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AUC GEOGRAPHICA, Vol 59 No 1 (2024), 93–107
Agricultural land suitability analysis in Manipur, India using GIS and AHP
Letminthang Baite, Niranjan Bhattacharjee, Jimmi Debbarma, Anup Saikia
DOI: https://doi.org/10.14712/23361980.2024.6
published online: 22. 05. 2024
abstract
This article aims to identify potential sites for agricultural use in the state of Manipur of north east India by employing the analytic hierarchy process in a geographic information system environment in conjunction with the use of remote sensing and soil data. Within the analytic hierarchy process, each terrain variable underwent a pairwise comparison and criteria weights were assigned according to their relative importance. Eight variables were selected and used in land suitability analysis for agriculture. It was found that Manipur had 57% (12,660 km2) of its total geographical area suitable for agriculture. However, 8126 km2 (37%) and 1374 km2 (6%) of the total geographical area was currently and permanently unsuitable land respectively. The distribution of suitable land varied greatly, with highly, moderately and marginally suitable land covering only 8%, 16% and 33% respectively of the total geographical area. The highly suitable agricultural land is predominantly concentrated in the Imphal valley (70%), though 90% of moderately suitable and 96% of marginally suitable land also exist in the hills. The hilly areas constitute 96% and 97% respectively of currently unsuitable and permanently unsuitable land in the state. Suitable land comprises of land with low to medium altitude, gentle to moderate slopes, soil of fine or acceptable quality, and with minimal flood risk. Unsuitable lands tend to be diametrically opposite to these attributes with steep hill slopes. The nature of distribution of land suitability types influences the agricultural pattern in Manipur. Agriculture in the hill areas comprises mainly of shifting cultivation on hill slopes, whereas in the valley region it is irrigated and permanent. This analysis of Manipur has a wider applicability since the shifting cultivation-irrigated agriculture combination is similar to that which exists across much of the highlands of South East Asia.
keywords: agriculture; analytic hierarchy process; geographic information systems; land suitability, terrain; Manipur, India
references (62)
1. Akinci, H., Özalp, A. Y., Turgut, B. (2013): Agricultural land use suitability analysis using GIS and AHP technique. Computers and Electronics in Agriculture 97, 71-82. CrossRef
2. Akpoti, K., Kabo-bah, A. T., Zwart, S. J. (2019): Agricultural land suitability analysis: State-of-the-art and outlooks for integration of climate change analysis. Agricultural systems 173, 172-208. CrossRef
3. Allan, N. J. R. (1986): Accessibility and altitudinal zonation models of mountains. Mountain Research and Development 6(3), 185-194. CrossRef
4. Anusha, B. N., Babu, K. R., Kumar, B. P., Sree, P. P., Veeraswamy, G., Swarnapriya, C., Rajasekhar, M. (2023): Integrated studies for land suitability analysis towards sustainable agricultural development in semi-arid regions of AP, India. Geosystems and Geoenvironment 2(2): 100131. CrossRef
5. Bandyopadhyay, S., Jaiswal, R. K., Hegde, V. S., Jayaraman, V. (2009): Assessment of land suitability potentials for agriculture using a remote sensing and GIS based approach. International Journal of Remote Sensing 30(4), 879-895. CrossRef
6. Baruah, U. D., Robeson, S. M., Mili, N., Chand, P. (2021): Perceptions and adaptation behaviour of farmers to climate change in the upper Brahmaputra Valley, India. Environment, Development and Sustainability 23(10), 15529-15549. CrossRef
7. Beckett, P. H. T., Webster, R., McNeil, G. M., Mitchell, C. W. (1972): Terrain Evaluation by Means of a Data Bank. The Geographical Journal 138(4), 430-449. CrossRef
8. Bhaskar, B. P., Srinivas, S., Kumar, S. C. R., Ramamurthy, V., Maske, S., Sujatha, K, Rajendra, H. (2021): Visual signs of Biophysical indicators for assessing the status of degradation in drylands of Pulivendula tehsil, Kadapa district, Andhra Pradesh. NBSS publication No.1151, NBSS & LUP, Nagpur.
