Fondazione Edmund Mach (FEM) IASMA Research and Innovation Centre Environment and Natural Resources Area GIS and Remote Sensing Unit 38010 S. Michele all'Adige (Trento), Italy
Abstract: Geomorphometry is the science of quantitative land-surface analysis. It draws upon mathematical, statistical, and image-processing techniques to quantify the shape of earthâs topography at various spatial scales. The focus of geomorphometry is the calculation of surface-form measures (land-surface parameters) and features (objects), which may be used to improve the mapping and modelling of landforms to assist in the evaluation of soils, vegetation,land use, natural hazards, and other information.This book provides a practical guide to preparing Digital Elevation Models(DEM) for analysis and extracting land-surface parameters and objects from DEMs through a variety of software. It further offers detailed instructions on applying parameters and objects in soil, agricultural, environmental and earth sciences. This is a manual of state-of-the-art methods to serve the various researchers who use geomorphometry.Soil scientists will use this book to further learn the methods for classifying and measuring the chemical, biological, and fertility properties of soils and gain a further understaing of the role of soil as a natural resource. Geologists will find value in the instruction this book provides for measuring the physical features of the soil such as elevation, porosity, and structure which geologists use to predict natural disasters such as earthquakes, volcanoes, and flooding.* Technical details on a variety of software packages allow researchers to solve real-life mapping issues* Provides soil and agronomy researchers best practice techniques for soil data analysis to assist in enhanced land-use and planning* Offers geologists essential tactics for better environmental management by providing a comprehensive analysis of the physical features of soil* Companion website includes access to the latest technological advancements previously unpublished in any other comprehensive source: geomorphometry software, DEM data sources, and applications
Abstract: This book focuses on the nature and characteristics of open source geospatial(OSG) software. TheÃÂ role of OSG approaches in spatial data handling is the cross-cutting theme of the book. Various sub-themes are explored are explored that introduce readers unfamiliar to OSG software to the nature, purpose and applications of OS programming, and to the key new OS tools and their application within the geospatial data domain. The book also includes a discussion of new tools, approaches and applications for those already using OS approaches to software development.
Abstract: With this third edition of Open Source GIS: A GRASS GIS Approach, we enter the new era of GRASS6, the first release that includes substantial new code developed by the International GRASS Development Team. The dramatic growth in open source software libraries has made the GRASS6 development more efficient, and has enhanced GRASS interoperability with a wide range of open source and proprietary geospatial tools. Thoroughly updated with material related to the GRASS 6, the third edition includes new sections on attribute database management and SQL support, vector networks analysis, lidar data processing and new graphical user interfaces. All chapters were updated with numerous practical examples using the first release of a comprehensive, state-of-the-art geospatial data set. Open Source GIS: A GRASS GIS Approach (third edition) preserves the continuity of previous editions by maintaining the proven bookâs structure and continues to target professional audience composed of researchers and practitioners in government and industry as well as graduate students interested in geospatial analysis and modeling. URL: http://www.grassbook.org/
Abstract: To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioural data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals' environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.
Abstract: Environmental heterogeneity is considered to be one of the main factors associated with biodiversity given that areas with highly heterogeneous environments can host more species due to their higher number of available niches. In this view, spatial variability extracted from remotely sensed images has been used as a proxy of species diversity, as these data provide an inexpensive means of deriving environmental information for large areas in a consistent and regular manner. The aim of this review is to provide an overview of the state of the art in the use of spectral heterogeneity for estimating species diversity. We will examine a number of issues related to this theme, dealing with: i) the main sensors used for biodiversity monitoring, ii) scale matching problems between remotely sensed and field diversity data, iii) spectral heterogeneity measurement techniques, iv) types of species taxonomic diversity measures and how they influence the relationship between spectral and species diversity, v) spectral versus genetic diversity, and vi) modeling procedures for relating spectral and species diversity. Our review suggests that remotely sensed spectral heterogeneity information provides a crucial baseline for rapid estimation or prediction of biodiversity attributes and hotspots in space and time.
