Entity

Time filter

Source Type

Hyderabad, India

National Remote Sensing Centre , located at Hyderabad is one of the centres of Indian Space Research Organisation , striving to realise the Indian Space Vision, as a key player in Earth Observation Programme and Disaster Management Support programme. NRSC is responsible for acquisition, processing, supply of aerial and satellite remote sensing data and continuously exploring the practical uses of remote sensing technology for multilevel applications. It provides the necessary trained manpower through capacity building in remote sensing applications.NRSC has wealth of images from Indian and foreign remote sensing satellites in its archives and also has the capability to acquire data pertaining to any part of the globe on demand. NRSC also supports, through ANTRIX, establishment of International Ground Stations and International reseller network to receive, process and market IRS data products globally.NRSC provides end-to-end solutions for utilization of data for natural resource management, geospatial applications and information services. NRSC facilitates several remote sensing & GIS application projects for natural resources and environmental management catering to food security, water security, energy security and sustainable development. NRSC is also providing single window, disaster management support services through the Decision Support Centre. Recently NRSC has started to give its services on Land use Land cover of India under an Information portal called BHOOSAMPADA. The major objective of this portal is- Dissemination and Sharing of Geo-spatial Information Derived from IRS Data on Land use and Land cover of India. Wikipedia.


Korada D.R.H.V.,Indian National Remote Sensing Centre
Water Resources Management | Year: 2014

Uneven distribution of domestic water in space and time is a major concern in many fast growing cities due to improper planning and lack of scientific approach. This problem is much severe where the maximum domestic water requirements are met from the groundwater resources. Optimising a single groundwater pumping scheme may be an easy task using simple linear programming technique but, if the number of pumping schemes and constraints are more, solutions for identifying such groundwater schemes are more difficult and laborious using conventional methods as the constraints varies in space and time. In this paper, a new technique was developed to identify new groundwater pumping schemes to meet the present and future domestic water requirements in space and time by integrating spatial optimisation technique with the groundwater model. The approach considers the possible optimum rate of groundwater pumping, minimising the cost of water supply scheme and having minimum impact on the downstream side groundwater table using high resolution satellite data (IKONOS), Geographical Information System (GIS) tools and optimisation techniques. Dehradun, which is one of the fast growing cities in India, was considered as a study area to demonstrate the proposed new technique. Domestic water demand for next two decades (up to 2,031) was forecasted and compared with the existing supplies. Nearly 48 additional groundwater pumping schemes were identified to cater the present and future demands. Its impact on the groundwater table was also studied using groundwater modelling technique. © 2014 Springer Science+Business Media Dordrecht. Source


Vadrevu K.P.,University of Maryland University College | Ellicott E.,University of Maryland University College | Badarinath K.V.S.,Indian National Remote Sensing Centre | Vermote E.,University of Maryland University College
Environmental Pollution | Year: 2011

Agricultural residue burning is one of the major causes of greenhouse gas emissions and aerosols in the Indo-Ganges region. In this study, we characterize the fire intensity, seasonality, variability, fire radiative energy (FRE) and aerosol optical depth (AOD) variations during the agricultural residue burning season using MODIS data. Fire counts exhibited significant bi-modal activity, with peak occurrences during April-May and October-November corresponding to wheat and rice residue burning episodes. The FRE variations coincided with the amount of residues burnt. The mean AOD (2003-2008) was 0.60 with 0.87 (+1σ) and 0.32 (-1σ). The increased AOD during the winter coincided well with the fire counts during rice residue burning season. In contrast, the AOD-fire signal was weak during the summer wheat residue burning and attributed to dust and fossil fuel combustion. Our results highlight the need for 'full accounting of GHG's and aerosols', for addressing the air quality in the study area. © 2011 Elsevier Ltd. All rights reserved. Source


Dadhwal V.K.,Indian National Remote Sensing Centre
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2012

Improved national carbon assessments are important for UNFCC communications, policy studies and improving the global assessment. Use of EO for land cover dynamics, forest type, cover and phytomass carbon density, productivity and related soil carbon density and regional extrapolation of point flux measurements. A National Carbon Project (NCP) under the Indian Space Research Organisation - Geosphere Biosphere Programme (ISRO - GBP) aims at improving the understanding and quantification of net carbon balance. The NCP has been implemented with three major components - (A) vegetation carbon pools, (B) Soil carbon pools and (C) Soil and Vegetation - Atmosphere Fluxes. A total of 6500 field plot data from forests and trees outside forests have been collected. 1500 field plots have been inventoried for the soil carbon based on the remotely sensed data stratification. A nationwide network of carbon flux towers in different ecosystems for the measurement and modeling of the net carbon flux using eddy covariance techniques is being established and upscaling using satellite remote sensing data and modelling is under process. The amplitude of the diurnal variation in NEE increased with growth of wheat and reached its peak around the pre-anthesis stage. Besides, under NCP, satellite diurnal CO2 have also analyzed the data obtained from AIRS and SCIAMACHY over India and surrounding oceans and was correlated with surface fluxes. The CASA model simulations over India using NOAA AVHRR NDVI. Source


Raj K.B.G.,Indian National Remote Sensing Centre
Geomatics, Natural Hazards and Risk | Year: 2010

The climate change of the 20th century has had a pronounced effect on glacier environments of the Himalayas. The formation of moraine dammed glacial lakes and outburst floods from such lakes are a major concern in countries such as Bhutan, Tibet (China), India, Nepal and Pakistan. The hazardous lakes, however, are situated in remote areas and are very difficult to monitor through ground surveys due to the rugged terrain and extreme climatic conditions. This paper depicts the growth of a glacial lake in Reru Valley, Zanskar Himalaya based on the observations made from temporal satellite data. The change detection studies show the glacier retreating at an average rate of 12 m per year, causing lateral growth of the lake. Peak discharge from the lake is estimated using empirical formulas and varies from 1.7 m 3 s -1 to 196 m 3 s -1. © 2010 Taylor & Francis. Source


Sharma N.,Indian National Remote Sensing Centre | Ali M.M.,Indian National Remote Sensing Centre
IEEE Geoscience and Remote Sensing Letters | Year: 2013

Tropospheric temperature measurements at high temporal, spatial, and vertical resolutions are required for many meteorological studies. Radiosonde and Global Positioning System radio occultation (GPSRO) observations have very high vertical resolutions but poor in spatial and temporal coverage. Although the sounders on geostationary satellites can provide high temporal and spatial resolutions, their vertical resolution is poor. In this letter, we proposed a method to increase the vertical resolution of tropospheric temperature profiles obtained from geostationary satellite observations based on an artificial neural network (ANN) approach so that high-resolution temperature profiles are available in all four dimensions. We simulated the pressure levels of the forthcoming Indian National Satellite System (INSAT) 3-D temperature measurements from 950 to 100 hPa using 1-D variational temperature profiles of the Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC). We used these low-resolution simulated profiles as the predictors and the high-resolution GPSRO COSMIC profiles as predictants. The data during 2007 and 2008 were used to develop the model, and the data during 2009 were used for validation. The correlation coefficient of greater than 0.94 is observed throughout the pressure levels for all the three data sets. The root-mean-square differences of training, selection, and validation sets are 0.43, 0.46, and 0.51, respectively. A scatter index of less than 0.002 for all the three data sets indicates the accuracy of the estimations. © 2004-2012 IEEE. Source

Discover hidden collaborations