Indian National Remote Sensing Centre
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.

Time filter
Source Type

Chacko N.,Indian National Remote Sensing Centre
Deep-Sea Research Part I: Oceanographic Research Papers | Year: 2016

Though previous studies have documented substantial increases in chlorophyll concentrations as a result of cyclones, most of them were based on satellite observations dealing with surface chlorophyll blooms. This study documents the subsurface biological response and the subsequent chlorophyll bloom observed in response to the tropical cyclone Hudhud as evident from a Bio-Argo float located at the central Bay of Bengal. Results show high chlorophyll concentrations of up to 4.5mgm-3 which is anomalous in the normally warm, stratified, and oligotrophic Bay of Bengal. The chlorophyll bloom is attributed to the combined effect of subsurface chlorophyll entrainment and nutrient injection. The presence of a pre-existing cyclonic eddy and the decreased translation speed of the cyclone over this region could have played a role in inducing the biological response. This is the first ever report to document the evolution of a subsurface chlorophyll bloom in response to cyclone forcing using Bio-Argo observations. © 2017 Elsevier Ltd.

Sudhakar Reddy C.,Indian National Remote Sensing Centre | Saranya K.R.L.,Indian National Remote Sensing Centre
Global and Planetary Change | Year: 2017

This study has generated a national level spatial database of land cover and changes in forest cover of Afghanistan for the 1975–1990, 1990–2005 and 2005–2014 periods. Using these results we have analysed the annual deforestation rates, spatial changes in forests, forest types and fragmentation classes over a period of 1975 to 2014 in Afghanistan. The land cover map of 2014 provides distribution of forest (dry evergreen, moist temperate, dry temperate, pine, sub alpine) and non-forest (grassland, scrub, agriculture, wetlands, barren land, snow and settlements) in Afghanistan. The largest land cover, barren land, contributes to 56% of geographical area of country. Forest is distributed mostly in eastern Afghanistan and constitutes an area of 1.02% of geographical area in 2014. The annual deforestation rate in Afghanistan's forests for the period from 1975 to 1990 estimated as 0.06% which was declined significantly from 2005 to 2014. The predominant forest type in Afghanistan is moist temperate which shows loss of 80 km2 of area during the last four decades of the study period. At national level, the percentage of large core forest area was calculated as 52.20% in 2014. © 2017 Elsevier B.V.

Patra A.K.,National Atmospheric Research Laboratory | Chaitanya P.P.,National Atmospheric Research Laboratory | Dashora N.,National Atmospheric Research Laboratory | Sivakandan M.,National Atmospheric Research Laboratory | Taori A.,Indian National Remote Sensing Centre
Journal of Geophysical Research: Space Physics | Year: 2016

In this paper we study equatorial electrodynamics and plasma irregularities linked with the 17 March 2015 severe magnetic storm in the Indian sector by using common volume observations made by the Gadanki Ionospheric Radar Interferometer, airglow imager, Digisonde, and GPS receiver established at Gadanki (13.5°N, 79.2°E). Observations show that with the initiation of the storm at ~06:00 UT on 17 March, which happened to be midday in the Indian sector, the low-latitude ionosphere responded in tune with the storm-induced electric field and by the sunset time the base of the F layer ascended to an altitude of 470 km with a peak upward velocity of 50 m s−1 eventually manifesting equatorial plasma bubble and irregularities causing strong GPS scintillation. The most important finding found in this study is the confinement of plasma bubble and irregularities in a narrow longitude zone of 69°E–98°E. Results also show reversal of zonal drift of the irregularities from ~120 m s−1 eastward drift to ~120 m s−1 westward drift in a time span of ~30 min. Both observations are shown to be linked with very special electrodynamical conditions induced by the magnetic storm-related electric field in the dusk sector. Intriguing details of the longitudinally localized electrodynamics and plasma irregularities are discussed in terms of prompt penetration and disturbed dynamo electric field effects. ©2016. American Geophysical Union. All Rights Reserved.

