Spatial And Temporal Characteristic And Driving Force Analysis Of Land Use Change

Under the background of the joint influence of natural process and human activities,the spatial pattern of land change in the lower Yellow River Depression Area?Kaifeng section?has undergone drastic changes.Quantitative monitoring of regional land change pattern has important reference value for rational planning of regional land resources and maintenance of balanced development of regional economy and agriculture in the future.To explore the influence degree of different driving mechanisms on land change and to clarify the spatiotemporal differences of different driving factors not only have important theoretical value for global change,but also have important reference significance for relieving food security pressure,improving ecological environment and promoting soil improvement.This study takes the lower Yellow River Depression Area?Kaifeng section?as the research area,in order to explore the spatial and temporal pattern distribution of land change and the detection of driving factors as the overall goal.Firstly,the spatial and temporal changes of land use in the study area in the2001-2016 were studied based on the selection of 2001,2008 and 2016 image data by remote sensing technology.Secondly,the correlation analysis model is used to verify the potential mutual dependence between different land changes in the study area.Finally,combining the first two steps,this paper analyzes the driving factors that lead to the land change in the study area,reveals the characteristics of its land use mode and land change,and puts forward some countermeasures and suggestions for the future land resource planning and management.The main conclusions of the study are as follows:?1?In the 2001-2016,the land use space-time pattern of the Back River Depression Area?Kaifeng section?in the lower Yellow River changed greatly.The concrete performance is as follows:In time,cultivated land and unused land continue to decrease,woodland,water,construction land increase year by year,this change mainly originates from ecological environment construction and the rapid development of township social economy.In space,the study area is mainly cultivated land,and the large area is distributed in all parts of the study area,the construction land is flake concentrated in the township center and extends to the surrounding area,the woodland and the water are distributed in the vicinity of the northern levee of the research zone,and the unused land is scattered in the northeast area of the levee.It is worth noting that during the study,the conversion of cultivated land to construction land is more obvious than that between other classes,therefore,in the future township development and regional ecological construction process,we should pay attention to the protection and utilization of cultivated land resources.?2?During the study period,there was a significant spatial positive correlation in the global distribution of the dominant cultivated land in the study area,and the agglomeration characteristics increased year by year.Among them,the south-east township cultivated land quality is high,cultivated land hotspot agglomeration trend is obvious and shows a small enhancement trend.The characteristics of cold spot agglomeration of cultivated land in the western part of the study area?near the main city of Kaifeng?are remarkable.Therefore,in the social and economic development of towns and villages,it is necessary to strengthen the interaction between towns and villages in order to promote the coordinated development of the region.?3?During the study period,the impact direction and influence degree of different factors on the change of cultivated land varied.Taking the cultivated land area as the cause variable and 13 explanatory factors as independent variables,this paper analyzes the whole area and local changes of cultivated land in the study areas,and on the whole area scale:Constructing the least squares regression model and spatial metering model,and the spatial metering model is obviously better than the least squares regression model,of which,in 2001-2008 years,the location and the influence of production variables on its change is obvious,and the influence degree of life variables increases gradually in 2008-2016 years.On the local scale:the geographically weighted regression model is more likely to reveal the influencing factors of cultivated land change than the least squares regression model,among which the total population of the region and the center distance from the county have a great influence on the change of cultivated land,and the variable X₆?fixed assets investment?,X₁₀?the total population of the region?,X₁₁?non-agricultural population?has obvious spatial non-stability to the change of cultivated land in the study area.Human activities are still the main factors leading to the change of cultivated land,and township development is inevitable,therefore,in the subsequent planning of land resource utilization,we should focus on the control of fixed assets investment,the total population of the region and the number of non-agricultural population,pay attention to the improvement of cultivated land quality and improve the efficiency of land production capacity.?4?This study systematically analyzes the temporal and spatial evolution of land change in the township of the Back River Depression Area?Kaifeng section?in the lower reaches of the Yellow River,and probes into the driving factors that affect the change of land structure,and provides theoretical basis and policy suggestions for relieving coastal agricultural production,safeguarding grain supply and developing the reserve resources of cultivated land,it provides reference for the innovation of land use mode in this section and even in the whole watershed.It is suggested that in the future land resource planning and management,the study area should adhere to the protection pattern of cultivated land quantity,quality and ecological"Trinity",strengthen the control of construction land,and promote the development of township linkage.