Refine your search
Collections
Co-Authors
Journals
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
Bakimchandra, Oinam
- Unprecedented Drought in North East India Compared to Western India
Abstract Views :311 |
PDF Views:81
Authors
Affiliations
1 Department of Civil Engineering, Shiv Nadar University, Greater Noida 201 314, IN
2 Department of Civil Engineering, National Institute of Technology, Manipur, Imphal 795 001, IN
1 Department of Civil Engineering, Shiv Nadar University, Greater Noida 201 314, IN
2 Department of Civil Engineering, National Institute of Technology, Manipur, Imphal 795 001, IN
Source
Current Science, Vol 109, No 11 (2015), Pagination: 2121-2126Abstract
The rainfall distribution over Western and North East India during the southwest (SW) monsoon season is geographically distinct with the heaviest seasonal rainfall occurs over the North Eastern Region (NER), while the lowest rainfall occurs over the Western region (Saurashtra and Kutch in Gujarat, and also in Rajasthan). Gujarat is located in arid to semiarid region and has more drought-prone areas. In contrast, Assam and Meghalaya have humid climate and occurrence of drought is unusual. Here, we analyse the percentage departure of rainfall for nearly two decades (1997-2014) along with crop statistics. Our results indicate that the SW monsoon rainfall in the NER has gradually dropped in recent years compared to the 1980s and 1990s. As a result, these regions have witnessed frequent unprecedented drought than Western India. In NER, probability of drought occurrence was 54%, and it is 27% for Western India in the recent decade (2000-2014). The frequent drought has caused adverse agricultural impacts and our results show a significant negative rice production anomaly during drought years 2005-06 and 2009 in Assam. Drought impacts were also reported from other states in NER during 2010-11 and 2013. Drought associated with El Niño was not so strong; however, increasing temperature and increased monsoon season rainfall variability have an impact on global climate change. This may cause warming-induced drought leading to adverse impact on agriculture and food security in the NER.Keywords
Crop Production, Meteorological and Agriculture Drought, Monsoon Season, Rainfall Departure.Full Text
References
- Davis, M., Late Victorian Holocausts: El Nino Famines and the Making of the Third World, Verso, London, 2001, p. 9.
- Appadurai A., How moral is South Asia's economy? – a review article. J. Asian Stud., 1984, 43, 481–497.
- Thenkabail, P. S., Gamage, N. and Smakhin, V., The use of remote sensing data for drought assessment and monitoring in south west Asia. IWMI Research Report 85, IWMI, Colombo, 2004, p. 25.
- EM-DAT: The OFDA/CRED International Disaster Database, Universite catholique de Louvain, Brussels, Belgium; www.emdat.be
- Annual Report 2011–12, North Eastern Space Applications Centre, Meghalaya, Department of Space, Government of India.
- Kumar, M. N., Murthy, C. S., Sesha Sai, M. V. R. and Roy, P. S., Spatiotemporal analysis of meteorological drought variability in the Indian region using standardized precipitation index. Meteorol. Apps., 2012, 19, 256–264.
- Patel, N. R., Parida, B. R., Venus, V., Saha, S. K. and Dadhwal, V. K., Analysis of agricultural drought using vegetation temperature condition index (VTCI) from Terra/MODIS satellite data. Environ. Monitor. Assess, 2012, 184, 7153–7163.
- Park, S., Feddema, J. J. and Egberts, S. L., MODIS land surface temperature composite data and their relationships with climatic water budget factors in the central Great Plains. Int. J. Remote Sensing, 2004, 26, 1127–1144.
- Jackson, R. D., Idso, S. B., Beginato, R. J. and Pinter, P. J., Canopy temperature as a crop water stress indicator. Water Resour. Res., 1981, 17, 1133–1138.
- Moran, M. S., Clarke, T. R., Inoue, U. and Vidal, A., Estimating crop water deficit using the relation between surface air temperature and spectral vegetation index. Remote Sensing Environ., 1994, 49, 246–263.
- Sandholt, I., Rasmussen, K. and Anderson, J., A simple interpretation of the surface temperature/vegetation index space for assessment of the surface moisture status. Remote Sensing Environ., 2002, 79, 213–224.
- Parida, B. R. and Oinam, B., Drought monitoring in India and the Philippines with satellite remote sensing measurements. EARSeL eProc., 2008, 7, 81–91.
