This document summarizes a study comparing dense 3D ground penetrating radar (GPR) data acquisition and processing to standard pseudo 3D GPR methods for archaeological applications. Two identical dense 3D GPR surveys of a test site were collected: one using a standard odometer-guided system, and one using a new laser-guided positioning system. The laser system acquired data twice as fast with more accurate positioning. Comparisons found that dense acquisition and processing resolved more subsurface targets than decimated and interpolated pseudo 3D data, demonstrating that standard methods may be missing important archaeological features.
Separability Analysis of Integrated Spaceborne Radar and Optical Data: Sudan ...rsmahabir
Abstract-The purpose of this study was to determine via spectral separability using divergence measures the best individual and combinations of various numbers of bands for five land cover/ land use classes along the Blue Nile in Sudan. The data for this analysis were a stack of 15 layers including RADARSAT-2 C-band and PALSAR L-band quad-polarized radar registered with ASTER optical data, as well as four variance texture measures extracted from the RADARSAT-2 images. Spectral signatures were obtained for each class and examined by various separability measures. This examination is useful for better understanding the relative value of different types of remote sensing data and best band combinations for possible visual analysis and for improving land cover/ land use classification accuracy. Results show that the best single band for analysis was the RADARSAT-2 VH variance texture measure. The best pair of bands was the ASTER visible red and the RADARSAT-2 HV variance texture, which also included the PALSAR VH band for the best three band combination, all bands being very different data types. Further, based upon the divergence values, only eight bands are needed to achieve maximum separation between land cover/ land use classes. Beyond this point, classification accuracy is expected to decrease, with as few as six bands needed to reach viable classification accuracy.
An Efficient K-Nearest Neighbors Based Approach for Classifying Land Cover Re...IDES Editor
In recent times, researchers in the remote
sensing community have been greatly interested in
utilizing hyperspectral data for in-depth analysis of
Earth’s surface. In general, hyperspectral imaging comes
with high dimensional data, which necessitates a pressing
need for efficient approaches that can effectively process
on these high dimensional data. In this paper, we present
an efficient approach for the analysis of hyperspectral
data by incorporating the concepts of Non-linear manifold
learning and k-nearest neighbor (k-NN). Instead of
dealing with the high dimensional feature space directly,
the proposed approach employs Non-linear manifold
learning that determines a low-dimensional embedding of
the original high dimensional data by computing the
geometric distances between the samples. Initially, the
dimensionality of the hyperspectral data is reduced to a
pairwise distance matrix by making use of the Johnson's
shortest path algorithm and Multidimensional scaling
(MDS). Subsequently, based on the k-nearest neighbors,
the classification of the land cover regions in the
hyperspectral data is achieved. The proposed k-NN based
approach is evaluated using the hyperspectral data
collected by the NASA’s (National Aeronautics and Space
Administration) AVIRIS (Airborne Visible/Infrared
Imaging Spectrometer) from Kennedy Space Center,
Florida. The classification accuracies of the proposed k-
NN based approach demonstrate its effectiveness in land
cover classification of hyperspectral data.
Automatic traffic light controller for emergency vehicle using peripheral int...IJECEIAES
Traffic lights play such important role in traffic management to control the traffic on the road. Situation at traffic light area is getting worse especially in the event of emergency cases. During traffic congestion, it is difficult for emergency vehicle to cross the road which involves many junctions. This situation leads to unsafe conditions which may cause accident. An Automatic Traffic Light Controller for Emergency Vehicle is designed and developed to help emergency vehicle crossing the road at traffic light junction during emergency situation. This project used Peripheral Interface Controller (PIC) to program a priority-based traffic light controller for emergency vehicle. During emergency cases, emergency vehicle like ambulance can trigger the traffic light signal to change from red to green in order to make clearance for its path automatically. Using Radio Frequency (RF) the traffic light operation will turn back to normal when the ambulance finishes crossing the road. Result showed the design is capable to response within the range of 55 meters. This project was successfully designed, implemented and tested.
