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151.
基于地理探测器和GWR模型的中国重点镇布局定量归因 总被引:1,自引:1,他引:0
重点镇是小城镇发展的龙头,形成科学合理的重点镇布局对优化中国城市化战略格局有重要意义。论文以2004年和2014年分别公布的1887个和3675个全国重点镇为样本,对其分布及效应的变动特征进行探究,进而在地级尺度对重点镇布局的影响因子及其作用进行地理探测和局部空间回归。结果表明:① 经增补调整,中国重点镇布局及建设效应的均衡性增强,主要集聚区西移北扩,冷热点的分布突破“胡焕庸线”,经济辐射效应的分化程度减弱,体现出政策因素的有力影响。除县际均衡和区域倾斜政策外,重点镇的分布还受到海拔高度、公路网密度、常住人口城镇化率等因子的显著作用。② 因子探测器、GWR模型和交互作用探测器的结合能更精准地刻画影响因子的作用方式、方向、路径和强度。中国重点镇的布局不是5个显著性因子均匀、独立、直接作用的结果,而是影响均具空间异质性的各因子两两交互作用后增效的产物。③ 县际均衡政策与其他因子的协同作用是形成现有重点镇分布格局的主导力量;区域倾斜政策的效果总体较好,但目标区域还需更准确。 相似文献
152.
Food security is the primary prerequisite for achieving other Millennium Development Goals(MDGs).Given that the MDG of“halving the proportion of hungers by 2015”was not realized as scheduled,it will be more pressing and challenging to reach the goal of zero hunger by 2030.So there is high urgency to find the pattern and mechanism of global food security from the perspective of spatio-temporal evolution.In this paper,based on the analysis of database by using a multi-index evaluation method and radar map area model,the global food security level for 172 countries from 2000 to 2014 were assessed;and then spatial autocorrelation analysis was conducted to depict the spatial patterns and changing characteristics of global food security;then,multi-nonlinear regression methods were employed to identify the factors affecting the food security patterns.The results show:1)The global food security pattern can be summarized as“high-high aggregation,low-low aggregation”.The most secure countries are mainly distributed in Western Europe,North America,Oceania and parts of East Asia.The least secure countries are mainly distributed in sub-Saharan Africa,South Asia and West Asia,and parts of Southeast Asia.2)Europe and sub-Saharan Africa are hot and cold spots of the global food security pattern respectively,while in non-aggregation areas,Haiti,North Korea,Tajikistan and Afghanistan have long-historical food insecurity problems.3)The pattern of global food security is generally stable,but the internal fluctuations in the extremely insecure groups were significant.The countries with the highest food insecurity are also the countries with the most fluctuated levels of food security.4)The annual average temperature,per capita GDP,proportion of people accessible to clean water,political stability and non-violence levels are the main factors influencing the global food security pattern.Research shows that the status of global food security has improved since the year 2000,yet there are still many challenges such as unstable global food security and acute regional food security issues.It will be difficult to understand these differences from a single factor,especially the annual average temperature and annual precipitation.The abnormal performance of the above factors indicates that appropriate natural conditions alone do not absolutely guarantee food security,while the levels of agricultural development,the purchasing power of residents,regional accessibility,as well as political and economic stability have more direct influence. 相似文献
153.
Journal of Geographical Sciences - There is a lack of basic theory and method to examine the effect of administrative division (AD) adjustment on the regional development. Based on the theory and... 相似文献
154.
Land cover and land use change (LCLUC) is a global phenomenon, and LCLUC in urbanizing regions has substantial impacts on humans and their environments. In this paper, a semi-automatic approach to identifying the type and starting time of urbanization was developed and tested based on dense time series of Vegetation-Impervious-Soil (V-I-S) maps derived from Landsat surface reflectance imagery. The accuracy of modeled V-I-S fractions and the estimated time of initial change in impervious cover were assessed. North Taiwan, one of the regions of the island of Taiwan that experienced the greatest urban LCLUC, was chosen as a test area, and the study period is 1990 to 2015, a period of substantial urbanization. In total, 295 dates of Landsat imagery were used to create 295 V-I-S fraction maps that were used to construct fractional cover time series for each pixel. Root Mean Square Error (RMSE)s for the modeled Vegetation, Impervious, and Soil were 25 %, 22 %, 24 % respectively. The time of Urban Expansion is estimated by logistic regression applied to Impervious cover time series, while the time of change for Urban Renewal is determined by the period of brief Soil exposure. The identified location and estimated time for newly urbanized lands were generally accurate, with 80% of Urban Expansion estimated within ±2.4 years. However, the accuracy of identified Urban Renewal was relatively low. Our approach to identifying Urban Expansion with dense time series of Landsat imagery is shown to be reliable, while Urban Renewal identification is not. 相似文献
155.
