Emergence of Marine Fishery Advisory services and their impact on achieving sustainable fisheries in India: A review

Abstract

Sustainable fisheries development is increasingly critical amid rising global demand for marine resources. In this context, the Indian Marine Fishery Advisories, particularly Potential Fishing Zone (PFZ) and Ocean State Forecast (OSF) Advisories, have emerged as key tools to enhance fishery practices while reducing uncertainty and risks. The Earth System Science Organization-Indian National Centre for Ocean Information Services, under the Ministry of Earth Sciences, has been providing satellite-based PFZ and OSF Advisories since 1999 and 2009, respectively. PFZ Advisories guide fishers to areas of high fish aggregation, whereas OSF services enhance safety through accurate ocean weather forecasts. These advisories are disseminated daily to the coastal fishing community across India through multiple channels. Despite demonstrable improvements in catch per unit effort and fisher incomes in many regions, significant disparities remain in access and utilization of these services. Public-private partnerships, particularly those involving non-profit organizations, have the potential to bridge these gaps by improving outreach and community capacity-building at the grassroots level. In addition, international experience shows that co-management practices can support long-term sustainability in fisheries. This study reviews the dissemination and utilization of PFZ and OSF Advisories globally, with a focus on India, and evaluates their socioeconomic and environmental impacts. It identifies barriers to access, highlights successful models, and explores future needs for inclusive and sustainable fishery development. The findings aim to inform policy frameworks that align with the Sustainable Development Goals, particularly those related to poverty reduction, food security, and marine resource sustainability.

Keywords

Potential fishing zones / Ocean state forecast / Indian National Centre for Ocean Information Services / Marine Fishery Advisory / Dissemination / Sustainable fisheries / Catch per unit effort / Sustainable Development Goals 14

Funding

None.

Conflict of interest

The authors declare that they have no competing interests.

References

[1] NABARD. Sectoral Paper on Fisheries and Aquaculture. Mumbai; 2018. Available from: https://www.nabard.org/auth/writereaddata/file/fisheriesandaquaculture.pdf [Last accessed on 2021 Apr 24].

[2] NFDB. National Fisheries Policy, 2020. Sixth Draft for Consideration. Hyderabad; 2020. Available from: https://nfdb.gov.in/pdf/policy/english.pdf [Last accessed on 2021 Apr 24].

[3] DADF.DADF Annual Report 2017-18; 2018. Available from: https://dadf.gov.in/sites/default/filess/annual_report_17-18.pdf [Last accessed on 2021 Apr 24].

[4] Department of Fisheries. Handbook on Fisheries Statistics 2018. New Delhi; 2019. Available from: https://dof.gov.in/sites/default/filess/handbookonfs2018.pdf [Last accessed on 2021 Apr 24].

[5] Sathianandan TV. Marine Fish Production in India - Present Status; 2017. Available from: https://eprints.cmfri.org.in/12164/1/2-marinefishproductioninindia.pdf [Last accessed on 2021 Apr 24].

[6] MPEDA. MPEDA Annual Report. Kochi; 2018. Available from: https://www.mpeda.gov.in/mpeda/admin/app/webroot/files/annualreport/1550120514mpedaar201718.pdf [Last accessed on 2021 Apr 24].

[7] Ministry of Statistics and Programme Implementation. Manual on Fishery Statistics 2011. New Delhi; 2011. Available from: https://www.mospi.gov.in/sites/default/files/publication_reports/manual_fishery_statistics_2dec11_0.pdf [Last accessed on 2021 Apr 24].

[8] DARE-ICAR.DARE-ICAR Annual Report 2016-17. New Delhi; 2018. Available from: https://icar.org.in/files/dare-icarannualreport2016-17english.pdf [Last accessed on 2021 Apr 24].

[9] Mudliar SL, Shashank S, Chandak M. Machine learning model to predict potential fishing zone. J Indian Assoc Environ Manag. 2019; 39(1-4):18-20.

[10] Singh TK, Patnaik S. Marine fisheries; Its current status, sustainable management and socio-economic status of the marine fishers of Odisha, through Indian marine policy: A case study. Res J Anim Vet Fish Sci Int Sci. 2014; 2(7):10-19.

[11] Mishra SK. Beach livelihoods of Odisha. Econ Polit Wkly. 2020; 55(10):69-70.