Separability Analysis of Integrated Spaceborne Radar and Optical Data: Sudan ...rsmahabir
Abstract-The purpose of this study was to determine via spectral separability using divergence measures the best individual and combinations of various numbers of bands for five land cover/ land use classes along the Blue Nile in Sudan. The data for this analysis were a stack of 15 layers including RADARSAT-2 C-band and PALSAR L-band quad-polarized radar registered with ASTER optical data, as well as four variance texture measures extracted from the RADARSAT-2 images. Spectral signatures were obtained for each class and examined by various separability measures. This examination is useful for better understanding the relative value of different types of remote sensing data and best band combinations for possible visual analysis and for improving land cover/ land use classification accuracy. Results show that the best single band for analysis was the RADARSAT-2 VH variance texture measure. The best pair of bands was the ASTER visible red and the RADARSAT-2 HV variance texture, which also included the PALSAR VH band for the best three band combination, all bands being very different data types. Further, based upon the divergence values, only eight bands are needed to achieve maximum separation between land cover/ land use classes. Beyond this point, classification accuracy is expected to decrease, with as few as six bands needed to reach viable classification accuracy.
An Efficient K-Nearest Neighbors Based Approach for Classifying Land Cover Re...IDES Editor
In recent times, researchers in the remote
sensing community have been greatly interested in
utilizing hyperspectral data for in-depth analysis of
Earth’s surface. In general, hyperspectral imaging comes
with high dimensional data, which necessitates a pressing
need for efficient approaches that can effectively process
on these high dimensional data. In this paper, we present
an efficient approach for the analysis of hyperspectral
data by incorporating the concepts of Non-linear manifold
learning and k-nearest neighbor (k-NN). Instead of
dealing with the high dimensional feature space directly,
the proposed approach employs Non-linear manifold
learning that determines a low-dimensional embedding of
the original high dimensional data by computing the
geometric distances between the samples. Initially, the
dimensionality of the hyperspectral data is reduced to a
pairwise distance matrix by making use of the Johnson's
shortest path algorithm and Multidimensional scaling
(MDS). Subsequently, based on the k-nearest neighbors,
the classification of the land cover regions in the
hyperspectral data is achieved. The proposed k-NN based
approach is evaluated using the hyperspectral data
collected by the NASA’s (National Aeronautics and Space
Administration) AVIRIS (Airborne Visible/Infrared
Imaging Spectrometer) from Kennedy Space Center,
Florida. The classification accuracies of the proposed k-
NN based approach demonstrate its effectiveness in land
cover classification of hyperspectral data.
Automatic traffic light controller for emergency vehicle using peripheral int...IJECEIAES
Traffic lights play such important role in traffic management to control the traffic on the road. Situation at traffic light area is getting worse especially in the event of emergency cases. During traffic congestion, it is difficult for emergency vehicle to cross the road which involves many junctions. This situation leads to unsafe conditions which may cause accident. An Automatic Traffic Light Controller for Emergency Vehicle is designed and developed to help emergency vehicle crossing the road at traffic light junction during emergency situation. This project used Peripheral Interface Controller (PIC) to program a priority-based traffic light controller for emergency vehicle. During emergency cases, emergency vehicle like ambulance can trigger the traffic light signal to change from red to green in order to make clearance for its path automatically. Using Radio Frequency (RF) the traffic light operation will turn back to normal when the ambulance finishes crossing the road. Result showed the design is capable to response within the range of 55 meters. This project was successfully designed, implemented and tested.
Investigation of Chaotic-Type Features in Hyperspectral Satellite Datacsandit
Hyperspectral images provide detailed spectral info
rmation with more than several hundred
channels. On the other hand, the high dimensionalit
y in hyperspectral images also causes to
classification problems due to the huge ratio betwe
en the number of training samples and the
features. In this paper, Lyapunov Exponents (LEs) a
re used to determine chaotic-type structure
of EO- 1 Hyperion hyperspectral image, a mixed fore
st site in Turkey. Experimental results
demonstrate that EO-1 Hyperion image has a chaotic
structure by checking distribution of
Lyapunov Exponents (LEs) and they can be used as d
iscriminative features to improve
classification accuracy for hyperspectral images.
Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+,
and EO-1 ALI sensors
Gyanesh Chander a,⁎, Brian L. Markham b, Dennis L. Helder c
a SGT, Inc. 1 contractor to the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198-0001, USA
b National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
c South Dakota State University (SDSU), Brookings, SD 57007, USA
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Supervised machine learning based dynamic estimation of bulk soil moisture us...eSAT Journals
Abstract In this paper artificial neural network based sensor informatics architecture has been investigated; including proposed continuous daily estimation of area wise surface soil moisture using cosmic ray sensor’s neutron count time series. Study was conducted based on cosmic ray data available from two Australian locations. The main focus of this study was to develop a data driven approach to convert neutron counts into area wise ground surface soil moisture estimates. Independent surface soil moisture data from the Australian Water Availability Project (AWAP) was used as ground truth. A comparative study using five different types of neural networks, namely, Feed Forward Back Propagation (FFBPN), Multi-Layer Perceptron (MLPN), Radial Basis Function (RBFN), Elman (EN), and Probabilistic networks (PNN) was conducted to evaluate the overall soil moisture estimation accuracy. Best performance from the Elman network outperformed all other neural networks with 94% accuracy with 92% sensitivity and 97% specificity based on Tullochgorum data. Overall high accuracy proved the effectiveness of the Elman neural network to estimate surface soil moisture continuously using cosmic ray sensors. Index Terms: Artificial Neural Network, Surface Soil Moisture, Cosmic Ray Sensors, Neutron Counts.
