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GW 1  1st Italian GRASS users meeting proceedings
[preface] [index]
Introduction to GRASS GIS 
Markus Neteler
Authors  Title 
Ludovico Biagi, Massimo De Lucca, Michele Stefanoni
Abstract 
Trend validation and kriging in GRASS

Maria A. Brovelli, Marco Negretti, Christian Saldarini
Abstract 
GRASS interfacing with DBMSs

Maria A. Brovelli , Damiano Triglione, Giovanna Venuti
Abstract 
GIS techniques for digital surface models outlier detection
Full Text 
Marco Ciolli, Domenico Sguerso, Paolo Zatelli
Abstract 
GIS applications with Grass
Full Text 
Marco Ciolli, Paolo Zatelli
Abstract 
Avalanche risk management using GRASS GIS
Full Text 
Marco Colombo, Marco Ciampa
Abstract 
Meteorological data to apple ripening model
Full Text 
Stefano Merler, Lorenzo Potrich, Cesare Furlanello
Abstract 
Incremental risk modeling and management with GRASS web interfaces

Valentina Portolan, Marco Ciampa
Abstract 
Grass utilization to realize spatial distribution of crops water requirements in an alpine valley
Full Text 
Marco Valagussa
Abstract 
Integration of GRASS within applications of geographic location on board of buses
Full Text 
The Abstract
Trend validation and kriging in GRASS
Ludovico Biagi, Massimo De Lucca, Michele Stefanoni
In order to analyze observations and to predict a field the so called deterministic interpolators (e.g. least squares, weighted means, ...) are often used; their main limits are in the constraints imposed to the prediction process, which usually are not based on knowledge of the actual field properties. Therefore, since the early '60, new methods have been studied and developed, which are based on a stochastic analysis of the observations; well known among them are least squares collocation and kriging (both ordinary and universal) used in geostatistics, which have been adopted in some GIS software, during the last years.
We are studying an innovative approach for observation analysis and field prediction. The aim of this approach is to estimate by least squares a trend in the observations; after that, a kriging prediction of the field is performed. Our approach is very similar to the universal kriging, with a small though substantial difference: the presence of a trend is not imposed a priori, as usually done in available kriging software, but is validated by a Fisher test.
The proposed approach is being implemented as a GRASS© command. The trend estimation and validation is realized by a dedicated C code; up to now we have implemented only polynomial (up to bicubic) surfaces for the trend: obviously, the library should be completed with other functions in the future. The kriging prediction is realized linking GRASS© with the GStat© software; this tool is a freeware geostatistic software, available as C source code for Unix OS: it provides the model variogram estimate by least squares on the empirical one, the kriging prediction of the field digital model and associated prediction accuracies.
In this work the new algorithm and its implementation in GRASS© are explained; some examples of data elaboration are also shown.
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GRASS interfacing with DBMSs
Maria A. Brovelli, Marco Negretti, Christian Saldarini
GRASS, as other GIS, is not only a data analyser and viewer, but allows also to efficiently store data in its own hierarchical archive, organised in GISDBASE, locations, mapsets and elements levels.
The data we have to manage in geographically related problems are characterised at least by the two planar coordinates. In that case, if we would like to interface our GIS with an external DBMS, it is better to use relational data structures with the spatial extensions and some particular indexing method.
In our work we have focused on the Oracle 8 Spatial Data Cartridge and the PostgresSQL DBMSs, as they have the previously mentioned characteristics and run both under Solaris and Linux operating systems.
New commands are implemented to displaying raster and site data stored in the DBMS tables (d.ora.raster, d.ora.sites, d.pg.raster, d.pg.sites).
Some tests show that, in case of the raster, the time need for the data retrieval, by using the DBMSs instead of GRASS archive, is higher; on the contrary, in case of sites the use of DBMS makes faster the procedure. Moreover further tests proved that the use of a special built up quadtree index directly in the GRASS site points archive is, in term of waiting time, the best solution. This result suggests the implementation of a new indexing method in PostgresSQL (the DBMS we have evaluated as the most adequate and fast for our needs) more suitable for sites (e.g.: quadtree instead of Rtree).
