Reclaimed Land Use Efficiency Assessment Of Chengdu’s Demolition Area Based On DEA Method

Land resource is available for the most basic and most precious natural resource of human existence, it is the basic for agricultural production. The intensive use of land resources and protection is an objective requirement of modern agricultural resources and socialdevelopment. Massive expansion of urban construction of Chengdu arable land occupancy.Chengdu, implement projects on the intensive utilization of land resources and protect, is the utilization of agricultural resources is the objective requirement of social development.In this paper, "based in the Wenchuan earthquake" disaster relief program in Chengdu city as an example Reclaimed plots consisting of reclaimed land for the study,Constructing evaluation index system based on DEA method and analysis.BCC model is core to the benefit evaluation of land use in the study area,CCR model and evaluation results for the control of gray situation decision method, comparison and analysis of evaluation results;Discussion on factors affecting land use efficiency levels and proposed countermeasures.In order to provide scientific reference for this area of research. The main findings are as follows:(1)In this study, the selection of reasonable evaluation unit and Evaluation Index System. Selected Chengdu’s completed project, and is located in the third circle of land reclamation typical nine projects as evaluation unit.This study is based on the characteristics of DEA method to establish evaluation index system.Selected7Input indicators:land reclamation fees, compensation and subsidies, fertilizer inputs, machinery and inputs, labor input, investment in science and technology services, pesticide inputs;Selected 9 Output indicators:land yield, land productivity, grain yield, labor productivity, can support the number of new, stable production index, food safety factor, land reclamation, soil improvement force, the establishment of land use efficiency evaluation index system.(2)This study completed the evaluation of the optimization process.The initial description of statistics indicators exhibit a large variability, severe degree of dimension, using standardized z-score method;Correlation analysis showed that the correlation between indicators is reasonable, there is a reciprocal link between indicators;Through land-use input and output indicators of reliability test results prove indicators are acceptable.Principal component analysis to solve the redundancy index of leading to error in the calculation model, extracted three input factors:reclamation of land use technology and capital investment, investment in agricultural production, land reclamation biography, agricultural labor and land reclamation mechanization inputs, outputs extracted three factors:the reclaimed land use economic and environmental efficiency, the reclaimed land use for food security and stability, social bearing capacity of reclamation land use.(3) Efficiency Evaluation of the reclaimed land use,Reclaimed Land BCC model to evaluate the use of the study area is moderate overall level of technical efficiency, BCC-the average output-oriented evaluation of land reclamation was effective use of technology to 0.875, compared with the overall best score low 12.50 percent.BCC-investment-oriented evaluation of land use to get the average technical efficiency of 0.872, lower than the 12.8% in the overall best score.Efficiency Evaluation of the results of the independent sample T test:the observed statistic is-0.028, P= 0.978 corresponding, since the P-value is greater than the significance level, technical efficiency evaluation of the two models was no significant difference in scores.Efficiency Evaluation of the results of correlation analysis showed that:technical efficiency scores obtained by the two models was highly positive.This study suggests that the main reason for the impact of land use and technological efficiency are:① agricultural science and technology;② agricultural science and technology;③ service and innovation capabilities technology demonstration park.(4)Evaluation scale reclamation of land use,Research BCC model to evaluate land use overall evaluation scale for the middle level,Reclaimed Land BCC-mean output-oriented evaluation obtained using economies of scale to 0.895, compared with the overall best score of 10.50 percent lower.BCC-mean investment-led evaluation to land use scale of 0.884, lower than the overall average of 11.6 per cent optimal.Scale evaluation of the results of independent samples T test showed:observation statistic is-0.153, P= 0.880 corresponding, since the P-value is greater than the significance level, scale evaluation of the two models was no significant difference in scores.Scale evaluation results of correlation analysis showed that:two model economies of scale resulting evaluation scores showed a significant positive correlation.Reclaimed Land of scale trend analysis:Land use scale increasing trend of evaluation units E, F, H;Land use scale decreasing trend evaluation unit is A, D, I, should take measures to control the investment land use.Evaluation unit B, C, G scale in equilibrium.Factors are:① land-use technology and capital investment;② land bearing on social security and social functions;③ labor and mechanization of agricultural production inputs.(5)Reclaimed Land Use Efficiency evaluation results and analysis,Comprehensive efficiency of land use overall poor performance.BCC-output-oriented and investment-led evaluation BCC-demolition of old reclaimed land use in the same comprehensive efficiency scores mean are 0.786, compared with the average of the overall best (θ composite= 1.000) Low 21.40%.Factors affecting the comprehensive efficiency are:① land-use technology and capital investment;②biography of agricultural production inputs; ③ infrastructure;④ social carrying capacity of land, agricultural safety and security capabilities;⑤ Policy and Management.(6)This study suggests that non-DEA effective evaluation units should take measures to:Optimal land use inputs and outputs;integration of regional development of agricultural industries;Deepen joint business model;Encourage agricultural science and technology innovation; Strengthen policy control and support.