Hyperspectral Data Compression Using Spatial-Spectral Lossless Coding TechniqueCSCJournals
Hyperspectral imaging is widely used in many applications; especially in vegetation, climate changes, and desert studies. Such kind of imaging has a huge amount of data, which requires transmission, processing, and storage resources especially for space borne imaging. Compression of hyperspectral data cubes is an effective solution for these problems. Lossless compression of the hyperspectral data usually results in low compression ratio, which may not meet the available resources; on the other hand, lossy compression may give the desired ratio, but with a significant degradation effect on object identification performance of the hyperspectral data. Moreover, most hyperspectral data compression techniques exploits the similarities in spectral dimensions; which requires bands reordering or regrouping, to make use of the spectral redundancy. In this paper, we analyze the spectral cross correlation between bands for Hyperion hyperspectral data; spectral cross correlation matrix is calculated, assessing the strength of the spectral matrix, and finally, we propose new technique to find highly correlated groups of bands in the hyperspectral data cube based on "inter band correlation square", from the resultant groups of bands we propose a new predictor that can predict efficiently the whole bands within data cube based on weighted combination of spectral and spatial prediction, the results are evaluated versus other state of the art predictor for lossless compression.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
We illustrate unsupervised and supervised learning algorithms that accurately classify the lithological variations in the 3D seismic data. We demonstrate blind source separation techniques such as the principal components (PCA) and noise adjusted principal
components in conjunction with Kohonen Self organizing maps to produce superior unsupervised classification maps.
Further, we utilize the PCA space training in Maximum likelihood (ML) supervised classification. Results demonstrate that the ML supervised classification produces an improved classification of the facies in the 3D seismic dataset from the Anadarko basin in central Oklahoma.
Investigation of Chaotic-Type Features in Hyperspectral Satellite Datacsandit
Hyperspectral images provide detailed spectral info
rmation with more than several hundred
channels. On the other hand, the high dimensionalit
y in hyperspectral images also causes to
classification problems due to the huge ratio betwe
en the number of training samples and the
features. In this paper, Lyapunov Exponents (LEs) a
re used to determine chaotic-type structure
of EO- 1 Hyperion hyperspectral image, a mixed fore
st site in Turkey. Experimental results
demonstrate that EO-1 Hyperion image has a chaotic
structure by checking distribution of
Lyapunov Exponents (LEs) and they can be used as d
iscriminative features to improve
classification accuracy for hyperspectral images.
Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+,
and EO-1 ALI sensors
Gyanesh Chander a,⁎, Brian L. Markham b, Dennis L. Helder c
a SGT, Inc. 1 contractor to the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198-0001, USA
b National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
c South Dakota State University (SDSU), Brookings, SD 57007, USA
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Supervised machine learning based dynamic estimation of bulk soil moisture us...eSAT Journals
Abstract In this paper artificial neural network based sensor informatics architecture has been investigated; including proposed continuous daily estimation of area wise surface soil moisture using cosmic ray sensor’s neutron count time series. Study was conducted based on cosmic ray data available from two Australian locations. The main focus of this study was to develop a data driven approach to convert neutron counts into area wise ground surface soil moisture estimates. Independent surface soil moisture data from the Australian Water Availability Project (AWAP) was used as ground truth. A comparative study using five different types of neural networks, namely, Feed Forward Back Propagation (FFBPN), Multi-Layer Perceptron (MLPN), Radial Basis Function (RBFN), Elman (EN), and Probabilistic networks (PNN) was conducted to evaluate the overall soil moisture estimation accuracy. Best performance from the Elman network outperformed all other neural networks with 94% accuracy with 92% sensitivity and 97% specificity based on Tullochgorum data. Overall high accuracy proved the effectiveness of the Elman neural network to estimate surface soil moisture continuously using cosmic ray sensors. Index Terms: Artificial Neural Network, Surface Soil Moisture, Cosmic Ray Sensors, Neutron Counts.
