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.
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, military engineering activities, blowing dust and sand, watershed responses, and flooding. This study explores
a novel 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 sensors for
Improvised Explosive Devices (IEDs) using the Countermine Simulation Test Bed in regions where access is denied.
The method has been tested in Helmand Province, Afghanistan, using a Landsat7 and a QuickBird image of April 23 and
24, 2009, respectively. The first implementation of the method yielded promising results.
Soil moisture conditions influence practically all aspects of Army activities and are increasingly affecting its systems and
operations. Regional distributions of high resolution soil moisture data will provide critical information on operational
mobility, performance of landmine and UXO sensors, and meteorological conditions at the km scale. The objective of
this study is to calibrate RADARSAT-2 surface soil moisture estimates with field measurements in the semi-arid Middle
Rio Grande Valley of New Mexico. RADARSAT-2 was launched in December 2007 and is the first SAR sensor to offer
an operational quad-polarization mode. This mode allows to generate soil moisture (and cm-scale surface roughness)
maps from single data sets. Future combination of such maps into time series will lead to further accuracy enhancement
through additional exploitation of soil moisture evolution constraints. We present RADARSAT-2 soil moisture maps,
field soil moisture measurements, and soil moisture maps derived from optical imagery. In addition, future work is
proposed that may contribute to enhanced algorithms for soil moisture mapping using RADARSAT-2.
A thorough understanding of thermal soil regimes is critical information for a wide variety of disciplines
and engineering applications as well as for the evaluation of potential and limitations of thermal and optical
sensors. In this study we have developed a procedure for the evaluation of global thermal soil regimes.
First, pedotransfer functions are used to derive thermal soil properties (volumetric soil heat capacity and
thermal conductivity) from readily available soil data on texture, bulk density, and organic carbon. Next,
the average annual soil temperature is derived from the average annual air temperature. Then, the thermal
top boundaries are derived either for well-watered sites using the daily and annual air temperature
amplitudes as proxies for the daily and annual soil surface temperature amplitudes or for a wide range of
environmental conditions using the model HYDRUS1D. A thorough validation of the proposed procedure
is needed for the quantification of the probability with which soil thermal regimes can be predicted.
Modeling studies and experimental work have demonstrated that the dynamic behavior of soil physical properties has a significant effect on most sensors for the detection of buried land mines. An outdoor test site has been constructed allowing full control over soil water content and continuous monitoring of important soil properties and environmental conditions. Time domain reflectometry sensors and thermistors measure soil water1 content and temperature, respectively, at different depths above and below the land mines as well as in homogeneous soil away from the land mines. During the two-year operation of the test-site, the soils have evolved to reflect real field soil conditions. This paper compares visual observations as well as ground-penetrating radar and thermal infrared measurements at this site taken immediately after construction in early 2004 with measurements from early 2006. The visual observations reveal that the 2006 soil surfaces exhibit a much higher spatial variability due to the development of mini-reliefs, "loose" and "connected" soil crusts, cracks in clay soils, and vegetation. Evidence is presented that the increased variability of soil surface characteristics leads to a higher natural spatial variability of soil surface temperatures and, thus, to a lower probability to detect landmines using thermal imagery. No evidence was found that the soil surface changes affect the GPR signatures of landmines under the soil conditions encountered in this study. The New Mexico Tech outdoor Landmine Detection Sensor Test Facility is easily accessible and anyone interested is welcome to use it for sensor testing.
In this paper we present the results of recent field and laboratory studies of the mineralogy and magnetic properties of
young and/or weakly developed soils in Montana and California. The Chevallier Ranch UXO site in Montana is
characterized by a basaltic plug and radiating feeder dikes, which is found surrounded by shales of the Spokane
Formation. The site in California consists of an offset alluvial fan soil chronosequence of Little Rock Creek along the
Mojave section of the San Andreas fault. The fan sediments include significant amounts of mafic material. The fan ages
range from 16 to 413 thousand years. The results of magnetic susceptibility measurements and laboratory analysis of
mineralogy demonstrate that the magnetic susceptibility in these soils is predominantly correlated with parent material
and less with age or landscape position. Slow rates of soil forming processes lead to relatively low frequency dependence
in magnetic susceptibility as compared to similar-age soils in tropical environments. The magnetic character of the soils
can be accurately predicted with a previously developed model.
