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Papers by Goru Srinivasa Rao

Research paper thumbnail of Characterizing Indian meteorological moisture anomaly condition using long‐term (1901–2013) gridded data: a multivariate moisture anomaly index approach

International Journal of Climatology, 2017

ABSTRACTThe long‐term (1901–2013) gridded rainfall and potential evapotranspiration (PET) data we... more ABSTRACTThe long‐term (1901–2013) gridded rainfall and potential evapotranspiration (PET) data were utilized to develop a new index, multivariate moisture anomaly index (MMAI), for characterizing the meteorological moisture anomaly condition during monsoon season over Indian region. The 6‐month timescale standardized precipitation index (SPI) and standardized evapotranspiration index (SEI) were computed using time series rainfall and PET data using gamma and log‐logistic distribution, respectively. The long‐term seasonal SPI and SEI were converted into moisture anomaly magnitude and duration information, and their trends were analysed using Sen's slope and Mann–Kendall test, respectively. The standardized precipitation evapotranspiration index (SPEI) at 6‐month timescale was also analysed to find the impact of rainfall and PET on meteorological moisture anomaly. Both the trends and probability analysis showed that SPEI was mainly representing the trends and pattern of SPI only a...

Research paper thumbnail of Defining a space-based disaster management system for floods: a case study for damage assessment due to 1998 Brahmaputra floods

Research paper thumbnail of Satellite Images for Extraction of Flood Disaster Footprints and Assessing the Disaster Impact:Brahmaputra Floods of June-July 2012, Assam, India

Current Science, Jun 25, 2013

ABSTRACT Satellite images provide information on the flood disaster footprints, which is essentia... more ABSTRACT Satellite images provide information on the flood disaster footprints, which is essential for assessing the disaster impact and taking up flood mitigation activities.The Brahmaputra floods that occurred during June–July 2012 devastated a large part of Assam. This article discusses the maximum spatial extent affected due to the flood event, villages marooned and population affected, with the aid of multi-temporal satellite images coupled with the hydrological observations and freely available gridded population data. The study shows that about 4.65 lakh ha area was submerged, 23 of the 27 districts in Assam had more than 5% of the total geographical area submerged, about 3829 villagesmarooned and 23.08 lakh people were affected.Identification of the spatial extent of areas most vulnerable to flooding, captured from the satellite images acquired during the peak flood period will be helpful for prioritizing appropriate flood control measures in the flood-affected regions.

Research paper thumbnail of Different Statistical Methods for the Discrimination of Tropical Mangrove Species Using In-Situ Hyperspectral Data

Journal of Hyperspectral Remote Sensing, 2019

The study highlights the hyperspectral characteristics of canopies of 14 tropical mangrove specie... more The study highlights the hyperspectral characteristics of canopies of 14 tropical mangrove species, belonging to nine families found in the tidal forests of the Indian Sundarbans. Hyperspectral observations were recorded using a field spectroradiometer, pre-processed and subjected to derivative analysis and continuum removal. Mann-Whitney U tests were applied on the spectral data in four spectral forms: (i) Reflectance Spectra (ii) First Derivative, (iii) Second Derivative and (iv) Continuum Removal Reflectance Spectra. Factor analysis was applied in each of the spectral forms for feature reduction and identification of the important wavelengths for species discrimination. Stepwise discriminant analysis was used on the feature reduced reflectance spectra to obtain optimal bands for computation of Jeffries–Matusita distance. The Mann-Whitney U test could be satisfactorily used for determining the significant (separable) bands for discriminating the species. In general, the red region...

Research paper thumbnail of Quantification of heat wave occurrences over the Indian region using long-term (1979–2017) daily gridded (0.5° × 0.5°) temperature data—a combined heat wave index approach