Hyperspectral Data Compression Using Spatial-Spectral Lossless Coding TechniqueCSCJournals
Hyperspectral imaging is widely used in many applications; especially in vegetation, climate changes, and desert studies. Such kind of imaging has a huge amount of data, which requires transmission, processing, and storage resources especially for space borne imaging. Compression of hyperspectral data cubes is an effective solution for these problems. Lossless compression of the hyperspectral data usually results in low compression ratio, which may not meet the available resources; on the other hand, lossy compression may give the desired ratio, but with a significant degradation effect on object identification performance of the hyperspectral data. Moreover, most hyperspectral data compression techniques exploits the similarities in spectral dimensions; which requires bands reordering or regrouping, to make use of the spectral redundancy. In this paper, we analyze the spectral cross correlation between bands for Hyperion hyperspectral data; spectral cross correlation matrix is calculated, assessing the strength of the spectral matrix, and finally, we propose new technique to find highly correlated groups of bands in the hyperspectral data cube based on "inter band correlation square", from the resultant groups of bands we propose a new predictor that can predict efficiently the whole bands within data cube based on weighted combination of spectral and spatial prediction, the results are evaluated versus other state of the art predictor for lossless compression.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
We illustrate unsupervised and supervised learning algorithms that accurately classify the lithological variations in the 3D seismic data. We demonstrate blind source separation techniques such as the principal components (PCA) and noise adjusted principal
components in conjunction with Kohonen Self organizing maps to produce superior unsupervised classification maps.
Further, we utilize the PCA space training in Maximum likelihood (ML) supervised classification. Results demonstrate that the ML supervised classification produces an improved classification of the facies in the 3D seismic dataset from the Anadarko basin in central Oklahoma.
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Because We Can.
GPR systems work by sending a tiny pulse of energy into a material via an antenna. An integrated computer records the strength and time required for the return of any reflected signals. Subsurface variations will create reflections that are picked up by the system and stored on digital media. These reflections are produced by a variety of material such as geological structure differences and man-made objects like pipes and wire.
La presentazione del Progetto SmartGeo a cura di Guido Satta, in occasione dell'evento "Bonifiche ambientali e potenzialità delle imprese" che si è tenuto a Cagliari il 7 novembre 2014.
Surveying for Civil engineering is a
particular type of surveying known as "land surveying", it is the
detailed study or inspection, as by gathering information through
observations, measurements in the field, questionnaires, or
research of legal instruments, and data analysis in the support of
planning, designing, and establishing of property boundaries.
Land surveying can include associated services such as mapping
and related data accumulation, construction layout surveys,
precision measurements of length, angle, elevation, area, and
volume, as well as horizontal and vertical control surveys, and
the analysis and utilization of land survey data. Surveyors use
various tools to do their work successfully and accurately, such
as total stations, robotic total stations, GPS receivers, prisms, 3D
scanners, radio communicators, handheld tablets, digital levels,
and surveying software.
Survey data can be directly entered into a GIS from digital
data collection systems on survey instruments. When data is
captured, the user should consider if the data should be captured
with either a relative accuracy or absolute accuracy, since this
could not only influence how information will be interpreted but
also the cost of data captured.
In this paper GIS maps were developed depending on the
field surveying data made for a two traverses. First one has ribs
less than 50m length and the other larger than 50m. Each
traverse is holding five times using five equipments and
instruments: Tape, Level, Digital level, Digital theodolite and
Laser tape. Also those maps were drawn by using both of ACAD
and ArcView softwares. Then a detail surveying map was
produced. The precision was computed for both traverses in each
method. Its value is range from 1/140 to 1/10000.
Adaptive 3D ray tracing approach for indoor radio signal prediction at 3.5 GHzIJECEIAES
This paper explained an adaptive ray tracing technique in modelling indoor radio wave propagation. As compared with conventional ray tracing approach, the presented ray tracing approach offers an optimized method to trace the travelling radio signal by introducing flexibility and adaptive features in ray launching algorithm in modelling the radio wave for indoor scenarios. The simulation result was compared with measurements data for verification. By analyzing the results, the proposed adaptive technique showed a better improvement in simulation time, power level and coverage in modelling the radio wave propagation for indoor scenario and may benefit in the development of signal propagation simulators for future technologies.