[12] Kundu SK, Santhanam H. A report on the impacts of cyclone Yaas over a fish landing centre vulnerable to cyclonic storms and natural hazards - Talsari, Northern Odisha. Local Environ. 2021; 26(9):1043-1050. doi: 10.1080/13549839.2021.1964457

[13] Filipe JA, Coelho M, Ferreira MAM, Mutharasu SA. Fisheries, chaos and ethics. A note on India status. Int J Latest Trends Financ Econ Sci. 2013; 3(1):365-371.

[14] Tummala SK, Masuluri NK, Nayak S.Benefits derived by the fisherman using potential fishing zone (PFZ) advisories. In: Frouin RJ, Andrefouet S, Kawamura H, Lynch MJ, Pan D, Platt T, editors. Remote Sensing of Inland, Coastal, and Oceanic Waters. Vol 7150. Qatar: SPIE; 2008. doi: 10.1117/12.804766

[15] Miguel A, Santos P. Fisheries oceanography using satellite and airborne remote sensing methods: A review. Fish Res. 2000; 49(1):1-20. doi: 10.1016/S0165-7836(00)00201-0

[16] Nayak S, Srinivaskumar T, Nagarajakumar M.Satellite-based fishery service in India. In: GEO Secretariat, editor. The Full Picture. Geneva, Switzerland: Tudor Rose; 2007. p. 256-257. Available from: https://www.researchgate.net/publication/233996104/satellite/based_fishery_service_in_india [Last accessed on 2021 Apr 24].

[17] Klemas V. Remote sensing of environmental indicators of potential fish aggregation: An overview. Baltica. 2012; 25(2):99-112. doi: 10.5200/baltica.2012.25.10

[18] Kundu SK, Santhanam H, Srikanth R. A Technical Assessment of the Use of Current Geospatial Technologies to Derive Marine Fishery Advisories in India and the Way Forward. In:Asian Conference on Remote Sensing (ACRS2020). Deqing, China: ACRS 2020 - 41st Asian Conference on Remote Sensing; 2020. p. 10. Available from: https://acrs-aars.org/proceeding/ACRS2020/ifomqo.pdf [Last accessed on 2025 Nov 03].

[19] Kundu SK, Santhanam H, Srikanth R. Use of geospatial technology for sustainable development of small scale fisheries in India: Challenges and way forward. In: AGU Fall Meeting 2020. Online Everywhere. United States: AGU; 2020. doi: 10.1002/essoar.10505256.1

[20] Bhaware BG, Kurhe AR, Mane UH. The catch per unit efforts (CPUE) through validations of potential fishing zone advisories along Sindhudurg District coast of Maharashtra State. Int J Pharm Biol Sci Fundam. 2013; 3(1):20-29.

[21] Dutta S, Maity S, Hazra S. Catch per unit effort comparison between potential fishing zone and non- potential fishing zone from 2008 to 2011 of West Bengal coast, India. Indian J Geo Marine Sci. 2016; 45(6):763-768.

[22] Kamei G, Felix JF, Shenoy L, Shukla SP, Devi HM. Application of remote sensing in fisheries:Role of potential fishing zone advisories. In: Sundaresan J, Santosh KM, Déri A, Roggema R, Singh R,editors. Geospatial Technologies and Climate Change. Cham: Springer International Publishing; 2014. p. 175-186. doi: 10.1007/978-3-319-01689-4

[23] Giri S, Manna S, Chanda A, et al. Implementing a spatial model to derive potential fishing zones in the Northern bay of bengal lying adjacent to West Bengal Coast, India. J Indian Soc Remote Sens. 2016; 44(1):59-66. doi: 10.1007/s12524-015-0472-2

[24] Balasubramanian S. Satellite data aid India’s fishermen for better livelihood. Rural Int J Rural Dev. 2015; 49(3):22-23.

[25] Subramanian S, Manjulekshmi N, Narendra Pratap S, Janhavi K, Tejaswini P, Pastta MF. A Manual on the use of Potential Fishing Zone (PFZ). Goa: ICAR Research Complex For Goa; 2014. doi: 10.13140/2.1.5169.0565

[26] Nammalwar P, Satheesh S, Ramesh R. Applications of remote sensing in the validations of potential fishing zones (PFZ) along the coast of North Tamil Nadu, India. Indian J Mar Sci. 2013; 42(3):283-292.

