نوع مقاله : نامههای علمی
نویسندگان
1 استادیار و عضو هیاتعلمی گروه مهندسی نقشهبرداری، دانشکده فنی و مهندسی، دانشگاه گلستان، ایران
2 دانشجوی دکتری، دانشکده منابع طبیعی، دانشگاه ملایر، ایران.
3 استادیار و عضو هیات علمی، پژوهشگاه نیرو، تهران، ایران.
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Soil surface moisture is a crucial factor in determining the extent of forest canopy cover and is influenced by land surface temperature and other factors like solar radiation and slope aspect. This study utilized remote sensing technology to quantify soil moisture and investigate its correlation with forest canopy cover. To this end, the TOTRAM soil moisture model and the FCD vegetation cover model were developed in the Sepiddasht forest area of Lorestan Province, Iran, employing Landsat 8 and 9 imagery acquired as a time series in 2015 and 2023. The FCD model incorporated four vegetation, soil, shadow, and thermal indices, along with the advanced shadow index and co-registered shadow index, utilizing appropriate thresholds. The results demonstrated a strong Pearson correlation coefficient between soil moisture (dependent variable) and temperature, vegetation cover, and forest density: 0.709, 0.813, and 0.691 in 2015, and 0.816, 0.875, and 0.702 in 2023, respectively. These findings indicate a significant relationship between soil moisture patterns and changes in vegetation cover. A strong correlation was observed between LST-NDVI and soil moisture. For example, a decrease in greenness, as evidenced by a decline in NDVI from 0.24 in 2015 to 0.19 in 2023, coupled with an increase in temperature from 29.95 to 33.62 degrees Celsius, resulted in a decrease in average soil moisture from 52% to 43%. Analysis of the results obtained from the TATRAMT model further supports the conclusion that soil moisture is highly dependent on variations in temperature and canopy cover.
کلیدواژهها [English]