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Co-Authors
- A. S. Rajawat
- H. B. Chauhan
- S. Rode
- R. J. Bhanderi
- M. Mahapatra
- Mohit Kumar
- R. Yadav
- S. P. Abraham
- S. S. Singh
- K. N. Keshri
- Ajai
- Thalkari Sanket Shivkumar
- P. Vetrivelan
- S. Sarvanan
- Glenford Mapp
- Nandini Ray Chaudhury
- Preeti Rajput
- Mohit Arora
- Ashwin Gujrati
- S. V. V. Arunkumar
- Ateeth Shetty
- Rakesh Baral
- Rakesh Patel
- Devanshi Joshi
- Harshad Patel
- Bharat Pathak
- K. S. Jayappa
- R. N. Samal
- H. Bhatti
- D. Ram Rajak
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Ratheesh, R.
- Assessment of Coastal Erosion along the Indian Coast on 1:25,000 Scale Using Satellite Data of 1989-1991 and 2004-2006 Time Frames
Abstract Views :231 |
PDF Views:108
Authors
A. S. Rajawat
1,
H. B. Chauhan
1,
R. Ratheesh
1,
S. Rode
1,
R. J. Bhanderi
1,
M. Mahapatra
1,
Mohit Kumar
1,
R. Yadav
2,
S. P. Abraham
3,
S. S. Singh
2,
K. N. Keshri
2,
Ajai
1
Affiliations
1 Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, IN
2 Central Water Commission, Ministry of Water Resources, New Delhi 110 606, IN
3 Central Water Commission, Ministry of Water Resources, Kochi 682 020, IN
1 Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, IN
2 Central Water Commission, Ministry of Water Resources, New Delhi 110 606, IN
3 Central Water Commission, Ministry of Water Resources, Kochi 682 020, IN
Source
Current Science, Vol 109, No 2 (2015), Pagination: 347-353Abstract
The long stretch of coastline on either side of the Indian peninsula is subjected to varied coastal processes and anthropogenic pressures, which makes the coast vulnerable to erosion. There is no systematic inventory of shoreline changes occurring along the entire Indian coast on 1 : 25,000 scale, which is required for planning measures to be taken up for protecting the coast at the national level. It is in this context that shoreline change mapping on 1 : 25,000 scale for the entire Indian coast based on multidate satellite data in GIS environment has been carried out for 1989-1991 and 2004-2006 time frame. The present communication discusses salient observations and results from the shoreline change inventory. The results show that 3829 km (45.5%) of the coast is under erosion, 3004 km (35.7%) is getting accreted, while 1581 km (18.8%) of the coast is more or less stable in nature. Highest percentage of shoreline under erosion is in the Nicobar Islands (88.7), while the percentage of accreting coastline is highest for Tamil Nadu (62.3) and Goa has the highest percentage of stable shoreline (52.4). The analysis shows that the Indian coast has lost a net area of about 73 sq. km during 1989-1991 and 2004-2006 time frame. In Tamil Nadu, a net area of about 25.45 sq. km has increased due to accretion, while along the Nicobar Islands about 93.95 sq. km is lost due to erosion. The inventory has been used to prepare a Shoreline Change Atlas of the Indian Coast.Keywords
Accretion, Coastal Erosion, Shoreline Changes, High and Low Tide Lines, Satellite Data.- Efficient Location and Capacity Planning of Node B for 3G Networks
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Authors
Affiliations
1 School of Electronics Engineering, VIT University, Chennai – 600127, Tamil Nadu, IN
2 School of Electronics Engineering, VIT University, Chennai – 600127, Tamil Nadu
3 RF Planning, Bharti Airtel Ltd, Chennai - 600028, Tamil Nadu, IN
4 Middlesex University, London, NW4 4BT, United Kingdom
1 School of Electronics Engineering, VIT University, Chennai – 600127, Tamil Nadu, IN
2 School of Electronics Engineering, VIT University, Chennai – 600127, Tamil Nadu
3 RF Planning, Bharti Airtel Ltd, Chennai - 600028, Tamil Nadu, IN
4 Middlesex University, London, NW4 4BT, United Kingdom
Source
Indian Journal of Science and Technology, Vol 9, No 7 (2016), Pagination:Abstract
Capacity planning of 3G network unlike 2G is cumbersome. The 3G capacity is multi-fold. It depends on Power Utilization, Code Utilization, Iub (interface between the Radio Network Controller (RNC) and the Node B) and Channel Element (CE). The location of Node B plays a crucial role in 3G Planning. The Radio Frequency planner needs to select the best optimal location for setting up the 3G site in order to a seamless coverage to the customers. In this paper, these topics are explored in a detail manner. For this planning the Node B layout for Airtel in the densely populated Santhome area of Chennai is discussed. The basis issue is the interdependence between coverage and capacity in 3G. In 3G systems, both capacity and quality should be monitored to ensure the best network performance. Planning of new base station has been first treated with an analytical study of the cell coverage range for a specific environment and service. The accomplished results have been checked using ASSET simulation tool and Geographical Information System (GIS) tool.Keywords
