Skip to main content

Advertisement

SpringerLink
Log in

Multi-influencing factor (MIF) and RS–GIS-based determination of agriculture site suitability for achieving sustainable development of Sub-Himalayan region, India

  • Published:
Environment, Development and Sustainability Aims and scope Submit manuscript

Abstract

Agriculture is the primary source of income in the Sub-Himalayan Jalpaiguri District; therefore, identifying the optimal use of existing agricultural land is crucial. The primary objective of this study is to identify potential agricultural sites in the Jalpaiguri District for the sustainable development of the region. About eleven parameters have been considered using the multi-influencing technique in combination with remote sensing (RS) and geographic information system to delineate and model potential agriculture sites. The final agriculture suitability map was created using the ‘Weighted Overlay technique,’ and the final output can be categorized into five classes, i.e., highly suitability (424.3 km2), moderately suitability (1191.8 km2), marginally suitable (1141.4 km2), currently not suitable (567.1 km2), and permanently not suitable (60.8 km2). Besides, the results have been thoroughly verified using Google Earth images, in comparison with Landsat 8 output, and field visits using GPS to increase the reliability of the results. The finding reveals potential outcomes for agricultural activity; however, building a sustainable management strategy and resilient farming practices should be adopted to boost the region’s agricultural output. Farmers, regional planners, and government officials can use the current agriculture suitability map to make comprehensive judgments for the region, such as determining the potential for agriculture sites, improving agricultural growth, and promoting self-reliant local economies.

Graphical abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Source: www.indiawris.gov.in)

Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

All the data used in the present study are freely available to all through proper request if needed by anyone for further research.

References

  • AbdelRahman, M. A., Natarajan, A., & Hegde, R. (2016). Assessment of land suitability and capability by integrating remote sensing and GIS for agriculture in Chamarajanagar district, Karnataka, India. The Egyptian Journal of Remote Sensing and Space Science, 19(1), 125–141. https://doi.org/10.1016/j.ejrs.2016.02.001

    Article  Google Scholar 

  • Abdullah, S. A., & Hezri, A. A. (2008). From forest landscape to agricultural landscape in the developing tropical country of Malaysia: Pattern, process, and their significance on policy. Environmental Management, 42(5), 907–917. https://doi.org/10.1007/s00267-008-9178-3

    Article  Google Scholar 

  • Aguiar, A. P. D., Câmara, G., & Escada, M. I. S. (2007). Spatial statistical analysis of land-use determinants in the Brazilian Amazonia: Exploring intra-regional heterogeneity. Ecological Modelling, 209(2–4), 169–188. https://doi.org/10.1016/j.ecolmodel.2007.06.019

    Article  Google Scholar 

  • Ahmad, F., Goparaju, L., & Qayum, A. (2019). FAO guidelines and geospatial application for agroforestry suitability mapping: Case study of Ranchi. Jharkhand State of India. Agroforestry Systems, 93(2), 531–544.

    Article  Google Scholar 

  • Akıncı, 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. https://doi.org/10.1016/j.compag.2013.07.006

    Article  Google Scholar 

  • 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. https://doi.org/10.1016/j.agsy.2019.02.013

    Article  Google Scholar 

  • Alemayehu, S., Ayana, E. K., Dile, Y. T., Demissie, T., Yimam, Y., Girvetz, E., & Worqlul, A. W. (2020). Evaluating land suitability and potential climate change impacts on alfalfa (Medicago sativa) production in ethiopia. Atmosphere, 11(10), 1124. https://doi.org/10.3390/atmos11101124

    Article  Google Scholar 

  • Al-Kaisi, M. (2000). Soil erosion: an agricultural production challenge.

  • Alkaradaghi, K., Ali, S. S., Al-Ansari, N., Laue, J., & Chabuk, A. (2019). Landfill site selection using MCDM methods and GIS in the Sulaimaniyah Governorate. Iraq. Sustainability, 11(17), 4530.