Ferrimagnetic minerals such as magnetite and maghaemite can affect ground-penetrating radar (GPR) signals. This may
lead to false alarms and missed targets when surveying for the detection of buried landmines and unexploded ordnance
(UXO). In most field situations ferrimagnetic mineral content is too low to affect GPR wave behavior. However, in soils
and sedimentary material with magnetite-rich parent material large concentrations of magnetite can be found. This paper
is a first systematic experimental effort to study the effects of large concentrations of magnetite for GPR detection of
subsurface targets. We study the effects of (i) different homogeneous mixtures of magnetite and quartz sand and (ii)
magnetite concentrated in layers (placer deposits), on the propagation behavior of GPR waves and reflection
characteristics of steel and plastic balls. The balls are buried in homogeneous mixtures of magnetite and quartz sand and
below a layer of pure magnetite. Important observations include that the simulated placer deposits did have a large effect
on the detectability of balls below the placer deposits and that homogeneous mixtures had no significant effect.
In recent years it has become apparent that the performance of detection sensors for land mines and UXO may be seriously hampered by the magnetic behavior of soils. In tropical soils it is common to find large concentrations of iron oxide minerals, which are the predominant cause for soil magnetism. However, a wide range of factors such as parent material, environmental conditions, soil age, and drainage conditions control soil development. In order to predict whether magnetic-type iron oxide minerals are present it is important to understand the controlling factors of soil development. In this paper we present a conceptual model for predicting magnetic soil characteristics as a function of geological and environmental information. Our model is based on field observations and laboratory measurements of soils from Hawaii, Ghana, and Panama. The conceptual model will lead to the development of pedotransfer functions that quantitatively predict the occurrence and nature of magnetism in soils.
Magnetic soils can seriously hamper the performance of electromagnetic sensors for the detection of buried land mines and unexploded ordnance (UXO). Soils formed on basaltic substrates commonly have large concentrations of ferrimagnetic iron oxide minerals, which are the main cause of soil magnetic behavior. Previous work has shown that viscous remanent magnetism (VRM) in particular, which is caused by the presence of ferrimagnetic minerals of different sizes and shapes, poses a large problem for electromagnetic surveys. The causes of the variability in magnetic soil properties in general and VRM in particular are not well understood. In this paper we present the results of laboratory studies of soil magnetic properties on three Hawaiian Islands: O’ahu, Kaho’olawe, and Hawaii. The data show a strong negative correlation between mean annual precipitation and induced magnetization, and a positive correlation between mean annual precipitation and the frequency dependent magnetic behavior. Soil erosion, which reduces the thickness of the soil cover, also influences the magnetic properties.
In this paper we present the results of a study of some soil magnetic properties in Ghana. The soils sampled formed in different parent materials: Granites, Birimian rocks, and Voltaian sandstones. We discuss the role of environmental controls such as parent material, soil drainage, and precipitation on the magnetic properties. The main conclusion of this reconnaissance study is that the eight different soil types sampled have their own unique magnetic signature. Future research will have to confirm whether this conclusion holds for other soils in Ghana. If it does, the measurement of magnetic soil properties may become a viable complement for the investigation of soil erosion, land degeneration, and pedogenesis. The magnetic soil properties measured would probably not pose any limitations for the use of electromagnetic sensors for the detection of land mines and UXO.
