Land use and land cover (LULC) change are one of the most important signals of regional environmental monitoring and study. Recently, the pull of capital cities has snowballed, an increasing number of people moving to the cities, especially in developing countries. Consequently, as more people arrive at cities, the more pressure will be on land. Land price getting high and constructions try using open green areas. A wide variety of green areas of different sizes will be solve many urban diseases and ecological problems at the same time improve the quality and life of urban residents, as urban green area provides various ecosystem services. The green area includes parks, woodlands, nature reserves and bare lands. With the population increase and expansion of cities, an increasing amount of open area, woodland and bare land has been converted into construction land, buildings due to the increasing demands and residential land. For the accuracy assessment, we applied an automatically supervised classification using the software QGIS 3.18. The reference values were based on ground truth data and visual interpretation.
Article develops recommendations for the use of reducing (incentive) coefficients in land tax calculation of on agricultural lands, taking into account the quality of land and interrelation between an increase and decrease in soil fertility, which leads to an increase in land tax. In calculating land taxation, this is formed based on the normative value of agricultural land. The calculation of the normative value of agricultural land is inextricably linked with the soil quality index (SQI), which determines the fertility of the soil. As decreasing and increasing coefficients in the growth of productivity in 11 agriultural farms of “Pakhtaobod” massif of Nishan adiminstrative district of Kashkadarya province, when the normative value changed for the better, the amount of land tax decreased by 18.933.000 UZS (19.5%) and in 10 agriсultural farms the increase in the amount of land tax by 7.070.820 UZS (15.8%) in the negative condition.
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