Geographic Resources Analysis Support System Research Articles

R.randomwalk v1, a multi-functional conceptual tool for mass movement routing

Abstract. We introduce r.randomwalk, a flexible and multi-functional open-source tool for backward and forward analyses of mass movement propagation. r.randomwalk builds on GRASS GIS (Geographic Resources Analysis Support System – Geographic Information System), the R software for statistical computing and the programming languages Python and C. Using constrained random walks, mass points are routed from defined release pixels of one to many mass movements through a digital elevation model until a defined break criterion is reached. Compared to existing tools, the major innovative features of r.randomwalk are (i) multiple break criteria can be combined to compute an impact indicator score; (ii) the uncertainties of break criteria can be included by performing multiple parallel computations with randomized parameter sets, resulting in an impact indicator index in the range 0–1; (iii) built-in functions for validation and visualization of the results are provided; (iv) observed landslides can be back analysed to derive the density distribution of the observed angles of reach. This distribution can be employed to compute impact probabilities for each pixel. Further, impact indicator scores and probabilities can be combined with release indicator scores or probabilities, and with exposure indicator scores. We demonstrate the key functionalities of r.randomwalk for (i) a single event, the Acheron rock avalanche in New Zealand; (ii) landslides in a 61.5 km2 study area in the Kao Ping Watershed, Taiwan; and (iii) lake outburst floods in a 2106 km2 area in the Gunt Valley, Tajikistan.

Exposure, hazard and risk mapping during a flood event using open source geospatial technology

After a flood event there is a need to delineate the hazard footprint as quickly as possible in order to assess the magnitude of losses and to plan for the relief operations. Delineation of such hazard footprint is generally hindered by the lack of geospatial data, technology and related software packages. This paper demonstrates the use of open source data and software packages which can be used to implement most recent technology available for flood hazard footprint delineation. This study utilizes open source software packages and web applications like Geographic Resource Analysis Support System, Quantum geographic information system and Google Earth to implement a complete process of hazard mapping using remotely sensed data which include pre-processing, mapping (both hazard and exposure) and accuracy assessment. In this study, Brisbane flood event of 2011 has been taken as a case study. For built-up extraction, the Landsat 7-band image has been transformed to a stack of 3-band image using vegetation, water and built-up indices. It has been observed by scattergram analysis that these transformations make vegetation, water and built-up classes more separable. Built-up area has been delineated using supervised maximum likelihood classification on the new 3-band image. For flood hazard mapping, thresholding of near-infrared band has been utilized along with the assistance of mid-infrared band to discriminate water from built-up classes. After delineating both exposure and hazard map, final risk map due to flood event has been generated to assess the urban exposure under the flood hazard impact.

Tools for Optimizing Management of a Spatially Variable Organic Field

Geostatistical tools were used to estimate spatial relations between wheat yield and soil parameters under organic farming field conditions. Thematic maps of each factor were created as raster images in R software using kriging. The Geographic Resources Analysis Support System (GRASS) calculated the principal component analysis raster images for soil parameters and yield. The correlation between the raster arising from the PC1 of soil and yield parameters showed high linear correlation (r = 0.75) and explained 48.50% of the data variance. The data show that durum wheat yield is strongly affected by soil parameter variability, and thus, the average production can be substantially lower than its potential. Soil water content was the limiting factor to grain yield and not nitrate as in other similar studies. The use of precision agriculture tools helped reduce the level of complexity between the measured parameters by the grouping of several parameters and demonstrating that precision agriculture tools can be applied in small organic fields, reducing costs and increasing wheat yield. Consequently, site-specific applications could be expected to improve the yield without increasing excessively the cost for farmers and enhance environmental and economic benefits.