Theoretical and Applied Climatology, 2020

In the changing climate scenario, the changing heat wave frequency and magnitude have a direct im... more In the changing climate scenario, the changing heat wave frequency and magnitude have a direct impact on the agriculture, society, economic, and public health. Hence, development of easy and effective tools is essential for quantifying the heat wave incidences for better planning and management towards reducing the impacts of heat waves. In the present study, Climate Prediction Centre (CPC) global daily maximum temperature data along with the long-term normal data for the period 1979–2017 were used for quantification of heat wave conditions. Spatial and temporal sub-setting was carried out to restrict our study within the Indian region and March–July period, respectively. Based on heat wave criteria prescribed by the India Meteorological Department, different heat wave parameters, viz. frequency, magnitude, and extent, were estimated. A new approach, i.e. combined heat-wave index (CHI), was proposed to quantify the impact of heat wave in a profound manner. The efficacy of the overall method of assessing the impact of heat wave had increased by using this new approach. It was found that Rajasthan, Punjab Haryana, and Madhya Pradesh experienced high frequency as well as magnitude of heat wave, while it was lower in north-east, peninsular, and parts of northern India during our study period. The trend analysis for the heat wave parameters along with CHI was carried out over the Indian region during the last 39 years. The increasing trends were found over Rajasthan, Haryana, Punjab, East Madhya Pradesh, and Orissa, while places like Uttar Pradesh, Bihar, Chhattisgarh, Telangana, and Andhra Pradesh showed decreasing trend over the last 39 years. Peninsular and north-east India showed almost no trend regarding heat wave. Further, the month with the maximum contribution towards the seasonal heat wave and its deviation was also estimated. It was observed that the month of May was contributing most over parts of north-western and central India, while it was June in Punjab, Haryana, and western Rajasthan. Hence, the present methodology may be adopted for better planning and management of heat waves.

Research paper thumbnail of Sensitivity of various topographic data in flood management: Implications on inundation mapping over large data-scarce regions

Journal of Hydrology, 2020

Topographic data in the form of digital elevation models (DEMs) play a significant role in flood ... more Topographic data in the form of digital elevation models (DEMs) play a significant role in flood management. Despite the increasing availability of DEMs for large regions, there is a need to evaluate their performance at the inundation/flood level, while considering the overall complexity of flood models. The present study identifies, for the first time, the uncertainties generated in both river channel and overland flooding while considering a set of nine variants from various sources (LiDAR, Cartosat, SRTM, and ASTER) and grid resolutions (resampled versions) in the presence of discharge, rainfall, and tide boundary conditions for a severely flood-prone catchment in the Mahanadi River Basin, India. Extensive geostatistical analyses reveal the existence of significant biases with global DEMs i.e., SRTM and ASTER, whereas interestingly the LiDAR and Carto DEMs exhibit a high degree of isotropy. The global DEMs fail to capture several inundated spots; thus plummeting the flood inundation extents to a sufficient degree of unacceptability. Prominently, the inability in identifying high and very high flood depths (> 1.5 m) over the coastal stretches results in large uncertainties in the majority of the grids. Our analysis reveals the existence of significant noise in global DEMs, which nullifies the hydrodynamic interaction during the coupling of 1-D and 2-D flood models in presence of tidal influence. We recommend that under unavailability of precise LiDAR DEMs, resampled and freely available Carto DEMs, that are as efficient as LiDAR if not more, be given higher preference. We caution against the copious usage of global DEMs for large data-scarce and flood-prone regions, as the DEM uncertainty may be substantially amplified at the inundation level during combined channel and overland flood simulations. Through this study, we would like to recommend the proposed framework as a guided step while selecting appropriate DEM for flood inundation mapping over large data scarce regions.

Research paper thumbnail of A new bivariate risk classifier for flood management considering hazard and socio-economic dimensions

Journal of Environmental Management, 2020

 Users may download and print one copy of any publication from the public portal for the purpose... more  Users may download and print one copy of any publication from the public portal for the purpose of private study or research.  You may not further distribute the material or use it for any profit-making activity or commercial gain  You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Research paper thumbnail of Development of flood inundation extent libraries over a range of potential flood levels: a practical framework for quick flood response

Geomatics, Natural Hazards and Risk, 2016

The aim of the present study is motivated to build an inundation library for a range of gauge hei... more The aim of the present study is motivated to build an inundation library for a range of gauge heights, which can be used by decision-makers to anticipate the likely extent of inundation and provide quick response towards warning the habitation at threat. In the present study, two approaches for developing a series of static flood-inundation extent libraries for a range of potential flood levels using historical satellite images, gauge heights and digital elevation model (DEM) are demonstrated. First method is based on the geotagging of gauge height data with corresponding satellite observed inundation extent and the other method supplements the first method in the absence of adequate satellite data-sets by simulating inundation using gauge data and DEM for a range of gauge heights. Simulated inundation extents are validated with the satellite-derived reference inundation extents using spatial statistics, which measure the correspondence between the estimated and observed occurrence of events like probability of detection (POD), false-alarm ratio, and critical success index (CSI). A good correlation between the simulated inundation and satellite-derived inundation extents, with POD varying between 87% and 94%, CSI between 75% and 80% is observed.

