Permeability of soils in Mississippi

USGS Publications Warehouse

O'Hara, Charles G.

1994-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

NASA Astrophysics Data System (ADS)

Baumgarten, Andreas

2014-05-01

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

Recent development in preparation of European soil hydraulic maps

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

One perspective on spatial variability in geologic mapping

USGS Publications Warehouse

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

1991-01-01

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

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

PubMed

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

2013-01-01

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

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

PubMed Central

Dey, Dipak K.; Willig, Michael R.

2013-01-01

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

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

USGS Publications Warehouse

Norman, Laura

2004-01-01

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

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

NASA Astrophysics Data System (ADS)

Dietrich, Peter; Werban, Ulrike; Sauer, Uta

2010-05-01

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

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

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, Leonardo; Alexandre Dematte, Jose

2010-05-01

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

Application of multispectral remote sensing to soil survey research in Indiana

NASA Technical Reports Server (NTRS)

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

1972-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

Greve, Mogens Humlekrog; Greve, Mette Balslev

2004-07-01

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

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

NASA Astrophysics Data System (ADS)

Montanarella, Luca

2014-05-01

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

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

NASA Technical Reports Server (NTRS)

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

1972-01-01

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

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

NASA Technical Reports Server (NTRS)

Quiroga, S. Q.

1977-01-01

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

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

PubMed

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

2017-10-01

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

Neighborhood size of training data influences soil map disaggregation

USDA-ARS?s Scientific Manuscript database

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

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

PubMed

Poggio, Laura; Gimona, Alessandro

2017-02-01

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

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

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

Soil property maps of Africa at 250 m resolution

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

Calzolari, C.

2012-04-01

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

Soils of Walker Branch Watershed

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

Lietzke, D.A.

1994-03-01

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

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

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Takács, Katalin; Pásztor, László

2015-04-01

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

Digital soils survey map of the Patagonia Mountains, Arizona

USGS Publications Warehouse

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

2002-01-01

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

Application of remote sensing technology to land evaluation, planning utilization of land resources, and assessment of wildlife areas in eastern South Dakota

NASA Technical Reports Server (NTRS)

1975-01-01

A soils map for land evaluation in Potter County (Eastern South Dakota) was developed to demonstrate the use of remote sensing technology in the area of diverse parent materials and topography. General land use and soils maps have also been developed for land planning LANDSAT, RB-57 imagery, and USGS photographs are being evaluated for making soils and land use maps. LANDSAT fulfilled the requirements for general land use and a general soils map. RB-57 imagery supplemented by large scale black and white stereo coverage was required to provide the detail needed for the final soils map for land evaluation. Color infrared prints excelled black and white coverage for this soil mapping effort. An identification and classification key for wetland types in the Lake Dakota Plain was developed for June 1975 using color infrared imagery. Wetland types in the region are now being mapped via remote sensing techniques to provide a current inventory for development of mitigation measures.

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

NASA Astrophysics Data System (ADS)

Florinsky, I. V.

2012-04-01

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

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

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1974-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-10-01

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

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

NASA Astrophysics Data System (ADS)

Duttmann, Rainer; Kuhwald, Michael; Nolde, Michael

2015-04-01

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

Predicting and mapping soil available water capacity in Korea.

PubMed

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1975-01-01

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

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

NASA Technical Reports Server (NTRS)

Westin, F. C.

1974-01-01

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

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

NASA Astrophysics Data System (ADS)

Lazareva, Margarita; Aparin, Boris; Sukhacheva, Elena

2017-04-01

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

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

USGS Publications Warehouse

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

1987-01-01

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

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

PubMed

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

2009-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Evaluation of automated global mapping of Reference Soil Groups of WRB2015

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

Treesearch

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

2003-01-01

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

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

PubMed Central

Liu, Mingyue; Du, Baojia; Zhang, Bai

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Large-extent digital soil mapping approaches for total soil depth

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

PubMed

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

2013-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

USGS Publications Warehouse

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

1988-01-01

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

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

PubMed

Heijting, S; Kempenaar, C

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

Brown, David J.

2015-04-01

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

Mapping specific soil functions based on digital soil property maps

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Combining land use data acquired from Landsat with soil map data

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

7 CFR 12.31 - On-site wetland identification criteria.

Code of Federal Regulations, 2011 CFR

2011-01-01

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

7 CFR 12.31 - On-site wetland identification criteria.

Code of Federal Regulations, 2014 CFR

2014-01-01

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

7 CFR 12.31 - On-site wetland identification criteria.

Code of Federal Regulations, 2010 CFR

2010-01-01

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

7 CFR 12.31 - On-site wetland identification criteria.

Code of Federal Regulations, 2013 CFR

2013-01-01

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

7 CFR 12.31 - On-site wetland identification criteria.

Code of Federal Regulations, 2012 CFR

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Digital Soil Mapping - A platform for enhancing soil learning

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

PubMed

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

2014-07-01

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

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

NASA Astrophysics Data System (ADS)

Ilieva, Diliana; Malinov, Ilia

2014-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-01-01

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

Evaluating the new soil erosion map of Hungary

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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

PubMed

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

2014-06-01

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

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

PubMed

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

2011-01-01

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

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

PubMed

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

2015-09-01

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

Covariate selection with iterative principal component analysis for predicting physical

USDA-ARS?s Scientific Manuscript database

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

Application of remote sensing technology to land evaluation, planning utilization of land resources, and assessment of westland habitat in eastern South Dakota, parts 1 and 2

NASA Technical Reports Server (NTRS)

Myers, V. I. (Principal Investigator); Cox, T. L.; Best, R. G.

1976-01-01

The author has identified the following significant results. LANDSAT fulfilled the requirements for general soils and land use information. RB-57 imagery was required to provide the information and detail needed for mapping soils for land evaluation. Soils maps for land evaluation were provided on clear mylar at the scale of the county highway map to aid users in locating mapping units. Resulting mapped data were computer processed to provided a series of interpretive maps (land value, limitations to development, etc.) and area summaries for the users.

Preliminary soil-slip susceptibility maps, southwestern California

USGS Publications Warehouse

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

2003-01-01

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

Soils of Walker Branch Watershed

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

Lietzke, D.A.

1994-01-01

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

Creating soil moisture maps based on radar satellite imagery

NASA Astrophysics Data System (ADS)

Hnatushenko, Volodymyr; Garkusha, Igor; Vasyliev, Volodymyr

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

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

NASA Astrophysics Data System (ADS)

Knight, J.; Adam, E.

2015-12-01

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

Mapping soil features from multispectral scanner data

NASA Technical Reports Server (NTRS)

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

1974-01-01

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

Analysis of Ricefield Land Damage in Denpasar City, Bali, Indonesia

NASA Astrophysics Data System (ADS)

Suyarto, R.; Wiyanti; Dibia, I. N.

2018-02-01

Soil as a natural resource, living area, environmental media, and factors of production including biomass production that supports human life and other living beings must be preserved, on the other hand, uncontrolled biomass production activities can cause soil damage, ultimately can threaten the survival of humans and other living things. Therefore, in order to control soil damage, first must inventories the soil condition data and its damage which then visualised in soil damage potential and soil damage status. The activities of the study are the preparation of a map of the initial soil conditions and the delineation of potentially land degradation distribution. Mapping results are used as work maps for verification on the field to take soil samples and create soil damage status. In general, Denpasar City have soil damage potential at very low, low until medium rate. Soil damage status in Denpasar City generally is low damage of bulk volume, total porosity, soil permeability and electrolyte conductivity which beyond limitation thresholds.

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

PubMed

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

2016-12-15

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

PubMed

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

2010-05-01

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

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

NASA Technical Reports Server (NTRS)

Huckle, H. F. (Principal Investigator)

1980-01-01

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

Geostatistics, remote sensing and precision farming.

PubMed

Mulla, D J

1997-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1978-01-01

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

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

PubMed Central

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

2007-01-01

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

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

PubMed

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

2007-08-01

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

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

USDA-ARS?s Scientific Manuscript database

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

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

USDA-ARS?s Scientific Manuscript database

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

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

USDA-ARS?s Scientific Manuscript database

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

Bouma, Johan

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

Debaene, Guillaume; Niedźwiecki, Jacek; Papierowska, Ewa

2016-04-01

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

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

DTIC Science & Technology

2016-08-02

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

Modelling and mapping the topsoil organic carbon content for Tanzania

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

Predictive spatial modelling for mapping soil salinity at continental scale

NASA Astrophysics Data System (ADS)

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 < 2mm fraction at 1315 georeferenced points across the continent at two depth intervals (TOS, 0-10 cm, and BOS, 60-80 cm) (see http://www.ga.gov.au/energy/projects/national-geochemical-survey/atlas.html) were log-transformed and combined with values for climate, elevation and terrain attributes, soil and lithology classes, geophysics, and MODIS vegetation indices extracted at the same locations which were used as predictors in decision tree models. The machine learning software 'Cubist' (www.rulequest.com) was used as the inference engine for the modelling, a 90:10 training:test set data split was used to validate results, and 100 randomly sampled trees were built using the training data. The results were good with an average internal correlation (r) of 0.88 between predicted and measured logEC1:5 (training data), an average external correlation of 0.48 (test subset), and a Lin's concordance correlation coefficient (which evaluates the 1:1 fit) of 0.61. Therefore, the rules derived were mapped and the mean prediction for each 90-m pixel was used for the final logEC1:5 map. This is the most detailed picture of soil salinity over Australia since the 2001 National Land and Water Resources Audit and is generally consistent with it. Our map will be useful as a baseline salinity map circa 2008, when the NGSA samples were collected, for future State of the Environment reports.

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

PubMed

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

2011-05-01

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

Vegetation types on acid soils of Micronesia

Treesearch

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

1987-01-01

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

Mapping of hydropedologic spatial patterns in a steep headwater catchment

Treesearch

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2006-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

Szymon Borkowski, Andrzej; Kwiatkowska-Malina, Jolanta

2016-04-01

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

General soil map Lower Pantano wash area, Pima County, Arizona

NASA Technical Reports Server (NTRS)

Richardson, M. L.

1972-01-01

High altitude color photography was used to determine soil type variation over large areas at a contact print scale of 1:125,000. It was found that color variation and land form could be used as a basis for assigning seven soil mapping units to the area as depicted on stereoscopic pairs of the color photography. A unit is assigned by soil scientists on the basis of similarity of soil features in the area to predetermined physical and chemical characteristics of the same soil type.

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

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

High-resolution soil moisture mapping in Afghanistan

NASA Astrophysics Data System (ADS)

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

2011-06-01

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

Considerations for applying digital soil mapping to ecological sites

USDA-ARS?s Scientific Manuscript database

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

Soil and ecological sites of the Santa Rita Experimental Range

Treesearch

Donald J. Breckenfeld; Daniel Robinett

2003-01-01

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

Mapping Soil pH Buffering Capacity of Selected Fields

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Spectral mapping of soil organic matter

NASA Technical Reports Server (NTRS)

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

1974-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Distribution of soil organic carbon in the conterminous United States

USGS Publications Warehouse

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

2014-01-01

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

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

USGS Publications Warehouse

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

1987-01-01

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

Use of remote sensing technology for inventorying and planning utilization of land resources in South Dakota

NASA Technical Reports Server (NTRS)

1975-01-01

A project was undertaken in Meade County, South Dakota to provide (1) a general county-wide resource survey of land use and soils and (2) a detailed survey of land use for the environmentally sensitive area adjacent to the Black Hills. Imagery from LANDSAT-1 was visually interpreted to provide land use information and a general soils map. A detailed land use map for the Black Hills area was interpreted from RB-57 photographs and interpretations of soil characteristics were input into a computer data base and mapped. The detailed land use data were then used in conjunction with soil maps to provide information for the development of zoning ordinance maps and other land use planning in the Black Hills area. The use of photographs as base maps was also demonstrated. In addition, the use of airborne thermography to locate spoilage areas in sugar beet piles and to determine the apparent temperature of rooftops was evaluated.

Measuring spatial variability in soil characteristics

DOEpatents

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

2002-01-01

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

7 CFR 657.4 - NRCS responsibilities.

Code of Federal Regulations, 2014 CFR

2014-01-01

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

7 CFR 657.4 - NRCS responsibilities.

Code of Federal Regulations, 2011 CFR

2011-01-01

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

7 CFR 657.4 - NRCS responsibilities.

Code of Federal Regulations, 2012 CFR

2012-01-01

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

7 CFR 657.4 - NRCS responsibilities.

Code of Federal Regulations, 2010 CFR

2010-01-01

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

7 CFR 657.4 - NRCS responsibilities.

Code of Federal Regulations, 2013 CFR

2013-01-01

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

Utilizing soil polypedons to improve model performance for digital soil mapping

USDA-ARS?s Scientific Manuscript database

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

Soils [Chapter 5

Treesearch

R. W. E. Hopper; P. M. Walthall

1994-01-01

This report describes the soils of the Lost Lake, West Glacier Lake, and East Glacier Lake watersheds of GLEES and presents the methods used in conducting both the field and laboratory work. In addition, general statements about the nature of the mapping units used in making the soil maps are provided.

Infrared thermal remote sensing for soil salinity assessment on landscape scale

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Landmarks of History of Soil Science in Sri Lanka

NASA Astrophysics Data System (ADS)

Mapa, R.

2012-04-01

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

Spectral signature selection for mapping unvegetated soils

NASA Technical Reports Server (NTRS)

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

1975-01-01

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

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

PubMed

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

2016-09-01

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

Alternate data sources for soil surveys on rangeland

USGS Publications Warehouse

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

1983-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Digital Soil Mapping – A platform for enhancing soil learning.

USDA-ARS?s Scientific Manuscript database

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

Mapping Soil Organic Matter with Hyperspectral Imaging

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Soils and the soil cover of the Valley of Geysers

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

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

NASA Astrophysics Data System (ADS)

Lacoste, Marine; Lemercier, Blandine; Walter, Christian

2011-10-01

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

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

NASA Astrophysics Data System (ADS)

Hendriks, Chantal; Stoorvogel, Jetse; Claessens, Lieven

2017-04-01

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

Mapping of available heavy metals in Catamarca (Argentina)

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

USDA-ARS?s Scientific Manuscript database

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

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

USDA-ARS?s Scientific Manuscript database

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

USGS Publications Warehouse

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

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

NASA Technical Reports Server (NTRS)

Morrison, R. B. (Principal Investigator)

1974-01-01

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

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

PubMed

Lamsal, S; Mishra, U

2010-08-01

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

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

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

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

NASA Technical Reports Server (NTRS)

Davidson, S. E.

1981-01-01

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

A potential global soils data base

NASA Technical Reports Server (NTRS)

Stoner, E. R.; Joyce, A. T.; Hogg, H. C.

1984-01-01

A general procedure is outlined for refining the existing world soil maps from the existing 1:1 million scale to 1:250,000 through the interpretation of Landsat MSS and TM images, and the use of a Geographic Information System to relate the soils maps to available information on climate, topography, geology, and vegetation.

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

USDA-ARS?s Scientific Manuscript database

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

A history of Soil Survey in England and Wales

NASA Astrophysics Data System (ADS)

Hallett, S.; Deeks, L.

2012-04-01

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

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

NASA Astrophysics Data System (ADS)

Siewert, Matthias; Hugelius, Gustaf

2017-04-01

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

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

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1974-01-01

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

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

NASA Astrophysics Data System (ADS)

Kearney, Michael R.; Maino, James L.

2018-06-01

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

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

NASA Technical Reports Server (NTRS)

Samson, S. A.

1985-01-01

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

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

PubMed Central

Welp, Gerhard; Thiel, Michael

2017-01-01

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

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

PubMed

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

2017-01-01

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

The Soil Series in Soil Classifications of the United States

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Comparing physiographic maps with different categorisations

NASA Astrophysics Data System (ADS)

Zawadzka, J.; Mayr, T.; Bellamy, P.; Corstanje, R.

2015-02-01

This paper addresses the need for a robust map comparison method suitable for finding similarities between thematic maps with different forms of categorisations. In our case, the requirement was to establish the information content of newly derived physiographic maps with regards to set of reference maps for a study area in England and Wales. Physiographic maps were derived from the 90 m resolution SRTM DEM, using a suite of existing and new digital landform mapping methods with the overarching purpose of enhancing the physiographic unit component of the Soil and Terrain database (SOTER). Reference maps were seven soil and landscape datasets mapped at scales ranging from 1:200,000 to 1:5,000,000. A review of commonly used statistical methods for categorical comparisons was performed and of these, the Cramer's V statistic was identified as the most appropriate for comparison of maps with different legends. Interpretation of multiple Cramer's V values resulting from one-by-one comparisons of the physiographic and baseline maps was facilitated by multi-dimensional scaling and calculation of average distances between the maps. The method allowed for finding similarities and dissimilarities amongst physiographic maps and baseline maps and informed the recommendation of the most suitable methodology for terrain analysis in the context of soil mapping.

The application of ERTS imagery to the FAO/Unesco soil map of the world

NASA Technical Reports Server (NTRS)

Dudal, R. J.; Pecrot, A. J. (Principal Investigator)

1977-01-01

The author has identified the following significant results. It was concluded that direct identification and mapping of the various soil degradation forms and intensities from the color composite imager was generally difficult, if not impossible. The imagery, however, provided valuable information on some main environmental criteria which can be used in connection other available field data to assess actual soil degradation and estimate soil degradation hazards.

Effective use of ERTS multisensor data in the Great Plains

NASA Technical Reports Server (NTRS)

Myers, V. I. (Principal Investigator)

1972-01-01

The author has identified the following significant results. One unique advantage of ERTS imagery for delineating soil associations is the large area that can be scanned with one photo. Although soil associations usually are published at scales of 1:500,000 or 1:1,000,000, the delineations are drawn on much larger scale maps covering small pieces of the scene and then pieced together. Alluvial areas are usually swollen out of proportion to other soil areas. ERTS imagery puts alluvial areas into their proper size. A second feature of ERTS imagery is that a soil association map constructed with its aid assures that the cartographic level of the associations is more nearly the same. Another advantage of ERTS imagery is that the actual shape and configuration of soil associations are apparent. Also with ERTS imagery significant new delineations may become apparent which were missed when constructing soil association maps from conventional large scale photos.

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

NASA Astrophysics Data System (ADS)

Samuel-Rosa, Alessandro; Anjos, Lúcia; Vasques, Gustavo; Heuvelink, Gerard

2014-05-01

Brazil is one of the world's largest food producers, and is home of both largest rainforest and largest supply of renewable fresh water on Earth. However, it lacks detailed soil information in extensive areas of the country. The best soil map covering the entire country was published at a scale of 1:5,000,000. Termination of governmental support for systematic soil mapping in the 1980's made detailed soil mapping of the whole country a very difficult task to accomplish. Nowadays, due to new user-driven demands (e.g. precision agriculture), most detailed soil maps are produced for small size areas. Many of them rely on as is freely available ancillary data, although their accuracy is usually not reported or unknown. Results from a validation exercise that we performed using ground control points from a small hilly catchment (20 km²) in Southern Brazil (-53.7995ºE, -29.6355ºN) indicate that most freely available ancillary data needs some type of correction before use. Georeferenced and orthorectified RapidEye imagery (recently acquired by the Brazilian government) has a horizontal accuracy (root-mean-square error, RMSE) of 37 m, which is worse than the value published in the metadata (32 m). Like any remote sensing imagery, RapidEye imagery needs to be correctly registered before its use for soil mapping. Topographic maps produced by the Brazilian Army and derived geological maps (scale of 1:25,000) have a horizontal accuracy of 65 m, which is more than four times the maximum value allowed by Brazilian legislation (15 m). Worse results were found for geological maps derived from 1:50,000 topographic maps (RMSE = 147 m), for which the maximum allowed value is 30 m. In most cases positional errors are of systematic origin and can be easily corrected (e.g., affine transformation). ASTER GDEM has many holes and is very noisy, making it of little use in the studied area. TOPODATA, which is SRTM kriged from originally 3 to 1 arc-second by the Brazilian National Institute for Space Research, has a vertical accuracy of 19 m and is strongly affected by double-oblique stripes which were intensified by kriging. Many spurious sinks were created which are not easily corrected using either frequency filters or sink-filling algorithms. The exceptions are SRTM v4.1, which is the most vertically accurate DEM available (RMSE = 18.7 m), and Google Earth imagery compiled from various sources (positional accuracy of RMSE = 8 m). It is likely that most mapping efforts will continue to be employed in small size areas to fulfill local user-driven demands in the forthcoming years. Also, many new techniques and technologies will possibly be developed and employed for soil mapping. However, employing better quality ancillary data still is a challenge to be overcome to produce high-quality soil information to allow better decision making and land use policy in Brazil.

Predictable bacterial composition and hydrocarbon degradation in Arctic soils following diesel and nutrient disturbance.

PubMed

Bell, Terrence H; Yergeau, Etienne; Maynard, Christine; Juck, David; Whyte, Lyle G; Greer, Charles W

2013-06-01

Increased exploration and exploitation of resources in the Arctic is leading to a higher risk of petroleum contamination. A number of Arctic microorganisms can use petroleum for growth-supporting carbon and energy, but traditional approaches for stimulating these microorganisms (for example, nutrient addition) have varied in effectiveness between sites. Consistent environmental controls on microbial community response to disturbance from petroleum contaminants and nutrient amendments across Arctic soils have not been identified, nor is it known whether specific taxa are universally associated with efficient bioremediation. In this study, we contaminated 18 Arctic soils with diesel and treated subsamples of each with monoammonium phosphate (MAP), which has successfully stimulated degradation in some contaminated Arctic soils. Bacterial community composition of uncontaminated, diesel-contaminated and diesel+MAP soils was assessed through multiplexed 16S (ribosomal RNA) rRNA gene sequencing on an Ion Torrent Personal Genome Machine, while hydrocarbon degradation was measured by gas chromatography analysis. Diversity of 16S rRNA gene sequences was reduced by diesel, and more so by the combination of diesel and MAP. Actinobacteria dominated uncontaminated soils with <10% organic matter, while Proteobacteria dominated higher-organic matter soils, and this pattern was exaggerated following disturbance. Degradation with and without MAP was predictable by initial bacterial diversity and the abundance of specific assemblages of Betaproteobacteria, respectively. High Betaproteobacteria abundance was positively correlated with high diesel degradation in MAP-treated soils, suggesting this may be an important group to stimulate. The predictability with which bacterial communities respond to these disturbances suggests that costly and time-consuming contaminated site assessments may not be necessary in the future.

Prediction of iron oxide contents using diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Marques, José, Jr.; Arantes Camargo, Livia

2015-04-01

Determining soil iron oxides using conventional analysis is relatively unfeasible when large areas are mapped, with the aim of characterizing spatial variability. Diffuse reflectance spectroscopy (DRS) is rapid, less expensive, non-destructive and sometimes more accurate than conventional analysis. Furthermore, this technique allows the simultaneous characterization of many soil attributes with agronomic and environmental relevance. This study aims to assess the DRS capability to predict iron oxides content -hematite and goethite - , characterizing their spatial variability in soils of Brazil. Soil samples collected from an 800-hectare area were scanned in the visible and near-infrared spectral range. Moreover, chemometric calibration was obtained through partial least-squares regression (PLSR). Then, spatial distribution maps of the attributes were constructed using predicted values from calibrated models through geostatistical methods. The studied area presented soils with varied contents of iron oxides as examples for the Oxisols and Entisols. In the spectra of each soil is observed that the reflectance decreases with the content of iron oxides present in the soil. In soils with a high content of iron oxides can be observed more pronounced concavities between 380 and 1100 nm which are characteristic of the presence of these oxides. In soils with higher reflectance it were observed concavity characteristics due to the presence of kaolinite, in agreement with the low iron contents of those soils. The best accuracy of prediction models [residual prediction deviation (RPD) = 1.7] was obtained for goethite within the visible region (380-800 nm), and for hematite (RPD = 2.0) within the visible near infrared (380-2300 nm). The maps of goethite and hematite predicted showed the spatial distribution pattern similar to the maps of clay and iron extracted by dithionite-citrate-bicarbonate, being consistent with the iron oxide contents of soils present in the study area. These results confirm the value of DRS in the mapping of iron oxides in large areas at detailed scale.

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

Treesearch

Brian J. Clough; Edwin J. Green; Richard B. Lathrop

2012-01-01

Managing forest soil organic matter (SOM) stocks is a vital strategy for reducing the impact of anthropogenic carbon dioxide emissions. However, the SOM pool is highly variable, and developing accurate estimates to guide management decisions has remained a difficult task. We present the results of a spatial model designed to map soil organic matter for all forested...

Field guide for mapping post-fire soil burn severity

Treesearch

Annette Parson; Peter R. Robichaud; Sarah A. Lewis; Carolyn Napper; Jess T. Clark

2010-01-01

Following wildfires in the United States, the U.S. Department of Agriculture and U.S. Department of the Interior mobilize Burned Area Emergency Response (BAER) teams to assess immediate post-fire watershed conditions. BAER teams must determine threats from flooding, soil erosion, and instability. Developing a postfire soil burn severity map is an important first step...

The Use of Electromagnetic Induction Techniques for Soil Mapping

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Doolittle, Jim

2015-04-01

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

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

PubMed

Triki Fourati, Hela; Bouaziz, Moncef; Benzina, Mourad; Bouaziz, Samir

2017-04-01

Traditional surveying methods of soil properties over landscapes are dramatically cost and time-consuming. Thus, remote sensing is a proper choice for monitoring environmental problem. This research aims to study the effect of environmental factors on soil salinity and to map the spatial distribution of this salinity over the southern east part of Tunisia by means of remote sensing and geostatistical techniques. For this purpose, we used Advanced Spaceborne Thermal Emission and Reflection Radiometer data to depict geomorphological parameters: elevation, slope, plan curvature (PLC), profile curvature (PRC), and aspect. Pearson correlation between these parameters and soil electrical conductivity (EC soil ) showed that mainly slope and elevation affect the concentration of salt in soil. Moreover, spectral analysis illustrated the high potential of short-wave infrared (SWIR) bands to identify saline soils. To map soil salinity in southern Tunisia, ordinary kriging (OK), minimum distance (MD) classification, and simple regression (SR) were used. The findings showed that ordinary kriging technique provides the most reliable performances to identify and classify saline soils over the study area with a root mean square error of 1.83 and mean error of 0.018.

Mapping Surface Soil Organic Carbon for Crop Fields with Remote Sensing

NASA Technical Reports Server (NTRS)

Chen, Feng; Kissel, David E.; West, Larry T.; Rickman, Doug; Luvall, J. C.; Adkins, Wayne

2004-01-01

The organic C concentration of surface soil can be used in agricultural fields to vary crop production inputs. Organic C is often highly spatially variable, so that maps of soil organic C can be used to vary crop production inputs using precision farming technology. The objective of this research was to demonstrate the feasibility of mapping soil organic C on three fields, using remotely sensed images of the fields with a bare surface. Enough soil samples covering the range in soil organic C must be taken from each field to develop a satisfactory relationship between soil organic C content and image reflectance values. The number of soil samples analyzed in the three fields varied from 22 to 26. The regression equations differed between fields, but gave highly significant relationships with R2 values of 0.93, 0.95, and 0.89 for the three fields. A comparison of predicted and measured values of soil organic C for an independent set of 2 soil samples taken on one of the fields gave highly satisfactory results, with a comparison equation of % organic C measured + 1.02% organic C predicted, with r2 = 0.87.

Cartographic modeling of heterogeneous landscape for footprint analysis of Eddy Covariance Measurements (Central Forest and Central Chernozem reserves, Russia)

NASA Astrophysics Data System (ADS)

Kozlov, Daniil

2014-05-01

The topographical, soil and vegetation maps of FLUXNET study areas are widely used for interpretation of eddy covariance measurements, for calibration of biogeochemical models and for making regional assessments of carbon balance. The poster presents methodological problems and results of ecosystem mapping using GIS, remote sensing, statistical and field methods on the example of two RusFluxNet sites in the Central Forest (33° E, 56°30'N) and Central Chernozem (36°10' E, 51°36'N) reserves. In the Central Forest reserve tacheometric measurements were used for topographical and peat surveys of bogged sphagnum spruce forest of 20-hectare area. Its common borders and its areas affected by windfall were determined. The supplies and spatial distribution of organic matter were obtained. The datasets of groundwater monitoring measurements on ten wells were compared with each other and the analysis of spatial and temporal groundwater variability was performed. The map of typical ecosystems of the reserve and its surroundings was created on the basis of analysis of multi-temporal Landsat images. In the Central Chernozem reserve the GNSS topographical survey was used for flux tower footprint mapping (22 ha). The features of microrelief predetermine development of different soils within the footprint. Close relationship between soil (73 drilling site) and terrain attributes (DEM with 2.5 m) allowed to build maps of soils and soil properties: carbon content, bulk density, upper boundary of secondary carbonates. Position for chamber-based soil respiration measurements was defined on the basis of these maps. The detailed geodetic and soil surveys of virgin lands and plowland were performed in order to estimate the effect of agrogenic processes such as dehumification, compaction and erosion on soils during the whole period of agricultural use of Central Chernozem reserve area and around. The choice of analogous soils was based on the similarity of their position within the landscape as judged from the terrain attributes of the DEM. The dynamics of soil cover during the last 50 years was estimated on the basis of repetitive detailed surveys of the five key plots conducted in 1963, 1984 and 2013. All results of this study and map analysis conclusions are presented in the poster.

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function

PubMed Central

Groenendyk, Derek G.; Ferré, Ty P.A.; Thorp, Kelly R.; Rice, Amy K.

2015-01-01

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth’s surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function. PMID:26121466

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed

Veronesi, F; Corstanje, R; Mayr, T

2014-07-15

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

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function.

PubMed

Groenendyk, Derek G; Ferré, Ty P A; Thorp, Kelly R; Rice, Amy K

2015-01-01

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth's surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function.

High-Resolution Global Soil Moisture Map

NASA Image and Video Library

2015-05-19

High-resolution global soil moisture map from NASA SMAP combined radar and radiometer instruments, acquired between May 4 and May 11, 2015 during SMAP commissioning phase. The map has a resolution of 5.6 miles (9 kilometers). The data gap is due to turning the instruments on and off during testing. http://photojournal.jpl.nasa.gov/catalog/PIA19337

Topsoil moisture mapping using geostatistical techniques under different Mediterranean climatic conditions.

PubMed

Martínez-Murillo, J F; Hueso-González, P; Ruiz-Sinoga, J D

2017-10-01

Soil mapping has been considered as an important factor in the widening of Soil Science and giving response to many different environmental questions. Geostatistical techniques, through kriging and co-kriging techniques, have made possible to improve the understanding of eco-geomorphologic variables, e.g., soil moisture. This study is focused on mapping of topsoil moisture using geostatistical techniques under different Mediterranean climatic conditions (humid, dry and semiarid) in three small watersheds and considering topography and soil properties as key factors. A Digital Elevation Model (DEM) with a resolution of 1×1m was derived from a topographical survey as well as soils were sampled to analyzed soil properties controlling topsoil moisture, which was measured during 4-years. Afterwards, some topography attributes were derived from the DEM, the soil properties analyzed in laboratory, and the topsoil moisture was modeled for the entire watersheds applying three geostatistical techniques: i) ordinary kriging; ii) co-kriging considering as co-variate topography attributes; and iii) co-kriging ta considering as co-variates topography attributes and gravel content. The results indicated topsoil moisture was more accurately mapped in the dry and semiarid watersheds when co-kriging procedure was performed. The study is a contribution to improve the efficiency and accuracy of studies about the Mediterranean eco-geomorphologic system and soil hydrology in field conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

A study of the utilization of ERTS-1 data from the Wabash River Basin. [soil mapping, crop identification, water resources

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1973-01-01

The author has identified the following significant results. In soil association mapping, computerized analysis of ERTS-1 MSS data has yielded images which will prove useful in the ongoing Cooperative Soil Survey program, involving the Soil Conservation Service of USDA and other state and local agencies. In the present mode of operation, a soil survey for a county may take up to 5 years to be completed. Results indicate that a great deal of soils information can be extracted from ERTS-1 data by computer analysis. This information is expected to be very valuable in the premapping conference phase of a soil survey, resulting in more efficient field operations during the actual mapping. In the earth surface features mapping effort it was found that temporal data improved the classification accuracy of forest classification in Tippecanoe County, Indiana. In water resources study a severe scanner look angle effect was observed in the aircraft scanner data of a test lake which was not present in ERTS-1 data of the same site. This effect was greatly accentuated by surface roughness caused by strong winds. Quantitative evaluation of urban features classification in ERTS-1 data was obtained. An 87.1% test accuracy was obtained for eight categories in Marion County, Indiana.

Evaluation of the spatial variability of soil water content at the spatial resolution of SMAP data products : case studies in Italy and Morocco

NASA Astrophysics Data System (ADS)

Menenti, Massimo; Akdim, Nadia; Alfieri, Silvia Maria; Labbassi, Kamal; De Lorenzi, Francesca; Bonfante, Antonello; Basile, Angelo

2014-05-01

Frequent and contiguous observations of soil water content such as the ones to be provided by SMAP are potentially useful to improve distributed models of soil water balance. This requires matching of observations and model estimates provided both sample spatial patterns consistently. The spatial resolution of SMAP soil water content data products ranges from 3 km X 3 km to 40 km X 40 km. Even the highest spatial resolution may not be sufficient to capture the spatial variability due to terrain, soil properties and precipitation. We have evaluated the SMAP spatial resolution against spatial variability of soil water content in two Mediterranean landscapes: a hilly area dominated by vineyards and olive orchards in Central Italy and a large irrigation schemes (Doukkala) in Morocco. The "Valle Telesina" is a 20,000 ha complex landscape located in South Italy in the Campania region, which has a complex geology and geomorphology and it is characterised by an E-W elongated graben where the Calore river flows. The main crops are grapevine (6,448 ha) and olive (3,390 ha). Soil information was mainly derived from an existing soil map at 1:50 000 scale (Terribile et al., 1996). The area includes 47 SMUs (Soil Mapping Units) and about 60 soil typological units (STUs). (Bonfante et al., 2011). In Doukkala, the soil water retention and unsaturated capillary conductivity were estimated from grain size distribution of a number of samples (22 pilot points, each one sampled in 3 horizons of 20cm), and combined with a soil map. The land use classification was carried out using a NDVI time series at high spatial resolution (Landsat TM and SPOT HRV). We have calculated soil water content for each soil unit in each area in response to several climate cases generating daily maps of soil water content at different depths. To reproduce spatial sampling by SMAP we have filtered these spatial patterns by calculating box averages with grid sizes of 1 km X 1 km and 5 km X 5 km. We have repeated this procedure for soil water content in the 0 to 5 cm and 0 to 10 cm depths. For each case we have compared the variance of filtered soil water content with the expected accuracy of SMAP soil water content. The two areas are very different as regards morphology and soil formation. The Valle Telesina is characterized by a very significant variability of soil hydrological properties leading to complex patterns in soil water content. Contrariwise, the soil properties estimated for all soil mapping units in the Dhoukkala collapse into just two pairs of water retention and hydraulic conductivity characteristics, leading to smoother patterns of soil water content.

[Effects of soil data and map scale on assessment of total phosphorus storage in upland soils.

PubMed

Li, Heng Rong; Zhang, Li Ming; Li, Xiao di; Yu, Dong Sheng; Shi, Xue Zheng; Xing, Shi He; Chen, Han Yue

2016-06-01

Accurate assessment of total phosphorus storage in farmland soils is of great significance to sustainable agricultural and non-point source pollution control. However, previous studies haven't considered the estimation errors from mapping scales and various databases with different sources of soil profile data. In this study, a total of 393×10 4 hm 2 of upland in the 29 counties (or cities) of North Jiangsu was cited as a case for study. Analysis was performed of how the four sources of soil profile data, namely, "Soils of County", "Soils of Prefecture", "Soils of Province" and "Soils of China", and the six scales, i.e. 1:50000, 1:250000, 1:500000, 1:1000000, 1:4000000 and1:10000000, used in the 24 soil databases established for the four soil journals, affected assessment of soil total phosphorus. Compared with the most detailed 1:50000 soil database established with 983 upland soil profiles, relative deviation of the estimates of soil total phosphorus density (STPD) and soil total phosphorus storage (STPS) from the other soil databases varied from 4.8% to 48.9% and from 1.6% to 48.4%, respectively. The estimated STPD and STPS based on the 1:50000 database of "Soils of County" and most of the estimates based on the databases of each scale in "Soils of County" and "Soils of Prefecture" were different, with the significance levels of P＜0.001 or P＜0.05. Extremely significant differences (P＜0.001) existed between the estimates based on the 1:50000 database of "Soils of County" and the estimates based on the databases of each scale in "Soils of Province" and "Soils of China". This study demonstrated the significance of appropriate soil data sources and appropriate mapping scales in estimating STPS.

