| Green development is the deep extension of sustainable development,and its essence is to reform the traditional mode of development,to require human to grasp the launching factors,utilization pattern and ecological effects of natural resources actively,for increasing more output and creating huge ecological assents in future.There is no doubt that land and resources is an important material source of human production,live and ecosystem.Studying its green development,it helps us to pay more attention on resources itself including the quantity and quality of resources,to reduce the cost of resources,environment and ecology,and to realize the harmony between human and nature.Presently,there is an excessive demand on exploitation and utilization of land and resources.Moreover,it gives arise to low efficiency of resource utilization and environment pollution,which makes the green development of land and resources being hindered.It has become an important issue for people to make a scientific evaluation,deeply clarify the connotation of the green development of land and resources in China.In this paper,Pearl River Estuary Bay Area was took as the research area,through the green development theory,and establish BP artificial neural network to evaluate the degree on green development of land and resources.And then the obstacle diagnosis model is used to identify the main obstacles to the green development of land resources in the study area.Finally,several suggestions have been brought about.The results show that:(1)This article has built the evaluation system of land and resources green development in Pearl River Estuary Bay area concerning the resources and environment carrying capacity,sustainable utilization of resources and green input and output,including 8 layers and 27 indicators,should better reflecting the land resources dynamic linkage and spatial suitability.(2)The development and utilization of land resources in the Pearl River Estuary Bay area towards the "green" situation.Green development index has showed a general upward trend,and its growth curve is more volatile,with an average annual growth rate of 7.5089% from 2004 to 2014.The green development level of land and resources in the bay area shifts from "low" to "medium".Similarly,the subsystem green development index score also showed a wave of dynamic rise.The sustainable utilization system gets more than 80 scores in 2014,initially entering the “good” level;The carrying capacity of resources and environment and the green output and input system of resources are 74.8 and 73.20 respectively,which is belongs to the “medium” level.(3)The green index score of land and resources in the Pearl River Estuary Bay area has obvious difference.Zhongshan ranks the first place,Dongguan ranks the second,and Guangzhou and Zhuhai list third、fourth place,Shenzhen ranks the fifth in 2014.The scores difference between Zhongshan and Dongguan is 34.71%,which showing the gap is obvious.In addition,Zhuhai was caught up in the low degree of green development,even the contrast,reflecting the development and utilization of regional land resources green development of a certain lag and failure.(4)It can be concluded that the obstruction types in the bay area are gradually shifting by the multi subsystem into a single subsystem,based on the obstacle diagnosis and least square error method,especially by the resources and environment carrying potential system constraints.The natural resources endowment and the level of resource exploitation and utilization are the main hindering layers to the green development of land and resources among them.(5)According to the frequency and persistence of hindering effects,that the per capita cultivated area,per capita forest area,per capita water resources,per capita sea area,forest coverage rate,per capita consumption of coal,per capita COD emissions and air quality days are the main obstacle factors.And the average proportion of these obstacle factors have reached 76.01%.In addition,because of the different stages of the development of the city,there are some difference with obstacles factors among cities. |