[27] Nair PG, Pillai VN. Satellite based potential fishing zone (PFZ) advisories - acceptance levels and benefits derived by the user community along the Kerala coast. Indian J Fish. 2012; 59(2):69-74.

[28] ESSO-INCOIS.ESSO-INCOIS Annual Report 2017-18. Hyderabad: ESSO-INCOIS; 2018. Available from: https://incois.gov.in/documents/annual_reports/2017-2018_english.p [Last accessed on 2021 Apr 24].

[29] Hossain S, Rahaman T, Parvin M, Khan MS. Advance use of GIS and RS in the Validation of Potential Fishing Zones (Pfz) Forecasting along the Bay of. In: Marine Conservation and Blue Economy Symposium. Dhaka, Bangladesh, 2015. p. 1-7.

[30] Solanki HU, Mankodi PC, Dwivedi RM, Nayak SR. Satellite observations of main oceanographic processes to identify ecological associations in the Northern Arabian Sea for fishery resources exploration. Hydrobiologia. 2008; 612(1):269-279. doi: 10.1007/s10750-008-9496-8

[31] Chandran RV, Solanki HU, Dwivedi RM, Nayak S, Jeyaram A, Adiga S. Studies on the drift of ocean colour features using satellite-derived sea surface wind for updating potential fishing zone. Indian J Mar Sci. 2004; 33(2):122-128.

[32] Solanki HU, Dwivedi RM, Nayak SR. Seasonal and spatial variability in satellite derived thermal and chlorophyll features:A synergistic application for exploring fishery resources. In: Large Marine Ecosystems: Exploration and Exploitation for Sustainable Development and Conservation on Fish Stocks. Mumbai: Fishery Survey of India; 2004. p. 166-182. Available from: https://login.proxy.lib.duke.edu/login?url=https://search.proquest.com/docview/17851482?accountid=10598%0ahttp://pm6mt7vg3j.search.serialssolutions.com?ctx_ver=z39.88/2004&ctx_enc=info:ofi/enc:utf/8&rfr_id=info:sid/aquatic+science+%2526+fisheries+abstract [Last accessed on 2021 Apr 24].

[33] Solanki HU, Mankodi PC, Nayak SR, Somvanshi VS. Evaluation of remote-sensing-based potential fishing zones (PFZs) forecast methodology. Cont Shelf Res. 2005; 25(18):2163-2173. doi: 10.1016/j.csr.2005.08.025

[34] Solanki HU, Dwivedi RM, Nayak S, Gulati DK, John ME, Somvanshi VS. Potential fishing zones (PFZ) forecast using satellite data derived biological and physical processes. J Indian Soc Remote Sens. 2003; 31(2):67-69. doi: 10.1007/BF03030773

[35] Solanki HU, Dwivedi RM, Nayak SR, et al. Application of Ocean colour monitor chlorophyll and AVHRR SST for fishery forecast: Preliminary validation results of Gujarat coast, northwest coast of India. Indian J Mar Sci. 2001; 30:132-138.

[36] Kripa V, Mohamed KS, Prema D, Mohan A, Abhilash KS. On the persistent occurrence of potential fishing zones in the southeastern Arabian Sea. Indian J Geo Marine Sci. 2014; 43(5):737-745.

[37] Mane SU, Mishra AD. Application of remote sensing with R Tool in validation of PFZ along coast of Ratnagiri: A survey. IOSR J Electron Commun Eng. 2017; 12(3):104-109. doi: 10.9790/2834-120302104109

[38] Tummala SK, Kumar N, Padmaja, Swetha N, Nayak S. Validation of Potential Fishing Zone (PFZ) Advisories (2006-2007)

[39] [ Report No: INCOIS-ASG-PFZ-TR-08-2007]. Hyderabad; 2007.]

[40] Pillai VN, Nair PG. Potential fishing zone (PFZ) advisories-are they beneficial to the coastal fisherfolk? A case study along Kerala coast, South India. Biol Forum Int J. 2010; 2(2):46-55.