Geochemical baseline studies of soil in Finland

NASA Astrophysics Data System (ADS)

Pihlaja, Jouni

2017-04-01

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

Agricultural land cover mapping in the context of a geographically referenced digital information system. [Carroll, Macon, and Gentry Counties, Missouri

NASA Technical Reports Server (NTRS)

Stoner, E. R.

1982-01-01

The introduction of soil map information to the land cover mapping process can improve discrimination of land cover types and reduce confusion among crop types that may be caused by soil-specific management practices and background reflectance characteristics. Multiple dates of LANDSAT MSS digital were analyzed for three study areas in northern Missouri to produce cover types for major agricultural land cover classes. Digital data bases were then developed by adding ancillary data such as digitized soil and transportation network information to the LANDSAT-derived cover type map. Procedures were developed to manipulate the data base parameters to extract information applicable to user requirements. An agricultural information system combining such data can be used to determine the productive capacity of land to grow crops, fertilizer needs, chemical weed control rates, irrigation suitability, and trafficability of soil for planting.

Ecosystem Services in Agricultural Landscapes: A Spatially Explicit Approach to Support Sustainable Soil Management

PubMed Central

Crossman, Neville D.; MacEwan, Richard J.; Wallace, D. Dugal; Bennett, Lauren T.

2014-01-01

Soil degradation has been associated with a lack of adequate consideration of soil ecosystem services. We demonstrate a broadly applicable method for mapping changes in the supply of two priority soil ecosystem services to support decisions about sustainable land-use configurations. We used a landscape-scale study area of 302 km2 in northern Victoria, south-eastern Australia, which has been cleared for intensive agriculture. Indicators representing priority soil services (soil carbon sequestration and soil water storage) were quantified and mapped under both a current and a future 25-year land-use scenario (the latter including a greater diversity of land uses and increased perennial crops and irrigation). We combined diverse methods, including soil analysis using mid-infrared spectroscopy, soil biophysical modelling, and geostatistical interpolation. Our analysis suggests that the future land-use scenario would increase the landscape-level supply of both services over 25 years. Soil organic carbon content and water storage to 30 cm depth were predicted to increase by about 11% and 22%, respectively. Our service maps revealed the locations of hotspots, as well as potential trade-offs in service supply under new land-use configurations. The study highlights the need to consider diverse land uses in sustainable management of soil services in changing agricultural landscapes. PMID:24616632

Ecosystem services in agricultural landscapes: a spatially explicit approach to support sustainable soil management.

PubMed

Forouzangohar, Mohsen; Crossman, Neville D; MacEwan, Richard J; Wallace, D Dugal; Bennett, Lauren T

2014-01-01

Soil degradation has been associated with a lack of adequate consideration of soil ecosystem services. We demonstrate a broadly applicable method for mapping changes in the supply of two priority soil ecosystem services to support decisions about sustainable land-use configurations. We used a landscape-scale study area of 302 km(2) in northern Victoria, south-eastern Australia, which has been cleared for intensive agriculture. Indicators representing priority soil services (soil carbon sequestration and soil water storage) were quantified and mapped under both a current and a future 25-year land-use scenario (the latter including a greater diversity of land uses and increased perennial crops and irrigation). We combined diverse methods, including soil analysis using mid-infrared spectroscopy, soil biophysical modelling, and geostatistical interpolation. Our analysis suggests that the future land-use scenario would increase the landscape-level supply of both services over 25 years. Soil organic carbon content and water storage to 30 cm depth were predicted to increase by about 11% and 22%, respectively. Our service maps revealed the locations of hotspots, as well as potential trade-offs in service supply under new land-use configurations. The study highlights the need to consider diverse land uses in sustainable management of soil services in changing agricultural landscapes.

Mapping soil landscape as spatial continua: The Neural Network Approach

NASA Astrophysics Data System (ADS)

Zhu, A.-Xing

2000-03-01

A neural network approach was developed to populate a soil similarity model that was designed to represent soil landscape as spatial continua for hydroecological modeling at watersheds of mesoscale size. The approach employs multilayer feed forward neural networks. The input to the network was data on a set of soil formative environmental factors; the output from the network was a set of similarity values to a set of prescribed soil classes. The network was trained using a conjugate gradient algorithm in combination with a simulated annealing technique to learn the relationships between a set of prescribed soils and their environmental factors. Once trained, the network was used to compute for every location in an area the similarity values of the soil to the set of prescribed soil classes. The similarity values were then used to produce detailed soil spatial information. The approach also included a Geographic Information System procedure for selecting representative training and testing samples and a process of determining the network internal structure. The approach was applied to soil mapping in a watershed, the Lubrecht Experimental Forest, in western Montana. The case study showed that the soil spatial information derived using the neural network approach reveals much greater spatial detail and has a higher quality than that derived from the conventional soil map. Implications of this detailed soil spatial information for hydroecological modeling at the watershed scale are also discussed.

Regional modeling of wind erosion in the North West and South West of Iran

NASA Astrophysics Data System (ADS)

Mirmousavi, S. H.

2016-08-01

About two-thirds of the Iran's area is located in the arid and semiarid region. Lack of soil moisture and vegetation is poor in most areas can lead to soil erosion caused by wind. So that the annual suffered severe damage to large areas of rich soils. Modeling studies of wind erosion in Iran is very low and incomplete. Therefore, this study aimed to wind erosion modeling, taking into three factors: wind speed, vegetation and soil types have been done. Wind erosion sensitivity was modeled using the key factors of soil sensitivity, vegetation cover and wind erodibility as proxies. These factors were first estimated separately by factor sensitivity maps and later combined by fuzzy logic into a regional-scale wind erosion sensitivity map. Large areas were evaluated by using publicly available datasets of remotely sensed vegetation information, soil maps and meteorological data on wind speed. The resulting estimates were verified by field studies and examining the economic losses from wind erosion as compensated by the state insurance company. The spatial resolution of the resulting sensitivity map is suitable for regional applications, as identifying sensitive areas is the foundation for diverse land development control measures and implementing management activities.

Geomorphically based predictive mapping of soil thickness in upland watersheds

NASA Astrophysics Data System (ADS)

Pelletier, Jon D.; Rasmussen, Craig

2009-09-01

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

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

NASA Astrophysics Data System (ADS)

Tilch, Nils; Römer, Alexander; Jochum, Birgit; Schattauer, Ingrid

2014-05-01

In the past years, several times large-scale disasters occurred in Austria, which were characterized not only by flooding, but also by numerous shallow landslides and debris flows. Therefore, for the purpose of risk prevention, national and regional authorities also require more objective and realistic maps with information about spatially variable susceptibility of the geosphere for hazard-relevant gravitational mass movements. There are many and various proven methods and models (e.g. neural networks, logistic regression, heuristic methods) available to create such process-related (e.g. flat gravitational mass movements in soil) suszeptibility maps. But numerous national and international studies show a dependence of the suitability of a method on the quality of process data and parameter maps (f.e. Tilch & Schwarz 2011, Schwarz & Tilch 2011). In this case, it is important that also maps with detailed and process-oriented information on the process-relevant geosphere will be considered. One major disadvantage is that only occasionally area-wide process-relevant information exists. Similarly, in Austria often only soil maps for treeless areas are available. However, in almost all previous studies, randomly existing geological and geotechnical maps were used, which often have been specially adapted to the issues and objectives. This is one reason why very often conceptual soil maps must be derived from geological maps with only hard rock information, which often have a rather low quality. Based on these maps, for example, adjacent areas of different geological composition and process-relevant physical properties are razor sharp delineated, which in nature appears quite rarly. In order to obtain more realistic information about the spatial variability of the process-relevant geosphere (soil cover) and its physical properties, aerogeophysical measurements (electromagnetic, radiometric), carried out by helicopter, from different regions of Austria were interpreted. Previous studies show that, especially with radiometric measurements, the two-dimensional spatial variability of the nature of the process-relevant soil, close to the surface can be determined. In addition, the electromagnetic measurements are more important to obtain three-dimensional information of the deeper geological conditions and to improve the area-specific geological knowledge and understanding. The validation of these measurements is done with terrestrial geoelectrical measurements. So both aspects, radiometric and electromagnetic measurements, are important and subsequently, interpretation of the geophysical results can be used as the parameter maps in the modeling of more realistic susceptibility maps with respect to various processes. Within this presentation, results of geophysical measurements, the outcome and the derived parameter maps, as well as first process-oriented susceptibility maps in terms of gravitational soil mass movements will be presented. As an example results which were obtained with a heuristic method in an area in Vorarlberg (Western Austria) will be shown. References: Schwarz, L. & Tilch, N. (2011): Why are good process data so important for the modelling of landslide susceptibility maps?- EGU-Postersession "Landslide hazard and risk assessment, and landslide management" (NH 3.6), Vienna. [http://www.geologie.ac.at/fileadmin/user_upload/dokumente/pdf/poster/poster_2011_egu_schwarz_tilch_1.pdf] Tilch, N. & Schwarz, L. (2011): Spatial and scale-dependent variability in data quality and their influence on susceptibility maps for gravitational mass movements in soil, modelled by heuristic method.- EGU-Postersession "Landslide hazard and risk assessment, and landslide management" (NH 3.6); Vienna. [http://www.geologie.ac.at/fileadmin/user_upload/dokumente/pdf/poster/poster_2011_egu_tilch_schwarz.pdf

Soil functional types: surveying the biophysical dimensions of soil security

NASA Astrophysics Data System (ADS)

Cécillon, Lauric; Barré, Pierre

2015-04-01

Soil is a natural capital that can deliver key ecosystem services (ES) to humans through the realization of a series of soil processes controlling ecosystem functioning. Soil is also a diverse and endangered natural resource. A huge pedodiversity has been described at all scales, which is strongly altered by global change. The multidimensional concept soil security, encompassing biophysical, economic, social, policy and legal frameworks of soils has recently been proposed, recognizing the role of soils in global environmental sustainability challenges. The biophysical dimensions of soil security focus on the functionality of a given soil that can be viewed as the combination of its capability and its condition [1]. Indeed, all soils are not equal in term of functionality. They show different processes, provide different ES to humans and respond specifically to global change. Knowledge of soil functionality in space and time is thus a crucial step towards the achievement soil security. All soil classification systems incorporate some functional information, but soil taxonomy alone cannot fully describe the functioning, limitations, resistance and resilience of soils. Droogers and Bouma [2] introduced functional variants (phenoforms) for each soil type (genoform) so as to fit more closely to soil functionality. However, different genoforms can have the same functionality. As stated by McBratney and colleagues [1], there is a great need of an agreed methodology for defining the reference state of soil functionality. Here, we propose soil functional types (SFT) as a relevant classification system for the biophysical dimensions of soil security. Following the definition of plant functional types widely used in ecology, we define a soil functional type as "a set of soil taxons or phenoforms sharing similar processes (e.g. soil respiration), similar effects on ecosystem functioning (e.g. primary productivity) and similar responses to global change (land-use, management or climate) for a particular soil-provided ecosystem service (e.g. climate regulation)". One SFT can thus include several soil types having the same functionality for a particular soil-provided ES. Another consequence is that SFT maps for two different ES may not superimpose over the same area, since some soils may fall in the same SFT for a service and in different SFT for another one. Soil functional types could be assessed and monitored in space and time by a combination of soil functional traits that correspond to inherent and manageable properties of soils. Their metrology would involve either classic (pedological observations) or advanced (molecular ecology, spectrometry, geophysics) tools. SFT could be studied and mapped at all scales, depending on the purpose of the soil security assessment (e.g. global climate modeling, land planning and management, biodiversity conservation). Overall, research is needed to find a pathway from soil pedological maps to SFT maps which would yield important benefits towards the assessment and monitoring of soil security. Indeed, this methodology would allow (i) reducing the spatial uncertainty on the assessment of ES; (ii) identifying and mapping multifunctional soils, which may be the most important soil resource to preserve. References [1] McBratney et al., 2014. Geoderma 213:203-213. [2] Droogers P, Bouma J, 1997. SSSAJ 61:1704-1710.

Soil classification based on cone penetration test (CPT) data in Western Central Java

NASA Astrophysics Data System (ADS)

Apriyono, Arwan; Yanto, Santoso, Purwanto Bekti; Sumiyanto

2018-03-01

This study presents a modified friction ratio range for soil classification i.e. gravel, sand, silt & clay and peat, using CPT data in Western Central Java. The CPT data was obtained solely from Soil Mechanic Laboratory of Jenderal Soedirman University that covers more than 300 sites within the study area. About 197 data were produced from data filtering process. IDW method was employed to interpolated friction ratio values in a regular grid point for soil classification map generation. Soil classification map was generated and presented using QGIS software. In addition, soil classification map with respect to modified friction ratio range was validated using 10% of total measurements. The result shows that silt and clay dominate soil type in the study area, which is in agreement with two popular methods namely Begemann and Vos. However, the modified friction ratio range produces 85% similarity with laboratory measurements whereby Begemann and Vos method yields 70% similarity. In addition, modified friction ratio range can effectively distinguish fine and coarse grains, thus useful for soil classification and subsequently for landslide analysis. Therefore, modified friction ratio range proposed in this study can be used to identify soil type for mountainous tropical region.

Effects of long-term soil and crop management on soil hydraulic properties for claypan soils

USDA-ARS?s Scientific Manuscript database

Regional and national soil maps have been developed along with associated soil property databases to assist users in making land management decisions based on soil characteristics. These soil properties include average values from soil characterization for each soil series. In reality, these propert...

Predictable bacterial composition and hydrocarbon degradation in Arctic soils following diesel and nutrient disturbance

PubMed Central

Bell, Terrence H; Yergeau, Etienne; Maynard, Christine; Juck, David; Whyte, Lyle G; Greer, Charles W

2013-01-01

Increased exploration and exploitation of resources in the Arctic is leading to a higher risk of petroleum contamination. A number of Arctic microorganisms can use petroleum for growth-supporting carbon and energy, but traditional approaches for stimulating these microorganisms (for example, nutrient addition) have varied in effectiveness between sites. Consistent environmental controls on microbial community response to disturbance from petroleum contaminants and nutrient amendments across Arctic soils have not been identified, nor is it known whether specific taxa are universally associated with efficient bioremediation. In this study, we contaminated 18 Arctic soils with diesel and treated subsamples of each with monoammonium phosphate (MAP), which has successfully stimulated degradation in some contaminated Arctic soils. Bacterial community composition of uncontaminated, diesel-contaminated and diesel+MAP soils was assessed through multiplexed 16S (ribosomal RNA) rRNA gene sequencing on an Ion Torrent Personal Genome Machine, while hydrocarbon degradation was measured by gas chromatography analysis. Diversity of 16S rRNA gene sequences was reduced by diesel, and more so by the combination of diesel and MAP. Actinobacteria dominated uncontaminated soils with <10% organic matter, while Proteobacteria dominated higher-organic matter soils, and this pattern was exaggerated following disturbance. Degradation with and without MAP was predictable by initial bacterial diversity and the abundance of specific assemblages of Betaproteobacteria, respectively. High Betaproteobacteria abundance was positively correlated with high diesel degradation in MAP-treated soils, suggesting this may be an important group to stimulate. The predictability with which bacterial communities respond to these disturbances suggests that costly and time-consuming contaminated site assessments may not be necessary in the future. PMID:23389106

Participatory GIS for Soil Conservation in Phewa Watershed of Nepal

NASA Astrophysics Data System (ADS)

Bhandari, K. P.

2012-07-01

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

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

PubMed

Mahmoudabadi, Ebrahim; Karimi, Alireza; Haghnia, Gholam Hosain; Sepehr, Adel

2017-09-11

Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R 2 RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

7 CFR 12.22 - Highly erodible field determination criteria.

Code of Federal Regulations, 2014 CFR

2014-01-01

... percent or more of the total field acreage is identified as soil map units which are highly erodible; or (2) 50 or more acres in such field are identified as soil map units which are highly erodible. (b...

7 CFR 12.22 - Highly erodible field determination criteria.

Code of Federal Regulations, 2013 CFR

2013-01-01

... percent or more of the total field acreage is identified as soil map units which are highly erodible; or (2) 50 or more acres in such field are identified as soil map units which are highly erodible. (b...

7 CFR 12.22 - Highly erodible field determination criteria.

Code of Federal Regulations, 2011 CFR

2011-01-01

... percent or more of the total field acreage is identified as soil map units which are highly erodible; or (2) 50 or more acres in such field are identified as soil map units which are highly erodible. (b...

7 CFR 12.22 - Highly erodible field determination criteria.

Code of Federal Regulations, 2012 CFR

2012-01-01

... percent or more of the total field acreage is identified as soil map units which are highly erodible; or (2) 50 or more acres in such field are identified as soil map units which are highly erodible. (b...

Do We Need a New Definition of Soil?

NASA Astrophysics Data System (ADS)

Arnold, Richard W.; Brevik, Eric C.

2014-05-01

Effective communication is really desirable to better relate with politicians, an interested lay public, and others not involved in soil science. Soil survey programs are intended to help people understand how soils function in their landscapes to make ecosystems operate better without damaging the environment and to indicate different kinds of suitability for various purposes. The properties of soils as recognized, described, and mapped at detailed scales form the basis for developing diagnostics for a systematic taxonomy that enables scientists to interact with other. In the USA mapping done at scales of 1:15,840± made it possible to define and use so-called "soil series", initially as soil map units, but later as central concepts of a set of soils which could be segregated using phases to indicate important features, primarily for farming. Detailed soil surveys published using a standard format helps maintain uniformity across the country. Soil series are recognized as the basic units of soils within the evolving hierarchical soil taxonomy and diagnostic properties are defined, measured and used to update and modify the scientific classification. Concepts like soil quality and soil function are considered to be "attributes" and not basic properties of soils. They are the collective interpretation of the combination of properties thought to be relevant for communicating important aspects of using, managing, restoring, and protecting the lands of any locality, region, or country. A famous example in the US was the land capability system with classes and subclasses of suitability for agricultural land uses. An updated soil survey in California contains over 500 pages providing details about classes of 30 different functional soil classifications for 155 map units. Over the years soil extension agents were the interpreters of the science to the lay folks and could help them form mental pictures of soils and soil landscapes locally They were the early leaders of what we think of as "field guides to natural resources" such as trees, flowers, birds, and so forth. There were not such books to identify soils but the basics have always been there waiting for proper attention, preparation, and use. At smaller scales the map units are always combinations of the basic units, and now it is possible to use some higher category classes to indicate the central concepts of larger areas. Every year soil scientists around the world observe and describe features and properties of soils in landscapes that are getting more attention than previously. Soil genesis studies help us to better understand the complexity of landscape and soil evolution. Often they indicate that current soils are commonly being formed from parts of previous soils. We do not need a new definition of soil. We do need to work on developing and testing complete interpretive classifications of soils to better meet the needs of societies today. This means "soil quality", "soil functions", and other attributes of soils require more attention, now and in the near future to permit politicians and lay publics to better understand the significance of soils to the future of civilization. "After all is said and done, more is said than done" Aesop, Greek storyteller

Near-Surface Geophysical Mapping of the Hydrological Response to an Intense Rainfall Event at the Field Scale

NASA Astrophysics Data System (ADS)

Martínez, G.; Vanderlinden, K.; Giraldez, J. V.; Espejo, A. J.; Muriel, J. L.

2009-12-01

Soil moisture plays an important role in a wide variety of biogeochemical fluxes in the soil-plant-atmosphere system and governs the (eco)hydrological response of a catchment to an external forcing such as rainfall. Near-surface electromagnetic induction (EMI) sensors that measure the soil apparent electrical conductivity (ECa) provide a fast and non-invasive means for characterizing this response at the field or catchment scale through high-resolution time-lapse mapping. Here we show how ECa maps, obtained before and after an intense rainfall event of 125 mm h-1, elucidate differences in soil moisture patterns and hydrologic response of an experimental field as a consequence of differed soil management. The dryland field (Vertisol) was located in SW Spain and cropped with a typical wheat-sunflower-legume rotation. Both, near-surface and subsurface ECa (ECas and ECad, respectively), were measured using the EM38-DD EMI sensor in a mobile configuration. Raw ECa measurements and Mean Relative Differences (MRD) provided information on soil moisture patterns while time-lapse maps were used to evaluate the hydrologic response of the field. ECa maps of the field, measured before and after the rainfall event showed similar patterns. The field depressions where most of water and sediments accumulated had the highest ECa and MRD values. The SE-oriented soil, which was deeper and more exposed to sun and wind, showed the lowest ECa and MRD. The largest differences raised in the central part of the field where a high ECa and MRD area appeared after the rainfall event as a consequence of the smaller soil depth and a possible subsurface flux concentration. Time-lapse maps of both ECa and MRD were also similar. The direct drill plots showed higher increments of ECa and MRD as a result of the smaller runoff production. Time-lapse ECa increments showed a bimodal distribution differentiating clearly the direct drill from the conventional and minimum tillage plots. However this kind of distribution could not be shown using MRD differences since they come from standardized distributions. Field-extend time-lapse ECa maps can provide useful images of the hydrological response of agricultural fields which can be used to evaluate different soil management strategies or to aid the assessment of biogeochemical fluxes at the field scale.

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

USGS Publications Warehouse

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

2008-01-01

Flooded, saturated, or poorly drained soils are commonly anaerobic, leading to microbially induced magnetite/maghemite dissolution and decreased soil magnetic susceptibility (MS). Thus, MS is considerably higher in well-drained soils (MS typically 40-80 ?? 10-5 standard international [SI]) compared to poorly drained soils (MS typically 10-25 ?? 10-5 SI) in Illinois, other soil-forming factors being equal. Following calibration to standard soil probings, MS values can be used to rapidly and precisely delineate hydric from nonhydric soils in areas with relatively uniform parent material. Furthermore, soil MS has a moderate to strong association with individual tree species' distribution across soil moisture regimes, correlating inversely with independently reported rankings of a tree species' flood tolerance. Soil MS mapping can thus provide a simple, rapid, and quantitative means for precisely guiding reforestation with respect to plant species' adaptations to soil drainage classes. For instance, in native woodlands of east-central Illinois, Quercus alba , Prunus serotina, and Liriodendron tulipifera predominantly occur in moderately well-drained soils (MS 40-60 ?? 10-5 SI), whereas Acer saccharinum, Carya laciniosa, and Fraxinus pennsylvanica predominantly occur in poorly drained soils (MS <20 ?? 10-5 SI). Using a similar method, an MS contour map was used to guide restoration of mesic, wet mesic, and wet prairie species to pre-settlement distributions at Meadowbrook Park (Urbana, IL, U.S.A.). Through use of soil MS maps calibrated to soil drainage class and native vegetation occurrence, restoration efforts can be conducted more successfully and species distributions more accurately reconstructed at the microecosystem level. ?? 2008 Society for Ecological Restoration International.

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

PubMed Central

de Lima, João L. M. P.; Abrantes, João R. C. B.; Silva, Valdemir P.; de Lima, M. Isabel P.; Montenegro, Abelardo A. A.

2014-01-01

Macropores and water flow in soils and substrates are complex and are related to topics like preferential flow, nonequilibrium flow, and dual-continuum. Hence, the quantification of the number of macropores and the determination of their geometry are expected to provide a better understanding on the effects of pores on the soil's physical and hydraulic properties. This exploratory study aimed at evaluating the potential of using infrared thermography for mapping macroporosity at the soil surface and estimating the number and size of such macropores. The presented technique was applied to a small scale study (laboratory soil flume). PMID:25371915

Application of Thermal Infrared Remote Sensing for Quantitative Evaluation of Crop Characteristics

NASA Technical Reports Server (NTRS)

Shaw, J.; Luvall, J.; Rickman, D.; Mask, P.; Wersinger, J.; Sullivan, D.; Arnold, James E. (Technical Monitor)

2002-01-01

Evidence suggests that thermal infrared emittance (TIR) at the field-scale is largely a function of the integrated crop/soil moisture continuum. Because soil moisture dynamics largely determine crop yields in non-irrigated farming (85 % of Alabama farms are non-irrigated), TIR may be an effective method of mapping within field crop yield variability, and possibly, absolute yields. The ability to map yield variability at juvenile growth stages can lead to improved soil fertility and pest management, as well as facilitating the development of economic forecasting. Researchers at GHCC/MSFC/NASA and Auburn University are currently investigating the role of TIR in site-specific agriculture. Site-specific agriculture (SSA), or precision farming, is a method of crop production in which zones and soils within a field are delineated and managed according to their unique properties. The goal of SSA is to improve farm profits and reduce environmental impacts through targeted agrochemical applications. The foundation of SSA depends upon the spatial and temporal characterization of soil and crop properties through the creation of management zones. Management zones can be delineated using: 1) remote sensing (RS) data, 2) conventional soil testing and soil mapping, and 3) yield mapping. Portions of this research have concentrated on using remote sensing data to map yield variability in corn (Zea mays L.) and soybean (Glycine max L.) crops. Remote sensing data have been collected for several fields in the Tennessee Valley region at various crop growth stages during the last four growing seasons. Preliminary results of this study will be presented.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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

USGS Publications Warehouse

Livo, K. Eric; Watson, Ken

2002-01-01

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

Soil depth mapping using seismic surface waves: Evaluation on eroded loess covered hillslopes

NASA Astrophysics Data System (ADS)

Bernardie, Severine; Samyn, Kevin; Cerdan, Olivier; Grandjean, Gilles

2010-05-01

The purposes of the multidisciplinary DIGISOIL project are the integration and improvement of in situ and proximal technologies for the assessment of soil properties and soil degradation indicators. Foreseen developments concern sensor technologies, data processing and their integration to applications of (digital) soil mapping (DSM). Among available techniques, the seismic one is, in this study, particularly tested for characterising soil vulnerability to erosion. The spectral analysis of surface waves (SASW) method is an in situ seismic technique used for evaluation of the stiffnesses (G) and associated depth in layered systems. A profile of Rayleigh wave velocity versus frequency, i.e., the dispersion curve, is calculated from each recorded seismogram before to be inverted to obtain the vertical profile of shear wave velocity Vs. Then, the soil stiffness can easily be calculated from the shear velocity if the material density is estimated, and the soil stiffness as a function of depth can be obtained. This last information can be a good indicator to identify the soil bedrock limit. SASW measurements adapted to soil characterisation is proposed in the DIGISOIL project, as it produces in an easy and quick way a 2D map of the soil. This system was tested for the digital mapping of the depth of loamy material in a catchment of the European loess belt. The validation of this methodology has been performed with the realisation of several acquisitions along the seismic profiles: - Several boreholes were drilled until the bedrock, permitting to get the geological features of the soil and the depth of the bedrock; - Several laboratory measurements of various parameters were done on samples taken from the boreholes at various depths, such as dry density, solid density, and water content; - Dynamic penetration tests were also conducted along the seismic profile, until the bedrock is attained. Some empirical correlations between the parameters measured with laboratory tests, the qc obtained from the dynamic penetration tests and the Vs acquired from the SASW measurements permit to assess the accuracy of the procedure and to evaluate its limitations. The depth to bedrock determined by this procedure can then be combined with the soil erosion susceptibility to produce a risk map. This methodology will help to target measures within areas that show a reduced soil depth associated with a high soil erosion susceptibility.

Effects of Long-term Soil and Crop Management on Soil Hydraulic Properties for Claypan Soils

USDA-ARS?s Scientific Manuscript database

Regional and national soil maps and associated databases of soil properties have been developed to help land managers make decisions based on soil characteristics. Hydrologic modelers also utilize soil hydraulic properties provided in these databases, in which soil characterization is based on avera...

The application of remote sensing technology to the solution of problems in the management of resources in Indiana

NASA Technical Reports Server (NTRS)

Weismiller, R. A. (Principal Investigator); Mroczynski, R. P.

1977-01-01

The author has identified the following significant results. The Lydich quadrangle area was successfully classified into seven cover types: (1) trees, (2) poorly drained soil and water, (3) pasture land, (4) well drained brown soil, (5) moderately well drained dark brown soil, (6) moderately drained soil, and (7) medium to poorly drained soil. Measurements of the percent of mapping unit represented by a named soil series range from 44 to 55 percent. If the class identified as vegetation is combined with the named unit, the range increases from 54 to 64 percent. The Xenia mapping unit was the only unit represented by less than 50 percent of the named unit. Results from the intensive tent moth study in Owensburg and Williams were interpreted from 70 mm color infrared and visually transferred to maps. A correction factor was necessary, because the date the sample photography was taken was a month later than the intensive site data (CF x acres defoliated in each level = expanded defoliated acres).

The Soil Moisture Active and Passive Mission (SMAP): Science and Applications

NASA Technical Reports Server (NTRS)

Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni

2009-01-01

The Soil Moisture Active and Passive mission (SMAP) will provide global maps of soil moisture content and surface freeze/thaw state. Global measurements of these variables are critical for terrestrial water and carbon cycle applications. The SMAP observatory consists of two multipolarization L-band sensors, a radar and radiometer, that share a deployable-mesh reflector antenna. The combined observations from the two sensors will allow accurate estimation of soil moisture at hydrometeorological (10 km) and hydroclimatological (40 km) spatial scales. The rotating antenna configuration provides conical scans of the Earth surface at a constant look angle. The wide-swath (1000 km) measurements will allow global mapping of soil moisture and its freeze/thaw state with 2-3 days revisit. Freeze/thaw in boreal latitudes will be mapped using the radar at 3 km resolution with 1-2 days revisit. The synergy of active and passive observations enables measurements of soil moisture and freeze/thaw state with unprecedented resolution, sensitivity, area coverage and revisit.

NASA Soil Moisture Mission Produces First Global Radar Map

NASA Image and Video Library

2015-04-21

With its antenna now spinning at full speed, NASA new Soil Moisture Active Passive SMAP observatory has successfully re-tested its science instruments and generated its first global maps, a key step to beginning routine science operations in May, 2015

NASA Soil Moisture Mission Produces First Global Radiometer Map

NASA Image and Video Library

2015-04-21

With its antenna now spinning at full speed, NASA new Soil Moisture Active Passive SMAP observatory has successfully re-tested its science instruments and generated its first global maps, a key step to beginning routine science operations in May, 2015

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

NASA Technical Reports Server (NTRS)

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

1972-01-01

Research to determine the optimum time or season for obtaining imagery to identify and map soil limitations was conducted in the proposed Oahe irrigation project area in South Dakota. The optimum time for securing photographs or imagery is when the soil surface patterns are most apparent. For cultivated areas similar to the study area, May is the optimum time. The density slicing analysis of the May image provided additional and more accurate information than did the existing soil map. The soil boundaries were more accurately located. The use of a density analysis system for an operational soil survey has not been tested, but is obviously dependent upon securing excellent photographs for interpretation. The colors or densities of photographs will have to be corrected for sun angle effects, vignetting effects, and processing to have maximum effectiveness for mapping soil limitations. Rangeland sites were established in Bennett County, South Dakota to determine the usefulness of ERTS imagery. Imagery from these areas was interpreted for land use and drainage patterns.

Case studies: Soil mapping using multiple methods

NASA Astrophysics Data System (ADS)

Petersen, Hauke; Wunderlich, Tina; Hagrey, Said A. Al; Rabbel, Wolfgang; Stümpel, Harald

2010-05-01

Soil is a non-renewable resource with fundamental functions like filtering (e.g. water), storing (e.g. carbon), transforming (e.g. nutrients) and buffering (e.g. contamination). Degradation of soils is meanwhile not only to scientists a well known fact, also decision makers in politics have accepted this as a serious problem for several environmental aspects. National and international authorities have already worked out preservation and restoration strategies for soil degradation, though it is still work of active research how to put these strategies into real practice. But common to all strategies the description of soil state and dynamics is required as a base step. This includes collecting information from soils with methods ranging from direct soil sampling to remote applications. In an intermediate scale mobile geophysical methods are applied with the advantage of fast working progress but disadvantage of site specific calibration and interpretation issues. In the framework of the iSOIL project we present here some case studies for soil mapping performed using multiple geophysical methods. We will present examples of combined field measurements with EMI-, GPR-, magnetic and gammaspectrometric techniques carried out with the mobile multi-sensor-system of Kiel University (GER). Depending on soil type and actual environmental conditions, different methods show a different quality of information. With application of diverse methods we want to figure out, which methods or combination of methods will give the most reliable information concerning soil state and properties. To investigate the influence of varying material we performed mapping campaigns on field sites with sandy, loamy and loessy soils. Classification of measured or derived attributes show not only the lateral variability but also gives hints to a variation in the vertical distribution of soil material. For all soils of course soil water content can be a critical factor concerning a succesful application of geophysical methods, e.g. GPR on wet loessy soils will result in a high attenuation of signals. Furthermore, with this knowledge we support the development of geophysical pedo-transfer-functions, i.e. the link between geophysical to soil parameters, which is active researched in another work package of the iSOIL project. Acknowledgement: iSOIL-Interactions between soil related sciences - Linking geophysics, soil science and digital soil mapping is a Collaborative Project (Grant Agreement number 211386) co-funded by the Research DG of the European Commission within the RTD activities of the FP7 Thematic Priority Environment.

Remotely sensed soil moisture input to a hydrologic model

NASA Technical Reports Server (NTRS)

Engman, E. T.; Kustas, W. P.; Wang, J. R.

1989-01-01

The possibility of using detailed spatial soil moisture maps as input to a runoff model was investigated. The water balance of a small drainage basin was simulated using a simple storage model. Aircraft microwave measurements of soil moisture were used to construct two-dimensional maps of the spatial distribution of the soil moisture. Data from overflights on different dates provided the temporal changes resulting from soil drainage and evapotranspiration. The study site and data collection are described, and the soil measurement data are given. The model selection is discussed, and the simulation results are summarized. It is concluded that a time series of soil moisture is a valuable new type of data for verifying model performance and for updating and correcting simulated streamflow.

Potential Electrokinetic Remediation Technologies of Laboratory Scale into Field Application- Methodology Overview

NASA Astrophysics Data System (ADS)

Ayuni Suied, Anis; Tajudin, Saiful Azhar Ahmad; Nizam Zakaria, Muhammad; Madun, Aziman

2018-04-01

Heavy metal in soil possesses high contribution towards soil contamination which causes to unbalance ecosystem. There are many ways and procedures to make the electrokinetic remediation (EKR) method to be efficient, effective, and potential as a low cost soil treatment. Electrode compartment for electrolyte is expected to treat the contaminated soil through electromigration and enhance metal ions movement. The electrokinetic is applicable for many approaches such as electrokinetic remediation (EKR), electrokinetic stabilization (EKS), electrokinetic bioremediation and many more. This paper presents a critical review on comparison of laboratory scale between EKR, EKS and EK bioremediation treatment by removing the heavy metal contaminants. It is expected to propose one framework of contaminated soil mapping. Electrical Resistivity Method (ERM) is one of famous indirect geophysical tools for surface mapping and subsurface profiling. Hence, ERM is used to mapping the migration of heavy metal ions by electrokinetic.

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

30 CFR 783.21 - Soil resources information.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Soil resources information. 783.21 Section 783... RESOURCES § 783.21 Soil resources information. (a) The applicant shall provide adequate soil survey... of the following: (1) A map delineating different soils; (2) Soil identification; (3) Soil...

Scaling up from field to region for wind erosion prediction using a field-scale wind erosion model and GIS

USGS Publications Warehouse

Zobeck, T.M.; Parker, N.C.; Haskell, S.; Guoding, K.

