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Sarma, K. K.
- Recognizing the Rapid Expansion of Rubber Plantation – A Threat to Native Forest in Parts of Northeast India
Abstract Views :341 |
PDF Views:106
Authors
Affiliations
1 North Eastern Space Applications Centre, Umiam 793 103, IN
2 Department of Ecology and Environmental Science, Assam University, Silchar 788 011, IN
1 North Eastern Space Applications Centre, Umiam 793 103, IN
2 Department of Ecology and Environmental Science, Assam University, Silchar 788 011, IN
Source
Current Science, Vol 114, No 01 (2018), Pagination: 207-213Abstract
With the current trend of land use/land cover (LULC) change taking place globally, several parts of northeast India are also showing signs of change in LULC pattern leading to forest loss. This study focusses on the expansion of monoculture rubber plantation (Hevea brasiliensis) in selected sub-watersheds in north-east India, and distributed in parts of north Tripura, Mizoram and a major portion in the Karimganj district of Assam. Remote sensing and GIS technique has been used to map and analyse the extent of rubber plantation using temporal IRS LISS III satellite data from 1997 to 2013. It has been observed that rubber plantation increased from 4.47 sq. km to 28.42 sq. km in various parts of the study area. The expansion was more rapid during recent times, i.e. during 2010 to 2013. The plantation took place in dense forest, open forest and degraded forest areas. The spread of the plantation was also observed in one reserved forest located within the study area. There are several instances of negative impacts of rubber plantation expansion in Southeast Asia. Similar expansion of rubber plantation has been observed in northeast India as well. Further spread of rubber plantations in the region needs to be regulated to avoid conversion of dense and reserved forest areas by fostering use of mixed cropping methods instead of rubber monocultures, and by adopting more sustainable land use and management practices.Keywords
Northeast India, Remote Sensing and GIS, Rubber Plantation.Full Text
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- Total Electron Content and Epicentral Distance of 2015 Mw 7.8 Nepal Earthquake Revealed by Continuous Observations Data
Abstract Views :524 |
PDF Views:88
Authors
Gopal Sharma
1,
S. Mohanty
2,
P. K. Champati Ray
3,
M. Somorjit Singh
1,
K. K. Sarma
1,
P. L. N. Raju
1
Affiliations
1 North Eastern Space Application Centre, Umiam 793 103, IN
2 Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, IN
3 Indian Institute of Remote Sensing, Dehradun 248 001, IN
1 North Eastern Space Application Centre, Umiam 793 103, IN
2 Indian Institute of Technology (Indian School of Mines), Dhanbad 826 004, IN
3 Indian Institute of Remote Sensing, Dehradun 248 001, IN
Source
Current Science, Vol 115, No 1 (2018), Pagination: 27-29Abstract
A large magnitude (Mw 7.8) earthquake occurred on 25 April 2015 (06:11 UTC) at 28.1473°N and 84.7079°E, 34 km east-southeast of Lamjung, Nepal. The devastating event was accompanied by two large aftershocks of Mw 6.6 (on 25 April 2015, 06:45 UTC) and Mw 6.7 (on 26 April 2015 at 09:10 UTC). According to the USGS earthquake catalogue, 65 aftershocks were recorded within a period of three days from the main event; the strongest aftershock had occurred on 12 May 2015 at 07:05 UTC.Full Text
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- Forest Biometric Parameter Extraction using Unmanned Aerial Vehicle to Aid in Forest Inventory Data Collection
Abstract Views :272 |
PDF Views:84
Authors
Kasturi Chakraborty
1,
Victor Saikom
1,
Suranjana B. Borah
1,
Mamita Kalita
1,
Chirag Gupta
1,
Laishram Ricky Meitei
2,
K. K. Sarma
1,
P. L. N. Raju
1
Affiliations
1 North Eastern Space Applications Centre, Umiam 793 103, IN
2 Botanical Survey of India, ERC, Shillong 793 003, IN
1 North Eastern Space Applications Centre, Umiam 793 103, IN
2 Botanical Survey of India, ERC, Shillong 793 003, IN
Source
Current Science, Vol 117, No 7 (2019), Pagination: 1194-1199Abstract
Frequent ground surveys and satellite-based information on tree height, canopy gaps and forest dynamics are limited by time, cost and spatial scales. In this study, an attempt has been made to derive forest biometric parameter on tree height by canopy height model and crown area projections using unmanned aerial vehicles (UAV)–RGB image. Sorensen’s coefficient has been used as an index to compare between ground inventory and UAV-based species identification. The statistical paired t-test showed UAV RGB can be used for maximum tree height and tree crown extraction to aid in ground surveys.Keywords
Canopy Height Model, Canopy Area Projection, Forest Biometry, Unmanned Aerial Vehicles.Full Text
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