Integrating GIS and Remote Sensing Data for Detecting Change in Agricultural Land during 1985-2024 in Qassim Region, Saudi Arabia

doi:10.21608/ejec.2024.381190

|
|
|
How to cite
RIS EndNote BibTeX APA MLA Harvard Vancouver
|
Share

	Integrating GIS and Remote Sensing Data for Detecting Change in Agricultural Land during 1985-2024 in Qassim Region, Saudi Arabia
Article 4, Volume 16, Issue 2, October 2024, Page 51-72 PDF (4.53 MB)
Document Type: Peer-reviewed articles
DOI: 10.21608/ejec.2024.381190
View on SCiNiTO
Abstract
The Qassim region is one of the most significant agricultural areas in Saudi Arabia, particularly for date cultivation. This study investigates changes in agricultural land in the Qassim region between 1985 and 2024, utilizing Geographic Information System (GIS) technology and remotely sensed data to analyze and quantify agricultural land transformations. Key factors contributing to these changes are identified, providing valuable insights into environmental dynamics and land cover patterns. This research aims to inform policymakers and land managers, facilitating sustainable agricultural practices and effective land management strategies. An object-based data analysis approach was employed for thematic mapping, considering both the spectral and spatial properties of the data extracted from the NDVI index. This method enables more accurate classification by leveraging the contextual information of image objects, resulting in improved extraction of agricultural land. Supervised classification was applied to the NDVI indices produced from Landsat images captured in the years 1985, 2000, 2015, and 2024 to identify agricultural lands. The results indicate that the agricultural landscape of the Qassim region in Saudi Arabia underwent significant changes over the past two decades. Agricultural lands declined between 2000 and 2015 due to government policies to rationalize water-intensive practices, but more recent data from 2024 shows a 14.4% increase in agricultural area to 2,438.16 square kilometers, attributed to strategic priorities focused on sustainable resource management, food security, rural development, and agricultural productivity. The expansion has been spatially distributed, with the Agricultural Development Fund playing a key role through promoting rational resource use, technology application, and investment facilitation.
Keywords
Remotely Sensed Data; Geographic Information Systems; Qassim; Agriculture Land
Main Subjects
Environmental changes in different eco-systems.


