Development of GIS based Disease Outbreak Detection System utilizing open source technologies

Abstract

In the recent times, design and implementation of desktop based disease outbreak detection system using open source technologies has always been a focused and challenging task. Health data has both the spatial and temporal variability in nature which is required to be mapped to have the clusters of the infected cases to understand the spreading of disease in an area. This paper outlines the development of desktop based disease outbreak detection system, a GIS tool by the use of open source applications like Python, Java and PostGIS along with interface design and database development whereas the WMS services of Bhuvan, Google Map and Geoserver has been used for the visualization purpose. Density base clustering approach has been used to map the point data and cluster formation. The data sets used for the study are standard health data generated by different government organization. The developed GUI will lead to detect clusters in the particular areas where the number of cases is much higher and results can be used to do the prospective and retrospective analysis to have the future scenarios generation to make the early decisions.

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DEVELOPMENT OF HYDROLOGICAL MODELING SYSTEM FOR FLOOD PEAK ESTIMATION USING OPEN SOURCE GEOSPATIAL TOOLS

Abstract

Freshwater-related risks of climate change including that of extreme weather events such as floods, will increase significantly with increasing greenhouse gas concentrations (IPCC 2014). Hydrological modelling is an effective method for quantifying the peak flood and area inundated by floods. The present study is an attempt to create an open source software system to estimate basic hydrological components from freely available topographical data, which can be used for estimating flood peak from a given rainfall event. This tool consists of two parts: Terrain processing part and Hydrological modelling part. Terrain processing part includes basic hydro processing functions such as fill sinks, flow direction, flow accumulation, stream definition and watershed delineation from given Digital Elevation Model (DEM). All the processes are automatic, only the raw DEM raster file and outlet shape file is needed as input. Output of the terrain processing is used as input of the hydrological processing section. The created GIS files can read in any open source freely available software such as QGIS or ILWIS. Hydrological modeling part consists of two parts: transformation method and flood routing. Synder’s unit hydrograph method is implemented as rainfall-runoff transformation method. Muskingum’s method is used as flood routing method. This tool is able to find the flood peak discharge for individual sub-watershed of a basin. The tool has been developed in Python scripting language, resulting this is machine independent and have more scope for further development by including more methods for runoff estimation and flow routing.

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Climate Grid Point Retrieval by Integrating R With QGIS

Abstract

Climate data is the very essential in the climate change, trend pattern and water resources studies. Most of the studies related with climate data are dealing with small areas but the climate data available are mostly global level or regional level. So retrieval of climate data for the area of interest is the cumbersome process. In order to overcome the difficulty developed a tool for retrieval of climate grid points using open source software R. A Graphical User Interface (GUI) is created using R, which takes the climate data in NetCDF format and returns the area of interest in the form of text file. This R code is later integrated with the QGIS. The R script created also able to project the obtained grid points in the DEM or shape file of the area of interest. Model tool has been verified for different climate model data. Keywords: Climate model data, Grid points retrieval, R language, QGIS.

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Hydrological modeling in hilly watershed with Free and Open Source Software (FOSS)

Abstract

The adversely changing climate, Land Use Land Cover (LULC) and its impact has become global issue in hydrology of mountainous region. A part of dun valley area of Dehradun, i.e., Asan river watershed has seen significant changes in urban landscape in last 15 years. To assess the effect of these changes on hydrological components, an integrated hydrological modeling approach will be needed. Soil and Water Assessment Tool (SWAT) hydrological model has wide spectrum of capabilities to deal with various hydrological, water and land management scenarios. Until 2014, SWAT model required commercial software ArcGIS as GIS interface for running its hydro processing and core water balance modules, whereas, most of the organizations which are involved in hydrology based projects have limited budget. To encourage the expertise and capability of user, open source softwares and tools designed and have similar capability without expenditure. In the present study, QSWAT an open source tool plugin which work with QGIS software, has been used for the estimation of snow melt, surface runoff and sediment estimation in the Asan watershed, Dehradun District, Uttarakhand. QGIS-QSWAT has been used for creation of watershed parameters from ASTER GDEM (30m), and different Climatic layers, Soil and LULC are generated as the model input. Results shows, the magnitude of flood peaks will be visualized as a simulation and other parameters will be seen as thematic layers. Continuous daily simulations of hydrological components of Asan watershed was successfully done from 1999 to 2014 using NCEP and ground based climatic data. Calibration and validation was done for years 1999-2004 and 2005 to 2010 respectively. This preliminary analysis will be taken as a reference for the engineers and planners. Key Words: Hilly watershed, open source hydrological model, SWAT, FOSS, QSWAT

