumed to be absorbed by the soil immediately surrounding the burial trench, have been detected far from sites. Discrepancies between predicted migration distances based on indirect methods such as laboratory and computer modeling and those observed at the field site are often significant. The homogeneity of subsurface media, often assumed in laboratory and modeling studies, is seldom found in the field. The use of tracers to determine the flow characteristics of a potential disposal site involves time and expense, but offers a direct evaluation of solute transport and eliminates the assumptions inherent in indirect methods. Current modeling of solute transport in nonhomogeneous porous media is limited by the quantification of input parameters. Several general models can predict solute transport in saturated-unsaturated media from low-level disposal sites if the hydraulic characteristics and chemical reactions expected in each unique water-solute-media system can be defined. The objective of this research was to develop a method of evaluating potential shallow-land burial waste disposal sites by interpreting tracer breakthrough curve structure with respect to the hydrologic properties of the media at the potential disposal site. This methodology will be helpful in evaluating the potential performance of many types of shallow-land waste burial sites such as low-level radioactive waste disposal, surface disposal of flyash, chemical waste disposal, waste sedimentation ponds, and sanitary landfills

  19. In situ mapping of radionuclides in subsurface and surface soils: 1994 Summary report

    International Nuclear Information System (INIS)

    Schilk, A.J.; Hubbard, C.W.; Knopf, M.A.; Abel, K.H.

    1995-04-01

    Uranium production and support facilities at several DOE sites occasionally caused local contamination of some surface and subsurface soils. The thorough cleanup of these sites is a major public concern and a high priority for the US Department of Energy, but before any effective remedial protocols can be established, the three-dimensional distributions of target contaminants must be characterized. Traditional means of measuring radionuclide activities in soil are cumbersome, expensive, time-consuming, and often do not accurately reflect conditions over very large areas. New technologies must be developed, or existing ones improved, to allow cheaper, faster, and safer characterization of radionuclides in soils at these sites. The Pacific Northwest Laboratory (PNL) was tasked with adapting, developing, and demonstrating technologies to measure uranium in surface and subsurface soils. In partial completion of this effort, PNL developed an improved in situ gamma-ray spectrometry system to satisfy the technical requirements. This document summarizes fiscal-year 1994 efforts at PNL to fulfill requirements for TTP number-sign 321103 (project number-sign 19307). These requirements included (a) developing a user-friendly software package for reducing field-acquired gamma-ray spectra, (b) constructing an improved data-acquisition hardware system for use with high-purity germanium detectors, (c) ensuring readiness to conduct field mapping exercises as specified by the sponsor, (d) evaluating the in situ gamma-ray spectrometer for the determination of uranium depth distribution, and (e) documenting these efforts

  20. Designing a national soil erosion monitoring network for England and Wales

    Science.gov (United States)

    Lark, Murray; Rawlins, Barry; Anderson, Karen; Evans, Martin; Farrow, Luke; Glendell, Miriam; James, Mike; Rickson, Jane; Quine, Timothy; Quinton, John; Brazier, Richard

    2014-05-01

    -domains within which, respectively, small or no erosion rates, and moderate or larger erosion rates are expected. Each stratum was then sampled independently and at random. The sample density need not be equal in the two strata, but is known and is accounted for in the estimation of the mean and its standard error. To divide the domains into strata we used information on slope angle, previous interpretation of erosion susceptibility of the soil associations that correspond to the soil map of E&W at 1:250 000 (Soil Survey of England and Wales, 1983), and visual interpretation of evidence of erosion from aerial photography. While each domain could be stratified on the basis of the first two criteria, air photo interpretation across the whole country was not feasible. For this reason we used a two-phase random sampling for stratification (TPRS) design (de Gruijter et al., 2006). First, we formed an initial random sample of 1-km grid cells from the target domain. Second, each cell was then allocated to a stratum on the basis of the three criteria. A subset of the selected cells from each stratum were then selected for field survey at random, with a specified sampling density for each stratum so as to increase the proportion of cells where moderate or larger erosion rates were expected. Once measurements of erosion have been made, an estimate of the spatial mean of the erosion rate over the target domain, its standard error and associated uncertainty can be calculated by an expression which accounts for the estimated proportions of the two strata within the initial random sample. de Gruijter, J.J., Brus, D.J., Biekens, M.F.P. & Knotters, M. 2006. Sampling for Natural Resource Monitoring. Springer, Berlin. Soil Survey of England and Wales. 1983 National Soil Map NATMAP Vector 1:250,000. National Soil Research Institute, Cranfield University.

  1. The soil structure investigation for the interpreting radiocaesium behaviour in upper horizons of Chernobyl contaminated sandy soils

    International Nuclear Information System (INIS)

    Vazhinskij, A.G.

    2002-01-01

    The soil-composing particles in natural environment form aggregates of different stability. For soils (topsoil) of contrasting type from Chernobyl NPP area the particle size and microaggregate analyses have been performed and the distribution of Cs 137 in the obtained fractions has been studied. Results of long-term investigation of Cs 137 vertical migration in sandy soils of 50-km zone around Chernobyl NPP have been compared with data on radiocaesium distribution among water-stable aggregates and particles of various size in studied soils. On the basis of particle size analysis and aggregate soil composition the size of soil components with vertical migration potential, and the amount of Cs 137 potentially tending to migrate with the soil components along soil profile have been assessed. Based on findings showing Cs 137 partitioning among water-stable soil aggregates of diverse size and pattern of the radionuclide vertical distribution in top 0-10 cm soil layer, it was assumed that neither shift of peak radiocaesium level from upper soil layer downwards nor the so-called slow constituent of Cs 137 vertical migration (in terms of quasi diffusion description of Cs 137 profile in soil) could not be explained by self-motion of soil aggregates and particles with associated radiocaesium. Hypothesis of root intermixing as principal mechanism responsible for Cs 137 vertical transport in top 0-10 cm soil layer was postulated

  2. Concentrations of some macro and micro plant nutrient of cultivated soils in Central and Eastern Blacksea Region and their mapping by inverse distance weighted (IDW method

    Directory of Open Access Journals (Sweden)

    Mehmet Arif Özyazıcı

    2015-11-01

    Full Text Available The aim of this study was to determine plant nutrients content and to in terms of soil variables their soil database and generate maps of their distribution on agricultural land in Central and Eastern Black Sea Region using geographical information system (GIS. In this research, total 3400 soil samples (0-20 cm depth were taken at 2.5 x 2.5 km grid points representing agricultural soils. Total nitrogen, extractable calcium, magnesium, sodium, boron, iron, copper, zinc and manganese contents were analysed in collected soil samples. Analysis results of these samples were classified and evaluated for deficiency, sufficiency or excess with respect to plant nutrients. Afterwards, in terms of GIS, a soil database and maps for current status of the study area were created by using inverse distance weighted (IDW interpolation method. According to this research results, it was determined sufficient plant nutrient elements in terms of total nitrogen, extractable iron, copper and manganese in arable soils of Central and Eastern Blacksea Region while, extractable calcium, magnesium, sodium were found good and moderate level in 66.88%, 81.44% and 64.56% of total soil samples, respectively. In addition, insufficient boron and zinc concentration were found in 34.35% and 51.36% of soil samples, respectively.

  3. Imputing historical statistics, soils information, and other land-use data to crop area

    Science.gov (United States)

    Perry, C. R., Jr.; Willis, R. W.; Lautenschlager, L.

    1982-01-01

    In foreign crop condition monitoring, satellite acquired imagery is routinely used. To facilitate interpretation of this imagery, it is advantageous to have estimates of the crop types and their extent for small area units, i.e., grid cells on a map represent, at 60 deg latitude, an area nominally 25 by 25 nautical miles in size. The feasibility of imputing historical crop statistics, soils information, and other ancillary data to crop area for a province in Argentina is studied.

  4. Using Water and Agrochemicals in the Soil, Crop and Vadose Environment (WAVE Model to Interpret Nitrogen Balance and Soil Water Reserve Under Different Tillage Managements

    Directory of Open Access Journals (Sweden)

    Zare Narjes

    2014-10-01

    Full Text Available Applying models to interpret soil, water and plant relationships under different conditions enable us to study different management scenarios and then to determine the optimum option. The aim of this study was using Water and Agrochemicals in the soil, crop and Vadose Environment (WAVE model to predict water content, nitrogen balance and its components over a corn crop season under both conventional tillage (CT and direct seeding into mulch (DSM. In this study a corn crop was cultivated at the Irstea experimental station in Montpellier, France under both CT and DSM. Model input data were weather data, nitrogen content in both the soil and mulch at the beginning of the season, the amounts and the dates of irrigation and nitrogen application. The results show an appropriate agreement between measured and model simulations (nRMSE < 10%. Using model outputs, nitrogen balance and its components were compared with measured data in both systems. The amount of N leaching in validation period were 10 and 8 kgha–1 in CT and DSM plots, respectively; therefore, these results showed better performance of DSM in comparison with CT. Simulated nitrogen leaching from CT and DSM can help us to assess groundwater pollution risk caused by these two systems.

  5. Preparation and Interpretation of Heat Flow Map of Turkey

    International Nuclear Information System (INIS)

    Ozturk, S.; Karli, R.; Destur, M.

    2007-01-01

    There exist a lot of data indicating our country takes place on an impotrant Kown heat flow anomaly. The preparation of a detailed 'Heat Flow Map' as a result of rational studies and depending upon this the determination of the distribution of heat in litosphere, except from the scientific benefits; shall enlighten subjects such as oil basen analysis, prospection of hydrothermal ores and earthquakes and further shall increase the feasibility of planning geothermal energy research.In between years 1995- 2005; as a part of project of the Geophysical Department of MTA with the purpose of preperation of Heat Flow Maps of Turkey, the heat flow measurments had been carried on at the convenient cold water wells. Using the Thermic and Gamma-Ray measurments and calculated conductivity coefficients of the representative rock samples of formation, heat flow map had been prepared. A distance of 10-30 km had been kept carefully betwen the wells of interest a total of 80204 m Thermic and Gamma-Ray logs and 420 rock samples from 695 wells, had been used in the study. Then according to the Lambert Projection, using the Surfer 8.02 and Grapher4 programmes The Heat Flow Maps of Turkey of scale 1:1000000 had been obtained.Some regional researches indicate that Turkey takes place in a part of Europe of high heat flux. Unfortunately there exist no detailed heat flow map of our country up to now. This shows the importance of present project

  6. 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 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.