Research paper thumbnail of Satellite-based assessment of the catastrophic Jhelum floods of September 2014, Jammu & Kashmir, India

Geomatics, Natural Hazards and Risk, 2016

The state of Jammu and Kashmir in North India experienced one of the worst floods in the past 60 ... more The state of Jammu and Kashmir in North India experienced one of the worst floods in the past 60 years, during the first week of September 2014. In the present study, multi-temporal synthetic aperture radar (SAR) satellite images acquired from Indian Remote Sensing (IRS) satellite RISAT-1 and Canadian satellite Radarsat-2 during the peak flood period (08thÀ23rd September 2014) are used for extraction of flood disaster footprints, mapping spatial and temporal dynamics of flood inundation and assessing the disaster impact. With the aid of pre-and post-flood satellite images, coupled with hydro-meteorological data, the unprecedented flood situation is analyzed. It is estimated that about 557 km 2 of the Kashmir Valley's geographical area was inundated. Bandipora, Pulwama, Srinagar, Baramulla and Budgam were the worst flood affected districts, having more than 50 km 2 of their area affected by flood waters. Of the total inundated area, about 80% of the area under agricultural activity was submerged, followed by built-up areas constituting about 12% of geographical area. About 22 lakh people in 287 villages were affected by floods. The flood waters persisted in the northern and central part of the valley for more than two weeks.

Research paper thumbnail of A decadal historical satellite data analysis for flood hazard evaluation: A case study of Bihar (North India)

Singapore Journal of Tropical Geography, 2015

Flood is one of the major recurrent natural disasters faced by the state of Bihar in north India.... more Flood is one of the major recurrent natural disasters faced by the state of Bihar in north India. In the present study the authors assess the severity of flood hazard in Bihar, using 128 decadal historical satellite datasets acquired during different flood magnitudes during 1998 to 2010. The satellite-based observations have been analysed in conjunction with the hydrological data, for assessing the frequency of inundation, severity of flood hazard and cropped land under flood hazard. This study assesses the spatial distribution of flooding and creation of systematic flood hazard database, which can be analysed from a spatial dimension in GIS. It is observed that about 24.56 lakh ha of the state's area and about 15.85 lakh ha of the cropped area are vulnerable to flood hazard. North Bihar is more vulnerable to flooding; 8 of the 10 areas identified as worst floodaffected districts lie in this region.

Research paper thumbnail of Emergency Management – a Geospatial Approach

Emergency can arise due to disaster caused by a technology or natural process. Emergency response... more Emergency can arise due to disaster caused by a technology or natural process. Emergency response needs rapid decisions in short time. In the circumstances of an emergency the normal channels of authority and communication cannot be relied upon to function routinely. The stress of the situation can lead to poor judgment resulting in severe losses. An emergency plan specifies procedures for handling sudden unexpected situations. The objective is to reduce the possible consequences of the emergency by (i) Preventing fatalities and injuries, (ii) Reducing damage to buildings, stock, and equipment and (iii) accelerating the resumption of normal operations. The geospatial data for emergency management has its significant importance. Data required for different kind of emergency range from spatial to attribute data. However, for technological disasters, required spatial information range from 1:10,000 to 1:2000, depending upon the kind of disaster that occurs. The emergency database can be developed on the basis of an object-oriented database design approach that proceeds from data collection, processing, organization and sharing through centralized data repository i.e. data warehouse. Emergency management is a typically multidisciplinary endeavour, requiring many types of data with spatial and temporal attributes that should be made available to key players in the right format for decisionmaking. There is an enormous amount of geospatial data of all kinds and formats, but it is often hard to find the right data at the right moment by the people who need the information for rescue work and recovery operations. The inability to access information and the lack of standardization, coordination, and communication are all obstacles that need to be overcome. Considering the importance to address the emergency management, Department of Space envisaged a programme for development of geospatial database at various scales along with decision support tools with multi-institutional support. This database, which will leverage much on the aerospace data, will have core data, hazard-specific data, and dynamic data in spatial as well as non-spatial forms. The proposed geospatial database will deliver the necessary information in time to the key players by adopting the latest developments in computer science and networking technologies. The required system configuration and network design using state of art technology is envisaged keeping in view of the functional requirements. The architecture incorporates the necessary features like multi-core/ multiprocessor systems, high-end storage and network devices to ensure good system response even with the overhead of additional security levels. A prototype decision support system was developed for certain emergencies arise out of natural disasters such as floods. It consists of generic display & query module to facilitate display of spatial & non-spatial data, identification of attribute information, overlays, simple thematic queries etc. besides analysis module catering to the specific needs pertaining to emergency management such as impact assessment, relief organization etc. The paper describes the conceptual geospatial database design envisaged and the decision support tools developed for emergency management. Application of the tools to selected case studies is also discussed in the paper.