Electromagnetic sensors such as ground penetrating radar and electromagnetic induction sensors are among the most widely used methods for the detection of buried land mines and unexploded ordnance. However, the performance of these sensors depends on the dielectric properties of the soil, which in turn are related to soil properties such as texture, bulk density, and water content. To predict the performance of electromagnetic sensors it is common to estimate the soil dielectric properties using models. However, the wide variety of available models, each with its own characteristics, makes it difficult to select the appropriate one for each occasion. In this paper we present an overview of the available methods, ranging from phenomenological Cole-Cole and Debye models to volume-based dielectric mixing models, and (semi-) empirical pedotransfer functions.
Remotely sensed images of the Earth’s surface provide information about the spatial distribution of evapotranspiration. Since the spatial resolution of evapotranspiration predictions depends on the sensor type; scaling transfer between images of different scales needs to be investigated. The objectives of this study are first to validate the consistency of SEBAL algorithms for satellite images of different scales and second to investigate the effect of up- and down-scaling procedures between evapotranspiration maps derived from LandSat 7 and MODIS images. The results of this study demonstrate: (1) good agreement of SEBAL evapotranspiration estimates between LandSat 7 and MODIS images; (2) up- and down-scaled evapotranspiration maps over the Middle Rio Grande Basin are very similar to evapotranspiration maps directly derived from LandSat 7 and MODIS images.
Previous modeling studies and experimental work have demonstrated that soil physical properties have a significant effect on most sensors for the detection of buried land mines. While a modeling approach allows for testing of the effects of a wide range of soil variables, most experimental work is limited to (field) soils with poorly known or controlled properties. With this in mind, we constructed a new outdoor test site with full control of soil water content and continuous monitoring of important soil properties and environmental conditions. In three wooden frames of 2 x 2 x 1 meter, filled with different soil types (sand, loam, and clay), we buried low-metal anti-tank and anti-personnel land mine simulants. We installed time domain reflectometry (for measurement of soil water content) and temperature probes at different depths above and below the land mines as well as in homogeneous soil away from the land mines. In this paper we document the features of this new test site and present results from the monitoring equipment.
Thermal signatures of buried land mines depend on a complex combination of environmental conditions, soil properties, and properties and burial depth of the land mine. Due to the complex nature of the problem most modeling and experimental efforts to understand thermal signatures of land mines have focused on the effects of one or a few variables. Of these variables, the effect of wind speed has received little attention in modeling and experimental studies. In this contribution we discuss the role of wind in the generation of thermal images and we present results of field experiments at the outdoor land mine detection test facility at New Mexico Tech. Here, several anti-tank and anti-personnel land mine simulants have been buried in sand, loam, and clay soils. During the measurements the environmental and soil conditions were continuously monitored using a fully equipped weather station and using probes for measurements of soil temperature and soil water content.
In previous work we have shown that GPR signatures are affected by
soil texture and soil water content. In this contribution we will
use a three dimensional electromagnetic model and a hydrological
soil model to explore in more detail the relationships between GPR
signatures, soil physical conditions and GPR detection performance.
First, we will use the HYDRUS2D hydrological model to calculate a
soil water content distribution around a land-mine. This model has
been verified against measured soil water distributions in previous
work. Next, we will use existing pedotransfer functions (e.g. Topp,
Peplinski, Dobson, Ulaby) to convert the predicted soil water
contents around the land-mines as well as known soil textures and
bulk densities into soil parameters relevant to the electromagnetic
behaviour of the soil medium. This will enable a mapping between the
hydrological model and the electromagnetic GPR model. Using existing
and new laboratory and field measurements from the land-mine test
facilities at TNO-FEL we will make a first attempt to verify our
modelling approach for the prediction of GPR signatures in field
soils. Finally a detection algorithm is used to evaluate the GPR
detection performance with respect to changing environmental soil
The presence of magnetic iron oxides in the soil can seriously hamper the performance of electromagnetic sensors for the detection of buried land mines and unexploded ordnance (UXO). Previous work has shown that spatial variability in soil water content and texture affects the performance of ground penetrating radar and thermal sensors for land mine detection. In this paper we aim to study the spatial variability of iron oxides in tropical soils and the possible effect on electromagnetic induction sensors for buried low-metal land mine and UXO detection. We selected field sites in Panama, Hawaii, and Ghana. Along several horizontal transects in Panama and Hawaii we took closely spaced magnetic susceptibility readings using Bartington MS2D and MS2F sensors. In addition to the field measurements, we took soil samples from the selected sites for laboratory measurements of dual frequency magnetic susceptibility and textural characteristics of the material. The magnetic susceptibility values show a significant spatial variation in susceptibility and are comparable to values reported to hamper the operation of metal detectors in parts of Africa and Asia. The absolute values of susceptibility do not correlate with both frequency dependence and total iron content, which is an indication of the presence of different types of iron oxides in the studied material.
