本文選題：國土資源 + 綠色發(fā)展指數(shù)��； 參考：《廣州大學(xué)》2017年碩士論文

【摘要】：綠色發(fā)展是可持續(xù)發(fā)展的深度延展,本質(zhì)上是改革傳統(tǒng)發(fā)展模式,要求人類主動地把握自然資源的發(fā)動因素,利用過程以及生態(tài)影響,為未來增加更多的產(chǎn)出和創(chuàng)造巨大的生態(tài)資產(chǎn)。國土資源是人類“生產(chǎn)-生活-生態(tài)”的重要物質(zhì)來源和發(fā)展載體,其綠色發(fā)展研究有利于關(guān)注資源自身可利用數(shù)量和可挖潛質(zhì)量,降低資源、環(huán)境和生態(tài)成本,實現(xiàn)人與自然相處和諧。目前,我們對國土資源開發(fā)利用的需求不斷增加,再加上資源利用效率不高和引發(fā)環(huán)境污染問題,使得國土資源開發(fā)利用綠色發(fā)展受到阻礙。探討國土資源綠色發(fā)展內(nèi)涵與路徑,科學(xué)評價國土資源綠色發(fā)展,已成為我國現(xiàn)階段資源利用的重要課題。以環(huán)珠江口灣區(qū)國土資源為研究對象,將綠色發(fā)展理念引入國土資源利用評價中,通過BP神經(jīng)網(wǎng)絡(luò)對灣區(qū)2004至2014年國土資源開發(fā)利用綠色發(fā)展指數(shù)進行評價,進而運用障礙診斷模型識別主要障礙因子,最后針對結(jié)果提出相應(yīng)的建議措施。研究結(jié)果有:(1)從資源環(huán)境承載潛力、資源持續(xù)利用水平和資源綠色產(chǎn)出與投入三個維度構(gòu)建了環(huán)珠江口灣區(qū)國土資源綠色發(fā)展指數(shù)評價體系,包括8個準則層以及27個具體指標,應(yīng)更好地體現(xiàn)國土資源的動態(tài)性,聯(lián)動性以及空間適宜性。(2)環(huán)珠江口灣區(qū)國土資源開發(fā)利用朝“綠色化”良好態(tài)勢發(fā)展。綠色發(fā)展指數(shù)從2004年到2014年總體上呈波動上升的發(fā)展趨勢,年均增長率達到7.51%。灣區(qū)國土資源開發(fā)利用綠色發(fā)展水平等級由“低”水平向“中等”水平轉(zhuǎn)變。同樣三大子系統(tǒng)綠色發(fā)展指數(shù)得分也呈上升發(fā)展趨勢。2014年資源持續(xù)利用水平系統(tǒng)綠色發(fā)展指數(shù)超過80,初步進入“良好”水平;資源環(huán)境承載潛力系統(tǒng)和資源綠色產(chǎn)出與投入系統(tǒng)綠色指數(shù)分別為74.8和73.20,屬于“中等”水平。(3)環(huán)珠江口灣區(qū)國土資源綠色指數(shù)得分具有明顯的差異性。截止2014年,中山市國土資源綠色指數(shù)得分暫列第1名,東莞市第2名,廣州市和珠海市列第3、4名,深圳市第5名。最高得分中山市與最低得分深圳市得分相差約13.62,差距較為明顯;而增長率最高的城市是東莞市與增長率最低的珠海市相差34.712%。除此之外,2014年珠海市被原本綠色發(fā)展程度較低的城市趕上甚至是反超,反映區(qū)域國土資源開發(fā)利用綠色發(fā)展緩慢和障礙。(4)通過障礙診斷模型和最小方差法,可以得知灣區(qū)內(nèi)各市阻礙類型都是由多系統(tǒng)逐漸過渡為單系統(tǒng)的阻礙模式,尤其受到資源環(huán)境承載潛力系統(tǒng)的約束。并且以自然資源稟賦和資源開發(fā)利用水平為國土資源開發(fā)利用綠色發(fā)展的主要障礙準則層。(5)根據(jù)出現(xiàn)的頻數(shù)以及阻礙作用的持久性,認為人均耕地面積、人均林地面積、人均水資源量、森林覆蓋率、人均煤炭消耗量、人均化學(xué)需氧量排放量和空氣質(zhì)量優(yōu)良天數(shù)是主要障礙因子。這些障礙因子累積占比達到了76.01%。除此之外,各城市的其他主要障礙因子存在一定的差異性。
[Abstract]:The green development is the deep extension of the sustainable development, in essence it is the reform of the traditional development model, which requires the human initiative to grasp the starting factors of natural resources, the use of the process and the ecological impact, to increase more output and create huge ecological assets for the future. Land and resources are the important material sources of human "production life ecology". And the development carrier, its green development research is helpful to pay attention to the available quantity and the quality of the resources, reduce the resources, environment and ecological cost, and realize the harmony between people and nature. At present, the demand for the development and utilization of land and resources is increasing, and the efficiency of resource utilization is not high and the environmental pollution is caused, and the land is caused by the environmental pollution. The green development of resources development and utilization is hindered. To explore the connotation and path of green development of land and resources, and to scientifically evaluate the green development of land and resources has become an important issue in the utilization of resources at the present stage of our country. The green development concept is introduced into the evaluation of land and resources utilization, and the BP neural network is adopted. This paper evaluates the green development index of land and resources development and utilization of the bay area from 2004 to 2014, then uses