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Co-Authors
- S. Sudhakar
- P. T. Das
- J. Goswami
- C. Goswami
- P. S. Singh
- C. J. Prabhakar
- C. M. Bajpeyi
- P. L. N. Raju
- Jonali Goswami
- Abdul Qadir
- Chirag Gupta
- Pratibha T. Das
- Ashu Negi
- Tapan Adhikari
- Chandan Goswami
- D. K. Gogoi
- N. Rasid
- G. Subrahmanyam
- P. P. Bora
- R. Das
- P. Jena
- F. Dutta
- D. K. Jha
- S. P. Aggarwal
- Bullo Yami
- N. J. Singh
- Sanjay Swami
Journals
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Handique, B. K.
- Timber Volume Estimation by Double Sampling Using High Resolution Satellite Data
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Authors
Affiliations
1 North Eastern Space Applications Centre Dept. of Space, Umiam 793103 Meghalaya, IN
1 North Eastern Space Applications Centre Dept. of Space, Umiam 793103 Meghalaya, IN
Source
Indian Forester, Vol 140, No 2 (2014), Pagination: 154-161Abstract
Double sampling or two-phase sampling design offers a variety of possibilities for effective use of auxiliary information such as those from high resolution remote sensing data. This study has been made to examine the possibilities of different forms of auxiliary information derived from remote sensing data in double sampling design and suggest an appropriate estimator for forest timber volume estimation in the context of preparing forest working plan inputs. A regression-cum-ratio estimator has been derived for double sampling using information on two auxiliary variables derived from high resolution satellite data. The estimator has been adopted for forest timber volume estimation utilizing tree crown diameter (x) and NDVI (z) as auxiliary variables. Relationship between timber volume (y) and 2 2 average crown diameter (x) has a higher value of R (0.733) as compared to that with NDVI (z), where R =0.528. It is shown that combination of these two auxiliary variables under doubling sampling design has significantly reduce the standard error of the timber volume estimate (CV of SE=11.49%) against estimates brought out by common sampling design (31% for simple random sampling, 22.34% for systematic sampling and 18.69% for stratified random sampling). This indicates that the estimator can be employed in a variety of conditions where there is good correlation of satellite derived auxiliary information with sample based ground measurements and when the cost of ground measurements is relatively high.Keywords
Double Sampling, Regression-cum-ratio Estimator, High Resolution Satellite Data, Timber Volume Estimation, Mean Square Error.References
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- FSI, (1996). Volume Equations for Forests of India, Nepal and Bhutan, Forest survey of India, Dehradun.
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- Gunawardena, A. R., Nissanka, S.P. and Dayawansa, N.D.K.( 2008). Development of Merchantable Timber Volume Estimation of Pinus caribaea Plantations using Multi-Spectral Satellite Images, Engineer, XXXXI (5), 68-73.
- Hidiroglou, M.A. and Sarndal, C.E. (1998). Use of auxiliary variable for two phase sampling, Survey Methodology, 24(1):11-20.
- Jensen, J.R. (1999). Introductory Digital Image processing, a Remotesensing Perspective, Prentice Hall, New Jersey.
- Jhajj, H.S. and Walia, G.S. (2011). A generalized Difference-cum-Ratio type estimator for the population mean in double sampling, Proceedings of the Statistics 2011 Canada: 5th Canadian Conference in Applied Statistics, July 1-4, 2011, Concordia University, Montreal, Canada.
- Johnson, E. W. (2000). Forest sampling desk reference, CRC Press, New York.
- Kadilar, C and Cingi, H. (2003). A study on the chain ratio-type estimator, Hacettepe Journal of Mathematics and Statistics. 32: 105-108.
- Katsch, C.H.R. and Van Laar, A. (2002). The estimation of the growing stock of eucalypt plantation forests, based on spectral signatures of satellite imagery, in South Africa. South African Forestry Journal, 194: 65-70.
- Khoshnevisan, M., Singh, H.P., Singh, S. and Smarandache, F. (2002). A general class of estimators of population median using two auxiliary variables in double sampling, In : Randomness and optimal estimation in data sampling ( 2nd edition), American Research Press, 26- 43.