  7. Soils - SOILS_STATSGO_IN: Soil Associations in Indiana (U.S. Dept. of Agriculture, 1:250,000, Polygon Shapefile)

    Data.gov (United States)

    NSGIC State | GIS Inventory — Natural Resources Conservation Service, STATSGO metadata reports- "This data set is a digital general soil association map developed by the National Cooperative Soil...

  8. SPATIAL CORRELATION BETWEEN PHYSICAL PROPERTIES OF SOIL AND WEEDS IN TWO MANAGEMENT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Valter Roberto Schaffrath

    2015-02-01

    Full Text Available The spatial correlation between soil properties and weeds is relevant in agronomic and environmental terms. The analysis of this correlation is crucial for the interpretation of its meaning, for influencing factors such as dispersal mechanisms, seed production and survival, and the range of influence of soil management techniques. This study aimed to evaluate the spatial correlation between the physical properties of soil and weeds in no-tillage (NT and conventional tillage (CT systems. The following physical properties of soil and weeds were analyzed: soil bulk density, macroporosity, microporosity, total porosity, aeration capacity of soil matrix, soil water content at field capacity, weed shoot biomass, weed density, Commelina benghalensis density, and Bidens pilosa density. Generally, the ranges of the spatial correlations were higher in NT than in CT. The cross-variograms showed that many variables have a structure of combined spatial variation and can therefore be mapped from one another by co-kriging. This combined variation also allows inferences about the physical and biological meanings of the study variables. Results also showed that soil management systems influence the spatial dependence structure significantly.

  9. Mapping land cover through time with the Rapid Land Cover Mapper—Documentation and user manual

    Science.gov (United States)

    Cotillon, Suzanne E.; Mathis, Melissa L.

    2017-02-15

    The Rapid Land Cover Mapper is an Esri ArcGIS® Desktop add-in, which was created as an alternative to automated or semiautomated mapping methods. Based on a manual photo interpretation technique, the tool facilitates mapping over large areas and through time, and produces time-series raster maps and associated statistics that characterize the changing landscapes. The Rapid Land Cover Mapper add-in can be used with any imagery source to map various themes (for instance, land cover, soils, or forest) at any chosen mapping resolution. The user manual contains all essential information for the user to make full use of the Rapid Land Cover Mapper add-in. This manual includes a description of the add-in functions and capabilities, and step-by-step procedures for using the add-in. The Rapid Land Cover Mapper add-in was successfully used by the U.S. Geological Survey West Africa Land Use Dynamics team to accurately map land use and land cover in 17 West African countries through time (1975, 2000, and 2013).

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

    Science.gov (United States)

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

    1987-01-01

    databases, such as the U.S. Department of Agriculture's SCS/S015 (Soil Survey Staff, 1983), to archive the large amounts of information that are collected in conjunction with mapping of natural resources in an easily retrievable manner.During the past 4 years the U.S. Geological Survey's EROS Data Center, in a cooperative effort with the Bureau of Land Management (BLM) and the Soil Conservation Service (SCS), developed a procedure that uses spatial and tabular databases to generate elevation, slope, aspect, and spectral map products that can be used during soil premapping. The procedure results in tabular data, residing in a database management system, that are indexed to the final soil delineations and help quantify soil map unit composition.The procedure was developed and tested on soil surveys on over 600 000 ha in Wyoming, Nevada, and Idaho. A transfer of technology from the EROS Data Center to the BLM will enable the Denver BLM Service Center to use this procedure in soil survey operations on BLM lands. Also underway is a cooperative effort between the EROS Data Center and SCS to define and evaluate maps that can be produced as derivatives of digital elevation data for 7.5-min quadrangle areas, such as those used during the premapping stage of the soil surveys mentioned above, the idea being to make such products routinely available.The procedure emphasizes the applications of digital elevation and spectral data to order-three soil surveys on rangelands, and will:Incorporate digital terrain and spectral data into a spatial database for soil surveys.Provide hardcopy products (that can be generated from digital elevation model and spectral data) that are useful during the soil pre-mapping process.Incorporate soil premaps into a spatial database that can be accessed during the soil survey process along with terrain and spectral data.Summarize useful quantitative information for soil mapping and for making interpretations for resource management.

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

    Science.gov (United States)

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

    2010-05-01

    The richness of African soil resources need to be protected for future generations. A number of threats are affecting the functioning of African soils, not only for the purpose of agricultural production, but also for other important environmental services that soil delivers to all of us. This is of particular importance once we know that many health-related problems in Africa are indirectly related to the services of soils. To raise the awareness of the general public, policy makers and other scientists to the importance of soil in Africa, the Joint Research Centre of the European Commission is to produce the first ever Soil Atlas of Africa. This is in collaboration with the African Union Commission, the Food and Agriculture Organization of the United Nations (FAO), the Africa Soil Science Society, ISRIC - World Soil Information and scientists from both Europe and Africa. The Atlas compiles existing information on different soil types as easily understandable maps (both at regional and continental scale) covering the African continent. The Soil Atlas of Africa intends to produce derived maps at continental scale with descriptive text (e.g. vulnerability to desertification, soil nutrient status, carbon stocks and sequestration potential, irrigable areas and water resources) as well as specific maps to illustrate threats such as soil erosion for instance. For each regional overview, large scale examples of soil maps and derived products are presented too. The Atlas will be published as a hardcover book containing 174 A3 pages, which will allow soils maps to be displayed at the A2 scale. Both French and English versions of the Atlas will be edited. The Atlas will be sold at a low cost and will be for free for educational purpose (Schools and Universities). A digital version on CD and eventually freely downloadable on internet will also be available. Together with the publication of the Atlas, associated datasets on soil characteristics for Africa will be made

  12. 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.

  13. Structural-genetic approach to analysis and mapping of Chernobyl's radionuclide contamination field

    International Nuclear Information System (INIS)

    Proskura, N.I.; Bujkov, M.; Nagorsky, V.A.; Tepikin, V.; Poletaev, V.; Solyanke, E.G.; Shkvorets, O.Y.; Shestopalov, V.M.; Skvortsov, V.

    1997-01-01

    As a main tool for revealing and interpreting the internal structure of radionuclide contamination field, around the Chernobyl NPP the reliable and validated detailed scale maps of contamination densities could serve. Such maps should have, on the one hand, a high enough density of initial observation points (not less than 1 to 10 points per 1 sq.cm. of final map) and, on the other hand, a high representativeness of each observation point, i.e. reliability of presentation of its vicinity (0.1 to 1 sq.km). The available analytical data files of soil sampling in the exclusion zone conform neither to the first requirement, nor to the second one: real density of sampling does not exceed 0-2 to 0.5 points per 1 sq.m, and the representativeness of obtained results has a typical variation from medium values (in the neighbourhood of 0.1 to 1 sq.km) to 3 to 5 times

  14. Soil erodibility mapping using the RUSLE model to prioritize erosion control in the Wadi Sahouat basin, North-West of Algeria.

    Science.gov (United States)

    Toubal, Abderrezak Kamel; Achite, Mohammed; Ouillon, Sylvain; Dehni, Abdelatif

    2018-03-12

    Soil losses must be quantified over watersheds in order to set up protection measures against erosion. The main objective of this paper is to quantify and to map soil losses in the Wadi Sahouat basin (2140 km 2 ) in the north-west of Algeria, using the Revised Universal Soil Loss Equation (RUSLE) model assisted by a Geographic Information System (GIS) and remote sensing. The Model Builder of the GIS allowed the automation of the different operations for establishing thematic layers of the model parameters: the erosivity factor (R), the erodibility factor (K), the topographic factor (LS), the crop management factor (C), and the conservation support practice factor (P). The average annual soil loss rate in the Wadi Sahouat basin ranges from 0 to 255 t ha -1  year -1 , maximum values being observed over steep slopes of more than 25% and between 600 and 1000 m elevations. 3.4% of the basin is classified as highly susceptible to erosion, 4.9% with a medium risk, and 91.6% at a low risk. Google Earth reveals a clear conformity with the degree of zones to erosion sensitivity. Based on the soil loss map, 32 sub-basins were classified into three categories by priority of intervention: high, moderate, and low. This priority is available to sustain a management plan against sediment filling of the Ouizert dam at the basin outlet. The method enhancing the RUSLE model and confrontation with Google Earth can be easily adapted to other watersheds.

  15. Assessment and interpretation of cross- and down-hole seismograms at the Paducah Gaseous Diffusion Plant

    Energy Technology Data Exchange (ETDEWEB)

    Staub, W.P.; Wang, J.C. (Oak Ridge National Lab., TN (United States)); Selfridge, R.J. (Automated Sciences Group, (United States))

    1991-09-01

    This paper is an assessment and interpretation of cross-and down-hole seismograms recorded at four sites in the vicinity of the Paducah Gaseous Diffusion Plant (PGDP). Arrival times of shear (S-) and compressional (P-) waves are recorded on these seismograms in milliseconds. Together with known distances between energy sources and seismometers lowered into boreholes, these arrival times are used to calculate S- and P-wave velocities in unconsolidated soils and sediments that overlie bedrock approximately 320 ft beneath PGDP. The soil columns are modified after an earlier draft by ERC Environmental and Energy Services Company (ERCE), 1990. In addition to S- and P- wave velocity estimates from this paper, the soil columns contain ERCE's lithologic and other geotechnical data for unconsolidated soils and sediments from the surface to bedrock. Soil columns for Sites 1 through 4 and a site location map are in Plates 1 through 5 of Appendix 6. The velocities in the four columns are input parameters for the SHAKE computer program, a nationally recognized computer model that simulates ground response of unconsolidated materials to earthquake generated seismic waves. The results of the SHAKE simulation are combined with predicted ground responses on rock foundations (caused by a given design earthquake) to predict ground responses of facilities with foundations placed on unconsolidated materials. 3 refs.

  16. 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.

