Document Type : Research Paper
Authors
1 Department of Biosystems Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
2 Department of Biosystems Engineering, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Iran, Ahvaz, Iran
3 Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran, Email
Abstract
Keywords
Main Subjects
Land represents a fundamental, finite, and irreplaceable natural resource that must be conserved and sustained for future generations. This critical resource is susceptible to pressures arising from both anthropogenic factors, such as population growth, and natural processes, including drought and erosion. Land use and land cover change (LULCC) are recognized as key drivers influencing global environmental change, impacting a wide array of environmental and natural resource attributes, including water quality, air and land resources, and ecosystem functions (Canaz et al., 2017). Timely and accurate detection of LULCC is therefore essential for enabling effective natural resource management and promoting sustainable land use practices. In recent decades, the increasing demand for food, energy, and living space driven by a growing global population has placed considerable strain on Earth’s limited resources. The escalating exploitation of natural resources to meet the needs of an expanding population represents a major challenge facing humanity today (Jiang et al., 2020). This intensifies pressure on ecosystems, leading to climate change, alterations in biogeochemical cycles (e.g., water and nutrient cycles), biodiversity loss, and significant LULCC (Yi-ming et al., 2022). Ahvaz County, one of Iran’s most important industrial and agricultural regions, and a major oil production hub, has faced numerous environmental, social, and economic challenges in recent years. A major contributing factor to this situation is the change in LULCC.
This study investigated land use and land cover (LULC) within Ahvaz County, classifying the area into four primary categories: built-up areas, barren lands, agricultural lands, and water bodies. Landsat satellite imagery was employed as the primary data source, utilizing Landsat 7 ETM+ and Landsat 8 OLI imagery acquired for four distinct time points: 2000, 2007, 2014, and 2020. The satellite images underwent rigorous preprocessing steps, including radiometric and atmospheric correction, to minimize distortions and enhance data quality. Subsequently, LULC classification was performed using the Maximum Likelihood Classification (MLC) algorithm. MLC was selected due to its demonstrated effectiveness and high accuracy in land cover mapping applications. Analysis of historical weather patterns indicated that March typically exhibits stable and favorable weather conditions in Khuzestan province. Therefore, satellite imagery acquired during March was preferentially used to facilitate consistent monitoring of LULC throughout the study period. The initial image preprocessing involved converting digital numbers to spectral radiance and correcting the images using the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) atmospheric correction model. FLAASH is particularly effective for correcting visible, near-infrared, and shortwave infrared wavelengths. Following atmospheric correction, images were mosaicked and cropped to the extent of the study area using ENVI 5.6 software. The classification accuracy was assessed using the Kappa coefficient and Overall Accuracy index, with values ranging from 87.23% to 93.23% for Kappa and 89.56% to 94.89% for Overall Accuracy, confirming the reliability of the classification results. These two metrics provide valuable information in evaluating classification models. Considering both metrics allows for a more comprehensive understanding of the models’ accuracy and predictive power, leading to more accurate and reliable results.
The classified LULC maps for the years 2000, 2007, 2014, and 2020 are presented in Figures 2 to 4. Analysis of these maps reveals notable changes in LULC patterns over the study period. In 2000, agricultural land cover was less extensive and more fragmented compared to subsequent years. Between 2000 and 2020, agricultural land increased by approximately 277%, built-up areas expanded by 297%, and water bodies slightly increased by 6%. In contrast, barren land decreased by 33%. The sharp increase in urban areas led to the loss of high-quality agricultural lands around cities. Specifically, the area of agricultural land in Ahvaz County increased from approximately 115 thousand hectares in 2000 to 319, 362, and 319 hectares in 2007, 2014, and 2020, respectively. This increase was primarily attributed to the conversion of barren land into agricultural land. However, in 2020, the trend of agricultural land expansion stopped and the area under cultivation of agricultural land decreased compared to 2014. This decline can be attributed to factors such as severe droughts, reduced availability of irrigation water resources, and continued expansion of urban areas. A more in-depth analysis of the factors influencing agricultural development during this period, including droughts, water policies and urban planning, is crucial for a better understanding of this phenomenon and future projections. Throughout the study period, built-up areas increased from 1.24% of Ahvaz county in 2000 to 3.27% in 2020. The majority of new construction occurred in the vicinity of urban area, often encroaching upon barren and agricultural land. These findings are consistent with other studies. For example, Ahmed et al. (2014) reported a 41.27% expansion of Lahore’s urban area between 2000 and 2020 accompanied by a 13.42% decrease in vegetation cover, 31.2% decrease in barren land, and 51.6% decrease in water water bodies. Similarly, Salem et al. (2020) found that approximately 9,600 hectares of agricultural land around Cairo, Egypt, were converted to urban use between 2010 and 2018, representing an average annual loss of 1,200 hectares.
Remote sensing technologies provide a cost-effective and accurate means for monitoring LULCC over extensive areas. These tools have become indispensable for natural resource management and environmental monitoring applications. The results of this study, covering the period from 2000 to 2020, indicate substantial LULCC in Ahvaz County. Specifically, compared to 2000, agricultural and built-up areas land increased by approximately 277 and 297 percent, respectively, while barren land decreased by 33 percent. These changes have resulted in alterations to land cover composition, landscape structure, and potentially ecosystem functions. The expansion of agricultural land has led to increased demand on natural resources, particularly water, placing strain on available water supplies. This limitation has likely contributed to the observed decrease in agricultural land area in 2020 compared to 2014. Concurrently, the expansion of built-up areas has resulted in the loss of valuable agricultural land, particularly in areas surrounding urban centers. The findings highlight the need for sustainable land use planning and water resource management to mitigate the negative impacts of rapid urbanization and agricultural expansion. Improved water resource management, including the implementation of efficient irrigation techniques, sustainable agricultural practices (utilizing precision agriculture techniques, soil and salinity management, etc.), and controlled urban development through regulations restricting urban expansion into agricultural lands, are key solutions to prevent the decline of agricultural land, mitigate agricultural environmental impacts, and ensure food security. This study provides valuable insights for policymakers to implement regulations that balance urban development with agricultural sustainability. Based on the findings of this research, it is suggested that future studies utilize machine learning models to predict future land use changes. Furthermore, assessing the impact of land use change on the regional microclimate, soil quality and erosion, quantity and quality of surface and groundwater resources, biodiversity, and the consequences for rural-urban migration patterns and demographic shifts is deemed essential.
Conceptualization, K.A., A.A and S.H.; methodology, K.A. and A.A; software, K.A. and S.H; validation, K.A., A.A and S.H.; formal analysis, K.A and A.A.; investigation, K.A.; resources, K.A. and A.A; data curation, A.A.; writing—original draft preparation, K.A; writing—review and editing, A.A and S.H; visualization, K.A.; supervision, A.A.; project administration, A.A.; funding acquisition, A.A. All authors have read and agreed to the published version of the manuscript. All authors contributed equally to the conceptualization of the article and writing of the original and subsequent drafts.
All data generated or analyzed during this study are available from the corresponding author on request
The authors express their gratitude to the Vice Chancellor for Research and Technology of Shahid Chamran University of Ahvaz, Iran, for providing financial support through the research grant (No. SCU.AA98.29747).
The authors avoided data fabrication, falsification, plagiarism, and misconduct.
The author declares no conflict of interest.
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