    Article  Google Scholar 

  • Atalay, I (2006). Toprak Oluşumu, Sınıflandırılması Ve Coğrafyası, Meta Basım, Baskı,

  • Aymen, A. T., Al-husban, Y., & Farhan, I. (2021). Land suitability evaluation for agricultural use using GIS and remote sensing techniques: The case study of Ma’an Governorate, Jordan. The Egyptian Journal of Remote Sensing and Space Science, 24(1), 109–117. https://doi.org/10.1016/j.ejrs.2020.01.001

    Article  Google Scholar 

  • Ayoade, J.O. (2004). Introduction to climatology for the tropics. Spectrum Book Limited, Ibadan.

  • Baja. S., Chapman. DM., Dragovich. D. (2001). A conceptual model for assessing agricultural land suitability at a catchment level using a continuous approach in GIS. In Proceedings of the geospatial information and agriculture conference. Accessed through http://www.regional.org.au/au/gia/26/828baja.htm

  • 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. https://doi.org/10.1080/01431160802395235

    Article  Google Scholar 

  • Bhagat, V. (2014). Use of IRS P6 LISS-IV data for land suitability analysis for cashew plantation in hilly zone. Asian Journal of Geoinformatics, 14(3).

  • Bhagat, V. S., & Sonawane, K. R. (2011). Use of LANDSAT ETM+ data for delineation of water bodies in hilly zones. J. Hydroinform., 13(4), 661–671.

    Article  Google Scholar 

  • Bhattacharya, S., Das, S., Das, S., Kalashetty, M., & Warghat, S. R. (2021). An integrated approach for mapping groundwater potential applying geospatial and MIF techniques in the semiarid region. Environment, Development and Sustainability, 23(1), 495–510.

    Article  Google Scholar 

  • Bojorquez-Tapia, L. A., Diaz-Mondragon, S., & Ezcurra, E. (2001). GIS-based approach for participatory decision making and land suitability assessment. International Journal of Geographical Information Science, 15(2), 129–151. https://doi.org/10.1080/13658810010005534

    Article  Google Scholar 

  • Brady, N. C., and Weil, R. R. (2002). In the nature and properties of soils 15th edition, 375–419.

  • Cengiz, T., & Akbulak, C. (2009). Application of analytical hierarchy process and geographic information systems in land-use suitability evaluation: A case study of Dümrek village (Çanakkale, Turkey). International Journal of Sustainable Development & World Ecology, 16(4), 286–294.

    Article  Google Scholar 

  • Chakraborty, K., & Mistri, B. (2015). Importance of soil texture in sustenance of agriculture: A study in Burdwan-I CD Block, Burdwan, West Bengal. Eastern Geographer, 21, 475–482.

    Google Scholar 

  • Chen, Y., Shuai, J., Zhang, Z., Shi, P., & Tao, F. (2014). Simulating the impact of watershed management for surface water quality protection: A case study on reducing inorganic nitrogen load at a watershed scale. Ecological Engineering, 62, 61–70.

    Article  Google Scholar 

  • Collins, M. G., Steiner, F. R., & Rushman, M. J. (2001). Land-use suitability analysis in the United States: Historical development and promising technological achievements. Environmental Management, 28(5), 611–621.

    Article  CAS  Google Scholar 

  • Cook, S. E., Fisher, M. J., Andersson, M. S., Rubiano, J., & Giordano, M. (2009). Water, food and livelihoods in river basins. Water International, 34(1), 13–29. https://doi.org/10.1080/02508060802673860

    Article  Google Scholar 

  • Das, S., & Paul, S. (2021). An assessment of cultivators’ perception about climate change and it’s-induced adaptation practices in agriculture of Cooch Behar Sadar Sub-division, West Bengal India. Applied Ecology and Environmental Sciences, 9(2), 271–279. https://doi.org/10.12691/aees-9-2-19

    Article  Google Scholar 

  • Datye, V. S., & Gupte, S. C. (1984). Association between agricultural land use and physico- socio-economic phenomena: A multivariate approach. Trans. Inst. Ind. Geogr., 6(2), 61–72.