Comparison of one-dimensional and two-dimensional GRASS-GIS models for flood mapping

The first step of a risk assessment analysis is the evaluation of flood-prone areas. Its importance is considered for both managing and planning emergency activities, such as hydraulic risk reduction management, and also town planning. Nowadays, using Geographic Information System (GIS) technology for risk assessment analysis is very common. However, it is not widely used for defining inundated areas. LiDAR data, such as digital elevation models (DEM), makes GIS numerical models attractive methods for obtaining a flooded area automatically. Using GIS tools is beneficial for effective processing and accuracy assessment in comparison to traditional methods which are based on topographic maps and field surveys. A first approach (Federici & Sguerso, Bollettino SIFET 4:25–42, 2007; Marzocchi, 2009) uses a GIS module in order to simulate perifluvial flood maps, having as prerequisites (i) the conformation of the river floodplain by a high-resolution DEM and (ii) a water surface profile along the river axis calculated for a given water discharge through a generic one-dimensional (1D) hydraulic model (HEC-RAS, Basement, MIKE 11, etc.). On the other hand, a second approach uses a GIS-embedded two-dimensional (2D) model in order to simulate flooded areas due to a dam break (Cannata & Marzocchi, Nat Hazards 61(3):1143–1159, 2012). This module solves the conservative form of the 2D shallow water equations (SWE) using a finite volume method (FVM). The intercell flux is computed by a one-side upwind conservative scheme extended to a 2D problem (Ying et al., J hydraul eng-ASCE 10:977–98, 2004). The newly developed GIS module gives as output maximum intensity maps which can be directly used in a risk assessment process. Both models have been implemented in geographic resources analysis support system (GRASS)-GIS software (Neteler et al., Environ Model Softw 31:124–130, 2012; GRASS, 2013) and two new commands (r.inund.fluv and r.damflood) have been created. Both are available on the official GRASS addons website and are distributed under the terms of the GNU General Public License (GPL). In this work we present a comparison between the two models mentioned above. We analyse the possibility of integrating these two approaches. We intend to use the 1D model, GIS embedded if possible, to calculate the water surface profile along the river axis and the 2D numerical one to analyse inundation beside the river levees.

An IO-efficient parallel implementation of an R2 viewshed algorithm for large terrain maps on a CUDA GPU

A rapid and flexible parallel approach for viewshed computation on large digital elevation models is presented. Our work is focused on the implementation of a derivate of the R2 viewshed algorithm. Emphasis has been placed on input/output (IO) efficiency that can be achieved by memory segmentation and coalesced memory access. An implementation of the parallel viewshed algorithm on the Compute Unified Device Architecture (CUDA), which exploits the high parallelism of the graphics processing unit, is presented. This version is referred to as r.cuda.visibility. The accuracy of our algorithm is compared to the r.los R3 algorithm (integrated into the open-source Geographic Resources Analysis Support System geographic information system environment) and other IO-efficient algorithms. Our results demonstrate that the proposed implementation of the R2 algorithm is faster and more IO efficient than previously presented IO-efficient algorithms, and that it achieves moderate calculation precision compared to the R3 algorithm. Thus, to the best of our knowledge, the algorithm presented here is the most efficient viewshed approach, in terms of computational speed, for large data sets.

A GRASS GIS parallel module for radio-propagation predictions

Geographical information systems are ideal candidates for the application of parallel programming techniques, mainly because they usually handle large data sets. To help us deal with complex calculations over such data sets, we investigated the performance constraints of a classic master–worker parallel paradigm over a message-passing communication model. To this end, we present a new approach that employs an external database in order to improve the calculation–communication overlap, thus reducing the idle times for the worker processes. The presented approach is implemented as part of a parallel radio-coverage prediction tool for the Geographic Resources Analysis Support System (GRASS) environment. The prediction calculation employs digital elevation models and land-usage data in order to analyze the radio coverage of a geographical area. We provide an extended analysis of the experimental results, which are based on real data from an Long Term Evolution (LTE) network currently deployed in Slovenia. Based on the results of the experiments, which were performed on a computer cluster, the new approach exhibits better scalability than the traditional master–worker approach. We successfully tackled real-world-sized data sets, while greatly reducing the processing time and saturating the hardware utilization.