Abstract: Continuous monitoring of extreme environments, such as the European Alps, is hampered by the sparse and/or irregular distribution of meteorological stations, the difficulties in performing ground surveys and the complexity of interpolating existing station data. Remotely sensed Land Surface Temperature (LST) is therefore of major interest for a variety of environmental and ecological applications. But while MODIS LST data from the Terra and Aqua satellites are aimed at closing the gap between data demand and availability, clouds and other atmospheric disturbances often obscure parts or even the entirety of these satellite images. A novel algorithm is presented in this paper, which is able to reconstruct incomplete MODIS LST maps. All nine years of the available daily LST data (2000âÂÂ2008) have been processed, allowing the original LST map resolution of 1,000 m to be improved to 200 m, which means the resulting LST maps can be applied at a regional level. Extracted time series and aggregated data are shown as examples and are compared to meteorological station time series as an indication of the quality obtained.
Abstract: Forests are among the most important habitats of the Earth for several ecological reasons and their management is a prior task when dealing with landscape conservation. Thematic maps and remote sensing data are powerful tools to be used in landscape planning and forest management; nevertheless, most of the European and Mediterranean forest monitoring and conservation programs do not take into account the continuity of the variation of habitats within the landscape but they only rely on boolean classification methods. The utilisation of a classification method that applies a continuity criterion is fundamental because it is expected to better represent the ecological gradients within a landscape. The aim of this paper is to assess the amount of classification uncertainty related to crisp (boolean) classes, particularly focusing on forest identification uncertainty. Forest fuzzy membership of the Tuscany region (Italy) derived from a Landsat ETM+ image scene was compared with the widely used crisp datasets in European forests management and conservation practices, i.e. the European JRC Forest/Non-Forest map, the CORINE Land Cover 2000 (levels 1 and 2), as well as the Global Land Cover 2000, in order to qualitatively and quantitatively assess the separability of crisp classes with respect to forest fuzzy membership. A statistically significant (p < 0.001) forest fuzzy membership separability among the considered crisp classes was found. Despite the crisp dataset and hierarchical level taken into account, both forest and non-forest crisp classes showed a high degree of forest fuzzy membership variability. Therefore, given the intrinsic mixture of crisp land cover classes, ecological studies on forestal ecosystems should rigorously take into account the classification uncertainty related to a crisp view of ecological entities which are being mapped.
Abstract: To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioural data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals' environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.
Abstract: Few studies exist that explicitly analyse the effect of grain, i.e. the sampling unit dimension, on vascular plant species turnover (beta-diversity) among sites. While high beta-diversity is often a result of high environmental heterogeneity, remotely sensed spectral distances among sampling units may be used as a proxy of environmental gradients which spatially shape the patterns of species turnover. In this communication, we aimed to (i) test the potential relation between spectral variation and species beta-diversity in a savanna environment and to (ii) investigate the effect of grain on the achieved patterns. Field data gathered by the BIOTA Southern Africa biodiversity monitoring programme were used to model the relation between spectral variation and species turnover at different spatial grains (10 m x 10 m and 20 m x 50 m). Our results indicate that the overall fit was greater at the larger grain size, confirming the theoretical assumption that using a lower grain size would generally lead to a higher noise in the calculation of species turnover. This communication represents one of the first attempts at relating beta-diversity to spectral variation, while incorporating the effects of grain size in the study. The results of this study could have significant implications for biodiversity research and conservation planning at a regional or even larger spatial scale.
