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- B. K. Handique
- P. T. Das
- J. Goswami
- C. Goswami
- P. S. Singh
- C. J. Prabhakar
- C. M. Bajpeyi
- Jonali Goswami
- Abdul Qadir
- Chirag Gupta
- Kasturi Chakraborty
- S. Sudhakar
- K. K. Sarma
- Ashesh Kr. Das
- Mayuri Sharma
- Victor Saikhom
- Dibyajyoti Chutia
- Avinash Chouhan
- Gopal Sharma
- S. Mohanty
- P. K. Champati Ray
- M. Somorjit Singh
- Pratibha T. Das
- Victor Saikom
- Suranjana B. Borah
- Mamita Kalita
- Laishram Ricky Meitei
- Gaurav Singhal
- Babankumar Bansod
- Lini Mathew
- B. U. Choudhury
- Ashu Negi
- Tapan Adhikari
- Chandan Goswami
- D. K. Gogoi
- N. Rasid
- G. Subrahmanyam
- P. P. Bora
- R. Das
Journals
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Raju, P. L. N.
- Expansion of Sericulture in India Using Geospatial Tools and Web Technology
Abstract Views :425 |
PDF Views:148
Authors
B. K. Handique
1,
P. T. Das
1,
J. Goswami
1,
C. Goswami
1,
P. S. Singh
1,
C. J. Prabhakar
2,
C. M. Bajpeyi
2,
P. L. N. Raju
1
Affiliations
1 North Eastern Space Applications Centre, Department of Space, Shillong 793 103, IN
2 Central Silk Board, Ministry of Textiles, B.T.M. Layout, Madivala, Bengaluru 560 068, IN
1 North Eastern Space Applications Centre, Department of Space, Shillong 793 103, IN
2 Central Silk Board, Ministry of Textiles, B.T.M. Layout, Madivala, Bengaluru 560 068, IN
Source
Current Science, Vol 111, No 8 (2016), Pagination: 1312-1318Abstract
Potential areas for expansion of sericulture in 108 selected districts covering 24 states in the country were mapped using remote sensing, GIS and GPS tools. Special emphasis was given to northeastern (NE) region, where 41 districts out of a total of 108 districts were selected. Potential area identification for sericulture development was based on land evaluation, water resources and climatic requirements for growing silkworm food plants as well as rearing silkworms. Among NE states, Mizoram has maximum highly suitable area (4.7% of total geographical area) followed by Meghalaya (2.8%), that can be brought under mulberry sericulture. Among non-traditional sericulture states, Himachal Pradesh has the highest suitable area (0.9% highly suitable and 6.2% moderately suitable areas) in the selected districts. Among the five traditional sericulture states, Tamil Nadu has the highest area under highly suitable category, which is about 4% of the total geographical area in the selected districts. To provide information on sericulture and spatial information on potential areas for the selected 108 districts, a geoportal titled 'Sericulture Information Linkages and Knowledge System' (SILKS) was conceptualized and developed using open source GIS, and put in the public domain (http://silks.csb.gov.in). Within three years, the portal could make a significant impact in the country particularly in NE states and a number of sericulture expansion activities have been taken up based on the study.Keywords
Geoportal, Geospatial Tools, Open Source GIS, Sericulture, Web Technology.References
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- CSB, Manual of Satellite Remote Sensing Applications for Sericulture Development, Central Silk Board, Bangalore, 1994.
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- FAO, Manual of Sericulture, United Nations, Rome, Italy, 1990.
- Patel, N. R., Mandal, U. K. and Pande, L. M., Agro-ecological zoning system. A remote sensing and GIS perspective. J. Agrometeorol., 2000, 2(1), 1–13.
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- Rapid Assessment of Boro Paddy Infestation by Brown Planthopper in Morigaon District, Assam, India Using Unmanned Aerial Vehicle
Abstract Views :336 |
PDF Views:138
Authors
Affiliations
1 North Eastern Space Applications Centre, Department of Space, Government of India, Umiam 793 103, IN
1 North Eastern Space Applications Centre, Department of Space, Government of India, Umiam 793 103, IN
Source
Current Science, Vol 111, No 10 (2016), Pagination: 1604-1606Abstract
In April 2016, farmers from Morigaon and Nagaon districts of Assam, India encountered severe pest infestation in their boro paddy (summer paddy) areas, which was unusual. Morigaon district with an area of 1550 sq. km having a population of about 9.6 lakhs (as of 2011), was the worst affected with four out of the five revenue circles, viz. Mayong, Bhuragaon, Laharighat, Morigaon and Mikirbheta being affected. Investigations by the District Agricultural Department and Regional Agricultural Research Station, Nagaon confirmed it to be infestation by brown planthopper (BPH), Nilaparvata lugens (Stal). Planthoppers are a problem in rainfed and irrigated wetland environments.References
- Preap, V., Zalucki, M. P. and Jahn, G. C., Cambodian J. Agric., 2006, 7(1), 17–25.
