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为了寻求一种人口分布的最优估计模型,提高人口分布的拟合效果,文章以2000年第五次人口普查和2010年第六次人口普查数据为基础,以ArcGIS强大的空间分析功能为依托,采用不同的地统计分析模型对江苏省两次普查的人口密度数据进行探索性数据分析,并从中选择最优模型进行克里格插值。结果表明,两次普查间江苏省人口分布整体格局变化不大,但呈现出各地区的整体密度不断增大、空间分布"两极分化"、人口分布重心逐渐南移等特征。 相似文献
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昆明作为云南省的省会城市,其人口的空间分布特征对该地区的城市规划和经济发展具有重要意义.本文以昆明市112个乡镇的矢量数据和2000、2010年的人口数据为基础,运用Moran I指数和Moran I散点图对昆明市2000和2010年的乡镇人口进行了空间自相关及其时空演变分析.结论如下:①2000和2010年,昆明市乡镇人口分布呈现显著的正向空间自相关特征,且人口分布出现以昆明市市中心和滇池为中心的"人口高地带"和北部山区的"人口低地带",这与昆明市海拔"北高南低"和地势"北部起伏大、南部和缓"趋于一致;②地形要素是昆明市乡镇人口2000和2010年空间自相关的基础,而随着交通条件的改善和城市化的发展,2000―2010年10年间昆明市乡镇人口空间自相关显著增强,但人口密度出现较大的空间差异. 相似文献
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基于随机森林算法对青藏高原TRMM降水数据进行空间统计降尺度研究 总被引：1，自引：0，他引：1
提高气象数据空间分辨率对水文、气象和生态等领域的流域尺度研究至关重要。青藏高原气候变化在全球气候研究中占有重要的位置,并且对局域降水分布的研究在大气科学中处于基础地位。为获取青藏高原地区准确、有效、更高空间分辨率的降水数据,基于随机森林算法,引入植被和地形因子,采用热带降水测量计划卫星(Tropical Rainfall Measuring Mission,TRMM) 3B43降水数据(0. 25°×0. 25°)、NOAA-AVHRR归一化植被数(normalized difference vegetation index,NDVI)数据(8 km×8 km)、航天飞机雷达地形测绘任务(Shuttle Radar Topography Mission,SRTM)数字高程模型(digital elevation model,DEM)数据(90 m×90 m)以及经纬度信息,建立了非线性空间统计降尺度模型,最终获得8 km分辨率降水降尺度结果。另外,采用将时间序列分析和非线性回归分析融合的方法,基于2000—2012年TRMM年均降水数据和NDVI数据,建立降水量时间尺度预测模型。分析结果表明,综合考虑植被和地形因子对青藏高原地区降水空间分布的影响,基于随机森林算法建立的降尺度模型,其降尺度结果与地面站点测量值拟合系数为0. 89,高于TRMM数据与地面站点测量值的拟合系数0. 81,说明降尺度结果提高了卫星遥感降水数据的空间分辨率。另外,降水预测模型能够较好地描述青藏高原地区的年际降水变化趋势和数量级,2006—2012年的预测降水量与TRMM降水数据拟合系数均高于0. 80。 相似文献
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地学工作者一直关注的ITRF2000地球参考框架初步结果已于2001年3月19日公布.ITRF2000综合了VLBI、SLR、LLR、GPS和DORIS技术,产生736个点位坐标和54个核心站.文中介绍了ITRF2000,并利用ITRF2000综合解的结果计算全球板块的欧拉矢量,建立了基于空间实测数据基础的最新全球板块运动模型. 相似文献
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扩展邻域元胞自动机模型城市扩张研究 总被引：1，自引：0，他引：1
元胞自动机近年来被广泛应用于动态模拟城市扩张,但其邻域类型一般固定于摩尔邻域.文章基于Geo-CA理论,自定义扩展邻域类型,并结合特定地理位置多层次约束性条件构建CA模型,扩展了CA模型的空间建模功能.以武汉市为例,将2000年和2009年TM遥感影像和城市用地数据作为基础,结合武汉市城市规划图、DEM、道路交通图、水域等多层次图像,构成空间数据库,建立武汉市城市扩张扩展邻域CA模型.最后以2009年数据为基础,对武汉市2018年城市用地扩张情况进行预测,为武汉市城镇建设提供参考. 相似文献
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为揭示城镇化背景下武汉市人口时序增长趋势和人口空间分布格局演变特征,本文基于1990年第四次、2000年第五次、2010年第六次全国人口普查和2014年武汉市人口普查数据,运用统计学原理和GIS空间分析方法,分析了武汉市人口增长的时空变化规律;应用人口密度空间分布的数学模型,得到武汉市人口空间分布格局的演变趋势。人口增长研究表明:1990年以后,武汉市人口数量迅速增长,总体上形成了中心聚集、外围扩散的空间发展格局。空间分布研究表明:1)武汉市的人口密度分布更加符合Clark模型,主城区Smeed模型拟合效果更好。近25年来,武汉市城镇化进程迅速,人口向主城区聚集。随着时间发展,主城区逐步呈现初级阶段的郊区化。2)武汉市主城区人口空间分布已经出现多中心化的趋势,并且已经有两个街道发育成为人口次中心。研究结果可为武汉市人口相关决策的制定和城市结构调整提供参考依据,有助于认识我国中部崛起城市的发展规律,为其他城市的发展和规划提供参考和借鉴。 相似文献
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黑龙江省耕地非农化的空间格局与重心曲线分析 总被引：1，自引：0，他引：1
为了揭示耕地非农化的空间格局与重心曲线,为耕地资源保护和利用政策制定提供决策支撑,该文以黑龙江省1980、1990、2000、2010、2015年土地利用数据为基础,运用GIS空间分析方法,引入重心模型分析黑龙江省耕地非农化的空间格局及重心曲线。研究结果表明:1980—2015年黑龙江省耕地非农化发展不平衡,4个时期耕地非农化面积呈波动增长的趋势;耕地非农化等级空间分布特征明显,等级较高的城市集中分布在西部地区;耕地非农化速度等级的重心曲线在空间分布上,具有从中心向边缘延伸的特点;耕地非农化围绕中心地区进行,其空间扩散路径在图形上呈现出一个回旋状。 相似文献
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基于CLUE-S模型的南京市土地利用变化模拟 总被引：3，自引：0，他引：3