Research paper thumbnail of Utilisation of Open Source Geo spatial Technologies for Disaster Preparedness

Research paper thumbnail of Mobile Technology Integrated with GIS for Better Management of Health Services

Research paper thumbnail of Implementation of service based architecture for satellite data archival & Decision support system development for Disaster Management Cyclone Phailin 2013 case study

Research paper thumbnail of Remote sensing and GIS in flood management in India

Research paper thumbnail of Development of Flood Hazard Maps for Assam State, India Using Historical Multitemporal Satellite Images

Flood Hazard Zonation (FHZ) is one of the most important non-structural measures, which facilitat... more Flood Hazard Zonation (FHZ) is one of the most important non-structural measures, which facilitates appropriate regulation, and development of floodplains thereby reducing the flood impact. The recurrent flood events at frequent intervals demand the need for identification of flood hazard prone areas for prioritizing appropriate flood control measures. A flood hazard map is considered as a preliminary, yet necessary input for all regional development policies.Decision Support Centre (DSC) of National Remote Sensing centre (NRSC), ISRO has prepared Flood Hazard Atlas for Assam State using more than 90 satellite datasets acquired from Indian Remote Sensing (IRS) and Radarsat satellites during flood season over Assam region for last 10 years (1998-2007). The flood hazard maps prepared using the satellite images acquired over the last one decade can be a critical scientific input in planning integrated basin flood management programme as a long term non-structural measure against recurr...

Research paper thumbnail of Space Technology for Flood Management: 25 Years of IRS

IRS satellites are the mainstay for the Disaster management activities in India especially flood ... more IRS satellites are the mainstay for the Disaster management activities in India especially flood monitoring. The flood monitoring activities initiated during the IRS 1A period has matured through the period and currently, all the major floods in the country are being monitored and the near real time information is being provided to the concerned for immediate actions. Flood hazard zonation based on the historical database, and river bank erosion monitoring are also being carried out. With the data from the IRS series of satellites, in addition to the flood events in the country, global disasters are also being supported.

Research paper thumbnail of Flood Monitoring and Management Using Remote Sensing

Flood disaster management cycle has three main phases viz. flood preparedness (before flood occur... more Flood disaster management cycle has three main phases viz. flood preparedness (before flood occurs), flood response (during a flood) and the last phase called flood mitigation (after flood has occurred). Flood preparedness involves identification of chronically flood prone areas, identification of areas that are liable to be affected by a flood and planning of optimum evacuation plans. Flood response involves the immediate action taken once the flood disaster has occurred in terms of the identification of the region affected, spatial extent of inundation, flood damage statistics, flood progression and recession etc which can help in carrying out the relief and rescue operations on ground. Flood mitigation phase starts after the flood has occurred by identification of the changes in the river course due to flooding, status of flood control works, river bank erosion, drainage congestion, flood hazard and risk vulnerability assessment .

Research paper thumbnail of Improved water management: The IRS-IC contribution

Research paper thumbnail of Ganga floods of 2010 in Uttar Pradesh, north India: a perspective analysis using satellite remote sensing data

Geomatics, Natural Hazards and Risk, 2014

The present study focuses on the unprecedented flood situation captured through multi-temporal sa... more The present study focuses on the unprecedented flood situation captured through multi-temporal satellite images, witnessed along the Ganga River in Uttar Pradesh during September 2010. At three gauge stations (Kannauj, Ankinghat and Kanpur), river water level exceeded the previous high-flood level attained by river more than a decade ago. The present communication with the aid of preand post-flood satellite images, coupled with hydrological (river water level) and meteorological (rainfall) data, explains about the unprecedented flood situation. In the latter part of the study, a novel and cost-effective method for building a library of flood inundation extents based on historical satellite data analysis and tagging the inundation layer with observed water level is demonstrated. During flood season, based on the forecasted water level, the library can be accessed to fetch the spatial inundation layer corresponding to the forecasted stage and anticipate in advance, likely spatial inundation pattern and submergence of villages and hence in alerting the habitation at risk. This method can be helpful in anticipating the areas to be affected in situations where satellite images cannot be effectively utilized due to cloud cover and also for providing information about the areas being partially covered in satellite data.

