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International Journal
of Ecology &
Development |
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ISSN 0972-9984 ( Print
); ISSN 0973-7308 (Online) |
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Abstract |
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Volume 8 |
No. F07 |
Fall 2007 |
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Spatial Variability and Topographic Factors of 137Cs Soil
Contamination at a Field Scale
V.G. Linnik 1, A.A. Saveliev 2,
A.P. Govorun 3, O.M. Ivanitsky 1, A.V. Sokolov 1 1 Vernadsky
Institute of Geochemistry and Analytical Chemistry Russian Academy of Sciences Kosygin
Street 19, Moscow, 117975, Russia 2 Faculty of Ecology, Kazan State University 18 Kremlevskaja
street, Kazan, 420008, Russia 3 RECOM Ltd, Russian Research Centre 'Kurchatov Institute’ Kurchatov Sq. 1, 123182, Moscow, Russia ABSTRACT
The spatial variability of 137Cs contamination was evaluated at a field
scale, at three study sites marked by different landscape positions. Two of
them are situated in a forest, and one – in a meadow. The sites are located
170 km away from the Chernobyl Nuclear Power Plant. The objectives of the
research were (a) to characterise variability of 137Cs contamination across the sites, and
(b) to determine and describe any relation of 137Cs contamination with topography. Soil
radioactive contamination was measured using in situ radiometric technique. Field radiometry data were analysed using
classical statistics and geostatistics. To describe
local geometry of the sites, Laplacian models were
derived from digital elevation models. A generalised
additive model was used to
model the dependence of 137Cs spatial distribution on the relief
features. For hydromorphic
areas of the sites, the variogram analysis showed that the 137Cs spatial distribution consists in patchy patterns
with the typical size from meters to tens of meters. For watershed areas, the
137Cs spatial distribution was random and did
not form any patterns. The 137Cs distribution is depend
crucially on the local topography in hydromorphic
conditions. Laplacian is the most
informative index for the process of the 137Cs lateral migration
while elevation is of subsidiary importance. Keywords: Field Radiometry,
Radionuclide, Geostatistics, 137Cs,
Spatial Variation, Generalized Additive Model, Digital Elevation Model, Laplacian. Mathematics Subject Classification: 62P12, 62H99, 86A32. JEL Classification: Q19, Q50. |
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Comparison of Automated Landform Classification
and Soil Mapping Units at a Farm Level
Vanda
Valerija Buivydaite 1,
Gintautas Mozgeris 2 1 Department of Soil Science & Agrochemistry, Agronomic Faculty Lithuanian University of Agriculture Studentu St. 11, LT–53361 Akademija, Kaunas R., Lithuania 2 GIS Education and Research Centre,
Institute of Environment Lithuanian
University of Agriculture Studentu St. 13, LT–53361 Akademija, Kaunas R., Lithuania ABSTRACT
More than twenty morphometric
attributes derived from digital elevation models (DEMs)
were correlated with soil mapping units available from conventional soil maps
at a scale of 1 : 2,000. The following
topographic attributes were involved into the analysis: slope steepness,
slope aspect, elevation, horizontal curvature, vertical curvature, mean
curvature, surface insolation, maximal curvature,
minimal curvature, catchment area, depression
depths, dispersal area, hill heights, gradient factor, difference curvature,
horizontal and vertical excess curvatures, rotor, unsphericity,
total Gaussian curvature, total accumulation curvature, total ring curvature,
and topographic index. A DEM with a grid size of 30 m was best suited to
describe the relationships between soil units and terrain variables. Soil
typological units and their classes correlated stronger with the landform
types derived using the Shary landform
classification (the contingency coefficients were over 0.6) rather than the Troeh and Gauss landform classifications. Mean and
horizontal curvatures, elevation, slope, gradient factor, and topographic
index were best correlated with the soil typological units of the soil
classification system of Lithuania, which is based on the international soil
classification. Keywords: Soil Map, Digital Elevation
Model, Morphometric Variable, Landform Type. Mathematics Subject Classification: 86A30, 62P12, 62H30, 62H99. JEL Classification: Q19, Q50. |
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A Study of Disturbed Soil Cover using Soil
Electrical Resistivity and Topographic Data
V.
P. Samsonova 1, A. I. Pozdnyakov, J. L. Meshalkina 2 Faculty of Soil Science Moscow State University Leninskie Gory, Moscow, 119992, Russia ABSTRACT
The soil maps are overwhelmingly created
using topographic data as secondary information. Under the condition of
anthropogenic pressure on territories, connections ‘topography-soils’ may be
weakened. The research was focused on the terrain of Bryansk
Opolje, one of the ancient agricultural areas in
Russia. The soil cover disturbance is seen in a number of places because of
continuous cultivation, erosion, and reclamation. The main types of soils are
grey forest soils and grey forest soils with the second humus horizons. The
traditional soil mapping has been performed on the 16-hectare field. The
electrical resistivity has been measured at nodes
of the sampling grid with the grid size of 25 m. The additional measurements
were done using four transects with a 5 m distance crossing various landscape
positions. A topographic map at the scale of 1 : 5,000
was digitised to produce a digital elevation model (DEM). Slope steepness,
slope aspect, profile curvature, tangential curvature, and Laplacian were derived from the DEM. Electrical resistivity was closely linked with soil classification
areas, which was proved by the one-way ANOVA. For the entire field, none of
the topographic attributes was totally connected with either soil
distributions or electrical resistivity. At the
same time, connections between terrain attributes and electrical resistivity are clearly expressed for some parts of the
study area. In the case of reclaimed territories, where connections between
relief and soils may be disturbed to a considerable degree, electrophysical methods may be informative for the soil
mapping purposes. Keywords: Electrical Resistivity, Spatial Variability, Soil Properties,
Topography, Precision Agriculture, Digital Elevation Model. Mathematics Subject Classification: 62P12, 86A25, 86A32. JEL Classification: Q19, Q50. |
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Solving Three Problems of Exploration and
Engineering Geology by Digital Terrain Analysis
I.V. Florinsky Institute of Mathematical Problems of
Biology Russian Academy of Sciences Pushchino, Moscow Region, 142290, Russia ABSTRACT
In the smooth-surface approximation, local
accumulation of a flow is controlled by relative deceleration and
convergence. Flow deceleration is determined by vertical curvature of the
land surface, while flow convergence is controlled by horizontal curvature.