CLEARMiner: Mining of Multitemporal Remote Sensing ImagesEditor IJCATR
A new unsupervised algorithm, called CLimate and rEmote sensing Association patterns Miner, for mining association patterns on
heterogeneous time series from climate and remote sensing data, integrated in a remote sensing information system is developed to improve the
monitoring of sugar cane fields. The system, called RemoteAgri, consists of a large database of climate data and low-resolution remote sensing
images, an image pre-processing module, a time series extraction module, and time series mining methods. The time series mining method
transforms series to symbolic representation in order to identify patterns in a multitemporal satellite images and associate them with patterns in
other series within a temporal sliding window. The validation process was achieved with agro climatic data and NOAA-AVHRR images of
sugar cane fields. Rules generated by the new algorithm show the association patterns in different periods of time in each time series, pointing to
a time delay between the occurrences of patterns in the series analyzed, corroborating what specialists usually forecast without having the burden
of dealing with many data charts. This new method can be used by agro meteorologists to mine and discover knowledge from their long time
series of past and forecasting data, being a valuable tool to support their decision-making process.
Data Collection via Synthetic Aperture Radiometry towards Global SystemIJERA Editor
Nowadays it is widely accepted that remote sensing is an efficient way of large data management philosophy. In
this paper, we present a future view of the big data collection by synthetic aperture radiometry as a passive
microwave remote sensing towards building a global monitoring system. Since the collected data may not have
any value, it is mandatory to analyses these data in order to get valuable and beneficial information with respect
to their base data. The collected data by synthetic aperture radiometry is one of the high resolution earth
observation, these data will be an intensive problems, Meanwhile, Synthetic Aperture Radar able to work in
several bands, X, C, S, L and P-band. The important role of synthetic aperture radiometry is how to collect data
from areas with inadequate network infrastructures where the ground network facilities were destroyed. The
future concern is to establish a new global data management system, which is supported by the groups of
international teams working to develop technology based on international regulations. There is no doubt that the
existing techniques are so limited to solve big data problems totally. There is a lot of work towards improving 2-
D and 3-D SAR to get better resolution.
Testing the global grid of master events for waveform cross correlation with ...Ivan Kitov
Abstract
The Comprehensive Nuclear-Test-Ban Treaty’s verification regime requires uniform distribution of monitoring capabilities over the globe. The use of waveform cross correlation as a monitoring technique demands waveform templates from master events outside regions of natural seismicity and test sites. We populated aseismic areas with masters having synthetic templates for predefined sets (from 3 to 10) of primary array stations of the International Monitoring System. Previously, we tested the global set of master events and synthetic templates using IMS seismic data for February 12, 2013 and demonstrated excellent detection and location capability of the matched filter technique. In this study, we test the global grid of synthetic master events using seismic events from the Reviewed Event Bulletin. For detection, we use standard STA/LTA (SNR) procedure applied to the time series of cross correlation coefficient (CC). Phase association is based on SNR, CC, and arrival times. Azimuth and slowness estimates based f-k analysis cross correlation traces are used to reject false arrivals.
Hyperparameters analysis of long short-term memory architecture for crop cla...IJECEIAES
Deep learning (DL) has seen a massive rise in popularity for remote sensing (RS) based applications over the past few years. However, the performance of DL algorithms is dependent on the optimization of various hyperparameters since the hyperparameters have a huge impact on the performance of deep neural networks. The impact of hyperparameters on the accuracy and reliability of DL models is a significant area for investigation. In this study, the grid Search algorithm is used for hyperparameters optimization of long short-term memory (LSTM) network for the RS-based classification. The hyperparameters considered for this study are, optimizer, activation function, batch size, and the number of LSTM layers. In this study, over 1,000 hyperparameter sets are evaluated and the result of all the sets are analyzed to see the effects of various combinations of hyperparameters as well the individual parameter effect on the performance of the LSTM model. The performance of the LSTM model is evaluated using the performance metric of minimum loss and average loss and it was found that classification can be highly affected by the choice of optimizer; however, other parameters such as the number of LSTM layers have less influence.
Similar to 3D GPR in Archaeology What can be gained fron Dense Data (20)
Hyperparameters analysis of long short-term memory architecture for crop cla...
3D GPR in Archaeology What can be gained fron Dense Data
1. 12th
International Conference on Ground Penetrating Radar, June 16-19, 2008, Birmingham, UK
3D GPR in Archaeology: What can be gained from dense
Data Acquisition and Processing ?