Research paper thumbnail of Characterizing Indian meteorological moisture anomaly condition using long‐term (1901–2013) gridded data: a multivariate moisture anomaly index approach

International Journal of Climatology, 2017

ABSTRACTThe long‐term (1901–2013) gridded rainfall and potential evapotranspiration (PET) data we... more ABSTRACTThe long‐term (1901–2013) gridded rainfall and potential evapotranspiration (PET) data were utilized to develop a new index, multivariate moisture anomaly index (MMAI), for characterizing the meteorological moisture anomaly condition during monsoon season over Indian region. The 6‐month timescale standardized precipitation index (SPI) and standardized evapotranspiration index (SEI) were computed using time series rainfall and PET data using gamma and log‐logistic distribution, respectively. The long‐term seasonal SPI and SEI were converted into moisture anomaly magnitude and duration information, and their trends were analysed using Sen's slope and Mann–Kendall test, respectively. The standardized precipitation evapotranspiration index (SPEI) at 6‐month timescale was also analysed to find the impact of rainfall and PET on meteorological moisture anomaly. Both the trends and probability analysis showed that SPEI was mainly representing the trends and pattern of SPI only a...

Research paper thumbnail of Defining a space-based disaster management system for floods: a case study for damage assessment due to 1998 Brahmaputra floods

Research paper thumbnail of Satellite Images for Extraction of Flood Disaster Footprints and Assessing the Disaster Impact:Brahmaputra Floods of June-July 2012, Assam, India

Current Science, Jun 25, 2013

ABSTRACT Satellite images provide information on the flood disaster footprints, which is essentia... more ABSTRACT Satellite images provide information on the flood disaster footprints, which is essential for assessing the disaster impact and taking up flood mitigation activities.The Brahmaputra floods that occurred during June–July 2012 devastated a large part of Assam. This article discusses the maximum spatial extent affected due to the flood event, villages marooned and population affected, with the aid of multi-temporal satellite images coupled with the hydrological observations and freely available gridded population data. The study shows that about 4.65 lakh ha area was submerged, 23 of the 27 districts in Assam had more than 5% of the total geographical area submerged, about 3829 villagesmarooned and 23.08 lakh people were affected.Identification of the spatial extent of areas most vulnerable to flooding, captured from the satellite images acquired during the peak flood period will be helpful for prioritizing appropriate flood control measures in the flood-affected regions.

Research paper thumbnail of Different Statistical Methods for the Discrimination of Tropical Mangrove Species Using In-Situ Hyperspectral Data

Journal of Hyperspectral Remote Sensing, 2019

The study highlights the hyperspectral characteristics of canopies of 14 tropical mangrove specie... more The study highlights the hyperspectral characteristics of canopies of 14 tropical mangrove species, belonging to nine families found in the tidal forests of the Indian Sundarbans. Hyperspectral observations were recorded using a field spectroradiometer, pre-processed and subjected to derivative analysis and continuum removal. Mann-Whitney U tests were applied on the spectral data in four spectral forms: (i) Reflectance Spectra (ii) First Derivative, (iii) Second Derivative and (iv) Continuum Removal Reflectance Spectra. Factor analysis was applied in each of the spectral forms for feature reduction and identification of the important wavelengths for species discrimination. Stepwise discriminant analysis was used on the feature reduced reflectance spectra to obtain optimal bands for computation of Jeffries–Matusita distance. The Mann-Whitney U test could be satisfactorily used for determining the significant (separable) bands for discriminating the species. In general, the red region...

Research paper thumbnail of Quantification of heat wave occurrences over the Indian region using long-term (1979–2017) daily gridded (0.5° × 0.5°) temperature data—a combined heat wave index approach