- Holt, J., Chancellor, T. C. B., Reynolds, D. R. and Tiongco, E., Crop Prot., 1996, 14(4), 359–368.
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- Nageswara Rao, P. P. and Rao, V. R., Proceedings of the third Asian Conference of Remote Sensing, Dhaka, Bangladesh, 4–7 December 1982, pp. 1–12.
- Ranganath, B. K., Pradeep, N., Manjula V. B., Gowda, B., Ranjana, M. D., Shettgar, D. and Nageswara Rao, P. P., J. Indian Soc. Remote Sensing, 2004, 32(10), 49–58.
- Everaerts, J., The Int. Arch. Photogramm., Remote Sensing Spatial Inf. Sci., 2008, XXXVII(part B1), 1187–1191.
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- Recognizing the Rapid Expansion of Rubber Plantation – A Threat to Native Forest in Parts of Northeast India
Abstract Views :478 |
PDF Views:189
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.References
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- Mertz, O., Padoch, C., Fox, J., Cramb, R. A., Leisz, S. J. and Lam, N. T., Swidden change in Southeast Asia: understanding causes and consequences. Hum. Ecol., 2009, 37, 259–264.
- Leisz, S. J., Yasuyuki, K., Fox, J., Masayuki, Y. and Rambo, T. A., Land use changes in the uplands of Southeast Asia: proximate and distant causes. J. Southeast Asian Stud., 2009, 47(3), 237–243.
- Thongmanivong, S., Fujita, Y., Phanvilay, K. and Vongvisouk, T., Agrarian land use transformation in Northern Laos: from swidden to rubber. J. Southeast Asian Stud., 2009, 47(3), 330–347.
- Shrestha, A. B. and Devkota, L. P., Climate Change in the Eastern Himalayas: Observed Trends and Model Projections Climate Change Impact and Vulnerability in the Eastern Himalayas – Technical Report 1, Kathmandu, ICIMOD, 2010.
- Li, H., Ma Y., Aide, T. M. and Liu, W., Past, present and future land-use in Xishuangbanna, China and the implications for carbon dynamics. For. Ecol. Manage, 2008, 255, 16–24.
- Hu, H., Liu, W. and Cao, M., Impact of land use and land cover changes on ecosystem services in Menglun, Xishuangbanna, Southwest China. Environ. Monit. Assess., 2008, 46(1–3), 147–156.
- Guardiola-Claramonte, M., Troch, P. A., Ziegler, A. D., Giambelluca, T. W., Durcik, M. and Vogler, J. B., Hydrologic effects of the expansion of rubber (Heveabrasiliensis) in a tropical catchment. Ecohydrology, 2010, 306–314.
- Mann, C. C., Addicted to rubber. Science, 2009, 325, 565–566.
- Ziegler, A. D., Fox, J. M. and Xu, J., The rubber juggernaut. Science, 2009, 324, 1024–1025.
- Hunter Jr., M. L. (ed.), Maintaining Biodiversity in Forest Ecosystems, Cambridge University Press, Cambridge, 1999, p. 716.
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- Thomas, E. W., Dolman, P. M. and Edwards, D. P., Increasing demand for natural rubber necessitates a robust sustainability initiative to mitigate impacts on tropical biodiversity. Conserv. Lett., 2015, 8(4), 230–241.
- Ahrends, A., Hollingsworth, P. M., Ziegler, A. D., Fox, J. M., Chen, H., Su, Y. and Xu, J., Current trends of rubber plantation expansion may threaten biodiversity and livelihoods. Glob. Environ. Change, 2015, 34, 48–58.
- International Tropical Timber Organization (ITTO), Encouraging Industrial Forest Plantations in the Tropics: Report of a Global Study, International Tropical Timber Organization, Yokohama, Japan, 2009.
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- Chen, H., Yi, Z.-F., Schmidt-Vogt, D., Ahrends, A., Beckschäfer, P. and Kleinn, C., Pushing the limits: the pattern and dynamics of rubber monoculture expansion in Xishuangbanna, SW China. PLoS ONE, 2016, 11(2), e0150062; doi:10.1371/journal.pone.0150062.
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- DeBlécourt, M., Brumme, R., Xu, J., Corre, M. D. and Veldkamp, E., Soil carbon stocks decrease following conversion of secondary forests to rubber (Hevea brasiliensis) plantations. PLoS ONE, 2013, 8, e69357.
