biblio_i04.bib
@INPROCEEDINGS{caprile04exact,
AUTHOR = {B. Caprile and S. Merler and C. Furlanello and G. Jurman},
TITLE = {Exact Bagging with $k$-Nearest Neighbour Classifiers},
BOOKTITLE = {Multiple Classifier Systems, Lecture Notes in Computer Science},
YEAR = {2004},
PAGES = {72--81},
EDITOR = {F. Roli and J. Kittler and T. Windeatt},
PUBLISHER = {Springer},
ABSTRACT = {A formula is derived for the exact computation of Bagging classifiers
when the base model adopted is $k$-Nearest Neighbour ($k$-NN). The
formula, that holds in any dimension and does not require the
extraction of bootstrap replicates, proves that Bagging cannot improve
$1$-Nearest Neighbour. It also proves that, for $k > 1$, Bagging has a
smoothing effect on $k$-NN. Convergence of empirically bagged $k$-NN
predictors to the exact formula is also considered. Efficient
approximations to the exact formula are derived, and their
applicability to practical cases is illustrated.}
}
@ARTICLE{furlanello2004news,
AUTHOR = {C. Furlanello and M. Serafini and S. Merler and G. Jurman},
TITLE = {Methods for predictive classification and molecular profiling from {DNA} microarray data},
YEAR = {2004},
JOURNAL = {Ital. Heart J.},
NUMBER = {1},
VOLUME = {5},
PAGES = {199--202}
}
@ARTICLE{merler2002bias,
AUTHOR = {S. Merler and B. Caprile and C. Furlanello},
TITLE = {Bias-Variance Control via Hard Points Shaving},
YEAR = {2004},
VOLUME = {18},
NUMBER = {5},
PAGES = {891--903},
JOURNAL = {International Journal of Pattern Recognition and Artificial Intelligence},
ABSTRACT = {The AdaBoost algorithm is one of the most successful classification
methods in use. While the algorithm largely preserves its general and
practical applicability, theoretical and experimental work shows that
AdaBoost can overfit when it is applied to noisy data.
In this paper, a procedure is proposed for bias-variance control when
the AdaBoost algorithm is employed in classification tasks. The method is
based on an earlier notion of {\em easy} and {\em hard} training
patterns as emerging from analysis of the dynamical evolutions of AdaBoost
weights. More specifically, the procedure consists in sorting data
points by hardness, and in progressively eliminating the hardest among
them from the data set. Effectiveness of the method is tested and
discussed on synthetic as well as natural data.}
}
@ARTICLE{jurman2004family,
AUTHOR = {G. Jurman},
TITLE = {A family of simple {L}ie algebras in characteristic two},
YEAR = {2004},
JOURNAL = {Journal of Algebra},
VOLUME = {271},
PAGES = {454--481}
}
@ARTICLE{mitasova2004freeJP,
AUTHOR = {H. Mitasova and M. Neteler},
JOURNAL = {The Journal of Survey},
MONTH = {February},
NUMBER = {2},
PAGES = {34-38},
TITLE = {Free general-purpose {GIS}. {A} {G}eographic {R}esources {A}nalysis {S}upport {S}ystem. (In {J}apanese)},
VOLUME = {54},
YEAR = {2004},
ABSTRACT = {The Geographic Resources Analysis, GRASS, a general purpose
GIS originally developed by U.S. Army Corps of Engineers Laboratory, has
grown into one of the main components of Open Source and Free Software
geospatial computational infrastructure. Current developments led by
international team of programmers, focus on improving the 2D and 3D raster
and vector data processing and analysis tools and 3D visualization
capabilities in the wake of publishing of the code under GPL in 1999.