- Palmer, W. C., Keeping track of crop moisture conditions, nationwide: The new Crop Moisture Index. Weatherwise, 1968, 21, 156–161.
- Shewale, M. P. and Kumar, S., Climatological features of drought incidences in India. Meteorological Monograph (Climatology 21/2005), National Climate Centre, India Meteorological Department.
- Pant, G. B. and Parthasarathy, B., Some aspects of an association between the southern oscillation and Indian summer monsoon. Arch. Meteorol. Geophys. Bioklimatol., Ser. B, 1981, 29, 245–251.
- Krishna Kumar, K., Kleeman, R., Cane, M. A. and Rajagopalan, B., Epochal changes in Indian monsoon–ENSO precursors. Geophys. Res. Lett., 1999, 26, 75–78.
- Krishna Kumar, K., Rajagopalan, B. and Cane, M. A., On the weakening relationship between the Indian monsoon and ENSO. Science, 1999, 25, 2156–2159.
- Anup, D. et al., Climate change in Northeast India: recent facts and events – worry for agricultural management. In ISPRS Archives XXXVIII-8/W3 Workshop Proceedings: Impact of Climate Change on Agriculture, 2009.
- Chaturvedi, R. K., Joshi, J., Jayaraman, M., Bala, G. and Ravindranath, N. H., Multi-model climate change projections for India under representative concentration pathways. Curr. Sci., 2012, 103, 791–802.
- Parry, M. L. et al. (eds), Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK, 200-7, p. 976.
- A Geospatial Approach to Assess Health Coverage and Scaling-Up of Healthcare Facilities
Abstract Views :359 |
PDF Views:81
Authors
Affiliations
1 Department of Civil Engineering, National Institute of Technology, Manipur 795 004, IN
2 Department of Community Medicine, Jawaharlal Nehru Institute of Medical Sciences, Manipur 795 004, IN
1 Department of Civil Engineering, National Institute of Technology, Manipur 795 004, IN
2 Department of Community Medicine, Jawaharlal Nehru Institute of Medical Sciences, Manipur 795 004, IN
Source
Current Science, Vol 118, No 5 (2020), Pagination: 728-736Abstract
The UN Sustainable Development Goals seek univer-sal health coverage and accessibility to quality healthcare services by 2030 for creating a healthier and equitable world. This study highlights the role of geospatial model in assessing the geographic coverage of healthcare facilities in Manipur, India, and the need for scaling-up of the existing health centres in the region. A geodatabase on the existing healthcare facilities has been developed in the study. Mapping of health centre facilities, coverage analysis and scaling-up assessment are carried out using ArcGIS and AccessMod. The model results show that locations of the existing healthcare services are significantly spa-tially clustered amongst themselves, with an observed mean distance of 2.62 km. Scaling-up analysis consid-ering the projected population of 2020 indicates the requirement of 66 new health facility centres, mostly in the hill districts of Manipur. This study indicates the need for scaling-up healthcare facilities that can cover the entire population in each district of Mani-pur. It also indirectly addresses one of the fundamen-tal aspects of the healthcare system, i.e. equity in the distribution of healthcare facilities and their accessi-bility to all sections of the society.Keywords
Geospatial Model, Health Care Facilities, Scaling-up Analysis, Universal Health Coverage.Full Text
References
- Goddard, M. and Smith, P., Equity of access to healthcare ser-vices: theory and evidence from the UK. Soc. Sci. Med., 2001, 53, 1149–1162; doi:10.1016/S0277-9536(00)00415-9.
- Oliver, A. and Mossialos, E., Equity of access to healthcare. Out-lining the foundations for action. J. Epidemiol. Commun. Health 2004, 58, 655–658.
- Anita, N., India’s vision for health: perspectives from the XIIth five-year plan (2012–2017). Int. J. Med. Public Health, 2014, 4(1), 46–50; doi:10.4103/2230-8598.127124.
- Mansour, S., Spatial analysis of public health facilities in Riyadh Governorate, Saudi Arabia: a GIS-based study to assess geograph-ic variations of service provision and accessibility. Geospatial Inf. Sci., 2016, 19(1), 26–38; doi:10.1080/10095020.2016.1151205.
- Perry, B. and Gesler, W., Physical access to primary health care in Andean Bolivia. Soc. Sci. Med., 2000, 50(9), 1177–1188; doi:10.1016/S0277-9536(99)00364-0.
