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Abstract We present an open-source computational tool for the 2D simulation of the Diffusive-Logistic Growth (DLG) model. The r.recovery module offers a complete environment for the simulation of forestry regeneration in conservation areas and includes a built-in tool for calibration and validation of the model parameters through the use of standard and freely available satellite imagery. It was implemented as an add-on to the GRASS software, a largely applied open-source Geographic Information System (GIS). To illustrate its application, we present a complete case study of forest regeneration carried out in the Espigão Alto State Park (EASP), Brazil, from which we assess typical values of forest diffusion and growth rate parameters, along with the prognostics of forest density status for the coming decades. We observe that the r.recovery tool can be advantageously applied by forestry managers and policy-makers as a form of acquiring technical and scientifically-based information for strategy development and decision-making. Highlights • This research makes a state-of-the-art forestry modeling framework available for a large public. • The module can be coupled to hydrological models in long-term simulations. • The module is user-friendly and can enhance the efficiency and response time of forestry management processes. • A complete walkthrough is presented to illustrate the application of the module. • The module is open-source and freely available for download at http://modelagemambientaluffs.blogspot.com.br/. [ABSTRACT FROM AUTHOR]

Spatial distribution and pattern recognition of geologic lineaments are very effective in hazard risk evaluation. To make the process automated, various algorithms with various data sources were applied. This paper aims to make a review on such algorithms as well as data sources used. Comparative analysis of the LINE algorithm in PCI Geomatica and Hough Transformation in MATLAB has been conducted to explore the procedural accuracy with reference to existing landslides in the Darjeeling Himalayan region. Another comparison was made based on data sources like Landsat-8 OLI and digital elevation model, with reference to the same. As lineament density affects the landslide occurrences predominantly, the output lineament density by these two methods as well as with ground reflection and ground elevation data, were correlated with that of the landslide inventory map. A relational illustration was also done in between the lithological thrust direction and the direction of the individual lineament outputs. Hence, this study provides a decision on the use of a reliable method and data source for the automated lineament extraction which can be considered as generating an output with higher accuracy and, hence, safer for using it in the structural planning and execution of projects on various natural hazard studies. [ABSTRACT FROM AUTHOR]

The availability of continental and global-scale spatio-temporal geographical data sets and the requirement to efficiently process, analyse and manage them led to the development of the temporally enabled Geographic Resources Analysis Support System (GRASS GIS). We present the temporal framework that extends GRASS GIS with spatio-temporal capabilities. The framework provides comprehensive functionality to implement a full-featured temporal geographic information system (GIS) based on a combined field and object-based approach. A significantly improved snapshot approach is used to manage spatial fields of raster, three-dimensional raster and vector type in time. The resulting timestamped spatial fields are organised in spatio-temporal fields referred to as space-time data sets. Both types of fields are handled as objects in our framework. The spatio-temporal extent of the objects and related metadata is stored in relational databases, thus providing additional functionalities to perform SQL-based analysis. We present our combined field and object-based approach in detail and show the management, analysis and processing of spatio-temporal data sets with complex spatio-temporal topologies. A key feature is the hierarchical processing of spatio-temporal data ranging from topological analysis of spatio-temporal fields over boolean operations on spatio-temporal extents, to single pixel, voxel and vector feature access. The linear scalability of our approach is demonstrated by handling up to 1,000,000 raster layers in a single space-time data set. We provide several code examples to show the capabilities of the GRASS GIS Temporal Framework and present the spatio-temporal intersection of trajectory data which demonstrates the object-based ability of our framework. [ABSTRACT FROM PUBLISHER]

Good estimates of ecosystem complexity are essential for a number of ecological tasks: from biodiversity estimation, to forest structure variable retrieval, to feature extraction by edge detection and generation of multifractal surface as neutral models for e.g. feature change assessment. Hence, measuring ecological complexity over space becomes crucial in macroecology and geography. Many geospatial tools have been advocated in spatial ecology to estimate ecosystem complexity and its changes over space and time. Among these tools, free and open source options especially offer opportunities to guarantee the robustness of algorithms and reproducibility. In this paper we will summarize the most straightforward measures of spatial complexity available in the Free and Open Source Software GRASS GIS, relating them to key ecological patterns and processes. [ABSTRACT FROM AUTHOR]