[41] Klemas V. Fisheries applications of remote sensing: An overview. Fish Res. 2013; 148:124-136. doi: 10.1016/j.fishres.2012.02.027

[42] Dutta S, Chanda A, Akhand A, Hazra S. Correlation of phytoplankton biomass (chlorophyll-a) and nutrients with the catch per unit effort in the PFZ forecast areas of Northern bay of bengal during simultaneous validation of winter fishing season. Turkish J Fish Aquat Sci. 2016; 16(4):767-777. doi: 10.4194/1303-2712-v16_4_03

[43] Jagannathan S, Samraj A, Rajavel M. Potential fishing zone estimation by rough cluster predictions. In: Proceedings of International Conference on Computational Intelligence, Modelling and Simulation; 2012. p. 82-87. doi: 10.1109/CIMSim.2012.34

[44] Pillai VN, Sivadas M, Santosh KM. Validation of potential fishing zone advisories in Minicoy region of Lakshadweep with special reference to skipjack tuna. In: Pillai NGK, Menon N., Pillai PP, Ganga U, editors. Management of Scombroid Fisheries. Kochi: Central Marine Fisheries Research Institute; 2002. p. 1-13. Available from: https://www.com/eprints.cmfri.org.in/4136 [Last accessed on 2021 Apr 24].

[45] Solanki HU, Pradhan Y, Dwivedi RM, Nayak S, Gulati DK, Somvamshi VS. Application of QuikSCAT SeaWinds data to improve remotely sensed potential fishing zones (PFZs) forecast methodology: Preliminary validation results. Indian J Mar Sci. 2005; 34(4):441-448.

[46] Arnone RA. Satellite-derived color-temperature relationship in the Alboran Sea. Remote Sens Environ. 1987; 23(3):417-437. doi: 10.1016/0034-4257(87)90099-X

[47] Laurs RM, Fiedler PC, Montgomery DR. Albacore tuna catch distributions relative to environmental features observed from satellites. Deep Sea Res Part A Oceanogr Res Pap. 1984; 31(9):1085-1099. doi: 10.1016/0198-0149(84)90014-1

[48] Karthikeyan K. Finding of Potential Fishing Zones Using Remote Sensing Techniques. Chennai; 2012. Available from: https://www.academia.edu/7216835/finding_of_potential_fishing_zones_using_remote_sensing_techniques [Last accessed on 2021 Apr 24].

[49] Tingote R, Mane U. Miscellaneous marine fishes caught under PFZ and Non-PFZ realm off Ratnagiri Coast, Maharashtra State, India. Int J Aquac Fish Sci. 2017; 3(2):30-34. doi: 10.17352/2455-8400.000025

[50] Wilson C, Morales J, Nayak S, Asanuma I. Ocean-colour radiometry and fisheries. In: Why Ocean Colour? The Societal Benefits of Ocean-Colour Technology. United States: IOCCG; 2008. p. 47-58.

[51] Chakraborty K, Maity S, Lotliker AA, Samanta A, Ghosh J, Masuluri NK. Modelling of marine ecosystem in regional scale for short term prediction of satellite-aided operational fishery advisories. J Oper Oceanogr. 2019; 12(Suppl 2):S157-S175. doi: 10.1080/1755876X.2019.1574951

[52] McClain EP, Pichel WG, Walton CC. Comparative performance of AVHRR-based multichannel sea surface temperatures. J Geophys Res. 1985; 90(C6):587-511, 601. doi: 10.1029/JC090iC06p11587

[53] Solanki HU, Dwivedi RM, Nayak SR. Synergistic analysis of SeaWiFS chlorophyll concentration and NOAA-AVHRR SST features for exploring marine living resources. Int J Remote Sens. 2001; 22(18):3877-3882. doi: 10.1080/01431160110069845

[54] Solanki HU, Dwivedi RM, Nayak SR, Somvanshi VS, Gulati DK, Pattnayak SK. Fishery forecast using OCM chlorophyll concentration and AVHRR SST: Validation results off Gujarat coast, India. Int J Remote Sens. 2003; 24(18):3691-3699. doi: 10.1080/0143116031000117029

[55] Nayak S, Solanki HU, Dwivedi RM. Utilization of IRS P4 ocean colour data for potential fishing zone - A cost benefit analysis. Indian J Mar Sci. 2003; 32(3):244-248.

[56] Dwivedi RM, Solanki HU, Nayak1 SR, Gulati D, Somvanshi VS. Exploration of fishery resources through integration of ocean colour with sea surface temperature: Indian experience. Indian J Mar Sci. 2005; 34(4):430-440.