Theoretical and Applied Climatology, 2020

In the changing climate scenario, the changing heat wave frequency and magnitude have a direct im... more In the changing climate scenario, the changing heat wave frequency and magnitude have a direct impact on the agriculture, society, economic, and public health. Hence, development of easy and effective tools is essential for quantifying the heat wave incidences for better planning and management towards reducing the impacts of heat waves. In the present study, Climate Prediction Centre (CPC) global daily maximum temperature data along with the long-term normal data for the period 1979–2017 were used for quantification of heat wave conditions. Spatial and temporal sub-setting was carried out to restrict our study within the Indian region and March–July period, respectively. Based on heat wave criteria prescribed by the India Meteorological Department, different heat wave parameters, viz. frequency, magnitude, and extent, were estimated. A new approach, i.e. combined heat-wave index (CHI), was proposed to quantify the impact of heat wave in a profound manner. The efficacy of the overall method of assessing the impact of heat wave had increased by using this new approach. It was found that Rajasthan, Punjab Haryana, and Madhya Pradesh experienced high frequency as well as magnitude of heat wave, while it was lower in north-east, peninsular, and parts of northern India during our study period. The trend analysis for the heat wave parameters along with CHI was carried out over the Indian region during the last 39 years. The increasing trends were found over Rajasthan, Haryana, Punjab, East Madhya Pradesh, and Orissa, while places like Uttar Pradesh, Bihar, Chhattisgarh, Telangana, and Andhra Pradesh showed decreasing trend over the last 39 years. Peninsular and north-east India showed almost no trend regarding heat wave. Further, the month with the maximum contribution towards the seasonal heat wave and its deviation was also estimated. It was observed that the month of May was contributing most over parts of north-western and central India, while it was June in Punjab, Haryana, and western Rajasthan. Hence, the present methodology may be adopted for better planning and management of heat waves.

Research paper thumbnail of Sensitivity of various topographic data in flood management: Implications on inundation mapping over large data-scarce regions

Journal of Hydrology, 2020

Topographic data in the form of digital elevation models (DEMs) play a significant role in flood ... more Topographic data in the form of digital elevation models (DEMs) play a significant role in flood management. Despite the increasing availability of DEMs for large regions, there is a need to evaluate their performance at the inundation/flood level, while considering the overall complexity of flood models. The present study identifies, for the first time, the uncertainties generated in both river channel and overland flooding while considering a set of nine variants from various sources (LiDAR, Cartosat, SRTM, and ASTER) and grid resolutions (resampled versions) in the presence of discharge, rainfall, and tide boundary conditions for a severely flood-prone catchment in the Mahanadi River Basin, India. Extensive geostatistical analyses reveal the existence of significant biases with global DEMs i.e., SRTM and ASTER, whereas interestingly the LiDAR and Carto DEMs exhibit a high degree of isotropy. The global DEMs fail to capture several inundated spots; thus plummeting the flood inundation extents to a sufficient degree of unacceptability. Prominently, the inability in identifying high and very high flood depths (> 1.5 m) over the coastal stretches results in large uncertainties in the majority of the grids. Our analysis reveals the existence of significant noise in global DEMs, which nullifies the hydrodynamic interaction during the coupling of 1-D and 2-D flood models in presence of tidal influence. We recommend that under unavailability of precise LiDAR DEMs, resampled and freely available Carto DEMs, that are as efficient as LiDAR if not more, be given higher preference. We caution against the copious usage of global DEMs for large data-scarce and flood-prone regions, as the DEM uncertainty may be substantially amplified at the inundation level during combined channel and overland flood simulations. Through this study, we would like to recommend the proposed framework as a guided step while selecting appropriate DEM for flood inundation mapping over large data scarce regions.

Research paper thumbnail of A new bivariate risk classifier for flood management considering hazard and socio-economic dimensions

Journal of Environmental Management, 2020

 Users may download and print one copy of any publication from the public portal for the purpose... more  Users may download and print one copy of any publication from the public portal for the purpose of private study or research.  You may not further distribute the material or use it for any profit-making activity or commercial gain  You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Research paper thumbnail of Development of flood inundation extent libraries over a range of potential flood levels: a practical framework for quick flood response

Geomatics, Natural Hazards and Risk, 2016

The aim of the present study is motivated to build an inundation library for a range of gauge hei... more The aim of the present study is motivated to build an inundation library for a range of gauge heights, which can be used by decision-makers to anticipate the likely extent of inundation and provide quick response towards warning the habitation at threat. In the present study, two approaches for developing a series of static flood-inundation extent libraries for a range of potential flood levels using historical satellite images, gauge heights and digital elevation model (DEM) are demonstrated. First method is based on the geotagging of gauge height data with corresponding satellite observed inundation extent and the other method supplements the first method in the absence of adequate satellite data-sets by simulating inundation using gauge data and DEM for a range of gauge heights. Simulated inundation extents are validated with the satellite-derived reference inundation extents using spatial statistics, which measure the correspondence between the estimated and observed occurrence of events like probability of detection (POD), false-alarm ratio, and critical success index (CSI). A good correlation between the simulated inundation and satellite-derived inundation extents, with POD varying between 87% and 94%, CSI between 75% and 80% is observed.

