Forecast of changes in land areas, population growth, dynamics of construction of buildings and structures

. In the scientific work, in the period of 2011-2020, on the example of the Bostonliq district of the Tashkent region, the number of inhabitants in agriculture and the land areas, structures and buildings used by them, the annual changes of the land area per person were studied, and based on the analysis, the improvement of the living conditions and well-being of the population during the years 2021-2030 forecasts for the increase were made and recommendations were developed.


Introduction
In the research work, the methodology of forming the geodatabase of state cadastres was first developed.As a result, a database was formed based on recommendations on the formation of state cadastres.In addition to future information integration and interactive service provision, this database allowed obtaining high-precision results by studying state cadastral objects, creating their mathematical model and forecasting.In addition, a system for classifying the names of state cadastral objects with special abbreviations and assigning them identification numbers was developed [1][2].
Important decisions are being made and measures are being implemented by the President and the Government of the Republic of Uzbekistan to improve the living conditions of the population and develop entrepreneurship.One such decision is "Important measures aimed at the welfare of the population and the development of entrepreneurship".In these measures, the need to effectively use more than 300,000 hectares of new land was noted.80,000 hectares of this land belong to reduced cotton and grain fields, and were given to 254,000 people on the basis of open competition.This indicator corresponds to an additional area of 500 hectares per district.
Based on purposeful research and created information base, data was modeled and highperformance forecasting was carried out.For this purpose, a program was created on the topic of "The Program for Studying the Dynamics of Land Fund Changes and Land Monitoring of the Republic of Uzbekistan".This program received a copyright certificate No. DGU 15846 dated April 30, 2022.With the help of the program, an effective result was achieved on information visualization and their integration [3][4][5].

Methods
In the implementation of cadastral works, the growth rate of agricultural lands, population, buildings and structures, and land area per person in Bostonliq district compared to previous years was studied in the period 2011-2020.Through the average annual change coefficient, the change between 2021 and 2030 was predicted, and the coefficient of agricultural land use was determined.The following designations were used: a-lands used in agriculture (ha); b -population; s -the number of buildings and structures; d -land area per district population (ha).
The data obtained from the survey of agricultural land, population, buildings and structures and per capita land area are presented in Table 1 below. .The coefficients of annual change of agricultural land in the district were determined according to the following formula: where a' is the area of land used in agriculture last year, a''-land area used for agriculture in the next year.The coefficients of annual change of the population of the district were determined according to the following formula: where b' is the population of the previous year, b'' is the population of the next year.The coefficients of annual change of buildings and structures in the district were determined according to the following formula: where c' is the number of buildings and structures in the previous year, c'' is the number of buildings and structures in the next year.
The coefficients of annual change of land area per district population were determined according to the following formula: where d' is the land area per district population in the previous year, d'' is the land area per district population in the next year.
Average annual change coefficients were calculated based on the calculation of the annual change coefficients for the above indicators during 2011-2020.Average annual change coefficients for agricultural land are determined by the following formula: where  2 -is the average annual change coefficient of the land area used in agriculture during the years 2011-2020, a1i-is the annual change coefficient of the land area used in agriculture in i-year.
The coefficients of average annual change in the population of the district are determined according to the following formula: where  2 -is the average annual change coefficient of the population during the years 2011-2020, b1-i is the annual change coefficient of the population in the i-th year (i=2011..2020).
The coefficients of average annual change in the number of buildings and structures in the district are determined using the following formula: where  2 is the average annual change coefficient of the number of buildings and structures during 2011-2020,  1 is the annual change coefficient of the number of buildings and structures in the i-th year (i=2011..2020).
Average annual change coefficients of land area per district population are determined using the following formula: where  2 is the average annual change coefficient of land area per district population during 2011-2020,  1 is the annual change coefficient of land area per district population in year i (i=2011..2020).
Based on the average annual change coefficients determined above, the land used in agriculture for 2022-2030, the number of inhabitants, buildings and structures, and the land area corresponding to the population of the district are: where a'-the area of land used for agriculture in the previous year,  ′′ −the area of land used for agriculture in the next year. ′′ = ′ •  2 (11) where ′ is the number of buildings and structures in the previous year,  ′′ is the number of buildings and structures in the next year.
where d'-the land area corresponding to the population of the district in the previous year, d''-the land area corresponding to the population of the district in the next year.
The land area corresponding to the population of the district is divided by the land area used in agriculture, and the coefficient of agricultural land use is determined.[6][7][8][9][10][11][12]:

Results
The following algorithm was developed to solve the problem under consideration in the research work: The information included in the developed program was deeply analyzed and systematized, and as a result of entering into the program, the dynamics of changes in the land used for agriculture, the number of people, buildings and structures over the years and the forecast for the next 10 years were obtained (Fig. 2, Fig. 3, Fig. 4, Fig. 5 , Figure 6, Figure 7, Figure 8) [13][14][15][16][17][18][19][20][21].

Conclusion
The following conclusions were drawn from the obtained numerical and graphical results: • During 2011-2030, the area of land used in agriculture will decrease by 0.00069735%-0.00278975%per year; • In the period 2011-2030, the population will grow significantly by 0.021444042%-3.623266085%per year; • Between 2011 and 2030, the number of buildings and structures will increase by 0.013635139%-0.022725981%per year; • During the years 2011-2030, the land area per district population will increase significantly by 0.021444042%-3.623266085%per year; • During 2011-2030, the coefficient of land use in agriculture will increase by 0.022839148%-3.626156855%per year.

Fig. 2 .
Fig. 2. Title of the program on forecasting the dynamics of land area and population growth.

Fig. 3 .Fig. 4 .
Fig. 3.In 2011-2021, the dynamics of changes in the land used in agriculture, population, and buildings.

Fig. 8 .
Fig. 8. Diagram of the dynamics of changes in land area per district population.

Table 1 .
Dynamics of data on land used in agriculture, population, structures, land area per person