Applications in the area of epidemiology, coastal management and water flow
modelling provide a snapshot of the capabilities.}
}
@ARTICLE{mitasova04grass,
AUTHOR = {H. Mitasova and M. Neteler},
JOURNAL = {Transactions in GIS},
TITLE = {{GRASS} as {O}pen {S}ource - {F}ree {S}oftware {GIS}: accomplishments and perspectives. {G}uest editorial.},
YEAR = {2004},
VOLUME = {8},
NUMBER = {2},
PAGES = {145-154},
MONTH = {April}
}
@INPROCEEDINGS{neteler2004modis,
AUTHOR = {M. Neteler},
TITLE = {{MODIS} time series remote sensing for epidemiological modeling},
YEAR = {2004},
KEYWORDS = {Remote sensing, epidemiology, MODIS, time series, Land Surface Temperature},
BOOKTITLE = {Proc. GeoInformatics for Spatial-Infrastructure Development in Earth \&
Allied Sciences: GIS-IDEAS. 2004, Sept. 16-18, Hanoi, Vietnam},
LINK = {http://mpa.itc.it/papers/neteler_gisideas2004_in_press.pdf},
ABSTRACT = {In epidemiological modeling, survey data are usually collected at sampling
sites and then regionalized within Geographical Information Systems (GIS).
To enhance the data density, continuous field data such as land surface
temperatures (LST), snow coverage, vegetation indices are commonly derived
from satellite data. The recent launches of the new satellite systems Terra
and Aqua significantly improve the situation of data availability for
scientific purposes and epidemiological studies and predictions. The most
interesting sensor onboard is MODIS which daily delivers two global coverages
at 250m (Red, NIR), 500m (MIR) and 1000m resolution (TIR).
The paper focuses on two of the numerous MODIS data products: Land Surface
Temperatures (LST), and vegetation index 16-day composites.
The integration of MODIS satellite data into a GIS requires several
pre-processing steps, such as the reprojection from MODIS-ISIN or MODIS-SIN
projections to another more common projection (UTM, national coordinate
systems etc.). The resulting maps are filtered pixelwise by applying the
related quality maps which are provided along the data products. Due to
limitations in the official cloud detection algorithm used to create these
land surface temperature quality maps, an outlier detection has been
implemented. Based on the scene statistics, this outlier filter aims at
removing all pixels which contain cloud temperatures instead of the
desired land surface temperatures.
Another set of MODIS time series data are NDVI and EVI vegetation indices.
They can be implemented into epidemiological models to introduce vegetation
dynamics. The 16-day composite product minimizes cloud cover and reflects
at a sufficient temporal resolution the current vegetation status.
The integration of MODIS data into epidemiological research enhances
the spatio-temporal resolution of climatological data in particular in
mountainous regions. The study area, a region of approximately 20000 sqkm,
is of complex terrain with elevation ranging from nearly sea level to
3800 meters with a varying density of meteorological stations.
The recent implementation of general time series processing for GRASS
raster maps supports univariate statistics for a series of MODIS scenes.
By selecting various time ranges and operators, a number of indicators
can be calculated. The comparison of LST with ground truth time series
from climatic stations showed that the LST match quite well with ground
temperatures. While surface and aerial temperatures differ by definition,
it is possible to transform surface to aerial temperatures by a regression
model. Results and comparisons will be presented in the paper.}
}
@INPROCEEDINGS{neteler2004imgproc,
AUTHOR = {M. Neteler and D. Grasso and I. Michelazzi and L. Miori and S. Merler and C. Furlanello},
TITLE = {New image processing tools for {GRASS}},
YEAR = {2004},
KEYWORDS = {Remote sensing, GIS, image registration, orthophoto, spectral unmixing,
image fusion, GRASS on openMosix Cluster},
BOOKTITLE = {Proc. Free/Libre and Open Source Software for Geoinformatics:
GIS-GRASS Users Conference 2004, Sept. 12-14, Bangkok, Thailand},
LINK = {http://gisws.media.osaka-cu.ac.jp/grass04/viewabstract.php?id=37},
ABSTRACT = {In this paper we present a suite of new image processing tools for
GRASS. These new programs provide support for image geocoding and
image fusion. Moreover, multi- and hyperspectral image analysis has
been implemented to derive landuse/landcover maps at subpixel
resolution.
PART I
The module 'i.linespoints' allows for image registration
by defining ground control points as well as corresponding lines.
The integration of lines into the registration procedure supports
accelerated and simplified search of corresponding structures in
source and target images. The resulting table of ground control points
is provided as input to the new rectification tool 'i.homography'.
A new module 'i.coregister' provides an alternative semiautomated
approach to find corresponding points in two overlapping images.