  17. Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

    Science.gov (United States)

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

    2017-09-11

    Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

  18. Regolith-geology mapping with support vector machine: A case study over weathered Ni-bearing peridotites, New Caledonia

    Science.gov (United States)

    De Boissieu, Florian; Sevin, Brice; Cudahy, Thomas; Mangeas, Morgan; Chevrel, Stéphane; Ong, Cindy; Rodger, Andrew; Maurizot, Pierre; Laukamp, Carsten; Lau, Ian; Touraivane, Touraivane; Cluzel, Dominique; Despinoy, Marc

    2018-02-01

    Accurate maps of Earth's geology, especially its regolith, are required for managing the sustainable exploration and development of mineral resources. This paper shows how airborne imaging hyperspectral data collected over weathered peridotite rocks in vegetated, mountainous terrane in New Caledonia were processed using a combination of methods to generate a regolith-geology map that could be used for more efficiently targeting Ni exploration. The image processing combined two usual methods, which are spectral feature extraction and support vector machine (SVM). This rationale being the spectral features extraction can rapidly reduce data complexity by both targeting only the diagnostic mineral absorptions and masking those pixels complicated by vegetation, cloud and deep shade. SVM is a supervised classification method able to generate an optimal non-linear classifier with these features that generalises well even with limited training data. Key minerals targeted are serpentine, which is considered as an indicator for hydrolysed peridotitic rock, and iron oxy-hydroxides (hematite and goethite), which are considered as diagnostic of laterite development. The final classified regolith map was assessed against interpreted regolith field sites, which yielded approximately 70% similarity for all unit types, as well as against a regolith-geology map interpreted using traditional datasets (not hyperspectral imagery). Importantly, the hyperspectral derived mineral map provided much greater detail enabling a more precise understanding of the regolith-geological architecture where there are exposed soils and rocks.

  19. Geological hazards investigation - relative slope stability map

    Energy Technology Data Exchange (ETDEWEB)

    Han, Dae Suk; Kim, Won Young; Yu, Il Hyon; Kim, Kyeong Su; Lee, Sa Ro; Choi, Young Sup [Korea Institute of Geology Mining and Materials, Taejon (Korea, Republic of)

    1997-12-01

    The Republic of Korea is a mountainous country; the mountains occupy about three quarters of her land area, an increasing urban development being taken place along the mountainside. For the reason, planners as well as developers and others must realize that some of the urban areas may be threaten by geologic hazards such as landslides and accelerated soil and rock creeps. For the purpose of environmental land-use planning, a mapping project on relative slope-stability was established in 1996. The selected area encompasses about 5,900 km{sup 2} including the topographic maps of Ulsan, Yongchon, Kyongju, Pulguksa, and Kampo, all at a scale of 1:50,000. Many disturbed and undisturbed soil samples, which were collected from the ares of the landslides and unstable slopes, were tested for their physical properties and shear strength. They were classified as GC, SP, SC, SM, SP-SM, SC-SM, CL, ML, and MH according to the Unified Soil Classification System, their liquid limit and plasticity index ranging from 25.3% to as high as 81.3% and from 4.1% to 41.5%, respectively. X-ray analysis revealed that many of the soils contained a certain amount of montmorillonite. Based on the available information as well as both field and laboratory investigation, it was found out that the most common types of slope failures in the study area were both debris and mud flows induced by the heavy rainfalls during the period of rainy season; the flows mostly occurred in the colluvial deposits at the middle and foot of mountains. Thus the deposits generally appear to be the most unstable slope forming materials in the study area. Produced for the study area were six different maps consisting of slope classification map, soil classification map, lineament density map, landslide distribution map, zonal map of rainfall, and geology map, most of them being stored as data base. Using the first four maps and GIS, two sheets of relative slope-stability maps were constructed, each at a scale of 1

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

    Science.gov (United States)

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

    2016-04-01

    Climate change, increasing pressure on farmland to satisfy the growing demand, and need to ensure environmental quality for agriculture in order to be competitive require an increasing capacity of water management. In this context, web-based for forecasting and monitoring the hydrological conditions of topsoil can be an effective means to save water, maximize crop protection and reduce soil loss and the leaching of pollutants. Such tools need to be targeted to the users and be accessible in a simple way in order to allow adequate take up in the practice. IASMHYN "Improved management of Agricultural Systems by Monitoring and Hydrological evaluation" is a web mapping service designed to provide and update on a daily basis the main water budget variables for farmland management. A beta version of the tool is available at www.gecosistema.com/iasmhyn . IASMHYN is an instrument for "second level monitoring" that takes into account accurate hydro-meteorological information's from ground stations and remote sensing sources, and turns them into practically usable decision variables for precision farming, making use of geostatistical analysis and hydrological models The main routines embedded in IASMYHN exclusively use open source libraries (R packages and Python), to perform following operations: (1) Automatic acquisition of observed data, both from ground stations and remote sensing, concerning precipitation (RADAR) and temperature (MODIS-LST) available from various sources; (2) Interpolation of acquisitions through regression kriging in order to spatially map the meteorological data; (3) Run of hydrological models to obtain spatial information of hydrological soil variables of immediate interest in agriculture. The real time results that are produced are available trough a web interface and provide the user with spatial maps and time series of the following variables, supporting decision on irrigation, soil protection from erosion, pollution risk of groundwater and

  1. 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

  2. Global Assessment of Human-induced Soil Degradation (GLASOD)

    NARCIS (Netherlands)

    Oldeman, L.R.; Hakkeling, R.T.A.; Sombroek, W.G.; Batjes, N.H.

    2014-01-01

    The GLASOD project (1987-1990) has produced a world map of human-induced soil degradation. Data were complied in cooperation with a large number of soil scientists throughout the world, using uniform Guidelines and international correlation. The status of soil degradation was mapped within loosely

  3. Modeling Soil-Landscape Relations in the Sonoran Desert, Arizona, USA

    Science.gov (United States)

    Regmi, N. R.; Rasmussen, C.

    2015-12-01

    Digital soil mapping (DSM) techniques that integrate remotely sensed surface topography and reflectance, and map soil-landscape associations have the potential in improve understanding of critical zone evolution and landscape processes. The goal of this study was to understand the soil-geomorphic evolution of Quaternary alluvial and eolian deposits in the Sonoran Desert using a data-driven DSM technique and mapping of soil-landscape relationships. An iterative principal component analysis (iPCA) data reduction routine was developed and implemented for a set of LiDAR elevation- and Landsat ETM+-derived environmental covariates that characterize soil-landscape variability. Principal components that explain more than 95% of the soil-landscape variability were then integrated and classified based on an ISODATA (Iterative Self-Organizing Data) unsupervised technique. The classified map was then segmented based on a region growing algorithm and multi-scale maps of soil-landscape relations were developed, which then compared with maps of major arid-region landforms that can be identified on aerial photographs and satellite images by their distinguishing tone and texture, and in the field by their distinguishing surface and sub-surface soil physical, chemical and biological properties. The approach identified and mapped the soil-landscape variability of alluvial and eolian landscapes, and illustrated the applicability of coupling covariate selection and integration by iPCA, ISODATA classifications of integrated layers, and image segmentation for effective spatial prediction of soil-landscape characteristics. The approach developed here is data-driven, cost- and time-effective, applicable for multi-scale mapping, allows incorporation of wide variety of covariates, and provides accurate quantitative prediction of wide range of soil-landscape attributes that are necessary for hydrologic models, land and ecosystem management decisions, and hazard assessment.

  4. an interpretation map: finding paths to reading processes

    African Journals Online (AJOL)

    the Free State, South Africa. .... socio‑political to a greater extent than have continental scholars. ... interpretation the analogy of the game (in the sense of playing a sport): ... Iser, a German but with broad exposure in English, was trained as a.

  5. Determination of radon in soil and water in parts of Accra, and generation of preliminary radon map for Ghana

    International Nuclear Information System (INIS)

    Osei, Peter

    2016-07-01

    The research was focused on determining the radon levels in soil and water in parts of Accra, generate a preliminary radon map for Ghana and estimate a pilot reference level for the country, using the data obtained from this research and collated data from other researchers. The radon gas measurement was done with the passive method, using the SSNTDs which are sensitive to alpha particles emitted by radon. Cellulose nitrate LR – 115 type II alpha particle detectors were used. The detectors were chemically etched in a 2.5 M NaOH solution at a temperature of 60 °C for 90 minutes, after two weeks and two months of exposure to soil and water respectively. The images of the etched detectors were acquired by means of a scanner and then tracks counted with ImageJ software. Inverse Distance Weighing (IDW) method of ArcGIS 10.2 was used to spatially distribute the radon concentration on a map. The average soil radon concentration in the study area ranges from 0.191 kBqm"-"3 to 3.416 kBqm"-"3 with a mean of 1.193 kBqm"-"3. The radon concentration in water from the study area ranges from 0.00346 BqL"-"1 to 0.00538 BqL"-"1 with an average of 0.00456 BqL"-"1. A strong negative correlation has been established between radon in soil and water in the study area. The preliminary national average indoor, water and soil radon concentrations are 137 Bqm"-"3, 361.93 Bqm"-"3 and 3716.74 Bqm"-"3 respectively. The average levels of water and indoor radon exceeded WHO’s reference level of 100 Bqm"-"3. Accordingly, the pilot national indoor radon reference level for Ghana is set as 200 Bqm"-"3. (au)

  6. 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.

  7. Soil carbon storage estimation in a forested watershed using quantitative soil-landscape modeling

    Science.gov (United States)

    James A. Thompson; Randall K. Kolka

    2005-01-01

    Carbon storage in soils is important to forest ecosystems. Moreover, forest soils may serve as important C sinks for ameliorating excess atmospheric CO2. Spatial estimates of soil organic C (SOC) storage have traditionally relied upon soil survey maps and laboratory characterization data. This approach does not account for inherent variability...

  8. Geotechnical Mapping of An-Najaf City, Iraq

    Directory of Open Access Journals (Sweden)

    Nadher Hassan Al-Baghdadi

    2016-12-01

    Full Text Available The present paper submits a set geotechnical maps for the area of An-Najaf city, by using contour lines to represent the different geotechnical properties of the soil. The present research work is very important step toward preparing a geotechnical database for this region, to complete the geotechnical database over all the country, (Iraq. Using such a database is very important in geotechincal investigation, reconnaissance phase, of construction projects. Within this phase of site investigation, numbers, depths and locations of the boreholes needed, will be determined. A well known commercial software (SURFER 11, was used to produce the all the contour maps of geotechnical properties presented herein. A forty nine (49 contour maps were produced to cover the variations, within the geotechnical properties of the soil, to produce realistic description to these soil properties. Both Google maps and Universal Transverse Mercator coordinate system (UTM have been used in the contour maps for easy use.

  9. Soil moisture memory at sub-monthly time scales

    Science.gov (United States)

    Mccoll, K. A.; Entekhabi, D.