[57] Sreedhar U. Remote sensing and fisheries. In: Handbook of Fishing Technology. 2002. p. 11. Available from: https://krishi.icar.gov.in/jspui/bitstream/123456789/47245/1/remote/sensing/andfisheries.pdf [Last accessed on 2021 Apr 24].

[58] Choudhury SB, Jena B, Rao MV, et al. Validation of integrated potential fishing zone (IPFZ) forecast using satellite based chlorophyll and sea surface temperature along the east coast of India. Int J Remote Sens. 2007; 28(12):2683-2693. doi: 10.1080/01431160600987878

[59] Swetha N, Kumar N, MNK, et al. Automated Identification of Oceanic Fronts for Operational Generation of Potential Fishing Zone (PFZ) Advisories. Hyderabad; 2017. Available from: https://www.com/moeseprints.incois.gov.in/4506 [Last accessed on 2021 Apr 24].

[60] Balaguru B, Ramakrishnan SS, Vidhya R, Thanabalan P. A comparative study on utilization of multi-sensorsatellite data to detect potential fishing zone (PFZ). Int Arch Photogramm Remote Sens Spat Inf Sci ISPRS Arch. 2014; 40(8):1017-1026. doi: 10.5194/isprsarchives-XL-8-1017-2014

[61] Andrews S, Varunbabu BS, Subash P, Swaminathan MR. Finding the high probabilistic potential fishing zone by accelerated SVM classification. Int J Inf Commun Technol. 2017; 11(4):576. doi: 10.1504/IJICT.2017.087460

[62] Natteshana NVS, Kumar NSA. Survey of various methods of potential fishing zone identification. Int J Control Theory Appl. 2016; 9(40):697-703.

[63] George G, Sarma K, Bharathi G, Kaliyamoorthy M, Krishnan P, Kirubasankar R. Efficacy of different modes in disseminating potential fishing zone (PFZ) forecasts - a case study from Andaman and Nicobar Islands reference points in Nicobar. Indian J Fish. 2014; 61(1):84-87.

[64] Solanki HU, Bhatpuria D, Chauhan P. Integrative analysis of AltiKa-SSHa, MODIS-SST, and OCM-Chlorophyll signatures for fisheries applications. Mar Geod. 2015; 38(Supp1):672-683. doi: 10.1080/01490419.2015.1010757

[65] MPEDA. Ban Period. Available from: https://www.mpeda.gov.in/mpeda/cms.php?id=ymfulxblcmlvza [Last accessed on 2020 May 20].

[66] ESSO-INCOIS. ESSO-INCOIS Annual Report 2018-19. Hyderabad; 2019. Available from: https://incois.gov.in/documents/annual_reports/2018-2019_english.pdf [Last accessed on 2021 Apr 24].

[67] NCAER. Impact Assessment and Economic Benefits of Weather and Marine Services. New Delhi; 2010. Available from: https://moes.gov.in/writereaddata/files/impactassessment-moes.pdf [Last accessed on 2021 Apr 24].

[68] MSSRF. Potential Fishing Zone Advisories and Conversion from Partnership in Gilakaladindi Village in Krishna District, Andhra Pradesh-a Preliminary Study. Chennai; 2014. Available from: https://incois.gov.in/documents/gilakaladindi_study.pdf [Last accessed on 2021 Apr 24].

[69] MSSRF. Impact of INCOIS Scientific Forecast Services Towards Improving the Lives and Livelihoods of Fishing Communities Across Tamilnadu and Puducherry. Chennai; 2014. Available from: https://incois.gov.in/documents/scientificforecastservices.pdf [Last accessed on 2021 Apr 24].

[70] Singh D. NAIP Component - 3: Strategies to Enhance Adaptive Capacity to Climate Change in Vulnerable Regions (Blue Ocean Innovation: MKRISHI® - Fisheries Service). Mumbai; 2012. Available from: https://incois.gov.in/documents/mkrishiblue_ocean_innovation_story.pdf [Last accessed on 2021 Apr 24].

[71] Chrispin CL, Ananthan PS, Krishnan M, Mahalakshmi P. Effectiveness of institutional arrangements for delivery of Potential Fishing Zone and Ocean State Forecast advisory services to fishers in Tamil Nadu. Agric Econ Res Rev. 2012; 25:485-493.