9. Bonan, G. (2015): Earth's Climate. In: Ecological climatology: concepts and applications. 3rd Ed. 73-100. Cambridge University Press. CrossRef
10. Boral, D., Moktan, S. (2022): Mapping the spatial distribution of the invasive Mexican Sunflower Tithonia diversifolia (Asteraceae) in South East Asia. Journal of Asia-Pacific Biodiversity 15(3), 425-434. CrossRef
11. Bozdağ, A., Yavuz, F., Günay, A. S. (2016): AHP and GIS based land suitability analysis for Cihanbeyli (Turkey) County. Environmental Earth Sciences 75: 813. CrossRef
12. Canco, I., Kruja, D., Iancu, T. (2021): AHP, a reliable method for quality decision making: A case study in business. Sustainability 13(24): 13932. CrossRef
13. Chen, J., Yang, S. T., Li, H. W., Zhang, B., Lv, J. R. (2013): Research on geographical environment unit division based on the method of natural breaks (Jenks). The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 40, 47-50. CrossRef
14. Choudhury, D., Sundriyal, R. C. (2003): Factors contributing to the marginalization of shifting cultivation in north-east India: Micro-scale issues. Outlook on Agriculture 32(1), 17-28. CrossRef
15. Devi, C. K., Das, P., Nath, M. Mishra, B. K. (2023): Attitude of Farm Women towards the Effects of Climate Change in Agriculture and Allied Activities: A Study in Imphal, East Districts of Manipur, India. International Journal of Environment and Climate Change 13(10), 3843-3849. CrossRef
16. Dikshit, K. R., Dikshit, J. K. (2014): Weather and Climate of North-East India. In: North-East India: Land, People and Economy. Advances in Asian Human-Environmental Research. Springer, Dordrecht. CrossRef
17. FAO. (1967): Soil Survey Interpretation and Its Use. FAO Soils Bulletin 8, 1-16. http://www.fao.org/docrep/018/64247e/64247e.pdf (accessed on 12 June 2023).
18. FAO. (1976): A framework for land evaluation. FAO Soils Bulletin 32, 36-47, https://www.fao.org/3/X5310E/X5310E00.htm (accessed on 08 June 2023).
19. FAO. (1985). Guidelines: Land Evaluation for Irrigated Agriculture. FAO Soils Bulletin 55, 45-46, https://www.fao.org/3/x5648e/x5648e07.htm#TopOfPage.
20. Feizizadeh, B., Blaschke, T. (2013): Land suitability analysis for Tabriz County, Iran: a multi-criteria evaluation approach using GIS. Journal of Environmental Planning and Management 56(1), 1-23. CrossRef
21. Florinsky, I. V. (2012): Influence of Topography on Soil Properties. In I. V. Florinsky (Ed.), Digital Terrain Analysis in Soil Science and Geology, 1st ed., 145-150. Academic Press. CrossRef
22. Ganguly, A., Oza, H., Padhya, V., Pandey, A., Chakra, S., Deshpande, R. D. (2023): Extreme local recycling of moisture via wetlands and forests in North-East Indian subcontinent: a Mini-Amazon. Scientific Reports 13: 521. CrossRef
23. Government of Manipur, GoM (2013): Manipur State Action Plan on Climate Change. Directorate of Environment, Government of Manipur. Climate Change and Vulnerability Assessment. Available online: https://moef.gov.in/wp-content/uploads/2017/09/Manipur.pdf (accessed on 25 July 2023).
24. Government of Manipur, GoM (2015): Economic Survey of Manipur 2016-17. Directorate of Economic and Statistics, Government of Manipur, 49-70.
25. Grose, C. J. (1999): Guidelines for the Classification of Agriculture Land in Tasmania (C. J. Grose (ed.); 2nd ed.). Department of Primary Industries, Water and Environment. Available online: https://nre.tas.gov.au/Documents/Land_Cap_Revised-handbook.pdf (accessed on 08 June 2023).
26. Geological Survey of India (GSI). (2011): Geology and Mineral Resources of Manipur, Mizoram, Nagaland and Tripura, Miscellaneous Publications 30(1). Available online: https://www.scribd.com/document/342438079/Geology-of-mani-mizo-naga-tripura-pdf (accessed on 08 June 2023).