ASSET, Capacity. Coverage Prediction, Pilot Pollution, 3G- Coastal Sediment Dynamics, Ecology and Detection of Coral Reef Macroalgae from AVIRIS-NG
Abstract Views :203 |
PDF Views:68
Authors
R. Ratheesh
1,
Nandini Ray Chaudhury
1,
Preeti Rajput
1,
Mohit Arora
1,
Ashwin Gujrati
1,
S. V. V. Arunkumar
1,
Ateeth Shetty
2,
Rakesh Baral
3,
Rakesh Patel
4,
Devanshi Joshi
4,
Harshad Patel
4,
Bharat Pathak
4,
K. S. Jayappa
2,
R. N. Samal
3,
A. S. Rajawat
1
Affiliations
1 Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, IN
2 Mangalore University, Mangalagangorti, Mangaluru 574 199, IN
3 Chilika Development Authority, Bhubaneswar 751 014, IN
4 Gujarat Ecological Education and Research Foundation, Gandhinagar 382 007, IN
1 Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, IN
2 Mangalore University, Mangalagangorti, Mangaluru 574 199, IN
3 Chilika Development Authority, Bhubaneswar 751 014, IN
4 Gujarat Ecological Education and Research Foundation, Gandhinagar 382 007, IN
Source
Current Science, Vol 116, No 7 (2019), Pagination: 1157-1165Abstract
This article highlights major scientific outcomes of the studies carried out using Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) airborne data over the coastal regions of Mangaluru, Gulf of Kachchh (GoK) and Chilika lagoon. Various hyperspectral remote sensing techniques involving bio-optical models and spectral classification algorithms are used to achieve different objectives related to coastal ecosystem monitoring. AVIRIS-NG airborne data are used to estimate particle size of suspended solids along the coastal waters of Mangaluru using an analytical optical model. The spatial distribution of particle size of the suspended solids in the coastal waters is brought out, while along the coastal land of Mangaluru, the beaches are classified based on uniform sediment characteristics using spectral matching algorithm. AVIRIS-NG data for Pirotan reef in GoK is analysed and species-level identification of the dominant brown macroalgae is carried out. Species-level distribution of brown macroalgae is mapped and used to study the microhabitat preference of different species. At Chilika lagoon, the AVIRIS-NG data are analysed to map the abundance of submerged seagrass using bio-optical model, which provides vital information to the coastal management community. The study asserts the importance of hyperspectral data and various advanced data analysis techniques related to the estimation of geophysical parameters of the coastal waters and monitoring the vital coastal ecosystems.Keywords
Brown Macroalgae, Coastal Regions, Suspended Sediment Properties, Submerged Seagrass.References
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- Quantification of Shoreline Changes along the Entire Indian Coast Using Indian Remote Sensing Satellite Images of 2004–06 and 2014–16
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Authors
Affiliations
1 Geo Sciences Division, GHCAG, Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, IN
1 Geo Sciences Division, GHCAG, Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, IN
Source
Current Science, Vol 124, No 5 (2023), Pagination: 578-584Abstract
The coastal region of India is highly vulnerable to various threats, including coastal erosion, due to natural processes enhanced by anthropogenic influences. Shoreline change inventories are the pre-requisite for identifying the coastal stretches subjected to erosion. In this study, the shoreline of the entire Indian coast was delineated at a scale of 1 : 25,000 using IRS LISS-IV images of 2004–06 and 2014–16 time frames. The spatial shift between the shoreline of two time frames was estimated in the GIS platform and a database of shoreline changes was prepared. The eroding, accreting and stable length of the shoreline were calculated for the Indian coast along with the area of erosion and accretion. This study discusses the imperative results of shoreline mapping and the status of shoreline changes on the Indian coast. The shoreline changes in terms of erosion and accretion were assessed for 7549 km of the Indian coast. It was found that the coast is eroding along 1144 km and accretion of the coast is along 1084 km, while 5321 km of the coastline shows no changes between the two time frames. The coastal land area lost due to erosion was 3680 ha; however, the increase in land area as a result of coastal deposition was 4042 ha. The regional coastal processes and the associated shoreline changes and coastal issues related to anthropogenic impacts are also discussed in this study. The inventory of shoreline changes has been used to prepare six volumes of Shoreline Change Atlas covering the entire Indian coast. The shoreline change database forms the baseline data for planning any coastal development activity by the maritime authorities apart from the potential use by the scientific community.Keywords
Coastal Erosion and Accretion, High Tide Line, Remote Sensing, Shoreline Changes.References
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