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1.
Urban land use information plays an essential role in a wide variety of urban planning and environmental monitoring processes. During the past few decades, with the rapid technological development of remote sensing (RS), geographic information systems (GIS) and geospatial big data, numerous methods have been developed to identify urban land use at a fine scale. Points-of-interest (POIs) have been widely used to extract information pertaining to urban land use types and functional zones. However, it is difficult to quantify the relationship between spatial distributions of POIs and regional land use types due to a lack of reliable models. Previous methods may ignore abundant spatial features that can be extracted from POIs. In this study, we establish an innovative framework that detects urban land use distributions at the scale of traffic analysis zones (TAZs) by integrating Baidu POIs and a Word2Vec model. This framework was implemented using a Google open-source model of a deep-learning language in 2013. First, data for the Pearl River Delta (PRD) are transformed into a TAZ-POI corpus using a greedy algorithm by considering the spatial distributions of TAZs and inner POIs. Then, high-dimensional characteristic vectors of POIs and TAZs are extracted using the Word2Vec model. Finally, to validate the reliability of the POI/TAZ vectors, we implement a K-Means-based clustering model to analyze correlations between the POI/TAZ vectors and deploy TAZ vectors to identify urban land use types using a random forest algorithm (RFA) model. Compared with some state-of-the-art probabilistic topic models (PTMs), the proposed method can efficiently obtain the highest accuracy (OA = 0.8728, kappa = 0.8399). Moreover, the results can be used to help urban planners to monitor dynamic urban land use and evaluate the impact of urban planning schemes.  相似文献   

2.
高分辨率遥感影像提供了丰富的外观信息和空间结构信息,广泛应用于土地利用分类当中,源于文章领域的视觉词袋（Bag-of-Visual-Words,BoVW）模型现已成功应用于图像分类领域。传统的BoVW模型忽略了特征之间的空间布局信息和像素一致性信息,提出多重分割关联子特征,融合图像的外观信息、空间布局信息和像素一致性信息,实验表明该方法能够获取优于许多经典的遥感图像特征的性能。  相似文献   

3.
Fine-scale population distribution data at the building level play an essential role in numerous fields, for example urban planning and disaster prevention. The rapid technological development of remote sensing (RS) and geographical information system (GIS) in recent decades has benefited numerous population distribution mapping studies. However, most of these studies focused on global population and environmental changes; few considered fine-scale population mapping at the local scale, largely because of a lack of reliable data and models. As geospatial big data booms, Internet-collected volunteered geographic information (VGI) can now be used to solve this problem. This article establishes a novel framework to map urban population distributions at the building scale by integrating multisource geospatial big data, which is essential for the fine-scale mapping of population distributions. First, Baidu points-of-interest (POIs) and real-time Tencent user densities (RTUD) are analyzed by using a random forest algorithm to down-scale the street-level population distribution to the grid level. Then, we design an effective iterative building-population gravity model to map population distributions at the building level. Meanwhile, we introduce a densely inhabited index (DII), generated by the proposed gravity model, which can be used to estimate the degree of residential crowding. According to a comparison with official community-level census data and the results of previous population mapping methods, our method exhibits the best accuracy (Pearson R = .8615, RMSE = 663.3250, p < .0001). The produced fine-scale population map can offer a more thorough understanding of inner city population distributions, which can thus help policy makers optimize the allocation of resources.  相似文献   

4.
基于光谱和纹理特征的ALOS影像土地利用信息提取   总被引：1，自引：0，他引：1  
针对高分辨率遥感影像易于反映地物纹理特征的特点,综合利用地物的光谱和纹理特征进行分类,探讨适用于ALOS影像的土地利用信息提取方法。以川东丘陵地区影像为例,基于GLCM提取纹理信息,将提取的纹理特征向量采用赋权值法融合为一个综合纹理信息波段,然后采用面向对象法将其与光谱特征信息共同参与分类。与最大似然法的提取结果对比表明,考虑了纹理特征的面向对象分类方法能明显提高分类精度,Kappa精度提高了0.12;避免了椒盐现象,分割的地类边界具有更好的语义表达,更贴合地物实际分布特征;建筑用地和林地具有明显的纹理特征,而旱地纹理特征不明显。该方法不仅分出了6个基本地物类型,而且对于林地、建筑用地等类型还能进一步细分。  相似文献   