Ground penetrating radar and thermal sensors hold much promise for the detection of non-metallic land mines. In previous work we have shown that the performance of ground penetrating radar strongly depends on field soil conditions such as texture, water content, and soil-water salinity since these soil parameters determine the dielectric soil properties. From soil physics and field measurements we know that the performance of thermal sensors also strongly depends on soil texture and water content. There is it critical that field soil conditions are taken into account when radar and thermal sensors are employed. The objectives of this contribution are (i) to make an inventory of readily available soil data bases world wide and (ii) to investigate how the information contained in these data bases can be used for derivation of soil dielectric and thermal properties relevant for operation of land mine sensors.
Thermal sensors hold much promise for the detection of non-metallic landmines. However, the prediction of their thermal signatures depends on a large number of factors. In this paper, an analytical solution for temperature propagation through homogeneous and layered soils is presented to predict surface temperatures as a function of soil heat flux amplitude, soil texture, soil water content, and thermal properties and burial depth of the landmine. Comparison with the numerical model HYDRUS-2D shows that the relatively simple analytical solution proposed here is reasonably accurate. The results show that an increase in soil water content has a significant effect on the thermal signature, as well as on the phase shift of the maximum temperature difference. Different soil textures have relatively little effect on the temperature at the surface. The thermal properties of the mine itself can play a significant role. It is shown that for most soils 10 cm is the maximum burial depth to produce a significant thermal signature at the surface.
Soil surface temperatures not only exhibit daily and annual cycles but also are very variable in space and time. Without knowledge of the spatial and temporal variability of soil surface temperatures, it will be difficult to determine what times of day are most suitable for mine detection using Thermal Infra Red (TIR) technology. In this study we monitor the spatial and temporal variability of soil surface temperatures under a range of soil texture and soil moisture conditions on undisturbed plots and plots with a buried anti-tank mine in arid New Mexico. We also analyzed soil surface temperature measurements taken at the test facility for land mine detection systems at the TNO Physics and Electronics Laboratory under the temperate climatic conditions of The Netherlands. The measurements in both areas show a cyclic behavior of the thermal signatures of the mines during the day and night that can be predicted by physics of the mine-soil-sensor system. However, unexpected behavior of the thermal signatures in a silt loam demonstrated that prediction of thermal signatures of buried mines is not straightforward.
The contrast in relative dielectric constant between landmines and the surrounding soil is one of the most important elements for radar detection purposes. For most geologic materials the relative dielectric constant lies within the range of 3-30, with dry sand at the lower end of this range at about 3-5. Nonmetallic landmines have a dielectric constant range of 3.2-9.8 whereas metallic landmines have a much higher relative dielectric constant. In previous work, literature data were used to compose a MATLAB model that determines whether or not field conditions are appropriate for use of GPR instruments. This model has been verified for dry and moist sand, silt, and clay soils in New Mexico. The objective of this paper is to validate this model over a wider range of soil texture and soil moisture conditions. Therefore, GPR measurements will be taken on experimental test facilities for landmine detection at Yuma Proving Grounds in Arizona and at the TNO Physics and Electronics Laboratory in The Netherlands. These facilities cover a wide range of soil textures from ferruginous sand to clay and peat as well as many levels of soil moisture.
