Time Series Geodata visualization in Web 2.0

Abstract

Many things that happen are having space and time as major dimensions. Visual representation of these datasets and information brings out unique opportunity to identify meaningful trends like Magnitude, Shape, Velocity, Direction etc. In this paper, we present various methodologies for Geodata time-series visualization using Opensource Geospatial solutions. Advantage of Web 2.0 for ‘Rich Internet Applications, Web-oriented Architecture and Social web’ by having dynamic data rendering, details on demand, Navigation are harnessed to disseminate the data and identity the trends. We explain Open Geospatial Consortium Web Standards for implementing this process.WMS with user defined array of time delay, WMS animator with format supporting multi-frame images in style layer descriptor(SLD), defining time in service metadata of WMS, are implemented in various Bhuvan applications like Events, Forest cover loss, Urban Sprawl etc. Depending on the context, time value is parameterized as a single value, a list of values, or an interval. WMS servers – Mapserver and Geoserver are configured to provide support temporal requests. Client side OpenLayers is used to make structured http requests to server with Slider, Swipe, Animate controls for effective Time Series Visualization.

Geographical Weighted Regression model for improved bathymetric estimation from multispectral imageries

Abstract

There is often a need for making a high-resolution or a complete bathymetric map based on sparse point measurements of water depth. The common practice of previous studies has been to calibrate a single global depth regression model for an entire image. The performance of conventional global models is limited when the bottom type and water quality vary spatially within the scene. For a more accurate and robust water-depth mapping, this study proposes a regression model for a geographical region or local area rather than using a global regression model. The global regression model and Geographical Weighted Regression (GWR) model are applied to Landsat 8 and RapidEye satellite images. The entire data analysis workflow was carried out using GRASS GIS Version 7.0.0. Comparison of results indicates that the GWR model improves the depth estimation significantly, irrespective of the spatial resolution of the data processed. GWR is also seen to be effective in addressing the problem introduced by heterogeneity of the bottom type and provide better bathymetric estimates in near coastal waters. The study was carried out at Pureto Rico, northeastern Caribbean Sea. Two different satellite data were collected in order to test the algorithm with high and moderate resolution data. RapidEye data has 12-bit radiometric resolution and 5 meter spatial resolution. Even though Landsat 8 data also has 12-bit radiometric resolution; it provides 30 m spatial resolution. In order to calibrate and evaluate the estimated depth, high accuracy LiDAR depth data (4 m resolution) provided by NOAA is used. The study was demonstrating GWR model to estimate depth, evaluate and compare the results with a global conventional regression model. The comparative study between conventional global model and GWR model shows that GWR model significantly increases the accuracy of the depth estimates and addresses spatial heterogeneity issue of the bottom type and water quality. The GWR model provide better accuracy at both Landsat 8 (R-squared=0.96 and RMSE=1.37m) and RapidEye (R-squared=0.95 and RMSE=1.63m) than global model at Landsat 8 (R-squared=0.71 and RMSE=3.71m) and RapidEye (R-squared=0.71 and RMSE=4.04m).

Geostatistical computing for spatial landscape modelling using open source technology

Abstract

Spatial landscape modelling for identification of Biological Rich (BR) areas in Indian landscape was developed by Department of Space (DOS) and Department of Biotechnology (DBT) Govt. of India under national level project on Biodiversity Characterization at landscape level using RS&GIS. The spatial landscape model developed during the study is in desktop GIS environment using proprietary software solutions. The model have many limitations such as licensing issues, version compatibility, single user access, static pre-defined parameters etc. There is no possibility to include user defined GIS layer for further enhancement of the model. To overcome these issue an attempt has been made to develop modified version of spatial landscape model using R programming as a Web Processing Service (WPS) for multi-user access. The functionalities are further enhanced to describe the geostatistical computing of landscape thematic data such as vegetation type map, digital elevation model, social, physical etc. The computing was initiated by detail description of landscape analysis parameters such as fragmentation, patchiness, porosity, juxtaposition, interspersion and proximity analysis. The R project for geostatistical computing is the key open source environment for spatial data exploratory and advanced computational statistics. The geo-statistical computing presented in this study are based on R open source software comprising the raster, sp, rgdal etc packages. The different algorithms for landscape analysis parameter have been elaborated by using R programming and its graphical user interface Rstudio. Keywords: Geostatistics, landscape analysis parameter, R programming, OGC, WPS

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Development of OGC WPS for Species Niche Modelling using environmental variables

