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Study On Dynamic Evolution Of Cultivated Land Pressure In Main Grain Producing Areas

Posted on:2023-02-27Degree:MasterType:Thesis
Country:ChinaCandidate:L Z WuFull Text:PDF
GTID:2530306848492384Subject:Applied Economics
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Cultivated land resources reflect the coordination degree of regional human land relationship to a certain extent.The dynamic evolution process of regional cultivated land pressure reflects the pressure degree of regional cultivated land resources and food security in different periods.Based on the comprehensive consideration of regional cultivated land quality and grain economic acquisition capacity,this thesis modifies the original cultivated land pressure index based on the perspective of food security,and then measures the cultivated land pressure of 13 provinces in the main grain producing areas,and studies the temporal and spatial differentiation characteristics of cultivated land pressure in each Province.Then it explores the influencing factors of cultivated land pressure in the main grain producing areas,and finally uses the deep learning model to predict the future cultivated land pressure in the main grain producing areas.It can provide a basis for the land management departments of all provinces in the main grain producing areas to formulate follow-up cultivated land protection policies.The policy suggestions are of great significance to alleviate the pressure of regional cultivated land and the contradiction between man and land.Research findings:(1)In the early stage of the study period,the number of cultivated land in each province decreased sharply due to the development process of urbanization and industrialization from 2000 to 2002.In 2003-2007,the number of cultivated land resources and various input factors of agriculture were also low due to the implementation of measures such as returning farmland to forest in most provinces.The minimum number of cultivated land resources in many provinces during the study period was also at this stage.From the absolute value of the increase in the number of cultivated land resources,Heilongjiang Province is the province with the largest increase in cultivated land resources.In 2020,it has 19.533 million hectares of cultivated land,an increase of 9.92 million hectares of cultivated land resources compared with 2000.The cultivated land area per capita in Northeast China is 26.0 hectares,which is larger than that in other cultivated areas in China.(2)The value of cultivated land pressure index corrected by cultivated land quality coefficient and grain economic acquisition rate is larger than the traditional cultivated land pressure index.The traditional cultivated land pressure index is mainly related to cultivated land resources and grain yield.With the development of agriculture,the index shows a downward trend and fluctuates steadily;However,the revised cultivated land pressure index shows a relatively fluctuating trend in different provinces,and the interannual variation range is large.On the whole,the cultivated land pressure index of the provinces in the main grain producing areas during the study period is declining.By 2020,except Hebei,Liaoning and Sichuan,other provinces are in the state of no pressure on cultivated land pressure,that is,the revised cultivated land pressure index is below 0.9.The cultivated land pressure indexes of Hebei,Liaoning and Sichuan in 2020 are 1.4,1.15 and 1.3 respectively.Therefore,the vulnerability of food security exists and the pressure on cultivated land in some provinces is high.With the restoration of cultivated land use and the increase of agricultural production investment,it is conducive to reducing the pressure on cultivated land in the provinces of the main grain producing areas.(3)In terms of the influencing factors of cultivated land pressure,the level of urbanization is the most significant factor affecting the overall cultivated land pressure in the main grain producing areas.When the urbanization level increases by 1 percentage point,the cultivated land pressure index will increase by 0.029.It shows that the quality level of urbanization development in the main grain producing areas is not high at present.With the continuous promotion of urbanization development,the agricultural labor force is continuously transferred from rural areas to cities,and the demand for construction land is increasing,resulting in the frequent occurrence of Cultivated Land Non-agricultural,dominant and compensating for the inferior.Therefore,we should improve the development quality of cultivated land,reserve high-quality cultivated land resources and improve the production capacity of cultivated land.Farmers’ income,disaster area,chemical fertilizer investment and economic development level also have an important impact on the pressure of cultivated land in the main grain producing areas.(4)Based on LSTM model and SVM model,the cultivated land pressure in the main grain producing areas from 2021 to 2025 is predicted.The prediction shows that although the cultivated land pressure index fluctuates slightly,the cultivated land pressure in most provinces of the main grain producing areas is in good condition.The pressure on cultivated land in Hebei,Liaoning and Sichuan provinces is also decreasing,but the food security in these provinces is still fragile,and the pressure on food security still exists.Therefore,as the core area to ensure food security,the main grain producing areas should adopt the cultivated land protection and development strategy according to local conditions,pay attention to the protection of cultivated land resources,continuously increase the investment in agricultural science and technology,reserve high-quality cultivated land resources,and continuously improve the production capacity of cultivated land.For Sichuan Province and other provinces with great pressure on cultivated land,the conversion of cultivated land to construction land should be strictly controlled to maintain the existing cultivated land resources and quality.
Keywords/Search Tags:modified cultivated land pressure index model, Dynamic evolution, LSTM model, SVM model
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