Agricultural Land Abandonment and Farmers’ Perceptions of Land Use Change in the Indus Plains of Pakistan: A Case Study of Sindh Province

Habibullah Rajpar, Anlu Zhang, Amar Razzaq, Khalid Mehmood, Maula Bux Pirzado and Weiyan Hu
Additional contact information
Habibullah Rajpar: College of Land Management, Huazhong Agricultural University, No. 1, Shizishan Street, Hongshan District, Wuhan 430070, China
Anlu Zhang: College of Land Management, Huazhong Agricultural University, No. 1, Shizishan Street, Hongshan District, Wuhan 430070, China
Amar Razzaq: College of Economics and Management, Huazhong Agricultural University, No. 1, Shizishan Street, Hongshan District, Wuhan 430070, China
Khalid Mehmood: Adaptive Research Farm Chakwal, Directorate General Agriculture (Extension and Adaptive Research), Government of Punjab, Lahore 54000, Pakistan
Maula Bux Pirzado: Department of Economics, Sindh Agricultural University, Tandojam Hyderabad 70060, Pakistan
Weiyan Hu: College of Land Management, Huazhong Agricultural University, No. 1, Shizishan Street, Hongshan District, Wuhan 430070, China

Sustainability, 2019, vol. 11, issue 17, 1-19

Abstract: Agriculture is the mainstay of Pakistan’s economy. However, it has been noticed that farmers are increasingly giving up agriculture in favor of non-agricultural activities. This study was conducted in the Khairpur district of Sindh province, which is part of the Indus Plains in Pakistan. The main purpose of the study was to investigate the current and future land use change (LUC) trends and to study farmers’ perceptions of the causes and consequences of LUC and agricultural land abandonment (ALA) in the study area. The study used field survey data and secondary data obtained from the government sources. The results show that agricultural land in the region has decreased by about 9% in the past two decades. Survey data analysis confirms this because more than 80% of farmers believe that agricultural land in the area has declined over time. In addition, farmers believe that socioeconomic and environmental changes are the main reasons for LUC and ALA. We used a logistic regression model to determine the factors that influence farmers’ decisions to sell agricultural land for other uses. The results show that the age, income, land ownership, farm inheritance by successors, social networks and lack of basic facilities in the study area are the main determinants of farmers’ decisions to sell agricultural lands. In particular, farmers’ integration into the social network and their belief that the farm will be inherited by heirs reduces the possibility of selling land. As for the consequences of LUC and ALA, the results indicate that farmland prices, weeds infestation, urban diffusion, and pressure on existing infrastructure have increased in the study area. In addition, the results show that the prospects of farming in the area remain grim as most farmers indicated that they were willing to abandon agricultural lands in favor of other revenue generation activities. The study suggests that policymakers should pay close attention to controlling rapid LUC and ALA to keep lands green.

Keywords: agriculture land abandonment; land use change; future land use; logistic regression model; social networks; Khairpur; Sindh (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/17/4663/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/17/4663/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:17:p:4663-:d:261435

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().