A temporal GIS for field based environmental modeling

Time in geographic information systems has been a research theme for more than two decades, resulting in comprehensive theoretical work, many research prototypes and several working solutions. However, none of the available solutions provides the ability to manage, analyze, process and visualize large environmental spatio-temporal datasets and the investigation and assessment of temporal relationships between them. We present in this paper a freely available field based temporal GIS (TGRASS) that fulfills these requirements. Our approach is based on the integration of time in the open source Geographic Resources Analysis Support System (GRASS). We introduce the concept of a space time dataset that is defined as a collection of time stamped raster, voxel or vector data. A dedicated set of spatio-temporal tools was implemented to manage, process and analyze space time datasets and their temporal and spatial relationships. We demonstrate the temporal GIS and environmental modeling capabilities of TGRASS by analyzing a multi-decadal European climate dataset.

Pygrass: An Object Oriented Python Application Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS)

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.

Vector–raster server-side analysis: a PostGIS benchmark

Report generation from coverages around points of interest (POIs) or in areas of interest (AOIs) is a common need in thematic research projects. The extracted information adds value to the POIs or AOIs dataset by enriching its information content. In a common scenario, POIs or AOIs are usually vector data whereas background thematic datasets are often raster data. The paper investigates different approaches for zonal statistic computation about both raster and vector data with particular focus on server-side free and open source software (FOSS)-based solutions. Extensive performance tests are based on PostGIS (the spatial extension of popular PostgreSQL (http://www.postgresql.org/) FOSS DBMS) 2.0. This version is the first to offer raster support. Previously, vector–raster analysis was not supported by any FOSS DBMS environment and such analyses were possible in a FOSS server-side environment using geographical information system (GIS) tools (e.g., Geographic Resources Analysis Support System (GRASS) GIS) and Open Geospatial Consortium (OGC) Web Processing Server. PostGIS performance data from the tests are compared to an almost standard ESRI ArcGIS desktop approach. A project aimed at monitoring fire alerts in African protected areas provides the benchmarking application. The computation of people living in the surroundings of POIs (alert points from Global Fire Information Management System) based on a world population density dataset (LandScan) is the benchmarking query. The impact of many parameters on performances is considered: the adopted tile size in the storing of the raster in the DBMS, the dimension of queried areas in relation to the above-mentioned tile size, the number of queried features.

GRASS GIS: A multi-purpose open source GIS

The GIS software sector has developed rapidly over the last ten years. Open Source GIS applications are gaining relevant market shares in academia, business, and public administration. In this paper, we illustrate the history and features of a key Open Source GIS, the Geographical Resources Analysis Support System (GRASS). GRASS has been under development for more than 28 years, has strong ties into academia, and its review mechanisms led to the integration of well tested and documented algorithms into a joint GIS suite which has been used regularly for environmental modelling. The development is community-based with developers distributed globally. Through the use of an online source code repository, mailing lists and a Wiki, users and developers communicate in order to review existing code and develop new methods. In this paper, we provide a functionality overview of the more than 400 modules available in the latest stable GRASS software release. This new release runs natively on common operating systems (MS-Windows, GNU/Linux, Mac OSX), giving basic and advanced functionality to casual and expert users. In the second part, we review selected publications with a focus on environmental modelling to illustrate the wealth of use cases for this open and free GIS.

Preliminary study of a cluster-based open-source parallel GIS based on the GRASS GIS

In response to the problem of how to give geographic information system (GIS) high-performance capabilities for certain specific GIS applications, a new GIS research direction, parallel GIS processing, has emerged. However, traditional research has focused mostly on implementing typical GIS parallel algorithms, with little discussion of how to parallelize an entire GIS package on clusters based on theory. Therefore, the authors have chosen the geographic resources analysis support system (GRASS) GIS as the object of their research and have put forward the concept of a cluster-based open-source parallel GIS (cluster-based OP-GIS) as a tool to support Digital Earth construction. The related theory includes not only the parallel computing mode, architecture, and software framework of such a system, but also various parallelization patterns. From experiments on the prototype system, it can be concluded that the parallel system has better efficiency and performance than the conventional system on certain selected modules.

