RMSI Pvt. Ltd.
RMSI Pvt. Ltd.
News Article | May 3, 2017
Geospatial can be defined as the geographical data having locational information described in terms of coordinates, address, city or ZIP code. It is gathered through satellite, (GPS), geo tagging and remote sensing. GIS is used for mapping and analyzing geospatial data whereas remote sensing tool is used to acquire geographical data through sensors such as radars, radiometers and lidar. Hence, geospatial analytics products combine geographic data and business data to achieve information to help business decisions such as logistics and marketing. The key drivers contributing to the growth of the market are the demand for the integration and convergence of geospatial information with mainstream technologies, commoditization of geospatial data for various industries. Also, the rising demand for geospatial analytics solutions with artificial intelligence capabilities across various industries and the rising adoption of geospatial solutions for safety and security. • DigitalGlobe, Inc. (U.S.), • Hexagon AB (Sweden), • Bentley Systems, Inc. (U.S.), • General Electric Co. (U.S.) • ESRI (U.S.), , • Trimble Navigation LTD. (U.S.), • MacDonald, Dettwiler & Associates, Ltd. (Canada), • Fugro N.V. (Netherlands), • RMSI (India), • Harris Corporation (U.S. ) The term geo can be defined as earth and spatial can be described as anything that takes up space. It is basically applied to anything that takes up space. The demand for the integration & convergence of geospatial information with mainstream technologies, the commoditization of geospatial data across various verticals, increasing demand for geospatial analytics solutions with artificial intelligence capabilities and the rising adoption of geospatial solutions for safety and security are factors contributing to the growth of the overall market. The analysis would help organizations for promotional of programs and target new customers. Reducing operational and logistic costs by organizations acts as opportunities for the growth of the market. Geospatial analytics can help government to detect crime locations, issue alerts in situation of natural calamities and designing disaster recovery mechanisms. The growing smart cities and increasing demand for technological advancements in developing countries is expected to boost the market for geospatial analytics. Also, legal issues related to storage of personal information and initial setups of geospatial analytics products which require high investment hinder the growth of the market. Also, innovations in technologies would increase the opportunities in geospatial analytics market. Factors such as privacy issues related to storage of geospatial data, legal issues related to storage of information and initial setup cost hamper the growth of the market. Taste the market data and market information presented through more than 30 market data tables and figures spread over 100 numbers of pages of the project report. Avail the in-depth table of content TOC & market synopsis on “Geospatial Analytics Market Research Report -Forecast to 2022”. The global geospatial market is expected to grow significantly. The market is highly application basis. Surveying segment of geospatial market globally drives the market. The market is expected to have higher growth rate as compared to the previous years. The increasing growth rate in the Asia-Pacific region can be attributed to the growing demand for adoption and usage of geospatial analytics across industries such as automotive. Also, smart city developments driving the geospatial analytics market. Regional Analysis: Regionally, Asia-Pacific region accounted for the largest market share, majorly due to increasing g adoption and usage of such analytics across various verticals. Also, infrastructure and smart city developments are factors driving the growth of the market in this region. Browse Related Report Software engineering Market, By Type (CAD, CAM, CAE, AEC, EDA), by Application (Automation design, Plant Design, Product Design, 3D Modelling, Others), by End-User (Aerospace & Defence, Automotive, Banking, Telecommunication, Oil & Gas, Healthcare, Others), - Forecast 2016-2022 About Market Research Future: At Market Research Future (MRFR), we enable our customers to unravel the complexity of various industries through our Cooked Research Report (CRR), Half-Cooked Research Reports (HCRR), Raw Research Reports (3R), Continuous-Feed Research (CFR), and Market Research & Consulting Services. MRFR team have supreme objective to provide the optimum quality market research and intelligence services to our clients. Our market research studies by products, services, technologies, applications, end users, and market players for global, regional, and country level market segments, enable our clients to see more, know more, and do more, which help to answer all their most important questions. For more information, please visit https://www.marketresearchfuture.com/reports/geospatial-market-2441
Kumar A.,RMSI Pvt. Ltd.