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Future Trends and Technologies: Big Data Analytics pro Web Processing Service

Abstract

Recent evolution is focused on interaction with large amount of datasets and challenges to design analysis technique. To meet these challenges, Big Data Analytics concept emerged which require advance technologies to process large volume of data efficiently by using distributed and parallel file systems and in terms of GIS it is an incipient technology which allows analysis of unstructured large volume datasets to solve complex spatial decision problems. Big Data Analytics enunciated through powerful and distributed framework offered by Apache Hadoop MapReduce. Hadoop and its ecosystem of Big Data technologies offer distributed storage, large scalable data processing platform which facilitate enterprises to build emerging types of data driven applications that are at the heart of their digital strategy. In former study, Indian Biodiversity data repository generates in Geo-RDBMS environment using PostgreSQL and POSTGIS during Biodiversity characterization study. The raster data is published as WMS and WFS standard which allows online query and visualization. The developed system is taking input from users as Shape file upload, WKT as AOI to perform raster based operation using python, GDAL/OGR, JavaScript and execute raster data analysis over the web using PHP and PostGIS. Indian Biodiversity contains large volume of geo-spatial data which can be processed through Big Data Analytics very efficiently. By using spatial data (satellite based primary information, secondary geospatially derived or modelled information and geospatially referenced field sample plots) from Biodiversity Information System (http://bis.iirs.gov.in), Climatic data, Plant species dataset, Biogeography and other datasets will also give valuable input towards climate change study. This study will characterize how to process enormous amount of data into web environment which solicit WPS (Web processing service). WPS specification endues interface rules that standardize inputs and outputs for geospatial processing services on web. Geospatial Data Processing can take advantage of the OGC WPS as web interface to allow for the dynamic deployment of user processes. However, intensive computation is required for processing of large amount of geospatial problem and it can be accomplished through Big Data analytics. High performance computing cluster will be used to configure Apache Hadoop framework for large scale processing to perform intensive computation for spatial data modeling and data required by WPS will available at the server. Considering effectively, the climate change in Indian Biodiversity requires further research to overcome this dilapidation.

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Creation of a Web GIS of Rural drinking water sources in Punjab using FOSS tools

Abstract

Use of free and open source GIS (Geographic Information Systems) tools (FOSS-GIS) to create Web GIS applications is increasing day by day. Technical features provided by FOSS tools are comparable to their proprietary peers. There is a variety of open source web GIS software freely available on the internet and they differ on parameters like ease of use, technology, complexity, support etc. In this research, open source software combination of MapServer and pmapper has been used to create a web GIS which provides information about the rural drinking water supply sources of Dept. of Water Supply & Sanitation (DWSS) in Punjab. Rural drinking water source (RDWS) information contains the details of the type of water source, date of commissioning, Scheme, Tubewell size, depth, coverage information, number of villages covered, strainer material and length, motor details, discharge, lithology details and location etc. Base layers like road, rail, canal, drainage, settlements, village, block and district boundaries add value to the database of RDWS in the state. This application has various tools like Pan, Zoom, Search, Identify and other common tools with the help of which a user can browse and search the data. The application also provides a comprehensive view about the spatial and non spatial data and can act as a decision support system for the DWSS officials, decision makers and planners.

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An open source application to compute urban morphometric parameters to understand urban winds

Abstract

Urban roughness is of major importance for understanding the wind dynamics and microclimate in an urban area. Morphometric methods are ideally suited for estimation of urban roughness in an urban environment due to increasing availability of 3D urban database, remote sensing and GIS (Geographical Information Systems). Frontal area is one of the key morphometric parameters required to compute roughness length (z0) and zero plane displacement height (zd). However the estimation of these morphometric parameters in a large area is computation intensive and complex. The advent of GIS and various open source computer technologies have eased the complexity of computation of these parameters. The present paper illustrates development of such an open source application, Urban Morphology Extractor (UME) and its deployment on a sample data. UME is a standalone application built using open source programming language Python and requires open source shapefile (.shp) data format for inputs and outputs. ME is a comprehensive application and is one of its kind, its capabilities include computation of frontal area using different criteria’s, computation of height-to-width ratio and generate shapefiles for eight different wind directions at user specified windline resolution. UME was tested over a sample dataset and overall accuracy of 92.5% and 90.3% was calculated for two wind direction for which computations were manually done.