A working environment for digital planetary data processing and mapping using ISIS and GRASS GIS

Since the beginning of planetary exploration, mapping has been fundamental to summarize observations returned by scientific missions. Sensor-based mapping has been used to highlight specific features from the planetary surfaces by means of processing. Interpretative mapping makes use of instrumental observations to produce thematic maps that summarize observations of actual data into a specific theme. Geologic maps, for example, are thematic interpretative maps that focus on the representation of materials and processes and their relative timing. The advancements in technology of the last 30 years have allowed us to develop specialized systems where the mapping process can be made entirely in the digital domain. The spread of networked computers on a global scale allowed the rapid propagation of software and digital data such that every researcher can now access digital mapping facilities on his desktop. The efforts to maintain planetary missions data accessible to the scientific community have led to the creation of standardized digital archives that facilitate the access to different datasets by software capable of processing these data from the raw level to the map projected one. Geographic Information Systems (GIS) have been developed to optimize the storage, the analysis, and the retrieval of spatially referenced Earth based environmental geodata; since the last decade these computer programs have become popular among the planetary science community, and recent mission data start to be distributed in formats compatible with these systems. Among all the systems developed for the analysis of planetary and spatially referenced data, we have created a working environment combining two software suites that have similar characteristics in their modular design, their development history, their policy of distribution and their support system. The first, the Integrated Software for Imagers and Spectrometers (ISIS) developed by the United States Geological Survey, represents the state of the art for processing planetary remote sensing data, from the raw unprocessed state to the map projected product. The second, the Geographic Resources Analysis Support System (GRASS) is a Geographic Information System developed by an international team of developers, and one of the core projects promoted by the Open Source Geospatial Foundation (OSGeo). We have worked on enabling the combined use of these software systems throughout the set-up of a common user interface, the unification of the cartographic reference system nomenclature and the minimization of data conversion. Both software packages are distributed with free open source licenses, as well as the source code, scripts and configuration files hereafter presented. In this paper we describe our work done to merge these working environments into a common one, where the user benefits from functionalities of both systems without the need to switch or transfer data from one software suite to the other one. Thereafter we provide an example of its usage in the handling of planetary data and the crafting of a digital geologic map.

Mapping eucalypt forest susceptible to dieback associated with bell miners ( Manorina melanophys) using laser scanning, SPOT 5 and ancillary topographical data

Mapping the location and extent of forest at risk from damaging agents or processes assists forest managers in prioritizing their planning and operational mitigation activities. In Australia, Bell Miner Associated Dieback (BMAD) refers to a form of canopy decline observed in eucalypt crowns occupied by colonies of bell miners ( Manorina melanophrys). High densities of bell miners are associated with decreased avian abundance and diversity and an increase in psyllid abundance on crown foliage. BMAD has recently been nominated as a key threatening process in New South Wales (NSW). Consequently, a modelling system for predicting bell miner distribution in coastal eucalypt forests of NSW has been developed. The presence or absence of bell miners was recorded in 130 plots located within a 12,800 ha catchment study area containing a range of eucalypt forest types. The modelling system was produced by integrating a machine learning software suite (WEKA), and the statistical software R within the geographic resources analysis support system (GRASS) geographical information system (GIS). The variable modelled was the binary variable: presence or absence of bell minors. Six modelling techniques (Logistic regression; generalised additive models; two tree-based ensemble classification algorithms, random forest and Adaboost and Neural Networks) were integrated with airborne laser scanning; SPOT 5 and topographic derived variables. Model evaluation and parameter selection were measured by three threshold dependent measures (sensitivity, specificity and kappa) and the threshold independent Receiver Operator Curve (ROC) analysis. The final presence and absence maps were obtained through maximisation of the kappa statistic and applied at a resolution of 10 m across the entire catchment study area. For this data set, the most accurate algorithm for predicting the distribution of bell miner colonies was random forest (kappa = 0.84; ROC area under curve = 0.97). Variables most commonly selected in the six models were the laser scanning metrics; coefficient of variation, skewness, and the 10th and 90th percentiles derived from the shape of the height frequency distribution which, in turn, is directly influenced by vertical structure of the forest. An image textural statistic based on the shortwave infrared (SWIR) band of SPOT 5 was also commonly selected by the models. The SWIR band is sensitive to vegetation and soil moisture content. These models predicted that forest stands with a sparse eucalypt canopy over a moist, dense understorey were susceptible to being colonised by bell miners and hence BMAD.