Abstract: BACKGROUND: The Western Tick-borne encephalitis (TBE) virus often causes devastating or lethal disease. In Europe, the number of human TBE cases has increased dramatically over the last decade, risk areas are expanding and new foci are being discovered every year. The early localisation of new TBE foci and the identification of the main risk factors associated with disease emergence represent a priority for the public health community. Although a number of socio-economic parameters have been suggested to explain TBE upsurges in eastern Europe, the principal driving factors in relatively stable western European countries have not been identified. METHODOLOGY/PRINCIPAL FINDINGS: In this paper, we analyse the correlation between the upsurge of TBE in 17 alpine provinces in northern Italy from 1992 to 2006 with climatic variables, forest structure (as a proxy for small mammal reservoir host abundance), and abundance of the principal large vertebrate tick host (roe deer), using datasets available for the last 40 years. No significant differences between the pattern of changes in climatic variables in provinces where TBE has emerged compared to provinces were no clinical TBE cases have been observed to date. Instead, the best model for explaining the increase in TBE incidence in humans in this area include changes in forest structure, in particular the ratio of coppice to high stand forest, and the density of roe deer. CONCLUSION/SIGNIFICANCE: Substantial changes in vegetation structure that improve habitat suitability for the main TBE reservoir hosts (small mammals), as well as an increase in roe deer abundance due to changes in land and wildlife management practices, are likely to be among the most crucial factors affecting the circulation potential of Western TBE virus and, consequently, the risk of TBE emergence in humans in western Europe. We believe our approach will be useful in predicting TBE risk on a wider scale.
Abstract: Roe deer Capreolus capreolus are among the most important feeding hosts for the sheep tick Ixodes ricinus, thus contributing to the occurrence of tick-borne diseases in Europe. Tick-borne encephalitis (TBE), which is transmitted by co-feeding of larvae and nymphs on rodents, requires precise climatic conditions to occur. We used roe deer as sentinels for potential circulation of TBE virus in Northern Italy, by examining the association between tick infestation, occurrence of TBE human cases, geographical and climatic parameters. Tick infestation on roe deer, and particularly frequency of co-feeding, was clearly associated with the geographic location and the autumnal cooling rate. Consistently, TBE occurrence in humans was geographically related to co-feeding tick abundance. The surveillance of tick infestation on roe deer, combined with remotely sensed climatic data, could therefore be used as an inexpensive early risk assessment tool of favourable conditions for TBE emergence and persistence in humans.
Abstract: Geospatial (geographical) software systems (GIS) are used for creating, viewing, managing, analysing and utilising geospatial data. Geospatial data can include socioeconomic, environmental, geophysical, and technical data about the Earth and societal infrastructure and it is pivotal in environmental modelling and management (EMM). Desktop, web-based, and embedded geospatial systems have become an essential part of EMM, providing pre- or post-processing of geospatial data, analysis and visualisation of results or a graphical user interface (GUI). Many local, regional, national, and international efforts are underway to create geospatial data infrastructures and tools for viewing and using geospatial data. When environmental attribute data is linked to these infrastructures, powerful tools for environmental management are instantly created. The growing culture of free/libre and open source software (FOSS) provides an alternative approach to software development for the field of GIS (FOSS4G). To provide an overview of FOSS4G for EMM, we analyse platforms, software stacks, and EMM workflows. In the FOSS world the barriers to interoperability are low and thus the software stack tends to be thicker than in the proprietary platform. The FOSS4G world thrives on the evolution of software stacks and platforms. We provide examples of software stacks built from current FOSS4G that support EMM workflows and highlight the advantages of FOSS4G solutions including opportunities to redistribute resulting modelling tools freely to end-users and to support general goals of openness and transparency with respect to modelling tools.
Abstract: New human cases of tick-borne encephalitis (TBE) have recently been recorded outside the recognised foci of this disease, i.e. in the province of Trento in northern Italy. In order to predict the highest risk areas for increased TBE virus activity, we have combined cross-sectional serological data, obtained from 459 domestic goats, with analysis of the autumnal cooling rate based on Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data. A significant relationship between finding antibodies against the virus in serum (seroprevalence) in goats and the autumnal cooling rate was detected, indicating that the transmission intensity of the virus does not only vary spatially, but also in relation to climatic factors. Virus seroprevalence in goats was correlated with the occurrence of TBE in humans and also with the average number of forestry workers' tick bites, demonstrating that serological screening of domestic animals, combined with an analysis of the autumnal cooling rate, can be used as early-warning predictors of TBE risk in humans.