Alexandre Novo(1)
, Mark Grasmueck(2)
, Dave A. Viggiano(2)
, Henrique Lorenzo(1)
(1) EUET Forestal. University of Vigo
Campus A Xunqueira s/n. 36005-Pontevedra (Spain)
alexnovo@uvigo.es; hlorenzo@uvigo.es
(0034) 986 80 19 08 (phone); (0034) 986 80 19 07 (fax)
(2) RSMAS Marine Geology and Geophysics. University of Miami
4600 Rickenbacker Causeway, Miami, Florida, 33149
mgrasmueck@rsmas.miami.edu; dviggiano@rsmas.miami.edu
(305) 421 48 58 (phone); (305) 421 46 32 (fax)
Abstract - Most archaeological 3D GPR surveys suffer from a
sampling bias: Spacing between GPR profiles is 5-10 times lar-
ger than trace spacing in profile direction. Such pseudo 3D
GPR surveys produce highly interpolated subsurface maps
which do not exploit the full resolution potential of GPR. This
project was designed to answer the critical questions of how
dense a GPR survey should be acquired and where are the res-
olution limits and bottlenecks of currently in archaeology
widely used GPR hardware and processing software.
Keywords – 3D GPR, Archaeology.
I. INTRODUCTION
Present standards of 3D GPR in archaeological prospection
are based on pseudo 3D methodologies which are charac-
terized by a cross-line spacing which ranges from 0,25 m to
1 m (being 0,5 m the most common), the use of 250-500
MHz antennas and vast interpolation to fill-in the data gaps.
Such methodologies along with powerful 3D visualization
techniques are widely applied in GPR surveys with archae-
ological purpose [2, 5]. These surveys are usually image
sites containing continuous linear features extending over
several meters length such as foundations, ditches, walls,
roads, etc. Most archaeological surveyors have not yet
pushed GPR to its full potential and experienced the bene-
fits of maximum resolution achieved with very dense data
acquisition and processing. Hence the following question
emerges: What is being lost by decimating data acquisition
and applying data interpolation?
Ultra-dense 3D GPR honoring spatial Nyquist sampling the-
orem have already been successfully utilized to obtain
unaliased 3D images of heterogeneous subsurface geomet-
ries such as: dune stratigraphy, tree roots and rock fractures.
High resolution 3D images of the subsurface can be ob-
tained if the space among traces is reduced to a quarter of
the wavelength in the host material in all directions. In addi-
tion, a highly precise positioning of the GPR antenna during
data acquisition is crucial, as it has been pointed out by other
authors [4] and [6].
The currently prevailing paradigm that archaeological GPR
datasets are already being gathered with enough density
seems the main reason why the applications of ultra-dense
3D GPR methodologies are still limited in archaeological
exploration. Besides, other geophysical techniques (such as
magnetometry or resistivity), in adequate subsurface envir-
onments, can produce the same pseudo 3D image quality
than GPR and resolve the main archaeological features in
much less time (several hectares per day). However, archae-
ologists sometimes need to locate isolated features smaller
than walls (i.e. objects, pits, postholes, burials or cisterns)
[1].
Objective of this paper is to show how the extra effort in
data-acquisition, refined methodology and processing can
improve GPR imaging results. To directly relate the results
to current practice, two identical ultra-dense 3D GPR sur-
veys were acquired: One with standard GPR equipment us-
ing a low cost odometer wheel together with tape measures
and strings as guidelines. The second survey was acquired
with a next generation laser-positioned 3D GPR system de-
veloped at University of Miami [3]. Pseudo 3D datasets
were generated by decimation of the dense surveys. Goal
was to compare the efficiency of ultra-dense data acquisi-
tion, the accuracy of both equipments and the data quality.
II. METHODOLOGY
2. 12th
International Conference on Ground Penetrating Radar, June 16-19, 2008, Birmingham, UK
Figure 1. Test area at Ingraham Park, Miami, USA.
Figure 2. GPR system developed at University of Miami (left).
Standard GPR equipment which was adapted for this compar-
ison project (right).
3.1 Field Site and Data Acquisition
The test site consisted of a natural grassy area in a public
park with tree roots, plastic pipes, old foundations and nu-
merous buried small objects as in-situ imaging targets. Both
tests used the same shielded bistatic 500 MHz antenna. As
well same acquisition parameters were set: 600
samples/scan, 8 stacks, a sample rate of 6141 MHz resulting
in a maximum two-way travel time of 98 ns.
The GPR data were acquired by pushing and pulling the cart
and never turning the antenna. The survey area of 20 m x
12.50 m area was covered with 251 parallel GPR lines
spaced by 5 cm recording a GPR trace every 2.5 cm in order
to obtain two unaliased full-resolution 3D GPR surveys.