本文以南京市为研究区,以南京市1986年的土地利用现状图为基础,分析研究区概况并根据数据的可获取性,选取13类土地利用变化驱动因素,利用逻辑斯蒂回归分析求解土地利用变化驱动因素作用系数矩阵。在此基础上运行CLUE-S模型,对南京市1996年的土地利用空间格局进行模拟。将模拟结果与南京市1996年土地利用现状图与进行对比,结果较为理想,模拟正确率达88.57%,KAPPA指数0.86。这说明CLUE-S模型具有成功模拟区域土地利用时空动态变化的能力,对土地利用预测、规划具有重要的指导作用。 相似文献
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利用多分类Logistic回归进行土地利用变化模拟——以湖北省嘉鱼县为例 总被引：1，自引：0，他引：1
提出了模拟土地利用变化的多分类Logistic回归模型,即将因变量的二分类扩展为多分类。分别计算各种类型之间的转换回归系数可提高模拟的精度。对于不同的土地利用类型,计算出了不同的回归系数。该模型用于研究湖北省嘉鱼县土地利用变化的正确率为73.4%。 相似文献
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城市空间结构及其扩展的模拟是城市科学管理与规划的重要前提,本文基于极限学习机提出了顾及不同非城市用地转化为城市用地差异与强度的城市扩展元胞自动机模型（ELM-CA）。模型验证表明：①ELM-CA模型的模拟精度达到70.30%,相比于逻辑回归和神经网络分别提高了2.21%和1.54%,FoM系数分别提高了0.025 9和0.017 9,Kappa系数分别提高了0.024 7和0.016 9,且Moran I指数接近于实际值,说明极限学习机模型较逻辑回归和神经网络能更有效模拟城市扩展的空间形态及其变化;②ELM模型的训练时间仅为神经网络的1/3左右,体现了ELM学习速度的优势;③在小样本情况下,逻辑回归和神经网络都受到明显的影响,而极限学习机还能保持良好的性能,这个特点使其在样本难以获取的情况下具有明显的优势。两个时相的城市扩展模拟与真实数据的比较表明：基于极限学习机的城市扩展元胞自动机模型（ELM-CA）,简化了CA模型的复杂度,并在小样本情况下能有效提高模拟精度,适合于复杂土地利用条件下城市扩展模拟与预测。 相似文献
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Urban Sprawl Analysis of Tripoli Metropolitan City (Libya) Using Remote Sensing Data and Multivariate Logistic Regression Model 总被引：1，自引：0，他引：1
Abubakr A. A. Alsharif Biswajeet Pradhan 《Journal of the Indian Society of Remote Sensing》2014,42(1):149-163
The main objective of this paper is to analyze urban sprawl in the metropolitan city of Tripoli, Libya. Logistic regression model is used in modeling urban expansion patterns, and in investigating the relationship between urban sprawl and various driving forces. The 11 factors that influence urban sprawl occurrence used in this research are the distances to main active economic centers, to a central business district, to the nearest urbanized area, to educational area, to roads, and to urbanized areas; easting and northing coordinates; slope; restricted area; and population density. These factors were extracted from various existing maps and remotely sensed data. Subsequently, logistic regression coefficient of each factor is computed in the calibration phase using data from 1984 to 2002. Additionally, data from 2002 to 2010 were used in the validation. The validation of the logistic regression model was conducted using the relative operating characteristic (ROC) method. The validation result indicated 0.86 accuracy rate. Finally, the urban sprawl probability map was generated to estimate six scenarios of urban patterns for 2020 and 2025. The results indicated that the logistic regression model is effective in explaining urban expansion driving factors, their behaviors, and urban pattern formation. The logistic regression model has limitations in temporal dynamic analysis used in urban analysis studies. Thus, an integration of the logistic regression model with estimation and allocation techniques can be used to estimate and to locate urban land demands for a deeper understanding of future urban patterns. 相似文献
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以深圳海岸带为研究区,基于1996、2005、2011年遥感影像得到研究区土地利用历史数据,选取自然、社会统计数据作为驱动因素,利用CLUE-S模型分别从不同时间尺度和空间尺度对研究区2005、2011年的土地利用分布予以模拟,并对模拟结果分别从类别和景观水平予以精度评价。从类别水平角度,选择ROC曲线对各地类的Logistic回归拟合精度进行评价;从景观水平角度,选取Kappa指数对模拟效果予以评估,以验证所选驱动因子的合理性。结果表明:在研究区范围内,CLUE-S模型的类别精度随着空间分辨率的改变而有所差异,100 m分辨率为本研究模拟的最佳尺度,各地类的ROC值均高于0.7;随着模拟时间的缩短模拟精度有所增加;东海岸由于受到人类影响较小,模拟效果整体相对较好。总体而言,CLUE-S模型适用于研究区土地利用模拟,所选驱动力因子能够对研究区土地利用变化予以较好的解释。 相似文献