    Google Scholar 

  • DCHB. (2011). District Census Handbook, Jalpaiguri District. Retriverd from https://censusindia.gov.in/2011census/dchb/DCHB_A/19/1902_PART_A_DCHB_JALPAIGURI.pdf

  • Dey, T., Pala, N. A., Shukla, G., Pal, P. K., & Chakravarty, S. (2017). Perception on impact of climate change on forest ecosystem in protected area of West Bengal, India. Journal of Forest and Environmental Science, 33(1), 1–7. https://doi.org/10.7747/JFES.2017.33.1.1

    Article  Google Scholar 

  • Dey, T., Pala, N. A., Shukla, G., Pal, P. K., Das, G., & Chakarvarty, S. (2018). Climate change perceptions and response strategies of forest fringe communities in Indian Eastern Himalaya. Environment, Development and Sustainability, 20(2), 925–938. https://doi.org/10.1007/s10668-017-9920-1

    Article  Google Scholar 

  • El Alfy, Z., Elhadary, R., & Elashry, A. (2010). Integrating GIS and MCDM to deal with landfill site selection. International Journal of Engineering & Technology, 10(6), 32–42.

    Google Scholar 

  • El Baroudy, A. A. (2016). Mapping and evaluating land suitability using a GIS-based model. CATENA, 140, 96–104. https://doi.org/10.1016/j.catena.2015.12.010

    Article  CAS  Google Scholar 

  • Elsheikh, R., Shariff, A. R. B. M., Amiri, F., Ahmad, N. B., Balasundram, S. K., & Soom, M. A. M. (2013). Agriculture land suitability evaluator (ALSE): A decision and planning support tool for tropical and subtropical crops. Computers and Electronics in Agriculture, 93, 98–110. https://doi.org/10.1016/j.compag.2013.02.003

    Article  Google Scholar 

  • Estrada, L. L., Rasche, L., & Schneider, U. A. (2017). Modeling land suitability for Coffea arabica L. in Central America. Environmental Modelling & Software, 95, 196–209. https://doi.org/10.1016/j.envsoft.2017.06.028

    Article  Google Scholar 

  • Everest, T., Sungur, A., & Ozcan, H. (2021). Determination of agricultural land suitability with a multiple-criteria decision-making method in Northwestern Turkey. International Journal of Environmental Science and Technology, 18(5), 1073–1088. https://doi.org/10.1007/s13762-020-02869-9

    Article  CAS  Google Scholar 

  • FAO. (1976). A framework for land evaluation. Italy.

    Google Scholar 

  • FAO. (1993). Guidelines for land-use planning. FAO development series I, FAO, Rome.

  • FAO. (2007). Land evaluation, towards a revised framework. Land and Water Discussion Paper 6. Rome: FAO Electronic publishing division.

  • 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. https://doi.org/10.1080/09640568.2011.646964

    Article  Google Scholar 

  • Gao, B. C. (1996). NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, 257–266.

    Article  Google Scholar 

  • Ghaley, B. B., Wösten, H., Olesen, J. E., Schelde, K., Baby, S., Karki, Y. K., & Porter, J. R. (2018). Simulation of soil organic carbon effects on long-term winter wheat (Triticum aestivum) production under varying fertilizer inputs. Frontiers in Plant Science, 9, 1158. https://doi.org/10.3389/fpls.2018.01158

    Article  Google Scholar 

  • Ghosh, M., & Ghosal, S. (2020). Climate change vulnerability of rural households in flood-prone areas of Himalayan foothills, West Bengal, India. Environment, Development and Sustainability, 23, 2570–2595. https://doi.org/10.1007/s10668-020-00687-0

    Article  Google Scholar 

  • Gil, J. D. B., Reidsma, P., Giller, K., et al. (2019). Sustainable development goal 2: Improved targets and indicators for agriculture and food security. Ambio, 48, 685–698. https://doi.org/10.1007/s13280-018-1101-4

    Article  CAS  Google Scholar 

  • Haddaway, N. R., Hedlund, K., Jackson, L. E., Kätterer, T., Lugato, E., Thomsen, I. K., & Söderström, B. (2015). What are the effects of agricultural management on soil organic carbon in boreo-temperate systems? Environmental Evidence, 4(1), 1–29. https://doi.org/10.1186/s13750-015-0049-0

    Article  Google Scholar 

  • Hengl, T., Toomanian, N., Reuter, H. I., & Malakouti, M. J. (2007). Methods to interpolate soil categorical variables from profile observations: Lessons from Iran. Geoderma, 140(4), 417–427.

