Assessing the Influence of Land Use/Land Cover Alteration on Climate Variability: An Analysis in the Aurangabad District of Maharashtra State, India

• Published in: Sustainability 2022-01, Vol.14 (2), p.642
• Main Authors: Masroor, Md, Avtar, Ram, Sajjad, Haroon, Choudhari, Pandurang, Kulimushi, Luc Cimusa, Khedher, Khaled Mohamed, Komolafe, Akinola Adesuji, Yunus, Ali P., Sahu, Netrananda
• Format: Article
• Language: English
• Subjects: Agricultural land; Agriculture; Algorithms; Barren lands; Classification; Climate change; Climate variability; Correlation analysis; Drought; Earth; Land cover; Land use; Landsat; Machine learning; Precipitation; Rain; Regression analysis; Rivers; Soil moisture; Soil temperature; Support vector machines; Sustainability; Urbanization; Variables; Wind; Wind speed
• ISSN: 2071-1050; 2071-1050
• DOI: 10.3390/su14020642

Examining the influence of land use/land cover transformation on meteorological variables has become imperative for maintaining long-term climate sustainability. Rapid growth and haphazard expansion have caused the conversion of prime agricultural land into a built-up area. This study used multitemporal Landsat data to analyze land use/land cover (LULC) changes, and Terra Climate monthly data to examine the impact of land transformation on precipitation, minimum and maximum temperature, wind speed, and soil moisture in the Aurangabad district of Maharashtra state in India during 1999–2019. Multiple linear regression and correlation analysis were performed to determine the association among LULC classes and climatic variables. This study revealed rapid urbanization in the study area over the years. The built-up area, water bodies, and barren lands have recorded a steep rise, while the agricultural area has decreased in the district. Drastic changes were observed in the climatic variables over the years. The precipitation and wind speed have shown decreasing trends during the study period. A positive relationship between soil moisture and agricultural land was found through a correlation analysis. Conspicuous findings about the positive relationship between the agricultural land and maximum temperature need further investigation. A multiple linear regression analysis demonstrated a negative relationship between the built-up area and precipitation. The intensity of the precipitation has reduced as a consequence of the developmental activities in the study area. Moreover, a positive relationship was observed between the built-up area and maximum temperature. Thus, this study calls for policy implications to formulate a futuristic land-use plan considering climate change projection in the district.