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Modelling coastal land use change by incorporating spatial autocorrelation into cellular automata models 总被引：1，自引：0，他引：1
This paper presents a spatial autoregressive (SAR) method-based cellular automata (termed SAR-CA) model to simulate coastal land use change, by incorporating spatial autocorrelation into transition rules. The model captures the spatial relationships between explained and explanatory variables and then integrates them into CA transition rules. A conventional CA model (LogCA) based on logistic regression (LR) was studied as a comparison. These two CA models were applied to simulate urban land use change of coastal regions in Ningbo of China from 2000 to 2015. Compared to the LR method, the SAR model yielded smaller accumulated residuals that showed a random distribution in fitting the CA transition rules. The better-fitting SAR model performed well in simulating urban land use change and scored an overall accuracy of 85.3%, improving on the LogCA model by 3.6%. Landscape metrics showed that the pattern generated by the SAR-CA model has less difference with the observed pattern. 相似文献
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Although traditional cellular automata (CA)‐based models can effectively simulate urban land‐use changes, they typically ignore the spatial evolution of urban patches, due to their use of cell‐based simulation strategies. This research proposes a new patch‐based CA model to incorporate a spatial constraint based on the growth patterns of urban patches into the conventional CA model for reducing the uncertainty of the distribution of simulated new urban patches. In this model, the growth pattern of urban patches is first estimated using a developed indicator that is based on the local variations in existing urban patches. The urban growth is then simulated by integrating the estimated growth pattern and land suitability using a pattern‐calibrated method. In this method, the pattern of new urban patches is gradually calibrated toward the dominant growth pattern through the steps of the CA model. The proposed model is applied to simulate urban growth in the Tehran megalopolitan area during 2000–2006–2012. The results from this model were compared with two common models: cell‐based CA and logistic‐patch CA. The proposed model yields a degree of patch‐level agreement that is 23.4 and 7.5% higher than those of these pre‐existing models, respectively. This reveals that the patch‐based CA model simulates actual development patterns much better than the two other models. 相似文献