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- Towards Generation of Effective 3D Surface Models from UAV Imagery Using Open Source Tools
Abstract Views :440 |
PDF Views:114
Authors
P. S. Singh
1,
Mayuri Sharma
2,
Victor Saikhom
1,
Dibyajyoti Chutia
1,
Chirag Gupta
1,
Avinash Chouhan
1,
P. L. N. Raju
1
Affiliations
1 North Eastern Space Applications Centre, Department of Space, Government of India, Umiam 793 103, IN
2 Department of Computer Science, Assam Don Bosco University, Guwahati 781 017, IN
1 North Eastern Space Applications Centre, Department of Space, Government of India, Umiam 793 103, IN
2 Department of Computer Science, Assam Don Bosco University, Guwahati 781 017, IN
Source
Current Science, Vol 114, No 02 (2018), Pagination: 314-321Abstract
There has been increasing popularity in large scale mapping for deriving 3D surface and elevation models of earth and building structures. The techniques of computer vision comprising feature detections and matching and photogrammetry play an important role in deriving near accurate 3D reconstruction of scenes from 2D images. Since the images captured by the unmanned aerial vehicle (UAVs) are of high resolution, there is need for more sophisticated processing and analysis of the imagery to generate 3D models and other useful imagery products. The open source softwares are excellent tools for research and can be modified or changed to suit our model, as specific or combinations of algorithms behave differently based on the nature of UAV image scene to be processed. Though many algorithms are available for performing feature extractions from images, few studies have been carried out to identify suitable detector algorithms to be used based on the nature of image or scene that the UAV captures. An attempt has been made to understand and analyse the suitability of feature detection and descriptor algorithms for different scene types. This article also describes the popular technique called structure from motion process pipeline for sequential processing of UAV images with high overlapping, which involves the estimation of 3D point clouds from the keypoint correspondences. The relative accuracy of the 3D point cloud derived from our approach is comparable with similar output from other state-of-the-art UAV processing systems and is found to match with high precision.Keywords
3D Reconstruction, Open Source, Point Clouds, Remote Sensing, Structure from Motion, Unmanned Aerial Vehicle.References
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- Changchang, W., Towards Linear-time Incremental Structure from Motion, 2013 International Conference on 3D Vision.
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- Mancini, F. et al., Using unmanned aerial vehicles (UAV) for high-resolution reconstruction of topography: the structure from motion approach on coastal environments. Remote Sensing, 2013, 5, 6880–6898; doi:10.3390/rs5126880.
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- Total Electron Content and Epicentral Distance of 2015 Mw 7.8 Nepal Earthquake Revealed by Continuous Observations Data
Abstract Views :629 |
PDF Views:116
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.References
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- Expansion of Boro Rice in Meghalaya using Space Technology
Abstract Views :322 |
PDF Views:107
Authors
Affiliations
1 North Eastern Space Applications Centre, Department of Space, Govt of India, Umiam 793 103, IN
1 North Eastern Space Applications Centre, Department of Space, Govt of India, Umiam 793 103, IN
Source
Current Science, Vol 115, No 10 (2018), Pagination: 1865-1870Abstract
Suitable areas for boro rice expansion in Meghalaya were identified using geospatial technology based on land evaluation using information on soil, slope, elevation, rainfall and temperature. The study showed that 635 ha area is highly suitable followed by 581.74 sq. km and 219.07 sq. km area is marginally and moderately suitable respectively. The suitable areas are distributed in 20 blocks of 8 districts. More than 50% of suitable areas are distributed in West Garo hills. The highest suitable areas are found in Selsella and Dadenggre block. The findings of this study are being used by the user department for expanding boro rice cultivation in the state.Keywords
Boro Rice, Geospatial Tools, Meghalaya, Site Suitability.References
- http://www.megagriculture.gov.in
- http://www.meghalaya.gov.in
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- Forest Biometric Parameter Extraction using Unmanned Aerial Vehicle to Aid in Forest Inventory Data Collection
Abstract Views :392 |
PDF Views:119
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.References
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- Comparison of Parametric and Non-Parametric Methods for Chlorophyll Estimation based on High-Resolution UAV Imagery
Abstract Views :397 |
PDF Views:116
Authors
Gaurav Singhal
1,
Babankumar Bansod
2,
Lini Mathew
3,
Jonali Goswami
4,
B. U. Choudhury
5,