2000-01-01

Factors that affect wind erosion such as surface vegetative and other cover, soil properties and surface roughness usually change spatially and temporally at the field-scale to produce important field-scale variations in wind erosion. Accurate estimation of wind erosion when scaling up from fields to regions, while maintaining meaningful field-scale process details, remains a challenge. The objectives of this study were to evaluate the feasibility of using a field-scale wind erosion model with a geographic information system (GIS) to scale up to regional levels and to quantify the differences in wind erosion estimates produced by different scales of soil mapping used as a data layer in the model. A GIS was used in combination with the revised wind erosion equation (RWEQ), a field-scale wind erosion model, to estimate wind erosion for two 50 km2 areas. Landsat Thematic Mapper satellite imagery from 1993 with 30 m resolution was used as a base map. The GIS database layers included land use, soils, and other features such as roads. The major land use was agricultural fields. Data on 1993 crop management for selected fields of each crop type were collected from local government agency offices and used to 'train' the computer to classify land areas by crop and type of irrigation (agroecosystem) using commercially available software. The land area of the agricultural land uses was overestimated by 6.5% in one region (Lubbock County, TX, USA) and underestimated by about 21% in an adjacent region (Terry County, TX, USA). The total estimated wind erosion potential for Terry County was about four times that estimated for adjacent Lubbock County. The difference in potential erosion among the counties was attributed to regional differences in surface soil texture. In a comparison of different soil map scales in Terry County, the generalised soil map had over 20% more of the land area and over 15% greater erosion potential in loamy sand soils than did the detailed soil map. As a result, the wind erosion potential determined using the generalised soil map Was about 26% greater than the erosion potential estimated by using the detailed soil map in Terry County. This study demonstrates the feasibility of scaling up from fields to regions to estimate wind erosion potential by coupling a field-scale wind erosion model with GIS and identifies possible sources of error with this approach.

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

PubMed

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Digital Mapping of Soil Organic Carbon Contents and Stocks in Denmark

PubMed Central

Adhikari, Kabindra; Hartemink, Alfred E.; Minasny, Budiman; Bou Kheir, Rania; Greve, Mette B.; Greve, Mogens H.

2014-01-01

Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance inventories. For Denmark, we modeled the vertical distribution of soil organic carbon (SOC) and bulk density, and mapped its spatial distribution at five standard soil depth intervals (0−5, 5−15, 15−30, 30−60 and 60−100 cm) using 18 environmental variables as predictors. SOC distribution was influenced by precipitation, land use, soil type, wetland, elevation, wetness index, and multi-resolution index of valley bottom flatness. The highest average SOC content of 20 g kg−1 was reported for 0−5 cm soil, whereas there was on average 2.2 g SOC kg−1 at 60−100 cm depth. For SOC and bulk density prediction precision decreased with soil depth, and a standard error of 2.8 g kg−1 was found at 60−100 cm soil depth. Average SOC stock for 0−30 cm was 72 t ha−1 and in the top 1 m there was 120 t SOC ha−1. In total, the soils stored approximately 570 Tg C within the top 1 m. The soils under agriculture had the highest amount of carbon (444 Tg) followed by forest and semi-natural vegetation that contributed 11% of the total SOC stock. More than 60% of the total SOC stock was present in Podzols and Luvisols. Compared to previous estimates, our approach is more reliable as we adopted a robust quantification technique and mapped the spatial distribution of SOC stock and prediction uncertainty. The estimation was validated using common statistical indices and the data and high-resolution maps could be used for future soil carbon assessment and inventories. PMID:25137066

Digital mapping of soil organic carbon contents and stocks in Denmark.

PubMed

Adhikari, Kabindra; Hartemink, Alfred E; Minasny, Budiman; Bou Kheir, Rania; Greve, Mette B; Greve, Mogens H

2014-01-01

Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance inventories. For Denmark, we modeled the vertical distribution of soil organic carbon (SOC) and bulk density, and mapped its spatial distribution at five standard soil depth intervals (0-5, 5-15, 15-30, 30-60 and 60-100 cm) using 18 environmental variables as predictors. SOC distribution was influenced by precipitation, land use, soil type, wetland, elevation, wetness index, and multi-resolution index of valley bottom flatness. The highest average SOC content of 20 g kg(-1) was reported for 0-5 cm soil, whereas there was on average 2.2 g SOC kg(-1) at 60-100 cm depth. For SOC and bulk density prediction precision decreased with soil depth, and a standard error of 2.8 g kg(-1) was found at 60-100 cm soil depth. Average SOC stock for 0-30 cm was 72 t ha(-1) and in the top 1 m there was 120 t SOC ha(-1). In total, the soils stored approximately 570 Tg C within the top 1 m. The soils under agriculture had the highest amount of carbon (444 Tg) followed by forest and semi-natural vegetation that contributed 11% of the total SOC stock. More than 60% of the total SOC stock was present in Podzols and Luvisols. Compared to previous estimates, our approach is more reliable as we adopted a robust quantification technique and mapped the spatial distribution of SOC stock and prediction uncertainty. The estimation was validated using common statistical indices and the data and high-resolution maps could be used for future soil carbon assessment and inventories.

Dependence of the cyclization of branched tetraethers on soil moisture in alkaline soils from arid-subhumid China: implications for palaeorainfall reconstructions on the Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

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

2014-12-01

The use of branched glycerol dialkyl glycerol tetraethers (bGDGTs) in loess-palaeosol sequences (LPSs) has shown promises in continental palaeotemperature reconstructions. Thus far, however, little is known about the effect of soil moisture on their distributions in the water-limited Chinese Loess Plateau (CLP). In this study, the relationships between environmental variables and the cyclization of branched tetraethers (CBT) were investigated in arid-subhumid China using 97 surface soils in the CLP and its vicinity, as well as 78 soils with pH > 7 which have been previously published. We find that CBT correlates best with soil water content (SWC) or mean annual precipitation (MAP) for the overall data set. This indicates that CBT is mainly controlled by soil moisture instead of soil pH in alkaline soils from arid-subhumid regions, where water availability is a limiting factor for the producers of bGDGTs. Therefore, we suggest that CBT can potentially be used as a palaeorainfall proxy on the alkaline CLP. According to the preliminary CBT-MAP relationship for modern CLP soils (CBT = -0.0021 × MAP + 1.7, n = 37, r = -0.93), palaeorainfall history was reconstructed from three LPSs (Yuanbao, Lantian, and Mangshan) with published bGDGT data spanning the past 70 ka. The CBT-derived MAP records of the three sites consistently show precession-driven variation resembling the monsoon record based on speleothem δ18O, supporting CBT as a reasonable proxy for palaeorainfall reconstruction in LPS. The direct application of CBT as a palaeorainfall proxy in corroboration with the bGDGT-based temperature proxy may enable us to further assess the temperature/hydrological association for palaeoclimate studies on the CLP.

Irrigation salinity hazard assessment and risk mapping in the lower Macintyre Valley, Australia.

PubMed

Huang, Jingyi; Prochazka, Melissa J; Triantafilis, John

2016-05-01

In the Murray-Darling Basin of Australia, secondary soil salinization occurs due to excessive deep drainage and the presence of shallow saline water tables. In order to understand the cause and best management, soil and vadose zone information is necessary. This type of information has been generated in the Toobeah district but owing to the state border an inconsistent methodology was used. This has led to much confusion from stakeholders who are unable to understand the ambiguity of the results in terms of final overall risk of salinization. In this research, a digital soil mapping method that employs various ancillary data is presented. Firstly, an electromagnetic induction survey using a Geonics EM34 and EM38 was used to characterise soil and vadose zone stratigraphy. From the apparent electrical conductivity (ECa) collected, soil sampling locations were selected and with laboratory analysis carried out to determine average (2-12m) clay and EC of a saturated soil-paste extract (ECe). EM34 ECa, land surface parameters derived from a digital elevation model and measured soil data were used to establish multiple linear regression models, which allowed for mapping of various hazard factors, including clay and ECe. EM38 ECa data were calibrated to deep drainage obtained from Salt and Leaching Fraction (SaLF) modelling of soil data. Expert knowledge and indicator kriging were used to determine critical values where the salinity hazard factors were likely to contribute to a shallow saline water table (i.e., clay ≤35%; ECe>2.5dS/m, and deep drainage >100mm/year). This information was combined to produce an overall salinity risk map for the Toobeah district using indicator kriging. The risk map shows potential salinization areas and where detailed information is required and where targeted research can be conducted to monitor soil conditions and water table heights and determine best management strategies. Copyright © 2016 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Integrating proximal soil sensing techniques and terrain indexes to generate 3D maps of soil restrictive layers in the Palouse region, Washington, USA

NASA Astrophysics Data System (ADS)

Poggio, Matteo; Brown, David J.; Gasch, Caley K.; Brooks, Erin S.; Yourek, Matt A.

2015-04-01

In the Palouse region of eastern Washington and northern Idaho (USA), spatially discontinuous restrictive layers impede rooting growth and water infiltration. Consequently, accurate maps showing the depth and spatial extent of these restrictive layers are essential for watershed hydrologic modeling appropriate for precision agriculture. In this presentation, we report on the use of a Visible and Near-Infrared (VisNIR) penetrometer fore optic to construct detailed maps of three wheat fields in the Palouse region. The VisNIR penetrometer was used to deliver in situ soil reflectance to an Analytical Spectral Devices (ASD, Boulder, CO, USA) spectrometer and simultaneously acquire insertion force. With a hydraulic push-type soil coring systems for insertion (e.g. Giddings), we collected soil spectra and insertion force data along 41m x 41m grid points (2 fields) and 50m x 50m grid points (1 field) to ≈80cm depth, in addition to interrogation points at 36 representative instrumented locations per field. At each of the 36 instrumented locations, two soil cores were extracted for laboratory determination of clay content and bulk density. We developed calibration models of soil clay content and bulk density with spectra and insertion force collected in situ, using partial least squares regression 2 (PLSR2). Applying spline functions, we delineated clay and bulk density profiles at each points (grid and 24 locations). The soil profiles were then used as inputs in a regression-kriging model with terrain indexes and ECa data (derived from an EM38 field survey, Geonics, Mississauga, Ontario, Canada) as covariates to generate 3D soil maps. Preliminary results show that the VisNIR penetrometer can capture the spatial patterns of restrictive layers. Work is ongoing to evaluate the prediction accuracy of penetrometer-derived 3D clay content and restriction layer maps.

Soil Salinity Mapping in Everglades National Park Using Remote Sensing Techniques

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Soil Fertility Evaluation and Land Management of Dryland Farming at Tegallalang Sub-District, Gianyar Regency, Bali, Indonesia

NASA Astrophysics Data System (ADS)

Sardiana, I. K.; Susila, D.; Supadma, A. A.; Saifulloh, M.

2017-12-01

The landuse of Tegallalang Subdistrict is dominated by dryland farming. The practice of cultivation on agricultural dryland that ignores the carrying capacity of the environment can lead to land degradation that makes the land vulnerable to the deterioration of soil fertility. Soil fertility evaluation and land management of dryland farming in Tegallalang Sub-district, Gianyar Regency were aimed at (1) identifying the soil fertility and it’s respective limiting factors, (2) mapping the soil fertility using Geographic Information Systems (GIS) and (3) developing land management for dryland farming in Tegallalang Sub-district. This research implementing explora-tory method which followed by laboratory analysis. Soil samples were taken on each homogene-ous land units which developed by overlay of slope, soil type, and land use maps. The following soil fertility were measured, such as CEC, base saturation, P2O5, K- Total and C-Organic. The values of soil fertility were mapping using QGIS 2.18.7 and refer to land management evaluation. The results showed that the soil fertility in the research area considered high, and low level. The High soil fertility presents on land units at the flat to undulating slope with different land management systems (fertilizer, without fertilizer, soil tillage and without soil tillage). The low soil fertility includes land units that present on steep slope, and without land managements. The limiting factors of soil fertility were texture, C-Organic, CEC, P2O5, and K- total. It was recommended to applying organic fertilizer, Phonska, and dolomite on the farming area.

Surficial geologic map of the Heath-Northfield-Southwick-Hampden 24-quadrangle area in the Connecticut Valley region, west-central Massachusetts

USGS Publications Warehouse

Stone, Janet R.; DiGiacomo-Cohen, Mary L.

2010-01-01

The surficial geologic map layer shows the distribution of nonlithified earth materials at land surface in an area of 24 7.5-minute quadrangles (1,238 mi2 total) in west-central Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text, quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Surficial geologic map of the Norton-Manomet-Westport-Sconticut Neck 23-quadrangle area in southeast Massachusetts

USGS Publications Warehouse

Stone, Byron D.; Stone, Janet R.; DiGiacomo-Cohen, Mary L.; Kincare, Kevin A.

2012-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of 23 7.5-minute quadrangles (919 mi2 total) in southeastern Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Surficial geologic map of the Mount Grace-Ashburnham-Monson-Webster 24-quadrangle area in central Massachusetts

USGS Publications Warehouse

Stone, Janet R.

2013-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of 24 7.5-minute quadrangles (1,238 mi2 total) in central Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction-aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Residual effects of monoammonium phosphate, gypsum and elemental sulfur on cadmium phytoavailability and translocation from soil to wheat in an effluent irrigated field.

PubMed

Qayyum, Muhammad Farooq; Rehman, Muhammad Zia Ur; Ali, Shafaqat; Rizwan, Muhammad; Naeem, Asif; Maqsood, Muhammad Aamer; Khalid, Hinnan; Rinklebe, Jörg; Ok, Yong Sik

2017-05-01

Cadmium (Cd) accumulation in agricultural soils is one of the major threats to food security. The application of inorganic amendments such as mono-ammonium phosphate (MAP), gypsum and elemental sulfur (S) could alleviate the negative effects of Cd in crops. However, their long-term residual effects on decreasing Cd uptake in latter crops remain unclear. A field that had previously been applied with treatments including control and 0.2, 0.4 and 0.8% by weight of each MAP, gypsum and S, and grown with wheat and rice and thereafter wheat in the rotation was selected for this study. Wheat (Triticum aestivum L.) was grown in the same field as the third crop without further application of amendments to evaluate the residual effects of the amendments on Cd uptake by wheat. Plants were harvested at maturity and grain, and straw yield along with Cd concentration in soil, straw, and grains was determined. The addition of MAP and gypsum significantly increased wheat growth and yield and decreased Cd accumulation in straw and grains compared to control while the reverse was found in S application. Both MAP and gypsum decreased AB-DTPA extractable Cd in soil while S increased the bioavailable Cd in soil. Both MAP and gypsum increased the Cd immobilization in the soil and S decreased Cd immobilization in a dose-additive manner. We conclude that MAP and gypsum had a significant residual effect on decreasing Cd uptake in wheat. The cost-benefit ratio revealed that gypsum is an effective amendment for decreasing Cd concentration in plants. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2005-12-01

American pedology has focused on the National Cooperative Soil Survey. Primary responsibility rests with the U.S. Department of Agriculture. The primary goals, are legislatively mandated, are to map the country's soils, make interpretations, provide information to clients, maintain and market the soil survey. The first goal is near completion and focus is shifting to the other three. Concomitantly, American pedological science is being impacted by several conditions: technological advances; land use changes at unprecedented scales and magnitudes; a burgeoning population increasingly "separated" from the land; and a major emphasis in universities upon biological ("life") sciences at the DNA scale - as if soil, nutrients and water are not life essentials. Effects of the Flood of 1993 and Hurricane Katrina suggest that humans do not understand earth/climate interactions, particularly climatic extremes. Pedologists know the focus on soil classification and mapping was at the expense of understanding processes. Hydropedology is a holistic approach to understanding soil and geomorphic process in order to predict the impacts of perturbations. Water movement on and in the soil is the primary mechanism of distributing and altering sediments and chemicals (pedogenesis), and depends for its success upon understanding that the soil profile is the record of developmental history at that landscape site. Hydropedologists believe soil scientists can use pedons (point data) from appropriate locations from flownets in complex landscapes to extrapolate processes. This is the "pedotransfer function" concept. Technological advances are coupled with the existing soil survey information to create important soil-landscape interpretations at a variety of scales. Early results have been very successful. Quantification of soil systems can be classified broadly into three categories; hard data, soft data and tacit knowledge. "Hard data" are measured numbers, and include such attributes as pH, texture, cation exchange capacity and event-specific rainfall. "Soft data" include soil maps, SSURGO data and climate maps. Soft data are combinations of observations, measurements and inferences that produce maps and models at various scales. "Tacit knowledge" is human understanding that results from focused experience within a system. A skilled soil scientist with tacit knowledge specific to a particular region can combination hard and soft data to develop important and useful interpretations and predictions. Illustrations from natural and urban settings will be provided. Soils and climate are temporally and spatially variable at all scales. Soil systems respond differently to different climates and perturbations. For example, the recent pluvial period in the Prairie Pothole region is changing surface soil sodium concentrations and locations and sizes of discharge wetlands. This is a relatively short-term response to a regional climate shift. Climatic shift in Oxisol landscapes will have little effect on soil cations. To optimize soil interpretations, focus must be on quantifying region-specific "dynamic" soil, geomorphic and climatic attributes. Recognizing these needs, the National Cooperative Soil Survey will develop regional watershed projects that focus on quantifying soil-water relationships that can be used at a variety of scales.

Towards quantitative usage of EMI-data for Digital Soil Mapping

NASA Astrophysics Data System (ADS)

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

2009-04-01

As formulated in the Thematic Strategy for Soil Protection prepared by the European Commission soil degradation is a serious problem in Europe. The degradation is driven or exacerbated by human activity and has a direct impact on water and air quality, biodiversity, climate and human life-quality. High-resolution soil property maps are one major prerequisite for the specific protection of soil function and restoration of degraded soils as well as sustainable land use, water and environmental management. However, the currently available techniques for (digital) soil mapping still have deficiencies in terms of reliability and precision, the feasibility of investigation of large areas (e.g. catchments and landscapes) and the assessment of soil degradation threats at this scale. The focus of the iSOIL (Interactions between soil related science - Linking geophysics, soil science and digital soil mapping) project is on improving fast and reliable mapping of soil properties, soil functions and soil degradation threats. This requires the improvement as well as integration of geophysical and spectroscopic measurement techniques in combination with advanced soil sampling approaches, pedometrical and pedophysical approaches. Many commercially available geophysical sensors and equipment (EMI, DC, gamma-spectroscopy, magnetics) are ready to use for measurements of different parameters. Data collection with individual sensors is well developed and numerously described. However comparability of data of different sensor types as well as reproducibility of data is not self-evident. In particular handling of sensors has to be carried out accurately, e.g. consistent calibration. Soil parameters will be derived from geophysical properties to create comprehensive soil maps. Therefore one prerequisite is the comparison of different geophysical properties not only qualitative but also quantitative. At least reproducibility is one of the most important conditions for monitoring tasks. The first parameter we focussed on is apparent electrical conductivity (ECa). It is an important geophysical properity in soil science since soil parameters (water content, etc.) can be deduced. Nowadays mobile geophysical platforms allow to survey large areas comprehensively in a short time period. These platforms have been equipped with EM38DD (Geonics) and Profiler EMP-400 (GSSI) - two different types of electromagnetic induction (EMI) instruments - within first iSOIL field campaign. While EM38DD measures in horizontal and vertical mode at the same time, Profiler measures three frequencies simultaneously and magnetic susceptibility additionally. Coil separation of the instruments is nearly the same, so penetration depth is similar. On the other hand, frequencies are arbitrary at Profiler but fixed at EM38DD. These differences in penetration depth have to taken into account. By our measurement we tested the comparability of the data to show differences between instruments of the same type (EM38DD-EM38DD) using different settings, and different types (EM38DD-Profiler). Moreover both sensors work in continuous as well in discontinuous mode. The results show that quality of data is comparable, but the quantities are varying. This has to be considered for further interpretations and monitoring. In the next steps we have to determine how to convert relative data into absolute data since ECa data from different locations are not comparable to each other in a quantitative way. In the talk we will give an introduction in the application of EMI for soil monitoring, followed by an overview about comparability and reproducibility of data.

Soil degradation level under particular annual rainfall at Jenawi District– Karanganyar, Indonesia

NASA Astrophysics Data System (ADS)

Herawati, A.; Suntoro; Widijanto, H.; Pusponegoro, I.; Sutopo, N. R.; Mujiyo

2018-03-01

The study of the climatic elements such as rainfall is vital for the sustainable development of agriculture at a region. The aims of the study were to evaluate the soil degradation based on the annual rainfall and to determine the key factors which responsible for the soil degradation at in Jenawi Sub-District. The mapping of soil degradation potency is an identification of initial soil condition to discover the potential of the land degradation. The mapping was done by overlaying the map of soil, slope, rainfall and land use with the standard procedures to obtain the value and status of Soil Degradation Potency (SDP). The result showed that SDP in Jenawi District categorized in very low (SDP I) 0.00 ha (0.00%); low (SDP II) 109.01 ha (2.57%); moderate (SDP III) 1,935.92 ha (45.63%); high (SDP IV) 1,959.54 ha (46.19%) and very high (SDP V) 238.08 ha (5.61%). The rainfall is the factor which has the strong correlation with the SDP (r = 0.65, P < 0.01, n = 306). The changes in the rainfall as the impact of climate change need to be anticipated to minimize soil degradation. The result can be adapted to the rainfall changes in various ways based on local soil-land characteristics.

Mapping soil erosion risk in Serra de Grândola (Portugal)

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

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

NASA Astrophysics Data System (ADS)

Lawrence, C. R.

2017-12-01

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

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

USGS Publications Warehouse

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

2007-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

The informativeness of NDVI for predictive mapping of the physical and chemical properties of plow horizons of soils on different slope positions within the first (280-310 m a.s.l.) and second (240-280 m a.s.l.) altitudinal steps has been examined. This index is uninformative for mapping soil properties in small hollows, whose factual width is less than the Landsat image resolution (30 m). In regression models, NDVI index explains 52% of variance in the content of humus; 35 and 24% of variance in the contents of total and nitrate nitrogen; 19 and 29% of variance in the contents of total and available phosphorus; 25 and 50% of variance in the contents of exchangeable calcium and manganese; and 30 and 29% of variance in the contents of fine silt and soil water, respectively. On the basis of the models obtained, prognostic maps of the soil properties have been developed. Spatial distribution patterns of NDVI calculated from Landsat 8 images (30-m resolution) serve as the cartographic base and the main indicator of the soil properties. The NDVI values and the contents of humus, physical clay (<0.01 mm) and fine silt particles, total and nitrate nitrogen, total phosphorus, and exchangeable calcium and manganese in the soils of the first altitudinal step are higher than those in the soils of the second altitudinal step. An opposite tendency has been found for the available phosphorus content: in the soils of the second altitudinal step and the hollow, its content is higher than that in the soils of the first altitudinal step by 1.8 and 2.4 times, respectively. Differences in the pH of soil water suspensions, easily available phosphorus, and clay in the soils of the compared topographic positions (first and second altitudinal steps and the hollow) are statistically unreliable.

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

USGS Publications Warehouse

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

2007-01-01

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

[Assessment of soil degradation in regions of nuclear power explosions at Semipalatinsk Nuclear Test Site].

PubMed

Evseeva, T I; Geras'kin, S A; Maĭstrenko, T A; Belykh, E S

2011-01-01

Degree of the soil cover degradation at the "Balapan" and "Experimental field" test sites was assessed based on Allium-test of soil toxicity results and international guidelines on radioactive restriction of solid materials (IAEA, 2004) and environment (Smith, 2005). Soil cover degradation maps of large-scale (1 : 25000) were made. The main part of the area mapped belongs to high-contaminated toxic degraded soil. A relationship between the soil toxicity and the total radionuclide activity concentrations was found to be described by power functions. When the calculated value (equal to 413-415 Bq/kg of air dry soil) increases, the soil becomes toxic for plants. This value is 7.8 times higher than the maximal value for background territories (53 Bq/kg) surrounding SNTS. Russian sanitary and hygienic guidelines (Radiation safety norms, 2009; Sanitary regulations of radioactive waste management, 2003) underestimate the degree of soil radioactive contamination for plants.

High resolution mapping of soil organic carbon stocks using remote sensing variables in the semi-arid rangelands of eastern Australia.

PubMed

Wang, Bin; Waters, Cathy; Orgill, Susan; Gray, Jonathan; Cowie, Annette; Clark, Anthony; Liu, De Li

2018-07-15

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

Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing

USGS Publications Warehouse

Kokaly, R.F.; Rockwell, B.W.; Haire, S.L.; King, T.V.V.

2007-01-01

Forest fires leave behind a changed ecosystem with a patchwork of surface cover that includes ash, charred organic matter, soils and soil minerals, and dead, damaged, and living vegetation. The distributions of these materials affect post-fire processes of erosion, nutrient cycling, and vegetation regrowth. We analyzed high spatial resolution (2.4??m pixel size) Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data collected over the Cerro Grande fire, to map post-fire surface cover into 10 classes, including ash, soil minerals, scorched conifer trees, and green vegetation. The Cerro Grande fire occurred near Los Alamos, New Mexico, in May 2000. The AVIRIS data were collected September 3, 2000. The surface cover map revealed complex patterns of ash, iron oxide minerals, and clay minerals in areas of complete combustion. Scorched conifer trees, which retained dry needles heated by the fire but not fully combusted by the flames, were found to cover much of the post-fire landscape. These scorched trees were found in narrow zones at the edges of completely burned areas. A surface cover map was also made using Landsat Enhanced Thematic Mapper plus (ETM+) data, collected September 5, 2000, and a maximum likelihood, supervised classification. When compared to AVIRIS, the Landsat classification grossly overestimated cover by dry conifer and ash classes and severely underestimated soil and green vegetation cover. In a comparison of AVIRIS surface cover to the Burned Area Emergency Rehabilitation (BAER) map of burn severity, the BAER high burn severity areas did not capture the variable patterns of post-fire surface cover by ash, soil, and scorched conifer trees seen in the AVIRIS map. The BAER map, derived from air photos, also did not capture the distribution of scorched trees that were observed in the AVIRIS map. Similarly, the moderate severity class of Landsat-derived burn severity maps generated from the differenced Normalized Burn Ratio (dNBR) calculation had low agreement with the AVIRIS classes of scorched conifer trees. Burn severity and surface cover images were found to contain complementary information, with the dNBR map presenting an image of degree of change caused by fire and the AVIRIS-derived map showing specific surface cover resulting from fire.

Soil erosion assessment using the Universal Soil Loss Equation (USLE) in a GIS framework: A case study of Zacatecas, México

NASA Astrophysics Data System (ADS)

Betanzos Arroyo, L. I.; Prol Ledesma, R. M.; da Silva Pinto da Rocha, F. J. P.

2014-12-01

The Universal Soil Loss Equation (USLE), which is considered to be a contemporary approach in soil loss assessment, was used to assess soil erosion hazard in the Zacatecas mining district. The purpose of this study is to produce erosion susceptibility maps for an area that is polluted with mining tailings which are susceptible to erosion and can disperse the particles that contain heavy metals and other toxic elements. USLE method is based in the estimation of soil loss per unit area and takes into account specific parameters such as precipitation data, topography, soil erodibility, erosivity and runoff. The R-factor (rainfall erosivity) was calculated from monthly and annual precipitation data. The K-factor (soil erodibility) was estimated using soil maps available from the CONABIO at a scale of 1:250000. The LS-factor (slope length and steepness) was determined from a 30-m digital elevation model. A raster-based Geographic Information System (GIS) was used to interactively calculate soil loss and map erosion hazard. The results show that estimated erosion rates ranged from 0 to 4770.48 t/ha year. Maximum proportion of the total area of the Zacatecas mining district have nil to very extremely slight erosion severity. Small areas in the central and south part of the study area shows the critical condition requiring sustainable land management.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

The assessment of spatial distribution of soil salinity risk using neural network.

PubMed

Akramkhanov, Akmal; Vlek, Paul L G

2012-04-01

Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km(2)) results were used to upscale soil salinity to a district area (∼300 km(2)). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m(-1)). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70-90% of locations were correctly estimated.

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

NASA Astrophysics Data System (ADS)

Cumbrera, Ramiro; Millán, Humberto; Martín-Sotoca, Juan Jose; Pérez Soto, Luis; Sanchez, Maria Elena; Tarquis, Ana Maria

2016-04-01

Soil moisture distribution usually presents extreme variation at multiple spatial scales. Image analysis could be a useful tool for investigating these spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to describe the local scaling of apparent soil moisture distribution and (ii) to define apparent soil moisture patterns from vertical planes of Vertisol pit images. Two soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. One was excavated in April/2011 and the other pit was established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak™ digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ≈373 μm of the photographed soil pit. For more details see Cumbrera et al. (2012). Geochemical exploration have found with increasingly interests and benefits of using fractal (power-law) models to characterize geochemical distribution, using the concentration-area (C-A) model (Cheng et al., 1994; Cheng, 2012). This method is based on the singularity maps of a measure that at each point define areas with self-similar properties that are shown in power-law relationships in Concentration-Area plots (C-A method). The C-A method together with the singularity map ("Singularity-CA" method) define thresholds that can be applied to segment the map. We have applied it to each soil image. The results show that, in spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used to study the dynamical change of soil moisture sampling in agreement with previous results (Millán et al., 2016). REFERENCES Cheng, Q., Agterberg, F. P. and Ballantyne, S. B. (1994). The separation of geochemical anomalies from background by fractal methods. Journal of Geochemical Exploration, 51, 109-130. Cheng, Q. (2012). Singularity theory and methods for mapping geochemical anomalies caused by buried sources and for predicting undiscovered mineral deposits in covered areas. Journal of Geochemical Exploration, 122, 55-70. Cumbrera, R., Ana M. Tarquis, Gabriel Gascó, Humberto Millán (2012) Fractal scaling of apparent soil moisture estimated from vertical planes of Vertisol pit images. Journal of Hydrology (452-453), 205-212. Martin Sotoca; J.J. Antonio Saa-Requejo, Juan Grau and Ana M. Tarquis (2016). Segmentation of singularity maps in the context of soil porosity. Geophysical Research Abstracts, 18, EGU2016-11402. Millán, H., Cumbrera, R. and Ana M. Tarquis (2016) Multifractal and Levy-stable statistics of soil surface moisture distribution derived from 2D image analysis. Applied Mathematical Modelling, 40(3), 2384-2395.

SOIL RADON POTENTIAL MAPPLING OF TWELVE COUNTIES IN NORTH-CENTRAL FLORIDA

EPA Science Inventory

The report describes the approach, methods, and detailed data used to prepare soil radon potential maps of 12 counties in North-Central Florida. he maps were developed under the Florida Radon Research Program to provide a scientific basis for implementing radon-protective buildin...

Multidate, multisensor remote sensing reveals high density of carbon-rich mountain peatlands in the páramo of Ecuador.

PubMed

Hribljan, John A; Suarez, Esteban; Bourgeau-Chavez, Laura; Endres, Sarah; Lilleskov, Erik A; Chimbolema, Segundo; Wayson, Craig; Serocki, Eleanor; Chimner, Rodney A

2017-12-01

Tropical peatlands store a significant portion of the global soil carbon (C) pool. However, tropical mountain peatlands contain extensive peat soils that have yet to be mapped or included in global C estimates. This lack of data hinders our ability to inform policy and apply sustainable management practices to these peatlands that are experiencing unprecedented high rates of land use and land cover change. Rapid large-scale mapping activities are urgently needed to quantify tropical wetland extent and rate of degradation. We tested a combination of multidate, multisensor radar and optical imagery (Landsat TM/PALSAR/RADARSAT-1/TPI image stack) for detecting peatlands in a 2715 km 2 area in the high elevation mountains of the Ecuadorian páramo. The map was combined with an extensive soil coring data set to produce the first estimate of regional peatland soil C storage in the páramo. Our map displayed a high coverage of peatlands (614 km 2 ) containing an estimated 128.2 ± 9.1 Tg of peatland belowground soil C within the mapping area. Scaling-up to the country level, páramo peatlands likely represent less than 1% of the total land area of Ecuador but could contain as much as ~23% of the above- and belowground vegetation C stocks in Ecuadorian forests. These mapping approaches provide an essential methodological improvement applicable to mountain peatlands across the globe, facilitating mapping efforts in support of effective policy and sustainable management, including national and global C accounting and C management efforts. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Spatial analysis of plutonium-239 + 240 and Americium-241 in soils around Rocky Flats, Colorado

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

Litaor, M.I.

1995-05-01

Plutonium and american contamination of soils around Rocky Flats, Colorado resulted from past outdoor storage practices. Four previous studies produce four different Pu isopleth maps. Spatial estimation techniques were not used in the construction of these maps and were also based on an extremely small number of soil samples. The purpose of this study was to elucidate the magnitude of Pu-239 + 240 and Am-241 dispersion in the soil environment east of Rocky Flats using robust spatial estimation techniques. Soils were sampled from 118 plots of 1.01 and 4.05 ha by compositing 25 evenly spaced samples in each plot frommore » the top 0.64 cm. Plutonium-239 + 240 activity ranged from 1.85 to 53 560 Bq/kg with a mean of 1924 Bq/kg and a standard deviation of 6327 Bq/kg. Americium-241 activity ranged from 0.18 to 9990 Bq/kg with a mean of 321 Bq/kg and a standard deviation of 1143 Bq/kg. Geostatistical techniques were used to model the spatial dependency and construct isopleth maps showing Pu-239 + 240 and Am-241 distribution. The isopleth configuration was consistent with the hypothesis that the dominant dispersal mechanism of Pu-239 + 240 was wind dispersion from west to east. The Pu-239 + 240 isopleth map proposed to this study differed significantly in the direction and distance of dispersal from the previously published maps. This ispleth map as well as the Am-241 map should be used as the primary data for future risk assessment associated with public exposure to Pu-239 + 240 and Am-241. 37 refs., 7 figs., 2 tabs.« less

Long-term comparison of Kuparuk Watershed active layer maps, northern Alaska, USA

NASA Astrophysics Data System (ADS)

Nyland, K. E.; Queen, C.; Nelson, F. E.; Shiklomanov, N. I.; Streletskiy, D. A.; Klene, A. E.

2017-12-01

The active layer, or the uppermost soil horizon that thaws seasonally, is among the most dynamic components of the permafrost system. Evaluation of the thickness and spatial variation of the active layer is critical to many components of Arctic research, including climatology, ecology, environmental monitoring, and engineering. In this study we mapped active-layer thickness (ALT) across the 22,278 sq. km Kuparuk River basin on Alaska's North Slope throughout the summer of 2016. The Kuparuk River extends from the Brooks Range through the Arctic Foothills and across the Arctic Coastal Plain physiographic provinces, and drains into the Beaufort Sea. Methodology followed procedures used to produce an ALT map of the basin in 1995 accounting for the effects of topography, vegetation, topoclimate, and soils, using the same spatial sampling scheme for direct ALT and temperature measurement at representative locations and relating these parameters to vegetation-soil associations. A simple semi-empirical engineering solution was used to estimate thaw rates for the different associations. An improved lapse-rate formulation and a higher-resolution DEM were used to relate temperature to elevation. Three ALT maps were generated for the 2016 summer, combining measured thaw depth, temperature records, the 25 m ArcticDEM, high resolution remote sensed data, empirical laps rates, and a topoclimatic index through the thaw solution. These maps were used to track the spatial progression of thaw through the 2016 summer season and estimate a total volume of thawed soil. Maps produced in this study were compared to the 1995 map to track areas of significant geographic changes in patterns of ALT and total volume of thawed soil.

