Spatio-temporal patterns and dynamics of sensitivity to sandification, in the Drylands of South Punjab, Pakistan

• Published in: GeoJournal 2024-01, Vol.89 (1), p.15, Article 15
• Main Authors: Mazhar, Nausheen, Nasar-u-Minallah, Muhammad, Shirazi, Safdar Ali, Mahmoudi, Peyman, Firoozi, Fatemeh
• Format: Article
• Language: English
• Subjects: Arid lands; Arid zones; Decision support systems; Desertification; Dynamics; Environmental Management; Geography; Human Geography; Land cover; Land use; Landsat; Landsat satellites; Monitoring; Policy making; Regions; Remote sensing; Sensitivity analysis; Social Sciences; Temporal patterns
• ISSN: 1572-9893; 0343-2521; 1572-9893
• DOI: 10.1007/s10708-024-11014-9

One of the most serious ecological problems affecting drylands worldwide is sandification, due to exacerbation of the desertification process. As sandified land grows larger, the potential for agriculture decreases. Particularly in Pakistan, desertification is also a significant issue, with numerous natural and human-caused contributors. Desertification often occurs in Pakistan's south Punjab's dry lands, and regularly monitoring the area's sandification dynamics can assist in mitigating the problem. The purpose of this study is to determine the sensitivity to the sandification phenomenon in South Punjab drylands (Rajanpur, Rahim Yar Khan, and Bahawalpur) Pakistan. ALOS PALSAR DEM of 12.5 m resolution and Level 2 Landsat 5, 7, and 8 data (1988, 2001, and 2018) were utilized to conduct this research. The sensitivity to sandification was determined using land use land cover ( LULC ) , slope, and aspect as the determining variables. These variables were separately integrated into ArcGIS using the weighted sum approach for the years 1988, 2001, and 2018. The analysis of sensitivity to sandification found that insensitive land expanded by 47 percent between 1988 and 2018, whereas very low sensitive and low sensitive classifications declined by -5.95 percent and -9.23 percent, respectively. The moderately sensitive area to sandification saw the largest percentage change between 1988 and 2018, changing by 1095.52%. The desertified land saw the second-largest percentage change, changing by 521.58%. However, the highly sensitive to sandification class showed the greatest percentage decrease (-53.65%). The most significant factor found to have an impact on the local sandification dynamics was LULC. By continuously monitoring the dynamics of sandification, the region's desertification intensity can be reduced. A Decision Support System (DSS) can be developed for this purpose through further study. Policymakers can use the DSS findings to assist them in creating strategies for reducing desertification in this region.