A set of computational tools and climatic data, tentatively named PVMAPS, is presented which makes it possible to calculate solar radiation and photovoltaic system power on inclined and/or sun-tracking surfaces over large geographical areas at arbitrarily high spatial resolution. Calculations of solar radiation and photovoltaic performance are done using validated models published in the scientific literature. The software has been implemented as modules in the open-source GRASS Geographical Information System and is delivered together with scripts to perform the calculations for any geographical region in the area covered by the data. The accompanying data set includes information about elevation, horizon height, average temperatures, solar radiation (direct and diffuse components) as well as data to calculate the effects of wind and spectral variations on PV performance. The geographical extent of the data at present includes Europe, Africa and most of Asia. All tools and data are freely available at no cost. [ABSTRACT FROM AUTHOR]

The aim of this work is to integrate the Minimal Glacier Model in a Geographic Information System Python module in order to obtain spatial simulations of glacier retreat and to assess the future scenarios with a spatial representation. The Minimal Glacier Models are a simple yet effective way of estimating glacier response to climate fluctuations. This module can be useful for the scientific and glaciological community in order to evaluate glacier behavior, driven by climate forcing. The module, called r.glacio.model , is developed in a GRASS GIS ( GRASS Development Team, 2016 ) environment using Python programming language combined with different libraries as GDAL, OGR, CSV, math, etc. The module is applied and validated on the Rutor glacier, a glacier in the south-western region of the Italian Alps. This glacier is very large in size and features rather regular and lively dynamics. The simulation is calibrated by reconstructing the 3-dimensional dynamics flow line and analyzing the difference between the simulated flow line length variations and the observed glacier fronts coming from ortophotos and DEMs. These simulations are driven by the past mass balance record. Afterwards, the future assessment is estimated by using climatic drivers provided by a set of General Circulation Models participating in the Climate Model Inter-comparison Project 5 effort. The approach devised in r.glacio.model can be applied to most alpine glaciers to obtain a first-order spatial representation of glacier behavior under climate change. [ABSTRACT FROM AUTHOR]

Abstract: Measurement of radionuclides from environmental samples includes a wide variety of matrix compositions and densities. To improve the traceability of environmental monitoring, LNE-LNHB intends to produce mixed γ-ray reference materials with a known mass activity and a composition as representative as possible of real environmental samples. This paper describes the preparation and characterization of a low density treated grass matrix spiked with mixed γ-emitters. This material was used in a proficiency test exercise whose results are presented. [Copyright &y& Elsevier]

Abstract: The assessment of species diversity in relatively large areas has always been a challenging task for ecologists, mainly because of the intrinsic difficulty to judge the completeness of species lists and to undertake sufficient and appropriate sampling. Since the variability of remotely sensed signal is expected to be related to landscape diversity, it could be used as a good proxy of diversity at species level. It has been demonstrated that the relation between species and landscape diversity measured from remotely sensed data or land use maps varies with scale. However, Free and Open Source tools (allowing an access to the source code) for assessing landscape diversity at different spatial scales are still lacking today. In this paper, we aim at: i) providing a theoretical background of the mostly used diversity indices stemmed from information theory that are commonly applied to quantify landscape diversity from remotely sensed data and ii) proposing a free and robust Open Source tool (r.diversity) with its source code for calculating diversity indices (and allowing an easy potential implementation of new metrics by multiple contributors globally) at different spatial scales from remotely-sensed imagery or land use maps, running under the widely used Open Source program GRASS GIS. r.diversity can be a valuable tool for calculating landscape diversity in an Open Source space given the availability of multiple indices at multiple spatial scales with the possibility to create new indices directly reusing the code. We expect that the subject of this paper will stimulate discussions on the opportunities offered by Free and Open Source Software to calculate landscape diversity indices. [Copyright &y& Elsevier]

PyGRASS is an object-oriented Python Application Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS), a powerful open source GIS widely used in academia, commercial settings and governmental agencies. We present the architecture of the PyGRASS library, covering interfaces to GRASS modules, vector and raster data, with a focus on the new capabilities that it provides to GRASS users and developers. Our design concept of the module interface allows the direct linking of inputs and outputs of GRASS modules to create process chains, including compatibility checks, process control and error handling. The module interface was designed to be easily extended to work with remote processing services (Web Processing Service (WPS), Web Service Definition Language (WSDL)/Simple Object Access Protocol (SOAP)). The new object-oriented Python programming API introduces an abstract layer that opens the possibility to use and access transparently the efficient raster and vector functions of GRASS that are implemented in C. The design goal was to provide an easy to use, but powerful, Python interface for users and developers who are not familiar with the programming language C and with the GRASS C-API. We demonstrate the capabilities, scalability and performance of PyGRASS with several dedicated tests and benchmarks. We compare and discuss the results of the benchmarks with dedicated C implementations. [ABSTRACT FROM AUTHOR]