    2017-12-01

    For soil moisture-climate feedbacks to occur, the soil moisture storage must have `memory' of past atmospheric anomalies. Quantifying soil moisture memory is, therefore, essential for mapping and characterizing land-atmosphere interactions globally. Most previous studies estimate soil moisture memory using metrics based on the autocorrelation function of the soil moisture time series (e.g., the e-folding autocorrelation time scale). This approach was first justified by Delworth and Manabe (1988) on the assumption that monthly soil moisture time series can be modelled as red noise. While this is a reasonable model for monthly soil moisture averages, at sub-monthly scales, the model is insufficient due to the highly non-Gaussian behavior of the precipitation forcing. Recent studies have shown that significant soil moisture-climate feedbacks appear to occur at sub-monthly time scales. Therefore, alternative metrics are required for defining and estimating soil moisture memory at these shorter time scales. In this study, we introduce metrics, based on the positive and negative increments of the soil moisture time series, that can be used to estimate soil moisture memory at sub-monthly time scales. The positive increments metric corresponds to a rapid drainage time scale. The negative increments metric represents a slower drying time scale that is most relevant to the study of land-atmosphere interactions. We show that autocorrelation-based metrics mix the two time scales, confounding physical interpretation. The new metrics are used to estimate soil moisture memory at sub-monthly scales from in-situ and satellite observations of soil moisture. Reference: Delworth, Thomas L., and Syukuro Manabe. "The Influence of Potential Evaporation on the Variabilities of Simulated Soil Wetness and Climate." Journal of Climate 1, no. 5 (May 1, 1988): 523-47. doi:10.1175/1520-0442(1988)0012.0.CO;2.

  10. 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

  11. Correlation signatures of wet soils and snows. [algorithm development and computer programming

    Science.gov (United States)

    Phillips, M. R.

    1972-01-01

    Interpretation, analysis, and development of algorithms have provided the necessary computational programming tools for soil data processing, data handling and analysis. Algorithms that have been developed thus far, are adequate and have been proven successful for several preliminary and fundamental applications such as software interfacing capabilities, probability distributions, grey level print plotting, contour plotting, isometric data displays, joint probability distributions, boundary mapping, channel registration and ground scene classification. A description of an Earth Resources Flight Data Processor, (ERFDP), which handles and processes earth resources data under a users control is provided.

  12. Predicting radiocaesium sorption characteristics with soil chemical properties for Japanese soils.

    Science.gov (United States)

    Uematsu, Shinichiro; Smolders, Erik; Sweeck, Lieve; Wannijn, Jean; Van Hees, May; Vandenhove, Hildegarde

    2015-08-15

    The high variability of the soil-to-plant transfer factor of radiocaesium (RCs) compels a detailed analysis of the radiocaesium interception potential (RIP) of soil, which is one of the specific factors ruling the RCs transfer. The range of the RIP values for agricultural soils in the Fukushima accident affected area has not yet been fully surveyed. Here, the RIP and other major soil chemical properties were characterised for 51 representative topsoils collected in the vicinity of the Fukushima contaminated area. The RIP ranged a factor of 50 among the soils and RIP values were lower for Andosols compared to other soils, suggesting a role of soil mineralogy. Correlation analysis revealed that the RIP was most strongly and negatively correlated to soil organic matter content and oxalate extractable aluminium. The RIP correlated weakly but positively to soil clay content. The slope of the correlation between RIP and clay content showed that the RIP per unit clay was only 4.8 mmol g(-1) clay, about threefold lower than that for clays of European soils, suggesting more amorphous minerals and less micaceous minerals in the clay fraction of Japanese soils. The negative correlation between RIP and soil organic matter may indicate that organic matter can mask highly selective sorption sites to RCs. Multiple regression analysis with soil organic matter and cation exchange capacity explained the soil RIP (R(2)=0.64), allowing us to map soil RIP based on existing soil map information. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Study of the behaviour of radon in soil and the interpretation of radon anomalies in the exploration for uranium

    International Nuclear Information System (INIS)

    Bhatnagar, A.S.

    1975-04-01

    The report presents detailed tables of data on radon distribution patterns to enable an interpretation of the anomalies to be carried out in the process of exploration for uranium. The distribution of radon in soils fits into a lognormal pattern. In places where uranium mineralization exists, the distribution pattern is a two lognormal one. This method can be used to classify areas and delineate them according to the distribution pattern found over them. The field work was carried out in the Delhi area, in Turumdih and in Udaisagar

  14. The role of soil quality maps in the reuse of lightly contaminated soil

    NARCIS (Netherlands)

    Lamé, F.P.J.; Leenaers, H.; Zegwaard, J.

    2000-01-01

    In 1999 the Dutch government agreed on a new policy regarding the reuse of lightly contaminated soil. From now on, lightly contaminated soil may be reused under conditions of soil-quality management. The municipal authorities supervise the reuse under this new regime. Two basic criteria need to be

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

    Science.gov (United States)

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

    1975-01-01

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

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

    Science.gov (United States)

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

    2014-05-01

    With the upcoming launch of the next generation of hyperspectral satellites that will routinely deliver high spectral resolution images for the entire globe (e.g. EnMAP, HISUI, HyspIRI, HypXIM, PRISMA), an increasing demand for the availability/accessibility of hyperspectral soil products is coming from the geoscience community. Indeed, many robust methods for the prediction of soil properties based on imaging spectroscopy already exist and have been successfully used for a wide range of soil mapping airborne applications. Nevertheless, these methods require expert know-how and fine-tuning, which makes them used sparingly. More developments are needed toward easy-to-access soil toolboxes as a major step toward the operational use of hyperspectral soil products for Earth's surface processes monitoring and modelling, to allow non-experienced users to obtain new information based on non-expensive software packages where repeatability of the results is an important prerequisite. In this frame, based on the EU-FP7 EUFAR (European Facility for Airborne Research) project and EnMAP satellite science program, higher performing soil algorithms were developed at the GFZ German Research Center for Geosciences as demonstrators for end-to-end processing chains with harmonized quality measures. The algorithms were built-in into the HYSOMA (Hyperspectral SOil MApper) software interface, providing an experimental platform for soil mapping applications of hyperspectral imagery that gives the choice of multiple algorithms for each soil parameter. The software interface focuses on fully automatic generation of semi-quantitative soil maps such as soil moisture, soil organic matter, iron oxide, clay content, and carbonate content. Additionally, a field calibration option calculates fully quantitative soil maps provided ground truth soil data are available. Implemented soil algorithms have been tested and validated using extensive in-situ ground truth data sets. The source of the HYSOMA

  17. Ultrahigh Dimensional Variable Selection for Interpolation of Point Referenced Spatial Data: A Digital Soil Mapping Case Study

    Science.gov (United States)

    Lamb, David W.; Mengersen, Kerrie

    2016-01-01

    Modern soil mapping is characterised by the need to interpolate point referenced (geostatistical) observations and the availability of large numbers of environmental characteristics for consideration as covariates to aid this interpolation. Modelling tasks of this nature also occur in other fields such as biogeography and environmental science. This analysis employs the Least Angle Regression (LAR) algorithm for fitting Least Absolute Shrinkage and Selection Operator (LASSO) penalized Multiple Linear Regressions models. This analysis demonstrates the efficiency of the LAR algorithm at selecting covariates to aid the interpolation of geostatistical soil carbon observations. Where an exhaustive search of the models that could be constructed from 800 potential covariate terms and 60 observations would be prohibitively demanding, LASSO variable selection is accomplished with trivial computational investment. PMID:27603135

  18. Research on Topographic Map Updating

    Directory of Open Access Journals (Sweden)

    Ivana Javorović

    2013-04-01

    Full Text Available The investigation of interpretability of panchromatic satellite image IRS-1C integrated with multispectral Landsat TM image with the purpose of updating the topographic map sheet at the scale of 1:25 000 has been described. The geocoding of source map was based on trigonometric points of the map sheet. Satellite images were geocoded using control points selected from the map. The contents of map have been vectorized and topographic database designed. The digital image processing improved the interpretability of images. Then, the vectorization of new contents was made. The change detection of the forest and water area was defined by using unsupervised classification of spatial and spectral merged images. Verification of the results was made using corresponding aerial photographs. Although this methodology could not insure the complete updating of topographic map at the scale of 1:25 000, the database has been updated with huge amount of data. Erdas Imagine 8.3. software was used. 

  19. An Overview of the Transactional Interpretation of Quantum Mechanics

    Science.gov (United States)

    Cramer, John G.

    1988-02-01

    The transactional interpretation of quantum mechanics (TI) is summarized and various points concerning the TI and its relation to the Copenhagen interpretation (CI) are considered. Questions concerning mapping the TI onto the CI, of advanced waves as solutions to proper wave equations, of collapse and the QM formalism, and of the relation of quantum mechanical interpretations to experimental tests and results are discussed.

  20. Mapping geogenic radon potential by regression kriging

    Energy Technology Data Exchange (ETDEWEB)

    Pásztor, László [Institute for Soil Sciences and Agricultural Chemistry, Centre for Agricultural Research, Hungarian Academy of Sciences, Department of Environmental Informatics, Herman Ottó út 15, 1022 Budapest (Hungary); Szabó, Katalin Zsuzsanna, E-mail: sz_k_zs@yahoo.de [Department of Chemistry, Institute of Environmental Science, Szent István University, Páter Károly u. 1, Gödöllő 2100 (Hungary); Szatmári, Gábor; Laborczi, Annamária [Institute for Soil Sciences and Agricultural Chemistry, Centre for Agricultural Research, Hungarian Academy of Sciences, Department of Environmental Informatics, Herman Ottó út 15, 1022 Budapest (Hungary); Horváth, Ákos [Department of Atomic Physics, Eötvös University, Pázmány Péter sétány 1/A, 1117 Budapest (Hungary)

    2016-02-15

    Radon ({sup 222}Rn) gas is produced in the radioactive decay chain of uranium ({sup 238}U) which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on the physical and meteorological parameters of the soil and can enter and accumulate in buildings. Health risks originating from indoor radon concentration can be attributed to natural factors and is characterized by geogenic radon potential (GRP). Identification of areas with high health risks require spatial modeling, that is, mapping of radon risk. In addition to geology and meteorology, physical soil properties play a significant role in the determination of GRP. In order to compile a reliable GRP map for a model area in Central-Hungary, spatial auxiliary information representing GRP forming environmental factors were taken into account to support the spatial inference of the locally measured GRP values. Since the number of measured sites was limited, efficient spatial prediction methodologies were searched for to construct a reliable map for a larger area. Regression kriging (RK) was applied for the interpolation using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly, the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Overall accuracy of the map was tested by Leave-One-Out Cross-Validation. Furthermore the spatial reliability of the resultant map is also estimated by the calculation of the 90% prediction interval of the local prediction values. The applicability of the applied method as well as that of the map is discussed briefly. - Highlights: • A new method