27. GSI and NRSC (2012): National geomorphological and Lineament mapping on 1 : 50,000 scale.
28. Natural Resources Census Project. National Remote Sensing Centre, ISRO, Hyderabad. Available online: https://bhuvan-app1.nrsc.gov.in/thematic/thematic/index.php (accessed on 21 September 2023).
29. Gupta, L., Dixit, J. (2022): A GIS-based flood risk mapping of Assam, India, using the MCDA-AHP approach at the regional and administrative level. Geocarto International 37(26), 11867-11899. CrossRef
30. Hassan, I., Javed, M. A., Asif, M., Luqman, M., Ahmad, S. R., Ahmad, A., Akhtar, S., Hussain, B. (2020): Weighted overlay based land suitability analysis of agriculture land in Azad Jammu and Kashmir using GIS and AHP. Pakistan Journal of Agricultural Sciences 57(6), 1509-1519.
31. Hudait, M., Patel, P. P. (2022): Site suitability assessment for traditional betel vine cultivation and crop acreage expansion in Tamluk Subdivision of Eastern India using AHP-based multi-criteria decision making approach. Computers and Electronics in Agriculture 200, 107220. CrossRef
32. Jahn, R., Blume, H. P., Asio, V. B., Spaargaren, O., Schad, P. (2006): Guidelines for soil description. FAO. Available online: https://www.fao.org/3/a0541e/a0541e.pdf (accessed on 20 October 2023).
33. Jin, Y., Li, A., Bian, J., Nan, X., Lei, G., Muhammad, K. (2021): Spatiotemporal analysis of ecological vulnerability along Bangladesh-China-India-Myanmar economic corridor through a grid level prototype model. Ecological Indicators 120: 106933. CrossRef
34. Kazemi, H., Akinci, H. (2018): A land use suitability model for rainfed farming by Multi-criteria Decision-making Analysis (MCDA) and Geographic Information System (GIS). Ecological Engineering 116, 1-6. CrossRef
35. Karra, K., Kontgis, C., Statman-Weil, Z., Mazzariello, J. C., Mathis, M., Brumpi, S. P. (2021): Global land use/land cover with Sentinel 2 and deep learning. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, 4704-4707. CrossRef
36. Mahato, R., Bushi, D., Nimasow, G., Dai Nimasow, O. (2024): Remote sensing and geographic information system-based land suitability analysis for precision agriculture: a case of paddy cultivation in East Siang district of Arunachal Pradesh (India). In Remote Sensing in Precision Agriculture (pp. 151-173). Academic Press. CrossRef
37. Martin, D., Saha, S. K. (2009): Land evaluation by integrating remote sensing and GIS for cropping system analysis in a watershed. Current Science, 569-575. Available online: https://www.jstor.org/stable/pdf/24105472.pdf (accessed on 10 November 2023).
38. Melese, T., Belay, T. (2022): Groundwater Potential Zone Mapping Using Analytical Hierarchy Process and GIS in Muga Watershed, Abay. Global Challenges, 2100068(6), 1-13. CrossRef
39. Ministry of Agriculture and Farmers Welfare (MoA&FW), (2018): Agriculture Census 2015-16.
40. In Department of Agriculture, Cooperation and Farmers Welfare (Vol. 1), Government of India. Available online: http://agcensus.nic.in/document/agcen1516/T1_ac_2015_16.pdf (accessed on 10 November 2023).
41. Mohanty, A., Wadhawan, S. (2021): Mapping India's Climate Vulnerability: A District Level Assessment. State of vulnerability of Indian districts and states, pp: 29-42 New Delhi: Council on Energy, Environment and Water (CEEW).
42. Montgomery, B., Dragićević, S., Dujmović, J., Schmidt, M. (2016): A GIS-based Logic Scoring of Preference method for evaluation of land capability and suitability for agriculture. Computers and Electronics in Agriculture, 124, 340-353. CrossRef
43. Nath, A. J., Kumar, R., Devi, N. B., Rocky, P., Giri, K., Sahoo, U. K., ... Pandey, R. (2021): Agroforestry land suitability analysis in the Eastern Indian Himalayan region. Environmental Challenges, 4, 100199. CrossRef
44. North, M. A. (2009): A Method for Implementing a Statistically Significant Number of Data Classes in the Jenks Algorithm," 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, Tianjin, China, 35-38. CrossRef
45. NRSC (2019): Status of Land Degradation in India: 2015-16 National Remote Sensing Centre ISRO, Govt. of India, Hyderabad.