Most mine detection sensors are affected by soil properties such as water content, temperature, electrical conductivity, and dielectric constant. The most important of these is water content since it directly influences the three other properties. The variability of these properties may be such that either potential landmine signatures are overshadowed or false alarms result. In this paper we present the results of field measurements in the Netherlands, Panama, and New Mexico on spatial variability of soil water content. We also discuss how the variability of soil water content affects the soils electrical conductivity and dielectric constant and the resulting response of a ground penetrating radar system.
Land mines are a major problem in many areas of the world. In spite of the fact that many different types of land mines sensors have been developed, the detection of non-metallic land mines remains very difficult. Most landmine detection sensors are affected by soil properties such as water content, temperature, electrical conductivity and dielectric constant. The most important of these is water content since it directly influences the three other properties. In this study, the ground penetrating radar and thermal IR sensors were used to identify non-metallic landmines in different soil and water content conditions.
The objective of this study is to expand our exploration of the effects of the soil environment on landmine detection by investigating the influence of soil texture and water content on surface soil temperatures above antitank mines buried at 15 cm depth and away from it. Temperature distributions in July were calculated in six soil textures for the climatic conditions of Kuwait and Sarajevo. We evaluated the temperature distributions in typical dry and wet soil profiles. The simulated temperature differences varied from .22-.63 degree Celsius in Kuwait to .16-.37 in Sarajevo. Temperature differences were - with one exception - larger in the wet than in the dry soils which suggests that soil watering may help improve thermal signatures. A major finding of this study is that the thermal signature of an anti tank mine strongly depends on the complex interaction between soil texture, water content, and geographical location. It is very difficult to predict the exact time or even the approximate hour of the appearance or nonappearance of a thermal signature. Therefore, this modeling study indicates that the use of a thermal sensor in a real mine field for instantaneous mine detection carries a high risk. On the other hand if a given area can b monitored constantly with a thermal sensor for twelve hours or longer the thermal signature will be detected if the signal to noise ratio of the mine environment allows so. Field experiments are needed to validate the results of this modeling study.
The complex dielectric constant of the soil surrounding a land mien and its contrast with the dielectric constant of the landmine are critical to the effectiveness of ground penetrating radar (GPR) for landmine detection. These parameters affect the velocity and attenuation of the radar signal as well as the strength of the reflection form the mine. The dielectric properties of the soil depend on the soil texture and bulk density as well as the soil water content. In previous work, we have simulated the unsaturated water flow around a landmine. In this paper we summarize a collection of models that can be used to predict the dielectric constant, velocity of the GPR signal, attenuation, and reflection coefficient form soil type and soil water content. These models have been integrated into a MATLAB software package. Using these models, we can determine whether or not field conditions are appropriate for use of GPR. Under dry conditions, the soil water content may be too low for good GPR performance. If the soil is too dry, we can select an appropriate level of soil water content and design a watering scheme to bring the soil water content up the desired level. We present a case study in which a soil watering scheme was designed, simulated, and the performed at a field site.
Many sensors for landmine detection are affected by soil water content, temperature, electrical conductivity and dielectric constant. The most important of these is water content since it directly influences the three other properties. We model water distribution around antitank mines buried in a loam and loamy sand soil under the climatic conditions of Bosnia and Kuwait. In Kuwait the loam and loamy sand have mean soil water contents of about 16 and 7 volume percent, respectively; in Bosnia, the mane water contents are higher with means of 30 and 14 volume percent in the loam and loamy sand. As a result the soil dielectric constant in Kuwait varied from about 4 to 8 in the loamy sand and from 8 to 14 in the loam. In Bosnia the higher water contents result in a soil dielectric constant from 4 to 12 in the loamy sand and from 9 to 50 in the loam. Water contents below the landmine were sometimes higher than above it. The modeling result demonstrate that a solid water content regimes and the resulting distributions of soil dielectric constants around landmines are strongly affected by the interaction between climate, soil type, and landmine geometry.