Effects of developmental level on forest area changes of rural areas in Arasbaran by satellite images

Livelihood of rural people depends on the use of land and the exploitation of natural resources and forest. Therefore, their activities can have significant effects on these resources. The magnitude of these effects and changes in the level of the forest are affected by the development level of the villages. The main objective of this study is to investigate the relationship between the development level of forest villages and the extent of forest degradation in the Arasbaran region. The research method is descriptive-analytical and library method is used to collect the research data. The data were collected and analyzed in two sections: determining the degree of development of villages and preparing the forest area changes. At first, the studied villages were classified in terms of degree of development based on socioeconomic, health education and infrastructural indicators in five developmental categories with Morris incoherent coefficients. In the next step, Landsat satellite images were used to determine the level of forest changes. Correlation coefficient was calculated between the amount of forest degradation in each village with variables such as rural development index, opportunity cost, altitude and population size. The results showed that from 15 villages, five villages were classified as developed villages and one village was classified as non-developed or deprived villages. Between 2007-2017, the forest area of Arzin, Kelaleh Ulya, Kharil and Ibrahim Biglou villages showed an increase about 74.58, 56.41, 55.55 and 48.51 hectares, respectively. Based on the results, the mean of forest area changes at the 1997-2007 and 2007-2017 was -6.08 and -32.5 ha, respectively. Based on the results, there was a significant difference between the changes of the first period and the second period with a confidence of 99%. The correlation coefficient showed that the rural development index and the village population had positive correlation with the forest degradation. In contrast, the cost of opportunity in each village and altitude the height of the sea level had a weak correlation with the rate of forest degradation in each village.