Investigation of Factors Affecting on Land Use Change in Khorasan Razavi
IntroductionThe soil is the bedrock of all human productive activities and the foundations of many of the great and ancient civilizations that have maintained soil conservation. Population growth and shortage of new land for agriculture, large areas of forests have become degraded and transformed into agricultural land and, consequently, agricultural land has become industrial and urban. The major impact of land use change on the physical and social environment is an incentive for research in relation to the reasons for land use change and its effects. Modeling and analyzing these factors can help to plan and plan agricultural land. One of the issues that have faced many problems in developing countries over the last few decades, the growing urbanization and urbanization that have led to the emergence of huge immigration trends in urban areas around the world. Immigration to cities in these countries has caused such problems as incompatibility in utilization, urban environs, and the lack of urban services to immigrants, the creation of marginalization, the destruction of agricultural lands around urban development, and the modification of its use to industrial and urban uses. In Iran, as in other developing countries, this trend has existed.
On the other hand, the lack of serious attention to rural areas and agriculture, as well as the reduction of the share of villages and rural areas in the strategies of economic development and industrial development has caused the productive forces of these points to be able to provide livelihoods and to cities And areas around cities. Investigating the changes in land cover and land use from distant lands on the surface of the earth, which is usually made in two ways the first type is the changes that are made by natural factors such as erosion and flood occurrence, and the second type is the changes that occur by humans. Recently, in most parts of the world, human activities have been one of the main factors influencing land use change.
Materials and MethodsThe data required for this study was completed by collecting 70 questionnaires in 2017. In the two-stage Hackman model, factors that can affect farmer's decision to change land management practices in agriculture, in the form of independent variables in the probit pattern and the factors that can affect the amount of change in use, in the set of independent variables in the linear regression model.
The second pattern is added by adding a new variable called MRI (IMR), which is constructed using the parameters, met the first pattern. The set of independent variables will be linked to the first stage. The dependent variable in the probit pattern consists of a binary variable with values 1 and zero. Accordingly, the dependent variable is the vector of the values 0 and 1 in which the number 1 is the decision to carry out the activity and the zero number means the decision to not perform that activity. This variable is based on the dependent variable in the Tobit model. Hence, for Yi whose value is greater than zero, the number 1 is set to zero, and for Yi whose value is zero, it remains zero. In this way, the independent variable of the probit pattern is constructed for all observations.
In the above models, β coefficients of pattern parameters, IMR Reverse Mills Ratio, V and Ei are error sentences. In the first step, the Hackman method, the probit pattern is estimated using the maximum exponential method.
In the second step, the Hackman method, The linear regression model is estimated for observations whose Yi is greater than zero¡ At this stage, the inverse of the Mills ratio is added to the set of independent variables in the regression model. The coefficient of this variable expresses the error caused by the sample selection. If the coefficient of this variable is statistically larger than zero, Deleting the zero views from the set of views will cause the skew of the estimated parameters of the template and if the coefficient of this variable is not meaningful, Deleting zero observations, although not leading to the error of the estimated parameters, But it will lead to the loss of performance of the estimator. The presence of the inverse of the Mills ratio in the linear regression model eliminates the existence of the heterogeneity of the primary model variance and allows the use of OLS. Therefore, it is possible to differentiate factors affecting agricultural land use change from the impact of factors on agricultural land use change. Static software has been used to estimate the two-stage Heckman model in this study.
Discussion of Results &
ConclusionThe first phase of the Hackman's two-stage method is the decision stage to make land use change.
In other words, this is the stage of the intention. Based final effects of significant variables with positive effect, with an increase in the number of farmers in the family, assuming that other factors are constant, The probability of a decision to change the use of agricultural land increases by 0.18 units. For the variable number of agricultural land plots, one increase in the number of land shares, the willingness to decide to change the use of agricultural land is increased by 0.53 units. Also, the level of education and literacy level of a farmer increases by one unit (for example, one section) in his education, his desire to increase the change of user by as much as 0.23 unit's increases. In general, for the variables mentioned, we can say that the population of the farmer's family, The number of land plots and farmer education levels have a direct relationship with the farmer's willingness and decision to change their utilities That is, with the increase, the change in agricultural land use is also increasing. On the other hand, regarding meaningful variables with negative effect and their final effect, it can be concluded that farmer's income has a negative effect on agricultural land use change so that by increasing one unit in farmer's income, assuming that other factors are constant, the person's desire to change the use of agricultural land is reduced by 0.8 units. In other words, in summary, one can say that income, The price of a major agricultural product and the amount of rainfall have a negative relationship with the change in agricultural land use Namely, as these three factors are strengthened, the willingness of the farmer to change the use of agricultural land will be less. According to the results obtained from the probit model, the coefficient of determination of the Mac-Faden model is 0.48 and false R ^ 2 is equal to 0.61, which shows good fit of the model. Therefore, these variables in the second stage of the model are estimated to The OLS method is eliminated, and the number of altered agricultural land lots in the second stage is considered as a dependent variable.
In the second Hackman stage, the presence of the Mills Image Ratio (IMR) in linear regression eliminates the model's heterogeneity and makes use of the linear pattern and serves as a variable in the model.
According to the findings of this research, in order to solve the problem of agricultural land use change, proper control and planning in relation to urban migration and urban areas, To create more incentives for the farmer through appropriate policies in the price of products, Encouraging the farmer to use high-yielding inputs to earn more money, Provide water resources management policies for farmers to better access and use water resources and adopt policies to reduce farmer's costs of production in all areas, Shipping costs and initial charges are offered.
Journal of Environmental Studies, Volume:44 Issue: 1, 2018
99 - 111
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