Venkata Sai Krishna VanamaIndian Institute of Technology Bombay | IIT Bombay · Center for Urban Science and Engineering
Venkata Sai Krishna Vanama
M.Tech RS & GIS with specialization in Human Settlement Analysis
About
31
Publications
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Introduction
Venkata Sai Krishna Vanama currently works at the Center for Urban Science and Engineering, Indian Institute of Technology Bombay. Venkata Sai Krishna does research in the application of geospatial technologies in Urban Planning Their current project is 'Urban Flood Mapping.'
Additional affiliations
January 2015 - January 2016
January 2015 - January 2016
Publications
Publications (31)
The absence of an integrated geospatial database hinders effective decision-making among various stakeholders in national projects and programs. The study aimed to create an integrated geospatial database for the Manesar tehsil, District Gurugram, Haryana. Another objective was to create a land use map to analyze the temporal change in land use pat...
Multi-agency investments require local coordination, planning, and implementation. GIS allows us to analyze and comprehend real-world processes by constructing and applying manipulation, analytical criteria, and models for daily decision making. This requires a geospatial database with surveyed land, assets, hydro, etc. Survey of India (SOI) is pub...
The new era of cloud platform technologies opens up many opportunities for near real-time dissemination of disaster information to the end-users. The present study utilizes the European Space Agency (ESA) Research and Service Support (RSS) CloudToolbox platform to monitor the spatio-temporal dynamics of a flood event. A collective flood monitoring...
The dual polarimetric study including degree of polarization (mL) and energy span (λ1+ λ2) for vegetation targets infer the accuracy of vegetation algorithms. The Sentinel – 1A and ALOS - 2 satellite data were utilized for dual polarimetric radar vegetation index (DPRVI), polarimetric radar vegetation index (PRVI) and radar vegetation index (RVI) c...
In August 2018, the southern Indian state of Kerala received unusually heavy rainfall leading to large-scale flooding and destruction. Reliable flood inunda-tion maps derived from remote sensing techniques help in flood disaster management activities. The freely available Sentinel-1A/B SAR data have the potential for flood inundation mapping due to...
The future projections of climate change envisage a global increase in extreme precipitation events and subsequent flooding. The reliable and rapid flood maps are the critical parameters in preparing the disaster management plans. This study demonstrated an effective flood mapping framework using freely available multi-temporal Earth Observation (E...
Estimation of economic loss due to flood often becomes necessary for flood damage assessment. Conventional practices to estimate damage by postflood survey are laborious and time-consuming. This study presents a framework of rapid estimation of flood damage using earth observation satellite data to minimize the time and efforts for damage assessmen...
Forest fires occur throughout the year in rainforests and deserts of Australia. The disastrous bush fire event occurred during November 2019, and lasted until February 2020, destroying more than 46 million acres of land. Burn area mapping is a major parameter in carrying out mitigation measures and regrowth activities by forest officials or fire ma...
The present state of the art technologies for flood mapping are typically tested on small geographical regions due to limitation of resources, which hinders the implementation of real-time flood management activities. We proposed a unified framework (GEE4FLOOD) for rapid flood mapping in Google Earth Engine (GEE) cloud platform. With the unexpected...
Sentinel-1 SAR data preprocessing is essential for several earth observation applications, including land cover classification, change detection, vegetation monitoring, urban growth, natural hazards, etc. The information can be extracted from the 2x2 covariance matrix [C2] of Sentinel-1 dual-pol (VV-VH) acquisitions. To generate the covariance matr...
Chennai, the capital city of Tamil Nadu state, India experienced a major disastrous flood during Nov-Dec 2015. The city is characterized by mixed land use with high built-up density. The freely available C-band Sentinel-1 temporal GRDH SAR images are used to analyze this flood event. We used the co-polarized (VV) SAR images for mapping the flood ar...
