中文摘要：

以河北省地价空间分布特征分析为基础,从地理区位、经济发展、城市规模和潜力、基础设施状况以及环境条件等方面选取9个地价影响因子,通过构建GWR模型,探索各因子对河北省地价影响程度的空间差异性,以期为京津冀协同发展提供建议。结果表明：①河北省不同地区地价受各因子的影响程度存在差异性。距京津距离和人口密度对环京津区地价影响最大;人均地区生产总值、城镇化率和公路里程对沧州地价影响大;医疗卫生机构床位数对冀中南区地价影响最大,单位GDP能耗对该地区影响程度次之;对太行山沿线地价驱动力最大的是城镇居民人均可支配收入;冀西北区地价受在岗职工平均工资影响大,受单位GDP能耗影响小;唐山、秦皇岛地区地价受单位GDP能耗影响最大。②京津冀协同发展突出了地理区位对河北省地价的影响,建议完善公路、铁路基础设施以缩短各地区距京津的最短距离,并且在各地区制定差别化的土地政策。

英文摘要：

Based on the analysis on spatial distribution characteristic of land price in Hebei Province, this pa- per chooses 9 factors of land price from the geographical location, economic development, urban size and potential, the construction of infrastructure and environment, and built the GWR model to explore the regional differences of land price influenced by each faetor which will provide proposal to the coordinated development of Beijing-Tianjin- Hebei. The research shows that, there is different effect of land price influenced by each factor in different area. Distance from Beijing and Tianjin and population density have the greatest influence on land price of surrounding Beijing-Tianjin area. per capita GDP, urbanization rate and highway mileage have the greatest influence to Cang- zhou eity. And the number of bed in medical institutions has the greatest impact on central south of Hebei, energy consumption per unit GDP takes seeond place. What influence the area along Taihang mountains best is the per ca- pita disposable income. The northwest area of Hebei is affected greatly by average wage of the worker, and it＇ s af- fected small by the energy consumption per unit GDP. The land price of Tangshan and Qinhuangdao is affected greatly by the energy consumption unit GDP. The strategy of coordinated development of Beijing-Tianjin-Hebei em- phasize on importance of geographical location to land price in Hebei Province. The paper recommends the infra- structure of highway and railway should be improved to shorten the distance from various places in Hebei Province to Beijing and Tianjin City as well as make different land poliey in different regions.