Estimating potential photovoltaic yield with r.sun and the open source Geographical Resources Analysis Support System

The package r.sun within the open source Geographical Resources Analysis Support System (GRASS) can be used to compute insolation including temporal and spatial variation of albedo and solar photovoltaic yield. A complete algorithm is presented covering the steps of data acquisition and preprocessing to post-simulation whereby candidate lands for incoming solar farms projects are identified. The optimal resolution to acquire reliable solar energy outputs to be integrated into PV system design software was determined to be 1 square km. A case study using the algorithm developed here was performed on a North American region encompassing fourteen counties in South-eastern Ontario. It was confirmed for the case study that Ontario has a large potential for solar electricity. This region is found to possess over 935,000 acres appropriate for solar farm development, which could provide 90 GW of PV. This is nearly 60% of Ontario’s projected peak electricity demand in 2025. The algorithm developed and tested in this paper can be generalized to any region in the world in order to foster the most environmentally-responsible development of large-scale solar farms.

A new approach to landslide geomorphological mapping using the Open Source software in the Olvera area (Cadiz, Spain)

This paper presents the preliminary results of a geomorphological survey of the Olvera area (Cadiz province, Betic Ranges, Spain) and the use of the Geographic Information System (GIS) Open Source (OS) software plus Database Management System (DBMS) for making available and distributing the landslide data over the Web. In the geomorphologic survey, different landforms have been identified in the area, including structural, anthropogenic, fluvial, karst, and slope forms. In particular, the majority of the slope forms are complex (from topple to rotational slides and falls), but there are also minor forms like debris flows and mudslides. To manage geomorphological data, an Open Source GIS was used, which contained the following components: QuantumGIS, System for Automated Geoscientific Analyses (SAGA), GIS and Geographic Resources Analysis Support System (GRASS), GIS for Digital Elevation Model (DEM) generation. A key aim was to make the project-derived data available over the Web. This was achieved using MapServer which allows for the representation of the derived geospatial data with pMapper providing the graphical Web interface. Our study highlights the process dynamics of run-off erosion in Olvera derived through the use of advanced computer-based mapping tools. The resulting map products and interpretations are available via the Internet. To date, derivative maps have been produced to improve maintenance of roads and transport and of the construction of new infrastructure.

How artefacts rule web-based communities: practices of free software development

This paper seeks to understand how complex tasks are accomplished by large web-based communities. In order to do so, we consider that technologies may embody organisational rules, hence becoming the core of coordination efforts in such communities. Our analysis is based on the concepts of translation and inscription taken from the Actor-Network Theory, while the data have been gathered using an ethnographic approach. We base our observation on the case of a Geographic Information System (GIS): the Geographic Resources Analysis Support System (GRASS) is a system developed by a small group of developers but sustained by a very large users' base located worldwide. In particular, we focus on small explanatory examples of everyday development activities of the GRASS community in relation to the internationalisation process. We focus on artefacts, such as the Concurrent Versioning System and the GRASS source code, that greatly affect the everyday activities of the community. The main result of our research is the illustration that complex tasks are accomplished by large web-based communities, thanks to many small contributions shaped and organised by the rules embodied in artefacts.