  1. Mapping geogenic radon potential by regression kriging

    International Nuclear Information System (INIS)

    Pásztor, László; Szabó, Katalin Zsuzsanna; Szatmári, Gábor; Laborczi, Annamária; Horváth, Ákos

    2016-01-01

    Radon ( 222 Rn) gas is produced in the radioactive decay chain of uranium ( 238 U) which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on the physical and meteorological parameters of the soil and can enter and accumulate in buildings. Health risks originating from indoor radon concentration can be attributed to natural factors and is characterized by geogenic radon potential (GRP). Identification of areas with high health risks require spatial modeling, that is, mapping of radon risk. In addition to geology and meteorology, physical soil properties play a significant role in the determination of GRP. In order to compile a reliable GRP map for a model area in Central-Hungary, spatial auxiliary information representing GRP forming environmental factors were taken into account to support the spatial inference of the locally measured GRP values. Since the number of measured sites was limited, efficient spatial prediction methodologies were searched for to construct a reliable map for a larger area. Regression kriging (RK) was applied for the interpolation using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly, the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Overall accuracy of the map was tested by Leave-One-Out Cross-Validation. Furthermore the spatial reliability of the resultant map is also estimated by the calculation of the 90% prediction interval of the local prediction values. The applicability of the applied method as well as that of the map is discussed briefly. - Highlights: • A new method, regression

  2. NEPR Geographic Zone Map 2015

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This geographic zone map was created by interpreting satellite and aerial imagery, seafloor topography (bathymetry model), and the new NEPR Benthic Habitat Map...

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

    Science.gov (United States)

    Oh, Hyun-Joo; Pradhan, Biswajeet

    2011-09-01

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

  4. L-band HIgh Spatial Resolution Soil Moisture Mapping using SMALL UnManned Aerial Systems

    Science.gov (United States)

    Dai, E.; Venkitasubramony, A.; Gasiewski, A. J.; Stachura, M.; Elston, J. S.; Walter, B.; Lankford, D.; Corey, C.

    2017-12-01

    Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 provided new passive global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions of 36 km. However, there exists a need for measurements of soil moisture on much smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters. Compared with other methods of validation based on either in-situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed ( km scale) coverage at very high spatial resolution ( 15 m) suitable for scaling studies, and at comparatively low operator cost. To demonstrate the LDCR several flights had been performed during field experiments at the Canton Oklahoma Soilscape site and Yuma Colorado Irrigation Research Foundation (IRF) site in 2015 and 2016, respectively, using LDCR Revision A and Tempest sUAS. The scientific intercomparisons of LDCR retrieved soil moisture and in-situ measurements will be presented. LDCR Revision B has been built and integrated into SuperSwift sUAS and additional field experiments will be performed at IRF in 2017. In Revision B the IF signal is sampled at 80 MS/s to enable digital correlation and RFI mitigation capabilities, in addition to analog correlation. [1] McIntyre, E.M., A.J. Gasiewski, and D. Manda D, "Near Real-Time Passive C

  5. Percolation theory and its application for interpretation of soil water retention curves

    International Nuclear Information System (INIS)

    Kodesova, R.

    2004-01-01

    The soil porous system has traditionally been deduced from the soil-water retention curve with the assumption of homogeneity and free accessibility of pores, defined as capillary tubes, from the sink/source of water. But real soil fabric is mostly characterized by aggregates. In this case, the soil porous system cannot be modeled as a homogeneous one. To examine the differences between homogeneous and heterogeneous soil porous systems, we studied two types of soils: sandy soil and coarse sandy soil. We applied image processing filters and the ARC/INFO Grid module to analyze pore sizes in both soils from their electron microscope images taken at two different magnifications. We used the resulting pore-size distribution data to generate 3-D porous media consisting of pores and throats. The homogeneous pore structure was created as a mono-modal pore-throat network with one pore-size distribution. The heterogeneous pore structure was designed as a bi-modal pore-throat network with two pore-size distributions, where the pore sizes were hierarchically arranged in the nodes of the network. We applied the percolation model to simulate water and air displacement in these networks. The distribution of water in the nodes of the networks was studied increasing/decreasing steps of pressure head and the drainage and wetting branches of the retention curves were evaluated. The soil-water retention curves modeled for the mono-modal and bi-modal porous systems had different characters. The simulated shape of the retention curve in the mono-modal case was close to the step-like form of a retention curve characteristic of unstructured soil. The shape of the simulated retention curve in the bi-modal case was smoother, more gradual, and closer to the shape of the retention curve of a real, structured soil. (author)

  6. Modelling and mapping the topsoil organic carbon content for Tanzania

    Science.gov (United States)

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

    2014-05-01

    Soil organic carbon (SOC), held in soil organic matter, is a key indicator of soil health and plays an important role in the global carbon cycle. The soil can act as a net source or sink of carbon depending on land use and management. Deforestation and forest degradation lead to the release of vast amounts of carbon from the soil in the form of greenhouse gasses, especially in tropical countries. Tanzania has a high deforestation rate: it is estimated that the country loses 1.1% of its total forested area annually. During 2010-2013 Tanzania has been a pilot country under the UN-REDD programme. This programme has supported Tanzania in its initial efforts towards reducing greenhouse gas emission from forest degradation and deforestation and towards preserving soil carbon stocks. Formulation and implementation of the national REDD strategy requires detailed information on the five carbon pools among these the SOC pool. The spatial distribution of SOC contents and stocks was not available for Tanzania. The initial aim of this research, was therefore to develop high-resolution maps of the SOC content for the country. The mapping exercise was carried out in a collaborative effort with four Tanzanian institutes and data from the Africa Soil Information Service initiative (AfSIS). The mapping exercise was provided with over 3200 field observations on SOC from four sources; this is the most comprehensive soil dataset collected in Tanzania so far. The main source of soil samples was the National Forest Monitoring and Assessment (NAFORMA). The carbon maps were generated by means of digital soil mapping using regression-kriging. Maps at 250 m spatial resolution were developed for four depth layers: 0-10 cm, 10-20 cm, 20-30 cm, and 0-30 cm. A total of 37 environmental GIS data layers were prepared for use as covariates in the regression model. These included vegetation indices, terrain parameters, surface temperature, spectral reflectances, a land cover map and a small

  7. An overview of the transactional interpretation of quantum mechanics

    Energy Technology Data Exchange (ETDEWEB)

    Cramer, J.G.

    1987-01-01

    We summarize the transactional interpretation of quantum mechanics (TI) and consider various points concerning the TI and its relation to the Copenhagen interpretation (CI). Questions concerning mapping the TI onto the CI, of advanced waves as solutions to proper wave equations, of collapse and the QM formalism, and of the relation of quantum mechanical interpretations to experimental tests and results are discussed. 12 refs.

  8. An overview of the transactional interpretation of quantum mechanics

    International Nuclear Information System (INIS)

    Cramer, J.G.

    1987-01-01

    We summarize the transactional interpretation of quantum mechanics (TI) and consider various points concerning the TI and its relation to the Copenhagen interpretation (CI). Questions concerning mapping the TI onto the CI, of advanced waves as solutions to proper wave equations, of collapse and the QM formalism, and of the relation of quantum mechanical interpretations to experimental tests and results are discussed. 12 refs

  9. Comparison of Capability of Digitizing Methods to Predict Soil classification According to the Soil Taxonomy and World Reference Base for Soil Resources

    Directory of Open Access Journals (Sweden)

    zohreh mosleh

    2017-02-01

    Full Text Available Introduction: Soil classification generally aims to establish a taxonomy based on breaking the soil continuum into homogeneous groups that can highlight the essential differences in soil properties and functions between classes.The two most widely used modern soil classification schemes are Soil Taxonomy (ST and World Reference Base for Soil Resources (WRB.With the development of computers and technology, digital and quantitative approaches have been developed. These new techniques that include the spatial prediction of soil properties or classes, relies on finding the relationships between soil and the auxiliary information that explain the soil forming factors or processes and finally predict soil patterns on the landscape. These approaches are commonly referred to as digital soil mapping (DSM (14. A key component of any DSM mapping activity is the method used to define the relationship between soil observation and auxiliary information (4. Several types of machine learning approaches have been applied for digital soil mapping of soil classes, such as logistic and multinomial logistic regressions (10,12, random forests (15, neural networks (3,13 and classification trees (22,4. Many decisions about the soil use and management are based on the soil differences that cannot be captured by higher taxonomic levels (i.e., order, suborder and great group (4. In low relief areas such as plains, it is expected that the soil forming factors are more homogenous and auxiliary information explaining soil forming factors may have low variation and cannot show the soil variability. Materials and Methods: The study area is located in the Shahrekord plain of Chaharmahal-Va-Bakhtiari province. According tothe semi-detailed soil survey (16, 120 pedons with approximate distance of 750 m were excavated and described according to the “field book for describing and sampling soils” (19. Soil samples were taken from different genetic horizons, air dried and

  10. Global assessment of soil organic carbon stocks and spatial distribution of histosols: the Machine Learning approach

    Science.gov (United States)

    Hengl, Tomislav

    2016-04-01

    Preliminary results of predicting distribution of soil organic soils (Histosols) and soil organic carbon stock (in tonnes per ha) using global compilations of soil profiles (about 150,000 points) and covariates at 250 m spatial resolution (about 150 covariates; mainly MODIS seasonal land products, SRTM DEM derivatives, climatic images, lithological and land cover and landform maps) are presented. We focus on using a data-driven approach i.e. Machine Learning techniques that often require no knowledge about the distribution of the target variable or knowledge about the possible relationships. Other advantages of using machine learning are (DOI: 10.1371/journal.pone.0125814): All rules required to produce outputs are formalized. The whole procedure is documented (the statistical model and associated computer script), enabling reproducible research. Predicted surfaces can make use of various information sources and can be optimized relative to all available quantitative point and covariate data. There is more flexibility in terms of the spatial extent, resolution and support of requested maps. Automated mapping is also more cost-effective: once the system is operational, maintenance and production of updates are an order of magnitude faster and cheaper. Consequently, prediction maps can be updated and improved at shorter and shorter time intervals. Some disadvantages of automated soil mapping based on Machine Learning are: Models are data-driven and any serious blunders or artifacts in the input data can propagate to order-of-magnitude larger errors than in the case of expert-based systems. Fitting machine learning models is at the order of magnitude computationally more demanding. Computing effort can be even tens of thousands higher than if e.g. linear geostatistics is used. Many machine learning models are fairly complex often abstract and any interpretation of such models is not trivial and require special multidimensional / multivariable plotting and data mining

  11. Soil magnetic susceptibility: A quantitative proxy of soil drainage for use in ecological restoration

    Science.gov (United States)

    Grimley, D.A.; Wang, J.-S.; Liebert, D.A.; Dawson, J.O.