Nayak R.K.,Indian National Remote Sensing Centre | Patel N.R.,Indian Institute of Remote Sensing | Dadhwal V.K.,Indian National Remote Sensing Centre
International Journal of Climatology | Year: 2013

Using satellite observations of Normalized Difference Vegetation Index together with climate data from other sources in a terrestrial biosphere model, inter-annual variability of Net Primary Productivity (NPP) over India during 1981-2006 was studied. It is revealed that the variability is large over mixed shrub and grassland (MGL), moderate over cropland and small over the forest regions. Inter-annual variability of NPP exhibits strong positive coherence with the variability of precipitation, and weak coherence with the variability of temperature and solar radiation. Estimated linear growth rate of annual NPP is 0.005 Pg C Yr-2 which is equivalent to 8.5% over the country during past 25 years. This increase is primarily due to the enhancement of productivity over agricultural lands in the country. NPP has increased over most parts of the country during the early 15-year period (1981-1995) resulting in a 10% growth rate of national NPP budget. On the other hand, the NPP growth rate has been reduced to 2.5% during later 15 years period (1991-2005) owing to large decline of NPP over the Indo-Gangetic plains. Climate had a strong control on NPP growth rate during both the periods. © 2012 Royal Meteorological Society.

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.

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.

Martha T.R.,Indian National Remote Sensing Centre | Vinod Kumar K.,Indian National Remote Sensing Centre
Landslides | Year: 2013

The Okhimath area in the Uttarakhand state of India witnessed a large-scale occurrence of landslides on 14 September 2012 due to intense rainfall. As per news reports, this event resulted in the death of 51 people and a significant loss of property. In this study, the damage assessment results of the Okhimath landslides derived from the analysis of very high resolution (VHR) images received from Cartosat-2, Resourcesat-2, Kompsat-2 and GeoEye-1 satellites are presented. These datasets were acquired through a coordinated effort of the Indian Space Research Organisation and International Charter Space and Major Disasters. A total of 126 buildings, 34.5 ha of agricultural land and 7.78 km of road were identified as damaged through the VHR satellite data analysis. Using a semi-automatic landslide detection technique, 473 landslides covering a 2.25-km2 area were also identified. Villages such as Mangali, Chunni, Brahman Kholi, Semla, Paldwadi, Saari and Giriyagaon are found to be most affected due to this event. The damage is mainly attributed to rock slides which originated in the escarpment zone which later converted to debris flows by scouring the material along the run-out zone. © 2013 Springer-Verlag Berlin Heidelberg.

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.

Jawak S.D.,Indian National Remote Sensing Centre | Luis A.J.,Indian National Remote Sensing Centre
Photogrammetric Engineering and Remote Sensing | Year: 2014

We devised a semiautomatic approach for extracting lake features based on a customized set of normalized difference water index (NDWI) information which was obtained by incorporating high resolution, 8-band WorldView-2 data. An extensive accuracy assessment was carried out for three semiautomatic feature extraction approaches for extracting 36 lake features on Larsemann Hills, Antarctica. The method was tested on five existing PAN-sharpening algorithms, which suggest that the customized NDWI approach renders intermediate performance (root mean square error varies from ~227 to ~235 m2) and highest stability when compared with existing feature extraction techniques. In general, the customized NDWI rendered a least misclassification (≈11 percent), followed by target detection (≈16 percent) and spectral processing (≈17 percent) methods for extraction of 36 lakes. We also found that customized NDWI caused consistently least misclassification (≈21 percent) than the target detection (≈23 percent) and spectral processing (≈30 percent) methods for extraction of partially snow or ice-covered 11 lakes. Our results indicate that the use of the customized NDWI approach and appropriate PAN-sharpening algorithm can greatly improve the semiautomatic extraction of lake features in cryospheric environment. © 2014 American Society for Photogrammetry and Remote Sensing.

Loading Indian National Remote Sensing Centre collaborators
Loading Indian National Remote Sensing Centre collaborators