Evaluation of Agricultural Nonpoint Source (AGNPS) model for small watersheds in Korea applying irregular cell delineation

The Agricultural Nonpoint Source (AGNPS) model was tested in two small agricultural watersheds in Korea. The model was calibrated for 412.5 ha located in the Balhan watershed. The rainfall amount distinguishing between antecedent moisture conditions (AMC) I and II was changed to calibrate the runoff volume. A validation was performed for 274.1 ha located in the Banwol watershed, with similar land use and soil characteristics as the 412.5 ha in the Balhan watershed. The input data were extracted from multiple GIS layers using the Geographic Resources Analysis Support System (GRASS)–AGNPS interface. The AGNPS model was modified to treat the undisturbed forest areas as irregular cells instead of the uniform cell division currently used by AGNPS. Simulated results from the irregular cell-based scheme (ICS) and the uniform grid scheme (UGS) of ANGPS were compared with the observed data. The ICS increased runoff volume and decreased peak flow rate and sediment yields from the watershed compared to the UGS. The ICS significantly reduced the number of cells in a watershed and provided better agreement for surface runoff and peak flow rate compared to the UGS.

Open source geographical resources analysis support system (GRASS) for landslide hazard assessment

PurposeThe primary aim of this research is to investigate the application of open source geographic information system software, geographical resources analysis support system (GRASS) for landslide hazard assessment.Design/methodology/approachFive parameters affecting landslide occurrence derived from topographical, geological and land use maps of Cameron highland were used for the assessment.FindingsThe results showed that about 93 percent of the study area falls under zone II that is of low hazard, with less than 7 percent on zone III with moderate hazard and only less than 1 percent falls under zone IV, which is of high hazard.Research limitations/implicationsThe accuracy of the landslide hazard map needs to be assessed by cross‐correlation with landslide occurrence in the field.Practical implicationsThe map produced showed the potential application of GRASS as a tool for producing landslide hazard assessment map.Originality/valueThe major outcome of this research is the possible use of open source GIS software in the application of landslide hazard assessment. The capability of GRASS in performing such environmental assessment will certainly attract many researchers and organizations with limited budgets, especially in developing countries such as Malaysia.

The groundwater modeling tool for GRASS (GMTG): Open source groundwater flow modeling

Geographic Information Systems (GIS) are used to store, manipulate and visualize both spatial and non-spatial data. Because of their data manipulating capabilities, GIS have been linked to different simulation models in different research areas and are commonly used for both surface and ground water modeling. Unfortunately this has been done mainly with proprietary GIS which are expensive and which do not provide access to their source code thus making them hard to customize. In order to overcome these problems, a module was created in the Open Source Geographic Resources Analysis Support System (GRASS) GIS to integrate it with the finite difference groundwater flow model MODFLOW, to take full advantage of the GIS capabilities. The results obtained with this module, when compared to those obtained with an existing MODFLOW pre and post-processor show that it can be used to develop groundwater flow models using uniform grid spacing on the horizontal plane. This module provides a tool for groundwater flow modeling to those users who cannot afford the commercially available processors and/or to those who wish to develop their models within a GIS.

Morphometric analysis in geographic information systems: applications of free software GRASS and R

Development and interpretation of morphometric maps are important tools in studies related to neotectonics and geomorphology; Geographic Information Systems (GIS) allows speed and precision to this process, but applied methodology will vary according to available tools and degree of knowledge of each researcher about involved software. A methodology to integrate GIS and statistics in morphometric analysis is presented for the most usual morphometric parameters—hypsometry, slope, aspect, swath profiles, lineaments and drainage density, surface roughness, isobase and hydraulic gradient. The GIS used was the Geographic Resources Analysis Support System (GRASS-GIS), an open-source project that offers an integrated environment for raster and vector analysis, image processing and maps/graphics creation. Statistical analysis of parameters can be carried out on R, a system for statistical computation and graphics, through an interface with GRASS that allows raster maps and points files to be treated as variables for analysis. The basic element for deriving morphometric maps is the digital elevation model (DEM). It can be interpolated from scattered points or contours, either in raster or vector format; it is also possible to use DEMs from NASA's Shuttle Radar Topographic Mission, with 30 m of ground resolution for the USA and 90 m for other countries. Proposed methodology can be adapted according to necessities and available tools. The use of free and open-source tools guarantees access to everyone, and its increasing popularization opens new development perspectives in this research field.