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

PubMed

Chen, Chong; Hu, Kelin; Li, Hong; Yun, Anping; Li, Baoguo

2015-01-01

Understanding spatial variation of soil organic carbon (SOC) in three-dimensional direction is helpful for land use management. Due to the effect of profile depths and soil texture on vertical distribution of SOC, the stationary assumption for SOC cannot be met in the vertical direction. Therefore the three-dimensional (3D) ordinary kriging technique cannot be directly used to map the distribution of SOC at a regional scale. The objectives of this study were to map the 3D distribution of SOC at a regional scale by combining kriging method with the profile depth function of SOC (KPDF), and to explore the effects of soil texture and land use type on vertical distribution of SOC in a fluvial plain. A total of 605 samples were collected from 121 soil profiles (0.0 to 1.0 m, 0.20 m increment) in Quzhou County, China and SOC contents were determined for each soil sample. The KPDF method was used to obtain the 3D map of SOC at the county scale. The results showed that the exponential equation well described the vertical distribution of mean values of the SOC contents. The coefficients of determination, root mean squared error and mean prediction error between the measured and the predicted SOC contents were 0.52, 1.82 and -0.24 g kg(-1) respectively, suggesting that the KPDF method could be used to produce a 3D map of SOC content. The surface SOC contents were high in the mid-west and south regions, and low values lay in the southeast corner. The SOC contents showed significant positive correlations between the five different depths and the correlations of SOC contents were larger in adjacent layers than in non-adjacent layers. Soil texture and land use type had significant effects on the spatial distribution of SOC. The influence of land use type was more important than that of soil texture in the surface soil, and soil texture played a more important role in influencing the SOC levels for 0.2-0.4 m layer.

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

PubMed Central

Chen, Chong; Hu, Kelin; Li, Hong; Yun, Anping; Li, Baoguo

2015-01-01

Understanding spatial variation of soil organic carbon (SOC) in three-dimensional direction is helpful for land use management. Due to the effect of profile depths and soil texture on vertical distribution of SOC, the stationary assumption for SOC cannot be met in the vertical direction. Therefore the three-dimensional (3D) ordinary kriging technique cannot be directly used to map the distribution of SOC at a regional scale. The objectives of this study were to map the 3D distribution of SOC at a regional scale by combining kriging method with the profile depth function of SOC (KPDF), and to explore the effects of soil texture and land use type on vertical distribution of SOC in a fluvial plain. A total of 605 samples were collected from 121 soil profiles (0.0 to 1.0 m, 0.20 m increment) in Quzhou County, China and SOC contents were determined for each soil sample. The KPDF method was used to obtain the 3D map of SOC at the county scale. The results showed that the exponential equation well described the vertical distribution of mean values of the SOC contents. The coefficients of determination, root mean squared error and mean prediction error between the measured and the predicted SOC contents were 0.52, 1.82 and -0.24 g kg-1 respectively, suggesting that the KPDF method could be used to produce a 3D map of SOC content. The surface SOC contents were high in the mid-west and south regions, and low values lay in the southeast corner. The SOC contents showed significant positive correlations between the five different depths and the correlations of SOC contents were larger in adjacent layers than in non-adjacent layers. Soil texture and land use type had significant effects on the spatial distribution of SOC. The influence of land use type was more important than that of soil texture in the surface soil, and soil texture played a more important role in influencing the SOC levels for 0.2-0.4 m layer. PMID:26047012

SoilInfo App: global soil information on your palm

NASA Astrophysics Data System (ADS)

Hengl, Tomislav; Mendes de Jesus, Jorge

2015-04-01

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

BOREAS TGB-12 Soil Carbon and Flux Data of NSA-MSA in Raster Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Knapp, David E. (Editor); Rapalee, Gloria; Davidson, Eric; Harden, Jennifer W.; Trumbore, Susan E.; Veldhuis, Hugo

2000-01-01

The BOREAS TGB-12 team made measurements of soil carbon inventories, carbon concentration in soil gases, and rates of soil respiration at several sites. This data set provides: (1) estimates of soil carbon stocks by horizon based on soil survey data and analyses of data from individual soil profiles; (2) estimates of soil carbon fluxes based on stocks, fire history, drain-age, and soil carbon inputs and decomposition constants based on field work using radiocarbon analyses; (3) fire history data estimating age ranges of time since last fire; and (4) a raster image and an associated soils table file from which area-weighted maps of soil carbon and fluxes and fire history may be generated. This data set was created from raster files, soil polygon data files, and detailed lab analysis of soils data that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. Also used were soils data from Susan Trumbore and Jennifer Harden (BOREAS TGB-12). The binary raster file covers a 733-km 2 area within the NSA-MSA.

SMAP Radiometer Captures Views of Global Soil Moisture

NASA Image and Video Library

2015-05-06

These maps of global soil moisture were created using data from the radiometer instrument on NASA Soil Moisture Active Passive SMAP observatory. Evident are regions of increased soil moisture and flooding during April, 2015.

High resolution regional soil carbon mapping in Madagascar : towards easy to update maps

NASA Astrophysics Data System (ADS)

Grinand, Clovis; Dessay, Nadine; Razafimbelo, Tantely; Razakamanarivo, Herintsitoaina; Albrecht, Alain; Vaudry, Romuald; Tiberghien, Matthieu; Rasamoelina, Maminiaina; Bernoux, Martial

2013-04-01

The soil organic carbon plays an important role in climate change regulation through carbon emissions and sequestration due to land use changes, notably tropical deforestation. Monitoring soil carbon emissions from shifting-cultivation requires to evaluate the amount of carbon stored at plot scale with a sufficient level of accuracy to be able to detect changes. The objective of this work was to map soil carbon stocks (30 cm and 100 cm depths) for different land use at regional scale using high resolution satellite dataset. The Andohahela National Parc and its surroundings (South-Est Madagascar) - a region with the largest deforestation rate in the country - was selected as a pilot area for the development of the methodology. A three steps approach was set up: (i) carbon inventory using mid infra-red spectroscopy and stock calculation, (ii) spatial data processing and (iii) modeling and mapping. Soil spectroscopy was successfully used for measuring organic carbon in this region. The results show that Random Forest was the inference model that produced the best estimates on calibration and validation datasets. By using a simple and robust method, we estimated uncertainty levels of of 35% and 43% for 30-cm and 100-cm carbon maps respectively. The approach developed in this study was based on open data and open source software that can be easily replicated to other regions and for other time periods using updated satellite images.

Distribution of heavy metals in agricultural soils near a petrochemical complex in Guangzhou, China.

PubMed

Li, Junhui; Lu, Ying; Yin, Wei; Gan, Haihua; Zhang, Chao; Deng, Xianglian; Lian, Jin

2009-06-01

The aim of the study was to investigate influence of an industrialized environment on the accumulation of heavy metals in agricultural soils. Seventy soil samples collected from surface layers (0-20 cm) and horizons of five selected pedons in the vicinity area of petrochemical complex in Guangzhou, China were analyzed for Zn, Cu, Pb, Cd, Hg and As concentrations, the horizontal and vertical variation of these metals were studied and geographic information system (GIS)-based mapping techniques were applied to generate spatial distribution maps. The mean concentrations of these heavy metals in the topsoils did not exceed the maximum allowable concentrations in agricultural soil of China with the exception of Hg. Significant differences between land-use types showed that Cu, Pb, Cd, Hg and As concentrations in topsoils were strongly influenced by agricultural practices and soil management. Within a radius of 1,300 m there were no marked decreasing trends for these element concentrations (except for Zn) with the increase of distance from the complex boundary, which reflected little influence of petroleum air emission on soil heavy metal accumulation. Concentrations of Zn, Cu, Pb, Cd, Hg and As in the five pedons, particularly in cultivated vegetable field and orchard, decreased with soil depth, indicating these elements mainly originated from anthropogenic sources. GIS mapping was a useful tool for evaluating spatial variability of heavy metals in the affected soil. The spatial distribution maps allowed the identification of hot-spot areas with high metal concentration. Effective measures should be taken to avoid or minimize heavy metal further contamination of soils and to remediate the contaminated areas in order to prevent pollutants affecting human health through agricultural products.

Mapping CO2 emission in highly urbanized region using standardized microbial respiration approach

NASA Astrophysics Data System (ADS)

Vasenev, V. I.; Stoorvogel, J. J.; Ananyeva, N. D.

2012-12-01

Urbanization is a major recent land-use change pathway. Land conversion to urban has a tremendous and still unclear effect on soil cover and functions. Urban soil can act as a carbon source, although its potential for CO2 emission is also very high. The main challenge in analysis and mapping soil organic carbon (SOC) in urban environment is its high spatial heterogeneity and temporal dynamics. The urban environment provides a number of specific features and processes that influence soil formation and functioning and results in a unique spatial variability of carbon stocks and fluxes at short distance. Soil sealing, functional zoning, settlement age and size are the predominant factors, distinguishing heterogeneity of urban soil carbon. The combination of these factors creates a great amount of contrast clusters with abrupt borders, which is very difficult to consider in regional assessment and mapping of SOC stocks and soil CO2 emission. Most of the existing approaches to measure CO2 emission in field conditions (eddy-covariance, soil chambers) are very sensitive to soil moisture and temperature conditions. They require long-term sampling set during the season in order to obtain relevant results. This makes them inapplicable for the analysis of CO2 emission spatial variability at the regional scale. Soil respiration (SR) measurement in standardized lab conditions enables to overcome this difficulty. SR is predominant outgoing carbon flux, including autotrophic respiration of plant roots and heterotrophic respiration of soil microorganisms. Microbiota is responsible for 50-80% of total soil carbon outflow. Microbial respiration (MR) approach provides an integral CO2 emission results, characterizing microbe CO2 production in optimal conditions and thus independent from initial difference in soil temperature and moisture. The current study aimed to combine digital soil mapping (DSM) techniques with standardized microbial respiration approach in order to analyse and map CO2 emission and its spatial variability in highly urbanized Moscow region. Moscow region with its variability of bioclimatic conditions and high urbanization level (10 % from the total area) was chosen as an interesting case study. Random soil sampling in different soil zones (4) and land-use types (3 non-urban and 3 urban) was organized in Moscow region in 2010-2011 (n=242). Both topsoil (0-10 cm) and subsoil (10-150 cm) were included. MR for each point was analysed using standardized microbial (basal) respiration approach, including the following stages: 1) air dried soil samples were moisturised up to 55% water content and preincubated (7 days, 22° C) in a plastic bag with air exchange; 2) soil MR (in μg CO2-C g-1) was measured as the rate of CO2 production (22° C, 24 h) after incubating 2g soil with 0.2 μl distilled water; 3) the MR results were used to estimate CO2 emission (kg C m-2 yr-1). Point MR and CO2 emission results obtained were extrapolated for the Moscow region area using regression model. As a result, two separate CO2 maps for topsoil and subsoil were created. High spatial variability was demonstrated especially for the urban areas. Thus standardized MR approach combined with DSM techniques provided a unique opportunity for spatial analysis of soil carbon temporal dynamics at the regional scale.

Soils of the Sylvania Wilderness-Recreation Area, western Upper Peninsula, Michigan.

Treesearch

James G. Bockheim; J.K. Jordan

2004-01-01

Characterizes 22 soil profiles in teh Sylvania Wilderness-Recreation Area on the Ottawa National Forest, including soil descriptions and laboratory data. A soil map at a scale of 1:24,000 is provided. The genesis of the soils is discussed.

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

30 CFR 779.21 - Soil resources information.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Soil resources information. 779.21 Section 779... § 779.21 Soil resources information. (a) The applicant shall provide adequate soil survey information of the permit area consisting of the following: (1) A map delineating different soils; (2) Soil...

Lots of legacy soil data are available, but which data do we need to collect for regional land use analysis?

NASA Astrophysics Data System (ADS)

Hendriks, Chantal; Stoorvogel, Jetse; Claessens, Lieven

2015-04-01

In the past, soil surveying techniques were mainly developed for qualitative regional land use analysis (RLUA) like land evaluation and land use planning. Conventional soil survey techniques usually describe soil types according to a soil classification scheme (e.g. Soil Taxonomy and World Reference Base). These soil surveys met the requirements of qualitative land evaluation and land use planning. However, during the last decades there is an increased need for quantitative RLUA resulting in an increased demand for quantitative soil data. The rapid developments in computing technology and the availability of auxiliary information (e.g. remote sensing and digital elevation models) allowed for the development of new soil surveying techniques like digital soil mapping. These new soil surveying techniques aim to produce continuous maps of quantitative functional soil properties. However, RLUA nowadays requires soil data that include a description of the spatial variability of the entire pedon in which correlations between soil properties are retained. Current surveying techniques do not fully fulfil these requirements resulting in a gap between the supply and demand of soil data in RLUA. The gap is caused by the fact that legacy soil data are collected for different purposes and inherently have different assumptions on e.g., soil variability. In this study, some of these assumptions are tested and verified using primary soil data collected during a recent field survey in Machakos and Makueni County (Kenya). Subsequently an ongoing RLUA, the Global Yield Gap Atlas (GYGA) project, is taken as a case study to evaluate the effect of different sources of soil data on the results of the RLUA. The results of the study show that various assumptions underlying the soil survey hamper the quality requirements of soil data for the specific objectives of the RLUA. To give a few examples: mapping soil properties individually ignores correlations between them, soil properties differed significantly between natural and agricultural land, discrete soil mapping units described by a representative soil profile showed internal variability. None of the legacy datasets fitted the requirements of the RLUA. However, resources to collect additional primary soil data are limited. Evaluating legacy data allows us to identify the soil data that we need to collect. Legacy data lack information on e.g. soil management and effective rooting depth, while these data are often required for RLUA. This results in the use of assumptions, estimations and simplifications in a RLUA. The choice of legacy data has a profound effect on the results of a RLUA. The GYGA case study shows for example that different sources of soil input data can lead to differences in simulated water-limited maize yields of up to 3 ton/ha.

Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Werban, Ulrike; Zacharias, Steffen; Pohle, Marco; Dietrich, Peter; Wollschläger, Ute

2017-01-01

Electromagnetic induction (EMI) measurements are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa). Although the use of non-invasive EMI for imaging spatial soil properties is very attractive, the dependence of ECa on several factors challenges any interpretation with respect to individual soil properties or states such as soil moisture (θ). The major aim of this study was to further investigate the potential of repeated EMI measurements to map θ, with particular focus on the temporal variability of the spatial patterns of ECa and θ. To this end, we compared repeated EMI measurements with high-resolution θ data from a wireless soil moisture and soil temperature monitoring network for an extensively managed hillslope area for which soil properties and θ dynamics are known. For the investigated site, (i) ECa showed small temporal variations whereas θ varied from very dry to almost saturation, (ii) temporal changes of the spatial pattern of ECa differed from those of the spatial pattern of θ, and (iii) the ECa-θ relationship varied with time. Results suggest that (i) depending upon site characteristics, stable soil properties can be the major control of ECa measured with EMI, and (ii) for soils with low clay content, the influence of θ on ECa may be confounded by changes of the electrical conductivity of the soil solution. Further, this study discusses the complex interplay between factors controlling ECa and θ, and the use of EMI-based ECa data with respect to hydrological applications.

Predicting risk of rill initiation in a sub-catchment of Lake Balaton, Hungary

NASA Astrophysics Data System (ADS)

Hausner, C.; Sisák, I.

2009-04-01

Rill erosion is an accelerated form of soil degradation. It removes much more soil and nutrients from the agricultural land than sheet erosion. Soils in the southern sub-watershed of Lake Balaton are especially prone to rill erosion and they contribute to siltation of ditches, to muddy floods and to eutrofication of the lake. The parent material in this region is mainly (sandy) loess and the soils are already moderately or strongly eroded thus, the low tolerance of loess against erosion determines erodibility. Identification of soils with high risk of rill erosion is crucial to plan mitigation measures. Soil erodibility has been investigated in this study in the catchment of Tetves stream. The USLE soil erodibility factor and soil slaking are widely accepted indicators for soil erosion. Both of them are published for all soil texture classes in handbooks of soil mapping. We have found that erodibility derived from our physical model has a close linear correlation with the product of the USLE soil erodibility factor and soil slaking grade thus, USLE could be directly used to assess parameters for physical based models. Rill erosion is highly probable if the product of KUSLE X slaking grade is above 2. Digital maps were produced to delineate soils with high potential for rill erosion. The basic data for the soil properties were drawn from the 1:10,000 soil map. Soil texture classes were used to assign KUSLE and slaking grade to the soil units. Beyond soil properties, other factors also influence rill formation: slope, surface cover, rainfall intensity. However, identifying soil properties, which make soils prone to rill erosion, is an important initial step for the reduction of diffuse agricultural loads to Lake Balaton. It might be the objective of River Basin Management Plans in the Water Framework Directive to prevent rill erosion and our study provides scientific evidence for targeting this policy.

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

PubMed Central

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

2016-01-01

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

Spatial distribution of soil radon as a tool to recognize active faulting on an active volcano: the example of Mt. Etna (Italy).

PubMed

Neri, Marco; Giammanco, Salvatore; Ferrera, Elisabetta; Patanè, Giuseppe; Zanon, Vittorio

2011-09-01

This study concerns measurements of radon and thoron emissions from soil carried out in 2004 on the eastern flank of Mt. Etna, in a zone characterized by the presence of numerous seismogenic and aseismic faults. The statistical treatment of the geochemical data allowed recognizing anomaly thresholds for both parameters and producing distribution maps that highlighted a significant spatial correlation between soil gas anomalies and tectonic lineaments. The seismic activity occurring in and around the study area during 2004 was analyzed, producing maps of hypocentral depth and released seismic energy. Both radon and thoron anomalies were located in areas affected by relatively deep (5-10 km depth) seismic activity, while less evident correlation was found between soil gas anomalies and the released seismic energy. This study confirms that mapping the distribution of radon and thoron in soil gas can reveal hidden faults buried by recent soil cover or faults that are not clearly visible at the surface. The correlation between soil gas data and earthquakes depth and intensity can give some hints on the source of gas and/or on fault dynamics. Copyright © 2011 Elsevier Ltd. All rights reserved.

Soils Diversity in the Southwest of Iberian Peninsula

NASA Astrophysics Data System (ADS)

Ramírez, Beatriz; Fernández-Pozo, Luis; Cabezas, José; Alexandre Castanho, Rui; Loures, Luís

2017-04-01

Back in 1960 the Seventh International Congress of Soil Science has proposed to develop a World Soil Mapping at a scale of 1: 1000000, with a purpose of getting a systematic inventory of soils, and also to allow a transfer of experiences between different countries and institutions. The mapping process has been coordinated by the European Soil Bureau (ESBN) and the European Commission, along with the participation of the European Environment Agency (EEA) and the Food and Agriculture Organization of the United Nations (FAO), based on the classification proposed by the "World Reference Base for Soil Resource" (WRB, FAO, 1998). Throughout this mapping and helped by the European Soil Database (v2.0), a mapping of soils and their diversity, in the area under analysis on the present paper - EUROACE (Alentejo-Centro-Extremadura) in the Southwest of Iberian Peninsula - has been developed and assessed using Geographic Information Systems (GIS) and algorithms of diversity. The obtained results have shown that in this particularly territory it is possible to identify 12 Reference Soil Groups (RSG) at first level, and 26 at second level, predominating Regosols and Dystrict Regosols respectively, whereas in the Mediterranean Region (Biogeographical Regions of Europe, BGRE) are 22 and 71 correspondingly with predominant for Cambisols and Calcaric Cambisols. By the analysis and assessment of soil diversity, the Shannon Index (H') is lower in EUROACE (1,67 vs 2,42 and 2,52 vs 3,35 to first and second levels); the evenness (E) shows a more equal distribution in RSG at first level in the Mediterranean Region (0,70 vs 0,67) and lower at the second level (0,67 vs 0,77 in EUROACE). These results will enable the development of a more complete pedodiversity inventory in several other regions, and also as tools to the study of soil susceptibility which will allow not only to protect a very important part of European natural heritage, but also to take specific measures to increase a better land use and management, which leads to sustainability.

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

NASA Astrophysics Data System (ADS)

Das, Sumanta; Choudhury, Malini Roy; Das, Subhasish; Nagarajan, M.

2016-12-01

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

Remote sensing for mapping soil moisture and drainage potential in semi-arid regions: Applications to the Campidano plain of Sardinia, Italy.

PubMed

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.

Mapping soil moisture across an irrigated field using electromagnetic conductivity imaging

USDA-ARS?s Scientific Manuscript database

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...

Mapping Soil Carbon in the Yukon Kuskokwim River Delta Alaska

NASA Astrophysics Data System (ADS)

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 <1% of the pan-Arctic watershed but containing >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 landcover class in our map, yielding a watershed-wide and spatially explicit map of soil carbon in the YK Delta. This map will provide the basis for understanding where carbon is stored in the watershed and the vulnerability of that carbon to climate change and fire.

Determining baselines and variability of elements in plants and soils near the Kenai National Wildlife Refuge, Alaska

USGS Publications Warehouse

Crock, J.G.; Severson, R.C.; Gough, L.P.

1992-01-01

Recent investigations on the Kenai Peninsula had two major objectives: (1) to establish elemental baseline concentrations ranges for native vegetation and soils; and, (2) to determine the sampling density required for preparing stable regional geochemical maps for various elements in native plants and soils. These objectives were accomplished using an unbalanced, nested analysis-of-variance (ANOVA) barbell sampling design. Hylocomium splendens (Hedw.) BSG (feather moss, whole plant), Picea glauca (Moench) Voss (white spruce, twigs and needles), and soil horizons (02 and C) were collected and analyzed for major and trace total element concentrations. Using geometric means and geometric deviations, expected baseline ranges for elements were calculated. Results of the ANOVA show that intensive soil or plant sampling is needed to reliably map the geochemistry of the area, due to large local variability. For example, producing reliable element maps of feather moss using a 50 km cell (at 95% probability) would require sampling densities of from 4 samples per cell for Al, Co, Fe, La, Li, and V, to more than 15 samples per cell for Cu, Pb, Se, and Zn.Recent investigations on the Kenai Peninsula had two major objectives: (1) to establish elemental baseline concentrations ranges for native vegetation and soils; and, (2) to determine the sampling density required for preparing stable regional geochemical maps for various elements in native plants and soils. These objectives were accomplished using an unbalanced, nested analysis-of-variance (ANOVA) barbell sampling design. Hylocomium splendens (Hedw.) BSG (feather moss, whole plant), Picea glauca (Moench) Voss (white spruce, twigs and needles), and soil horizons (02 and C) were collected and analyzed for major and trace total element concentrations. Using geometric means and geometric deviations, expected baseline ranges for elements were calculated. Results of the ANOVA show that intensive soil or plant sampling is needed to reliably map the geochemistry of the area, due to large local variability. For example, producing reliable element maps of feather moss using a 50 km cell (at 95% probability) would require sampling densities of from 4 samples per cell Al, Co, Fe, La, Li, and V, to more than 15 samples per cell for Cu, Pb, Se, and Zn.

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Cerda, Artemi; Strielko, Irina

2014-05-01

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

Predicting and quantifying soil processes using “geomorphon” landform Classification

USDA-ARS?s Scientific Manuscript database

Soil development and behavior vary spatially at multiple observation scales. Predicting and quantifying soil properties and processes via a catena integrates predictable landscape scale variation relevant to both management decisions and soil survey. Soil maps generally convey variation as a set of ...

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

NASA Astrophysics Data System (ADS)

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.

BOREAS TE-1 Soils Data Over The SSA Tower Sites in Raster Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Anderson, Darwin; Knapp, David E.

2000-01-01

The BOREAS TE-1 team collected various data to characterize the soil-plant systems in the BOREAS SSA. This data set was gridded from vector layers of soil maps that were received from Dr. Darwin Anderson (TE-1), who did the original soil mapping in the field during 1994. The vector layers were gridded into raster files that cover approximately 1 square kilometer over each of the tower sites in the SSA. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Mapping surface soil moisture with L-band radiometric measurements

NASA Technical Reports Server (NTRS)

Wang, James R.; Shiue, James C.; Schmugge, Thomas J.; Engman, Edwin T.

1989-01-01

A NASA C-130 airborne remote sensing aircraft was used to obtain four-beam pushbroom microwave radiometric measurements over two small Kansas tall-grass prairie region watersheds, during a dry-down period after heavy rainfall in May and June, 1987. While one of the watersheds had been burned 2 months before these measurements, the other had not been burned for over a year. Surface soil-moisture data were collected at the time of the aircraft measurements and correlated with the corresponding radiometric measurements, establishing a relationship for surface soil-moisture mapping. Radiometric sensitivity to soil moisture variation is higher in the burned than in the unburned watershed; surface soil moisture loss is also faster in the burned watershed.

Assessment of potential soil degradation on agricultural land in the czech republic.

PubMed

Šarapatka, Bořivoj; Bednář, Marek

2015-01-01

Many attempts have been made worldwide to develop methods to identify the areas most threatened by soil degradation. Some soils in afflicted areas may be irreversibly degraded and thus have very little resilience (the ability to restore themselves). For the purpose of assessing the current state of soil degradation in the Czech Republic (CZ) we have developed an overall indicator of land vulnerability to the threat of soil degradation on the basis of individual factors that contribute to soil degradation and are monitored on a long-term basis in various research worksites in the CZ. Individual degradation factors were divided into two groups: chemical and physical degradation. On the basis of principal component analysis, individual degradation factors were assigned a specific weight of influence. With the use of a GIS, the input factors of degradation were combined to create maps of chemical and physical soil degradation, and consequently a map of overall degradation-threatened soils for the CZ, along with a map of areas differentiated according to the prevailing type of degradation. Results showed that, at present, the most important degradation factor in the CZ is water erosion, followed by loss of organic matter. Statistical analysis showed that approximately 51% of agricultural land is moderately threatened in the CZ. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Assessing soil erosion risk using RUSLE through a GIS open source desktop and web application.

PubMed

Duarte, L; Teodoro, A C; Gonçalves, J A; Soares, D; Cunha, M

2016-06-01

Soil erosion is a serious environmental problem. An estimation of the expected soil loss by water-caused erosion can be calculated considering the Revised Universal Soil Loss Equation (RUSLE). Geographical Information Systems (GIS) provide different tools to create categorical maps of soil erosion risk which help to study the risk assessment of soil loss. The objective of this study was to develop a GIS open source application (in QGIS), using the RUSLE methodology for estimating erosion rate at the watershed scale (desktop application) and provide the same application via web access (web application). The applications developed allow one to generate all the maps necessary to evaluate the soil erosion risk. Several libraries and algorithms from SEXTANTE were used to develop these applications. These applications were tested in Montalegre municipality (Portugal). The maps involved in RUSLE method-soil erosivity factor, soil erodibility factor, topographic factor, cover management factor, and support practices-were created. The estimated mean value of the soil loss obtained was 220 ton km(-2) year(-1) ranged from 0.27 to 1283 ton km(-2) year(-1). The results indicated that most of the study area (80 %) is characterized by very low soil erosion level (<321 ton km(-2) year(-1)) and in 4 % of the studied area the soil erosion was higher than 962 ton km(-2) year(-1). It was also concluded that areas with high slope values and bare soil are related with high level of erosion and the higher the P and C values, the higher the soil erosion percentage. The RUSLE web and the desktop application are freely available.

Soil amplification maps for estimating earthquake ground motions in the Central US

USGS Publications Warehouse

Bauer, R.A.; Kiefer, J.; Hester, N.

2001-01-01

The State Geologists of the Central United States Earthquake Consortium (CUSEC) are developing maps to assist State and local emergency managers and community officials in evaluating the earthquake hazards for the CUSEC region. The state geological surveys have worked together to produce a series of maps that show seismic shaking potential for eleven 1 X 2 degree (scale 1:250 000 or 1 in. ??? 3.9 miles) quadrangles that cover the high-risk area of the New Madrid Seismic Zone in eight states. Shear wave velocity values for the surficial materials were gathered and used to classify the soils according to their potential to amplify earthquake ground motions. Geologic base maps of surficial materials or 3-D material maps, either existing or produced for this project, were used in conjunction with shear wave velocities to classify the soils for the upper 15-30 m. These maps are available in an electronic form suitable for inclusion in the federal emergency management agency's earthquake loss estimation program (HAZUS). ?? 2001 Elsevier Science B.V. All rights reserved.

The threat of soil salinity: A European scale review.

PubMed

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

2016-12-15

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

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

NASA Astrophysics Data System (ADS)

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 soil material as a result of tillage and erosion are fundamental for the estimation of soil loss in the studied test field (Royall 2001). The map of soil erosion shows maximum removal of soil material in the steepest parts of the testing localities. The magnetic method is very well suitable for mapping at the chernozem locality (Brumovice) and measurement of soil magnetic susceptibility is in this case a useful and fast technique for quantitative estimation of soil loss caused by erosion and tillage. However, it is less suitable (probably due to high terrain heterogeneity) for mapping in areas with luvisol as dominant soil unit. Acknowledgement: This study was supported by NAZV Agency of the Ministry of Agriculture of the Czech Republic through grant No QJ1230319. References : Royall, D. (2001). Use of mineral magnetic measurements to investigate soil erosion and sediment delivery in small agricultural catchment in limestone terrain. Catena, 46, 15-34. Kapicka, A., Dlouha, S., Grison, H., Jaksik, O., Kodesova, R., Petrovsky, E. (2013) Magnetism of soils applied for estimation of erosion at an agricultural land. Geophys Res Abstr Vol. 15, EGU2013 -4774.

Integrating depth functions and hyper-scale terrain analysis for 3D soil organic carbon modeling in agricultural fields at regional scale

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, L.; van Wesemael, B.; Stevens, A.; Doetterl, S.; Van Oost, K.; Behrens, T.; Schmidt, K.

2012-04-01

Soil Organic Carbon (SOC) represents a key component in the global C cycle and has an important influence on the global CO2 fluxes between terrestrial biosphere and atmosphere. In the context of agricultural landscapes, SOC inventories are important since soil management practices have a strong influence on CO2 fluxes and SOC stocks. However, there is lack of accurate and cost-effective methods for producing high spatial resolution of SOC information. In this respect, our work is focused on the development of a three dimensional modeling approach for SOC monitoring in agricultural fields. The study area comprises ~420 km2 and includes 4 of the 5 agro-geological regions of the Grand-Duchy of Luxembourg. The soil dataset consist of 172 profiles (1033 samples) which were not sampled specifically for this study. This dataset is a combination of profile samples collected in previous soil surveys and soil profiles sampled for other research purposes. The proposed strategy comprises two main steps. In the first step the SOC distribution within each profile (vertical distribution) is modeled. Depth functions for are fitted in order to summarize the information content in the profile. By using these functions the SOC can be interpolated at any depth within the profiles. The second step involves the use of contextual terrain (ConMap) features (Behrens et al., 2010). These features are based on the differences in elevation between a given point location in the landscape and its circular neighbourhoods at a given set of different radius. One of the main advantages of this approach is that it allows the integration of several spatial scales (eg. local and regional) for soil spatial analysis. In this work the ConMap features are derived from a digital elevation model of the area and are used as predictors for spatial modeling of the parameters of the depth functions fitted in the previous step. In this poster we present some preliminary results in which we analyze: i. The use of different depth functions, ii. The use of different machine learning approaches for modeling the parameters of the fitted depth functions using the ConMap features and iii. The influence of different spatial scales on the SOC profile distribution variability. Keywords: 3D modeling, Digital soil mapping, Depth functions, Terrain analysis. Reference Behrens, T., K. Schmidt, K., Zhu, A.X. Scholten, T. 2010. The ConMap approach for terrain-based digital soil mapping. European Journal of Soil Science, v. 61, p.133-143.

A method for testing land resource area concepts

USDA-ARS?s Scientific Manuscript database

Land Resource Units (LRUs) are defined by the National Soil Survey Handbook as aggregations of soil map units and subunits of Major Land Resource Areas (MLRAs). In the USDA NRCS Land Resource Hierarchy, LRUs are defined as the level between MLRAs and STATSGO and are mapped at 1:1 million scale. They...

Mapping pocket gopher burrow systems with expanding polyurethane foam

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

Felthauser, M.; McInroy, D.

The impetus for this study arose from the need to isolate buried chemical and radioactive waste from burrowing animals. In a study of barrier materials that inhibit burrowing by pocket gophers (Thomomys spp.) into waste material, it was necessary to map tunnel systems as a function of depth and soil type. A method of mapping burrow systems was needed that would be economical, portable, useful in a variety of soil types, and give accurate, permanent records of burrow configurations. A method is described for injecting an expanding polyurethane foam to map burrow systems in situ.

How well do we succeed in modeling the global soil carbon pools?

NASA Astrophysics Data System (ADS)

Viskari, T.; Liski, J.

2017-12-01

Terrestrial carbon pools are a crucial part of the global carbon cycle. Carbon from vegetation is deposited to the soil, which in turn releases carbon dioxide back to the atmosphere through heterotrophic respiration. The resulting soil carbon storage in the largest on land. While there are continuous efforts to improve the modeling of global soil carbon and how this storage is affected by climate change, this research requires still a more reliable baseline on how well the models estimate the current global soil carbon pools. Especially such comparisons are important for identifying the major challenges in the current soil carbon models. Here, we used the Yasso soil carbon model to create a global soil carbon map at a 0.5 degree resolution based on the available climate, land cover and vegetation productivity information. Yasso model describes the soil carbon cycling by pools that represent the breaking down of dead organic matter. We compared the model results to a measurement based projection of global soil carbon pools, and we examined the differences and spatial correlations between the two maps. In our findings, the modelled predictions captured the overall soil carbon distributions within 5 kgCm-2 on 63 % of the land area. The spatial distributions fit each other as well. The average soil carbon is smaller with the Yasso prediction ( 8.5 kg m-2) than with the measurement map ( 10 kg m-2) and there are notable areas, such as Siberia and Southern North America, where there are large differences between the model predictions and measurements. These results not only encourage future development of soil carbon models, but also highlight problem areas to focus and improve upon.

Approaches for improving field soil identification

USDA-ARS?s Scientific Manuscript database

Use of soil survey information by non-soil scientists is often limited by their inability to 6 select the correct soil map unit component (COMP). Here, we developed two approaches that 7 can be deployed to smartphones for non-soil scientists to identify COMP using location alone, or 8 location toget...

Advanced in-situ measurement of soil carbon content using inelastic neutron scattering

USDA-ARS?s Scientific Manuscript database

Measurement and mapping of natural and anthropogenic variations in soil carbon stores is a critical component of any soil resource evaluation process. Emerging modalities for soil carbon analysis in the field is the registration of gamma rays from soil under neutron irradiation. The inelastic neutro...

Mapping soil types from multispectral scanner data.

NASA Technical Reports Server (NTRS)

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

1971-01-01

Multispectral remote sensing and computer-implemented pattern recognition techniques were used for automatic ?mapping' of soil types. This approach involves subjective selection of a set of reference samples from a gray-level display of spectral variations which was generated by a computer. Each resolution element is then classified using a maximum likelihood ratio. Output is a computer printout on which the researcher assigns a different symbol to each class. Four soil test areas in Indiana were experimentally examined using this approach, and partially successful results were obtained.

Use of remote sensing techniques for inventorying and planning utilization of land resources in South Dakota

NASA Technical Reports Server (NTRS)

Myers, V. I.; Frazee, C. J.; Rusche, A. E.; Moore, D. G.; Nelson, G. D.; Westin, F. C.

1974-01-01

The basic procedures for interpreting remote sensing imagery to rapidly develop general soils and land use inventories were developed and utilized in Pennington County, South Dakota. These procedures and remote sensing data products were illustrated and explained to many user groups, some of whom are interested in obtaining similar data. The general soils data were integrated with land soils data supplied by the county director of equalization to prepare a land value map. A computer print-out of this map indicating a land value for each quarter section is being used in tax reappraisal of Pennington County. The land use data provided the land use planners with the present use of land in Pennington County. Additional uses of remote sensing applications are also discussed including tornado damage assessment, hail damage evaluation, and presentation of soil and land value information on base maps assembled from ERTS-1 imagery.

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

PubMed

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.

WOCAT mapping, GIS and the Góis municipality

NASA Astrophysics Data System (ADS)

Esteves, T. C. J.; Soares, J. A. A.; Ferreira, A. J. D.; Coelho, C. O. A.; Carreiras, M. A.; Lynden, G. V.