Abstract: We present a modelling framework for predicting forest areas. The framework is obtained by integrating a machine learning software suite within the GRASS Geographical Information System (GIS) and by providing additional methods for predictive habitat modelling. Three machine learning techniques (Tree-Based Classification, Neural Networks and Random Forest) are available in parallel for modelling from climatic and topographic variables. Model evaluation and parameter selection are measured by sensitivity-specificity ROC analysis, while the final presence and absence maps are obtained through maximisation of the kappa statistic. The modelling framework is applied at a resolution of 1km. with Iberian subpopulations of Pinus sylvestris L. forests. For this data set, the most accurate algorithm is Breiman's random forest, an ensemble method which provides automatic combination of tree-classifiers trained on bootstrapped subsamples and randomised variable sets. All models show a potential area of P.syluestris for the Iberian Peninsula which is larger than the present one, a result corroborated by regional pollen analyses. (c) 2006 Elsevier B.V All rights reserved.
Abstract: In this paper we present a suite of new image processing tools for the GRASS Geographic Information System. New modules are suggested to support improved and semi-automated geocoding of vertical imagery. The ortho-rectification procedures have been extended to rectify oblique imagery from digital hand-held cameras for rendering purposes. Multi- and hyperspectral image analysis has been implemented to derive landuse/landcover maps at subpixel resolution. Image fusion with the Brovey transform is shown. We finally show high performance SMAP image classification on an openMosix cluster.
Abstract: This paper reports on the processing of time series of MODIS NDVI/EVI and LST satellite data in a Geographical Information System (GIS). The required data preparations for the integration of MODIS data in GIS is described with focus on the reprojection from MODIS/Sinusoidal projection to national coordinate systems. To remove low quality pixels, the MODIS quality maps are utilised. We explain subsequent filtering of Land Surface Temperature maps with an outlier detector to eliminate originally undetected cloud pixels. Further analysis of time series is briefly discussed as well as related landscape epidemiological applications in the field of tick-borne diseases.
Abstract: One of the undesired effects of software evolution is the proliferation of unused components, which are not used by any application. As a consequence, the size of binaries and libraries tends to grow and system maintainability tends to decrease. At the same time, a major trend of today's software market is the porting of applications on hand-held devices or, in general, on devices which have a limited amount of available resources. Refactoring and, in particular, the miniaturization of libraries and applications are therefore necessary. We propose a Software Renovation Framework (SRF) and a toolkit covering several aspects of software renovation, such as removing unused objects and code clones, and refactoring existing libraries into smaller more cohesive ones. Refactoring has been implemented in the SRF using a hybrid approach based on hierarchical clustering, on genetic algorithms and hill climbing, also taking into account the developers' feedback. The SRF aims to monitor software system quality in terms of the identified affecting factors, and to perform renovation activities when necessary. Most of the framework activities are language-independent, do not require any kind of source code parsing, and rely on object module analysis. The SRF has been applied to GRASS, which is a large open source Geographical Information System of about one million LOCs in size. It has significantly improved the software organization, has reduced by about 50% the average number of objects linked by each application, and has consequently also reduced the applications' memory requirements. (c) 2004 Elsevier Inc. All rights reserved.
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.
Abstract: Recent developments of the communication technologies in the last years opened a new dimension to Geographical Information Systems and Geoinformation Techno-logies. 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.