    Article  Google Scholar 

  • Hui, F., Xu, B., Huang, H., Yu, Q., & Gong, P. (2008). Modelling spatial-temporal change of Poyang Lake using multitemporal Landsat imagery. International Journal of Remote Sensing, 29(20), 5767–5784. https://doi.org/10.1080/01431160802060912

    Article  Google Scholar 

  • Hussein, A. F., Jameel, B. I., & Abd, K. K. (2018). Comparative analysis of Fuzzy MCDM methods for material selection in biomedical application. Association of Arab Universities Journal of Engineering Sciences, 25(2), 137–148.

    Google Scholar 

  • Iizumi, T., & Ramankutty, N. (2015). How do weather and climate influence cropping area and intensity. Global Food Security, 4, 46–50. https://doi.org/10.1016/j.gfs.2014.11.003

    Article  Google Scholar 

  • JDP report. (2011). Jalpaiguri district profile, Govt. of West Bengal. Accessed: http://jalpaiguri.gov.in/district-profile.

  • Ngetich, K. F. (2020). Multi-influencing-factors’ evaluation for organic-based soil fertility technologies out-scaling in Upper Tana Catchment in Kenya. Scientific African, 7, e00231. https://doi.org/10.1016/j.sciaf.2019.e00231

    Article  Google Scholar 

  • Kalogirou, S. (2002). Expert systems and GIS: An application of land suitability evaluation. Computers, Environment and Urban Systems, 26(2–3), 89–112.

    Article  Google Scholar 

  • Kangas, J., & Kangas, A. (2005). Multiple criteria decision support in forest management—the approach, methods applied, and experiences gained. Forest Ecology and Management, 207(1–2), 133–143.

    Article  Google Scholar 

  • Kapluhan, E. (2013). Drought in Turkey and effect of drought on agriculture. Marmara Geography Magazine ISSN, 1303–2429.

  • Kazemi, A., Attari, M. Y. N., & Khorasani, M. (2016). Evaluating service quality of airports with integrating TOPSIS and VIKOR under fuzzy environment. International Journal of Services, Economics and Management, 7(2–4), 154–166.

    Article  Google Scholar 

  • Kim, S., Lee, W., Shin, K., Kafatos, M., Seo, D., & Kwak, H. (2011). Comparison of spatial interpolation techniques for predicting climate factors in Korea. Forest Science and Technology, 6, 97–109. https://doi.org/10.1080/21580103.2010.9671977

    Article  Google Scholar 

  • King, A. E., Ali, G. A., Gillespie, A. W., & Wagner-Riddle, C. (2020). Soil organic matter as catalyst of crop resource capture. Frontiers in Environmental Science, 8, 50. https://doi.org/10.3389/fenvs.2020.00050

    Article  Google Scholar 

  • Koulouri, M., & Giourga, C. (2007). Land abandonment and slope gradient as key factors of soil erosion in Mediterranean terraced lands. CATENA, 69(3), 274–281.

    Article  Google Scholar 

  • Kumar, A., Pramanik, M., Chaudhary, S., & Negi, M. S. (2021). Land evaluation for sustainable development of Himalayan agriculture using RS-GIS in conjunction with analytic hierarchy process and frequency ratio. Journal of the Saudi Society of Agricultural Sciences, 20(1), 1–17. https://doi.org/10.1016/j.jssas.2020.10.001

    Article  Google Scholar 

  • Lal, R. (2004). Soil carbon sequestration to mitigate climate change. Geoderma, 123, 1–22. https://doi.org/10.1016/j.geoderma.2004.01.032

    Article  CAS  Google Scholar 

  • Li, X., Chang, S. X., Liu, J., Zheng, Z., & Wang, X. (2017). Topography-soil relationships in a hilly evergreen broadleaf forest in subtropical China. Journal of Soils and Sediments, 17(4), 1101–1115. https://doi.org/10.1007/s11368-016-1573-4

    Article  CAS  Google Scholar 

  • Lupia, D. F. (2014). Crop/land suitability analysis by ArcGIS tools. Technical report.