    2008-01-01

    Flooded, saturated, or poorly drained soils are commonly anaerobic, leading to microbially induced magnetite/maghemite dissolution and decreased soil magnetic susceptibility (MS). Thus, MS is considerably higher in well-drained soils (MS typically 40-80 ?? 10-5 standard international [SI]) compared to poorly drained soils (MS typically 10-25 ?? 10-5 SI) in Illinois, other soil-forming factors being equal. Following calibration to standard soil probings, MS values can be used to rapidly and precisely delineate hydric from nonhydric soils in areas with relatively uniform parent material. Furthermore, soil MS has a moderate to strong association with individual tree species' distribution across soil moisture regimes, correlating inversely with independently reported rankings of a tree species' flood tolerance. Soil MS mapping can thus provide a simple, rapid, and quantitative means for precisely guiding reforestation with respect to plant species' adaptations to soil drainage classes. For instance, in native woodlands of east-central Illinois, Quercus alba , Prunus serotina, and Liriodendron tulipifera predominantly occur in moderately well-drained soils (MS 40-60 ?? 10-5 SI), whereas Acer saccharinum, Carya laciniosa, and Fraxinus pennsylvanica predominantly occur in poorly drained soils (MS Urbana, IL, U.S.A.). Through use of soil MS maps calibrated to soil drainage class and native vegetation occurrence, restoration efforts can be conducted more successfully and species distributions more accurately reconstructed at the microecosystem level. ?? 2008 Society for Ecological Restoration International.

  12. Soil structural behaviour of flooded soils

    International Nuclear Information System (INIS)

    Taboada, M.A.

    2004-01-01

    The objectives of this presentation are to: identify factors determining of the structural behaviour of flooded soils, as compared to those acting in upland soils; analyse the influence of reductive processes on aggregate stabilising agents; discuss mechanisms of structural deterioration and recovery during the flooding-drying cycle, on the basis of a case study: cattle trampling effects in the flooding Pampa of Argentina. Flooded soils, now known as Hydric soils, are characteristic of wetlands and irrigated fields cropped to rice (paddy soils). In them, water covers the soil, or is present either at or near the surface of the soil all year or for varying periods of time during the year. Hydric soils belong to different taxa of the FAO-UNESCO Soil Map (2000). Fluvisols, Planosols and Gleysols are widespread distributed in the globe. The generation of redoximorphic features is due to different causes in each of them. Fluvisols are covered part of the year by surface water from river overflows; Planosols are soils having an impervious Bt horizon, supporting perched water during short periods; and Gleysols are soils affected by stagnant water tables during long periods

  13. New geological and tectonic map of Paleoproterozoic basement in western Burkina Faso: integrated interpretation of airborne geophysical and field data

    Science.gov (United States)

    Metelka, Vaclav; Baratoux, Lenka; Jessell, Mark; Naba, Seta

    2010-05-01

    The recent acquisition of regional scale airborne datasets over most of the West African craton sparked off a number of studies concentrating on their litho-tectonic interpretation. In such polydeformed terrains, where outcrop is very sparse or virtually nonexistent due to the presence of thick lateritic cover, geophysics and specifically geomagnetic surveying provide a wealth of information that facilitates the deciphering of regional litho-structural hierarchies. A revised geological and tectonic map of the Houndé and Boromo greenstone belts was derived by interpretation of aeromagnetic and gamma-ray spectrometric data constrained by field observations where available. Medium resolution geophysical data gridded at 250 meters acquired during the SYSMIN project served as a basis for the interpretation. This dataset was integrated with the SRTM digital elevation model and over 600 field observations. Furthermore, the BRGM/BUMIGEB SYSMIN project outcrops database (Castaing et al., 2003) as well as older outcrop maps, maintained by BUMIGEB, were used. Locally, outcrop maps and high resolution geophysics provided by mining companies (Orezone, SEMAFO, Volta Resources, Wega Mining) were employed. 2-D geophysical inversion modeling in GM-sys software using the ground gravity and airborne magnetic data was applied to three selected E-W profiles. Principal component analysis (PCA) of magnetic and radiometric data was a powerful tool for distinguishing different lithological units, in particular tholeiitic suites of basalts and gabbros and various volcano-sedimentary units. Some of the granite pluton limits can be traced as well using the PCA; however thick lateritic cover substantially hinders precise mapping. Magnetic data used on its own gave better results not only for granite limits but also for determining internal structures such as shear zones and concentric compositional zoning. Several major N-S to NNE-SSW oriented shear zones, representing most probably deep

  14. Soil erosion vulnerability in the verde river basin, southern minas gerais

    Directory of Open Access Journals (Sweden)

    Vinícius Augusto de Oliveira

    2014-06-01

    Full Text Available Soil erosion is one of the most significant environmental degradation processes. Mapping and assessment of soil erosion vulnerability is an important tool for planning and management of the natural resources. The objective of the present study was to apply the Revised Universal Soil Loss Equation (RUSLE using GIS tools to the Verde River Basin (VRB, southern Minas Gerais, in order to assess soil erosion vulnerability. A annual rainfall erosivity map was derived from the geographical model adjusted for Southeastern Brazil, calculating an annual value for each pixel. The maps of soil erodibility (K, topographic factor (LS, and use and management of soils (C were developed from soils and their uses map and the digital elevation model (DEM developed for the basin. In a GIS environment, the layers of the factors were combined to create the soil erosion vulnerability map according to RUSLE. The results showed that, in general, the soils of the VRB present a very high vulnerability to water erosion, with 58.68% of soil losses classified as "High" and "Extremely High" classes. In the headwater region of VRB, the predominant classes were "Very High" and "Extremely High" where there is predominance of Cambisols associated with extensive pastures. Furthermore, the integration of RUSLE/GIS showed an efficient tool for spatial characterization of soil erosion vulnerability in this important basin of the Minas Gerais state.

  15. 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...

  16. Soil

    International Nuclear Information System (INIS)

    Freudenschuss, A.; Huber, S.; Riss, A.; Schwarz, S.; Tulipan, M.

    2002-01-01

    Environmental soil surveys in each province of Austria have been performed, soils of about 5,000 sites were described and analyzed for nutrients and pollutants, the majority of these data are recorded in the soil information system of Austria (BORIS) soil database, http://www.ubavie.gv.at/umweltsituation/boden/boris), which also contains a soil map of Austria, data from 30 specific investigations mainly in areas with industry and results from the Austria - wide cesium investigation. With respect to the environmental state of soils a short discussion is given, including two geographical charts, one showing which sites have soil data (2001) and the other the cadmium distribution in top soils according land use (forest, grassland, arable land, others). Information related to the soil erosion, Corine land cover (Europe-wide land cover database), evaluation of pollutants in soils (reference values of As, Cd, Co, Cr, Cu, Hg, Mo, Ni, Se, Pb, Tl, Va, Zn, AOX, PAH, PCB, PCDD/pcdf, dioxin), and relevant Austrian and European standards and regulations is provided. Figs. 2, Tables 4. (nevyjel)

  17. 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.

  18. 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.

  19. Detailed deposition density maps constructed by large-scale soil sampling for gamma-ray emitting radioactive nuclides from the Fukushima Dai-ichi Nuclear Power Plant accident.

    Science.gov (United States)

    Saito, Kimiaki; Tanihata, Isao; Fujiwara, Mamoru; Saito, Takashi; Shimoura, Susumu; Otsuka, Takaharu; Onda, Yuichi; Hoshi, Masaharu; Ikeuchi, Yoshihiro; Takahashi, Fumiaki; Kinouchi, Nobuyuki; Saegusa, Jun; Seki, Akiyuki; Takemiya, Hiroshi; Shibata, Tokushi

    2015-01-01

    Soil deposition density maps of gamma-ray emitting radioactive nuclides from the Fukushima Dai-ichi Nuclear Power Plant (NPP) accident were constructed on the basis of results from large-scale soil sampling. In total 10,915 soil samples were collected at 2168 locations. Gamma rays emitted from the samples were measured by Ge detectors and analyzed using a reliable unified method. The determined radioactivity was corrected to that of June 14, 2011 by considering the intrinsic decay constant of each nuclide. Finally the deposition maps were created for (134)Cs, (137)Cs, (131)I, (129m)Te and (110m)Ag. The radioactivity ratio of (134)Cs-(137)Cs was almost constant at 0.91 regardless of the locations of soil sampling. The radioactivity ratios of (131)I and (129m)Te-(137)Cs were relatively high in the regions south of the Fukushima NPP site. Effective doses for 50 y after the accident were evaluated for external and inhalation exposures due to the observed radioactive nuclides. The radiation doses from radioactive cesium were found to be much higher than those from the other radioactive nuclides. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

  20. 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.

