Published March 15, 2026 | Version v1
Journal article Open

Geomatics for forest protection, improved agricultural production and hunger/malnutrition reduction among farm-families in South, South Nigeria

Authors/Creators

  • 1. Department of Geoinformatics and Surveying, University of Nigeria, Nsukka, Enugu State, Nigeria

Contributors

  • 1. Department of Geomatics, University of Benin, Benin City, Edo State, Benin
  • 2. Department of Surveying and Geoinformatics, Federal University of Technology, Owerri, Imo State, Nigeria
  • 3. Department of Geoinformatics and Surveying, University of Nigeria, Nsukka, Enugu State, Nigeria
  • 4. Department of Urban and Regional Planning, Federal University of Technology, Owerri, Imo State, Nigeria
  • 5. Department of Agricultural Economics, University of Agricultural and Environmental Sciences, Umuagwo, Imo State, Nigeria
  • 6. Department of Computer Information Systems, Prairie View A&M University, Texas, United States
  • 7. Department of Agribusiness, Federal University of Technology, Owerri, Imo State, Nigeria
  • 8. Department of Agricultural Extension, Federal University of Technology, Owerri, Imo State, Nigeria

Description

This study examined spatial tools for forest protection, agricultural production and hunger/malnutrition reduction in South-South Nigeria. A total of 450 farmers were interviewed with questionnaires and oral discussions. Data collected were analyzed descriptively. Results showed that the geomatics tools for improvement include Geographic Information System (GIS) (91.1%), remote sensing (94.4%), global positioning system (GPS) (97.4%) and others. The agricultural production challenges faced include the use of geomatics tools such as poor knowledge of soil conditions (M= 2.50), unreliable rainfall (M= 2.74), pest/disease outbreak (M= 2.61), land degradation/declining soil productivity (M= 3.81) among others. Geomatics reduces hunger and malnutrition and improves agriculture by production of land suitability maps (M= 3.41), identification of appropriate fertilizers to apply (M= 3.25), identification of drought-prone areas (M = 3.25), provision of weather forecasts (M= 2.91), detection of pests/diseases (M = 2.30) among other roles. It supports forest protection by forest mapping (M = 3.50), monitoring deforestation (M= 3.45), detection of fire outbreaks (M = 3.05), biodiversity conservation (M= 2.84), illegal logging and law enforcement (M= 3.10), and urban encroachment on forest areas (M= 3.45) among other roles. The challenges faced include limited awareness and capacity building (84.4%), weak extension services (87.5%), high cost of technology (91.1%), inadequate infrastructure (94.4%) among others. To address the challenges, the following measures are suggested: use of GIS for site-specific management (87.5%), farm-level decision support systems (94.4%), encourage early warning systems and capacity building/awareness programmes (95.5%).

published by the International Journal of Biosciences | IJB

 

Files

IJB-V28-No3-p139-154.pdf

Files (1.1 MB)

Name Size Download all
md5:05e672e9fd2a581d118ecd84d000c3de
1.1 MB Preview Download

Additional details

Identifiers

URL
https://innspub.net/geomatics-for-forest-protection-improved-agricultural-production-and-hunger-malnutrition-reduction-among-farm-families-in-south-south-nigeria/