There is a concurrent action of flow convergence and relative deceleration at
areas marked by negative values of both of these curvatures. These areas are
said to be relative accumulation
zones. We describe basic principles of applying maps of relative
accumulation zones to solve three problems of exploration and engineering
geology: (1) exploration of alluvial placers; (2) prediction of landsliding on reservoir shores; and (3) prediction
of soil degradation and contamination along pipelines. The deposition of
placer minerals is most likely to occur in relative accumulation zones with
slope steepness below 3°, all other factors being equal. The activation of
slope instability is most probably to occur in relative accumulation zones
with slope steepness beyond 15°, which are adjacent to, upslope the reservoir
water level. Soil degradation (waterlogging and salinisation) may be observed in relative accumulation
zones adjacent to, upslope a pipeline. After the pipeline failure, one can
use a map of specific catchment area to determine
paths of lateral migration of petroleum in the landscape. Petroleum products
are most likely to concentrate in relative accumulation zones situated along
a flow line originating at a pipeline hole. To refine the prediction, one
should analyse accumulation zone maps together with geological, geophysical,
geochemical, soil, plant, and remotely sensed data as well as with models of
other topographic variables. Keywords: Digital Terrain Model,
Accumulation, Placer, Reservoir, Landslide, Pipeline, Soil, Degradation,
Contamination. Mathematics Subject Classification: 62H99, 62P12, 86A05, 86A60, 86A30. JEL Classification: Q19, Q50. |
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Vertical Accuracy of Shuttle Radar Topography
Mission (SRTM) Elevation and Void-Filled Data in the Libyan Desert
Paul Elsner 1, Michael Bonnici 2 School of Geography Birkbeck College, University of London Malet
Street, London WC1E 7HX, UK ABSTRACT
Elevation data produced by NASA’s Shuttle
Radar Topography Mission (SRTM) is currently the most detailed publicly
available, free-of-cost, near-global digital elevation model (DEM). While
generally very successful in collecting complete and accurate elevation data,
the mission C-band Radar had limitations over specific landscapes, including
sand deserts. This paper presents the results of a validation study using
data from ground surveys in the Libyan Sahara. It tests (a) the accuracy
of finished Level 2 SRTM DEM data; and (b) the performance of an
interpolation procedure that is routinely applied to fill SRTM data voids on
a global scale. The results show that SRTM data consistently meets its own
accuracy specifications, with a root mean square error (RMSE) of 1.3 to 5.2
m. Interpolated void-filled data achieved lower accuracy, with RMSE of
approximately 7 m for an area of smaller dunes, and RMSE of 14 m within an
extensive field of strongly undulating dunes with heights of more than 100 m,
meaning that the accuracy specification of SRTM data in this area is not met.
It is concluded that void-filling by interpolation in areas of extensive dune
fields does not reproduce the representative topography of such a landscape,
and spatially higher resolved elevation data is needed to achieve this via
interpolation. Keywords: Shuttle Radar
Topography Mission, SRTM, Digital Elevation Model, Sahara, Validation,
Accuracy Assessment. Mathematics Subject Classification: 65G99, 62H35, 86A30, 65D05. JEL Classification: Q19, Q50. |
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Filtering of Digital Terrain Models by Two‑Dimensional
Singular Spectrum Analysis
N.E. Golyandina 1, K.D. Usevich 1, I.V. Florinsky 2 1 Department of
Statistical Modelling St.-Petersburg
State University University
pr. 28, Petrodvoretz, St.-Petersburg, 198504,
Russia 2 Institute of Mathematical Problems
of Biology Russian Academy of Sciences Pushchino, Moscow Region, 142290, Russia ABSTRACT
Singular Spectrum Analysis (SSA) has been
approved as a model-free technique to analyse time series. SSA can solve
different problems such as decomposition into a sum of trend, periodicities,
and noise, smoothing, and others. In this paper, we validate abilities of
2D-SSA (the extension of SSA to analyse two-dimensional scalar fields) to
treat digital terrain models (DTMs). The study is
exemplified by a 30-arc-second digital elevation model of a part of South
America derived from GTOPO30. Results demonstrate that 2D-SSA is an efficient
method to denoise and generalise DTMs. It can be also used to decompose a topographic
surface into components of continental, regional, and local scales. Keywords: Digital Elevation Model,
Singular Spectrum Analysis, Image Processing, Filtering, Periodicity, Noise. Mathematics Subject Classification: 62H35, 68U10, 62M15, 93E14, 93E11, 86A30, 86A60 JEL Classification: Q19, Q50. |
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