3.1.1 Odometer wheel acquisition:
After signposting with plastic pegs the grid corners, two
measurement tapes were placed in the shorter pair of parallel
sides of the grid for measuring the 5 cm spacing between the
two survey tapes to mark the exact profile location. The per-
son who moved the cart precisely followed the string in or-
der to ensure straight profiles. Parallel to the survey tapes,
two spray lines were drawn at a distance equal to the offset
between the rear edge of the cart and the centre of the an-
tenna. Thus the rear edge of the cart was used as a control
point to start and end every profile consistently as shown in
Figure 3.
Before starting surveying, the odometer wheel was calib-
rated for this terrain both in back and forward movement
over 50 metres to maximize accuracy in both directions. To
maintain a constant survey speed a metronome was utilized
keep moving the antenna cart at the same pace throughout
the survey.
3.1.2 Rotary laser acquisition
Novel rotary laser positioning system (RLPS) technology
was integrated with GPR into an efficient 3-D imaging sys-
tem [3]. The new system enables acquisition of centi-
metre-accurate x, y, and z coordinates from small detectors
attached to moving GPR antennae. Laser coordinates
streaming with 20 updates per second from each detector are
fused in real-time with the GPR data. The person moving the
GPR antenna is automatically guided by an array of LED
elements along precomputed tracks following a dense lawn-
mower pattern to acquire parallel GPR profiles spaced by 5
cm covering the entire survey area.
Figure 3. Methodology used with the standard GPR equip-
ment: strings as guidelines for navigation, measurement tapes
to place every profile and spray marks to help the operator to
start and end each profile with better than 5 cm precision.
3.2 Basic Data Processing
For a direct horizontal slice comparison care was taken to
exactly align the first breaks of both datasets. This Detrend-
ing and Zero-time adjustment step compensates for long-
term instrument drift due to temperature changes by auto-
3. 12th
International Conference on Ground Penetrating Radar, June 16-19, 2008, Birmingham, UK
matic picking of first breaks and applying spatially
smoothed vertical shifts to traces. The same dewow and
gain were applied to both the odometer and RLPS acquired
data. The dewow step removes very low frequency com-
ponents of the data. The gain curve is based on an averaged
and smoothed Hilbert transform of a representative set of
traces extracted from both 3D surveys.
3.3 Advanced Processing for 3D visualization
Pseudo 3D processing:
GPR-SLICE (c) v5.0 (www.gpr-survey.com) was de-
veloped for processing and visualization of pseudo 3D data-
sets. For this experiment we had to first decimate the dense
odometer data. From decimated datasets (cross-line spa-
cing: 0,5 m and 0,25 m) horizontal slices were generated by
spatially averaging the squared wave amplitudes of radar
reflections. Thickness of horizontal slices was set to 30
samples. The data were gridded using an Inverse Distance
algorithm which includes a search of all data within a 0,75
m radius of the desired point to be interpolated on the grid
and a smoothing factor.
Full-Resolution 3D Processing:
This processing sequence was applied to the dense 3D data
acquired with the RLPS system. For the full-resolution 3D
processing we use a combination of modules we developed
in LabView (National Instruments) and, where mentioned,
commercially available seismic processing software. The
data processing consists of the following steps: Data fusion
assigns laser derived x, y, and z coordinates to each radar
trace acquired. Regularization populates a 2.5 cm x 5 cm
bin grid with the nearest available trace. The horizontal res-
olution of the data was increased with the Promax (Land-
mark Graphics) 3D phase shift migration using a constant
velocity field. The migration velocity of 0.08 m/ns was de-
termined from diffraction hyperboloid analyses with Re-
flexW (Sandmeier Scientific Software).
IV. RESULTS
The comparison of the 2 methods revealed some interesting
results: Data acquisition of the very dense 3D GPR survey
with the conventional odometer system took 4 people more
than 6 hrs while the same survey could be completed by 2
people in less than 4hrs using the laser positioned system.
Subsurface maps generated by both surveys without neither
interpolation nor decimation resolved the same targets (Fig-
ure 4). Despite of the fact that apparently there are not sig-
nificant differences in the track-lines between surveys, the
odometer survey contained random horizontal shifts (see
Figure 5). The laser system produces a clearer representa-
tion of the subsurface target signatures. Decimation to wider line spacing and interpolation of the
missing data shows how pseudo 3D GPR surveying blurs or
misses many targets. Only the thickest tree roots can be
seen and some of the linear signatures from pipes and
Figure 4. Unmigrated horizontal slices at 14 ns show plastic
pipes and a part of the old foundations. Left: 3D GPR im-
age obtained from the new generation RLPS positioned
GPR system. Right: 3D GPR image obtained from the
standard GPR system with odometer wheel. (Yellow dash
lines indicate zoom-in captures that are shown below)
Figure 5. Zoom-in of images in Figure 4. Above: Random
jitter noise caused by the odometer wheel acquisition is
evident. Below: Laser positioned data shows improvements
in image clarity when compared with the best practically
possible result with conventional GPR equipment.
