本文選題：住宅地價 + GWR模型��； 參考：《華中農(nóng)業(yè)大學(xué)》2014年碩士論文

【摘要】：土地價格是土地經(jīng)濟(jì)作用的反映,受土地市場上供求關(guān)系的影響,土地價格始終處于變動狀態(tài)。從空間的層面來看,地價及其變動具有明顯的區(qū)域與區(qū)位差異,即地價的空間分異特征。研究地價空間分異特征的形成、影響因素及其規(guī)律性,有助于充分發(fā)揮價格機(jī)制對于土地市場的調(diào)控作用,加強(qiáng)地價管理和調(diào)整土地的供求區(qū)位,從而在城市“精明增長”理念的指導(dǎo)下,落實(shí)土地利用的“精明規(guī)劃”,促進(jìn)城市土地資源的效率配置。 以往同類研究主要基于線性回歸或特征價格模型展開,此類模型基于城市空間勻質(zhì)的假設(shè)前提,認(rèn)為在城市內(nèi)部的不同區(qū)位上,住宅地價的各影響因素對住宅地價的貢獻(xiàn)度均等。然而由于城市區(qū)域內(nèi)部自然及社會經(jīng)濟(jì)資源分布的不均等性,在不同的微觀區(qū)位上,住宅地價的影響因素對于住宅地價的邊際增長作用應(yīng)該是可變的。地理加權(quán)回歸模型(GWR)擴(kuò)展了傳統(tǒng)的回歸模型框架,通過在線性回歸模型中假定回歸系數(shù)是觀測點(diǎn)地理位置的函數(shù),從而將數(shù)據(jù)的空間特性納入到模型中,為分析回歸關(guān)系的空間特征創(chuàng)造了條件,并通過優(yōu)化權(quán)重,使得模型能夠?qū)臻g非穩(wěn)定性數(shù)據(jù)進(jìn)行局部估計。因此,相對于傳統(tǒng)的回歸模型,使用GWR模型來研究城市地價的空間分異規(guī)律,可以更為深入的研究城市地價空間的形成機(jī)理及影響因素的作用機(jī)制。 本文選擇城市住宅地價為研究對象,以武漢市主城區(qū)為研究區(qū)域,分析了2003-2012年期間武漢市的住宅地價的空間分異特征,發(fā)現(xiàn)武漢市的住宅地價總體上仍表現(xiàn)為單中心結(jié)構(gòu),并以該中心為核心向外圈層式遞減；在此基礎(chǔ)上,選取地塊面積、容積率、大學(xué)、中小學(xué)、醫(yī)院、主干道、地鐵、生活品市場、水域及公園10個住宅地價微觀影響因素,構(gòu)建GWR模型分析住宅地價空間分異特征的形成規(guī)律,結(jié)果表明：容積率、主干道、生活品市場及教育資源對住宅地價貢獻(xiàn)度的區(qū)位差異顯著。一方面表現(xiàn)出城市居民在選擇居住區(qū)位時對生活便利程度、教育資源及交通條件的偏好,另一方面也說明了教育資源、生活品市場以及交通條件等因素在研究區(qū)內(nèi)的分布不夠均衡。 相對于傳統(tǒng)的線性回歸或特征價格模型,GWR模型更適合于從微觀區(qū)位的角度為住宅空間規(guī)劃和地價更新提供依據(jù),更為符合城市精明增長的規(guī)劃理念,為優(yōu)化配置城市土地資源提供理論實(shí)踐指導(dǎo)。
[Abstract]:The land price is the reflection of the land economy, and the land price is always in the state of change under the influence of the supply and demand in the land market.From the spatial aspect, the land price and its change have obvious regional and regional differences, that is, the spatial differentiation of land price.The study of the formation, influencing factors and regularity of spatial differentiation of land price is helpful to give full play to the role of price mechanism in regulating the land market, to strengthen the land price management and to adjust the land supply and demand location.Therefore, under the guidance of the urban "smart growth" concept, the "smart planning" of land use can be carried out to promote the efficient allocation of urban land resources.In the past, similar studies were mainly based on linear regression or characteristic price model. This kind of model was based on the assumption of urban spatial homogeneity.The contribution of all factors to residential land price is equal.However, due to the uneven distribution of natural and social economic resources in urban areas, the influence factors of residential land price on the marginal growth of residential land price should be variable in different micro-location.Geo-weighted regression model (GWR) extends the traditional regression model framework. By assuming that the regression coefficient is a function of the geographical location of the observation point in the linear regression model, the spatial characteristics of the data are incorporated into the model.Conditions are created for the analysis of spatial features of regression relations and local estimation of spatial instability data can be made by optimizing weights.Therefore, compared with the traditional regression model, the use of GWR model to study the spatial differentiation of urban land price, can be more in-depth study of the formation mechanism of urban land price space and the action mechanism of influencing factors.This paper chooses the urban residential land price as the research object, taking the main urban area of Wuhan as the research area, analyzes the spatial differentiation characteristics of the residential land price in Wuhan from 2003 to 2012, and finds that the residential land price in Wuhan is still characterized by a single central structure.On the basis of this, we select the microcosmic influencing factors of land area, volume ratio, university, primary and middle school, hospital, trunk road, subway, life product market, water area and park 10 residential land price.The GWR model is constructed to analyze the spatial differentiation characteristics of residential land price. The results show that: volume ratio, main road, market of living goods and educational resources have significant regional differences to the contribution of residential land price.On the one hand, it shows the preference of urban residents for living convenience, educational resources and traffic conditions when they choose residential areas. On the other hand, it also shows that educational resources.The distribution of market and traffic conditions in the study area is not balanced.Compared with the traditional linear regression model or the characteristic price model, GWR model is more suitable to provide the basis for housing spatial planning and land price renewal from the perspective of micro-location, and is more in line with the urban smart growth planning concept.To optimize the allocation of urban land resources to provide theoretical and practical guidance.
【學(xué)位授予單位】：華中農(nóng)業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：F301.4;F224

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