Research paper thumbnail of Satellite-based assessment of the catastrophic Jhelum floods of September 2014, Jammu & Kashmir, India

Geomatics, Natural Hazards and Risk, 2016

The state of Jammu and Kashmir in North India experienced one of the worst floods in the past 60 ... more The state of Jammu and Kashmir in North India experienced one of the worst floods in the past 60 years, during the first week of September 2014. In the present study, multi-temporal synthetic aperture radar (SAR) satellite images acquired from Indian Remote Sensing (IRS) satellite RISAT-1 and Canadian satellite Radarsat-2 during the peak flood period (08thÀ23rd September 2014) are used for extraction of flood disaster footprints, mapping spatial and temporal dynamics of flood inundation and assessing the disaster impact. With the aid of pre-and post-flood satellite images, coupled with hydro-meteorological data, the unprecedented flood situation is analyzed. It is estimated that about 557 km 2 of the Kashmir Valley's geographical area was inundated. Bandipora, Pulwama, Srinagar, Baramulla and Budgam were the worst flood affected districts, having more than 50 km 2 of their area affected by flood waters. Of the total inundated area, about 80% of the area under agricultural activity was submerged, followed by built-up areas constituting about 12% of geographical area. About 22 lakh people in 287 villages were affected by floods. The flood waters persisted in the northern and central part of the valley for more than two weeks.

Research paper thumbnail of A decadal historical satellite data analysis for flood hazard evaluation: A case study of Bihar (North India)

Singapore Journal of Tropical Geography, 2015

Flood is one of the major recurrent natural disasters faced by the state of Bihar in north India.... more Flood is one of the major recurrent natural disasters faced by the state of Bihar in north India. In the present study the authors assess the severity of flood hazard in Bihar, using 128 decadal historical satellite datasets acquired during different flood magnitudes during 1998 to 2010. The satellite-based observations have been analysed in conjunction with the hydrological data, for assessing the frequency of inundation, severity of flood hazard and cropped land under flood hazard. This study assesses the spatial distribution of flooding and creation of systematic flood hazard database, which can be analysed from a spatial dimension in GIS. It is observed that about 24.56 lakh ha of the state's area and about 15.85 lakh ha of the cropped area are vulnerable to flood hazard. North Bihar is more vulnerable to flooding; 8 of the 10 areas identified as worst floodaffected districts lie in this region.

Research paper thumbnail of Emergency Management – a Geospatial Approach

Emergency can arise due to disaster caused by a technology or natural process. Emergency response... more Emergency can arise due to disaster caused by a technology or natural process. Emergency response needs rapid decisions in short time. In the circumstances of an emergency the normal channels of authority and communication cannot be relied upon to function routinely. The stress of the situation can lead to poor judgment resulting in severe losses. An emergency plan specifies procedures for handling sudden unexpected situations. The objective is to reduce the possible consequences of the emergency by (i) Preventing fatalities and injuries, (ii) Reducing damage to buildings, stock, and equipment and (iii) accelerating the resumption of normal operations. The geospatial data for emergency management has its significant importance. Data required for different kind of emergency range from spatial to attribute data. However, for technological disasters, required spatial information range from 1:10,000 to 1:2000, depending upon the kind of disaster that occurs. The emergency database can be developed on the basis of an object-oriented database design approach that proceeds from data collection, processing, organization and sharing through centralized data repository i.e. data warehouse. Emergency management is a typically multidisciplinary endeavour, requiring many types of data with spatial and temporal attributes that should be made available to key players in the right format for decisionmaking. There is an enormous amount of geospatial data of all kinds and formats, but it is often hard to find the right data at the right moment by the people who need the information for rescue work and recovery operations. The inability to access information and the lack of standardization, coordination, and communication are all obstacles that need to be overcome. Considering the importance to address the emergency management, Department of Space envisaged a programme for development of geospatial database at various scales along with decision support tools with multi-institutional support. This database, which will leverage much on the aerospace data, will have core data, hazard-specific data, and dynamic data in spatial as well as non-spatial forms. The proposed geospatial database will deliver the necessary information in time to the key players by adopting the latest developments in computer science and networking technologies. The required system configuration and network design using state of art technology is envisaged keeping in view of the functional requirements. The architecture incorporates the necessary features like multi-core/ multiprocessor systems, high-end storage and network devices to ensure good system response even with the overhead of additional security levels. A prototype decision support system was developed for certain emergencies arise out of natural disasters such as floods. It consists of generic display & query module to facilitate display of spatial & non-spatial data, identification of attribute information, overlays, simple thematic queries etc. besides analysis module catering to the specific needs pertaining to emergency management such as impact assessment, relief organization etc. The paper describes the conceptual geospatial database design envisaged and the decision support tools developed for emergency management. Application of the tools to selected case studies is also discussed in the paper.