  • Mandal, P., Mandal, S., Halder, S., & Paul, S. (2021). Assessing and mapping cropland suitability applying geospatial and MIF techniques in the semiarid region with an integrated approach. Arabian Journal of Geosciences, 14(18), 1–19. https://doi.org/10.1007/s12517-021-08171-3

    Article  Google Scholar 

  • McDonald, G. T., & Brown, A. L. (1984). The land suitability approach to strategic land-use planning in urban fringe areas. Landscape Planning, 11(2), 125–150.

    Article  Google Scholar 

  • Mendas, A., Mebrek, A., & Mekranfar, Z. (2021). Comparison between two multicriteria methods for assessing land suitability for agriculture: Application in the area of Mleta in western part of Algeria. Environment, Development and Sustainability, 23, 9076–9089. https://doi.org/10.1007/s10668-020-01012-5

    Article  Google Scholar 

  • Mojid, M. A., Mustafa, S. M. T., & Wyseure, G. C. L. (2009). Growth, yield and water use efficiency of wheat in silt loam-amended loamy sand. Journal of Bangladesh Agricultural University, 7(2), 403–410.

    Article  Google Scholar 

  • Mollier, L., Seyler, F., Chotte, J. L., & Ringler, C. (2017). End hunger, achieve food security and improved nutrition and promote sustainable agriculture: SDG 2.

  • Mussa, K. R., & MjemahMachunda, I. C. R. L. (2020). Open-source software application for hydrogeological delineation of potential groundwater recharge zones in the Singida Semi-Arid, Fractured Aquifer. Central Tanzania. Hydrology, 7(2), 28. https://doi.org/10.3390/hydrology7020028

    Article  Google Scholar 

  • Mustafa, A. A., Singh, M., Sahoo, R. N., Ahmed, N., Khanna, M., & Sarangi, A. (2011). Land suitability analysis for different crops: A multi-criteria decision-making approach using remote sensing and GIS. Researcher, 3(12), 61–84.

    Google Scholar 

  • Ndamani, F., & Watanabe, T. (2015). Influences of rainfall on crop production and suggestions for adaptation. International Journal of Agricultural Sciences, 5(1), 367–374.

    Google Scholar 

  • Neina, D. (2019). The role of soil pH in plant nutrition and soil remediation. Applied and Environmental Soil Science. https://doi.org/10.1155/2019/5794869

    Article  Google Scholar 

  • Nganga, W. B., Ng'etich, K. O., Macharia, M. J., Kiboi, N. M., Adamtey, N., & Ngetich, K. F. (2020). Multi-influencing-factors’ evaluation for organic-based soil fertility technologies out-scaling in Upper Tana Catchment in Kenya. Scientific African, 7, e00231. https://doi.org/10.1016/j.sciaf.2019.e00231

  • Orhan, O. (2021). Land suitability determination for citrus cultivation using a GIS- based multi-criteria analysis in Mersin Turkey. Computers and Electronics in Agriculture, 190, 106433. https://doi.org/10.1016/j.compag.2021.106433

    Article  Google Scholar 

  • Özkan, B., Dengiz, O., & Turan, İD. (2020). Site suitability analysis for potential agricultural land with spatial fuzzy multi-criteria decision analysis in regional scale under semi-arid terrestrial ecosystem. Scientific Reports, 10(1), 1–18. https://doi.org/10.1038/s41598-020-79105-4

    Article  CAS  Google Scholar 

  • Pramanik, M. K. (2016). Site suitability analysis for agricultural land use of Darjeeling district using AHP and GIS techniques. Modeling Earth Systems and Environment, 2(2), 56. https://doi.org/10.1007/s40808-016-0116-8

    Article  Google Scholar 

  • PRB. (2018). Population Reference Bureau (PRB). https://www.prb.org/2018-world-population-data-sheet-with-focus-on-changing1age-structures.

  • Prokop, P., & Walanus, A. (2017). Impact of the Darjeeling-Bhutan Himalayan front on rainfall hazard pattern. Natural Hazards, 89, 387–404. https://doi.org/10.1007/s11069-017-2970-8

    Article  Google Scholar 

  • Rabia, A. H., Figueredo, H., Huong, T. L., Lopez, B. A. A., Solomon, H. W., & Alessandro, V. (2013). Land suitability analysis for policy making assistance: A GIS based land suitability comparison between surface and drip irrigation systems. International Journal of Environmental Science Development, 4(1), 1–6.