2012-04-01

In the scope of the goals of the association "The World Overview of Conservation Approaches and Technologies" (WOCAT), the established methodology intends to support the sustainable development of new techniques and the process of decision making in Sustainable Soil Management (SSM). Its main goal is to promote the co-existence with nature, in order to assure the wellbeing of upcoming generations. SSM is defined as the use of terrestrial resources, including soil, water, fauna, flora, for the production of goods that fulfill human needs, guaranteeing simultaneously a long-term productive potential for these resources, as well as the maintenance of their environmental functions. The EU-funded DESIRE (Desertification Mitigation & Remediation of Land: a global approach for local solutions) project is centered on SSM, having as a main goal the development and study of promising conservation, soil use and management strategies, therefore contributing for the protection of arid and semi-arid vulnerable areas. In Portugal, one of the main soil degradation and desertification agents are wildfires. There is consequently an urgent need to establish integrated conservation measures to reduce or prevent these occurrences. To do so, and for the DESIRE project, the WOCAT methodology was implemented, where it could be foreseen as 3 major questionnaires for: technologies (WOCAT Technologies), approaches (WOCAT Approaches) and mapping (WOCAT Mapping). The established methodology for WOCAT Mapping was created in order to attend the questions associated to the soil and water degradation, emphasizing the direct and socio-economic causes of this degradation. It evaluates what type of soil degradation is occurring, where, why and what actions are in practice in what respects to SSM. The association of this questionnaire to Geographical Information Systems (GIS) allows not only to produce maps, but also to calculate areas, taking into account several aspects of soil degradation and conservation. The map database and their outputs give a comprehensive and powerful tool to obtain a global vision of the degradation state of a given territory, at the desired local or regional scale. However for the selected study area, the Portuguese Góis Municipality, there was no base information prepared to be readily inserted in the geographical database. It was necessary to create the requested mapping units, so that the WOCAT Mapping questionnaire could be used.As a result, municipal cartography with 39 mapping units was obtained, and for each one, an exhaustive field work was made, allowing to characterize them in detail and answer the required information by WOCAT Mapping. These answers allowed creating a clearer image of what is happening in the territory in what respects to the used techniques, degradation degree and conservation measures applied. The all-important contact with the municipalities main stakeholders is an important aspect to refer, once they are the ones to help validate the obtained results for the WOCAT Mapping methodology, due to their extensive knowledge of the territory.

Spatial variability of soil carbon, pH, available phosphorous and potassium in organic farm located in Mediterranean Croatia

NASA Astrophysics Data System (ADS)

Bogunović, Igor; Pereira, Paulo; Šeput, Miranda

2016-04-01

Soil organic carbon (SOC), pH, available phosphorus (P), and potassium (K) are some of the most important factors to soil fertility. These soil parameters are highly variable in space and time, with implications to crop production. The aim of this work is study the spatial variability of SOC, pH, P and K in an organic farm located in river Rasa valley (Croatia). A regular grid (100 x 100 m) was designed and 182 samples were collected on Silty Clay Loam soil. P, K and SOC showed moderate heterogeneity with coefficient of variation (CV) of 21.6%, 32.8% and 51.9%, respectively. Soil pH record low spatial variability with CV of 1.5%. Soil pH, P and SOC did not follow normal distribution. Only after a Box-Cox transformation, data respected the normality requirements. Directional exponential models were the best fitted and used to describe spatial autocorrelation. Soil pH, P and SOC showed strong spatial dependence with nugget to sill ratio with 13.78%, 0.00% and 20.29%, respectively. Only K recorded moderate spatial dependence. Semivariogram ranges indicate that future sampling interval could be 150 - 200 m in order to reduce sampling costs. Fourteen different interpolation models for mapping soil properties were tested. The method with lowest Root Mean Square Error was the most appropriated to map the variable. The results showed that radial basis function models (Spline with Tension and Completely Regularized Spline) for P and K were the best predictors, while Thin Plate Spline and inverse distance weighting models were the least accurate. The best interpolator for pH and SOC was the local polynomial with the power of 1, while the least accurate were Thin Plate Spline. According to soil nutrient maps investigated area record very rich supply with K while P supply was insufficient on largest part of area. Soil pH maps showed mostly neutral reaction while individual parts of alkaline soil indicate the possibility of penetration of seawater and salt accumulation in the soil profile. Future research should focus on spatial patterns on soil pH, electrical conductivity and sodium adsorption ratio. Keywords: geostatistics, semivariogram, interpolation models, soil chemical properties

Transferability of multi- and hyperspectral optical biocrust indices

NASA Astrophysics Data System (ADS)

Rodríguez-Caballero, E.; Escribano, P.; Olehowski, C.; Chamizo, S.; Hill, J.; Cantón, Y.; Weber, B.

2017-04-01

Biological soil crusts (biocrusts) are communities of cyanobacteria, algae, microfungi, lichens and bryophytes in varying proportions, which live within or immediately on top of the uppermost millimeters of the soil in arid and semiarid regions. As biocrusts are highly relevant for ecosystem processes like carbon, nitrogen, and water cycling, a correct characterization of their spatial distribution is required. Following this objective, considerable efforts have been devoted to the identification and mapping of biocrusts using remote sensing data, and several mapping indices have been developed. However, their transferability to different regions has only rarely been tested. In this study we investigated the transferability of two multispectral indices, i.e. the Crust Index (CI) and the Biological Soil Crust Index (BSCI), and two hyperspectral indices, i.e. the Continuum Removal Crust Identification Algorithm (CRCIA) and the Crust Development Index (CDI), in three sites dominated by biocrusts, but with differences in soil and vegetation composition. Whereas multispectral indices have been important and valuable tools for first approaches to map and classify biological soil crusts, hyperspectral data and indices developed for these allowed to classify biocrusts at much higher accuracy. While multispectral indices showed Kappa (κ) values below 0.6, hyperspectral indices obtained good classification accuracy (κ ∼ 0.8) in both the study area where they had been developed and in the newly tested region. These results highlight the capability of hyperspectral sensors to identify specific absorption features related to photosynthetic pigments as chlorophyll and carotenoids, but also the limitation of multispectral information to discriminate between areas dominated by biocrusts, vegetation or bare soil. Based on these results we conclude that remote sensing offers an important and valid tool to map biocrusts. However, the spectral similarity between the main surface components of drylands and biocrusts demand for mapping indices based on hyperspectral information to correctly map areas dominated by biocrusts at ecosystem scale.

Studying of Forests Potentials for Introducing of Mediterranean Industrial Woody Species to Desertification Combating

NASA Astrophysics Data System (ADS)

Mahdavi Najafabadi, R.; Khajeddin, S. J.; Sofyanian, A. R.; Karimzadeh, H. R.; Rezaei, M.

2009-04-01

Most of arid and semiarid parts of the world suffer from great lack of forest land. Therefore taking a good care of these forest lands quantity and quality and control of renewable natural resources is very important. Zagroass forests are located in semiarid parts of Iran. The main purpose of this research is to determine the potential habitat of forest olive for Chaharmahal va Bakhtiary using GIS. This province has a total area of 1653300 hectars. The main steps of this project are as follows: collecting data and maps, digitizing topographic maps with scale of 1:25000, and developing maps of slope, elevation levels, aspect, climatic classification. Regretion analysis was performed on the climatic data and the gradian equations were developed with a high R2 value. Using these equations the following maps were developed. For the whole province: isothermal, isoheytal, abs. max isothermal, relative humidity relative humidity of dry months. Soil maps were also digitized and the information system suitable for this study was developed. Using this bank the following layers were made: land units, soil depth, two soil textures, EC, pH, CaCo3. The following layers were made using digitized data, land use hydraulic network, lake and marsh land. Considering ecological needs of olive and extracting them from all diferent layers using boolean method. The layers showing suitable locations for planting olive(olea europea) was made. One of these maps includes all types of soils suitable for planting olive and the other excludes silty clay loam soils which are not so suitable. The total area achived was 9500 hectars in the whole province and the area excluding silty clay loam soils was determined to be 900 hectars. Using RS information and GIS technology in these types of projects can increase accuracy specialy including some more layers is recommended.

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

PubMed

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

2009-04-01

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

Fate of 1-(1',4'-cyclohexadienyl)-2-methylaminopropane (CMP) in soil: route-specific by-product in the clandestine manufacture of methamphetamine.

PubMed

Pal, Raktim; Megharaj, Mallavarapu; Kirkbride, K Paul; Naidu, Ravi

2012-02-01

We investigated the fate of 1-(1',4'-cyclohexadienyl)-2-methylaminopropane (CMP) in soil. CMP is the major route-specific byproduct in the clandestine manufacture of methamphetamine (MAP) by the use of excess alkali metal (e.g., lithium) in liquid ammonia, which is commonly referred to as the "Nazi method". This is one of the most common methods used in many countries for the illicit production of MAP. Knowledge on the fate of CMP in the terrestrial environment is essential to combat potential threats arising from illegal dumping of clandestine laboratory wastes. We report on the sorption-desorption, degradation, and metabolism patterns of CMP in three South Australian soils investigated in laboratory scale. CMP sorption in the test soils followed a Freundlich isotherm in the concentration range of 5 to 100μgmL(-1). Degradation studies showed that CMP was fairly unstable in both non-sterile and sterile soils, with half-life values typically less than one week. The role of biotic and abiotic soil processes in the degradation of CMP also varied significantly between the different soils, and with the length of the incubation period. Interestingly, but not surprisingly, the results showed that the CMP was not actually degraded to any simpler compounds but transformed to more persistent MAP. Thus, the main concern with Nazi method is the potential hazard from MAP rather than CMP if wastes are disposed of into the environment. Copyright © 2011 Elsevier B.V. All rights reserved.

Fate of Zinc Oxide Nanoparticles Coated onto Macronutrient Fertilizers in an Alkaline Calcareous Soil

PubMed Central

Milani, Narges; Hettiarachchi, Ganga M.; Kirby, Jason K.; Beak, Douglas G.; Stacey, Samuel P.; McLaughlin, Mike J.

2015-01-01

Zinc oxide (ZnO) nanoparticles may provide a more soluble and plant available source of Zn in Zn fertilizers due to their greater reactivity compared to equivalent micron- or millimetre-sized (bulk) particles. However, the effect of soil on solubility, spatial distribution and speciation of ZnO nanoparticles has not yet been investigated. In this study, we examined the diffusion and solid phase speciation of Zn in an alkaline calcareous soil following application of nanoparticulate and bulk ZnO coated fertilizer products (monoammonium phosphate (MAP) and urea) using laboratory-based x-ray techniques and synchrotron-based μ-x-ray fluorescence (μ–XRF) mapping and absorption fine structure spectroscopy (μ–XAFS). Mapping of the soil-fertilizer reaction zones revealed that most of the applied Zn for all treatments remained on the coated fertilizer granule or close to the point of application after five weeks of incubation in soil. Zinc precipitated mainly as scholzite (CaZn2(PO4)2.2H2O) and zinc ammonium phosphate (Zn(NH4)PO4) species at the surface of MAP granules. These reactions reduced dissolution and diffusion of Zn from the MAP granules. Although Zn remained as zincite (ZnO) at the surface of urea granules, limited diffusion of Zn from ZnO-coated urea granules was also observed for both bulk and nanoparticulate ZnO treatments. This might be due to either the high pH of urea granules, which reduced solubility of Zn, or aggregation (due to high ionic strength) of released ZnO nanoparticles around the granule/point of application. The relative proportion of Zn(OH)2 and ZnCO3 species increased for all Zn treatments with increasing distance from coated MAP and urea granules in the calcareous soil. When coated on macronutrient fertilizers, Zn from ZnO nanoparticles (without surface modifiers) was not more mobile or diffusible compared to bulk forms of ZnO. The results also suggest that risk associated with the presence of ZnO NPs in calcareous soils would be the same as bulk sources of ZnO. PMID:25965385

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

Treesearch

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...

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

One of the main objectives of the EU's Common Agricultural Policy is to encourage maintaining agricultural production in Areas Facing Natural Constraints (ANC) in order to sustain agricultural production and use natural resources, in such a way to secure both stable production and income to farmers and to protect the environment. ANC assignment has both ecological and severe economical aspects. Recently the delimitation of ANCs is suggested to be carried out by using common biophysical diagnostic criteria on low soil productivity and poor climate conditions all over Europe. The criterion system was elaborated and has been repeatedly upgraded by JRC. The operational implementation is under member state competence. This process requires application of available soil databases and proper thematic and spatial inference methods. In our paper we present the inferences applied for the latest identification and delineation of areas with low soil productivity in Hungary according to JRC biophysical criteria related to soil: limited soil drainage, texture and stoniness (coarse texture, heavy clay, vertic properties), shallow rooting depth, chemical properties (salinity, sodicity, low pH). The compilation of target specific maps were based on the available legacy and recently collected data. In the present work three different data sources were used. The most relevant available data were queried from the datasets for each mapped criterion for either direct application or for the compilation a suitable, synthetic (non-measured) parameter. In some cases the values of the target variable originated from only one, in other cases from more databases. The reference dataset used in the mapping process was set up after substantial statistical analysis and filtering. It consisted of the values of the target variable attributed to the finally selected georeferenced locations. For spatial inference regression kriging was applied. Accuracy assessment was carried out by Leave One Out Cross Validation (LOOCV). In some cases the DSM product directly provided the delineation result by simple querying, in other cases further interpretation of the map was necessary. As the result of our work not only spatial fulfilment of the European biophysical criteria was assessed and provided for decision makers, but unique digital soil map products were elaborated regionalizing specific soil features, which were never mapped before, even nationally with 1 ha spatial resolution. Acknowledgement: Our work was supported by the "European Fund for Agricultural and Rural Development: Europe investing in rural areas" with the support of the European Union and Hungary and by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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 function. Spectra obtained near a sampled location were averaged. The collected spectra were correlated to TOC of the 15 representative samples using multivariate regression techniques (Unscrambler 9.7; Camo ASA, Oslo, Norway). Two types of calibrations were performed: using only spectra and using spectra together with the auxiliary data (EC-SH and EC-DP). These calibration equations were computed using PLS regression, segmented cross-validation method on centred data (using the raw spectral data, log 1/R). Six different spectra pre-treatments were conducted: (1) only spectra, (2) Savitsky-Golay smoothing over 11 wavelength points and transformation to a (3) 1'st and (4) 2'nd Savitzky and Golay derivative algorithm with a derivative interval of 21 wavelength points, (5) with or (6) without smoothing. The best treatment was considered to be the one with the lowest Root Mean Square Error of Prediction (RMSEP), the highest r2 between the VIS/NIR-predicted and measured values in the calibration model and the lowest mean deviation of predicted TOC values. The best calibration model was obtained with the mathematical pre-treatment's including smoothing, calculating the 2'nd derivative and outlier removal. The two TOC maps were compared after interpolation using kriging. They showed a similar pattern in the TOC distribution. Despite the unfavourable field conditions the VIS/NIR system performed well in both low and high TOC areas. Water content in places exceeding field capacity in the lower parts of the investigated field did not seriously degrade measurements. The present study represents the first attempt to apply the mobile Veris VIS/NIR system to the mapping of TOC of peat soils in Denmark. The result from this study show that a mobile VIS/NIR system can be applied to cost effective TOC mapping of mineral and organic soils with highly varying water content. Key words: VIS/NIR spectroscopy, organic soils, TOC

Predictor variable resolution governs modeled soil types

USDA-ARS?s Scientific Manuscript database

Soil mapping identifies different soil types by compressing a unique suite of spatial patterns and processes across multiple spatial scales. It can be quite difficult to quantify spatial patterns of soil properties with remotely sensed predictor variables. More specifically, matching the right scale...

Remote Sensing-based Models of Soil Vulnerability to Compaction and Erosion from Off-highway Vehicles

NASA Astrophysics Data System (ADS)

Villarreal, M. L.; Webb, R. H.; Norman, L.; Psillas, J.; Rosenberg, A.; Carmichael, S.; Petrakis, R.; Sparks, P.

2014-12-01

Intensive off-road vehicle use for immigration, smuggling, and security of the United States-Mexico border has prompted concerns about long-term human impacts on sensitive desert ecosystems. To help managers identify areas susceptible to soil erosion from vehicle disturbances, we developed a series of erosion potential models based on factors from the Revised Universal Soil Loss Equation (RUSLE), with particular focus on the management factor (P-factor) and vegetation cover (C-factor). To better express the vulnerability of soils to human disturbances, a soil compaction index (applied as the P-factor) was calculated as the difference in saturated hydrologic conductivity (Ks) between disturbed and undisturbed soils, which was then scaled up to remote sensing-based maps of vehicle tracks and digital soils maps. The C-factor was improved using a satellite-based vegetation index, which was better correlated with estimated ground cover (r2 = 0.77) than data derived from regional land cover maps (r2 = 0.06). RUSLE factors were normalized to give equal weight to all contributing factors, which provided more management-specific information on vulnerable areas where vehicle compaction of sensitive soils intersects with steep slopes and low vegetation cover. Resulting spatial data on vulnerability and erosion potential provide land managers with information to identify critically disturbed areas and potential restoration sites where off-road driving should be restricted to reduce further degradation.

Using Multispectral and Elevation Data to Predict Soil Properties for a Better Management of Fertilizers at Field Scale

NASA Astrophysics Data System (ADS)

Drouin, Ariane; Michaud, Aubert; Sylvain, Jean-Daniel; N'Dayegamiye, Adrien; Gasser, Marc-Olivier; Nolin, Michel; Perron, Isabelle; Grenon, Lucie; Beaudin, Isabelle; Desjardins, Jacques; Côté, Noémi

2013-04-01

This project aims at developing and validating an operational integrated management and localized approach at field scale using remote sensing data. It is realized in order to support the competitiveness of agricultural businesses, to ensure soil productivity in the long term and prevent diffuse contamination of surface waters. Our intention is to help agrienvironmental advisors and farmers in the consideration of spatial variability of soil properties in the management of fields. The proposed approach of soil properties recognition is based on the combination of elevation data and multispectral satellite imagery (Landsat) within statistical models. The method is based on the use of the largest possible number of satellite images to cover the widest range of soil moisture variability. Several spectral indices are calculated for each image (normalized brightness index, soil color index, organic matter index, etc.). The assignation of soils is based on a calibration procedure making use of the spatial soil database available in Canada. It includes soil profile point data associated to a database containing the information collected in the field. Three soil properties are predicted and mapped: A horizon texture, B horizon texture and drainage class. All the spectral indices, elevation data and soil data are combined in a discriminant analysis that produces discriminant functions. These are then used to produce maps of soil properties. In addition, from mapping soil properties, management zones are delineated within the field. The delineation of management zones with relatively similar soil properties is created to enable farmers to manage their fertilizers by taking greater account of their soils. This localized or precision management aims to adjust the application of fertilizer according to the real needs of soils and to reduce costs for farmers and the exports of nutrients to the stream. Mapping of soil properties will be validated in three agricultural regions in Quebec through an experimental field protocol (spatial sampling by management zones). Soils will be sampled, but crop yields under different nitrogen rates will also be assessed. Specifically, in each of the management areas defined, five different doses of nitrogen were applied (0, 50, 100, 150, 200 kg N / ha) on corn fields. In fall, the corn is harvested to assess differences in yields between the management areas and also in terms of doses of nitrogen. Ultimately, on the basis of well-established management areas, showing contrasting soil properties, the farmer will be able to ensure optimal correction of soil acidity, nitrogen fertilization, richness of soil in P and K, and improve soil drainage and physical properties. Environmentally, the principles of integrated and localized management carries significant benefits, particularly in terms of reduction of diffuse nutrient pollution.

Bolivian satellite technology program on ERTS natural resources

NASA Technical Reports Server (NTRS)

Brockmann, H. C. (Principal Investigator); Bartoluccic C., L.; Hoffer, R. M.; Levandowski, D. W.; Ugarte, I.; Valenzuela, R. R.; Urena E., M.; Oros, R.

1977-01-01

The author has identified the following significant results. Application of digital classification for mapping land use permitted the separation of units at more specific levels in less time. A correct classification of data in the computer has a positive effect on the accuracy of the final products. Land use unit comparison with types of soils as represented by the colors of the coded map showed a class relation. Soil types in relation to land cover and land use demonstrated that vegetation was a positive factor in soils classification. Groupings of image resolution elements (pixels) permit studies of land use at different levels, thereby forming parameters for the classification of soils.

Horizontal and vertical variability of soil properties in a trace element contaminated area

NASA Astrophysics Data System (ADS)

Burgos, Pilar; Madejón, Engracia; Pérez-de-Mora, Alfredo; Cabrera, Francisco

2008-02-01

The spatial distribution of some soil chemical properties and trace element contents of a plot affected by the Aznalcóllar mine spill were investigated using statistical and geostatistical methods to assess the extent of soil contamination. Total and EDTA-extractable soil trace element concentrations and total S content showed great variability and high coefficients of variation in the three examined depths. Soil in the plot was found to be significantly contaminated by As, Cd, Cu, Pb and Zn within a wide range of pH. Total trace element concentrations at all depths (0-60 cm) were much higher than background values of non-affected soil, indicating that despite the clean-up operations, the concentration of trace elements in the experimental plot was still high. The spatial distribution of the different variables was estimated by kriging to design contour maps. These maps allowed the identification of specific zones with high metal concentrations and low pH values corresponding to spots of residual sludge. Moreover, kriged maps showed distinct spatial distribution and hence different behaviour for the elements considered. This information may be applied to optimise remediation strategies in highly and moderately contaminated areas.

Modeling soil organic matter (SOM) from satellite data using VISNIR-SWIR spectroscopy and PLS regression with step-down variable selection algorithm: case study of Campos Amazonicos National Park savanna enclave, Brazil

NASA Astrophysics Data System (ADS)

Rosero-Vlasova, O.; Borini Alves, D.; Vlassova, L.; Perez-Cabello, F.; Montorio Lloveria, R.

2017-10-01

Deforestation in Amazon basin due, among other factors, to frequent wildfires demands continuous post-fire monitoring of soil and vegetation. Thus, the study posed two objectives: (1) evaluate the capacity of Visible - Near InfraRed - ShortWave InfraRed (VIS-NIR-SWIR) spectroscopy to estimate soil organic matter (SOM) in fire-affected soils, and (2) assess the feasibility of SOM mapping from satellite images. For this purpose, 30 soil samples (surface layer) were collected in 2016 in areas of grass and riparian vegetation of Campos Amazonicos National Park, Brazil, repeatedly affected by wildfires. Standard laboratory procedures were applied to determine SOM. Reflectance spectra of soils were obtained in controlled laboratory conditions using Fieldspec4 spectroradiometer (spectral range 350nm- 2500nm). Measured spectra were resampled to simulate reflectances for Landsat-8, Sentinel-2 and EnMap spectral bands, used as predictors in SOM models developed using Partial Least Squares regression and step-down variable selection algorithm (PLSR-SD). The best fit was achieved with models based on reflectances simulated for EnMap bands (R2=0.93; R2cv=0.82 and NMSE=0.07; NMSEcv=0.19). The model uses only 8 out of 244 predictors (bands) chosen by the step-down variable selection algorithm. The least reliable estimates (R2=0.55 and R2cv=0.40 and NMSE=0.43; NMSEcv=0.60) resulted from Landsat model, while Sentinel-2 model showed R2=0.68 and R2cv=0.63; NMSE=0.31 and NMSEcv=0.38. The results confirm high potential of VIS-NIR-SWIR spectroscopy for SOM estimation. Application of step-down produces sparser and better-fit models. Finally, SOM can be estimated with an acceptable accuracy (NMSE 0.35) from EnMap and Sentinel-2 data enabling mapping and analysis of impacts of repeated wildfires on soils in the study area.

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

PubMed Central

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

2015-01-01

80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. Over the period 2008–2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management—organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na). We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15–75% in Root Mean Squared Error (RMSE) across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols) help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring pedological knowledge from data rich countries to countries with limited soil data. PMID:26110833

Interpolation Approaches for Characterizing Spatial Variability of Soil Properties in Tuz Lake Basin of Turkey

NASA Astrophysics Data System (ADS)

Gorji, Taha; Sertel, Elif; Tanik, Aysegul

2017-12-01

Soil management is an essential concern in protecting soil properties, in enhancing appropriate soil quality for plant growth and agricultural productivity, and in preventing soil erosion. Soil scientists and decision makers require accurate and well-distributed spatially continuous soil data across a region for risk assessment and for effectively monitoring and managing soils. Recently, spatial interpolation approaches have been utilized in various disciplines including soil sciences for analysing, predicting and mapping distribution and surface modelling of environmental factors such as soil properties. The study area selected in this research is Tuz Lake Basin in Turkey bearing ecological and economic importance. Fertile soil plays a significant role in agricultural activities, which is one of the main industries having great impact on economy of the region. Loss of trees and bushes due to intense agricultural activities in some parts of the basin lead to soil erosion. Besides, soil salinization due to both human-induced activities and natural factors has exacerbated its condition regarding agricultural land development. This study aims to compare capability of Local Polynomial Interpolation (LPI) and Radial Basis Functions (RBF) as two interpolation methods for mapping spatial pattern of soil properties including organic matter, phosphorus, lime and boron. Both LPI and RBF methods demonstrated promising results for predicting lime, organic matter, phosphorous and boron. Soil samples collected in the field were used for interpolation analysis in which approximately 80% of data was used for interpolation modelling whereas the remaining for validation of the predicted results. Relationship between validation points and their corresponding estimated values in the same location is examined by conducting linear regression analysis. Eight prediction maps generated from two different interpolation methods for soil organic matter, phosphorus, lime and boron parameters were examined based on R2 and RMSE values. The outcomes indicate that RBF performance in predicting lime, organic matter and boron put forth better results than LPI. However, LPI shows better results for predicting phosphorus.

Drought monitoring with soil moisture active passive (SMAP) measurements

NASA Astrophysics Data System (ADS)

Mishra, Ashok; Vu, Tue; Veettil, Anoop Valiya; Entekhabi, Dara

2017-09-01

Recent launch of space-borne systems to estimate surface soil moisture may expand the capability to map soil moisture deficit and drought with global coverage. In this study, we use Soil Moisture Active Passive (SMAP) soil moisture geophysical retrieval products from passive L-band radiometer to evaluate its applicability to forming agricultural drought indices. Agricultural drought is quantified using the Soil Water Deficit Index (SWDI) based on SMAP and soil properties (field capacity and available water content) information. The soil properties are computed using pedo-transfer function with soil characteristics derived from Harmonized World Soil Database. The SMAP soil moisture product needs to be rescaled to be compatible with the soil parameters derived from the in situ stations. In most locations, the rescaled SMAP information captured the dynamics of in situ soil moisture well and shows the expected lag between accumulations of precipitation and delayed increased in surface soil moisture. However, the SMAP soil moisture itself does not reveal the drought information. Therefore, the SMAP based SWDI (SMAP_SWDI) was computed to improve agriculture drought monitoring by using the latest soil moisture retrieval satellite technology. The formulation of SWDI does not depend on longer data and it will overcome the limited (short) length of SMAP data for agricultural drought studies. The SMAP_SWDI is further compared with in situ Atmospheric Water Deficit (AWD) Index. The comparison shows close agreement between SMAP_SWDI and AWD in drought monitoring over Contiguous United States (CONUS), especially in terms of drought characteristics. The SMAP_SWDI was used to construct drought maps for CONUS and compared with well-known drought indices, such as, AWD, Palmer Z-Index, sc-PDSI and SPEI. Overall the SMAP_SWDI is an effective agricultural drought indicator and it provides continuity and introduces new spatial mapping capability for drought monitoring. As an agricultural drought index, SMAP_SWDI has potential to capture short term moisture information similar to AWD and related drought indices.

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

PubMed

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

2015-01-01

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

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

NASA Technical Reports Server (NTRS)

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.

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

Treesearch

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...

30 CFR 785.17 - Prime farmland.

Code of Federal Regulations, 2014 CFR

2014-07-01

... authority in consultation with the U.S. Soil Conservation Service shall determine the nature and extent of... a soil survey exists for those lands and whether soil mapping units in the permit area have been designated as prime farmland. If no soil survey exists, the applicant shall have a soil survey made of the...

30 CFR 785.17 - Prime farmland.

Code of Federal Regulations, 2011 CFR

2011-07-01

... authority in consultation with the U.S. Soil Conservation Service shall determine the nature and extent of... a soil survey exists for those lands and whether soil mapping units in the permit area have been designated as prime farmland. If no soil survey exists, the applicant shall have a soil survey made of the...

30 CFR 785.17 - Prime farmland.

Code of Federal Regulations, 2013 CFR

2013-07-01

... authority in consultation with the U.S. Soil Conservation Service shall determine the nature and extent of... a soil survey exists for those lands and whether soil mapping units in the permit area have been designated as prime farmland. If no soil survey exists, the applicant shall have a soil survey made of the...

30 CFR 785.17 - Prime farmland.

Code of Federal Regulations, 2012 CFR

2012-07-01

... authority in consultation with the U.S. Soil Conservation Service shall determine the nature and extent of... a soil survey exists for those lands and whether soil mapping units in the permit area have been designated as prime farmland. If no soil survey exists, the applicant shall have a soil survey made of the...

The use of soil electrical conductivity to investigate soil homogeneity in Story County, Iowa, USA

USDA-ARS?s Scientific Manuscript database

Precision agriculture, environmental applications, and land use planning needs have led to calls for more detailed soil maps. A remote sensing technique that can differentiate soils with a high degree of accuracy would be ideal for soil survey purposes. One technique that has shown promise in Iowa i...

Using electrical resistance tomography to map subsurface temperatures

DOEpatents

Ramirez, A.L.; Chesnut, D.A.; Daily, W.D.

1994-09-13

A method is provided for measuring subsurface soil or rock temperatures remotely using electrical resistivity tomography (ERT). Electrical resistivity measurements are made using electrodes implanted in boreholes driven into the soil and/or at the ground surface. The measurements are repeated as some process changes the temperatures of the soil mass/rock mass. Tomographs of electrical resistivity are calculated based on the measurements using Poisson's equation. Changes in the soil/rock resistivity can be related to changes in soil/rock temperatures when: (1) the electrical conductivity of the fluid trapped in the soil's pore space is low, (2) the soil/rock has a high cation exchange capacity and (3) the temperature changes are sufficiently high. When these three conditions exist the resistivity changes observed in the ERT tomographs can be directly attributed to changes in soil/rock temperatures. This method provides a way of mapping temperature changes in subsurface soils remotely. Distances over which the ERT method can be used to monitor changes in soil temperature range from tens to hundreds of meters from the electrode locations. 1 fig.

Using electrical resistance tomography to map subsurface temperatures

DOEpatents

Ramirez, Abelardo L.; Chesnut, Dwayne A.; Daily, William D.

1994-01-01

A method is provided for measuring subsurface soil or rock temperatures remotely using electrical resistivity tomography (ERT). Electrical resistivity measurements are made using electrodes implanted in boreholes driven into the soil and/or at the ground surface. The measurements are repeated as some process changes the temperatures of the soil mass/rock mass. Tomographs of electrical resistivity are calculated based on the measurements using Poisson's equation. Changes in the soil/rock resistivity can be related to changes in soil/rock temperatures when: (1) the electrical conductivity of the fluid trapped in the soil's pore space is low, (2) the soil/rock has a high cation exchange capacity and (3) the temperature changes are sufficiently high. When these three conditions exist the resistivity changes observed in the ERT tomographs can be directly attributed to changes in soil/rock temperatures. This method provides a way of mapping temperature changes in subsurface soils remotely. Distances over which the ERT method can be used to monitor changes in soil temperature range from tens to hundreds of meters from the electrode locations.

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

NASA Astrophysics Data System (ADS)

Orlicki, Katharine M.

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

The magnetic susceptibility of soils in Krakow, southern Poland

NASA Astrophysics Data System (ADS)

Wojas, Anna

2017-06-01

Studies into the magnetic susceptibility have been used to assess the soils contamination in the Krakow area. The results of topsoil (over a 2 × 2 km grid), subsoil (37 shallow holes) and soil samples (112) measurements were presented as maps of soil magnetic susceptibility (both volume and mass) illustrating the distribution of parameters in topsoil horizon (0-10 cm) and differential magnetic susceptibility maps between topsoil horizon and subsoil (40-60 cm). All evidence leads to the finding that the highest values of magnetic susceptibility of soil are found exclusively in industrial areas. Taking into consideration the type of land use, the high median value (89.8 × 10-8 m3kg-1) was obtained for samples of cultivated soils and is likely to be connected with occurrence of fertile soil (chernozem). Moreover, enrichment of soils with Pb and Zn accompanies magnetic susceptibility anomalies in the vicinity of the high roads and in the steelworks area, respectively.

Chemical-biogeographic survey of secondary metabolism in soil.

PubMed

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

2014-03-11

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed

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.

Ethiopia Schistosomiasis and Soil-Transmitted Helminthes Control Programme: Progress and Prospects.

PubMed

Negussu, Nebiyu; Mengistu, Birhan; Kebede, Biruck; Deribe, Kebede; Ejigu, Ephrem; Tadesse, Gemechu; Mekete, Kalkidan; Sileshi, Mesfin

2017-01-01

Schistosomiasis and soil-transmitted helminthes are among seventeen WHO prioritized neglected tropical diseases that infect humans. These parasitic infections can be treated using single-dose and safe drugs. Ethiopia successfully mapped the distribution of these infections nationwide. According to the mapping there are an estimated 37.3 million people living in schistosomiasis endemic areas, and 79 million in schistosomiasis and soil-transmitted helminthes endemic areas. The Federal Ministry of Health successfully scaled up Schistosomiasis and schistosomiasis and soil-transmitted helminthes intervention in endemic areas and treated over 19 million individuals in 2015. The Ministry of Health has made a huge effort to establish neglected tropical diseases, including schistosomiasis and soil-transmitted helminthes program in the health system which helped to map majority of the woredas and initiate nationwide intervention. The National control programme is designed to achieve elimination for those diseases as a major public health problem by 2020 and aim to attain transmission break by 2025. The programme focuses on reaching those school-aged children who are not attending school, integration between neglected tropical diseases programme, and further collaboration with the WASH actors.

Near Surface Investigation of Agricultural Soils using a Multi-Frequency Electromagnetic Sensor

NASA Astrophysics Data System (ADS)

Sadatcharam, K.; Unc, A.; Krishnapillai, M.; Cheema, M.; Galagedara, L.

2017-12-01

Electromagnetic induction (EMI) sensors have been used as precision agricultural tools over decades. They are being used to measure spatiotemporal variability of soil properties and soil stratification in the sense of apparent electrical conductivity (ECa). We mapped the ECa variability by horizontal coplanar (HCP) and by vertical coplanar (VCP) orientation of a multi-frequency EMI sensor and identified its interrelation with physical properties of soil. A broadband, multi-frequency handheld EMI sensor (GEM-2) was used on a loamy sand soil cultivated with silage-corn in western Newfoundland, Canada. Log and line spaced, three frequency ranges (weak, low, and high), based on the factory calibration were tested using HCP and VCP orientation to produce spatiotemporal data of ECa. In parallel, we acquired data on soil moisture content, texture and bulk density. We then assessed the statistical significance of the relationship between ECa and soil physical properties. The test site had three areas of distinct soil properties corresponding to the elevation, in particular. The same spatial variability was also identified by ECa mapping at different frequencies and the two modes of coil orientations. Data analysis suggested that the high range frequency (38 kHz (log-spaced) and 49 kHz (line-spaced)) for both HCP and VCP orientations produced accurate ECa maps, better than the weak and low range frequencies tested. Furthermore, results revealed that the combined effects of soil texture, moisture content and bulk density affect ECameasurements as obtained by both frequencies and two coil orientations. Keywords: Apparent electrical conductivity, Electromagnetic induction, Horizontal coplanar, Soil properties, Vertical coplanar

Extent and drainage status of organic soils in the Lake Victoria catchment

NASA Astrophysics Data System (ADS)

Barthelmes, Reni; Barthelmes, Alexandra; Joosten, Hans

2016-04-01

When considering peatlands and organic soils in the tropics, the huge areas in SE Asia prevail in public and scientific perception, whereas Africa has largely been out of focus. However, East Africa contains large areas of organic soils as well. They basically occur in the high altitudes of the uplifted flanks of the East African Rift System, isolated volcanoes and the Ethiopian highlands, in the Zambezian floodplains (e.g. Zambia), and in coastal environments (e.g. Mozambique and Madagascar). We used a mapping approach that integrates old field data and maps, specialized landscape and peatland-related knowledge, and modern RS and GIS techniques to elaborate a comprehensive and rather reliable overview of organic soils (incl. peatlands) in the Lake Victoria catchment. Maps at a scale of 1:25,000 have been prepared for Burundi, Kenya, Rwanda, Tanzania and Uganda. The land use intensity has been estimated for all organic soil areas based on satellite and aerial imagery. Feeding the Nile River, sustaining a fast growing and widely poor population and already facing climatic changes, organic soils of the Lake Victoria neighbouring countries are partially under heavy threat. We mapped 10,645 km2 of organic soils for the entire area of which 8,860 km2 (83.2%) seem to be in near natural condition. We assume slightly drainage and low degradation for 564 km2 (5.3%) and intensive drainage and heavy degradation for 1,222 km2 (11.5%). Degradation hotspot is Burundi with 522 km2 (79.5%) of heavily drained and degrading organic soils. This area assessment has been quite conservative to not overestimate the extent of organic soils. A reserve of 5-7,000 km2 of wetlands in the Lake Victoria catchment may include peatlands too, which needs to be confirmed in field surveys. Considering the key role of peatlands and organic soils for water provision and regulation and their rapid degradation due to drainage and inappropriate use, this inventory might be a step towards organic soil protection, and the development (or rediscovery) of sustainable land use options for undrained or future rewetted areas.

