Optimalisasi ArcGIS dan Google Earth Pro untuk Meningkatkan Produktivitas Usahatani Desa Suratmajan

Authors

  • Abi Al Mukarom Author
  • Umi Rohmatul Ummah Author

Keywords:

ArcGIS, Google Earth Pro, Farm Productivity, Geographic Information System, Data-Driven Agriculture

Abstract

Farm productivity is strongly influenced by resource management quality and decision-making accuracy. The utilization of geospatial technologies such as ArcGIS and Google Earth Pro offers an alternative approach to support data-driven agricultural systems at the village level. This study aimed to analyze the optimization of ArcGIS and Google Earth Pro in improving farm productivity in Suratmajan Village. A descriptive qualitative approach supported by simple spatial analysis was employed. Data were collected through field observations, semi-structured interviews, coordinate documentation, Google Earth Pro imagery analysis, document reviews, and thematic mapping using ArcGIS. Data analysis involved data reduction, source triangulation, spatial overlay, and SWOT analysis. The results indicate that spatial information utilization enhances farm planning through land boundary mapping, production road accessibility identification, water resource mapping, and prioritization of cultivation interventions. ArcGIS and Google Earth Pro also facilitate coordination among stakeholders in village agricultural management. Major challenges include limited geospatial literacy, the absence of standardized land databases, and inadequate institutional support for data management. Therefore, the development of a geospatial-based village agricultural information system should be supported by continuous training, periodic data updates, and institutional strengthening to sustainably improve farm productivity.

Author Biographies

  • Abi Al Mukarom

    S1 Sosial Ekonomi Pertanian

  • Umi Rohmatul Ummah

    S1 Sosial Ekonomi Pertanian

References

[1] M. Weiss, F. Jacob, and G. Duveiller, “Remote sensing for agricultural applications: A meta-review,” Remote Sensing of Environment, vol. 236, pp. 1–15, 2020.

[2] M. Amani, S. Mahdavi, B. Brisco, and J. Huang, “Remote sensing applications for precision agriculture: A review,” Remote Sensing, vol. 12, no. 19, pp. 1–24, 2020.

[3] P. A. Longley, M. F. Goodchild, D. J. Maguire, and D. W. Rhind, Geographic Information Systems and Science, 5th ed. Hoboken, NJ, USA: Wiley, 2021.

[4] P. Bolstad, GIS Fundamentals: A First Text on Geographic Information Systems, 7th ed. White Bear Lake, MN, USA: Eider Press, 2022.

[5] M. de Smith, M. Goodchild, and P. Longley, Geospatial Analysis: A Comprehensive Guide, 7th ed. Leicester, UK: Winchelsea Press, 2021.

[6] J. B. Campbell and M. Shin, Introduction to Remote Sensing, 6th ed. New York, NY, USA: Guilford Press, 2020.

[7] J. Chang, “Integration of GIS and Earth observation technologies for sustainable agriculture,” International Journal of Agricultural Technology, vol. 17, no. 4, pp. 1123–1137, 2021.

[8] B. Pham, T. Nguyen, and H. Tran, “Spatial information systems in agricultural planning and development,” Sustainability, vol. 14, no. 8, pp. 1–18, 2022.

[9] R. Bareth, M. Aasen, and M. Bendig, “Advances in precision agriculture using geospatial technologies,” Agronomy, vol. 11, no. 5, pp. 1–20, 2021.

[10] R. P. Sishodia, R. L. Ray, and S. K. Singh, “Applications of remote sensing in precision agriculture: A review,” Remote Sensing, vol. 12, no. 19, pp. 1–29, 2020.

[11] L. A. Cisternas, A. Velásquez, and M. Caro, “Precision agriculture and sustainable crop management: A review,” Agricultural Systems, vol. 187, pp. 1–12, 2020.

[12] S. Wolfert, L. Ge, C. Verdouw, and M. J. Bogaardt, “Big data in smart farming: Challenges and opportunities,” Agricultural Systems, vol. 189, pp. 1–13, 2021.

[13] W. Dong, H. Yang, and J. Liu, “Geospatial technologies for agricultural sustainability assessment,” Journal of Environmental Management, vol. 276, pp. 1–11, 2020.

[14] R. Kitchin, The Data Revolution: Power, Data and Knowledge Infrastructure, 2nd ed. London, U.K.: Sage Publications, 2021.

[15] M. J. Kraak and R. E. Roth, Thematic Cartography and Geovisualization, 5th ed. New York, NY, USA: Routledge, 2021.

[16] G. Brown and M. Kyttä, “Key issues and priorities in participatory mapping,” Landscape and Urban Planning, vol. 204, pp. 1–11, 2020.

[17] S. Khanal, J. Fulton, and S. Shearer, “An overview of precision agriculture technologies and challenges,” Computers and Electronics in Agriculture, vol. 170, pp. 1–13, 2020.

[18] M. F. Goodchild and W. Li, “GeoAI: Artificial intelligence and the future of geographic information science,” International Journal of Geographical Information Science, vol. 35, no. 8, pp. 1–17, 2021.

[19] T. Hengl, J. M. de Jesus, and G. B. M. Heuvelink, “Soil mapping and digital agriculture applications,” Geoderma, vol. 376, pp. 1–14, 2020.

[20] W. Dong, X. Zhang, and H. Liu, “Spatial decision support systems for sustainable agricultural development,” Sustainability, vol. 12, no. 18, pp. 1–16, 2020.

[21] M. K. McCall, “Participatory mapping and community-based geographic information systems,” Cartography and Geographic Information Science, vol. 48, no. 3, pp. 201–214, 2021.

[22] A. Leszczynski, “Data ethics, privacy and governance in digital geographies,” Progress in Human Geography, vol. 44, no. 6, pp. 1–15, 2020.

Downloads

Published

15-06-2026

Issue

Vol. 1 No. 2 (2025): AgroTalk : Journal of Agricultural Science

Section

Articles

License

Copyright (c) 2025 AgroTalk : Journal of Agricultural Science

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

Al Mukarom, A., & Rohmatul Ummah, U. (2026). Optimalisasi ArcGIS dan Google Earth Pro untuk Meningkatkan Produktivitas Usahatani Desa Suratmajan. AgroTalk : Journal of Agricultural Science, 1(2), 1-12. https://ejournal.rumahtani.com/index.php/AgroTalk/article/view/30

Similar Articles

You may also start an advanced similarity search for this article.