P. L. N. Raju
4
Affiliations
1 CSIR-Central Scientific Instruments Organization, Chandigarh 160 030, IN
2 Academy of Scientific and Innovative Research, Ghaziabad 201 002, IN
3 National Institute of Technical Teachers, Training and Research, Chandigarh 160 019, IN
4 North East Space Application Centre, Barapani 793 103, IN
5 ICAR Research Complex for NEH Region, Umiam 793 103, IN
1 CSIR-Central Scientific Instruments Organization, Chandigarh 160 030, IN
2 Academy of Scientific and Innovative Research, Ghaziabad 201 002, IN
3 National Institute of Technical Teachers, Training and Research, Chandigarh 160 019, IN
4 North East Space Application Centre, Barapani 793 103, IN
5 ICAR Research Complex for NEH Region, Umiam 793 103, IN
Source
Current Science, Vol 117, No 11 (2019), Pagination: 1874-1879Abstract
The present study provides a systematic comparison of parametric and non-parametric retrieval methods using high-resolution data provided by the unmanned aerial vehicle (UAV). We used turmeric crop reflectance data to evaluate the vegetation index (VI)-based parametric methods and compared them with linear and nonlinear non-parametric methods to build a rigorous LCC estimation model. The study demonstrates that the best-performing VI was the normalized green red difference index (GNRDI), with R2 = 0.68, RMSE = 0.13 and high processing speed of 0.08 s. With regard to non-parametric methods, almost all methods outperformed their parametric counterparts. Particularly, methods such as random forest (RF) and kernel ridge regression (KRR) showed the best performance characterized by R2 > 0.72 and RMSE ≤ 0.12 mg/g of fresh leaf weight. These nonparametric methods possessed the benefit of total spectral information utilization and enabled robust, non-linear relationship between the predictor and target variables, but computational complexity is a major drawback.Keywords
Chlorophyll, Machine Learning, Unmanned Aerial Vehicle, Vegetation Index.References
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- Site-suitability Analysis for Turmeric in Jaintia Hills of Meghalaya, India, using Analytical Hierarchical Process and Weighted Overlay Analysis:A Comparative Approach
Abstract Views :297 |
PDF Views:127
Authors
Affiliations
1 North Eastern Space Applications Centre, Umiam 793 103, IN
1 North Eastern Space Applications Centre, Umiam 793 103, IN
Source
Current Science, Vol 118, No 8 (2020), Pagination: 1246-1254Abstract
India is the largest producer, consumer and exporter of turmeric (Curcuma longa L.). The Lakadong variety of turmeric is endemic to Jaintia Hills of Meghalaya, India. It is considered as the best quality turmeric containing 7.5% curcumin, which is about three times higher than the other varieties (2–3%). This study identifies potential sites for turmeric cultivation in Jaintia Hills using geospatial techniques, viz. analytical hierarchical process (AHP) and weighted overlay analysis (WOA). WOA identified a total of 162,263.70 ha suitable for the expansion of Lakadong variety of turmeric in Jaintia Hills, of which 18% was highly suitable, 31% moderately suitable and 32% was marginally suitable. In the case of AHP, 21% area was found to be highly suitable, 25% moderately suitable and 45% marginally suitable.Keywords
Analytical Hierarchical Process, Site Suitability Analysis, Turmeric, Weighted Overlay Analysis.References
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- Development of a Muga Disease Early Warning System – A Mobile-Based Service for Seri Farmers
Abstract Views :328 |
PDF Views:116
Authors
J. Goswami
1,
D. K. Gogoi
2,
N. Rasid
1,
B. K. Handique
1,
G. Subrahmanyam
2,
P. P. Bora
2,
R. Das
2,
P. L. N. Raju
1
Affiliations
1 North Eastern Space Applications Centre, Department of Space, Umiam 793 103, IN
2 Central Muga Eri Research and Training Institute, Central Silk Board, Lahdoigarh, Jorhat 785 700, IN
1 North Eastern Space Applications Centre, Department of Space, Umiam 793 103, IN
2 Central Muga Eri Research and Training Institute, Central Silk Board, Lahdoigarh, Jorhat 785 700, IN
Source
Current Science, Vol 121, No 10 (2021), Pagination: 1328-1334Abstract
Flacherie is a major bacterial disease causing >40% loss during Muga summer crops. For finding the ischolar_main causes of the diseases, relationships were established between rearing and production data corresponding to land use/land cover, land surface temperature and meteorological parameters. Adverse affects were found in farms associated with anthropogenic activities, in contrast to forest cover which shows a negative trend. Muga disease early warning system, a mobile-based application and dashboard has been developed to predict rate of flacherie infestation at least 5–10 days in advance, for proper precautionary measures by the farmers to avoid disease outbreak and crop lossKeywords
Crop Loss, Early Warning System, Flacherie Disease, Mobile-Based Service, Muga Silkworm, Remote Sensing. Muga Silkworm.References
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