In order to obtain a good registration accuracy, first two regions
are roughly indicated on screeen, with very general requirements to
image dimensions and overlapping zone characteristics. Given the
matching region, the algorithm defines dynamic search windows and
computes the cross-correlation function within subwindows. Based on
the Fast Fourier Transform, the maximum correlation value delivers
the positions of the GCPs, which are saved into the common POINTS
structure for later use with 'i.rectify'. The list of GCPs created by
above modules can optionally be converted into the POINTS structure
of 'i.ortho.photo' by a new script 'i.points2orthophoto.sh'.
A new application of the 'i.ortho.photo' algorithm is proposed for
the registration of oblique imagery as produced by hand-held digital
cameras. The underlying idea is to improve the visual perception
of perspective rendering based on orthophotos. While oblique rendering
using a digital elevation model and orthophotos usually suffers from
perspective displacements, we show that digital photos even taken
by a cheap digital camera can be geocoded and used to improve the
visual impression.
PART II
In the next part of this paper, we present two methods related to
multi- and hyperspectral cameras. Spectral angle mapping has been
implemented in the new module 'i.spectral.sam'. The algorithm is
calculating for a set of bands the angles to a set of object spectra
read from a spectral library.
Spectral unmixing for landuse/landcover mapping at subpixel precision
has been implemented in the module 'i.spectral.unmix'. Multi- and
hyperspectral data can be analysed against a spectral library. Instead
of single resulting map as received from common classification algorithms,
here as many abundance maps as object spectra are generated.
A new script 'i.fusion.brovey' has been written to support PAN sharpening
of multispectral satellites such as LANDSAT-7, QuickBird and SPOT. The
algorithm performs Brovey transform image fusion of the high resolution
panchromatic channel with the multispectral channels at lower resolution.
Finally, we will show a high performance solution for image classification
in GRASS at meso-scale and high spatial resolution. A script-based
approach to run standard GRASS on an openMosix cluster (20 PCs, 40 CPUs)
has been implemented to classify multispectral color orthophotos with SMAP
algorithm. The study area covers approximately 6200 square kilometers,
the resolution of the orthophotos is at one meter per pixel. In tests, the
required time to analyse 280 orthophotos at the given resolution was
reduced from estimated 118 days on a single CPU to 5 days on the
openMosix cluster.}
}
@BOOK{neteler2004openSourceGIS,
AUTHOR = {M. Neteler and H. Mitasova},
TITLE = {Open {S}ource {GIS}: {A} {GRASS} {GIS} {A}pproach},
PAGES = {424},
EDITION = {Second},
MONTH = {June},
YEAR = {2004},
SERIES = {SECS},
NUMBER = {773},
PUBLISHER = {Kluwer Academic Publishers/Springer, Boston},
NOTE = {ISBN: 1-4020-8064-6; also published as eBook: ISBN 1-4020-8065-4},
LINK = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,5-40109-22-33975319-0,00.html},
ABSTRACT = {Since the first edition of Open Source GIS: A GRASS GIS
Approach was published in 2002, GRASS has undergone major
improvements. This second edition includes numerous updates related
to the new development; its text is based on the GRASS 5.3 version
from December 2003. Besides changes related to GRASS 5.3
enhancements, the introductory chapters have been re-organized,
providing more extensive information on import of external data. Most
of the improvements in technical accuracy and clarity were based on
valuable feedback from readers.
Open Source GIS: A GRASS GIS Approach, Second Edition, provides
updated information about the use of GRASS, including geospatial
modeling with raster, vector and site data, image processing,
visualization, and coupling with other open source tools for
geostatistical analysis and web applications. A brief introduction to
programming within GRASS encourages new development. The sample data
set used throughout the book has been updated and is available on the
GRASS web site. This book also includes links to sites where the
GRASS software and on-line reference manuals can be downloaded and
additional applications can be viewed.