    Article  Google Scholar 

  • Romano, G., Dal Sasso, P., Liuzzi, G. T., & Gentile, F. (2015). Multi-criteria decision analysis for land suitability mapping in a rural area of Southern Italy. Land Use Policy, 48, 131–143.

    Article  Google Scholar 

  • Roy, P. B., & Barman, U. K. (2014). Crop concentration and diversification in Jalpaiguri district of West Bengal: A case study. International Journal of Food, Agriculture and Veterinary Sciences, 4(3), 5–9.

    Google Scholar 

  • Roy, S., Bose, A., & Chowdhury, I. R. (2021a). Flood risk assessment using geospatial data and multi-criteria decision approach: A study from historically active flood-prone region of Himalayan foothill India. Arabian Journal of Geosciences, 14(11), 1–25. https://doi.org/10.1007/s12517-021-07324-8

    Article  Google Scholar 

  • Roy, S., Bose, A., & Mandal, G. (2021c). Modeling and mapping geospatial distribution of groundwater potential zones in Darjeeling Himalayan region of India using analytical hierarchy process and GIS technique. Modeling Earth Systems and Environment, 7(01), 1–22. https://doi.org/10.1007/s40808-021-01174-9

    Article  CAS  Google Scholar 

  • Roy, S., Bose, A., Singha, N., Basak, D., & Chowdhury, I. R. (2021b). Urban waterlogging risk as an undervalued environmental challenge: An integrated MCDA- GIS based modeling approach. Environmental Challenges, 4, 100194.

    Article  Google Scholar 

  • Sabbaghian, R. J., Zarghami, M., Nejadhashemi, A. P., Sharifi, M. B., Herman, M. R., & Daneshvar, F. (2016). Application of risk-based multiple criteria decision analysis for selection of the best agricultural scenario for effective watershed management. Journal of Environmental Management, 168, 260–272.

    Article  Google Scholar 

  • Saha, S., Sarkar, D., Mondal, P., & Goswami, S. (2021). GIS and multi-criteria decision-making assessment of sites suitability for agriculture in an anabranching site of sooin river India. Modeling Earth Systems and Environment, 7(1), 571–588. https://doi.org/10.1007/s40808-020-00936-1

    Article  Google Scholar 

  • Sarkar, R., Molla, S. H. (2021). Land suitability evaluation for agricultural crops in selected blocks of south 24 Parganas district, West Bengal. In: Agriculture, food and nutrition security (79–101). Springer, Cham. https://doi.org/10.1007/978-3-030-69333-6_5

  • Sharma, E., Chettri, N., & Oli, K. P. (2010). Mountain biodiversity conservation and management: A paradigm shift in policies and practices in the Hindu Kush- Himalayas. Ecological Research, 25(5), 909–923.

    Article  Google Scholar 

  • Shashikant, V., Mohamed Shariff, A. R., Wayayok, A., Kamal, M. R., Lee, Y. P., & Takeuchi, W. (2021). Utilizing TVDI and NDWI to classify severity of agricultural drought in Chuping Malaysia. Agronomy, 11(6), 1243. https://doi.org/10.3390/agronomy11061243

    Article  Google Scholar 

  • Singh, L., Saravanan, S., Jennifer, J. J.,Abijith, D. (2021). Application of multi- influence factor (MIF) technique for the identification of suitable sites for urban settlement in Tiruchirappalli City, Tamil Nadu, India. Asia-Pacific Journal of Regional Science, 1–27.

  • Slessarev, E. W., Lin, Y., Bingham, N. L., Johnson, J. E., Dai, Y., & Schimel, J. P. (2016). Water balance creates a threshold in soil pH at the global scale [J]. Nature, 540(7634), 567.

    Article  CAS  Google Scholar 

  • Stewart, T. J. (1992). A critical survey on the status of multiple criteria decision making theory and practice. Omega, 20(5–6), 569–586.

    Article  Google Scholar 

  • Sys, C., Van Ranst, E., & Debaveye, J. (1991). Land evaluation: Principles in land evaluation and crop production calculations. General Administration for Development Cooperation.