- Gatrell, A. and Senior, M., Health and health care applications. In Geographical Information Systems: Principles and Applications (eds Longley, P. A. et al.), Longman, London, 1999, 2nd edn.
- McLafferty, S. L., GIS and health care. Annu. Rev. Public Health, 2003, 24, 25–42.
- Luo, W. and Wang, F., Measures of spatial accessibility to healthcare in a GIS environment: synthesis and a case study in Chicago region. Environ. Plann. B, 2003; 3, 865–884.
- Pui-Jen, T., Men-Lung, L., Chien-Min, C. and Cheng-Hwang, P., Spatial autocorrelation analysis of health case hotspots in Taiwan in 2006. BMC Public Health, 2009, 9, 464.
- Al-Ahmadi, K. and Al-Zahrani, A., Spatial autocorrelation of can-cer incidence in Saudi Arabia. Int. J. Environ. Res. Public Health, 2013, 10, 7207–7228.
- Bejleri, I., Steiner, R., Neff, D., Harman, J., Lutz, B. and Yoon, S., Informing planning to address healthcare disparities: assessing spatial accessibility to healthcare using GIS analysis. In CUPUM 2015 – 14th International Conference on Computers in Urban Planning and Urban Management, MIT, Cambridge, Massachu-setts, USA, 2015.
- Lee, K. S. and Moon, K. J., Hospital distribution in a metropolitan city: assessment by a geographical information system grid model-ling approach. Geospatial Health, 2014, 8, 537–544.
- Murad, A. A., Using geographical information systems for defin-ing the accessibility to healthcare facilities in Jeddah City, Saudi Arabia. Geospatial Health, 2014, 8(3), S661–S669.
- Ni, J., Qian, T., Xi, C., Rui, Y. and Wang, J., Spatial distribution characteristics of healthcare facilities in Nanjing: network point pattern analysis and correlation analysis. Int. J. Environ. Res. Public Health, 2016; 13(8), 833; pmid:27548197.
- Ruiz, M. and Sharma, A., Application of GIS in public health in India: a literature-based review, analysis, and recommendations. Indian J. Public Health, 2016, 60, 51–58.
- Luis, A. D. A. and Cabral, P., Geographic accessibility to primary healthcare centers in Mozambique. Int. J. Equity Health, 2016, 15(1); doi:10.1186/s12939-016-0455-0.
- Environmental Systems Research Institute (ESRI), Geographic information systems and environmental health: incorporating ESRI technology and services. An ESRI White paper. 2011; http://www.esri.com/library/whitepapers/pdfs/gis_and_env_health.pdf
- ESRI, Modeling spatial relationships, 2018; https://pro.arcgis.com/en/pro-app/tool-reference/spatial-statistics/modeling-spatial-relationships.html.pdf
- Ray, N. and Ebener, S., AccessMod 3.0: computing geographic coverage and accessibility to healthcare services using anisotropic movement of patients. Int. J. Health Geogr., 2008, 7(1), 63.
- Ray, N., Ebener, S. and Moser, F., User Guide and Tutorial: Ac-cessMod 5.0 Supporting Universal Health Coverage by Modelling Physical Accessibility to Health Care, World Health Organization, Geneva, Switzerland, 2017; https://doc.accessmod.org/display/EN
- Government of Manipur (GoM), Approach paper on new land use policy/project of Manipur. Report by Planning Department, GoM, 2014; http://dcimanipur.gov.in/MSME/Approach%20Paper%20-on%20NLUP%20Manipur%202014.pdf
- State Health Society, State Programme Implementation Plan (SPIP 2010–11), Manipur under National Rural Health Mission (NRHM), GoM, 2011; nrhmmanipur.org/wp-content/uploads/2011/01/PIP-2010-2011.pdf
- State Health Society, State Programme Implementation Plan (SPIP 2012–13) Manipur under NRHM, GoM, 2011; nrhmmani-pur.org/wp-content/uploads/2011/01/SPIP-2012-133.pdf.2011
- NRHM, Rural health statistics in India. 2012; National Rural Health Mission, Government of India; https://nhm.gov.in/images/pdf/publication/RHS-2012.pdf
- Center for International Earth Science Information Network – CIESIN – Columbia University, Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 10. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC), 2017; https://doi.org/10.7927/H4DZ068D
- Planning Commission, High level expert group report on univer-sal health coverage for India. Working Paper id: 4646, eSocial- Sciences; 2011; http://planningcommission.nic.in/reports/genrep/rep_uhc0812.pdf