Iron content of soils as a precipitation proxy

NASA Astrophysics Data System (ADS)

Dzombak, R.; Sheldon, N. D.

2016-12-01

Given that different iron phases form under different precipitation and drainage regimes, soil iron content could be used as a proxy for both volume and seasonality of precipitation. Constraining these factors is important for predicting future precipitation trends, especially for a warmer climate that will likely see more frequent extreme weather events. Specifically, using paleoprecipitation data from periods of higher temperatures and atmospheric CO2 concentrations helps inform models of future `greenhouse' climate. Forty-five modern samples from across the continental United States were analyzed, with MAP ranging from 200 to 1200 mm yr-1 and MAT ranging from 5 to 22°C. Soil types included Alfisols (N=15), Inceptisols (N=8), Mollisols (N=15), and Aridisols (N=7), and ranged from seasonally wet to well-drained. Analytical techniques included combustion-elemental analysis and organic carbon isotope analysis, a sequential iron extraction modified with a sodium hypochlorite step for the extraction of organic matter-bound iron, and the extraction of iron sulfides. The sequential extractions yield five different `pools' of iron found in sediment: crystalline iron oxides (e.g., goethite, hematite), magnetite, carbonate-bound, organic matter-bound, and labile/easily reducible iron minerals (e.g., ferrihydrite). Analysis by ICP-OES yielded a strong relationship between magnetite-bound iron and MAP, and fair relationships between the other iron pools and MAP. Individual soil orders tended to show stronger relationships to the iron pools than all soils analyzed together, potentially indicating the need for separate proxy relationships for each soil order. Pyrite concentrations were well below 1% by weight for these soils, suggesting that none of these soils has a long enough wet season to encourage its formation and that the presence vs. absence of pyrite in paleosols may be a useful proxy for soil moisture state. In contrast to some earlier work, no significant relationship was found between A horizon δ13C and MAP, but one may emerge as the size of the dataset increases. Ongoing work will include a wider selection of modern soils, increasing the range of both precipitation and temperature, the number of soil orders, and the degree of drainage.

Convergence of soil nitrogen isotopes across global climate gradients

USGS Publications Warehouse

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.

Convergence of soil nitrogen isotopes across global climate gradients.

PubMed

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

2015-02-06

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 δ(15)N 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 δ(15)N 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.

Assessing the pollution risk of soil Chromium based on loading capacity of paddy soil at a regional scale

PubMed Central

Qu, Mingkai; Li, Weidong; Zhang, Chuanrong; Huang, Biao; Zhao, Yongcun

2015-01-01

The accumulation of a trace metal in rice grain is not only affected by the total concentration of the soil trace metal, but also by crop variety and related soil properties, such as soil pH, soil organic matter (SOM) and so on. However, these factors were seldom considered in previous studies on mapping the pollution risk of trace metals in paddy soil at a regional scale. In this study, the spatial nonstationary relationships between rice-Cr and a set of perceived soil properties (soil-Cr, soil pH and SOM) were explored using geographically weighted regression; and the relationships were then used for calculating the critical threshold (CT) of soil-Cr concentration that may ensure the concentration of rice-Cr being below the permissible limit. The concept of “loading capacity” (LC) for Cr in paddy soil was then defined as the difference between the CT and the real concentration of Cr in paddy soil, so as to map the pollution risk of soil-Cr to rice grain and assess the risk areas in Jiaxing city, China. Compared with the information of the concentration of the total soil-Cr, such results are more valuable for spatial decision making in reducing the accumulation of rice-Cr at a regional scale. PMID:26675587

Assessing the pollution risk of soil Chromium based on loading capacity of paddy soil at a regional scale.

PubMed

Qu, Mingkai; Li, Weidong; Zhang, Chuanrong; Huang, Biao; Zhao, Yongcun

2015-12-17

The accumulation of a trace metal in rice grain is not only affected by the total concentration of the soil trace metal, but also by crop variety and related soil properties, such as soil pH, soil organic matter (SOM) and so on. However, these factors were seldom considered in previous studies on mapping the pollution risk of trace metals in paddy soil at a regional scale. In this study, the spatial nonstationary relationships between rice-Cr and a set of perceived soil properties (soil-Cr, soil pH and SOM) were explored using geographically weighted regression; and the relationships were then used for calculating the critical threshold (CT) of soil-Cr concentration that may ensure the concentration of rice-Cr being below the permissible limit. The concept of "loading capacity" (LC) for Cr in paddy soil was then defined as the difference between the CT and the real concentration of Cr in paddy soil, so as to map the pollution risk of soil-Cr to rice grain and assess the risk areas in Jiaxing city, China. Compared with the information of the concentration of the total soil-Cr, such results are more valuable for spatial decision making in reducing the accumulation of rice-Cr at a regional scale.

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).

NASA Astrophysics Data System (ADS)

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).

Loess Thickness Variations Across the Loess Plateau of China

NASA Astrophysics Data System (ADS)

Zhu, Yuanjun; Jia, Xiaoxu; Shao, Mingan

2018-07-01

The soil thickness is very important for investigating and modeling soil-water processes, especially on the Loess Plateau of China with its deep loess deposit and limited water resources. A digital elevation map (DEM) of the Loess Plateau and neighborhood analysis in ArcGIS software were used to generate a map of loess thickness, which was then validated by 162 observations across the plateau. The generated loess thickness map has a high resolution of 100 m × 100 m. The map indicates that loess is thick in the central part of the plateau and becomes gradually shallower in the southeast and northwest directions. The areas near mountains and river basins have the shallowest loess deposit. The mean loess thickness is the deepest in the zones with 400-600-mm precipitation and decreases gradually as precipitation varies beyond this range. Our validation indicates that the map just slightly overestimates loess thickness and is reliable. The loess thickness is mostly between 0 and 350 m in the Loess Plateau region. The calculated mean loess thickness is 105.7 m, with the calibrated value being 92.2 m over the plateau exclusive of the mountain areas. Our findings provide very basic data of loess thickness and demonstrate great progress in mapping the loess thickness distribution for the plateau, which are valuable for a better study of soil-water processes and for more accurate estimations of soil water, carbon, and solute reservoirs in the Loess Plateau of China.

Loess Thickness Variations Across the Loess Plateau of China

NASA Astrophysics Data System (ADS)

Zhu, Yuanjun; Jia, Xiaoxu; Shao, Mingan

2018-01-01

The soil thickness is very important for investigating and modeling soil-water processes, especially on the Loess Plateau of China with its deep loess deposit and limited water resources. A digital elevation map (DEM) of the Loess Plateau and neighborhood analysis in ArcGIS software were used to generate a map of loess thickness, which was then validated by 162 observations across the plateau. The generated loess thickness map has a high resolution of 100 m × 100 m. The map indicates that loess is thick in the central part of the plateau and becomes gradually shallower in the southeast and northwest directions. The areas near mountains and river basins have the shallowest loess deposit. The mean loess thickness is the deepest in the zones with 400-600-mm precipitation and decreases gradually as precipitation varies beyond this range. Our validation indicates that the map just slightly overestimates loess thickness and is reliable. The loess thickness is mostly between 0 and 350 m in the Loess Plateau region. The calculated mean loess thickness is 105.7 m, with the calibrated value being 92.2 m over the plateau exclusive of the mountain areas. Our findings provide very basic data of loess thickness and demonstrate great progress in mapping the loess thickness distribution for the plateau, which are valuable for a better study of soil-water processes and for more accurate estimations of soil water, carbon, and solute reservoirs in the Loess Plateau of China.

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

NASA Astrophysics Data System (ADS)

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.

Application of spatial pedotransfer functions to understand soil modulation of vegetation response to climate

USDA-ARS?s Scientific Manuscript database

A fundamental knowledge gap in understanding land-atmosphere interactions is accurate, high resolution spatial representation of soil physical and hydraulic properties. We present a novel approach to predict hydraulic soil parameters by combining digital soil mapping techniques with pedotransfer fun...

Using geophysical images of a watershed subsurface to predict soil textural properties

USDA-ARS?s Scientific Manuscript database

Subsurface architecture, in particular changes in soil type across the landscape, is an important control on the hydrological and ecological function of a watershed. Traditional methods of mapping soils involving subjective assignment of soil boundaries are inadequate for studies requiring a quantit...

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Geostatistical interpolation of available copper in orchard soil as influenced by planting duration.

PubMed

Fu, Chuancheng; Zhang, Haibo; Tu, Chen; Li, Lianzhen; Luo, Yongming

2018-01-01

Mapping the spatial distribution of available copper (A-Cu) in orchard soils is important in agriculture and environmental management. However, data on the distribution of A-Cu in orchard soils is usually highly variable and severely skewed due to the continuous input of fungicides. In this study, ordinary kriging combined with planting duration (OK_PD) is proposed as a method for improving the interpolation of soil A-Cu. Four normal distribution transformation methods, namely, the Box-Cox, Johnson, rank order, and normal score methods, were utilized prior to interpolation. A total of 317 soil samples were collected in the orchards of the Northeast Jiaodong Peninsula. Moreover, 1472 orchards were investigated to obtain a map of planting duration using Voronoi tessellations. The soil A-Cu content ranged from 0.09 to 106.05 with a mean of 18.10 mg kg -1 , reflecting the high availability of Cu in the soils. Soil A-Cu concentrations exhibited a moderate spatial dependency and increased significantly with increasing planting duration. All the normal transformation methods successfully decreased the skewness and kurtosis of the soil A-Cu and the associated residuals, and also computed more robust variograms. OK_PD could generate better spatial prediction accuracy than ordinary kriging (OK) for all transformation methods tested, and it also provided a more detailed map of soil A-Cu. Normal score transformation produced satisfactory accuracy and showed an advantage in ameliorating smoothing effect derived from the interpolation methods. Thus, normal score transformation prior to kriging combined with planting duration (NSOK_PD) is recommended for the interpolation of soil A-Cu in this area.

Mapping polycyclic aromatic hydrocarbon and total toxicity equivalent soil concentrations by visible and near-infrared spectroscopy.

PubMed

Okparanma, Reuben N; Coulon, Frederic; Mayr, Thomas; Mouazen, Abdul M

2014-09-01

In this study, we used data from spectroscopic models based on visible and near-infrared (vis-NIR; 350-2500 nm) diffuse reflectance spectroscopy to develop soil maps of polycyclic aromatic hydrocarbons (PAHs) and total toxicity equivalent concentrations (TTEC) of the PAH mixture. The TTEC maps were then used for hazard assessment of three petroleum release sites in the Niger Delta province of Nigeria (5.317°N, 6.467°E). As the paired t-test revealed, there were non-significant (p > 0.05) differences between soil maps of PAH and TTEC developed with chemically measured and vis-NIR-predicted data. Comparison maps of PAH showed a slight to moderate agreement between measured and predicted data (Kappa coefficient = 0.19-0.56). Using proposed generic assessment criteria, hazard assessment showed that the degree of action for site-specific risk assessment and/or remediation is similar for both measurement methods. This demonstrates that the vis-NIR method may be useful for monitoring hydrocarbon contamination in a petroleum release site. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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 tools. Results of model fitting using the R packages nnet, randomForest and the h2o software (machine learning functions) show that significant models can be fitted for soil classes, bulk density (R-square 0.76), soil organic carbon (R-square 0.62) and coarse fragments (R-square 0.59). Consequently, we were able to estimate soil organic carbon stock for majority of the land mask (excluding permanent ice) and detect patches of landscape containing mainly organic soils (peat and similar). Our results confirm that hotspots of soil organic carbon in Tropics are peatlands in Indonesia, north of Peru, west Amazon and Congo river basin. Majority of world soil organic carbon stock is likely in the Northern latitudes (tundra and taiga of the north). Distribution of histosols seems to be mainly controlled by climatic conditions (especially temperature regime and water vapor) and hydrologic position in the landscape. Predicted distributions of organic soils (probability of occurrence) and total soil organic carbon stock at resolutions of 1 km and 250 m are available via the SoilGrids.org project homepage.

The soil moisture active passive experiments (SMAPEx): Towards soil moisture retrieval from the SMAP mission

USDA-ARS?s Scientific Manuscript database

NASA’s Soil Moisture Active Passive (SMAP) mission, scheduled for launch in 2014, will carry the first combined L-band radar and radiometer system with the objective of mapping near surface soil moisture and freeze/thaw state globally at near-daily time step (2-3 days). SMAP will provide three soil ...

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

PubMed

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

2014-01-01

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

Towards decadal soil salinity mapping using Landsat time series data

NASA Astrophysics Data System (ADS)

Fan, Xingwang; Weng, Yongling; Tao, Jinmei

2016-10-01

Salinization is one of the major soil problems around the world. However, decadal variation in soil salinization has not yet been extensively reported. This study exploited thirty years (1985-2015) of Landsat sensor data, including Landsat-4/5 TM (Thematic Mapper), Landsat-7 ETM+ (Enhanced Thematic Mapper Plus) and Landsat-8 OLI (Operational Land Imager), for monitoring soil salinity of the Yellow River Delta, China. The data were initially corrected for atmospheric effects, and then matched the spectral bands of EO-1 (Earth Observing One) ALI (Advanced Land Imager). Subsequently, soil salinity maps were derived with a previously developed PLSR (Partial Least Square Regression) model. On intra-annual scale, the retrievals showed that soil salinity increased in February, stabilized in March, and decreased in April. On inter-annual scale, soil salinity decreased within 1985-2000 (-0.74 g kg-1/10a, p < 0.001), and increased within 2000-2015 (0.79 g kg-1/10a, p < 0.001). Our study presents a new perspective for use of multiple Landsat data in soil salinity retrieval, and further the understanding of soil salinization development over the Yellow River Delta.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Definition of spectrally separable classes for soil survey research

NASA Technical Reports Server (NTRS)

Cipra, J. E.; Swain, P. H.; Gill, J. H.; Baumgardner, M. F.; Kristof, S. J.

1972-01-01

A procedure is outlined for defining spectral classes such that the differences between classes can be quantified. It also facilitates determination of a number of classes such that the classes are spectrally discriminable. This is accomplished by partitioning the data into many classes and then combining similar spectral classes on the basis of appropriate criteria. Multispectral data were collected over a 12-mile flightline in White County, Indiana, in connection with the 1971 Corn Blight Watch Experiment. Data were collected in May by the University of Michigan airborne scanning spectrometer at an altitude of 5000 feet. Spectral maps resulting from the analysis were compared to existing soil surveys of the National Cooperative Soil Survey. The method should help determine the extent to which spectral properties of soil surfaces can be associated with morphologic and topographic differences of interest to soil surveyors engaged in operational soil mapping.

FOREST SOIL INFORMATION FOR ENVIRONMENTAL ASSESSMENT IN THE WESTERN OREGON CASCADES BASED ON LANDTYPE MAPPING

EPA Science Inventory

Forest health monitoring and other environmental assessments require information on the spatial distribution of basic soil physical and chemical properties. Traditional soil surveys are not available for large areas of forestland in the western US but there are some soil resour...

Digital soil classification and elemental mapping using imaging Vis-NIR spectroscopy: How to explicitly quantify stagnic properties of a Luvisol under Norway spruce

NASA Astrophysics Data System (ADS)

Kriegs, Stefanie; Buddenbaum, Henning; Rogge, Derek; Steffens, Markus

2015-04-01

Laboratory imaging Vis-NIR spectroscopy of soil profiles is a novel technique in soil science that can determine quantity and quality of various chemical soil properties with a hitherto unreached spatial resolution in undisturbed soil profiles. We have applied this technique to soil cores in order to get quantitative proof of redoximorphic processes under two different tree species and to proof tree-soil interactions at microscale. Due to the imaging capabilities of Vis-NIR spectroscopy a spatially explicit understanding of soil processes and properties can be achieved. Spatial heterogeneity of the soil profile can be taken into account. We took six 30 cm long rectangular soil columns of adjacent Luvisols derived from quaternary aeolian sediments (Loess) in a forest soil near Freising/Bavaria using stainless steel boxes (100×100×300 mm). Three profiles were sampled under Norway spruce and three under European beech. A hyperspectral camera (VNIR, 400-1000 nm in 160 spectral bands) with spatial resolution of 63×63 µm² per pixel was used for data acquisition. Reference samples were taken at representative spots and analysed for organic carbon (OC) quantity and quality with a CN elemental analyser and for iron oxides (Fe) content using dithionite extraction followed by ICP-OES measurement. We compared two supervised classification algorithms, Spectral Angle Mapper and Maximum Likelihood, using different sets of training areas and spectral libraries. As established in chemometrics we used multivariate analysis such as partial least-squares regression (PLSR) in addition to multivariate adaptive regression splines (MARS) to correlate chemical data with Vis-NIR spectra. As a result elemental mapping of Fe and OC within the soil core at high spatial resolution has been achieved. The regression model was validated by a new set of reference samples for chemical analysis. Digital soil classification easily visualizes soil properties within the soil profiles. By combining both techniques, detailed soil maps, elemental balances and a deeper understanding of soil forming processes at the microscale become feasible for complete soil profiles.

Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen

2016-04-01

Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under different hydrologic conditions and the factors controlling the temporal variability of the ECa-soil moisture relationship. The approach provided valuable insight into the time-varying contribution of local and nonlocal factors to the characteristic spatial patterns of soil moisture and the transition mechanisms. The spatial organization of soil moisture was controlled by different processes in different soil horizons, and the topsoil's moisture did not mirror processes that take place within the soil profile. Results show that, for the Schäfertal hillslope site which is presumed to be representative for non-intensively managed soils with moderate clay content, local soil properties (e.g., soil texture and porosity) are the major control on the spatial pattern of ECa. In contrast, the ECa-soil moisture relationship is small and varies over time indicating that ECa is not a good proxy for soil moisture estimation at the investigated site.Occasionally observed stronger correlations between ECa and soil moisture may be explained by background dependencies of ECa to other state variables such as pore water electrical conductivity. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales, and to transfer observation concepts and process understanding to larger or less instrumented sites, as well as to constrain the use of EMI-based ECa data for hydrological applications.

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

USGS Publications Warehouse

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

2012-01-01

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

L-band Soil Moisture Mapping using Small UnManned Aerial Systems

NASA Astrophysics Data System (ADS)

Dai, E.

2015-12-01

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, and impacts water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 promises to provide global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions as low as 5 km for some products. However, there exists a need for measurements of soil moisture on 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 (i.e., the height of the platform) .Compared with various other proposed methods of validation based on either 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 scale studies, and at comparatively low operator cost. The LDCR on Tempest unit can supply the soil moisture mapping with different resolution which is of order the Tempest altitude.

Soil properties, soil functions and soil security

NASA Astrophysics Data System (ADS)

Poggio, Laura; Gimona, Alessandro

2017-04-01

Soil plays a crucial role in the ecosystem functioning such as food production, capture and storage of water, carbon and nutrients and in the realisation of a number of UN Sustainable Developments Goals. In this work we present an approach to spatially and jointly assess the multiple contributions of soil to the delivery of ecosystem services within multiple land-use system. We focussed on the modelling of the impact of soil on sediment retention, carbon storage, storing and filtering of nutrients, habitat for soil organisms and water regulation, taking into account examples of land use and climate scenarios. Simplified models were used for the single components. Spatialised Bayesian Belief networks were used for the jointly assessment and mapping of soil contribution to multiple land use and ecosystem services. We integrated continuous 3D soil information derived from digital soil mapping approaches covering the whole of mainland Scotland, excluding the Northern Islands. Uncertainty was accounted for and propagated across the whole process. The Scottish test case highlights the differences in roles between mineral and organic soils and provides an example of integrated study assessing the contributions of soil. The results show the importance of the multi-functional analysis of the contribution of soils to the ecosystem service delivery and UN SDGs.

NASA applications project in Miami County, Indiana

NASA Technical Reports Server (NTRS)

Fernandez, R. Norberto; Lozano-Garcia, D. Fabian; Wyss, Phillip J.; Johannsen, Chris J.

1989-01-01

The study site selection is intended to serve all of the different research areas within the project, i.e., soil conditions, soil management, etc. There are seven major soil associations or soils formed on similar landscapes in the Miami Co., and over 38 soil series that were mapped. Soil sampling was conducted in some sites because of its variability in soils and cover types, variable topography, and presence of erosion problems. Results from analysis of these soil data is presented.

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.).

PubMed

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.

Analysis of slope stabillity and controlling factor on residual soil of folded breccia formation

NASA Astrophysics Data System (ADS)

Rachman, S.; Muslim, D.; Sulaksana, N.; Burhannuddinnur, M.; Pramudito, H.

2018-01-01

This research aims to obtain a potential landslide zonation. Theresearch area is located in Depok Village and surroundings, Jatigede District, Sumedang regency, West Java province. Geographically located at the point of coordinates 06°50‧33-06°51‧00″ South Latitude and 108°05‧37 ″- 108°06‧17″ East Longitude. This research is intended to mapping the identification of landslide and soil properties data. The mapping and soil sampling were conducted only in the research area. The methodology used was mapping and finding the safety factor with Bishop Analysis. The morphological condition of the study area indicates moderate conditions undulating hilly area with slopes between 15° - 40°, with a tick soil layer was covering the slope. This condition is greatly affected by rainfall. This research is to know the type of ground movement along with the value of the safety factor of the slope so that can provide suggestions for overcoming instability in the study area.

Radar response to vegetation. [soil moisture mapping via microwave backscattering

NASA Technical Reports Server (NTRS)

Ulaby, F. T.

1975-01-01

Active microwave measurements of vegetation backscatter were conducted to determine the utility of radar in mapping soil moisture through vegetation and mapping crop types. Using a truck-mounted boom, spectral response data were obtained for four crop types (corn, milo, soybeans, and alfalfa) over the 4-8 GHz frequency band, at incidence angles of 0 to 70 degrees in 10-degree steps, and for all four linear polarization combinations. Based on a total of 125 data sets covering a wide range of soil moisture, content, system design criteria are proposed for each of the aforementioned objectives. Quantitative soil moisture determination was best achieved at the lower frequency end of the 4-8 GHz band using HH polarized waves in the 5- to 15-degree incidence angle range. A combination of low and high frequency measurements are suggested for classifying crop types. For crop discrimination, a dual-frequency dual-polarization (VV and cross) system operating at incidence angles above 40 degrees is suggested.

Large area mapping of soil moisture using the ESTAR passive microwave radiometer

NASA Technical Reports Server (NTRS)

Jackson, T. J.; Levine, D. M.; Swift, C. T.; Schmugge, T. J.

1994-01-01

Investigations designed to study land surface hydrologic-atmospheric interactions, showing the potential of L band passive microwave radiometry for measuring surface soil moisture over large areas, are discussed. Satisfying the data needs of these investigations requires the ability to map large areas rapidly. With aircraft systems this means a need for more beam positions over a wider swath on each flightline. For satellite systems the essential problem is resolution. Both of these needs are currently being addressed through the development and verification of Electronically Scanned Thinned Array Radiometer (ESTAR) technology. The ESTAR L band radiometer was evaluated for soil moisture mapping applications in two studies. The first was conducted over the semiarid rangeland Walnut Gulch watershed located in south eastern Arizona (U.S.). The second was performed in the subhumid Little Washita watershed in south west Oklahoma (U.S.). Both tests showed that the ESTAR is capable of providing soil moisture with the same level of accuracy as existing systems.

GEMAS: The Fennoscandian perspective

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

3D-Digital soil property mapping by geoadditive models

NASA Astrophysics Data System (ADS)

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 account for nonlinear effects of covariates by fitting componentwise smooth, nonlinear functions to the covariates (additive terms). REML estimation of model parameters and computing best linear unbiased predictions (BLUP) builds in the geoAM framework on the fact that both geostatistical and additive models can be parametrized as linear mixed models Wand, 2003. For 3D-DSM analysis of soil data, it is natural to model depth profiles of soil properties by additive terms of soil depth. Including interactions between these additive terms and covariates of the spatial mean function allows to model spatially varying depth profiles. Furthermore, with suitable choice of the basis functions of the additive term (e.g. polynomial regression splines), non-constant support of the soil data can be taken into account. Finally, boosting (Bühlmann and Hothorn, 2007) can be used for selecting covariates for the spatial mean function. The presentation will detail the geoAM approach and present an example of geoAM for 3D-analysis of legacy soil data. Arrouays, D., McBratney, A. B., Minasny, B., Hempel, J. W., Heuvelink, G. B. M., MacMillan, R. A., Hartemink, A. E., Lagacherie, P., and McKenzie, N. J. (2014). The GlobalSoilMap project specifications. In GlobalSoilMap Basis of the global spatial soil information system, pages 9-12. CRC Press. Bishop, T., McBratney, A., and Laslett, G. (1999). Modelling soil attribute depth functions with equal-area quadratic smoothing splines. Geoderma, 91(1-2), 27-45. Bühlmann, P. and Hothorn, T. (2007). Boosting algorithms: Regularization, prediction and model fitting. Statistical Science, 22(4), 477-505. Kammann, E. E. and Wand, M. P. (2003). Geoadditive models. Journal of the Royal Statistical Society. Series C: Applied Statistics, 52(1), 1-18. Kyriakidis, P. (2004). A geostatistical framework for area-to-point spatial interpolation. Geographical Analysis, 36(3), 259-289. Orton, T., Pringle, M., and Bishop, T. (2016). A one-step approach for modelling and mapping soil properties based on profile data sampled over varying depth intervals. Geoderma, 262, 174-186. Wand, M. P. (2003). Smoothing and mixed models. Computational Statistics, 18(2), 223-249.

Effect of inorganic amendments for in situ stabilization of cadmium in contaminated soils and its phyto-availability to wheat and rice under rotation.

PubMed

Rehman, Muhammad Zia-ur; Rizwan, Muhammad; Ghafoor, Abdul; Naeem, Asif; Ali, Shafaqat; Sabir, Muhammad; Qayyum, Muhammad Farooq

2015-11-01

Cadmium (Cd) toxicity is a widespread problem in crops grown on contaminated soils, and little information is available on the role of inorganic amendments in Cd immobilization, uptake, and tolerance in crops especially under filed conditions. The effect of three amendments, monoammonium phosphate (MAP), gypsum, and elemental sulfur (S), on Cd immobilization in soil and uptake in wheat and rice plants, under rotation, were investigated under field conditions receiving raw city effluent since >20 years and contaminated with Cd. Three levels of each treatment, 0.2, 0.4, and 0.8% by weight, were applied at the start of the experiment, and wheat was sown in the field. After wheat harvesting, rice was sown in the same field without application of amendments. Both crops were harvested at physiological maturity, and data regarding grain yield, straw biomass, Cd concentrations, and uptake in grain and straw, and bioavailable Cd in soil and soil pH were recorded. Both MAP and gypsum application increased grain yield and biomass of wheat and rice, while S application did not increase the yield of both crops. MAP and gypsum amendments decreased gain and straw Cd concentrations and uptake in both crops, while S application increased Cd concentrations in these parts which were correlated with soil bioavailable Cd. We conclude that MAP and gypsum amendments could be used to decrease Cd uptake by plants receiving raw city effluents, and gypsum might be a better amendment for in situ immobilization of Cd due to its low cost and frequent availability.

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

USGS Publications Warehouse

Fullerton, D. S.; Ringrose, S.M.; Clayton, Lee; Schreiner, B.T.; Goebel, J.E.

2000-01-01

The Quaternary Geologic Map of the Winnipeg 4? ? 6? Quadrangle, United States and Canada, is a component of the U.S. Geological Survey Quaternary Geologic Atlas of the United States map series (Miscellaneous Investigations Series I-1420), an effort to produce 4? ? 6? Quaternary geologic maps, at 1:1 million scale, of the entire conterminous United States and adjacent Canada. The map and the accompanying text and supplemental illustrations provide a regional overview of the areal distributions and characteristics of surficial deposits and materials of Quaternary age (~1.8 Ma to present) in parts of North Dakota, Minnesota, Manitoba, and Saskatchewan. The map is not a map of soils as soils are recognized in agriculture. Rather, it is a map of soils as recognized in engineering geology, or of substrata or parent materials in which agricultural soils are formed. The map units are distinguished chiefly on the basis of (1)genesis (processes of origin) or environments of deposition: for example, sediments deposited primarily by glacial ice (glacial deposits or till), sediments deposited in lakes (lacustrine deposits), or sediments deposited by wind (eolian deposits); (2) age: for example, how long ago the deposits accumulated; (3) texture (grain size)of the deposits or materials; (4) composition (particle lithology) of the deposits or materials; (5) thickness; and (6) other physical, chemical, and engineering properties. Supplemental illustrations show (1) temporal correlation of the map units, (2) the areal relationships of late Wisconsin glacial ice lobes and sublobes, (3) temporal and spatial correlation of late Wisconsin glacial phases, readvance limits, and ice margin stillstands, (4) temporal and stratigraphic correlation of surface and subsurface glacial deposits in the Winnipeg quadrangle and in adjacent 4? ? 6? quadrangles, and (5) responsibility for state and province compilations. The database provides information related to geologic hazards (for example, materials that are characterized by expansive clay minerals; landslide deposits or landslide-prone deposits), natural resources (for example, sources of aggregate, peat, and clay; potential shallow sources of groundwater), and areas of environmental concern (for example, areas that are potentially suitable for specific ecosystem habitats; areas of potential soil and groundwater contamination). All of these aspects of the database relate directly to land use, management, and policy. The map, text, and accompanying illustrations provide a database of regional scope related to geologic history, climatic changes, the stratigraphic and chronologic frameworks of surface and subsurface deposits and materials of Quaternary age, and other problems and concerns.

Soil Parameter Mapping and Ad Hoc Power Analysis to Increase Blocking Efficiency Prior to Establishing a Long-Term Field Experiment.

PubMed

Collins, Doug; Benedict, Chris; Bary, Andy; Cogger, Craig

2015-01-01

The spatial heterogeneity of soil and weed populations poses a challenge to researchers. Unlike aboveground variability, below-ground variability is more difficult to discern without a strategic soil sampling pattern. While blocking is commonly used to control environmental variation, this strategy is rarely informed by data about current soil conditions. Fifty georeferenced sites were located in a 0.65 ha area prior to establishing a long-term field experiment. Soil organic matter (OM) and weed seed bank populations were analyzed at each site and the spatial structure was modeled with semivariograms and interpolated with kriging to map the surface. These maps were used to formulate three strategic blocking patterns and the efficiency of each pattern was compared to a completely randomized design and a west to east model not informed by soil variability. Compared to OM, weeds were more variable across the landscape and had a shorter range of autocorrelation, and models to increase blocking efficiency resulted in less increase in power. Weeds and OM were not correlated, so no model examined improved power equally for both parameters. Compared to the west to east blocking pattern, the final blocking pattern chosen resulted in a 7-fold increase in power for OM and a 36% increase in power for weeds.

Assessment of lead pollution in topsoils of a southern Italy area: Analysis of urban and peri-urban environment.

PubMed

Guagliardi, Ilaria; Cicchella, Domenico; De Rosa, Rosanna; Buttafuoco, Gabriele

2015-07-01

Exposure to lead (Pb) may affect adversely human health. Mapping soil Pb contents is essential to obtain a quantitative estimate of potential risk of Pb contamination. The main aim of this paper was to determine the soil Pb concentrations in the urban and peri-urban area of Cosenza-Rende to map their spatial distribution and assess the probability that soil Pb concentration exceeds a critical threshold that might cause concern for human health. Samples were collected at 149 locations from residual and non-residual topsoil in gardens, parks, flower-beds, and agricultural fields. Fine earth fraction of soil samples was analyzed by X-ray Fluorescence spectrometry. Stochastic images generated by the sequential Gaussian simulation were jointly combined to calculate the probability of exceeding the critical threshold that could be used to delineate the potentially risky areas. Results showed areas in which Pb concentration values were higher to the Italian regulatory values. These polluted areas were quite large and likely, they could create a significant health risk for human beings and vegetation in the near future. The results demonstrated that the proposed approach can be used to study soil contamination to produce geochemical maps, and identify hot-spot areas for soil Pb concentration. Copyright © 2015. Published by Elsevier B.V.

Use of remote sensing and GIS in mapping the environmental sensitivity areas for desertification of Egyptian territory

NASA Astrophysics Data System (ADS)

Gad, A.; Lotfy, I.

2008-06-01

Desertification is defined in the first art of the convention to combat desertification as "land degradation in arid, semiarid and dry sub-humid areas resulting from climatic variations and human activities". Its consequence include a set of important processes which are active in arid and semi arid environment, where water is the main limiting factor of land use performance in such ecosystem . Desertification indicators or the groups of associated indicators should be focused on a single process. They should be based on available reliable information sources, including remotely sensed images, topographic data (maps or DEM'S), climate, soils and geological data. The current work aims to map the Environmental Sensitivity Areas (ESA's) to desertification in whole territory of Egypt at a scale of 1:1 000 000. ETM satellite images, geologic and soil maps were used as main sources for calculating the index of Environmental Sensitivity Areas (ESAI) for desertification. The algorism is adopted from MEDALLUS methodology as follows; ESAI = (SQI * CQI * VQI)1/3 Where SQI is the soil quality index, CQI is the climate quality index and VQI is the vegetation quality index. The SQI is based on rating the parent material, slope, soil texture, and soil depth. The VQI is computed on bases of rating three categories (i.e. erosion protection, drought resistance and plant cover). The CQI is based on the aridity index, derived from values of annual rainfall and potential evapotranspiration. Arc-GIS 9 software was used for the computation and sensitivity maps production. The results show that the soil of the Nile Valley are characterized by a moderate SQI, however the those in the interference zone are low soil quality indexed. The dense vegetation of the valley has raised its VQI to be good, however coastal areas are average and interference zones are low. The maps of ESA's for desertification show that 86.1% of Egyptian territory is classified as very sensitive areas, while 4.3% as Moderately sensitive, and 9.6% as sensitive. It can be concluded that implementing the maps of sensitivity to desertification is rather useful in the arid and semi arid areas as they give more likely quantitative trend for frequency of sensitive areas. The integration of different factors contributing to desertification sensitivity may lead to plan a successful combating. The usage of space data and GIS proved to be suitable tools to rely estimation and to fulfill the needed large computational requirements. They are also useful in visualizing the sensitivity situation of different desertification parameters.