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- Expansion of Sericulture in India Using Geospatial Tools and Web Technology
Abstract Views :245 |
PDF Views:95
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
- Rama Rao, N., Protection for Indian Sericulture. Curr. Sci., 1938, 7(6), 263–266.
- Navalgund, R. R., Parihar, J. S., Ajai and Nageswara Rao, P. P., Crop inventory using remotely sensed data. Curr. Sci., 1991, 61(3&4), 162–171.
- Nageswara Rao, P. P., Ranganath, B. K. and Chandrashekhar, M. G., Remote sensing applications in sericulture. Indian Silk, 1991, 30, 7–15.
- CSB, Manual of Satellite Remote Sensing Applications for Sericulture Development, Central Silk Board, Bangalore, 1994.
- Sys, C., Land Evaluation: Part I, II& III. 1985, State University Ghent Publication, Belgium.
- Sys, C., Ranst, V., Debaveye, J. and Beernaert, F., Land evaluation Part III, crop requirements. Agric. Pub. 1993, No. 7, ITC, Ghent.
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- NRSC, Wasteland Atlas of India, National Remote Sensing Agency, Hyderabad, 2011, pp. 4–14.
- 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 :248 |
PDF Views:91
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.
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- Expansion of Boro Rice in Meghalaya using Space Technology
Abstract Views :235 |
PDF Views:82
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
- FAO, A framework for land evaluation. Soil Bulletin, Food and Agriculture Organisation, United Nations, Rome, Italy, 1976, no. 32.
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- Bandyopadhyay, S., Jaiswal, R. K., Hegde, V. S. and Jayaraman, V., Assessment of land suitability potentials for agriculture using a remote sensing and GIS based approach. Int. J. Remote Sensing, 2009, 30(4), 879–895.
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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 :173 |
PDF Views:85
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
- Moorthi, C. and Kathiresan, K., Curcumin–piperine/curcumin– quercetin/curcumin–silibinin dualdrug-loaded nanoparticulate combination therapy: a novel approach to target and treat multi-drug-resistant cancers. J. Med. Hypotheses Ideas, 2013, 7(1), 15–20.
- Mandal, D. K., Khule, S., Mandal, C., Lal, S., Hajare, N. and Prasad, J., Soil suitability evaluation for turmeric in Wardha district of Maharashtra. Agropedology, 2008, 18(2), 83–92.
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- Deshmukh, N. A. Jha, A. K., Verma, V. K., Rymbai, H., Deka, B. C. and Ngachan, S. V., Megha Turmeric-1: popularization through farmers’ participatory mode in Meghalaya: a success story, ICAR Research Complex for NEH Region, Meghalaya, 2017.
- Saaty, T. L. and Vargas, G. L., Models Methods, Concepts and Applications of the Analytical Heirarchy Process, Kluwer, Boston, USA, 2001.
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- Development of a Muga Disease Early Warning System – A Mobile-Based Service for Seri Farmers
Abstract Views :183 |
PDF Views:79
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
- Tikader, A., Vijayan, K. and Saratchandra, B., Muga silkworm, Antheraea assamensis (Lepidoptera: Saturniidae) – an overview of distribution, biology and breeding. Eur. J. Entomol., 2013, 110(2).
- Kumar, R. and Rajkhowa, G., Muga silkworm, Antheraea assamensis (Insecta: Lepidoptera: Saturniidae): rearing and insect. Hartmann and Weipert. Proceedings: Biodiversität und Naturausstattung im Himalaya IV.–Erfurt, Germany, 2012, pp. 187–190.
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- Madhusudhan, K. N. et al., Impact of varying different abiotic factors on the survivability of tasar silkworm in outdoor rearing fields. J. Entomol. Zool. Stud., 2017, 5(6), 957–963.
- Chakravorty, C., Das, R., Neog, R., Das, K and Sahu, M., A Diagnostic Manual for Diseases and Pests of Muga Silkworms and their Host Plants, Central Muga Eri Research and Training Institute, CSB Publication, 2007, 1st edn.
- Subrahmanyam, G. et al., Isolation and molecular identification of microsporidian pathogen causing nosemosis in Muga silkworm, Antheraea assamensis Helfer (Lepidoptera: Saturniidae). Indian J. Microbiol., 2019, 59(4), 525–529.