5.
Land use classification has benefited from the emerging big data, such as mobile phone records and taxi trajectories. Temporal activity variations derived from these data have been used to interpret and understand the land use of parcels from the perspective of social functions, complementing the outcome of traditional remote sensing methods. However, spatial interaction patterns between parcels, which could depict land uses from a perspective of connections, have rarely been examined and analysed. To leverage spatial interaction information contained in the above-mentioned massive data sets, we propose a novel unsupervised land use classification method with a new type of place signature. Based on the observation that spatial interaction patterns between places of two specific land uses are similar, the new place signature improves land use classification by trading off between aggregated temporal activity variations and detailed spatial interactions among places. The method is validated with a case study using taxi trip data from Shanghai.  相似文献   

6.
This study evaluates land use/cover changes and urban expansion in Greater Dhaka, Bangladesh, between 1975 and 2003 using satellite images and socio-economic data. Spatial and temporal dynamics of land use/cover changes were quantified using three Landsat images, a supervised classification algorithm and the post-classification change detection technique in GIS. Accuracy of the Landsat-derived land use/cover maps ranged from 85 to 90%. The analysis revealed that substantial growth of built-up areas in Greater Dhaka over the study period resulted significant decrease in the area of water bodies, cultivated land, vegetation and wetlands. Urban land expansion has been largely driven by elevation, population growth and economic development. Rapid urban expansion through infilling of low-lying areas and clearing of vegetation resulted in a wide range of environmental impacts, including habitat quality. As reliable and current data are lacking for Bangladesh, the land use maps produced in this study will contribute to both the development of sustainable urban land use planning decisions and also for forecasting possible future changes in growth patterns.  相似文献   

7.
城市轨道交通对土地利用变化的时空效应   总被引：3，自引：1，他引：2  
定量分析轨道交通对城市内部精细土地利用复杂变化影响的时空效应,对于预测未来新建站点对土地利用的影响以及规划方案的调整与优化具有重要的指导意义。本文提出结合历史高分遥感影像与POI数据获取多时间节点精细土地利用信息的方法,并以广州市二号和八号地铁线为例,结合逐步回归模型与站点用地功能分类,从时间和空间两个维度定量研究地铁对土地利用转变的复杂影响过程与空间差异规律。结果表明,轨道交通促使站点周边低密度居住用地向商业用地、高密度居住用地等高效益土地利用方式的转变;轨道交通在规划、建设、运营不同阶段对于周边土地利用的影响呈现显著的差异规律;地铁站点对土地利用变化影响规律具有明显的空间异质性特征,与站点在城市里的位置以及站点周边的土地利用有关,对城市中心区域的影响较小,对郊区的影响主要与可用的非建设用地面积相关,而工业用地对土地利用变化具有限制作用;轨道交通还带来用地功能和性质的转变,这样的转变大多发生在地铁站点开通运营的时间点。  相似文献   

8.
以福州市为研究区,采用1988～2008年5个时间点的LandsatTM／ETM遥感影像为数据源,利用遥感信息提取技术,获取福州市建设用地扩展信息。从扩展来源、扩展的规模和强度、分形特征、重心和方位变化等方面分析了福州市建设用地扩展的时空变化,并从自然、经济、社会等方面探讨福州建设用地扩展的驱动力。研究结果表明：（1）福州市建设用地扩展的主要来源一直以耕地为主;（2）福州市建设用地的扩展,经历了一个由“快－慢－快－更快”的阶段性过程,城市形态越来越趋于复杂,遵循着“先东后西再南,北部稳定发展”的时空规律;（3）城市建设用地扩展是多种因素综合作用的结果,在不同的扩展阶段,不同的因素组合占主导。  相似文献   