References
References: - Al-Daghiri, A. A. (2019). The physical geography of the Qassim region: Saudi Arabia. Dar Al- Assar Al-Alami for Publishing and Distribution, and the Arab Society Library for Publishing and Distribution, Amman, Jordan. - ALfehaid, S., Abdelmageed, A., & Abd-Elmoniem, E. (2022). Effect of Chemical, Organic and Bio Fertilizers on Growth, Yield and Quality of Cucumber Plant (Cucumis sativus L.) grown under Greenhouse Conditions. Journal of Sohag Agriscience (JSAS), 7(1), 28-40. doi: 10.21608/jsasj.2022.245699 - Alharbi M, Alharbi F, AlTuwayjiri A, Alharbi Y, Alhofair Y, Alanazi A, AlJlajle F, Khalil R, Al-Wutayd O. (2022). Assessment of health-related quality of life in patients with heart failure: a cross-sectional study in Saudi Arabia. Health Qual Life Outcomes. 30; (1), 20:128. - Al-Harbi, K.M.. (2010). Monitoring of agricultural area trend in Tabuk region – Saudi Arabia using Landsat TM and SPOT data. The Egyptian Journal of Remote Sensing and Space Science. 13. 37-42. 10.1016/j.ejrs.2010.07.005. - Almalki, Raid, Mehdi Khaki, Patricia M. Saco, and Jose F. Rodriguez. (2022). "Monitoring and Mapping Vegetation Cover Changes in Arid and Semi-Arid Areas Using Remote Sensing Technology: A Review" Remote Sensing 14, no. 20: 5143. https://doi.org/10.3390/rs14205143 - Alotaibi, Bader Alhafi, Mirza Barjees Baig, Mohamed M. M. Najim, Ashfaq Ahmad Shah, and Yosef A. Alamri. (2023) . "Water Scarcity Management to Ensure Food Scarcity through Sustainable Water Resources Management in Saudi Arabia" Sustainability 15, no. 13: 10648. https://doi.org/10.3390/su151310648 - Alqurashi, A.; Kumar, L. (2013). Investigating the use of remote sensing and GIS techniques to detect land use and land cover change: A review. Adv. Remote Sens. 2, 193–204. - Al-Wabel, Mohammad & Sallam, Abdelazeem & Usman, Adel & Ahmad, Mahtab & El-Naggar, Ahmed & EL-Saeid, Mohamed & Al-Faraj, Abdulelah & El-Enazi, Khaled & Alromian, Fahad. (2017). Trace metal levels, sources, and ecological risk assessment in a densely agricultural area from Saudi Arabia. Environmental Monitoring and Assessment. 189. 10.1007/s10661-017-5919-1. - Bahamdan, Nada, Jamil, Abdul Hamid. (2022) Monitoring the change in agricultural areas in the Qassim region (Kingdom of Saudi Arabia) using remote sensing techniques and geographic information systems 1973 - 2020 AD. Journal of Nature, Life and Applied Sciences Volume (6), Issue (4): December 30, 2022, pp: 1 – 25 - Bégué, Agnès & Lebourgeois, Valentine & Bappel, Eric & Todoroff, Pierre & Pellegrino, Anne & Baillarin, Florence & Siegmund, Bernard. (2010). Spatio-temporal variability of sugarcane fields and recommendations for yield forecast using NDVI. International Journal of Remote Sensing. 31. 5391–5407. 10.1080/01431160903349057. - Berberoglu, S., Satir, O., & Atkinson, P. M. (2009). Mapping percentage tree cover from Envisat MERIS data using linear and nonlinear techniques. International Journal of Remote Sensing, 30(18), 4747–4766. https://doi.org/10.1080/01431160802660554 - Buraidah City Profle. M Ministry of Municipal and Rural Afairs. United Nations Human Settlements Programme (UN-Habitat). ISBN: 978-6038279-03-8. 2019. https://unhabitat.org/sites/default/fles/2020/04/burai dah.pdf. Accessed 11 Nov 2021. - Cui, X.; Gibbes, C.; Southworth, J.; Waylen, P.(2013). Using remote sensing to quantify vegetation change and ecological resilience in a semi-arid system. Land , 2, 108–130. - FAO. (2022). World Food and Agriculture – Statistical Yearbook 2022. Rome. https://doi.org/10.4060/cc2211en - General Authority for Statistics. (2022). Agricultural statistics publication. https://www.stats.gov.sa/en/1176 - Huang, Zhi & Jia, Xiuping. (2012). Integrating remotely sensed data, GIS and expert knowledge to update object-based land use/land cover information. International Journal of Remote Sensing. 33. 905-921. 10.1080/01431161.2010.536182. - International Food Policy Research Institute (IFPRI). (2017). Global Food Policy Report; IFPRI: Washington, DC, USA; Available online: http://www.Ifpri.Org/publication/2017-global-food-policy-report (accessed on 12 October 2017). - Jeevalakshmi, D.; Reddy, S.N.; Manikiam, B. (2016) Land cover classification based on NDVI using LANDSAT8 time series: A case study Tirupati region. In Proceedings of the International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 6–8 April 2016; pp. 1332–1335. - Liping, C.; Yujun, S.; Saeed, S.(2018). Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques—A case study of a hilly area, Jiangle, China. PLoS ONE 2018, 13, e0200493. - Ministry of Economy and Planning. Fifth Development Plan 1990–1995; Ministry of Economy and Planning: Riyadh, Saudi Arabia, 1990. - Ministry of Economy and Planning. Fourth Development Plan 1985–1990; Ministry of Economy and Planning: Riyadh, Saudi Arabia, 1985. - Ministry of Economy and Planning. Sixth Development Plan 1995–2000; Ministry of Economy and Planning: Riyadh, Saudi Arabia, 1995. - Ministry of Environment, Water and Agriculture. (2018). [National Water Strategy 2030]. https://www.mewa.gov.sa - MohanRajan, S.N.; Loganathan, A.; Manoharan, P. (2020). Survey on Land Use/Land Cover (LU/LC) change analysis in remote sensing and GIS environment: Techniques and Challenges. Environ. Sci. Pollut. Res. 27, 29900–29926. - Monsha'at. (2023). SME Monitor Monsha'at Quarterly Report Q3 2023. Retrieved from https://www.monshaat.gov.sa/sites/default/files/2023-11/EN%20Monsha%27at%20Q3%20SME%20Monitor_0.pdf . - Morawitz, D.F.; Blewett, T.M.; Cohen, A.; Alberti, M. (2006) Using NDVI to Assess Vegetative Land Cover Change in Central Puget Sound. Environ. Monit. Assess. 114, 85–106. - Potapov, P.; Hansen, M.C.; Stehman, S.V.; Loveland, T.R.; Pittman, K. (2008). Combining MODIS and Landsat imagery to estimate and map boreal forest cover loss. Remote Sens. Environ. 112, 3708–3719. - Qassim Municipality, 2023. https://www.qassim.gov.sa/ - Raziq, A.; Xu, A.; Li, Y.; Zhao, Q. (2016). Monitoring of land use/land cover changes and urban sprawl in Peshawar City in Khyber Pakhtunkhwa: An application of geo-information techniques using of multi-temporal satellite data. J. Remote Sens. 5, 174. - Richards, J.A.; Jia, X. Remote Sensing Digital Image Analysis: An Introduction. (2006), 4th ed.; Springer: Secaucus, NJ, USA; p. 263. - Stavi, I., Roque de Pinho, J., Paschalidou, A. K., Adamo, S. B., Galvin, K., de Sherbinin, A., Even, T., Heaviside, C., & van der Geest, K. (2022). Food security among dryland pastoralists and agropastoralists: The climate, land-use change, and population dynamics nexus. The Anthropocene Review, 9(3), 299-323. https://doi.org/10.1177/20530196211007512 - Tewabe, Dires & Adametie, Temesgen. (2020). Assessing land use and land cover change detection using remote sensing in the Lake Tana Basin, Northwest Ethiopia. Cogent Environmental Science. 6. 10.1080/23311843.2020.1778998. - The General Authority for Statistics, (2023) - The National Center for Meteorology (NCM). (2023). https://www.spa.gov.sa/ - Un-habitat. (2020). State of Urban Development in Al-Qassim (2020) Key Statistics in 13 Urban Areas.https://unhabitat.org/sites/default/files/2021/08/state_of_urban_development_in_al-qassim.pdf - Vibhute, A.D.; Gawali, B.W. Analysis and Modeling of Agricultural Land use using Remote Sensing and Geographic Information System: A Review. Int. J. Eng. Res. Appl. 2012, 3, 81–91. - Youssef, Ahmed M., Mazen M. Abu Abdullah, Biswajeet Pradhan, and Ahmed F. D. Gaber. (2019). "Agriculture Sprawl Assessment Using Multi-Temporal Remote Sensing Images and Its Environmental Impact; Al-Jouf, KSA" Sustainability 11, no. 15: 4177. https://doi.org/10.3390/su11154177 - Yu, J.; Wu, J. (2018). The Sustainability of Agricultural Development in China: The Agriculture Environment Nexus. Sustainability, 10, 1776.
Statistics Article View: 248 PDF Download: 277