Remote sensing plays a prominent role in the rapid detection of the flood event at a regional level. In this paper, the potential of AMSR-E images in regional level flood detection was identified. The study area of the research covers a part of Krishna river basin in the Andhra Pradesh state of India. Spatio-temporal database of daily Land Surface...
Climatological variables such as rainfall, temperature have been extensively used by researchers for drought monitoring at a larger spatial region. These variables have a direct influence on the soil moisture which in turn extends the application of soil moisture in drought assessment. With the advancement of technology, various satellites provide...
Forest fires are the most frequent phenomenon during the summer season in India, and especially in the hilly terrains of Uttarakhand forests. Remote sensing sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Very High Resolution Radiometer (AVHRR), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) a...
Land Surface Water Coverage (LSWC) is one of the critical parameters in large-scale flood identification and agriculture monitoring. In this paper, a time series geospatial database of LSWC was created to analyse the large-scale flooding pattern. Normalized Difference polarization Index (NDPI) was computed from AMSR-E brightness temperature of vert...
Urban areas are characterized by heterogeneous land uses. The city development pattern, socioeconomic
and anthropogenic activities result in the formation of Urban Heat Island (UHI) which are characterized by
high Land Surface Temperatures (LST). Cities are experiencing a rapid increase in LST. Urban green spaces such as parks, playgrounds, lawns a...
Remote sensing plays a prominent role in the rapid detection of
the flood at a regional level. In this paper, the potential of AMSR-E images
in regional level flood detection was identified. The study area of the research
covers a part of Krishna river basin in the Andhra Pradesh state of
India. Spatio-temporal database of daily Land Surface Water...
Many Indian cities are facing abnormal changes in urban land surface temperatures (LST) due to the formation of urban heat islands (UHI). Heavy increase of pollution and greenhouse gases in the urban atmosphere are the major driving forces to changes in urban local climate. Urban LST plays a major role in the urban development and planning purposes...
Solid waste generation is increasing rapidly in urban areas of India as well as globally. As land resources for waste disposal are limited in highly populated countries like India, identification of solid waste disposal sites in urban centres is a challenging task, as this involves physical, socio-economic and environmental factors. Dehradun, the c...
Many Indian cities that are of national importance are affected by floods. The recent flooding in Bangalore during July 28-29, 2016 is one such example. In the present research, C-band RISAT-1 satellite data with medium resolution scanning (MRS) mode is used for urban flood extent mapping (UFEM). Pre (July 5, 2016) and post (July 30, 2016) flood SA...
Urban expansion, water bodies and climate change are inextricably linked with each other. The macro and micro level climate changes are leading to extreme precipitation events which have severe consequences on flooding in urban areas. Flood simulations shall be helpful in demarcation of flooded areas and effective flood planning and preparedness. T...
The identity, requirement, demand and usage of space-based satellite images depends on their image characteristics, especially their inherent resolutions, i.e. spatial, spectral and temporal. Multi-spatial resolutions images for a given location provides different levels of information (scale) for a particular object. Image fusion techniques are em...
Questions
Questions (15)
Conference Paper Sentinel-1 Global Coverage Foreshortening Mask Extraction: a...
Hi,
The link for GEE code given in the article is not opening. Can you share the code which will be helpful to my work.
The paper was very well written. I would like to implement it on my study area.
Can you share the GEE code?
Can anybody mention the sources from which I can access the data?
The default option of saving the map document for "save" option is saving it in its current version for Arcmap 10.2.2. But in sofware like autocad there is an option to these default setting.
Is there any options for arcgis like that?
I have a set of 30 Arcmap 10.3 documents due to some reasons I have uninstalled the software and installed 10.1 can i build any model in model builder to automatically convert the higher version documents into lower versions?
The study area is one of the metro cities of India.
I have done some image processing which resulted me some 'n' number of bands with same resolution in tif format of same location. The number of rows and columns are slightly different in all the bands. Then I have stack all the layers and used 'extract values to point' tool in GIS but it didnt work. Then I have done it band wise it worked which took lot of time. Can any one suggest any alternative method in any other software or in GIS itself.