Abstract

Species distribution prediction modeling plays a key role in Bio-diversity research. There are increasing needs for species distribution modeling ranging from basic ecological and biogeography research to routine conservation practices. Currently forest scientists and conservationists are looking for web enabled customized tools to model species loss on the fly since they have enormous field data available with them to analyze and visualize. Though they have many desktop tools developed under open source initiative for understanding species loss with regard to climate change scenarios. Nevertheless web enabled Web Processing Services are still unavailable to them to perform modeling. We propose to publish an Open Geospatial Consortium’s (OGC) Web Processing Service (WPS) that performs species distribution modeling process as a Web service and composite them into modeling systems using the scientific workflow approach. Our work demonstrates how a Species Distribution Model can be hosted as a WPS web service. As the requirements of Species Distribution Modeling deal with data, algorithms, calculation models and computing capability, we use 52 degree North Web Processing Service with R-backend (WPS4R) framework that allows to upload and expose R scripts dynamically as WPS processes with the support of high computation capabilities. We predict the distribution model of the species Hippophae Rhamnoides. L (Sea Buckthorn) in the area Lahaul and Spiti (Bounding Box: 76.3700, 31.7439, 78.6541, 33.2653) district, Himachal Pradesh using Maximum Entropy (MaxEnt) modeling technique to predict the distribution of species. We use species occurrence data collected from Global Biodiversity Informatics Facility and DOS-DBT project. The primary advantage of this approach being, scientists no longer need to use the desktop tools while predicting the species distribution model. They can, on the fly, use their data, request for predicting the species by combining with geospatial processes to produce the prediction map over the web unswervingly. Henceforth the project aims to develop an OGC WPS services for species niche modeling making this applicable to a wide range of species of significant importance for the research and industry community.

A comparative study of performance analysis of MongoDB and PostGIS-PostGreSQL databases for Line Intersection Spatial Queries

Abstract

With the increased shift towards GeoSpatial Web Services on both the Web and mobile platforms especially in the user-centric services, there is a need to improve the query response time. This paper attempt to evaluate the performance of an existing NoSQL database and SQL database with respect to LineIntersection problem across a range of databases. SQL databases face scalability and agility challenges and fail to take the advantage of the cheap memory and processing power available these days. While NoSQL databases can handle the rise in the data stored and frequency at which it is accessed and processed which are essential features needed in a multiple geospatial data where we do not need a fixed schema(geometry) and fixed data size. For this comparative study, MongoDB is the NoSQL engine while the PostGIS is the chosen SQL engine. The dataset consisted of two independent layers of horizontal lines and vertical lines with incremental lengths and their size varied from ten lines to ten thousand lines in each layer. All the data in the analysis was processed using In-memory and no secondary memory was used. Initial results suggest that MongoDB performs better by an average factor of 25x which increases exponentially as the data size increases in both indexed and non-indexed operations. Given these results NoSQL databases may be better stated for simultaneous multiple-user query systems including Web-GIS and mobile-GIS. Further studies are required to understand the full potential of NoSQL databases across various geometries and spatial query types.

The quality Assessment of OpenStreetMap

Abstract

—Just a few year ago mapping was primarily used in cars for navigation but now it enables everything from lucrative location lased services to game changing autonomous driving in era of internet of things. Revolutionary computer technology given us method of sharing and computing data contributed by users called Crowdsourcing. This method give rise to user generated geographical information system such as OpenStreetMap (OSM). The problem with OSM is because of loose coordination and no top-down quality assurance processes and little knowledge about contributors their skills and devices used for mapping. So there is big challenge to the quality of OSM. There is a challenge to the quality of OSM. This paper focuses on the quality of assessment of OSM data as compare to Ordnance Survey data, we have assessed the logical consistency of both datasets and it has been concluded as crowdsourced data has got more no features mapped as compare to Ordnance survey data and comparable quality. But with lots of logical errors, It may not suitable for navigation purposes.

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Semantic Interoperability Model for transforming IFC & CityGML Building Models

Abstract

The significance of 3D city modeling and its promising applications in the fields of city planning, cadastral mapping, urban simulations, etc. are progressively increasing. One of the major problems being faced in the applications of 3D city modeling is the lack of Interoperability between different BIM (Building Information Modeling) and GIS (Geographical Information Systems) 3D data models. IFC (Industry Foundation Classes) and CityGML (City Geographic Markup Language) are considered as the most prominent 3D data models in the BIM and GIS industry. Considerable problems arises while transforming data from one data model to another including loss of information, inappropriate transformation, loss of topology and relationships, etc. IFC and CityGML differ widely in terms of geometrical and semantic model of information. Semantic heterogeneity presents a major challenge when the focus is on interoperability, which makes it difficult to acquire a direct matching of different entities between the two domains. In this paper, we propose a semantic model of interoperability for IFC and CityGML based on reference ontologies for the transformation of building models’ information between the two data models. UML (Unified Modeling Language) has been selected for building the conceptual model of transformative mapping, owing to its widespread acknowledgement. The purpose is to describe an efficient schema mapping process encapsulating both, the IFC and CItyGML data models, thus avoiding loss of information arising from transformation of Solid based geometry (IFC) to Surface based representations (CityGML). The intention is to reconstruct the entities with maximum level of details.