Open Source GIS: A GRASS GIS Approach, Second Edition is designed for
a professional audience, composed of researchers and practitioners in
government and industry. This book is also suitable as a secondary
text for graduate-level students in geomatics, computer science and
geosciences.}
}
@ARTICLE{rizzoli2004Ixodes,
AUTHOR = {A. Rizzoli and R. Ros\`{a} and B. Mantelli and E. Pecchioli and
H. Hauffe and V. Tagliapietra and T. Beninati and M. Neteler and C. Genchi},
JOURNAL = {Parassitologia},
TITLE = {Ixodes ricinus, transmitted diseases and reservoirs (in Italian)},
YEAR = {2004},
VOLUME = {46},
NUMBER = {1-2},
PAGES = {119-122},
MONTH = {June},
LINK = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15305699},
ABSTRACT = {The tick Ixodes ricinus has been recorded in most Italian
regions especially in thermo-mesophilous woods and shrubby habitats
where the relative humidity allow the tick to complete its 3 year
developmental cycle, as predicted for the European climatic
ranges. This tick acts both as vector and reservoir for a series of
wildlife zoonotic pathogens, especially the agents of Lyme diseases,
Tick borne encephalitis and Human Granulocytic Ehrlichiosis, which are
emerging in most of Europe. To assess the spatial distribution of
these pathogens and the infection risk for humans and animals within
the territory of the Province of Trento, we carried out a long term
study using a combination of eco-epidemiological surveys and
mathematical modelling. An extensive tick collection with a GIS based
habitat suitability analysis allowed us to identify the areas where
tick occurs at various density. To identify the areas with higher
infection risk, we estimated the values of R0 for Borrelia burgdorferi
s.l., TBE virus and Anaplasma phagocytophila under different
ecological conditions. We assessed the infection prevalence in the
vector and in the wildlife reservoir species that play a central role
in the persistence of these infections, ie the small mammals
A. flavicollis and C. glareolus. We also considered the double effect
of roe deer (Capreolus capreolus) which act as reservoir for
A. phagocytophila but is an incompetent host for B. burgdorferi and
TBE virus, thus reducing the infection prevalence in ticks of these
last two pathogens. Infection prevalence with B. burgdorferi and
A. phagocytophila in the vector was assessed by PCR screening 1212
I. ricinus nymphs collected by dragging in six main study areas during
2002. The mean infection prevalence recorded was 1.32\% for
B. burgdorferi s.l. and 9.84\% for A. phagocytophila. Infection
prevalence in nymphs with TBE virus, as assessed in a previous study
was 0.03\%. Infection prevalence in rodents was assessed by screening
(with ELISA and PCR) tissues and blood samples collected from 367
rodent individuals trapped extensively during 2002 within 6 main study
areas. A. flavicollis (N=238) was found to be infected with all three
pathogens investigated, with infection prevalence ranging from 3.3\%
for TBE virus to 11.7\% for A. phagocytophila, and 16.6\% with
B. burgdorferi s.l. C. glareolus (N=108) showed an infection
prevalence of 6.5\% with A. phagocytophila and 12.7\% with
B. burgdorferi s.l., while no individuals were infected with TBE
virus. We also screened 98 spleen samples collected from roe deer with
PCR, resulting in a mean prevalence of infection with
A. phagocytophila of 19.8\%. Using a deterministic model we explored
the condition for diseases persistence under different rodent and roe
deer densities. R0 values resulted largely above 1 for B. burgdorferi
s.l. in the vast majority of the areas classified as suitable for
I. ricinus occurrence in Trentino, while the condition for TBE
persistence appeared to be more restricted by a combination of
climatic condition and host densities.}
}
@ARTICLE{stankovic04mobile,
AUTHOR = {J. Stankovic and M. Neteler and R. Flor},
JOURNAL = {Transactions in GIS},
TITLE = {Mobile Wireless {GRASS} {GIS} for Handheld Computers Running {GNU}/{L}inux},
YEAR = {2004},
ANNOTE = {Url: \texttt{http://www.blackwell-synergy.com/links/doi/10.1111/j.1467-9671.2004.00177.x/abs/}},
VOLUME = {8},
NUMBER = {2},
PAGES = {225-233},
MONTH = {April},
ABSTRACT = {Recent developments of the communication technologies in the last years opened a
new dimension to Geographical Information Systems and Geoinformation Technologies.
This new dimension is mobility. It is simplifying data gathering, processing and
presentation independent from the area of application. A new branch,
Mobile Geoinformation Technologies, is based on wireless communication systems,
mobile personal computers, positioning systems and GIS. There are some proprietary
GIS software solutions for mobile or handheld devices available on the market,
but they are more focused on data logging tasks than providing full powered GIS support
or data processing functions. In this paper, we propose a mobile implementation of
the free and easily expandable GRASS GIS software in combination with the GNU/Linux
operating system run on handheld devices. This approach supports real time in the
field computations, data processing and cooperation of several active mobile
clients using wireless networking.}
}