Abstract: There may be several reasons to reduce a software system to its bare bone removing the extra fat introduced during development or evolution. Porting the software system on embedded devices or palmtops are just two examples. This paper presents an approach to re-factoring libraries with the aim of reducing the memory requirements of executables. The approach is organized in two steps. The ï¬Ârst step deï¬Ânes an initial solution based on clustering methods, while the subsequent phase reï¬Ânes the initial solution via genetic algorithms. In particular, a novel genetic algorithm approach, considering the initial clusters as the starting population, adopting a knowledge-based mutation function and a multi-objective ï¬Âtness function, is proposed. The approach has been applied to several medium and large-size open source software systems such as GRASS, KDE-QT, Samba and MySQL, allowing to effectively produce smaller, loosely coupled libraries, and to reduce the memory requirement for each application.
Abstract: This paper discusses the recent developments of the Geographic Resources Analysis Support System (GRASS), a general purpose geographical information system, which focus on the improvement of 2D and 3D raster and vector data processing and analysis tools and 3D visualization capabilities. Also discussed are the applications of GRASS in different fields such as landscape epidemiology, hydrologic and sediment transport modelling, and short term coastal change assessment.
Abstract: This article outlines the salient features and current state of development of the Open Source GIS GRASS. We discuss the concepts and issues related to the development of GRASS that represents the only full fledged, multi-platform GIS available as OSS. Further, we highlight the potential of GRASS GIS in developing spatial data infrastructure and put forth a proposal for establishing a GRASS Consortium to support, nurture and accelerate furher developments.
Abstract: How to set-up GRASS GIS; computing DEMs from various data sources; local and regional land-surface parameters; land-surface modelling and applications; DEM quality analysis; GRASS command examples with online database
Abstract: Geospatial (geographical) software systems (GIS) are used for creating, viewing, managing, analysing and utilising geospatial data. Geospatial data can include socioeconomic, environmental, geophysical, and technical data about the Earth and societal infrastructure and it is pivotal in environmental modelling and management (EMM). Desktop, web-based, and embedded geospatial systems have become an essential part of EMM, providing pre- or post-processing of geospatial data, analysis and visualisation of results or a graphical user interface (GUI). Many local, regional, national, and international efforts are underway to create geospatial data infrastructures and tools for viewing and using geospatial data. When environmental attribute data is linked to these infrastructures, powerful tools for environmental management are instantly created. The growing culture of free/libre and open source software (FOSS) provides an alternative approach to software development for the field of GIS (FOSS4G). To provide an overview of FOSS4G for EMM, we analyse platforms, software stacks, and EMM workflows. In the FOSS world the barriers to interoperability are low and thus the software stack tends to be thicker than in the proprietary platform. The FOSS4G world thrives on the evolution of software stacks and platforms. We provide examples of software stacks built from current FOSS4G that support EMM workflows and highlight the advantages of FOSS4G solutions including opportunities to redistribute resulting modelling tools freely to end-users and to support general goals of openness and transparency with respect to modelling tools.
Abstract: GRASS is a full featured, general purpose Open Source geographic information system (GIS) with raster, vector and image processing capabilities. There has been constant development of the software since 1982, with recent major improvements reflecting renewed efforts by the international development team to make it one of the core components of the Open Source geospatial software stack. It can handle 2D and 3D raster data, includes a topological 2D/3D vector engine, network analysis functions, and SQL-based attribute management. This chapter presents an overview and practical examples of the GRASS 6 capabilities relevant to environmental and planning applications including new functionality. Enhancements to 3D visualization and approaches to environmental models are also discussed, as well as image processing routines pertaining to LIDAR and multi-band imagery. Integration of GRASS with other Open Source software packages for geostatistical analysis, cartographic output and Web GIS applications are described. Trends for future development are also discussed.
Abstract: There may be several reasons to reduce a software system to its bare bone removing the extra fat introduced during development or evolution. Porting the software system on embedded devices or palmtops are just two examples.This paper presents an approach to re-factoring libraries with the aim of reducing the memory requirements of executables. The approach is organized in two steps. The first step defines an initial solution based on clustering methods, while the subsequent phase refines the initial solution via genetic algorithms.In particular, a novel genetic algorithm approach, considering the initial clusters as the starting population, adopting a knowledge-based mutation function and a multi-objective fitness function, is proposed.The approach has been applied to several medium and large-size open source software systems such as GRASS, KDE-QT, Samba and MySQL, allowing to effectively produce smaller, loosely coupled libraries, and to reduce the memory requirement for each application.