.
4. 12th
International Conference on Ground Penetrating Radar, June 16-19, 2008, Birmingham, UK
foundations can not be identified as clearly (see Figure 6
and 7). As many of the small objects were only imaged by
one line it becomes difficult to distinguish real targets from
random noise.
Figure 6. Unmigrated horizontal slices at 5 ns from the stand-
ard system. Left: Image obtained from GPR lines spaced 5 cm
and non-interpolated 3D processing shows the tree roots.
Right: Image obtained from GPR lines spaced 25 cm by using
the pseudo 3D processing, the roots are almost invisible.
V. CONCLUSIONS
Overall, the current practice of producing archaeological
subsurface maps with 3D GPR has still lots of untapped po-
tential. The GPR map resolution can be improved by ac-
quiring denser than quarter wavelength data in all directions
and avoiding interpolation and decimation processing
schemes. Faster 3D data acquisition equipments plus pre-
cise positioning systems are important future needs in ar-
chaeological geophysics. While PCs and graphics cards are
already powerful enough, most current commercial GPR
software tools are unfortunately not yet suitable for pro-
cessing of such dense datasets. For the data example shown
in this paper 3D migration in RefleW would have been only
possible after reducing the data to half the samples in time
direction.
However, a little unexpected but encouraging was the result
of this experiment in terms of how much detail can be cap-
tured on unmigrated data acquired very densely with the
odometer wheel. Even a low-cost odometer wheel posi-
tioned GPR system coupled with a large data acquisition ef-
fort can produce usable full-resolution 3D results. However,
to achieve crisp GPR maps free of acquisition jitter noise,
centimetre precise coordinates for all GPR traces are a re-
quirement.
Figure 7. Images at 14 ns. Upper-left: migrated slice from full-
resolution 3D processing. Upper-right: unmigrated slice from
non-interpolated, non-decimated data recorded with the odo-
meter wheel system. Both show plastic pipes, irrigation lines
and old foundations. The last two images show how data
decimation to coarser cross-line spacing (25 cm, left and 50
cm, right) plus the pseudo 3D processing method degrade the
resulting image which becomes blurrier until losing the tar-
gets.
ACKNOWLEDGMENTS
I would like to thank University of Miami and University of
Vigo for their support. Also, I would like to thank the “3D
GPR team 07” composed by: Jorien Schaaf, Jürg Hunziker
and Federico Caprotti. Måla Geoscience USA is acknow-
ledged for providing a shielded 500 MHz antenna and RTC
cart for the experiment reported in this article.
5. 12th
International Conference on Ground Penetrating Radar, June 16-19, 2008, Birmingham, UK
REFERENCES
[1] Gaffney, C. 2008. Detecting trends in the prediction of
the buried past: A review of geophysical techniques in
archaeology. Archaeometry 50, 313-336.
[2] Goodman, D, J. Steinberg, B. Damiata, Y. Nishimura,
K. Schneider, H. Hiromichi, N. Higashi. 2006. GPR
Overlay Analysis for Archaeological Prospection. Pro-
ceedings of the 11th
International Conference on
Ground Penetrating Radar 2006, Columbus, Ohio,
USA.
[3] Grasmueck, M. and D.A. Viggiano. 2007. Integration
of Ground-Penetrating Radar and Laser Positioning
Sensors for Real-Time 3-D Data Fusion. IEEE Trans-
actions on Geoscience and Remote Sensing, vol 45, N.
1, January 2007.
[4] Groenenboom, J., J. van der Kruk and J.H. Zeeman.
2001. 3D GPR data acquisition and the influence of
positioning errors on image quality. 63rd EAGE Con-
ference and Technical Exhibition, Amsterdam, 11-15
June 2201, 4 pp.
[5] Leckebusch, J. 2003. Ground-Penetrating Radar: A
Modern Three-dimensional Prospection Method. Ar-
chaeological Prospection, 10, 213-240.
[6] Lualdi, M., L. Zanzi and G. Sosio. 2006. A 3D GPR
Survey Methodology for Archaeological Applications.
Proceedings of the 11th
International Conference on
Ground Penetrating Radar 2006, Columbus, Ohio,
USA.