[72] NCAER. Economic Benefits of Dynamic Weather and Ocean Information and Advisory Services in India And Cost and Pricing of Customized Products and Services of ESSO NCMRWF & ESSO-INCOIS. New Delhi; 2015. Available from: https://incois.gov.in/documents/impactassessment-ncaer2015.pdf [Last accessed on 2021 Apr 24].

[73] NCAER. Estimating the Economic Benefits of Investment in Monsoon Mission and High Performance Computing Facilities. New Delhi; 2020. Available from: https://www.ncaer.org/wp/content/uploads/2020/07/1604990035report_moes2020.pdf [Last accessed on 2021 Apr 24].

[74] Santhanam H, Kundu SK. Assessment of socio-technical constraints of marine fishers in the utilisation of marine fishery advisories in Southern Odisha, India. Anthr Sci. 2022; 1:109-120. doi: 10.1007/s44177-022-00014-4

[75] Kundu SK, Santhanam H. Transitional contexts and transformational pathways through the utilisation of marine fishery advisories in Odisha, India: Challenges and way forward. Anthr Sci. 2024; 3(1-2):35-49. doi: 10.1007/s44177-024-00069-5

[76] Maity S, Kumar TS, Dutta S, Akhand A, Hazra S. Satellite based integrated potential fishing zone advisories: A feasibility analysis in the coastal water of West Bengal. Proc Zool Soc. 2015; 68(1):14-19. doi: 10.1007/s12595-013-0088-x

[77] Das S, Madhu VR, Sreejith PT, Jethva JK, Meenakumari B.Validation of Potential Fishing Zones along Saurashtra Coast, Gujarat Validation of Potential Fishing Zones along Saurashtra Coast, Gujarat. In: Coastal Fishery Resources of India Conservation and Sustainable Utilisation. Kochi; 2010. p. 138-144. Available from: https://www.researchgate.net/publication/258505375%0avalidation [Last accessed on 2021 Apr 24].

[78] George G, Krishnan P, Roy SD, et al. Validation of potential fishing zone (PFZ) forecasts from Andaman and Nicobar Islands. Fish Technol. 2013; 50:1-5.

[79] Sreekanth GB, Subramanian S, Lekshmi NM, Fernandes PM, Singh NP. Potential Fishing Zone Advisories - A Promising Tool for Precision Fishing. Goa; 2014. Available from: https://ccari.res.in/extension%20folder%20no.%2070.pdf [Last accessed on 2021 Apr 24].

[80] Sreekanth GB, Subramanian S, Lekshmi NM, Madhu VR, Fernandes PM, Singh NP. Validations on satellite based potential fishing zone advisories along Goa, South-West coast of India. Indian J Fish. 2016; 63(1):8-15. doi: 10.21077/ijf.2016.63.1.44455-02

[81] Devi GK, Ganasri BP, Dwarakish GS. Applications of Remote Sensing in Satellite Oceanography: A Review. Aquat Procedia. 2015; 4(Icwrcoe):579-584. doi:10.1016/j.aqpro.2015.02.075

[82] Masuluri NK, Nair P, Pillai VN, Kumar TS. Environmental benefits due to adoption of satellite-based fishery advisories. Fish Technol. 2018; 55:100-103.

[83] Kundu SK, Santhanam H. All pain and no gain: Factors impacting local and regional sustainability due to COVID- 19 pandemic with respect to the Indian marine fisheries. Curr Res Environ Sustain. 2021; 3:100086. doi: 10.1016/j.crsust.2021.100086

[84] Naskar P. A study of changing livelihoods of Odisha’s coastal fishing communities : Reasons and effects. Int J Humanit Soc Sci Invent. 2018; 7(6):14-17.

[85] DeviNongmaithem B, Ngangbam AK. Socioeconomic conditions and cultural profile of the fishers in India- a review. IOSR J Agric Vet Sci. 2014; 7(9):42-48. doi: 10.9790/2380-07914248

[86] Kundu SK, Santhanam H. Modelling the influence of marine fishery advisories on the reduction of carbon dioxide emissions for Odisha under varying climate change scenarios using CMIP models:An evidence-based approach for policymaking. In: Dhyani S, Adhikari D, Dasgupta R, Kadaverugu R,editors. Ecosystem and Species Habitat Modeling for Conservation and Restoration. Singapore: Springer Nature Singapore; 2023. p. 341-353. doi: 10.1007/978-981-99-0131-9_18

[87] Kundu SK. Evidence Based Assessment of the Utilisation of Geospatial Technology Products for Marine Fishing in Odisha India; 2023. Available from: https://shodhganga.inflibnet.ac.in/handle/10603/525516 [Last accessed on 2021 Apr 24].

