Abstract
Climate change is of paramount importance for ecosystems, especially in arid and semi-arid areas. The major aim of the current study is to monitor vegetation and land use changes, and run drought assessment using field and satellite data. The main precipitation proportions in the studied region are influenced by the Westerlies, meaning that any variations in these precipitation systems significantly impact the region. The utilized data entailed MODIS images for 16- and 8-day intervals between 2000 and 2013, TM and OLI sensor images recorded in 1985 and 2013, precipitation network data of TRMM satellite between 2000 and 2013, and synoptic data 32-year period. The Mann–Kendall (MK) test was used to monitor temporal changes in meteorological station data in annual and seasonal scales. The results indicated that there was a downward trend in 50% of the meteorological stations in the annual scale. This falling trend was statistically significant at the level of 95%. At the end, drought was assessed using PCI, APCI, VSWI, and NVSWI. The results showed that vegetation, forest, pasture, and agriculture areas recorded the strongest correlations with initial precipitation at the beginning of the study. Based on interactions among various factors influencing vegetation indices, reduction in green vegetation, especially the area of oak forests in the studied period, is around 95,744 hectares, which is attributed to lower precipitation rate. Increasing of agricultural land and water zones during the studied years is the result of human management and depends on how surface and underground water resources are exploited.
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Availability of data and material
The Landsat, MODIS, and TRMM images analyzed during the current study are available in the https://earthexplorer.usgs.gov, http://rever.echo.nasa.gov and https://giovanni.gsfc.nasa.gov/giovanni datasets repository respectively, and stationary data are available in IRIMO.
Code availability
The software was used in this study was R, which has been used as a programming language and free software for statistical computing and graphics.
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Heidari, S., Shamsipour, A., Kakroodi, A.A. et al. Monitoring land cover changes and droughts using statistical analysis and multi-sensor remote sensing data. Environ Monit Assess 195, 618 (2023). https://doi.org/10.1007/s10661-023-11195-9
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DOI: https://doi.org/10.1007/s10661-023-11195-9