Investigation of Land use Changes and Climatic Components in Meshkinshahr City

Subject Areas : Application of computer in water and soil issues

Batool Zeynali ¹ , Elham Mollanouri ² , Shiva Safary ³

1 - Associate Professor, Department of Natural Geography, Faculty of Literature and Humanities, University of Mohaghegh Ardabili, Ardabil, Iran.
2 - Ph.D. Student in Hydrology and Meteorology, Mohaghegh Ardabili University, Ardabil, Iran.
3 - MSc of Mohaghegh Ardabili University, Ardabil, Iran.

Received: 2022-07-31 Accepted : 2022-10-16 Published : 2023-03-21

Keywords: land use, Climate Change, TOTRAM algorithm, NDVI,

Abstract :

Introduction: Climate change has negative effects on water resources and human societies, especially in arid and semi-arid regions. Remote sensing is widely used in studies such as monitoring the environment, agriculture, and climate of the earth. This technology makes it possible to research and investigate such studies in large areas with the high spatial and temporal resolution, especially inaccessible areas or areas that do not have ground measurement stations (such as synoptic stations) provides. Considering the expansion of the cold semi-desert climate in the northwestern region of the country and the changes in land use in the Meshkinshahr region in recent years, the purpose of this research is to investigate the interrelationship between climatic components of temperature, precipitation, and soil moisture with land use changes. Methods: Meshkinshahr city is located in the northwest of Iran and is one of the important cities of Ardabil province. In the present research, the studied area using satellite images of Landsat 5 for 2002 and Landsat 8 for 2021 in seven classes of irrigated agriculture, rain-fed agriculture, residential area, water areas, snow cover, good pasture, and poor pasture for investigation of the changes in land-use has been classified. In the following, temperature and precipitation components (along with verification with ground data) respectively using the single-channel algorithm and GPM database and soil moisture using the optical thermal algorithm (TOTRAM) by applying LST and NDVI parameters as a time series were reviewed for the years 2002, 2006, 2011, 2016, 2019 and 2021. Result: By examining the resulting maps, it has been observed that there have been significant changes in different land uses, and most of these changes have been related to the increase of irrigated agricultural lands and poor pastures, and the loss of quality pastures. Also, temperature and precipitation fluctuations in the studied years are quite clear and do not have a regular trend, so for example, in 2011, a sudden increase in precipitation to the amount of 46 mm is observed. But the minimum temperature compared to its maximum in different years shows a greater increase compared to 2002. Vegetation and soil fertility do not have a particular upward or downward trend and show different values ​​in different years, but the maximum vegetation cover, i.e. value 1 in the case of the NDVI index, is observed in 2002. Conclusion: According to the results and fluctuations in the values ​​of climatic components, especially sudden changes in some years, signs of climate change can be observed in the region, but a definite opinion cannot be expressed regarding the trend of land use changes and climate changes. Examining the results shows that land use changes, especially in the agricultural sector, can be affected by climatic conditions. The dependence of climatic components on each other and the influence of soil moisture and vegetation on these components are other results of this study. So, with the increase in temperature, we see a decrease in the amount of humidity and the level of vegetation. The times when soil moisture is higher than in other years, due to the cooling role of evaporation, low temperature, and vegetation cover are favorable. As a result, there is a clear dependence between the different components and the change in one parameter affects the other parameters, but it seems that the temperature component plays a more colorful role than the other parameters.

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