Abstract: Recently developed modules in GRASS GIS combine a wide variety of spatial data such as climatic, geological, and cultural in order to estimate how long-term interactions among these factors contribute to the evolution of natural environment and anthropogenic landscapes. Additionally, these modules allow users to visualize anthropogenic impacts of extensive agropastoralism on landscapes by subjecting the pre-defined catchment areas to repeated land use activities. The results emphasize the economic and ecological value of extensive agropastoralism in the marginal landscapes, which make anthropogenic activities more sustainable in the long-term. The results of this research are not only significant for its methodological contributions in anthropological archaeology but also have broader significance for researchers interested in interdisciplinary approaches in assessing the long-term dynamics of human-environment relations. [Copyright &y& Elsevier]

Motivation: The increasing availability of second-generation high-throughput sequencing (HTS) technologies has sparked a growing interest in de novo genome sequencing. This in turn has fueled the need for reliable means of obtaining high-quality draft genomes from short-read sequencing data. The millions of reads usually involved in HTS experiments are first assembled into longer fragments called contigs, which are then scaffolded, i.e. ordered and oriented using additional information, to produce even longer sequences called scaffolds. Most existing scaffolders of HTS genome assemblies are not suited for using information other than paired reads to perform scaffolding. They use this limited information to construct scaffolds, often preferring scaffold length over accuracy, when faced with the tradeoff.Results: We present GRASS (GeneRic ASsembly Scaffolder)—a novel algorithm for scaffolding second-generation sequencing assemblies capable of using diverse information sources. GRASS offers a mixed-integer programming formulation of the contig scaffolding problem, which combines contig order, distance and orientation in a single optimization objective. The resulting optimization problem is solved using an expectation–maximization procedure and an unconstrained binary quadratic programming approximation of the original problem. We compared GRASS with existing HTS scaffolders using Illumina paired reads of three bacterial genomes. Our algorithm constructs a comparable number of scaffolds, but makes fewer errors. This result is further improved when additional data, in the form of related genome sequences, are used.Availability: GRASS source code is freely available from http://code.google.com/p/tud-scaffolding/.Contact: a.gritsenko@tudelft.nlSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM PUBLISHER]

Abstract: Kilometric Abundance Index (KAI) is a common measure used in wildlife studies because it allows a straightforward comparison of species abundance in different sites or at different times. KAI expresses the ratio of the total number of individuals (or of signs of presence) observed along a transect by the total transect length covered at each site. v.transect.kia is a new tool for GRASS GIS, developed for automating the evaluation of KAI, reducing the risk of manual errors especially when handling large datasets. It can also split the transects according to one environmental variable (typically habitat type) and evaluate true 3D transect length. It calculates KAI using a point map of sightings and saves the results in the attribute table, the output can be displayed in any GIS or used for further statistical analysis. The tool has been tested on field data from Northern Italy for mountain hare (Lepus timidus), allowing a first wide-area estimate. [Copyright &y& Elsevier]

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The article discusses the interaction with geospatial information through the innovative coupling of an open source geographic information systems (GIS) tool and a three-dimensional physical modeling system. This technology allows users to modify the surface model by hand and observe the impacts on terrain parameters in real time. The laser scans the tangible model's surface while the user manipulates it, and the Geographic Resource Analysis Support System (GIS) processes the altitudes. The effects of these several terrain parameters' surface are computed and maps demonstrating the results of any changes are projected back onto the surface.

Talks about the use of Geographic Information Systems in general computational infrastructure. Development of geoinformation technology within the Open Source and Free Software community; Operating system used in geoinformation technology; Information on Geographical Resources Analysis Support System as an Open Source Free Software.

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 FROM AUTHOR]

The present work aims at introducing a basic theory, implementing methodology and algorithms for 3-D modeling, and visualizing a geologic model using the Open Source Free GIS GRASS environment. A 3-D geologic model is constructed from the boundary surfaces of geologic units and the logical model of geologic structure. The algorithms for construction and visualization of the proposed model are based on the geologic function g. The geologic function g assigns a unique geologic unit to every point in the objective 3-D space. The boundary surface that divides the objective space into two subspaces is estimated using data from field survey. The logical model showing the hierarchical relationship between these boundary surfaces and geologic units can be automatically generated based on the stratigraphic sequence and knowledge of geologic structures. Based on these algorithms, a 3-D geologic model can be constructed virtually in the GRASS GIS. Applying this model, various geologic surfaces and section models can be visualized in the GRASS GIS environment. “Nviz” was used for dynamic visualization of geologic cross-sections and generation of animated image sequences. Further, the described algorithms and methods are applied and an online 3-D geologic modeling system is developed. [ABSTRACT FROM AUTHOR]