Spatial variability of total carbon and soil organic carbon in agricultural soils in Baranja region, Croatia

NASA Astrophysics Data System (ADS)

Bogunović, Igor; Trevisani, Sebastiano; Pereira, Paulo; Šeput, Miranda

2017-04-01

Climate change is expected to have an important influence on the crop production in agricultural regions. Soil carbon represents an important soil property that contributes to mitigate the negative influence of climate change on intensive cropped areas. Based on 5063 soil samples sampled from soil top layer (0-30 cm) we studied the spatial distribution of total carbon (TC) and soil organic carbon (SOC) content in various soil types (Anthrosols, Cambisols, Chernozems, Fluvisols, Gleysols, Luvisols) in Baranja region, Croatia. TC concentrations ranged from 2.10 to 66.15 mg/kg (with a mean of 16.31 mg/kg). SOC concentrations ranged from 1.86 to 58.00 mg/kg (with a mean of 13.35 mg/kg). TC and SOC showed moderate heterogeneity with coefficient of variation (CV) of 51.3% and 33.8%, respectively. Average concentrations of soil TC vary in function of soil types in the following decreasing order: Anthrosols (20.9 mg/kg) > Gleysols (19.3 mg/kg) > Fluvisols (15.6 mg/kg) > Chernozems (14.2 mg/kg) > Luvisols (12.6 mg/kg) > Cambisols (11.1 mg/kg), while SOC concentrations follow next order: Gleysols (15.4 mg/kg) > Fluvisols (13.2 mg/kg) = Anthrosols (13.2 mg/kg) > Chernozems (12.6 mg/kg) > Luvisols (11.4 mg/kg) > Cambisols (10.5 mg/kg). Performed geostatistical analysis of TC and SOC; both the experimental variograms as well as the interpolated maps reveal quite different spatial patterns of the two studied soil properties. The analysis of the spatial variability and of the spatial patterns of the produced maps show that SOC is likely influenced by antrophic processes. Spatial variability of SOC indicates soil health deterioration on an important significant portion of the studied area; this suggests the need for future adoption of environmentally friendly soil management in the Baranja region. Regional maps of TC and SOC provide quantitative information for regional planning and environmental monitoring and protection purposes.

Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment

NASA Astrophysics Data System (ADS)

Meusburger, K.; Konz, N.; Schaub, M.; Alewell, C.

2010-06-01

The focus of soil erosion research in the Alps has been in two categories: (i) on-site measurements, which are rather small scale point measurements on selected plots often constrained to irrigation experiments or (ii) off-site quantification of sediment delivery at the outlet of the catchment. Results of both categories pointed towards the importance of an intact vegetation cover to prevent soil loss. With the recent availability of high-resolution satellites such as IKONOS and QuickBird options for detecting and monitoring vegetation parameters in heterogeneous terrain have increased. The aim of this study is to evaluate the usefulness of QuickBird derived vegetation parameters in soil erosion models for alpine sites by comparison to Cesium-137 (Cs-137) derived soil erosion estimates. The study site (67 km 2) is located in the Central Swiss Alps (Urseren Valley) and is characterised by scarce forest cover and strong anthropogenic influences due to grassland farming for centuries. A fractional vegetation cover (FVC) map for grassland and detailed land-cover maps are available from linear spectral unmixing and supervised classification of QuickBird imagery. The maps were introduced to the Pan-European Soil Erosion Risk Assessment (PESERA) model as well as to the Universal Soil Loss Equation (USLE). Regarding the latter model, the FVC was indirectly incorporated by adapting the C factor. Both models show an increase in absolute soil erosion values when FVC is considered. In contrast to USLE and the Cs-137 soil erosion rates, PESERA estimates are low. For the USLE model also the spatial patterns improved and showed "hotspots" of high erosion of up to 16 t ha -1 a -1. In conclusion field measurements of Cs-137 confirmed the improvement of soil erosion estimates using the satellite-derived vegetation data.

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

NASA Astrophysics Data System (ADS)

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.

Design of a Horizontal Penetrometer for Measuring On-the-Go Soil Resistance

PubMed Central

Topakci, Mehmet; Unal, Ilker; Canakci, Murad; Celik, Huseyin Kursat; Karayel, Davut

2010-01-01

Soil compaction is one of the main negative factors that limits plant growth and crop yield. Therefore, it is important to determine the soil resistance level and map it for the field to find solutions for the negative effects of the compaction. Nowadays, high powered communication technology and computers help us on this issue within the approach of precision agriculture applications. This study is focused on the design of a penetrometer, which can make instantaneous soil resistance measurements in the soil horizontally and data acquisition software based on the GPS (Global Positioning System). The penetrometer was designed using commercial 3D parametric solid modelling design software. The data acquisition software was developed in Microsoft Visual Basic.NET programming language. After the design of the system, manufacturing and assembly of the system was completed and then a field experiment was carried out. According to the data from GPS and penetration resistance values which are collected in Microsoft SQL Server database, a Kriging method by ArcGIS was used and soil resistance was mapped in the field for a soil depth of 40 cm. During operation, no faults, either in mechanical and software parts, were seen. As a result, soil resistance values of 0.2 MPa and 3 MPa were obtained as minimum and maximum values, respectively. In conclusion, the experimental results showed that the designed system works quite well in the field and the horizontal penetrometer is a practical tool for providing on-line soil resistance measurements. This study contributes to further research for the development of on-line soil resistance measurements and mapping within the precision agriculture applications. PMID:22163410

Design of a horizontal penetrometer for measuring on-the-go soil resistance.

PubMed

Topakci, Mehmet; Unal, Ilker; Canakci, Murad; Celik, Huseyin Kursat; Karayel, Davut

2010-01-01

Soil compaction is one of the main negative factors that limits plant growth and crop yield. Therefore, it is important to determine the soil resistance level and map it for the field to find solutions for the negative effects of the compaction. Nowadays, high powered communication technology and computers help us on this issue within the approach of precision agriculture applications. This study is focused on the design of a penetrometer, which can make instantaneous soil resistance measurements in the soil horizontally and data acquisition software based on the GPS (Global Positioning System). The penetrometer was designed using commercial 3D parametric solid modelling design software. The data acquisition software was developed in Microsoft Visual Basic.NET programming language. After the design of the system, manufacturing and assembly of the system was completed and then a field experiment was carried out. According to the data from GPS and penetration resistance values which are collected in Microsoft SQL Server database, a Kriging method by ArcGIS was used and soil resistance was mapped in the field for a soil depth of 40 cm. During operation, no faults, either in mechanical and software parts, were seen. As a result, soil resistance values of 0.2 MPa and 3 MPa were obtained as minimum and maximum values, respectively. In conclusion, the experimental results showed that the designed system works quite well in the field and the horizontal penetrometer is a practical tool for providing on-line soil resistance measurements. This study contributes to further research for the development of on-line soil resistance measurements and mapping within the precision agriculture applications.

Simulation of future groundwater recharge using a climate model ensemble and SAR-image based soil parameter distributions - A case study in an intensively-used Mediterranean catchment.

PubMed

Herrmann, Frank; Baghdadi, Nicolas; Blaschek, Michael; Deidda, Roberto; Duttmann, Rainer; La Jeunesse, Isabelle; Sellami, Haykel; Vereecken, Harry; Wendland, Frank

2016-02-01

We used observed climate data, an ensemble of four GCM-RCM combinations (global and regional climate models) and the water balance model mGROWA to estimate present and future groundwater recharge for the intensively-used Thau lagoon catchment in southern France. In addition to a highly resolved soil map, soil moisture distributions obtained from SAR-images (Synthetic Aperture Radar) were used to derive the spatial distribution of soil parameters covering the full simulation domain. Doing so helped us to assess the impact of different soil parameter sources on the modelled groundwater recharge levels. Groundwater recharge was simulated in monthly time steps using the ensemble approach and analysed in its spatial and temporal variability. The soil parameters originating from both sources led to very similar groundwater recharge rates, proving that soil parameters derived from SAR images may replace traditionally used soil maps in regions where soil maps are sparse or missing. Additionally, we showed that the variance in different GCM-RCMs influences the projected magnitude of future groundwater recharge change significantly more than the variance in the soil parameter distributions derived from the two different sources. For the period between 1950 and 2100, climate change impacts based on the climate model ensemble indicated that overall groundwater recharge will possibly show a low to moderate decrease in the Thau catchment. However, as no clear trend resulted from the ensemble simulations, reliable recommendations for adapting the regional groundwater management to changed available groundwater volumes could not be derived. Copyright © 2015 Elsevier B.V. All rights reserved.

Spatial distribution of pH and organic matter in urban soils and its implications on site-specific land uses in Xuzhou, China.

PubMed

Mao, Yingming; Sang, Shuxun; Liu, Shiqi; Jia, Jinlong

2014-05-01

The spatial variation of soil pH and soil organic matter (SOM) in the urban area of Xuzhou, China, was investigated in this study. Conventional statistics, geostatistics, and a geographical information system (GIS) were used to produce spatial distribution maps and to provide information about land use types. A total of 172 soil samples were collected based on grid method in the study area. Soil pH ranged from 6.47 to 8.48, with an average of 7.62. SOM content was very variable, ranging from 3.51 g/kg to 17.12 g/kg, with an average of 8.26 g/kg. Soil pH followed a normal distribution, while SOM followed a log-normal distribution. The results of semi-variograms indicated that soil pH and SOM had strong (21%) and moderate (44%) spatial dependence, respectively. The variogram model was spherical for soil pH and exponential for SOM. The spatial distribution maps were achieved using kriging interpolation. The high pH and high SOM tended to occur in the mixed forest land cover areas such as those in the southwestern part of the urban area, while the low values were found in the eastern and the northern parts, probably due to the effect of industrial and human activities. In the central urban area, the soil pH was low, but the SOM content was high, which is mainly attributed to the disturbance of regional resident activities and urban transportation. Furthermore, anthropogenic organic particles are possible sources of organic matter after entering the soil ecosystem in urban areas. These maps provide useful information for urban planning and environmental management. Copyright © 2014 Académie des sciences. Published by Elsevier SAS. All rights reserved.

The History of Electromagnetic Induction Techniques in Soil Survey

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Doolittle, Jim

2014-05-01

Electromagnetic induction (EMI) has been used to characterize the spatial variability of soil properties since the late 1970s. Initially used to assess soil salinity, the use of EMI in soil studies has expanded to include: mapping soil types; characterizing soil water content and flow patterns; assessing variations in soil texture, compaction, organic matter content, and pH; and determining the depth to subsurface horizons, stratigraphic layers or bedrock, among other uses. In all cases the soil property being investigated must influence soil apparent electrical conductivity (ECa) either directly or indirectly for EMI techniques to be effective. An increasing number and diversity of EMI sensors have been developed in response to users' needs and the availability of allied technologies, which have greatly improved the functionality of these tools. EMI investigations provide several benefits for soil studies. The large amount of georeferenced data that can be rapidly and inexpensively collected with EMI provides more complete characterization of the spatial variations in soil properties than traditional sampling techniques. In addition, compared to traditional soil survey methods, EMI can more effectively characterize diffuse soil boundaries and identify included areas of dissimilar soils within mapped soil units, giving soil scientists greater confidence when collecting spatial soil information. EMI techniques do have limitations; results are site-specific and can vary depending on the complex interactions among multiple and variable soil properties. Despite this, EMI techniques are increasingly being used to investigate the spatial variability of soil properties at field and landscape scales.

The comparative evaluation of ERTS-1 imagery for resource inventory in land use planning. [Oregon - Newberry Caldera, Mt. Washington, and Big Summit Prairie in Crook County

NASA Technical Reports Server (NTRS)

Schrumpf, B. J. (Principal Investigator); Simonson, G. H.; Paine, D. P.; Lawrence, R. D.; Pyott, W. T.; Herzog, J. H.; Murray, R. J.; Norgren, J. A.; Cornwell, J. A.; Rogers, R. A.

1974-01-01

The author has identified the following significant results. Multidiscipline team interpretation and mapping of resources for Crook County is complete on 1:250,000 scale enlargements of ERTS imagery and 1:120,000 hi-flight photography. Maps of geology, soils, vegetation-land use and land resources units were interpreted to show limitations, suitabilities, and geologic hazards for land use planning. Mapping of lineaments and structures from ERTS imagery has shown a number of features not previously mapped in Oregon. A multistage timber inventory of Ochoco National Forest was made, using ERTS images as the first stage. Inventory of forest clear-cutting practices was successfully demonstrated with color composites. Soil tonal differences in fallow fields correspond with major soil boundaries in loess-mantled terrain. A digital classification system used for discriminating natural vegetation and geologic material classes was successful in separating most major classes around Newberry Caldera, Mt. Washington, and Big Summit Prairie.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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 range.

A comparative study of the SMAP passive soil moisture product with existing satellite-based soil moisture products

USDA-ARS?s Scientific Manuscript database

NASA Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015 to provide global mapping of high-resolution soil moisture and freeze thaw state every 2-3 days using an L-band (active) radar and an L-band (passive) radiometer. The radiometer-only soil moisture product (L2...

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

NASA Astrophysics Data System (ADS)

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, can be classified as Kastanozems. Besides the Kastanozems, Regosols are most common at the sand dune sites as well as at sites that are defined as bare soil which are characterized by little or no vegetation. Gleysols are mostly found at sites in the vicinity of the Xilin river, which are connected to the groundwater. They can also be found in small valleys or depressions where sub-surface waters from neighboring areas collect. The richest soils are found in mountain meadow areas. Pedogenetic conditions here are most favorable and lead to the formation of Chernozems with deep humic Ah horizons. Other soil types that occur in the study area are Arenosols, Calcisols, Cambisol and Phaeozems. In addition, soil taxonomic distance is implemented into the decision tree procedure as a measure of classification error. The results of incorporating taxonomic distance as a loss function in the decision tree will be compared with the standard application of the decision tree.

Presenting the 3rd edition of WRB

NASA Astrophysics Data System (ADS)

Schad, Peter

2014-05-01

The third edition of the international soil classification system "World Reference Base for Soil Resources" (WRB) will be presented during der 20th World Congress of Soil Science, Jeju, Korea, June 9-12. The second edition was published in 2006 and the first in 1998, which, in turn, was based on the Legends of the FAO Soil Map of the World. Now, after eight years of experience with the second edition, time was due for a revision. The major changes are: 1. The second edition had two different qualifier sequences for naming soils (IUSS Working Group WRB, 2006, update 2007) and for creating map legends (Guidelines for creating small-scale map legends using the WRB; IUSS Working Group WRB, 2010). The third edition has one sequence for both. The qualifiers for every Reference Soil Group are subdivided into a small number of main qualifiers that are ranked and a larger number of additional qualifiers that are not ranked and given in an alphabetical order. The name of a pedon must comprise all applying qualifiers. The name of a map unit comprises a specified small number of main qualifiers, depending on scale, whereas all other qualifiers are optional. 2. For some soils, problems have been reported. Albeluvisols are difficult to detect in the field and cover only small surfaces. They have been replaced by Retisols, which have a broader definition that is easier to identify in the field. 3. The use of some diagnostics was difficult. Examples are: The argic horizon had too low limit values, so we had much more soils with argic horizons than justified. The definitions of the cambic horizon and the gleyic and stagnic properties were not precise enough. Organic material, mollic and umbric horizons had an unnecessary complicated definition. 4. Some changes in the key to the Reference Soil Groups seemed to be justified. Fluvisols were moved further down, Durisols and Gypsisols switched their position, also Arenosols and Cambisols. The soils with an argic horizon were brought into a new sequence. 5. The umbrella function of WRB aims to allow the allocation of soil classes existing in a national classification system within the WRB. Characteristics that in a national system are regarded to be important must be considered in WRB - not necessarily at the highest level, but at least somewhere. The third edition of WRB allows a better accommodation of soil types, e.g., of the Australian and the Brazilian system. 6. Some environments or even ecoregions had not been well represented in WRB. The third edition allows a better accommodation of soils of ultra-continental permafrost regions, acid-sulphate soils and Technosols. 7. How to explain complicated sets of characteristics? For the third edition, efforts were made to give better structured definitions that can be more easily grasped. The editors of the third edition are convinced that the new WRB allows a more precise classification of soils including both, a better naming of pedons and a better elaboration of soil map legends.

Riparian habitat on the Humboldt River, Deeth to Elko, Nevada

NASA Technical Reports Server (NTRS)

Price, K. P.; Ridd, M. K.

1983-01-01

A map inventory of the major habitat types existing along the Humbolt River riparian zone in Nevada is described. Through aerialphotography, 16 riparian habitats are mapped that describe the ecological relationships between soil and vegetation types, flooding and soil erosion, and the various management practices employed to date. The specific land and water management techniques and their impact on the environment are considered.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

The Iranian loess plateau is covered by loess deposits, up to 70 m thick. Tectonic uplift triggered deep erosion and valley incision into the loess and underlying marine deposits. Soil development strongly relates to the aspect of these incised slopes, because on northern slopes vegetation protects the soil surface against erosion and facilitates formation and preservation of a Cambisol, whereas on south-facing slopes soils were probably eroded and weakly developed Entisols formed. While the whole area is intensively stocked with sheep and goat, rain-fed cropping of winter wheat is practiced on the valley floors. Most time of the year, the soil surface is unprotected against rainfall, which is one of the factors promoting soil erosion and serious flooding. However, little information is available on soil distribution, plant cover and the geomorphological evolution of the plateau, as well as on potentials and problems in land use. Thus, digital landform and soil mapping is needed. As a requirement of digital landform and soil mapping, four different landform classification methods were compared and evaluated. These geomorphometric classifications were run on two different scales. On the whole area an ASTER GDEM and SRTM dataset (30 m pixel resolution) was used. Likewise, two high-resolution digital elevation models were derived from Pléiades satellite stereo-imagery (< 1m pixel resolution, 10 by 10 km). The high-resolution information of this dataset was aggregated to datasets of 5 and 10 m scale. The applied classification methods are the Geomorphons approach, an object-based image approach, the topographical position index and a mainly slope based approach. The accuracy of the classification was checked with a location related image dataset obtained in a field survey (n ~ 150) in September 2015. The accuracy of the DEMs was compared to measured DGPS trenches and map-based elevation data. The overall derived accuracy of the landform classification based on the high-resolution DEM with a resolution of 5 m is approximately 70% and on a 10 m resolution >58%. For the 30 m resolution datasets is the achieved accuracy approximately 40%, as several small scale features are not recognizable in this resolution. Thus, for an accurate differentiation between different important landform types, high-resolution datasets are necessary for this strongly shaped area. One major problem of this approach are the different classes derived by each method and the various class annotations. The result of this evaluation will be regarded for the derivation of landform and soil maps.

LiDAR-derived topographic indices to inform sampling and mapping of soil moisture at the plot to field scale

NASA Astrophysics Data System (ADS)

Kaleita, A. L.

2013-12-01

Identifying field-scale soil moisture patterns, and quantifying their impact on hydrology and nutrient flux, is currently limited by the time and resources required to do sufficient monitoring. A small number of monitoring locations or occasions may not be sufficient to capture the true spatial and temporal dynamics of these patterns. While process models can help to fill in data gaps, it is often difficult if not impossible to effectively parameterize them at the field and sub-field scale. Thus, empirical methods that can optimize sampling and mapping of soil moisture by using a minimal amount of readily available data may be of significant value. LiDAR is one source of such readily available data. Various topographic indices, including relative elevation, land slope, curvature, and slope aspect are known to influence soil moisture patterns, though the exact nature of that relationship appears to vary from study to study. The objective of this study was to use these data to identify critical sampling locations for mapping soil moisture, and to upscale point measurements at those locations to both a single field-average value, and to a high-resolution pattern map for the field. This study analyzed in-situ soil moisture measurements from the working agricultural field in Story County, Iowa. Theta probe soil moisture measurement values were taken every 50 meters on a 300 x 250 meter grid (~18 acres) during the summer growing seasons of 2004, 2005, 2007, and 2008. The elevation in the field varies by approximately 5 meters and the grid covers six different soil types and a variety of different landscape positions throughout the field. We used self-organizing maps (SOMs) and K-means clustering algorithms to split apart the field study area into distinct categories of similarly-characterized locations. We then used the SOM and clustering metrics to identify locations within each group that were representative of the behavior of that group of locations. We developed a weighted upscaling process to estimate a whole-field average soil moisture content from these few critical samples, and we compared the results to those obtained through the more traditional 'temporal stability' approach. The cluster-based approach was as good as and often better than the temporal stability approach, with the significant advantage that the former does not require any initial period of exhaustive soil moisture monitoring, whereas the latter does. A second objective was to use the classification results of the landscape data to interpolate these sparse critical sampling point data over the whole field. Using what we term 'feature-space interpolation' we were able to re-create a high-resolution soil moisture map for the field using only three measurements, by giving locations with similar landscape characteristics similar soil moisture values. The results showed a small but significant statistical improvement over traditional distance-based interpolation methods, and the resulting patterns also had stronger correlation with end-of-season yield, suggesting this approach may have valuable applications in production agriculture decision-making and assessment.

Spatial and temporal heterogeneity of water soil erosion in a Mediterranean rain-fed crop

NASA Astrophysics Data System (ADS)

López-Vicente, M.; Quijano, L.; Gaspar, L.; Machín, J.; Navas, A.

2012-04-01

Fertile soil loss by raindrop impact and runoff processes in croplands presents significant variations at temporal and spatial scales. The combined use of advanced GIS techniques and detailed databases allows high resolution mapping of runoff and soil erosion processes. In this study the monthly values of soil loss are calculated in a medium size field of rain-fed winter barley and its drainage area located in the Central Spanish Pre-Pyrenees. The field is surrounded by narrow strips of dense Mediterranean vegetation (mainly holm oaks) and grass. Man-made infrastructures (paved trails and drainage ditches) modify the overland flow pathways and the study site appears hydrologically closed in its northern and western boundaries. This area has a continental Mediterranean climate with two humid periods, one in spring and a second in autumn and a dry summer with rainfall events of high intensity from July to October. The average annual rainfall is 495 mm and the average monthly rainfall intensity ranges from 1.1 mm / h in January to 7.4 mm / h in July. The predicted rates were obtained after running the RMMF model (Morgan, 2001) with the enhancements made to this model by Morgan and Duzant (2008) to the topographic module, and by López-Vicente and Navas (2010) to the hydrological module. A total of 613 soil samples were collected and all input and output maps were generated at high spatial resolution (1 x 1 m of cell size) with ArcMapTM 10.0. A map of effective cumulative runoff was calculated for each month of the year with a weighted multiple flow algorithm and four sub-catchments were distinguished within the field. The average soil erosion in the cultivated area is 1.32 Mg / ha yr and the corresponding map shows a high spatial variability (s.d. = 7.52 Mg / ha yr). The highest values of soil erosion appear in those areas where overland flow is concentrated and slope steepness is higher. The unpaved trail present the highest values of soil erosion with an average value of 72.23 Mg / ha yr, whereas the grass and forested areas have annual rates lower than 0.1 Mg / ha yr. The highest values of soil erosion appear in March, April, May, October and November showing a very good correlation with the depth of monthly rainfall (Pearson's r = 0.97) and a good correlation with the number of rainy days per month (Pearson's r = 0.76). However, no correlation was obtained with the values of monthly rainfall intensity. The availability of a detailed database of soil properties, weather values and a high resolution DEM allows mapping and calculating the spatial and temporal variations of the soil erosion processes within the cultivated area and the area surrounding the crop. Thus, the application of soil erosion models at high spatial and temporal resolution improves their predicting capability due to the complexity and large number of relevant interactions between the different sub-factors.

Surficial Geologic Map of the Worcester North-Oxford- Wrentham-Attleboro Nine-Quadrangle Area in South- Central Massachusetts

USGS Publications Warehouse

Stone, Byron D.; Stone, Janet R.; DiGiacomo-Cohen, Mary L.

2008-01-01

The surficial geologic map layer shows the distribution of nonlithified earth materials at land surface in an area of nine 7.5-minute quadrangles (417 mi2 total) in south-central Massachusetts (fig. 1). Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and in resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, or organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for water resources, construction aggregate resources, earth-surface hazards assessments, and land-use decisions. The mapped distribution of surficial materials that lie between the land surface and the bedrock surface is based on detailed geologic mapping of 7.5-minute topographic quadrangles, produced as part of an earlier (1938-1982) cooperative statewide mapping program between the U.S. Geological Survey and the Massachusetts Department of Public Works (now Massachusetts Highway Department) (Page, 1967; Stone, 1982). Each published geologic map presents a detailed description of local geologic map units, the genesis of the deposits, and age correlations among units. Previously unpublished field compilation maps exist on paper or mylar sheets and these have been digitally rendered for the present map compilation. Regional summaries based on the Massachusetts surficial geologic mapping studies discuss the ages of multiple glaciations, the nature of glaciofluvial, glaciolacustrine, and glaciomarine deposits, and the processes of ice advance and retreat across Massachusetts (Koteff and Pessl, 1981; papers in Larson and Stone, 1982; Oldale and Barlow, 1986; Stone and Borns, 1986; Warren and Stone, 1986). This compilation of surficial geologic materials is an interim product that defines the areas of exposed bedrock and the boundaries between glacial till, glacial stratified deposits, and overlying postglacial deposits. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This surficial geologic map layer covering nine quadrangles revises previous digital surficial geologic maps (Stone and others, 1993; MassGIS, 1999) that were compiled on base maps at regional scales of 1:125,000 and 1:250,000. The purpose of this study is to provide fundamental geologic data for the evaluation of natural resources, hazards, and land information within the Commonwealth of Massachusetts.

Advanced microwave soil moisture studies. [Big Sioux River Basin, Iowa

NASA Technical Reports Server (NTRS)

Dalsted, K. J.; Harlan, J. C.

1983-01-01

Comparisons of low level L-band brightness temperature (TB) and thermal infrared (TIR) data as well as the following data sets: soil map and land cover data; direct soil moisture measurement; and a computer generated contour map were statistically evaluated using regression analysis and linear discriminant analysis. Regression analysis of footprint data shows that statistical groupings of ground variables (soil features and land cover) hold promise for qualitative assessment of soil moisture and for reducing variance within the sampling space. Dry conditions appear to be more conductive to producing meaningful statistics than wet conditions. Regression analysis using field averaged TB and TIR data did not approach the higher sq R values obtained using within-field variations. The linear discriminant analysis indicates some capacity to distinguish categories with the results being somewhat better on a field basis than a footprint basis.

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

PubMed

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.

18 CFR 415.43 - Mapped and unmapped delineations.

Code of Federal Regulations, 2013 CFR

2013-04-01

... data submitted, soil surveys, historic flood maps, high water marks and other empirical data, the... 18 Conservation of Power and Water Resources 2 2013-04-01 2012-04-01 true Mapped and unmapped... ADMINISTRATIVE MANUAL BASIN REGULATIONS-FLOOD PLAIN REGULATIONS Administration § 415.43 Mapped and unmapped...

18 CFR 415.43 - Mapped and unmapped delineations.

Code of Federal Regulations, 2012 CFR

2012-04-01

... data submitted, soil surveys, historic flood maps, high water marks and other empirical data, the... 18 Conservation of Power and Water Resources 2 2012-04-01 2012-04-01 false Mapped and unmapped... ADMINISTRATIVE MANUAL BASIN REGULATIONS-FLOOD PLAIN REGULATIONS Administration § 415.43 Mapped and unmapped...

18 CFR 415.43 - Mapped and unmapped delineations.

Code of Federal Regulations, 2014 CFR

2014-04-01

... data submitted, soil surveys, historic flood maps, high water marks and other empirical data, the... 18 Conservation of Power and Water Resources 2 2014-04-01 2014-04-01 false Mapped and unmapped... ADMINISTRATIVE MANUAL BASIN REGULATIONS-FLOOD PLAIN REGULATIONS Administration § 415.43 Mapped and unmapped...

7 CFR 12.21 - Identification of highly erodible lands criteria.

Code of Federal Regulations, 2011 CFR

2011-01-01

...) Basis for identification as highly erodible. Soil map units and an erodibility index will be used as the basis for identifying highly erodible land. The erodibility index for a soil is determined by dividing the potential average annual rate of erosion for each soil by its predetermined soil loss tolerance (T...

7 CFR 12.21 - Identification of highly erodible lands criteria.

Code of Federal Regulations, 2012 CFR

2012-01-01

...) Basis for identification as highly erodible. Soil map units and an erodibility index will be used as the basis for identifying highly erodible land. The erodibility index for a soil is determined by dividing the potential average annual rate of erosion for each soil by its predetermined soil loss tolerance (T...

7 CFR 12.21 - Identification of highly erodible lands criteria.

Code of Federal Regulations, 2013 CFR

2013-01-01

...) Basis for identification as highly erodible. Soil map units and an erodibility index will be used as the basis for identifying highly erodible land. The erodibility index for a soil is determined by dividing the potential average annual rate of erosion for each soil by its predetermined soil loss tolerance (T...

7 CFR 12.21 - Identification of highly erodible lands criteria.

Code of Federal Regulations, 2014 CFR

2014-01-01

...) Basis for identification as highly erodible. Soil map units and an erodibility index will be used as the basis for identifying highly erodible land. The erodibility index for a soil is determined by dividing the potential average annual rate of erosion for each soil by its predetermined soil loss tolerance (T...

7 CFR 12.21 - Identification of highly erodible lands criteria.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) Basis for identification as highly erodible. Soil map units and an erodibility index will be used as the basis for identifying highly erodible land. The erodibility index for a soil is determined by dividing the potential average annual rate of erosion for each soil by its predetermined soil loss tolerance (T...

7 CFR 12.30 - NRCS responsibilities regarding wetlands.

Code of Federal Regulations, 2011 CFR

2011-01-01

... development and application of criteria to identify hydric soils in consultation with the National Technical Committee for Hydric Soils and make available to the public an approved county list of hydric soil map units, which is based upon the National List of Hydric Soils; (2) Coordinate with the U.S. Fish and Wildlife...

Impacts of precipitation and potential evapotranspiration patterns on downscaling soil moisture in regions with large topographic relief

USDA-ARS?s Scientific Manuscript database

Mapping of soil moisture is important for many applications such as flood forecasting, soil protection, and crop management. Soil moisture can be estimated at coarse resolutions (>1 km) using satellite remote sensing, but that resolution is poorly suited for many applications. The Equilibrium Mois...

7 CFR 12.30 - NRCS responsibilities regarding wetlands.

Code of Federal Regulations, 2014 CFR

2014-01-01

... development and application of criteria to identify hydric soils in consultation with the National Technical Committee for Hydric Soils and make available to the public an approved county list of hydric soil map units, which is based upon the National List of Hydric Soils; (2) Coordinate with the U.S. Fish and Wildlife...

7 CFR 12.30 - NRCS responsibilities regarding wetlands.

Code of Federal Regulations, 2013 CFR

2013-01-01

... development and application of criteria to identify hydric soils in consultation with the National Technical Committee for Hydric Soils and make available to the public an approved county list of hydric soil map units, which is based upon the National List of Hydric Soils; (2) Coordinate with the U.S. Fish and Wildlife...

7 CFR 12.30 - NRCS responsibilities regarding wetlands.

Code of Federal Regulations, 2012 CFR

2012-01-01

... development and application of criteria to identify hydric soils in consultation with the National Technical Committee for Hydric Soils and make available to the public an approved county list of hydric soil map units, which is based upon the National List of Hydric Soils; (2) Coordinate with the U.S. Fish and Wildlife...

About | USDA Plant Hardiness Zone Map

Science.gov Websites

of plants. Wind, soil type, soil moisture, humidity, pollution, snow, and winter sunshine can greatly it might cause rapid changes in the plant's temperature. Soil moisture: Plants have different requirements for soil moisture, and this might vary seasonally. Plants that might otherwise be hardy in your

Investigating Groundwater/Surface Water Interaction at the Diversion Dam Site: Report Documentary 2007-2008

DTIC Science & Technology

2011-05-01

operations, and soil properties. Key findings of this study indicate that soils within the study reach are conductive, with groundwater responding...16 3 Develop Detailed Map of Soils and Their Properties in Bosque Adjacent to...27 4 Evaluate Ecological Impact of River Levels, Soil Types, and Dam

Soils [Chapter 4.2

Treesearch

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...

How serious a problem is subsoil compaction in the Netherlands? A survey based on probability sampling

NASA Astrophysics Data System (ADS)

Brus, Dick J.; van den Akker, Jan J. H.

2018-02-01

Although soil compaction is widely recognized as a soil threat to soil resources, reliable estimates of the acreage of overcompacted soil and of the level of soil compaction parameters are not available. In the Netherlands data on subsoil compaction were collected at 128 locations selected by stratified random sampling. A map showing the risk of subsoil compaction in five classes was used for stratification. Measurements of bulk density, porosity, clay content and organic matter content were used to compute the relative bulk density and relative porosity, both expressed as a fraction of a threshold value. A subsoil was classified as overcompacted if either the relative bulk density exceeded 1 or the relative porosity was below 1. The sample data were used to estimate the means of the two subsoil compaction parameters and the overcompacted areal fraction. The estimated global means of relative bulk density and relative porosity were 0.946 and 1.090, respectively. The estimated areal fraction of the Netherlands with overcompacted subsoils was 43 %. The estimates per risk map unit showed two groups of map units: a low-risk group (units 1 and 2, covering only 4.6 % of the total area) and a high-risk group (units 3, 4 and 5). The estimated areal fraction of overcompacted subsoil was 0 % in the low-risk unit and 47 % in the high-risk unit. The map contains no information about where overcompacted subsoils occur. This was caused by the poor association of the risk map units 3, 4 and 5 with the subsoil compaction parameters and subsoil overcompaction. This can be explained by the lack of time for recuperation.

Role of geospatial technology in identifying natural habitat of malarial vectors in South Andaman, India.

PubMed

Shankar, Shiva; Agrawal, Deepak Kumar

2016-03-01

Malaria is a serious disease which has repeatedly threatened Andaman, an island territory of India. Uncharted dense vegetation and inaccessibility are the salient features of the area and the major areas are covered by remotely sensed data to identify the malaria vector's natural habitat. The present investigation appraises the role of geospatial technologies in identifying the natural habitat of malarial vectors. The base map was prepared from Survey of India's toposheets, the landuse map was prepared from indices techniques like normalised difference vegetation index (NDVI), normalised difference water index (NDWI), modified normalised difference water index (MNDWI), normalised difference pond index (NDPI), and normalized difference turbidity index (NDTI) in conjugation with visual interpretation. The soil moisture content map was reproduced from the soil atlas of Andaman and Nicobar Islands followed by generation of an aspect profile from ASTER-GDEM satellite data. Both the landuse map and aspect profile were validated for accuracy in the field. A weighted overlay analysis of the classes like landuse, soil moisture and aspect profile of the study area resulted in identification of the potential natural habitat map of malaria vector surrounding the areas of Tushnabad, Garacharma, Manglutan, Chouldari, Ferrargunj and Wimberlygunj hamlets. The natural habitat of malaria vector indicated that Tushnabad, Garacharma, Manglutan, Chouldari, Ferrargunj and Wimberlygunj hamlets are within the proximity of 2.5 km from the prime habitat location with more number of malaria positive cases. Also these hamlets are surrounded by dense evergreen forest and the land surface is draped by clay loam and clay soil texture exhibiting high soil moisture content warranting high rates of survival and proliferation of the vector ensuring resurgence of malaria every year. It is thus concluded that application of geospatial technologies plays an important role in identifying the natural habitat of malaria vector.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Production of high-resolution forest-ecosite maps based on model predictions of soil moisture and nutrient regimes over a large forested area.

PubMed

Yang, Qi; Meng, Fan-Rui; Bourque, Charles P-A; Zhao, Zhengyong

2017-09-08

Forest ecosite reflects the local site conditions that are meaningful to forest productivity as well as basic ecological functions. Field assessments of vegetation and soil types are often used to identify forest ecosites. However, the production of high-resolution ecosite maps for large areas from interpolating field data is difficult because of high spatial variation and associated costs and time requirements. Indices of soil moisture and nutrient regimes (i.e., SMR and SNR) introduced in this study reflect the combined effects of biogeochemical and topographic factors on forest growth. The objective of this research is to present a method for creating high-resolution forest ecosite maps based on computer-generated predictions of SMR and SNR for an area in Atlantic Canada covering about 4.3 × 10 6 hectares (ha) of forestland. Field data from 1,507 forest ecosystem classification plots were used to assess the accuracy of the ecosite maps produced. Using model predictions of SMR and SNR alone, ecosite maps were 61 and 59% correct in identifying 10 Acadian- and Maritime-Boreal-region ecosite types, respectively. This method provides an operational framework for the production of high-resolution maps of forest ecosites over large areas without the need for data from expensive, supplementary field surveys.