Alternatively the proposal is, at least, to introduce this indexing method directly in the management of site points.
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GIS applications with Grass
Maria A. Brovelli, Damiano Triglione, Giovanna Venuti
In the present work strategies to cope with outliers detection are defined both for datasets stored on 2D lattices and on 1D profiles.
Assuming that (Hawkins D. M., 1980): "the outlier is an observation which deviates so much from other observations as to arouse suspicious that it was generated by different mechanism" we studied the problem of outlier detection in digital surface models, as first preprocessing and validation step. The methods proposed and the tools implemented have been applied to digital terrain models (DTMs), gridded geophysical data (gridded borehole depths, seismic velocities, amplitudes and phases, magnetic data, gravity data) but their use can be extended to data within different fields, as long as they represent surface models described by grid stored information.
We decided to implement the software to blunders detection by adding apposite tools in GRASS (Geographical Resources Analysis Support System).
The validation techniques are characterized by a common localization procedure: we examine the entire dataset by considering only a small subset at a time. Our basic hypothesis is that the values in the moving window (the mask) are observations affected by normal distributed white noise. An interpolating surface (apriori model) is computed from the points surrounding the center of the moving mask (suspected blunder). The choice of the model determines the residual between the observation an the surface at the mask central point P0 and therefore the capability to detect the possible outlier. The surface model can be obtained in the following ways: polynomial interpolation, robust estimation by using the median, collocation (or kriging). For each of them we define an associated test in order to decide whether the point P0 is a blunder or not. The paper focus on the first approach.
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GIS applications with Grass
Marco Ciolli, Domenico Sguerso, Paolo Zatelli
The application of GIS has become fundamental in environmental studies since it allows the integration of heterogeneous data.
Several applications of the GRASS GIS where the use of different data types leads to the realization of environmental models are presented.
The GRASS GIS has been used to develop and test forest fire risk models combining several morphologic, vegetational and anthropic factors; it has been used to set up a new avalanche risk model which allows the evaluation of the ability of the different vegetation types to protect against avalanches. A procedure for the automatic determination of the forest coverage evolution has been developed using the GRASS image analysis capability. The production of GPS satellites' visibility maps has been automated using the shadow generation algorithm in GRASS. This algorithm is also used to evaluate solar radiation and its relation to vegetation types.
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Avalanche risk management using GRASS GIS
Marco Ciolli, Paolo Zatelli
The GRASS system has been used to evaluate avalanche risk. This has been done by combining heterogeneous data. Val di Pejo, located in the northwestern Trentino, an Italian alpine region which shows frequent and sometimes huge avalanche phenomena, has been selected as test area.
A morphologic risk has been defined in those areas where the slope is between 28 and 55 for a minimum surface of about 625 m2 with an upstream slope change greater than 10.
An algorithm which uses these morphologic rules has been developed and applied using the GRASS MAPCALC feature to obtain a map of the "morphologic risk", i.e. areas showing an avalanche probability based only on their geometric features.
The ability of the vegetation to protect against the avalanche phenomena has been evaluated by recognizing three different coverage types depending on their density, since the latter influences their ability to avoid the creation of a compact and homogeneous snow layer. A map of the vegetation's protection ability has been obtained. vegetation types has been obtained using the information of the Trento's Forest Management Bureau. The boundaries of the vegetation types in the maps used for forest management are generally approximated, so it has been necessary to verify the real extension of the different kinds of vegetation. An orthophoto has been obtained by differential rectification of digitalized aerial photographs using the DTM and some control points in GRASS. The orthoimages have been used to test the real location of the boundaries and the extension of the parcels.