The ability to manage and process fully three-dimensional information has only recently been made available for a few Geographical Information Systems (GIS). An example of integrated and complementary use of 2D and 3D GRASS modules for the evaluation and representation of thermally induced slope winds over complex terrain is presented. The analytic solution provided by Prandtl (1942) to evaluate wind velocity and (potential) temperature anomaly induced by either diurnal heating or nocturnal cooling on a constant angle slope is adopted to evaluate wind and temperature profiles at any point over both idealised and real complex terrain. As these quantities depend on the slope angle of the ground and on the distance from the slope surface suitable procedures are introduced to determine the coordinate n of a point in the 3D volume measured along the direction locally normal to the terrain surface. A new GRASS module has been developed to evaluate this quantity and to generate a 3D raster file where each cell is assigned the value of the cell on the surface belonging to the normal vector. The application of the algorithm implemented in GRASS to an ideal valley and to a real valley close to the city of Trento in the Alps provides results in accordance with data reported in the literature. An extension of Prandtl's (1942) model to take into account humidity and evaporation processes on the soil is also proposed and implemented. [ABSTRACT FROM AUTHOR]

The South African Weather Service (SAWS) operates a radar station network, providing data continuity back to 1994, which is unique for southern Africa. The Geographical Resources Analysis Support System (GRASS) GIS was introduced to the SAWS “Meteorological Systems and Technology” (METSYS) radar research center in 1999 where it is still used for meteorologic research. The predominantly convective nature of precipitation in southern Africa creates a public demand for severe weather information systems for convective cells. Such a system was set up in GRASS GIS, using rule-based expert systems to classify convective clouds. It isolates storm cells from stacks of reflectivity fields and derives information about their development stages. This data is both archived and also used to send out customised messages to target groups in specific areas of interest. Further, nationwide HTML-maps can be created, serving as an interactive front-end for a web-based weather information system. This service can also be made accessible from remote locations by broad-casting it as a datastream from satellite through the Worldspace digital radio system. [ABSTRACT FROM AUTHOR]

This study presents a spatiotemporal analysis tool, called Shyska. This tool allows the simulation and prediction of flash floods in semiarid basins. Shyska has been developed by Geographical Information System (GIS)-embedded functions, allowing the integration of hydrometeorological information from modern technologies of data acquisition in real time. A Digital Elevation Model (DEM) is used in order to obtain the relevant parameters from the integrated rainfall-runoff models. Some of its most relevant modules and methodology employed for its development are described. Case studies in basins of south-east Spain illustrate the applicability of the proposed techniques. [ABSTRACT FROM AUTHOR]

During the past few decades, numerous missions to Mars have sent information about the red planet. The missions have shown that Mars has ice on its poles and that ice could be present all over the planet subsurface. The presence of ice on the subsurface could drive particular geological structures called ‘wrinkle ridges’. In this work, Viking image data and the latest Mars Global Suveyor (MGS) data have been imported and stored in a common geospatial database using GRASS GIS as a tool for planetary geology. This study has focused on a subregion of Solis Planum where wrinkle ridges have been localised and both Viking images and MGS altimetry and imagery data are available. Raster data at different resolutions and with different projection parameters have been imported into GRASS GIS and projected in a common reference system. Raw, unprojected data have been processed and rectified using the GRASS image modules. Imagery data have been used to detect planimetric features, whereas basic morphometrical analysis has been performed from the gridded elevation data coming from MGS Mars Orbiter Laser Altimeter. [ABSTRACT FROM AUTHOR]

Environmental observations are usually sampled at irregularly spaced points, but, in most cases, are representative of continuous phenomena; therefore, to restore the original information a continuous thematic map should be interpolated from the available observations. To interpolate the thematic map, the stochastic approach is often the best method to apply: it is based on the hypothesis that the observed phenomenon is the sum of a deterministic trend and a stochastic process. Usually, the stochastic approaches implemented in GIS software require a priori knowledge of the deterministic trend: a simplified and automated approach to the trend model selection has been studied. One of the main advantages of the stochastic prediction approaches is that they make available both the prediction map (thematic map) and a related prediction error map; starting from these two information layers a procedure has been implemented to verify if in some areas the predicted data are within an assigned range or exceed a threshold value at some certain degree of probability. The procedures were developed by creating GRASS commands calling upon and integrating the Gstat statistics program, and commands which allow the probabilistic computing of risk areas. [ABSTRACT FROM AUTHOR]