  1. Assessment and visualization of uncertainty for countrywide soil organic matter map of Hungary using local entropy

    Science.gov (United States)

    Szatmári, Gábor; Pásztor, László

    2016-04-01

    Uncertainty is a general term expressing our imperfect knowledge in describing an environmental process and we are aware of it (Bárdossy and Fodor, 2004). Sampling, laboratory measurements, models and so on are subject to uncertainty. Effective quantification and visualization of uncertainty would be indispensable to stakeholders (e.g. policy makers, society). Soil related features and their spatial models should be stressfully targeted to uncertainty assessment because their inferences are further used in modelling and decision making process. The aim of our present study was to assess and effectively visualize the local uncertainty of the countrywide soil organic matter (SOM) spatial distribution model of Hungary using geostatistical tools and concepts. The Hungarian Soil Information and Monitoring System's SOM data (approximately 1,200 observations) and environmental related, spatially exhaustive secondary information (i.e. digital elevation model, climatic maps, MODIS satellite images and geological map) were used to model the countrywide SOM spatial distribution by regression kriging. It would be common to use the calculated estimation (or kriging) variance as a measure of uncertainty, however the normality and homoscedasticity hypotheses have to be refused according to our preliminary analysis on the data. Therefore, a normal score transformation and a sequential stochastic simulation approach was introduced to be able to model and assess the local uncertainty. Five hundred equally probable realizations (i.e. stochastic images) were generated. The number of the stochastic images is fairly enough to provide a model of uncertainty at each location, which is a complete description of uncertainty in geostatistics (Deutsch and Journel, 1998). Furthermore, these models can be applied e.g. to contour the probability of any events, which can be regarded as goal oriented digital soil maps and are of interest for agricultural management and decision making as well. A

  2. Mapping of transuranic elements in soil by nuclear track methodology

    International Nuclear Information System (INIS)

    Espinosa, G.

    2001-01-01

    An alternative method is presented to map the distribution of transuranic elements, which is characterized by its simplicity in both implementation and instrumentation. The method is based on the interaction of alpha particles in polymeric materials and the formation of tracks, which become visible after chemical etching. Nuclear track detectors are placed on the soil in order to evaluate the distribution of the radioactive material and its relative intensity for transuranic contaminants. CR-39 polycarbonate was used as a nuclear track detector in this study. Chemical etching was done with a 6.25M KOH solution in a closed system for 16 hours. The readings were performed in an automatic system using digital image analysis. The results show the distribution of the contaminants and their location, identifying the zones with large intensities. This method is attractive for use in areas contaminated with alpha particles, and specially transuranic elements, because it involves in situ measurements, generates very low amounts of radioactive waste, and the detectors are easily handled. (author)

  3. Diagnostic of the soils fertility and estimation about the necessities of fertilizers for the watering district of the Zulia River (North of Santander)

    International Nuclear Information System (INIS)

    Sanchez Ortega, Gloria Patricia; Yepes Orjuela, Rodrigo Hernando; Mesa Lopez, Luis Jorge

    1998-01-01

    A diagnosis of the main chemical characteristics of the rice-growing soils of the Zulia River irrigation district (Norte de Santander) was made between the semesters 1994b and 1995a, aimed at identifying the main nutritional limitants and seeking the definition of some parameters on the adequate managements of fertilizers and amends. The use of the pre-existing soil mapping, as well us mineralogical, leaf and irrigation-water quality analysis, associated with a survey carried out among the farmers, allowed for a greater sample precision, better interpretation of the results, and more accurate final recommendations

  4. Spatial and temporal monitoring of soil moisture using surface electrical resistivity tomography in Mediterranean soils

    NARCIS (Netherlands)

    Alamry, Abdulmohsen S.; van der Meijde, Mark; Noomen, Marleen; Addink, Elisabeth A.|info:eu-repo/dai/nl/224281216; van Benthem, Rik; de Jong, Steven M.|info:eu-repo/dai/nl/120221306

    2017-01-01

    ERT techniques are especially promising in (semi-arid) areas with shallow and rocky soils where other methods fail to produce soil moisture maps and to obtain soil profile information. Electrical Resistivity Tomography (ERT) was performed in the Peyne catchment in southern France at four sites

  5. 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.

  6. 238U content in soils of Byelorussia

    International Nuclear Information System (INIS)

    Shagalova, Eh.D.

    1986-01-01

    Results of detection in Byelorussian soils of a heavy natural radionuclide 238 U and its content in humus horizons of the soils on map-schemes are presented. 238 U content is determined by complete decomposition of soils by acids, isolation from thorium using EhDEh-10 P anionite and subsequent solution colorimetry. It is shown that the content of uranium-238 in soils decreases from the North to the South. Its maximum amount (>2x10 -4 %) is detected in turfy-podsolic soils in lake-glacier loams; the minimum one ( -4 %)- in peatymarshy soils. The map-scheme of 238 U content is a background base. Using the background base it is possible to trace the change in uranium content in soils under conditions of technogenic effect and to substantiate the efficiency of environment protection measures

  7. Soils [Chapter 4.2

    Science.gov (United States)

    Daniel G. Neary; Johannes W. A. Langeveld

    2015-01-01

    Soils are crucial for profitable and sustainable biomass feedstock production. They provide nutrients and water, give support for plants, and provide habitat for enormous numbers of biota. There are several systems for soil classification. FAO has provided a generic classification system that was used for a global soil map (Bot et al., 2000). The USDA Natural Resources...

  8. Geo-environmental mapping tool applied to pipeline design

    Energy Technology Data Exchange (ETDEWEB)

    Andrade, Karina de S.; Calle, Jose A.; Gil, Euzebio J. [Geomecanica S/A Tecnologia de Solo Rochas e Materiais, Rio de Janeiro, RJ (Brazil); Sare, Alexandre R. [Geomechanics International Inc., Houston, TX (United States); Soares, Ana Cecilia [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil)

    2009-07-01

    The Geo-Environmental Mapping is an improvement of the Geological-Geotechnical Mapping used for basic pipeline designs. The main purpose is to assembly the environmental, geotechnical and geological concepts in a methodological tool capable to predict constrains and reduce the pipeline impact to the environment. The Geo-Environmental mapping was built to stress the influence of soil/structure interaction, related to the physical effect that comes from the contact between structures and soil or rock. A Geological-Geotechnical-Environmental strip (chart) was presented to emphasize the pipeline operational constrains and its influence to the environment. The mapping was developed to clearly show the occurrence and properties of geological materials divided into geotechnical domain units (zones). The strips present construction natural properties, such as: excavability, stability of the excavation and soil re-use capability. Also, the environmental constrains were added to the geological-geotechnical mapping. The Geo-Environmental Mapping model helps the planning of the geotechnical and environmental inquiries to be carried out during executive design, the discussion on the types of equipment to be employed during construction and the analysis of the geological risks and environmental impacts to be faced during the built of the pipeline. (author)

  9. World Reference Base for Soil Resources

    NARCIS (Netherlands)

    Deckers, J.A.; Driessen, P.M.; Nachtergaele, F.O.; Spaargaren, O.C.

    2002-01-01

    In 1998, the International Union of Soil Sciences (IUSS) officially adopted the world reference base for soil resources (WRB) as the Union's system for soil correlation. The structure, concepts, and definitions of the WRB are strongly influenced by the FAO-UNESCO legend of the soil map of the world

  10. Geochemical baseline studies of soil in Finland

    Science.gov (United States)

    Pihlaja, Jouni

    2017-04-01

    The soil element concentrations regionally vary a lot in Finland. Mostly this is caused by the different bedrock types, which are reflected in the soil qualities. Geological Survey of Finland (GTK) is carrying out geochemical baseline studies in Finland. In the previous phase, the research is focusing on urban areas and mine environments. The information can, for example, be used to determine the need for soil remediation, to assess environmental impacts or to measure the natural state of soil in industrial areas or mine districts. The field work is done by taking soil samples, typically at depth between 0-10 cm. Sampling sites are chosen to represent the most vulnerable areas when thinking of human impacts by possible toxic soil element contents: playgrounds, day-care centers, schools, parks and residential areas. In the mine districts the samples are taken from the areas locating outside the airborne dust effected areas. Element contents of the soil samples are then analyzed with ICP-AES and ICP-MS, Hg with CV-AAS. The results of the geochemical baseline studies are published in the Finnish national geochemical baseline database (TAPIR). The geochemical baseline map service is free for all users via internet browser. Through this map service it is possible to calculate regional soil baseline values using geochemical data stored in the map service database. Baseline data for 17 elements in total is provided in the map service and it can be viewed on the GTK's web pages (http://gtkdata.gtk.fi/Tapir/indexEN.html).

  11. Combining a finite mixture distribution model with indicator kriging to delineate and map the spatial patterns of soil heavy metal pollution in Chunghua County, central Taiwan

    International Nuclear Information System (INIS)

    Lin Yupin; Cheng Baiyou; Shyu, G.-S.; Chang, T.-K.

    2010-01-01

    This study identifies the natural background, anthropogenic background and distribution of contamination caused by heavy metal pollutants in soil in Chunghua County of central Taiwan by using a finite mixture distribution model (FMDM). The probabilities of contaminated area distribution are mapped using single-variable indicator kriging and multiple-variable indicator kriging (MVIK) with the FMDM cut-off values and regulation thresholds for heavy metals. FMDM results indicate that Cr, Cu, Ni and Zn can be individually fitted by a mixture model representing the background and contamination distributions of the four metals in soil. The FMDM cut-off values for contamination caused by the metals are close to the regulation thresholds, except for the cut-off value of Zn. The receiver operating characteristic (ROC) curve validates that indicator kriging and MVIK with FMDM cut-off values can reliably delineate heavy metals contamination, particularly for areas lacking background information and high heavy metal concentrations in soil. - Effectively determine pollution threshold and map contaminated areas.

  12. 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.)

    Energy Technology Data Exchange (ETDEWEB)

    Samecka-Cymerman, A., E-mail: sameckaa@biol.uni.wroc.p [Department of Ecology, Biogeochemistry and Environmental Protection, Wroclaw University, ul. Kanonia 6/8, 50-328 Wroclaw (Poland); Stankiewicz, A.; Kolon, K. [Department of Ecology, Biogeochemistry and Environmental Protection, Wroclaw University, ul. Kanonia 6/8, 50-328 Wroclaw (Poland); Kempers, A.J. [Department of Environmental Sciences, Radboud University of Nijmegen, Toernooiveld, 6525 ED Nijmegen (Netherlands)

    2009-07-15

    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 Olesnica (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 Wroclaw 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. - Once trained, SOFM could be used in the future to recognize types of pollution.

  13. Automatic interpretation of seismic micro facies using the fuzzy mathematics method

    Energy Technology Data Exchange (ETDEWEB)

    Dongrun, G.; Gardner, G.H.F.

    1988-01-01

    The interpretation of seismic micro facies concentrates on changes involving single reflection or several reflections, and endeavors to explain the relations between these changes and stratigraphic variation or hydrocarbon accumulation. In most cases, one can not determine the geological significance of reflection character anomalies on single or several seismic sections. But when one maps them on a plane, their distribution may on the whole indicate the geological significance. It is stated how the fuzzy method is used on a VAX computer to automatically construct a plane map of the reflection character changes in a time window. What an interpreter needs to do for whole interpretation is only to provide some parameters, such as time window, threshold, weight coefficients etc.

