In urban lands, decision makers and planners need accurate information about land cover. Remote sensing data is one of the valuable and valuable information sources for identifying land covers and their changes. Land use changes are one of the most critical global problems. This process has many effects on the environment. One of the important effects of land use changes is the change in hydrological conditions. Land use changes are one of the most apparent effects of human intervention on the planet and can affect human health and ecological systems. Considering the ever-increasing changes in land use and the need for managers to be aware of the changes and transformations that have occurred for policy-making and solution-thinking to solve the existing problem, it seems necessary to reveal the changes in order to determine the process of changes over time. On the other hand, predicting and modeling future changes is also essential to know the quantity and quality of possible future changes. The model means the facts that exist in a system, or it can be said that it is a simplified representative of the whole system. Land use change models are tools to support analyses related to the factors and consequences of repeatable land use changes and complement our existing mental abilities in analyzing land use change and making more informed decisions.The spatial modeling of land use changes is a technique for understanding land use change processes in terms of location and amount of change. The land use change modeler (LCM) provides a detailed analysis of land changes by creating maps of use changes, diagrams, transitions of use class, and their flow.

The modeling steps include: examining changes, modeling transfer potential, modeling land cover changes, and assessing the correctness of modeling. In this regard, the purpose of this study is to investigate the land use changes in Khosefcountyduring the years (2008-2022) and to predict the land use changes in the studied area, using the logistic regression method in the LCM model.

Materials & Methods:

Khosufcounty consists of two parts: the central part and the Mazhan plain. In Khoor wetland, one of the most giant desert reeds in South Khorasan province, is also located in this county. This area has a permanent vegetation cover and is a habitat for migratory birds in the winter season, as well as a source of fodder and water for the herders of the area. For this purpose, the land use map was revealed for the studied area for the three years of 2008, 2013 and 2022. The accuracy of the maps was evaluated by the error matrix method. In this method, three sub-models of barren to agriculture, barren to residential and agriculture to barren land use transfer rate and four variables including: digital model of height, distance from road, distance from residential areas and distance from agricultural land for a calibration period of 2008-2013 are used. Using the Markov chain, the changes of each user were determined, and finally, the land use maps for 2022 were predicted using a complex prediction model.

Results & Discussion:

During this period, the most changes during the studied period included the conversion of barren lands to agricultural use. After running the models, the results of the 2022 simulation were compared with the ground reality map, After ensuring the accuracy of the model and considering the accuracy of the modeling, the prediction of the land use map for the year 2040 was made. Based on this, in 2040, land use changes will be more in agricultural and residential uses. The projected area for these uses will be 10488.18 hectares for agricultural use, 750.04 hectares for urban use, and 1932.15714 hectares for barren use.

Also, in this study, the trend of changes in the Khoorwetland was examined and analyzed. As it was said, Khoor wetland is one of the most extensive desert reeds in South Khorasan province and also the most extensive reeds of Lut desert in Iran, which has a vegetation cover of sedum with brackish water. NDVI index was used to investigate its condition. The vegetation area of Khoor wetland in 2008 was 117.75 hectares, which has decreased to 70.83 hectares in 2022. Also, the prediction of the vegetation area of Khoor wetland for the year 2040 was 48.48 hectares.

Conclusion:

In this research, a land change modeler was used to model the land use changes of Khosufcounty. The variables that were used in this research included: distance from agricultural land, distance from residential areas, and distance from the road, and also the sub-models obtained in this research were barren transfer, agricultural transfer, and residential transfer. Based on the results of the land cover maps of 2008 and 2013 in this study, it was shown that agricultural lands have increased the most over time, followed by residential areas, It should be noted that according to the studies done, the green index is mainly related to agricultural lands or artificial factors, not pastures and reeds, which is not of much value in terms of the environment, the green cover of the agricultural land. For the accuracy and efficiency of the model and the benefits of the model, based on this analysis, it was determined that the green cover area of Khoor wetland decreased to 46.92 hectares between 2008 and 2022. It was also predicted for the year 2040 that if the change process continues as in the past, the green cover area of the lagoon will reach 48.48 hectares. Due to the recent drought and water shortages, land use changes cannot be continued because these changes cause water to be taken from wells and reservoirs, and with the continuation of the drought, there will be pressure on the static level of underground water. Bring and prevent the runoff from entering the estuary lagoon and cause irreparable damage to the environment, so these drastic changes in land use must be managed, and agriculture should be replaced with low-water crops and new irrigation methods.