The real ability of the different vegetation classes to offer protection against avalanches has been evaluated comparing the morphologic avalanche risk area with the extension of the events occurred. The ratio between the real surface covered by avalanches on the C.L.P.V. "Carta di Localizzazione Probabile delle Valanghe" (C.L.P.V. Possible Avalanche Location Map) and the potential surface obtained following the described criteria, divided in three different vegetation classes, highlights the importance of the vegetation coverage in protecting from avalanche risk.
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Meteorological data to apple ripening model
Marco Colombo, Marco Ciampa
Aiming at an estimation of harvest time and an evaluation of fruit quality of a Golden Delicious
apple cultivar, a spatial interpolation of temperature and solar radiation has been performed,
searching for temporal and spatial relations among meteorological data and chemicalphysical
parameters, in GRASS frame. The study as been carried out using meteorological data obtained
from 12 stations in an alpine valley for the period 19951998. The spatial interpolation method
yielding the least mean error for daily temperatures (about 1C) is the inversesquareddistance,
performed after a homogenization of values, all carried at a standard level of 0 m, making use of a
second degree equation for modelling the vertical profile. The computation of mean errors was
carried out by means of crossvalidation. Measured solar radiation was submitted to computation
algorithms in GRASS in order to obtain the spatial distribution of radiation on an inclined plane
with several aspects. The result of interpolation were used for a agricultural model: the prediction
of harvest time and quality of apples.
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Incremental risk modeling and management with GRASS web interfaces
Stefano Merler, Lorenzo Potrich, Cesare Furlanello
Nel controllo dell'evoluzione di eventi di natura geografica ed in particolare nel monitoraggio di fenomeni che comportano rischio ambientale, si rende spesso indispensabile consultare e aggiornare le informazioni contenute in un sistema informativo geografico (GIS) centralizzato da parte di operatori distribuiti sul territorio. In questo lavoro, è analizzata una soluzione al problema sviluppata in ambiente GRASS. Come esempio di applicazione è presentata un'interfaccia web per la gestione della mappa di rischio degli investimenti stradali di ungulati in Trentino. In particolare, l'applicazione consente l'inserimento delle informazioni all'interno di un database in ambiente PostgreSQL interfacciato al GISGRASS.
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Grass utilization to realize spatial distribution of crops water requirements in an alpine valley
Valentina Portolan, Marco Ciampa
Aiming at an estimation of crop daily water requirements, a spatial interpolation of temperature,
potential evapotranspiration (PET) and precipitation has been performed in GRASS frame. The
study as been carried out using meteorological data obtained from 12 stations and 5 rain gauges in
an alpine valley for the period 19941998. The spatial interpolation method yielding the least mean
error for daily temperatures (about 1C) is the inversesquareddistance, performed after a
homogenization of values, all carried at a standard level of 0 m, making use of a second degree
equation for modelling the vertical profile. For the interpolation of precipitation, the inverse
squareddistance method wase implemented with a mean error for the rainy days of about 3060%.
The computation of mean errors was carried out by means of crossvalidation. The implementation
of Hargreaves' equation in GRASS provided the spatial distribution of daily PET. The result of
interpolation were used for a agricultural model: the computation of crop daily water requirements.
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Integration of GRASS within applications of geographic location on board of buses
Marco Valagussa
Within a more general project about management and control of public transport services, provided
by SAD in Bolzano/Bozen, the necessity has arisen of managing the cartographies of Bolzano
county and partly of Trento county.
The service rods and the description of connections among them have been necessary to manage on
board buses services.
GRASS has been utilized for:
 raster maps acquisition of both provinces into UTM coordinates;
 pointing out of rods, of ways of connection among them and service lines necessary to settle the service paths of buses;
 providing applications, lacking of knowledge of utilized GIS solution, with a Xwindow containing as background the cartographic maps of the required area with the drawing of rods and the connections inside. On this Xwindow the application superimpses its information.
Software per leggere i documenti
in formato pdf
Geomatics Workbooks n° 1
Editorial Board: Maria A. Brovelli, Ludovico Biagi, Marco NegrettiEditor: Maria A. Brovelli