9.
遥感数据为土地利用/覆盖变化提供了海量数据来源,如何选择合适空间分辨率的遥感影像进行特定地区的土地利用/覆盖变化研究,成为土地利用/覆盖变化研究的一个重要内容。地统计学方法已经广泛应用与遥感图像处理以及土地覆盖分类研究中,但应用于土地利用/覆盖变化的研究还比较缺乏。北京地区为研究区,运用遥感和地统计分析方法对该区土地利用/覆盖变化的空间结构的变异特征和合理的遥感影像数据源的选取问题做了初步探讨。研究表明地统计学方法能够揭示土地利用/覆盖变化的空间变异特征,有助于选择有效的遥感影像数据进行不同地区的土地利用/覆盖变化分析。  相似文献   

10.
基于TM和ETM+遥感分析的石家庄市土地利用/覆被变化研究   总被引：25，自引：10，他引：15  
文章利用Landsat的TM 和ETM+数据,对石家庄市1987年和2001年的土地利用/覆被进行分类,并对这一期间发生的土地利用/覆被变化进行了定量分析。结果显示:研究区主要土地利用/覆被类型可以划分为城市用地、居住用地、农田、菜地、林地、果园、草地、水体、沙地/裸地等9类;研究区域发生的土地利用/覆被变化主要由近年来的快速城市化过程引起。变化较大的土地利用类型为城市用地、农田、菜地和林地;变化较大的区域主要分布在城市的边缘和市区的东部及西北部。  相似文献   

11.
西安城市扩张及其驱动力分析   总被引：79，自引：6，他引：73  
随着人口的增长与经济的发展,尤其我国西部城市在西部大开发的背景下,大中城市的扩张十分明显,深刻地影响城市周边的生态环境。如何快速准确地获取城市扩张信息,并分析其驱动力机制,对于指导城市规划,优化西部生态环境与可持续发展都具有十分重要的意义。作者分别采用了监督分类法和归一化裸露指数 (NDBI) 法提取了西安市的城市边界信息,并对二者进行对比分析,认为监督分类法提取的城市边界信息较为准确。在此基础上通过对相关统计资料的分析,认为西安市城区快速扩张与西部大开发以来西安市固定资产投资额的大幅增加以及经济的快速发展有密切的关系,此外人口的增加、交通等基础设施的发展也是重要的驱动因素。  相似文献   

12.
基于多源遥感的聚落与多级人口统计 数据的关系分析   总被引：2，自引：1，他引：1  
在四川省市州、区县和典型村等三级尺度上,探讨了基于多源遥感的聚落面积与多级人口统计数据的关系。首先,从LANSAT TM影像中提取农村和城镇聚落信息,从Quickbird 影像上提取农村聚落及其房屋地基信息。其次,通过叠加统计得到各级统计单元内的聚落面积;再次,在四川省市州和区县尺度上,分别对城乡聚落面积和总人口数、城镇聚落面积和非农业人口数、农村聚落面积和农业人口数等进行相关性分析, 城镇聚落和非农业人口数的相关系数最高,分别为0.962和0.791,并建立了基于城镇聚落面积的非农业人口数估算模型,其模型的判定系数分别为0.926和0.625;最后,在村级尺度上,对农村聚落及其房屋地基面积与农村人口数之间的相关性进行分析,其相关系数分别为0.806和0.825,分别建立基于农村聚落及其房屋地基面积的农村人口数估算模型,其模型的判定系数分别为0.65和0.68。研究表明,LANDSAT TM适用于大尺度的非农业人口估算,估算效果随尺度的降低而有所降低;Quickbird适合于精细尺度的农业人口估算。  相似文献   