The Lower Mississippi Alluvial Valley (LMAV) was home to about ten million hectare bottomland hardwood (BLH) forests in the Southern U.S. It experienced over 80 % area loss of the BLH forests in the past centuries and large-scale afforestation in recent decades. Due to the lack of a high-resolution cropland dataset, impacts of land use change (LUC) on the LMAV ecosystem services have not been fully understood. In this study, we developed a novel framework by integrating the machine learning algorithm, county-level agricultural census, and satellite-based cropland products to reconstruct the LMAV cropland distribution during 1850–2018 at a 30-m resolution. Results showed that the LMAV cropland area increased from 0.78 × 104 km2 in 1850 to 6.64 × 104 km2 in 1980 and then decreased to 6.16 × 104 km2 in 2018. Cropland expansion rate was the largest in the 1960s (749 km2 yr−1) but decreased rapidly thereafter, whereas cropland abandonment rate increased substantially in recent decades with the largest rate of 514 km2 yr−1 in the 2010s. Our dataset has three notable features: (1) the depiction of fine spatial details, (2) the integration of the county-level census, and (3) the inclusion of a machine-learning algorithm trained by satellite-based land cover product. Most importantly, our dataset well captured the continuous increasing trend in cropland area from 1930–1960, which was misrepresented by other cropland datasets reconstructed from the state-level census. Our dataset would be important to accurately evaluate the impacts of historical deforestation and recent afforestation efforts on regional ecosystem services, attribute the observed hydrological changes to anthropogenic and natural driving factors, and investigate how the socioeconomic factors control regional LUC pattern. Our framework and dataset are crucial to developing managerial and policy strategies for conserving natural resources and enhancing ecosystem services in the LMAV. 相似文献
156.
Forest structural diversity metrics describing diversity in tree size and crown shape within forest stands can be used as indicators of biodiversity. These diversity metrics can be generated using airborne laser scanning (LiDAR) data to provide a rapid and cost effective alternative to ground-based inspection. Measures of tree height derived from LiDAR can be significantly affected by the canopy conditions at the time of data collection, in particular whether the canopy is under leaf-on or leaf-off conditions, but there have been no studies of the effects on structural diversity metrics. The aim of this research is to assess whether leaf-on/leaf-off changes in canopy conditions during LiDAR data collection affect the accuracy of calculated forest structural diversity metrics. We undertook a quantitative analysis of LiDAR ground detection and return height, and return height diversity from two airborne laser scanning surveys collected under leaf-on and leaf-off conditions to assess initial dataset differences. LiDAR data were then regressed against field-derived tree size diversity measurements using diversity metrics from each LiDAR dataset in isolation and, where appropriate, a mixture of the two. Models utilising leaf-off LiDAR diversity variables described DBH diversity, crown length diversity and crown width diversity more successfully than leaf-on (leaf-on models resulted in R² values of 0.66, 0.38 and 0.16, respectively, and leaf-off models 0.67, 0.37 and 0.23, respectively). When LiDAR datasets were combined into one model to describe tree height diversity and DBH diversity the models described 75% and 69% of the variance (R² of 0.75 for tree height diversity and 0.69 for DBH diversity). The results suggest that tree height diversity models derived from airborne LiDAR, collected (and where appropriate combined) under any seasonal conditions, can be used to differentiate between simple single and diverse multiple storey forest structure with confidence. 相似文献
157.
城市层面的火灾风险评估主要包括火灾危险性、危害性及救援能力等方面。本文选取火灾危险性评估进行针对性研究,在大数据思维的指导下,以相关关系代替因果关系,采用多源数据对评估指标权重、分值进行率定,得出福州市城区火灾危险性时空分布图。首先利用高德地图API对消防历史出警记录进行地址解析,将近万条火灾出警地址空间落点,获得福州市历史火灾空间分布;然后综合城市用地性质现状、用地开发性质、人口分布热力图等多源异构数据,探索其与历史火灾空间分布的相关性;最后以福州城区为例,初步实现具有充分数理支撑的火灾危险性评估方法,形成火灾危险性动态评估成果,为城市消防规划等提供支撑和依据。 相似文献
158.
159.
针对海底地形与重力异常和重力异常垂直梯度在相应频段呈现强线性相关的特点,引入多元回归分析技术,提出并详细推导了联合多元重力数据的海底地形建模方法。然后,在西南印度洋SWIR(Southwest India Ridge)所在部分海域开展了海底地形反演试验及地形地貌分析研究。试验结果表明:6种海深模型中,基于多元回归分析技术构建的海深模型(BDVG模型)检核精度最高,相较于S&S V18.1模型和ETOPO1模型精度分别提高了11.51%和57.81%左右;2000 m以上水深海域,各个海深模型的检核精度较高,相对误差波动较小,反映了深海海域具有良好的反演效果;地形起伏剧烈海域或者浅海海域,BDVG海深模型,相较于以重力异常和重力异常垂直梯度作为单一输入源建立的BDG模型和BVGG模型相对误差及相对误差波动变化较小,反映了BDVG模型拥有更好的稳定性,从而体现了联合反演的必要性和优势。Indomed FZ—Gallieni FZ上唯一轴部缺失裂谷洋脊段(27洋脊段)目前属于岩浆供应充足阶段,构造作用的海底扩张对其影响较小;同时由于对称裂离方式影响,27洋脊段沿轴南北对称分布有地形隆起。 相似文献
160.