A Web GIS template for Societal-GIS: namma-mysuru.org

Abstract

Digital globes like OpenStreetMap (OSM), Sahana Eden, and WorldMap are offering user friendly GIS features for public utility. Geospatial data located on a Map helps decision makers to be able to make more meaningful decisions and mapping clients can combine data from both existing geospatial database and a range of external sources to provide a rich environment for display and analysis. Quantum GIS is a shining example for this. Individual cases of Geospatial data requirement of Indian cities may need further elaboration than existing attribute schema of OSMs Open Geospatial data. This paper deals with a case for the City of Mysuru, with a well developed vector data on OSM; thanks to a dedicated group of contributors hailing from the University of Mysore. A scheme of action from updating the OSM data using OsmAnd an Android based mobile application, to downloading OSM vectors through JavaOpenStreetMaps, adding as a PostGIS database after modifying attribution and serving the data through Geoserver in an Openlayers environment resulting in namma-mysuru.org is explaied in this paper. The resultant website namma-mysuru.org can showcase themes of societal use like, Sewage, Garbage disposal, water distribution, Slums, Elementary Schools other than, roads, traffic, bus-stops, bazars, hotels etc. For desktop GIS the website also provides Web Feature Service (WFS) to view/download the themes and analyse with other existing themes. Keywords : Open Street Maps, Open Web GIS, Open Geospatial data.

HYDROMETEOROLOGICAL DATA ASSIMILATION IN WEATHER FORECASTING MODEL USING OPEN SOURCE TOOLS

Abstract

In this paper, we perform data assimilation using radiance data from different sensors mhs, amsu-a for the improved weather prediction in for the study area covering Uttarakhand and Himachal Pradesh at different resolutions of 27km, 9km and 3km. Two fairly successful cases of explicit prediction of precipitation are presented. Two heavy rain events each in the year 2013, 2014 and 2015 selected with different rainfall distribution in space and time are utilized to examine the improvement for rainfall forecast after data assimilation. The simulation experiments and analysis have been carried out using open source softwares and tools WRF 3.6.1 3DVAR, Grid Analysis and Display System (GrADS) and MET. The Grid Analysis and Display System (GrADS) is a programmable interface that is used for easy access, manipulation, and visualization of various data. MET is designed to be a highly-configurable, state-of-the-art suite of verification tools. There is a high impact of initial conditions on the modeling accuracy of numerical weather prediction (NWP). Here we investigate the potential of data assimilation in improving the NWP rainfall forecasts in the area. The general behavior and evolution of the reanalyzed precipitation agree very well with the observations. Observations from satellite radiance were assimilated into the model at different intervals. The resulting forecast, covering a period of several days, accurately reproduced the intensification and evolution of the events. The simulated rainfall has also been compared with that derived from the Tropical Rainfall Measuring Mission (TRMM) satellite NCEP FNL, CPC and in situ observations. The encouraging results from the study can be the basis for further investigation of the direct assimilation of radiance data in 3DVAR system and Ensemble method of Kalman filter. It is remarkable that, the satellite radiances have greater effect on rainfall forecasts than initial dynamic downscaling.

Development of a Land Change Modeling Platform using Open Source Tools and Technologies

Abstract

Availability of past, present and future status of land-use/ land-cover (LULC) information in a spatially distributed manner is vital for land-use planning, climate studies and understanding environmental implications. Simulating future scenarios of LULC requires understanding the linkage between LULC change processes and drivers (biophysical and socio-economic) of change. LULC change simulation models primarily fall in two groups: (1) empirical-statistical models, and (2) process-based models. This paper presents development of a Land Change Modeling Platform (LCMP) using open source tools and technologies following the statistical approach. The platform has been developed with embedded principle of integrated iterative modeling process by loosely coupling select, model, and analyse cycle. The software provides provision of suitability map generation based the logistics, linear regression or artificial neural network (ANN) technique. The established relationship between drivers and LULC class can then be analysed based on the statistical significance which helps the modeler to select the drivers for each LULC class to include in the modeling process. There is also a provision to include the spatial context and policy related features. The policy related features are addressed through demand variation by altering Markovian matrix and by defining LULC class inertia. It also has map visualisation module along with accuracy assessment. The developed modeling platform has been used to generate the future LULC scenarios in different river basins of India. Keywords: Land-use/ land-cover, LULC change, LULC modeling, Land change modeling platform, Open source tools Submitted to: FOSS4G-India 2015 National Conference on Open Source Geospatial Tools in Climate Change Research and Natural Resource Management, June 8-10, 2015, Dehradun, India.