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This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-economic variables dealing with urban sprawl were operationalised to create a probability surface of spatiotemporal states of built-up land use for the years 2006, 2016, and 2026. For validation, the model was evaluated by means of relative operating characteristic values for different sets of variables. The approach was calibrated for 2006 by cross comparing of actual and simulated land use maps. The achieved outcomes represent a match of 89% between simulated and actual maps of 2006, which was satisfactory to approve the calibration process. Thereafter, the calibrated hybrid approach was implemented for forthcoming years. Finally, future land use maps for 2016 and 2026 were predicted by means of this hybrid approach. The simulated maps illustrate a new wave of suburban development in the vicinity of Tehran at the western border of the metropolis during the next decades. 相似文献
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Hong Shi Xia Li Zhenzhi Yang Taohong Li Yun Ren Tingting Liu Ningdong Yang Hang Zhang Guangzhao Chen Xun Liang 《Transactions in GIS》2020,24(4):1119-1138
Previous studies on tourism land use primarily focus on the spatial distribution, and its related impacts on the environment. Here, we propose a future tourism land use simulation model for mountain vacations based on the cellular automata and Markov chain methods, having verified and simulated tourism land use in Emeishan city at a spatial resolution of 30 × 30 m using remote sensing and GIS. In addition, we introduced a tourism land use intensity index to study the spatial expansion mode of tourism land use. The results have confirmed the validity of the model and demonstrated its ability to simulate future tourism land use. The average growth rate of tourism land use from 2010 to 2015 is 33.36%, and tourism land use will rise from 1.26% of Emeishan city’s land area in 2015 to 2.95% in 2030. Tourism land use shows a spatial expansion pattern along channels from scenic spots to the urban area. The growth of tourism land use in the protected area has an increasing trend when there is no restriction on development, especially in the Eshan region. The simulation results can provide useful implications and guides for regional tourism planning and management. 相似文献
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Land use is changing at accelerated rates in Taiwan, and illegal land use change practices (ILP) are regularly observed within conservation areas. For this reason, we map high-potential areas of ILP within the Soil and water conservation zone (SWCZ) as an aid for effective land management and conducted an exploratory analysis of explanatory variables to evaluate their variability within ILP hot spots. We used variables relevant to hot spots to develop a logistic regression model and identified seven statistically significant variables. We re-applied the logistic regression approach to produce spatially explicit predictions of ILP. High probability areas are distributed along the coastal regions, covering 26% of the SWCZ, and their major drivers are related to accessibility and topography. The results from this research provide relevant information on the major drivers of ILP and high-potential areas, which can support officials in monitoring efforts for better planning and governance within the SWCZ. 相似文献