the obstacle diagnosis model to identify the main obstacle factors, and finally puts forward some suggestions for the results. The results are as follows: (1) from the resources and environment carrying potential, the level of sustainable utilization of resources and the green output and input of resources in three dimensions. The evaluation system of green development index of land and resources in the Pearl River mouth Bay area has been built, including 8 criteria and 27 specific indexes, which should better reflect the dynamic, linkage and Spatial Suitability of land and resources. (2) the development and utilization of land and resources in the Pearl River mouth Bay Area developed well. The green development index is from 2004 to 20. The overall growth trend of 14 years is fluctuating, the average annual growth rate reaches the level of 7.51%. Bay area development and utilization of land and resources, the level of green development is changed from "low" level to "medium" level. The same three sub-system green development index scores are also on the rise and development trend, and the green development index of the sustainable utilization level system of the.2014 year source is the same. More than 80, initially entered the "good" level; the green index of the resource environment bearing potential system and the green output and input system were 74.8 and 73.20 respectively. (3) the green index score of the land and resources in the Pearl River mouth Bay area was distinctly different. In 2014, the green index of land and resources in Zhongshan was temporarily scored. First in Dongguan, second in Dongguan, second in Guangzhou and Zhuhai, fifth in Shenzhen. The highest score in Zhongshan and the lowest score in Shenzhen is about 13.62, and the gap is more obvious; and the city with the highest growth rate is the difference of the Dongguan city and the lowest growth rate in Zhuhai by 34.712%. In addition, the Zhuhai city was originally green in 2014. The lower level cities catch up with even the anti super, reflecting the slow development and obstacle of the development and utilization of land resources in the region. (4) through the obstacle diagnosis model and the minimum variance method, it can be found that all the barriers in the bay area are all gradually transition from multi system to the single system, especially by the resources and environment bearing potential system. And with natural resources and resources development and utilization level as the main barrier criteria for the development and utilization of land and resources for green development. (5) according to the frequency of occurrence and the persistence of the hindrance, it is considered that the per capita cultivated land area, per capita woodland area, per capita water resources, forest cover rate, per capita coal consumption, and per capita chemical oxygen demand. The number of good days of emission and air quality is the main obstacle factor. In addition to the cumulative proportion of these barriers to 76.01%., the other major obstacle factors in each city are different.
【學(xué)位授予單位】：廣州大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F205

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相關(guān)期刊論文 前10條

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本文編號：1935843