    Google Scholar 

  • Szabo, S., Hossain, M. S., Renaud, F., Traore, D., Hussain, A., Matczak, P., Matthews, Z (2018), Accelerating progress toward the zero hunger goal in cross- boundary climate change hotspots. Environment: Science and Policy for Sustainable Development, 60(3), 18–27.

  • Tashayo, B., Honarbakhsh, A., Azma, A., & Akbari, M. (2020). Combined fuzzy AHP– GIS for agricultural land suitability modeling for a watershed in southern Iran. Environmental Management, 66(3), 364–376. https://doi.org/10.1007/s00267-020-01310-8

    Article  Google Scholar 

  • Thapa, R., Gupta, S., Guin, S., & Kaur, H. (2017). Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS: A case study from Birbhum district West Bengal. Applied Water Science, 7(7), 4117–4131. https://doi.org/10.1007/s13201-017-0571-z

    Article  Google Scholar 

  • Thapa, R. B., & Murayama, Y. (2008). Land evaluation for peri-urban agriculture using analytical hierarchical process and geographic information system techniques: A case study of Hanoi. Land Use Policy, 25(2), 225–239.

    Article  Google Scholar 

  • Thomas, R., & Duraisamy, V. (2018). Hydrogeological delineation of groundwater vulnerability to droughts in semi-arid areas of western Ahmednagar district. The Egyptian Journal of Remote Sensing and Space Science, 21(2), 121–137.

    Article  Google Scholar 

  • Times of India. (2019). Changing climate wreaks havoc on West Bengal crops, hits kharif yield. Accessed: https://timesofindia.indiatimes.com/city/kolkata/changing-climate-wreaks-havoc-on-bengal-crops-hits-kharif-yield/articleshow/72062758.cms

  • UBKV report, 2015. Present scenario of North Bengal- Vison. (2030). Uttar Banga Krishi Viswavidyalaya. Accessed: https://www.ubkv.ac.in/wp-content/uploads/CH-I-Present-scenario_VISION.pdf

  • UN Food and Agriculture Organization. (1976). A framework for land evaluation. Soils Bulletin, 32.

  • Van Diepen, C. A., Van Keulen, H., Wolf, J., Berkhout, J. A. A. (1991). Land evaluation: from intuition to quantification. Advances in soil science, 139–204.

  • Waleed, M., Ahmad, S. R., Javed, M. A., & Samiullah, S. (2020). Identification of irrigation potential areas, using multi-criteria analysis in Khyber District Pakistan. Environmental Science and Pollution Research, 27(32), 39832–39840. https://doi.org/10.1007/s11356-020-08967-y

    Article  Google Scholar 

  • Wang, S., Fu, B. J., Gao, G. Y., Yao, X. L., & Zhou, J. (2012). Soil moisture and evapotranspiration of different land cover types in the Loess Plateau China. Hydrology and Earth System Sciences, 16(8), 2883–2892.

    Article  Google Scholar 

  • Winkler, K., Fuchs, R., Rounsevell, M., & Herold, M. (2021). Global land use changes are four times greater than previously estimated. Nature Communications, 12(1), 1–10. https://doi.org/10.1038/s41467-021-22702-2

    Article  CAS  Google Scholar 

  • Worqlul, A. W., Dile, Y. T., Jeong, J., Adimassu, Z., Lefore, N., Gerik, T., & Clarke, N. (2019). Effect of climate change on land suitability for surface irrigation and irrigation potential of the shallow groundwater in Ghana. Computers and Electronics in Agriculture, 157, 110–125. https://doi.org/10.1016/j.compag.2018.12.040

    Article  Google Scholar 

  • Xu, H. (2006). Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing, 27(14), 3025–3033.