[88] Santhanam H, Kundu SK, Ghosh A. A new transitions policy index to assess the co-benefits of infrastructural enhancement and technological development for Sustainable Marine Fisheries Management in India. Sustain Futur. 2025; 9:100812. doi: 10.1016/j.sftr.2025.100812

[89] Freebairn JW, Zillman JW. Economic benefits of meteorological services. Meteorol Appl. 2002; 9(1):33-44. doi: 10.1017/S1350482702001044

[90] Arnason R. Property rights in fisheries: Iceland’s experience with ITQs. Rev Fish Biol Fish. 2005; 15(3):243-264. doi: 10.1007/s11160-005-5139-6

[91] Pomeroy RS, Berkes F. Two to tango: The role of government in fisheries co-management. Mar Policy. 1997; 21(5):465-480. doi: 10.1016/S0308-597X(97)00017-1

[92] McCky BJ, Jentoft S. From the bottom up: Participatory issues in fisheries management. Soc Nat Resour. 1996; 9:237-250. doi: 10.1080/08941929609380969

[93] White AT, Courtney CA, Salamanca A. Experience with marine protected area planning and management in the Philippines experience with marine protected area planning and management in the Philippines. Coast Manag. 2002; 30(1):1-26. doi: 10.1080/08920750252692599

[94] Pinkerton EW. Local fisheries co-management: A review of international experiences and their implications for salmon management in British Columbia. Can J Fish Aquat Sci. 1994; 51(10):2363-2378. doi: 10.1139/f94-238

[95] Pomeroy RS. Devolution and fisheries co-management. In: Collective Action, Property Rights and Devolution of Natural Resource Management: Exchange of Knowledge and Implications for Policy. The International Aquatic Resources Management (ICLARM); 2001. p. 108-145. Available from: https://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=3d3adce14f7026147749adadf98888da?doi=10.1.1.298.4927&rep=rep1&type=pdf [Last accessed on 2021 Apr 24].

[96] Hinds L. World marine fisheries: Management and development problems. Mar Policy. 1992; 16(5):394-403. doi: 10.1016/0308-597X(92)90007-C

[97] Shixing H. Fritz LW, Lucas JR, editors.Reomte sensing in Chinese fisheries. In: XVIIth ISPRS Congress, Technical Commission VII: Interpretation of Photographic and Remote Sensing Data. Washington, DC; 1992. p. 66-68. Available from: https://www.isprs.org/proceedings/xxix/congress/part7/66_xxix-part7.pdf [Last accessed on 2021 Apr 24].

[98] Mansor S, Tan CK, Ibrahim HM, Shariff R. Satellite Fish Forecasting in South China Sea. 22nd Asian Conference on Remote Sensing. Vol. 2. 2001. p. 5-9. Available from: https://www.crisp.nus.edu.sg/-acrs2001/pdf/015venka.pdf [Last accessed on 2021 Apr 24].

[99] Dimech M, Darmanin M, Philip Smith I, Kaiser MJ, Schembri PJ. Fishers’ perception of a 35-year old exclusive fisheries management zone. Biol Conserv. 2009; 142(11):2691-2702. doi: 10.1016/j.biocon.2009.06.019

[100] Karunakaran D, Mohanty BP. Information technology - potential application in fisheries. Environ Ecol. 2014; 24(2):359-365.

[101] ECOSOC. Special Edition: Progress towards the Sustainable Development Goals. United Nations Economic and Social Council; 2019. Available from: https://www.com/undocs.org/e/2019/68 [Last accessed on 2021 Apr 24].

[102] FAO. Exploring SDG 14.b and its proposed indicator 14.b. 1. In: Franz N, editor. FAO Fisheries and Aquaculture Proceedings. Vol 59. Rome:Food and Agriculture Organization of the United Nations; 2018. p. 1-39. Available from: https://www.fao.org/3/ca0140en/ca0140en.pdf [Last accessed on 2021 Apr 24].