Abstract: We discuss how sophisticated machine learning methods may be rapidly integrated within a GIS for the development of new approaches in landscape epidemiology. A multitemporal predictive map is obtained by modeling in R, analyzing geodata and digital maps in GRASS, and managing biodata samples and weather data in PostgreSQL. In particular, we present a risk mapping system for tick-borne diseases, applied to model the risk of exposure to Lyme borreliosis and tick-borne encephalitis (TBE) in...
Abstract: The presentation describes the new GRASS 5.1 vector library architecture. This new architecture overcomes the vector limitations of GRASS 4.x-5.0 by extending the vector support with attributes stored in external relational databases and by new 3D capabilities. Besides internal file based storage the geometry may alternatively be stored in PostGIS database. This enables users to maintain large data sets with simultaneous write access. External GIS formats such as SHAPE-files may be used...
Abstract: Software miniaturization is a form of software re-factoring focused on reducing an application to the bare bone. Porting an application on a hand-held device is very likely to require a preliminary step of software miniaturization, plus the development of device drivers dedicated to the new environment and hardware architecture. This paper presents the process and the lessons learned re-factoring a large Open Source application to get rid of extra fat, to introduce shared libraries, to remove circular dependencies among libraries and, more generally, to minimize inter-library dependencies. While the final goal was to fully exploit shared libraries capabilities, among the various possibilities we defined a process based on the existing knowledge about the application, and aimed to minimize the maintenance effort required by the miniaturization activities.
Abstract: We report on work in progress on the integration of the GRASS GIS, the R data analysis programming language and environment, and the PostgreSQL database system. All of these components are released under Open Source licenses. This means that application programming interfaces are documented both in source code and in other materials, simplifying insight into the workings of the respective systems. Current versions of this note and accompanying code are to be found at the Hannover GRASS site,...
Abstract: Geospatial software tools (GIS) are used for creating, viewing, managing, analyzing, and utilizing geospatial data. Geospatial data can include socio-economic, environmental, geophysical, and technical data about the Earth and societal infrastructure and it is pivotal in environmental modeling and management (EMM). Desktop, web-based, and embedded geospatial tools and systems have become an essential part of EMM. Environmental simulation models often require pre- or post-processing of geospatial data, or they can be tightly linked to a GIS, using it as a graphical user interface (GUI). Many local, regional, national, and international efforts are underway to create geospatial data infrastructures and tools for viewing and using geospatial data. When environmental attribute data is linked to these infrastructures, powerful tools for environmental management are instantly created. The growing culture of free and open source software (FOSS) provides an alternative approach to software development also in the field of GIS (FOSS4G). For a systematic look at FOSS4G for EMM platforms, software stacks, and EMM workflows need to be analyzed. Platform is a service abstraction on which software stacks are built. A software stack for FOSS4G comprises system software, data processing tools, data serving tools, user interface tools, and end-user applications. Digital map creation, support for numerical modeling, and geospatial information systems are main areas of use for FOSS4G in EMM. The dividing line between FOSS and proprietary software is fuzzy, partly because it is in the interest of developers of proprietary software to make it fuzzy and partly because the end-users are getting reluctant to buy software. In the FOSS world the barriers to interoperability are low and thus the software stack tends to be thicker than in the proprietary platform. The FOSS4G world thrives on the evolution of software stacks and platforms. Our examples show that it is possible to build software stacks from current FOSS4G to support EMM workflows. In the examples we mention for example how a particular funding agency has chosen FOSS4G solutions because of the opportunities to redistribute resulting modeling tools freely to end-users and to support general goals of openness and transparency with respect to modeling tools.