    Article  Google Scholar 

  • Yalew, S. G., Van Griensven, A., Mul, M. L., & van der Zaag, P. (2016a). Land suitability analysis for agriculture in the Abbay basin using remote sensing, GIS and AHP techniques. Modeling Earth Systems and Environment, 2(2), 1–14. https://doi.org/10.1007/s40808-016-0167-x

    Article  Google Scholar 

  • Yalew, S. G., van Griensven, A., & van der Zaag, P. (2016b). AgriSuit: A web- based GIS MCDA framework for agricultural land suitability assessment. Computers and Electronics in Agriculture, 128, 1–8. https://doi.org/10.1016/j.compag.2016.08.008

    Article  Google Scholar 

  • Yeh, H. F., Lee, C. H., Hsu, K. C., & Chang, P. H. (2009). GIS for the assessment of the groundwater recharge potential zone. Environmental Geology, 58(1), 185–195.

    Article  Google Scholar 

  • Yohannes, H., & Soromessa, T. (2018). Land suitability assessment for major crops by using GIS-based multi-criteria approach in Andit Tid watershed Ethiopia. Cogent Food & Agriculture, 4(1), 1470481. https://doi.org/10.1080/23311932.2018.1470481

    Article  Google Scholar 

  • Zhang, J., Su, Y., Wu, J., & Liang, H. (2015). GIS based land suitability assessment for tobacco production using AHP and fuzzy set in Shandong province of China. Computers and Electronics in Agriculture, 114, 202–211. https://doi.org/10.1016/j.compag.2015.04.004

    Article  Google Scholar 

  • Zhang, R., & Wienhold, B. J. (2002). The effect of soil moisture on mineral nitrogen, soil electrical conductivity, and pH. Nutrient Cycling in Agroecosystems, 63(2), 251–254. https://doi.org/10.1023/A:1021115227884

    Article  CAS  Google Scholar 

  • Zhang, Y. Y., Wu, W., & Liu, H. (2019). Factors affecting variations of soil pH in different horizons in hilly regions. PLoS ONE, 14(6), e0218563. https://doi.org/10.1371/journal.pone.0218563

    Article  CAS  Google Scholar 

  • Zolekar, R. B., & Bhagat, V. S. (2014). Use of IRS P6 LISS-IV data for land suitability analysis for cashew plantation in hilly zone. Asian Journal of Geoinformatics, 14(3), 23–35.

    Google Scholar 

  • 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. https://doi.org/10.1016/j.compag.2015.09.016

    Article  Google Scholar 

Download references

Acknowledgements

Firstly, the authors would like to express their sincere gratitude to the Department of Geography and Applied Geography, the University of North Bengal, for providing the opportunity in conducting the research work. Besides, the author also would like to thank Krishi Vigyan Kendra and Krishi Vaban of Jalpaiguri for providing information regarding research. The author would also like to thank Dr. Jayanta Das, Assistant Professor, Department of Geography, Rampurhat College, for providing a few data related to the present study. The authors received no specific funding for this study; however, it was completed during the period of UGC-JRF. Lastly, the authors would like to express their sincere gratitude to the Editor and two anonymous reviewers for the insightful suggestions and comments, which immensely helped in the improvement in the earlier version of the manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Department of Geography and Applied Geography, University of North Bengal, Siliguri, West Bengal, 734013, India

    Subham Roy, Arghadeep Bose, Debanjan Basak & Indrajit Roy Chowdhury

  2. Department of Geography, Cooch Behar Panchanan Barma University, Cooch Behar, West Bengal, 736101, India

    Nimai Singha

Authors
  1. Subham Roy
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nimai Singha
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Arghadeep Bose
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Debanjan Basak
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Indrajit Roy Chowdhury
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

SR contributed to writing–original draft, review and editing, conceptualization, methodology, software, and validation; NS contributed to methodology and validation; AB and DB contributed to formal analysis, review and editing, and methodology; IRC performed review and editing, supervision, and validation.

Corresponding author

Correspondence to Indrajit Roy Chowdhury.

Ethics declarations

Conflict of interest

The authors declare that they had no known conflicting interests.

Consent for publication

All the authors read the manuscript carefully and gave consent for submission.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 28 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Roy, S., Singha, N., Bose, A. et al. Multi-influencing factor (MIF) and RS–GIS-based determination of agriculture site suitability for achieving sustainable development of Sub-Himalayan region, India. Environ Dev Sustain 25, 7101–7133 (2023). https://doi.org/10.1007/s10668-022-02360-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10668-022-02360-0

Keywords

Search

Navigation