- Ueda, S., Kimura, R. and Suzuki, K., Studies on the growth of the silkworm, Bombyx mori L., 4: Mutual relationships between the growth in the fifth instar larvae and the productivity of silk substance. Bull. Sericult. Exp. Station, 1975.
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- Handique, B. K. et al., Expansion of sericulture in India using geospatial tools and web technology. Curr. Sci., 2016, 111(8), 1312–1318.
- National Remote Sensing Agency, Manual of National Land Use/Land Cover Mapping using Multi-Temporal Satellite Data, Hyderabad, 2006.
- Malik, B., The problem of shifting cultivation in the Garo Hills of North-East India, 1860–1970. Conserv. Soc., 2003, 287–315.
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- Tajima, Y. and Ohnuma, A., Preliminary experiments on the breeding procedure for synthesizing a high temperature resistant commercial strain of the silkworm, Bombyx mori. Rep. Silk Sci. Res. Inst. (Jpn), 1995, 1–16.
- Space technology support for development of agriculture in the North Eastern Region of India – scope and challenges
Abstract Views :149 |
PDF Views:83
Authors
B. K. Handique
1,
C. Goswami
1,
P. T. Das
1,
J. Goswami
1,
P. Jena
1,
F. Dutta
1,
D. K. Jha
1,
S. P. Aggarwal
1
Affiliations
1 North Eastern Space Applications Centre, Umiam 793 103, India, IN
1 North Eastern Space Applications Centre, Umiam 793 103, India, IN
Source
Current Science, Vol 123, No 8 (2022), Pagination: 975-986Abstract
The North Eastern Region of India (NER) has tremendous scope for accelerating its growth in agriculture and allied areas through advanced data acquisition, interpretation and dissemination methods with geospatial technology. For several thematic applications, geospatial tools and techniques are being used to provide synoptic, cost-efficient and timely information for effective crop planning and monitoring in the region. A review of space applications in agriculture, horticulture, sericulture, land-use suitability, shifting cultivation, groundwater prospecting, soil resources management, etc. has been made, highlighting the scope and limitation of using these advanced technologies. Satellite remote sensing has several limitations in NER, viz. small and fragmented farmlands, persistent clouds during monsoon, mixed farming, steep hills, etc. Considering these facts, unmanned aerial vehicles (UAVs) are used as an alternative for satellite remote sensing applications in agriculture. The increased availability of very high resolution satellite and UAV data will offer opportunities for innovative solutions to fulfil specific user needs of agriculture and allied sectors in NERReferences
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1 College of Post Graduate Studies in Agricultural Sciences, Central Agricultural University, Imphal–Umroi Road, Umiam 793 103, IN
2 North Eastern Space Applications Centre, Department of Space, Government of India, Umiam 793 103, IN
1 College of Post Graduate Studies in Agricultural Sciences, Central Agricultural University, Imphal–Umroi Road, Umiam 793 103, IN
2 North Eastern Space Applications Centre, Department of Space, Government of India, Umiam 793 103, IN
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Current Science, Vol 124, No 12 (2023), Pagination: 1431-1444Abstract
The soil carbon sinking ability is dominantly controlled by local topographical settings, soil–crop management and traditional farming practices on which the food demand of the major population is dependent. The degradation of natural resources causing poor soil health is likely to strain the hilly and mountain ecosystem. This study aims to map soil organic carbon (SOC) of rice–fallow system under varying slopes and its changes during the past 20 years under traditional management practice using geospatial tools and techniques. Regression models of SOC were derived from remote sensing (RS)-based indices using multiple linear regression-stepwise (MLR-stepwise), partial least square regression (PLSR) and principal component analysis-regression (PCA-R). The MLR-stepwise model was found to be superior in performance with high R2 (0.87) and least RMSE (0.026) compared to PLSR (R2 = 0.71 and RMSE = 0.05) and PCA-R (R2 = 0.27 and RMSE = 0.11) models for SOC prediction.Keywords
Regression Models, Remote Sensing, Rice–Fallow System, Soil Organic Carbon, Spectral Indices.References
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