46. Pawe, C. K., Saikia, A. (2022): These hills called home: quantifying urban forest dynamics in the hills of the Guwahati metropolitan area, india. Geografisk Tidsskrift-Danish Journal of Geography, 122(2), 87-102. CrossRef
47. Phanjoubam, P. (2005): Manipur: fractured land. India International Centre Quarterly, 32(2/3), 275-287. Available online: https://www.jstor.org/stable/pdf/23006034.pdf (accessed on 06 October 2023).
48. Podvezko, V. (2009): Application of AHP technique. Journal of Business Economics and Management 10(2), 181-189. CrossRef
49. Rai, P.K., Vanlalruati (2022): Societal perception on environmental and socio-economic implications of Tithonia diversifolia (Hemsl.) A. Gray invasion in an Indo-Burma biodiversity hotspot. Environmental and Socio-Economic Studies 10(3), 59-66. CrossRef
50. Ritung, S., Wahyunto, Hidayat, F. (2007): Land suitability evaluation with a case map of Aceh Barat District. World Agroforestry Centre, https://apps.worldagroforestry.org/downloads/Publications/PDFS/MN15224.pdf (accessed on 06 October 2023).
51. Roy, S. S., Ansari, M. A., Sharma, S. K., Sailo, B., Devi, C. B., Singh, I. M., … Ngachan, S. V. (2018): Climate resilient agriculture in Manipur. Current Science, 115(7), 1342-1350. CrossRef
52. Saaty, T. L. (2001): Fundamentals of the analytic hierarchy process. In: Schmoldt, D.L., Kangas, J., Mendoza, G. A., Pesonen, M. (eds) The Analytic Hierarchy Process in Natural Resource and Environmental Decision Making. Managing Forest Ecosystems 3. Springer, Dordrecht. CrossRef
53. Saaty, T. L. (2008): Decision making with the analytic hierarchy process. International Journal of Services Sciences 1(1), 83-98. CrossRef
54. Sahoo, S., Vasu, D., Paul, R., Sen, T. K., Ray, S. K., Chandran, P. (2020): Acid soils of Manipur of the north-eastern region of India: their mineralogy, pedology, taxonomy and edaphology. Clay Research 39(1), 31-43. CrossRef
55. Sarkar, D., Saha, S., Mondal, P. (2023): Modelling agricultural land suitability for vegetable crops farming using RS and GIS in conjunction with bivariate techniques in the Uttar Dinajpur district of Eastern India. Green Technologies and Sustainability 1(2): 100022. CrossRef
56. Sen, T. K., Chamuah, G. S., Maji, A. K., Sehgal, J. (1996): Soils of Manipur for Optimising Land Use. NBSS Publ. 56b (Soils of India Series), National Bureau of Soil Survey and Land Use Planning, Nagpur, India.
57. Sitorus, S. R. P. (2010): Land Capability Classification for Land Evaluation: a Review. Journal Sumberdaya Lahan 4(2), 69-78. Available online: https://scholar.google.com (accessed on 30 April 2023).
58. Takhell, D. (2023): Manipur farmers blame institutional failures for low yield and demand compensation. Mongabay-India, 6 January 2023.
59. Tempa, K. (2022): District flood vulnerability assessment using analytic hierarchy process (AHP) with historical flood events in Bhutan. PLoS ONE 17(6): e0270467. CrossRef
60. Thockchom, L., Kshetrimayum, K. S. (2019): Assessment of quality contributing parameters using hydrochemistry and hydrogeology for irrigation in intermontane Manipur valley in northeast India. Groundwater for Sustainable Development 8, 667-679. CrossRef
61. Wang, F. (1994): The use of artificial neural networks in a geographical information system for agricultural land-suitability assessment. Environment & Planning A 26(2), 265-284. CrossRef
62. Zolekar, R. B., Bhagat, V. S. (2015): Multi-criteria land suitability analysis for agriculture in hilly zone: Remote sensing and GIS approach. Computers and Electronics in Agriculture 118, 300-321. CrossRef
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