Remote Sensing for Mapping Soybean Crop in the Brazilian Cerrado

NASA Astrophysics Data System (ADS)

Trabaquini, K.; Bernardes, T.; Mello, M. P.; Formaggio, A.; Rosa, V. G.

2011-12-01

The soybean expansion in the Brazilian Cerrado has been strongly affected by internal and external markets. The main factors driving that expansion are the climatic conditions, the development of technologies and genetic improvement. Recent studies have shown that the soybean expansion has become a major cause of reduction of native vegetation in Mato Grosso State - Brazil, responding for 17% of deforestation from 2000 to 2004. This work aims to map soybean areas in the Brazilian Cerrado in Mato Grosso State, using MODIS data. Thirteen MODIS images (MOD13 - 16 days composition), acquired from September, 2005 to March, 2006, were used to run principal component analysis (PCA) in order to reduce the dimensionality of the data. The first three components (PC1, PC2 and PC3), which contained about 90% of data variability were segmented and utilized as input for an unsupervised classification using the ISOSEG classifier, implemented in the SPRING software. Eighty field work points were randomly selected for the accuracy assessment. An intersection between the soybean map and a map generated by the "Project Monitoring Deforestation of Brazilian Biomes Satellite - PMDBBS", which aimed at identifying anthropic areas, was conducted in order to evaluate the distribution of soybeans within those areas. Moreover a soil map was used in order to evaluate the soybean distribution over the classes of soil. The classification result presented overall index of 83% and the kappa coefficient of 0.64 for the soybean map, which presented a total soybean area of about 42,317 square kilometers. Furthermore, it was verified that 27% of anthropic area was covered by soybean. In relation to the soil analysis, 87% of the total soybean area was planted in Oxisoils. Despite the economic gain related to the soybean production, an adequate management is needed to avoid soil acidification, soil erosion and pollution, aiming at providing a sustainable environment.

Understanding controls of hydrologic processes across two headwater monolithological catchments using model-data synthesis

NASA Astrophysics Data System (ADS)

Xiao, D.; Shi, Y.; Hoagland, B.; Del Vecchio, J.; Russo, T. A.; DiBiase, R. A.; Li, L.

2017-12-01

How do watershed hydrologic processes differ in catchments derived from different lithology? This study compares two first order, deciduous forest watersheds in Pennsylvania, a sandstone watershed, Garner Run (GR, 1.34 km2), and a shale-derived watershed, Shale Hills (SH, 0.08 km2). Both watersheds are simulated using a combination of national datasets and field measurements, and a physics-based land surface hydrologic model, Flux-PIHM. We aim to evaluate the effects of lithology on watershed hydrology and assess if we can simulate a new watershed without intensive measurements, i.e., directly use calibration information from one watershed (SH) to reproduce hydrologic dynamics of another watershed (GR). Without any calibration, the model at GR based on national datasets and calibration inforamtion from SH cannot capture some discharge peaks or the baseflow during dry periods. The model prediction agrees well with the GR field discharge and soil moisture after calibrating the soil hydraulic parameters using the uncertainty based Hornberger-Spear-Young algorithm and the Latin Hypercube Sampling method. Agreeing with the field observation and national datasets, the difference in parameter values shows that the sandstone watershed has a larger averaged soil pore diameter, greater water storage created by porosity, lower water retention ability, and greater preferential flow. The water budget calculation shows that the riparian zone and the colluvial valley serves as buffer zones that stores water at GR. Using the same procedure, we compared Flux-PIHM simulations with and without a field measured surface boulder map at GR. When the boulder map is used, the prediction of areal averaged soil moisture is improved, without performing extra calibration. When calibrated separately, the cases with or without boulder map yield different calibration values, but their hydrologic predictions are similar, showing equifinality. The calibrated soil hydraulic parameter values in the with boulder map case is more physically plausible than the without boulder map case. We switched the topography and soil properties between GR and SH, and results indicate that the hydrologic processes are more sensitive to changes in domain topography than to changes in the soil properties.

Precipitation gradient determines the tradeoff between soil moisture and soil organic carbon, total nitrogen, and species richness in the Loess Plateau, China.

PubMed

Wang, Cong; Wang, Shuai; Fu, Bojie; Li, Zongshan; Wu, Xing; Tang, Qiang

2017-01-01

A tight coupling exists between biogeochemical cycles and water availability in drylands. However, studies regarding the coupling among soil moisture (SM), soil carbon/nitrogen, and plants are rare in the literature, and clarifying these relationships changing with climate gradient is challenging. Thus, soil organic carbon (SOC), total nitrogen (TN), and species richness (SR) were selected as soil-plant system variables, and the tradeoff relationships between SM and these variables and their variations along the precipitation gradient were quantified in the Loess Plateau, China. Results showed these variables increased linearly along the precipitation gradient in the woodland, shrubland, and grassland, respectively, except for the SR in the woodland and grassland, and SOC in the grassland (p>0.05). Correlation analysis showed that the SM-SOC and SM-TN tradeoffs were significantly correlated with mean annual precipitation (MAP) across the three vegetation types, and SM-SR tradeoff was significantly correlated with MAP in grassland and woodland. The linear piece-wise quantile regression was applied to determine the inflection points of these tradeoffs responses to the precipitation gradient. The inflection point for the SM-SOC tradeoff was detected at MAP=570mm; no inflection point was detected for SM-TN tradeoff; SM-SR tradeoff variation trends were different in the woodland and grassland, and the inflection points were detected at MAP=380mm and MAP=570mm, respectively. Before the turning point, constraint exerted by soil moisture on SOC and SR existed in the relatively arid regions, while the constraint disappears or is lessened in the relatively humid regions in this study. The results demonstrate the tradeoff revealed obvious trends along the precipitation gradient and were affected by vegetation type. Consequently, tradeoffs could be an ecological indicator and tool for restoration management in the Loess Plateau. In further study, the mechanism of how the tradeoff is affected by the precipitation gradient and vegetation type should be clarified. Copyright © 2016 Elsevier B.V. All rights reserved.

Mapping freeze/thaw boundaries with SMMR data

NASA Technical Reports Server (NTRS)

Zuerndorfer, B. W.; England, A. W.; Dobson, M. C.; Ulaby, F. T.

1989-01-01

Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) data are used to map daily freeze/thaw patterns in the upper Midwest for the Fall of 1984. The combination of a low 37 GHz radiobrightness and a negative 10.7, 18, and 37 GHz spectral gradient, Partial Derivative of Tb with Respect to f, appears to be an effective discriminant for classifying soil as frozen or thawed. The 37 GHz emissivity is less sensitive to soil moisture than are the lower frequency emissivities so that the 37 GHz radiobrightness appears to track soil surface temperature relatively well. The negative gradient for frozen ground is a consequence of volume scatter darkening at shorter microwave wavelengths. This shorter wavelength darkening is not seen in thawed moist soils.

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

NASA Astrophysics Data System (ADS)

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.

MAPPING SPATIAL ACCURACY AND ESTIMATING LANDSCAPE INDICATORS FROM THEMATIC LAND COVER MAPS USING FUZZY SET THEORY

EPA Science Inventory

This paper presents a fuzzy set-based method of mapping spatial accuracy of thematic map and computing several ecological indicators while taking into account spatial variation of accuracy associated with different land cover types and other factors (e.g., slope, soil type, etc.)...

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

NASA Astrophysics Data System (ADS)

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., (2011). Soil tillage erosion by using magnetism of soils - a case study from Bulgaria. Environ. Monit. Assess, 183, 381-394. Menshov O. Pereira P., Kruglov O., (2015). Spatial variability of soil magnetic susceptibility in an agricultural field located in Eastern Ukraine. Geophysical Research Abstracts, 17, EGU2015-578-2. Pereira, P., Cerdà, A., Úbeda, X., Mataix-Solera, J. Arcenegui, V., Zavala, L. (2015) Modelling the impacts of wildfire on ash thickness in a short-term period, Land Degradation and Development, 26, 180-192. DOI: 10.1002/ldr.2195

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

USDA-ARS?s Scientific Manuscript database

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

Soils maps supplement to soil moisture ground truth, Lafayette, Indiana, site St. Charles, Missouri, site

NASA Technical Reports Server (NTRS)

Jones, E. B.; Olt, S. E.

1975-01-01

A compilation of soils information obtained as the result of a library search of data on the Lafayette, Indiana, site and St. Charles, Missouri, site is presented. Soils data for the Lafayette, Indiana, site are shown in Plates 1 and 2; and soils data for the St. Charles, Missouri, site are shown in Plates 3 and 4.

Surface soil moisture retrieval using the L-band synthetic aperture radar onboard the Soil Moisture Active Passive satellite and evaluation at core validation sites

USDA-ARS?s Scientific Manuscript database

This paper evaluates the retrieval of soil moisture in the top 5-cm layer at 3-km spatial resolution using L-band dual-copolarized Soil Moisture Active Passive (SMAP) synthetic aperture radar (SAR) data that mapped the globe every three days from mid-April to early July, 2015. Surface soil moisture ...

Regional Characterization of Soil Properties via a Combination of Methods from Remote Sensing, Geophysics and Geopedology

NASA Astrophysics Data System (ADS)

Meyer, Uwe; Fries, Elke; Frei, Michaela

2016-04-01

Soil is one of the most precious resources on Earth. Preserving, using and enriching soils are most complex processes that fundamentally need a sound regional data base. Many countries lack this sort of extensive data or the existing data must be urgently updated when land use recently changed in major patterns. The project "RECHARBO" (Regional Characterization of Soil Properties) aims at the combination of methods from remote sensing, geophysics and geopedology in order to develop a new system to map soils on a regional scale in a quick and efficient manner. First tests will be performed on existing soil monitoring districts, using newly available sensing systems as well as established techniques. Especially hyperspectral and infrared data measured from satellites or airborne platforms shall be combined. Moreover, a systematic correlation between hyperspectral imagery and gamma-ray spectroscopy shall be established. These recordings will be compared and correlated to measurements upon ground and on soil samples to get hold of properties such as soil moisture, soil density, specific resistance plus analytic properties like clay content, anorganic background, organic matter etc. The goal is to generate a system that enables users to map soil patterns on a regional scale using airborne or satellite data and to fix their characteristics with only a limited number of soil samples.

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

NASA Astrophysics Data System (ADS)

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.

Postfire soil burn severity mapping with hyperspectral image unmixing

USGS Publications Warehouse

Robichaud, P.R.; Lewis, S.A.; Laes, D.Y.M.; Hudak, A.T.; Kokaly, R.F.; Zamudio, J.A.

2007-01-01

Burn severity is mapped after wildfires to evaluate immediate and long-term fire effects on the landscape. Remotely sensed hyperspectral imagery has the potential to provide important information about fine-scale ground cover components that are indicative of burn severity after large wildland fires. Airborne hyperspectral imagery and ground data were collected after the 2002 Hayman Fire in Colorado to assess the application of high resolution imagery for burn severity mapping and to compare it to standard burn severity mapping methods. Mixture Tuned Matched Filtering (MTMF), a partial spectral unmixing algorithm, was used to identify the spectral abundance of ash, soil, and scorched and green vegetation in the burned area. The overall performance of the MTMF for predicting the ground cover components was satisfactory (r2 = 0.21 to 0.48) based on a comparison to fractional ash, soil, and vegetation cover measured on ground validation plots. The relationship between Landsat-derived differenced Normalized Burn Ratio (dNBR) values and the ground data was also evaluated (r2 = 0.20 to 0.58) and found to be comparable to the MTMF. However, the quantitative information provided by the fine-scale hyperspectral imagery makes it possible to more accurately assess the effects of the fire on the soil surface by identifying discrete ground cover characteristics. These surface effects, especially soil and ash cover and the lack of any remaining vegetative cover, directly relate to potential postfire watershed response processes. ?? 2006 Elsevier Inc. All rights reserved.

The distribution of selected elements and minerals in soil of the conterminous United States

USGS Publications Warehouse

Woodruff, Laurel G.; Cannon, William F.; Smith, David; Solano, Federico

2015-01-01

In 2007, the U.S. Geological Survey initiated a low-density (1 site per 1600 km2, 4857 sites) geochemical and mineralogical survey of soil of the conterminous United States as part of the North American Soil Geochemical Landscapes Project. Three soil samples were collected, if possible, from each site; (1) a sample from a depth of 0 to 5 cm, (2) a composite of the soil A-horizon, and (3) a deeper sample from the soil C-horizon or, if the top of the C-horizon was at a depth greater than 100 cm, from a depth of approximately 80–100 cm. The < 2 mm fraction of each sample was analysed for a suite of 45 major and trace elements following near-total multi-acid digestion. The major mineralogical components in samples from the soil A- and C-horizons were determined by a quantitative X-ray diffraction method using Rietveld refinement. Sampling ended in 2010 and chemical and mineralogical analyses were completed in May 2013. Maps of the conterminous United States showing predicted element and mineral concentrations were interpolated from actual soil data for each soil sample type by an inverse distance weighted (IDW) technique using ArcGIS software. Regional- and national-scale map patterns for selected elements and minerals apparent in interpolated maps are described here in the context of soil-forming factors and possible human inputs. These patterns can be related to (1) soil parent materials, for example, in the distribution of quartz, (2) climate impacts, for example, in the distribution of feldspar and kaolinite, (3) soil age, for example, in the distribution of carbonate in young glacial deposits, and (4) possible anthropogenic loading of phosphorus (P) and lead (Pb) to surface soil. This new geochemical and mineralogical data set for the conterminous United States represents a major step forward from prior national-scale soil geochemistry data and provides a robust soil data framework for the United States now and into the future.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Spatially Resolved Carbon Isotope and Elemental Analyses of the Root-Rhizosphere-Soil System to Understand Below-ground Nutrient Interactions

NASA Astrophysics Data System (ADS)

Denis, E. H.; Ilhardt, P.; Tucker, A. E.; Huggett, N. L.; Rosnow, J. J.; Krogstad, E. J.; Moran, J.

2017-12-01

The intimate relationships between plant roots, rhizosphere, and soil are fostered by the release of organic compounds from the plant (through various forms of rhizodeposition) into soil and the simultaneous harvesting and delivery of inorganic nutrients from the soil to the plant. This project's main goal is to better understand the spatial controls on bi-directional nutrient exchange through the rhizosphere and how they impact overall plant health and productivity. Here, we present methods being developed to 1) spatially track the release and migration of plant-derived organics into the rhizosphere and soil and 2) map the local inorganic geochemical microenvironments within and surrounding the rhizosphere. Our studies focused on switchgrass microcosms containing soil from field plots at the Kellogg Biological Station (Hickory Corners, Michigan), which have been cropped with switchgrass for nearly a decade. We used a 13CO2 tracer to label our samples for both one and two diel cycles and tracked subsequent movement of labeled organic carbon using spatially specific δ13C analysis (with 50 µm resolution). The laser ablation-isotope ratio mass spectrometry (LA-IRMS) approach allowed us to map the extent of 13C-label migration into roots, rhizosphere, and surrounding soil. Preliminary results show the expected decrease of organic exudates with distance from a root and that finer roots (<0.1 mm) incorporated more 13C-label than thicker roots, which likely correlates to specific root growth rates. We are adapting both laser induced breakdown spectroscopy (LIBS) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) to spatially map inorganic nutrient content in the exact same samples used for LA-IRMS analysis. Both of these methods provide rapid surface mapping of a wide range of elements (with high dynamic range) at 150 μm spatial resolution. Preliminary results show that, based on elemental content, we can distinguish between roots, rhizosphere, soil, and specific types of mineral grains within soil. Integrating spatially resolved analysis of photosynthate distribution with local geochemical microenvironments may reveal key properties of nutrient exchange hotspots that help direct overall plant health and productivity.

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

NASA Astrophysics Data System (ADS)

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 <50-μm particle-size fractions followed by the measurement of char-carbon using 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.

DSM for soil erosion risk in Scotland

NASA Astrophysics Data System (ADS)

Poggio, Laura; Gimona, Alessandro; McLeaod, Jim; Castellazzi, Marie; Baggio Compagnucci, Andrea; Irvine, Justin

2017-04-01

Soils play a crucial role in ecosystem functioning, and modelling its risk of degradation is fundamental, especially in the context of climate change. In this work we used continuous 3D soil information derived from digital soil mapping (DSM) approaches to map sediment erosion and deposition patterns due to rainfall. The test area covers the whole of mainland Scotland, excluding the Northern Islands. Soil profiles data were interpolated using a geo-statistical hybrid Generalised Additive Models method for a range of soil properties such as organic matter, texture, soil depth and peat presence. The same method was used to interpolate climatic data and management information. Remote sensing data were integrated in the process and land use data included. Information on grazing (sheep and deer) pressure was taken into account in the modelling. The uncertainty was accounted and propagated across the whole process. The Scottish test case highlights the differences in roles between mineral and organic soils with an assessment adapted to each of them. The results and intermediate steps were compared with available continental scale results. The results show the importance of the use of DSM approaches for modeling soils and ecosystem functions and assessing uncertainty propagation.

SMAP Global Map of Surface Soil Moisture Aug. 25-27, 2015

NASA Image and Video Library

2015-09-02

A three-day composite global map of surface soil moisture as retrieved from NASA SMAP radiometer instrument between Aug. 25-27, 2015. Dry areas appear yellow/orange, such as the Sahara Desert, western Australia and the western U.S. Wet areas appear blue, representing the impacts of localized storms. White areas indicate snow, ice or frozen ground. http://photojournal.jpl.nasa.gov/catalog/PIA19877

Environmental Inventory Upper Cumberland River, Harlan, Kentucky.

DTIC Science & Technology

1981-12-01

presents a vicini- ty map for the area. The nearest major city is Knoxville, Tennessee, approxi- mately 140 miles southwest of the study area. Corbin...Harlan study area lies within the Cumberland Mountains section of the Ap- palachian Plateau Physiographic Province. This section has a topography typi...or unpublished mapping was available, instead a specific soils survey of the study area was implemented by the Soil Conser- vation Service (SCS) office

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

USGS Publications Warehouse

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

1994-01-01

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

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

NASA Astrophysics Data System (ADS)

Karthikeyan, L.; Kumar, D. Nagesh

2016-10-01

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

Soil erosion risk mapping: how to explain the stakeholders what lies behind?

NASA Astrophysics Data System (ADS)

Cerdan, Olivier; Degan, Francesca; Salvador-Blanes, Sebastien

2014-05-01

Recent demographic projections of the impact of global changes point to the need of increasing food and biomass production to meet expected global demand. This issue is particularly complex as it must comply with an increasing awareness that environmental quality must be preserved. Increased production can be achieved through either an intensification of agricultural practices or an increase of cultivated areas. In both cases, significant adverse effects are expected in terms of land degradation and its ability to maintain sustainable agricultural productivity. In this context, soil degradation vulnerability assessment is becoming more and more integrated in land management planning. Soil erosion being one of the major causes of soil degradation, the demand for soil erosion risk maps is increasing. However, the 2D representation of a process that shows strong non-linear dynamics in space and time is far from trivial. Important assumptions on the way to integrate these heterogeneities in time and space have to be made. How to integrate the crop rotation calendar and the climatic seasonal variability at the yearly scale? Or, how to characterise the erosion vulnerability of a geographical space that combines areas having different erosion risks? Moreover, other important questions arise with the resolution and the uncertainties associated with the available input data. And, last but not least, the final map needs, not only to integrate all these issues, but, more importantly, to be understandable by public managers. In this paper we illustrate the different difficulties inherent to soil erosion mapping, taking an example in different catchments of the Loire valley in France and present possible options to the spatial integration of both temporal and spatial variations in erosion risk.

Variation in photosynthetic and nonphotosynthetic vegetation along edaphic and compositional gradients in northwestern Amazonia

NASA Astrophysics Data System (ADS)

Higgins, M. A.; Asner, G. P.; Perez, E.; Elespuru, N.; Alonso, A.

2014-03-01

Tropical forests vary substantially in aboveground properties such as canopy height, canopy structure, and plant species composition, corresponding to underlying variations in soils and geology. Forest properties are often difficult to detect and map in the field, however, due to the remoteness and inaccessibility of these forests. Spectral mixture analysis of Landsat imagery allows mapping of photosynthetic and nonphotosynthetic vegetation quantities (PV and NPV), corresponding to biophysical properties such as canopy openness, forest productivity, and disturbance. Spectral unmixing has been used for applications ranging from deforestation monitoring to identifying burn scars from past fires, but little is known about variations in PV and NPV in intact rainforest. Here we use spectral unmixing of Landsat imagery to map PV and NPV in northern Amazonia, and to test their relationship to soils and plant species composition. To do this we sampled 117 sites crossing a geological boundary in northwestern Amazonia for soil cation concentrations and plant species composition. We then used the Carnegie Landsat Analysis System to map PV and NPV for these sites from multiple dates of Landsat imagery. We found that soil cation concentrations and plant species composition consistently explain a majority of the variation in remotely sensed PV and NPV values. After combining PV and NPV into a single variable (PV-NPV), we determined that the influence of soil properties on canopy properties was inseparable from the influence of plant species composition. In all cases, patterns in PV and NPV corresponded to underlying geological patterns. Our findings suggest that geology and soils regulate canopy PV and NPV values in intact tropical forest, possibly through changes in plant species composition.

Variation in photosynthetic and nonphotosynthetic vegetation along edaphic and compositional gradients in northwestern Amazonia

NASA Astrophysics Data System (ADS)

Higgins, M. A.; Asner, G. P.; Perez, E.; Elespuru, N.; Alonso, A.

2014-07-01

Tropical forests vary substantially in aboveground properties such as canopy height, canopy structure, and plant species composition, corresponding to underlying variations in soils and geology. Forest properties are often difficult to detect and map in the field, however, due to the remoteness and inaccessibility of these forests. Spectral mixture analysis of Landsat imagery allows mapping of photosynthetic and nonphotosynthetic vegetation quantities (PV and NPV), corresponding to biophysical properties such as canopy openness, forest productivity, and disturbance. Spectral unmixing has been used for applications ranging from deforestation monitoring to identifying burn scars from past fires, but little is known about variations in PV and NPV in intact rainforests. Here we use spectral unmixing of Landsat imagery to map PV and NPV in northern Amazonia, and to test their relationship to soils and plant species composition. To do this we sampled 117 sites crossing a geological boundary in northwestern Amazonia for soil cation concentrations and plant species composition. We then used the Carnegie Landsat Analysis System to map PV and NPV for these sites from multiple dates of Landsat imagery. We found that soil cation concentrations and plant species composition consistently explain a majority of the variation in remotely sensed PV and NPV values. After combining PV and NPV into a single variable (PV-NPV), we determined that the influence of soil properties on canopy properties was inseparable from the influence of plant species composition. In all cases, patterns in PV and NPV corresponded to underlying geological patterns. Our findings suggest that geology and soils regulate canopy PV and NPV values in intact tropical forests, possibly through changes in plant species composition.

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

ERIC Educational Resources Information Center

King, D.; And Others

1994-01-01

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

First forest soil survey gives significant results.

Treesearch

Robert F. Tarrant

1947-01-01

The first forest soil survey on national forest lands in the Pacific Northwest was completed last year on the Pringle Falls Experimental Forest when a detailed soil map covering four square miles was made by W.J. Leighty, Assistant Inspector, Bureau of Plant Industry, Soils and Agricultural Engineering. Arrangements for the survey were made by Region 6 of the Forest...

Validation of SMAP soil moisture for the SMAPVEX15 field campaign using a hyper-resolution model

USDA-ARS?s Scientific Manuscript database

Accurate global mapping of soil moisture is the goal of the Soil Moisture Active Passive (SMAP) mission, which is expected to improve the estimation of water, energy, and carbon exchanges between the land and the atmosphere. Like other satellite products, the SMAP soil moisture retrievals need to be...

Site Suitability Analysis for Dissemination of Salt-tolerant Rice Varieties in Southern Bangladesh

NASA Astrophysics Data System (ADS)

Sinha, D. D.; Singh, A. N.; Singh, U. S.

2014-11-01

Bangladesh is a country of 14.4 million ha geographical area and has a population density of more than 1100 persons per sq. km. Rice is the staple food crop, growing on about 72 % of the total cultivated land and continues to be the most important crop for food security of the country. A project "Sustainable Rice Seed Production and Delivery Systems for Southern Bangladesh" has been executed by the International Rice Research Institute (IRRI) in twenty southern districts of Bangladesh. These districts grow rice in about 2.9 million ha out of the country's total rice area of 11.3 million ha. The project aims at contributing to the Government of Bangladesh's efforts in improving national and household food security through enhanced and sustained productivity by using salinity-, submergence- and drought- tolerant and high yielding rice varieties. Out of the 20 project districts, 12 coastal districts are affected by the problem of soil salinity. The salt-affected area in Bangladesh has increased from about 0.83 million ha in 1973 to 1.02 million ha in 2000, and 1.05 million ha in 2009 due to the influence of cyclonic storms like "Sidr", "Laila" and others, leading to salt water intrusion in croplands. Three salinity-tolerant rice varieties have recently been bred by IRRI and field tested and released by the Bangladesh Rice Research Institute (BRRI) and Bangladesh Institute of Nuclear Agriculture (BINA). These varieties are BRRI dhan- 47 and Bina dhan-8 and - 10. However, they can tolerate soil salinity level up to EC 8-10 dSm-1, whereas the EC of soils in several areas are much higher. Therefore, a large scale dissemination of these varieties can be done only when a site suitability analysis of the area is carried out. The present study was taken up with the objective of preparing the site suitability of the salt-tolerant varieties for the salinity-affected districts of southern Bangladesh. Soil salinity map prepared by Soil Resources Development Institute of Bangladesh shows five classes of salinity. viz., non-saline with some very slight saline soil, very slightly saline with some slight saline soil, slightly saline with some moderately saline soil, strongly saline with some moderately saline soil, and very strongly saline with some strongly saline soil. The soil EC level of different classes range from 2 dSm-1 to >16 dSm-1. The soil map was geo-referenced and digitized using Arc GIS. Salinity tolerance characteristics of the rice varieties were matched with the soil characteristics shown on the map. Three suitability classes were made; soils suitable for salt-tolerant varieties, not suitable for salt-tolerant varieties due to high soil salinity, and suitable for other high yielding varieties due to slight salinity. The mauza (smallest revenue unit) boundary provided by the Bangladesh Agriculture Research Council was also geo-referenced and digitized in the same projection. Overlaying and intersecting the mauza boundary on the soil suitability map provided the suitable and not suitable mauza. A total of 4070 mauzas in the 12 salinity-affected districts were listed and maps showing suitability of mauza prepared. About 0.6 million ha out of total 0.87 million ha salinity affected area were found suitable for growing the salinity-tolerant BRRI dhan-47, Bina dhan-8 and -10 in these districts. The maps and other generated information have helped the Dept. of Agriculture Extension (DAE) of Bangladesh in large scale dissemination of seeds of the salinity-tolerant rice varieties in different districts during the past two years.

Remote Sensing Assessment of Soil Moisture, Soil Mineralogy and other Environmental Factors Influencing Mosquito-borne Infection Risks in the Lower Rio Grande Valley, U.S. - Mexico Border (Invited)

NASA Astrophysics Data System (ADS)

Hubbard, B. E.; Folger, H. W.; Page, W. R.

2010-12-01

A dengue fever outbreak occurred near Matamoros, Mexico along the Lower Rio Grande Valley during the summer of 2005 following heavy rainfall from Tropical Storm Gert and Hurricane Emily. This outbreak exemplifies the need for monitoring soil moisture and mapping soil permeability factors affecting the breeding and distribution of mosquito species capable of spreading disease. For example, the Rio Grande delta of South Texas and North Tamaulipas Mexico is inhabited by over 50 native and invasive species of mosquitoes capable of hosting Malaria, West Nile Virus and other types of human and livestock infecting Encephalitis. They range in ecological habitats from coastal salt marshes to freshwater riparian wetlands, tree holes and/or urban containers, flooded agricultural fields, and the many irrigation canals and ditches present throughout our study area. For this study, water-saturated and flooded soils were mapped using a “soil moisture availability” index (Mo) based on normalized difference vegetation index (NDVI) images and surface radiant and/or kinetic temperature images derived from multi-temporal Landsat-7 ETM+ and ASTER imagery. In particular, the Landsat-7 imagery covers ten cloud-free or minimal cloud cover acquisition dates during drought and wet periods of 2002, prior to the scan-line corrector failure in 2003. This includes one date (August 18, 2002) of co-orbital swath coverage between Landsat and ASTER, acquired after the land fall and dissipation of Tropical Storm Bertha (August 09, 2002). ASTER image dates used include those before and after the land fall of Hurricane Emily on July 20, 2005. The resulting maps show the distribution of relatively permeable (i.e. sandier) and impermeable soil types, the latter of which are dominated by clay-rich soils deposited in remnant interdistributary channels as channel-fill, and overbank flood deposits along the modern Rio Grande delta and portions of the (remapped) Pleistocene Beaumont coastal deltaic plain. Pools of standing rain water on impermeable soils can become ideal habitats for mosquito ovipositing and larval development between storms, which in turn can pose a higher risk for infection to humans and livestock animals. Because clay and other fine-grained minerals strongly affect a soil’s physical and chemical properties such as porosity, permeability and surface sealing/crusting upon saturation, 211 soil samples were collected at approximately 3-5 km sample spacing. The mineralogy of both the < 2 mm- and the < 2 micron-grain size fractions were then analyzed. The results show the distribution and relative abundance of kaolinite, illite and montmorillonite, for which we compare to ASTER remote sensing derived mineral maps based on drought period imagery (March 15, 2001), and airborne geophyisical data showing the distribution of radiometric K-bearing minerals (e.g. mainly illite/mica and orthoclase feldspar). The ASTER mineral maps show areas of clay-rich impermeable soils that are prone to ponding of standing water after storms. Our results show the utility of using remote sensing observations for mapping flood prone areas that may pose mosquito related health threats to both people and livestock on both sides of the border.

Global patterns of the isotopic composition of soil and plant nitrogen

USGS Publications Warehouse

Amundson, Ronald; Austin, A.T.; Schuur, E.A.G.; Yoo, K.; Matzek, V.; Kendall, C.; Uebersax, A.; Brenner, D.; Baisden, W.T.

2003-01-01

We compiled new and published data on the natural abundance N isotope composition (??15N values) of soil and plant organic matter from around the world. Across a broad range of climate and ecosystem types, we found that soil and plant ??15N values systematically decreased with increasing mean annual precipitation (MAP) and decreasing mean annual temperature (MAT). Because most undisturbed soils are near N steady state, the observations suggest that an increasing fraction of ecosystem N losses are 15N-depleted forms (NO3, N2O, etc.) with decreasing MAP and increasing MAT. Wetter and colder ecosystems appear to be more efficient in conserving and recycling mineral N. Globally, plant ??15N values are more negative than soils, but the difference Nitrogen isotopes reflect time integrated measures of the controls on N storage that are critical for predictions of how these ecosystems will respond to human-mediated disturbances of the global N cycle.

Application of remote sensing to estimating soil erosion potential

NASA Technical Reports Server (NTRS)

Morris-Jones, D. R.; Kiefer, R. W.

1980-01-01

A variety of remote sensing data sources and interpretation techniques has been tested in a 6136 hectare watershed with agricultural, forest and urban land cover to determine the relative utility of alternative aerial photographic data sources for gathering the desired land use/land cover data. The principal photographic data sources are high altitude 9 x 9 inch color infrared photos at 1:120,000 and 1:60,000 and multi-date medium altitude color and color infrared photos at 1:60,000. Principal data for estimating soil erosion potential include precipitation, soil, slope, crop, crop practice, and land use/land cover data derived from topographic maps, soil maps, and remote sensing. A computer-based geographic information system organized on a one-hectare grid cell basis is used to store and quantify the information collected using different data sources and interpretation techniques. Research results are compared with traditional Universal Soil Loss Equation field survey methods.

Selenium in soils of the Lower Wasatch Formation, Campbell County, Wyoming: Geochemistry, distribution, and environmental hazards

NASA Technical Reports Server (NTRS)

Kolm, K. E.

1975-01-01

The author has identified the following significant results. Seleniferous Shingle series soils and sandstone outcrops of section 27, T 48 N, R 71 W, Wyoming are mapped on aerial photography by their association with Astragalus bisulcatus. Chemical leachate analyses and atomic absorption methods reveal all studied Samsil and Shingle soils to contain acid, base, and water soluble selenium compounds, and that water extractions showed varied concentration behavior due to soil pH. Acid-soluble selenium is found to be associated with smectite. Statistical analyses confirm that A. bisulcatus presence has a weak influence on soil-lens organic selenium concentration, and determine the importance of other geobotanical factors for convertor presence. Environmental procedures of high selenium lens burial, convertor plant eradication, and revegetated site monitoring are recommended. Usage of density analysis and photographic enlargement are used to successfully produce both a control area and a Campbell County, Wyoming regional map of A. bisulcatus supportive soils and outcrops using Skylab photography.

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

NASA Astrophysics Data System (ADS)

Sahakyan, Lilit; Saghetalyan, Armen; Asmaryan, Shushanik

2010-05-01

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

Crowdsourcing Austrian data on decomposition with the help of citizen scientists

NASA Astrophysics Data System (ADS)

Sandén, Taru; Berthold, Helene; Schwarz, Michael; Baumgarten, Andreas; Spiegel, Heide

2017-04-01

Decay of organic material, decomposition, is a critical process for life on earth. Through decomposition, food becomes available for plants and soil organisms that they use in their growth and maintenance. When plant material decomposes, it loses weight and releases the greenhouse gas carbon dioxide (CO2) into the atmosphere. Terrestrial soils contain about three times more carbon than the atmosphere and, therefore, changes in the balance of soil carbon storage and release can significantly amplify or attenuate global warming. Many factors affecting the global carbon cycle are already known and mapped; however, an index for decomposition rate is still missing, even though it is needed for climate modelling. The Tea Bag Index (TBI) measures decomposition in a standardised, achievable, climate-relevant, and time-relevant way by burying commercial nylon tea bags in soils for three months (Keuskamp et al., 2013). In the summer of 2016, TBI (expressed as decomposition rate (k) and stabilisation index (S)) was measured with the help of Austrian citizen scientists at 7-8 cm soil depth in three different land uses (maize croplands, grasslands and forests). In total ca. 2700 tea bags were sent to the citizen scientists of which ca. 50% were returned. The data generated by the citizen scientists will be incorporated into an Austrian as well as a global soil map of decomposition. This map can be used as input to improve climate modelling in the future.

Soil Parameter Mapping and Ad Hoc Power Analysis to Increase Blocking Efficiency Prior to Establishing a Long-Term Field Experiment

PubMed Central

Collins, Doug; Benedict, Chris; Bary, Andy; Cogger, Craig

2015-01-01

The spatial heterogeneity of soil and weed populations poses a challenge to researchers. Unlike aboveground variability, below-ground variability is more difficult to discern without a strategic soil sampling pattern. While blocking is commonly used to control environmental variation, this strategy is rarely informed by data about current soil conditions. Fifty georeferenced sites were located in a 0.65 ha area prior to establishing a long-term field experiment. Soil organic matter (OM) and weed seed bank populations were analyzed at each site and the spatial structure was modeled with semivariograms and interpolated with kriging to map the surface. These maps were used to formulate three strategic blocking patterns and the efficiency of each pattern was compared to a completely randomized design and a west to east model not informed by soil variability. Compared to OM, weeds were more variable across the landscape and had a shorter range of autocorrelation, and models to increase blocking efficiency resulted in less increase in power. Weeds and OM were not correlated, so no model examined improved power equally for both parameters. Compared to the west to east blocking pattern, the final blocking pattern chosen resulted in a 7-fold increase in power for OM and a 36% increase in power for weeds. PMID:26247056