Development of Web Based Rural Utility System Using Open Source Geospatial Tools

Abstract

The planning and execution of any economic policy for the nation like India has to begin with villages. Government of India has recently launched new programmes like ‘Digital India’ which is an initiative to create the digital infrastructure, digital literacy; and ‘Sansad Adarsh Gram Yojana’ which is a rural development programme broadly focusing upon the development in the villages. Rural utility management system serves as an efficient system, designed to customize and integrate web GIS system based on open source tools for effective dissemination, sharing and management of spatial information related to utilities in village and its development. The present study deals with the development of web interface for utility system for Gangadevipalli village in Telangana by using open source geospatial tools such as Openlayer and Geoserver. This Web interface will help the local people and the administration to efficiently mange and develop the existing utilities of this village.

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SedYield: AN OPEN SOURCE GEOSPATIAL TOOL FOR SOIL EROSION AND SEDIMENT YIELD ASSESSMENT AT WATERSHED SCALE

Abstract

In this cyber era of innumerable number of Geographical Information System (GIS) packages and functionalities, the problem faced by the users from different research domains are different from each other’s. They require technical skill and expertise on this advanced software. The ready to use GIS packages may not have the exact functionality required by the user or the functionality, being part of commercial package comes at very high cost. These limitations have hindered the wide spread use of GIS packages in majority of sectors and especially in the sector of natural resource management. This gap can be filled by customizing specific GIS applications as required by the end users in the open source environment. With this background, an attempt has been made in present study to develop a tool for estimating distributed soil erosion and sediment yield using an open source environment. In general the available tools for soil erosion and sediment yield estimation are not tightly coupled, this makes the task of estimation of sediment yield time consuming and less dynamic in nature. In present tool, called ‘SedYield’ hence forth, the spatially distributed soil erosion-sediment yield models are tightly coupled. The soil erosion estimation in the model has been done using Revised Universal Soil Loss Equation (RUSLE). The topographical factors of RUSLE (i.e. 2 dimensional LS factor) have been derived using DEM hydro-processing tools incorporated in the developed the tool. The ‘SedYield’ has been developed using Python and the interface has been designed using PyQt4. The sediment routing for estimation of distributed sediment yield has been done using the surface sediment transport schema suggested by Verstraeten et. al, (2007). The developed tool has been tested (calibrated and validated) using observed data of Naula Watershed, a sub-watershed of Ramganga reservoir catchment, Uttarakhand, India. The ‘SedYield’ has been designed in modular structure with four main modules viz., (1) HydPro (Processing the DEM), (2) Erosion (Estimation of gross soil erosion), (3) Calibration of Sediment Yield and (4) Validation. The ‘SedYield’ has been calibrated using four years observed data (1979-1982) of Naula Watershed. The predicted gross soil erosion obtained from the Erosion module of the ‘SedYield’ were found to be ranging from 24.9 to 38.6 t ha-1 yr-1. The calibrated Transport Capacity Coefficient (Ktc) value was found to be 0.000063 for Naula Watershed. Validation of ‘SedYield’ tool has been done using two years observed data of Naula and two years data of Chaukhutia observation stations. A model efficiency (ME) of 0.62 and a RRMSE of 0.12 were achieved through validation module. The time taken by the tool to perform one iteration of sediment yield routing for one year was less than 1 minute.

Social Forestry Information System (SOFIS): Standalone software for holistic planning of Social Forestry activities

Abstract

Social forestry aims at raising plantations for the common man so as to meet the growing demand for timber, fuel wood, fodder, etc., thereby reducing the pressure on the notified or protected forest areas. Through the social forestry scheme, the government has involved community participation, as part of a drive towards afforestation, and rehabilitating the degraded forest and common lands. One of the major lacunae in social forestry is the lack of information about the place or suitable sites where to implement the social forestry activities. Information about the length & type of roads, canals and railways along with the population pressure in and around it and the proximity to protected areas are crucial for the implementation of social forestry activities. SOFIS is application software developed for Social Forestry Department, Maharashtra State with the objective to identify the suitable sites for road/rail/canal side and block plantation. This standalone software was developed with third party open source GIS component – MAPWINGIS and Microsoft visual studio. MAPWINGIS component has wide functionalities of GIS processing and fulfils the requirement of the application. It does not require any cost for user. This software provides end to end functionality of display, navigation, rendering, archival of existing plantations, querying and site suitability analysis with the desired GIS datasets. Various thematic layers, administrative boundaries (with socio-economic data) and infrastructure layers along with Cartosat-1 satellite data pertaining to Nagpur social forestry circle were integrated to the software for modeling the desirable output. This software facilitates site specific reporting about thematic, socio-economic and infrastructure details of interested areas. Suitability analysis module will provide suitable sites for proposed linear/block plantation based on criterion specified. Ultimately planning module deliver the holistic planning of social forestry activities at a specified period for the desired administrative level.

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