  14. MAPRAD: mapping of radioactivity in Brazilian soils

    International Nuclear Information System (INIS)

    Ribeiro, Fernando C.A.; Signorelli, Carla de A.; Conti, Claudio de C.; Lauria, Dejanira da C.; Ferreira, Ingryd M.; Carvalho, Laercio L. de; Rio, Monica A. Pires do; Trindade Filho, Octavio Luiz; Gonzalez, Sergio de A.; Silva, Tadeu Augusto de A.; Sousa, Wanderson de O.; Cunha, Fernanda G. da

    2011-01-01

    The MAPRAD Project main objective is to increase the knowledge of the distribution of natural radioactivity in soils of Brazilian national territory and to provide (among others) information which are essential for medical geology and environmental radiation safety researches and for decision-making process regarding soil contamination levels. It also aims to make available the generated information for researchers and for public, through an online database. Soil samples are collected by the Geological Survey of Brazil (CPRM) and are sent to the Institute of Radioprotection and Dosimetry (IRD), National Commission of Nuclear Energy (CNEN), where they are processed and analyzed for determination of concentrations of radionuclides by gamma spectrometry. The results are inserted into a database containing the sample information as geographic coordinates of the samples and land use. After the sample analysis, results are made available for the scientific community access on Internet. (author)

  15. ERTS data user no. 119: Effective use of ERTS multisensor data in the Great Plains. ERTS-1 MSS imagery: A tool for identifying soil associations

    Science.gov (United States)

    Myers, V. I. (Principal Investigator); Westin, F. C.

    1973-01-01

    The author has identified the following significant results. Soil association maps show the spatial relationships of land units developed in unique climatic, geologic, and topographic environments, and having characteristic slopes, soil depths, textures, available water capacities, permeabilities, and the like. ERTS-1 imagery was found to be a useful tool in the identification of soil associations since it provides a synoptic view of an 8 million acre scene, which is large enough so that the effect can be seen on soils of climate, topography, and geology. A regional view also allows soil associations to be observed over most, if not all, of their extent. ERTS-1 MSS imagery also provides four spectral bands taken every 18 days which give data on relief, hydrology, and vegetation, all of which bear on the delineation and interpretation of soil associations. Enlarged prints derived from the individual spectral bands and shown in gray tones were useful for identifying soil associations.

  16. Relação entre solo, vegetação e topografia em área de cerrado (Parque Estadual de Vassununga, SP: como se expressa em mapeamentos? The relationship among soil, vegetation and topography in a cerrado area (Vassununga State Park, SP: how well is it expressed in maps ?

    Directory of Open Access Journals (Sweden)

    Patricia Guidão Cruz Ruggiero

    2006-06-01

    map, b topographic map based on 5 m contour curves, and c a soil map based on chemical and physical soil features (soil samples collected at 54 sites at 0-5, 5-25, 40-60 e 80-100 cm depths and aerial photographs (1988, 1:40.000. These maps were reclassified to generate secondary maps at different levels of detail, and overlayed through a geographic information system. Contingency tables were generated, and chi-squared values and Cramér correlation coefficients were obtained to investigate the relationships between the maps. The semideciduous forest showed a strong correlation with the Oxissols; "campo cerrado" was associated to 620-650 m altitudes, probably due to sub-surface water dynamics. The refinement of the mapped information did not add to the interpretation of the relationships among soil, vegetation and topography, as the vegetation physiognomy does not respond directly nor independently to topography or to the usual soil classification.

  17. Distribution of soil organic carbon in the conterminous United States

    Science.gov (United States)

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

    2014-01-01

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

  18. The soils of the Parque Natural da Arrábida

    Directory of Open Access Journals (Sweden)

    Rolf Schrittenlocher

    1997-11-01

    Full Text Available The soils of the Parque Natural da Arrábida are surveyed along four "catenae" right across the Parque. Dominant soil formating processes and their regional importance are shown. The soils are described as units according to FAO (1988. On the basis of the FAO units an attempt is made to combine soil units with ecological classes. A comparison with the soil map 38-B and the portuguese classification (Cardoso 1964 is given. Unfortunately it is not possible to transform the units of that map into soil units according to FAO (1988.

  19. A GIS semiautomatic tool for classifying and mapping wetland soils

    Science.gov (United States)

    Moreno-Ramón, Héctor; Marqués-Mateu, Angel; Ibáñez-Asensio, Sara

    2016-04-01

    Wetlands are one of the most productive and biodiverse ecosystems in the world. Water is the main resource and controls the relationships between agents and factors that determine the quality of the wetland. However, vegetation, wildlife and soils are also essential factors to understand these environments. It is possible that soils have been the least studied resource due to their sampling problems. This feature has caused that sometimes wetland soils have been classified broadly. The traditional methodology states that homogeneous soil units should be based on the five soil forming-factors. The problem can appear when the variation of one soil-forming factor is too small to differentiate a change in soil units, or in case that there is another factor, which is not taken into account (e.g. fluctuating water table). This is the case of Albufera of Valencia, a coastal wetland located in the middle east of the Iberian Peninsula (Spain). The saline water table fluctuates throughout the year and it generates differences in soils. To solve this problem, the objectives of this study were to establish a reliable methodology to avoid that problems, and develop a GIS tool that would allow us to define homogeneous soil units in wetlands. This step is essential for the soil scientist, who has to decide the number of soil profiles in a study. The research was conducted with data from 133 soil pits of a previous study in the wetland. In that study, soil parameters of 401 samples (organic carbon, salinity, carbonates, n-value, etc.) were analysed. In a first stage, GIS layers were generated according to depth. The method employed was Bayesian Maxim Entropy. Subsequently, it was designed a program in GIS environment that was based on the decision tree algorithms. The goal of this tool was to create a single layer, for each soil variable, according to the different diagnostic criteria of Soil Taxonomy (properties, horizons and diagnostic epipedons). At the end, the program

  20. Mapping of forest types confined to the lay of land

    Directory of Open Access Journals (Sweden)

    S. K. Farber

    2018-04-01

    Full Text Available The principles for the formation of forest typological classification and outlines promising areas for development, allowing to solve problems of not only inventory and forest management, but also mapping forest types are discussed in the paper. The analysis is performed by interpreting the concept of «natural regularity» proposed by D. L. Armand (1975. It is shown when the left side of the pattern is a set of indicators of site condition, structure of forest typological constructions will take into account not only the static indicators of the stands, but also their location, the origin and direction of the succession. For relatively similar climatic conditions, the indicators of the lay of land mainly limit the environment of formation of vegetation cover. The method of mapping forest types provides for consideration of site condition and indicators of stands of forest types. Testing is conducted on a test axis West-Sayan forest district, located in the mountains of southern Siberia. Conjugation types of forests, indicators of the topography revealed through the analysis of literary sources and characteristics of forest types accompanying diagnostic table (Smagin et al., 1980. The work is done in a GIS environment using DEM SRTM and Landsat space images. For indexing locations, the inputs are accepted: altitude (gradation 100 m, flat location, slope up to 20° and 20° slopes with northern and southern exposure. Classification of pixels of satellite images is conducted by the method of unsupervised classification separately for each scene, the high-altitude zone and location, which allows increase of the quality of interpretation, because the types of forests are confined to the topography. However completely avoiding mistakes is not possible. The main reasons are an inaccuracy of the DEM and the hit in one class of spectral brightness of different objects of interpretation. The map legend includes characteristics of the terrain, description

  1. World Reference Base | FAO SOILS PORTAL | Food and Agriculture

    Science.gov (United States)

    > Soil classification > World Reference Base FAO SOILS PORTAL Survey Assessment Biodiversity Management Degradation/Restoration Policies/Governance Publications Soil properties Soil classification World Soil Maps and Databases World Reference Base Dominant soils of the world The World Reference Base (WRB

  2. Procedure for deriving qualitative contaminant attenuation maps from land type data

    CSIR Research Space (South Africa)

    Sililo, OTN

    2001-01-15

    Full Text Available A procedure is presented for deriving qualitative contaminant attenuation maps from available soils information. Unfortunately, in South Africa, no soil map with national coverage exists at a scale larger than 1:2 500 000. However, 1:250 000 land...

  3. Mind mapping in qualitative research.

    Science.gov (United States)

    Tattersall, Christopher; Powell, Julia; Stroud, James; Pringle, Jan

    We tested a theory that mind mapping could be used as a tool in qualitative research to transcribe and analyse an interview. We compared results derived from mind mapping with those from interpretive phenomenological analysis by examining patients' and carers' perceptions of a new nurse-led service. Mind mapping could be used to rapidly analyse simple qualitative audio-recorded interviews. More research is needed to establish the extent to which mind mapping can assist qualitative researchers.

  4. The use of proximal soil sensor data fusion and digital soil mapping for precision agriculture

    OpenAIRE

    Ji, Wenjun; Adamchuk, Viacheslav; Chen, Songchao; Biswas, Asim; Leclerc, Maxime; Viscarra Rossel, Raphael

    2017-01-01

    Proximal soil sensing (PSS) is a promising approach when it comes to detailed characterization of spatial soil heterogeneity. Since none of existing PSS systems can measure all soil information needed for implementation precision agriculture, sensor data fusion can provide a reasonable al- ternative to characterize the complexity of soils. In this study, we fused the data measured using a gamma-ray sensor, an apparent electrical conductivity (ECa) sensor, and a commercial Veris MS...

  5. Spatial distribution of soil moisture in precision farming using integrated soil scanning and field telemetry data

    Science.gov (United States)

    Kalopesas, Charalampos; Galanis, George; Kalopesa, Eleni; Katsogiannos, Fotis; Kalafatis, Panagiotis; Bilas, George; Patakas, Aggelos; Zalidis, George

    2015-04-01

    Mapping the spatial variation of soil moisture content is a vital parameter for precision agriculture techniques. The aim of this study was to examine the correlation of soil moisture and conductivity (EC) data obtained through scanning techniques with field telemetry data and to spatially separate the field into discrete irrigation management zones. Using the Veris MSP3 model, geo-referenced data for electrical conductivity and organic matter preliminary maps were produced in a pilot kiwifruit field in Chrysoupoli, Kavala. Data from 15 stratified sampling points was used in order to produce the corresponding soil maps. Fusion of the Veris produced maps