Mausam | Year: 2011
The monsoon depression of September 2008, which crossed Orissa coast near Chandbali on 16 th had contributed heavy rainfall over Orissa, Chhattisgarh and northern India along the track of the system. The sensitivity of three cumulus parameterization schemes viz., Kain-Fritch (KF) scheme, Grell-Devenyi (GD) scheme and Betts-Miller-Janjic (BMJ) Scheme are tested using high resolution advanced version (3.0) Weather Research Forecasting (WRF) model in forecasting the monsoon depression. The results of the present study shows that the genesis of the system was almost well captured in the model as indicated in 48hr forecast with all three convective parameterization schemes. It is seen that the track of monsoon depression is quite sensitive to the cumulus parameterization schemes used in the model and is found that the track forecast using three different cumulus schemes are improved when the model was started from the initial condition of a depression stage compared to that when it started from the initial condition of low pressure area. It is also seen that when the system was over land all the schemes performed reasonably well with KF and GD schemes closely followed the observed track compared to that of BMJ track. The performance of KF and GD schemes are almost similar till 72 hrs with lowest landfall error in KF scheme compared to other two schemes, whereas the BMJ scheme gives lowest mean forecast error upto 48 hr and largest mean forecast error at 72 hr. The overall rainfall forecast associated with the monsoon depression is also well captured in WRF model with KF scheme compared to that of GD scheme and BMJ scheme with observed heavy rainfall over Orissa, Chhattisgarh and western Himalayas is well captured in the model with KF scheme compared to that with GD scheme and BMJ scheme.
Mohindra R.,RMSI Pvt. Ltd. |
Nair A.K.S.,RMSI Pvt. Ltd. |
Gupta S.,RMSI Pvt. Ltd. |
Sur U.,RMSI Pvt. Ltd. |
Sokolov V.,Karlsruhe Institute of Technology
International Journal of Geophysics | Year: 2012
A stochastic-event probabilistic seismic hazard model, which can be used further for estimates of seismic loss and seismic risk analysis, has been developed for the territory of Yemen. An updated composite earthquake catalogue has been compiled using the databases from two basic sources and several research publications. The spatial distribution of earthquakes from the catalogue was used to define and characterize the regional earthquake source zones for Yemen. To capture all possible scenarios in the seismic hazard model, a stochastic event set has been created consisting of 15,986 events generated from 1,583 fault segments in the delineated seismic source zones. Distribution of horizontal peak ground acceleration (PGA) was calculated for all stochastic events considering epistemic uncertainty in ground-motion modeling using three suitable ground motion-prediction relationships, which were applied with equal weight. The probabilistic seismic hazard maps were created showing PGA and MSK seismic intensity at 10% and 50% probability of exceedance in 50 years, considering local soil site conditions. The resulting PGA for 10% probability of exceedance in 50 years (return period 475 years) ranges from 0.2 g to 0.3 g in western Yemen and generally is less than 0.05 g across central and eastern Yemen. The largest contributors to Yemens seismic hazard are the events from the West Arabian Shield seismic zone. © 2012 Rakesh Mohindra et al.
Brindha K.,Anna University |
Elango L.,Anna University |
Rajesh V.G.,RMSI Pvt. Ltd.
Indian Journal of Environmental Protection | Year: 2010
Effluent resulting due to various ^processes from tanning industries may lead to groundwater pollution when they are disposed off without proper treatment. This study was carried out with the objective of studying the impact of effluent let out by these industries on groundwater quality in Chromepet area of Chennai, Tamil Nadu which is the home town of a number of small and large scale leather tanning industries. 36 samples were collected during March 2008 and the groundwater samples were analysed for the concentration of chromium and copper using atomic absorption spectrophotometer. About 86% of the groundwater samples possessed concentration of chromium above the permissible limit while 28% of the groundwater samples had copper concentration above the limits. Thus this study indicates the impact of effluent from tanning industries on the deterioration of groundwater quality in this area. © 2010 - Kalpana Corporation.
Malviya S.,TERI University |
Priyanka N.,TERI University |
Irfan-Ullah M.,RMSI Pvt Ltd |
Davande S.,RMSI Pvt Ltd |
Joshi P.K.,TERI University
International Journal of Geoinformatics | Year: 2013
The impacts of climate change are global concerns, but m India, where large parts of the population are chronically vulnerable to natural hazards, climate change impacts are particularly critical. Agriculture (largest sector ofIndian economy), accounts for some 17.2% of the GDP and 52% of labor force, is already under pressure and impacts of climate variability cause an additional risk Livelihood diversification is one means of adapting to climate change. It is being realized through development of a robust low cost input technology that gives maximum returns within a short gestation period. In the present study, current and future distribution model of Simarouba glauca is developed The results indicate that many Indian states and districts are suitable for its introduction/cultivation and hold a great potential under climate change projections. The species cultivation is an example of a low input cost technology that would give assured returns and focus on rural livelihood improvement. © Geoinformatics International.