Dates

Available
2026-03-15
article published

References

  • Asner GP, Clark JK, Mascaro J. 2012. High-resolution mapping of forest carbon stocks in the Colombian Amazon. Biogeosciences 9, 2683–2696.
  • Atzberger C. 2013. Advances in remote sensing of agriculture: context description, existing operational monitoring systems and major information needs. Remote Sensing 5(2), 949–981.
  • Basso B, Cammarano D, Ritchie JT. 2020. Remote sensing applications in precision agriculture. Journal of Agricultural Science 12(3), 45–60.
  • Battersby J, Peyton S. 2014. The geography of urban food insecurity in Cape Town, South Africa. South African Geographical Journal 96(1), 1–23.
  • Beaulac J, Kristjansson E, Cummins S. 2009. A systematic review of food deserts, 1966–2007. Preventing Chronic Disease 6(3), A105.
  • Chiaka JC, Zhen L, Xiao Y, Hu Y, Wen X, Muhirwa F. 2024. Spatial assessment of land suitability potential for agriculture in Nigeria. Foods 13(4), 568.
  • Chukwuma EC, Afolabi OOD, Okonkwo CC, Olamigoke OO, Okonkwo CE. 2024. Application of geospatial technology and decision model in the development of improved food security index. Scientific Reports 14, 30204.
  • Chuvieco E, Giglio L, Justice C. 2014. Global characterization of fire activity: toward defining fire regimes from Earth observation data. Global Change Biology 20(2), 345–365.
  • D'Haese M, Vandeplas A, Speelman S, Van Campenhout B. 2020. A GIS-based approach to improve food distribution networks in rural areas. Journal of Spatial Science 65(2), 243–259.
  • Elwood S, Goodchild MF, Sui DZ. 2020. Prospects for open access geospatial data. Transactions in GIS 24(1), 1–20.
  • FAO, IFAD, UNICEF, WFP, WHO. 2023. The state of food security and nutrition in the world 2023. Food and Agriculture Organization of the United Nations.
  • FAO. 2018. The state of food and agriculture: migration, agriculture and rural development. Food and Agriculture Organization of the United Nations.
  • FAO. 2020. Global forest resources assessment 2020. Rome: Food and Agriculture Organization of the United Nations.
  • FAO. 2023. Food security definition and concepts. Food and Agriculture Organization of the United Nations.
  • Gebbers R, Adamchuk VI. 2010. Precision agriculture and food security. Science 327(5967), 828–831.
  • Gebbers R, Adamchuk VI. 2018. Precision agriculture and food security. Science Advances 4(8), eaar1379.
  • Hansen MC, Potapov PV, Moore R, Hancher M, Turubanova S, Tyukavina A, Townshend JR. 2013. High-resolution global maps of forest cover change. Science 342(6160), 850–853.
  • Ikelegbe A. 2013. The politics of oil resource conflicts in the Niger Delta region of Nigeria. African Studies Review 56(1), 123–143.
  • Kerekes J. 2021. Remote sensing limitations in tropical environments. International Journal of Remote Sensing 42(6), 2150–2167.
  • Khadka R, Bhatta B. 2020. Challenges and opportunities in the integration of GIS in environmental management. Journal of Geospatial Science 8(2), 123–135.
  • Lawrence D, Saha S, Sanchez M. 2021. Linking satellite data and forest conservation policy. Environmental Research Letters 16(4), 045015.
  • Longley PA, Goodchild MF, Maguire DJ, Rhind DW. 2015. Geographic information science and systems. Wiley.
  • Mbuli TR, Chirwa PW, Moyo S. 2022. Institutional constraints to geospatial technology adoption in sub-Saharan Africa. African Journal of Science, Technology, Innovation and Development 14(1), 45–57.
  • Miller HJ, Goodchild MF. 2015. Data driven geography. GeoJournal 80, 449–461.
  • Morland K, Wing S, Roux AD. 2002. The contextual effect of the local food environment on residents' diets: the Atherosclerosis Risk in Communities study. American Journal of Public Health 92(11), 1761–1768.
  • Nguyen LT, Tran DT, Pham HT. 2021. Capacity building for GIS applications in agriculture: barriers and strategies. Journal of Agricultural Informatics 12(3), 78–89.
  • Nwilo PC, Badejo OT. 2006. Impacts of oil spills along the Nigerian coast. Association for Environmental Health and Sciences Journal 8(2), 95–100.
  • Nwokeabia OD. 2002. Forestry and food security in Nigeria. Food and Agriculture Organization.
  • Paneque-Gálvez J, McCall MK, Napoletano BM. 2014. Small drones for community-based forest monitoring. Remote Sensing 6(12), 12885–12912.
  • Rahut DB. 2023. Agricultural practices and food security in developing countries. Sustainable Agriculture Studies.
  • Rasolofoson RA. 2018. Impacts of forests on children's dietary diversity. Frontiers in Sustainable Food Systems.
  • Rosenstock TS. 2019. The future of food and agriculture: Trends and challenges. Annual Review of Environment and Resources 44, 431–463.
  • Shiferaw A, Tesfaye K, Belay K. 2020. GIS data integration challenges in multi-sectoral planning. Geoinformatics Journal 6(1), 89–102.
  • Sieber R, Johnson PA. 2015. Place, participation and geographic information: a historical exploration of public participation GIS (PPGIS). In: Craglia M, McLaren R, Weiner D (Eds), Spatially enabled society, Springer, 41–66.
  • Thornton PK, Ericksen PJ, Herrero M, Challinor AJ. 2019. Climate variability and food security risk. Annual Review of Environment and Resources 44, 117–144.
  • Turner BL, Lambin EF, Reenberg A. 2021. The emergence of land change science for sustainable landscape planning. Proceedings of the National Academy of Sciences 118(7), e2018177118.
  • Turner W, Spector S, Gardiner N. 2003. Remote sensing for biodiversity science and conservation. Trends in Ecology and Evolution 18(6), 306–314.
  • Watts M. 2008. Blood oil: The anatomy of a petro-insurgency in the Niger Delta, Nigeria. Foucault Studies 5, 50–80.
  • World Bank. 2017. ICT in agriculture: Connecting smallholders to knowledge, networks, and institutions. World Bank Publications.
  • World Food Programme (WFP). 2021. Hunger map and early warning systems. Rome: WFP.
  • Zhang C, Kovacs JM. 2019. The application of small unmanned aerial systems for precision agriculture: A review. Precision Agriculture 20(2), 1–20.
  • Zhang N, Wang M, Wang N. 2002. Precision agriculture: A worldwide overview. Computers and Electronics in Agriculture 36(2–3), 113–132.
  • Zhang X. 2022. Remote sensing and crop yield estimation: a review. Agronomy 12(3), 550.
  • Zhang Y, Zhao L, Wang X. 2023. Access to satellite imagery and its impact on precision agriculture adoption. Remote Sensing Letters 14(4), 367–379.