Research paper thumbnail of Utilisation of Open Source Geo spatial Technologies for Disaster Preparedness

Research paper thumbnail of Mobile Technology Integrated with GIS for Better Management of Health Services

Research paper thumbnail of Implementation of service based architecture for satellite data archival & Decision support system development for Disaster Management Cyclone Phailin 2013 case study

Research paper thumbnail of Remote sensing and GIS in flood management in India

Research paper thumbnail of Development of Flood Hazard Maps for Assam State, India Using Historical Multitemporal Satellite Images

Flood Hazard Zonation (FHZ) is one of the most important non-structural measures, which facilitat... more Flood Hazard Zonation (FHZ) is one of the most important non-structural measures, which facilitates appropriate regulation, and development of floodplains thereby reducing the flood impact. The recurrent flood events at frequent intervals demand the need for identification of flood hazard prone areas for prioritizing appropriate flood control measures. A flood hazard map is considered as a preliminary, yet necessary input for all regional development policies.Decision Support Centre (DSC) of National Remote Sensing centre (NRSC), ISRO has prepared Flood Hazard Atlas for Assam State using more than 90 satellite datasets acquired from Indian Remote Sensing (IRS) and Radarsat satellites during flood season over Assam region for last 10 years (1998-2007). The flood hazard maps prepared using the satellite images acquired over the last one decade can be a critical scientific input in planning integrated basin flood management programme as a long term non-structural measure against recurr...

Research paper thumbnail of Space Technology for Flood Management: 25 Years of IRS

IRS satellites are the mainstay for the Disaster management activities in India especially flood ... more IRS satellites are the mainstay for the Disaster management activities in India especially flood monitoring. The flood monitoring activities initiated during the IRS 1A period has matured through the period and currently, all the major floods in the country are being monitored and the near real time information is being provided to the concerned for immediate actions. Flood hazard zonation based on the historical database, and river bank erosion monitoring are also being carried out. With the data from the IRS series of satellites, in addition to the flood events in the country, global disasters are also being supported.

Research paper thumbnail of Flood Monitoring and Management Using Remote Sensing

Flood disaster management cycle has three main phases viz. flood preparedness (before flood occur... more Flood disaster management cycle has three main phases viz. flood preparedness (before flood occurs), flood response (during a flood) and the last phase called flood mitigation (after flood has occurred). Flood preparedness involves identification of chronically flood prone areas, identification of areas that are liable to be affected by a flood and planning of optimum evacuation plans. Flood response involves the immediate action taken once the flood disaster has occurred in terms of the identification of the region affected, spatial extent of inundation, flood damage statistics, flood progression and recession etc which can help in carrying out the relief and rescue operations on ground. Flood mitigation phase starts after the flood has occurred by identification of the changes in the river course due to flooding, status of flood control works, river bank erosion, drainage congestion, flood hazard and risk vulnerability assessment .

Research paper thumbnail of Improved water management: The IRS-IC contribution

Research paper thumbnail of Ganga floods of 2010 in Uttar Pradesh, north India: a perspective analysis using satellite remote sensing data

Geomatics, Natural Hazards and Risk, 2014

The present study focuses on the unprecedented flood situation captured through multi-temporal sa... more The present study focuses on the unprecedented flood situation captured through multi-temporal satellite images, witnessed along the Ganga River in Uttar Pradesh during September 2010. At three gauge stations (Kannauj, Ankinghat and Kanpur), river water level exceeded the previous high-flood level attained by river more than a decade ago. The present communication with the aid of preand post-flood satellite images, coupled with hydrological (river water level) and meteorological (rainfall) data, explains about the unprecedented flood situation. In the latter part of the study, a novel and cost-effective method for building a library of flood inundation extents based on historical satellite data analysis and tagging the inundation layer with observed water level is demonstrated. During flood season, based on the forecasted water level, the library can be accessed to fetch the spatial inundation layer corresponding to the forecasted stage and anticipate in advance, likely spatial inundation pattern and submergence of villages and hence in alerting the habitation at risk. This method can be helpful in anticipating the areas to be affected in situations where satellite images cannot be effectively utilized due to cloud cover and also for providing information about the areas being partially covered in satellite data.