13.
Geo-temporal Twitter demographics   总被引：1，自引：0，他引：1  
This paper seeks and uses highly disaggregate social media sources to characterize Greater London in terms of flows of people with modelled individual characteristics, as well as conventional measures of land use morphology and night-time residence. We conduct three analyses. First, we use the Shannon Entropy measure to characterize the geography of information creation across the city. Second, we create a geo-temporal demographic classification of Twitter users in London. Third, we begin to use Twitter data to characterize the links between different locations across the city. We see all three elements as data rich, highly disaggregate geo-temporal analysis of urban form and function, albeit one that pertains to no clearly defined population. Our conclusions reflect upon this severe shortcoming in analysis using social media data, and its implications for progressing our understanding of socio-spatial distributions within cities.  相似文献   

14.
The excessive expansion of urbanized areas has resulted in haphazard land utilization, immoderate consumption of superior agricultural land and water resources, significant fragmentation of agricultural landscape, and gradual deterioration of the agro-ecological environment. Combined, these factors cause poor land use efficiency. Under these circumstances, comprehensively assessing land use efficiency for urban agriculture is a key issue in land use research. Currently, evaluation methods for agricultural land use efficiency narrowly concentrate on aspects of economic input and output. However, urban agro-ecosystems can provide diverse economic, social, and ecological services and functions. In particular, the social and ecological services and functions originating from agricultural land, which have a higher value than economic services, play a significant role in ensuring regional social, ecological, and environmental security. However, recent research has rarely taken these benefits into consideration. Therefore, land use value has been greatly underestimated, which has resulted in mishandled and poor land use policies. In this study, we apply Landsat imagery and social and economic statistical data for the Xi'an metropolitan zone(XMZ) to investigate agricultural multi-functionality. We develop an evaluation framework for urban agricultural land use efficiency and identify agro-ecosystem services and functions as important outputs from agricultural land. The land use efficiency of urban agriculture is then evaluated using ecosystem services models, providing a mechanism for assessing spatial-temporal changes in land use efficiency in the XMZ from 1999 to 2015. Four important conclusions are reached from this analysis. First, the rapid urbanization and agricultural transformation from traditional cereal cultivation to modern urban agriculture has resulted in steadily increasing costs, outputs, and land use efficiency of urban agriculture. The total output value increased 41% and land use efficiency per hectare increased by 33.13% on average. Second, the spatial patterns of comprehensive output and land use efficiency were dominated by economic outputs from agricultural land. Areas near cities, which are dominated by orchard and arable land, providemore economic functions. These areas support and regulate services due to the transformation from extensive cereal production to intensive modern urban agriculture; therefore, they have higher output value and land use efficiency. In contrast, areas distant from cities, towns, and high traffic roads, namely, remote rural areas, provide more support and regulating services, but have relatively lower economic function due to inaccessibility to urban markets and slow agricultural transformation. Therefore, these areas have lower output value and land use efficiency. The spatial change in agricultural output and land use efficiency in urban areas is strongly dependent on the degree of urbanization and agricultural transformation. Third, the total output value and land use efficiency of urban agriculture measured with our approach are much higher than evaluations using traditional methods. However, the spatial patterns measured using the two approaches are in agreement. The evaluation framework integrates ecological services and economic and social functions into a comprehensive output from agricultural land. This approach is more methodical and accurate for evaluating the comprehensive efficiency of land use based on quantities and spatial scale because they are at the pixel scale. Finally, the evaluation results have important implications for enhancing current agricultural subsidies and even implementing ecological payment policies in China. Most importantly, they can be directly applied to agricultural transformation regulations, decision-making, and guidance for rational land utilization.  相似文献   

15.
基于谱间特征和归一化指数分析的城市建筑用地信息提取   总被引：36，自引：0，他引：36  
徐涵秋 《地理研究》2005,24(2):311-320
以福州市ETM+影像为例,研究了城市建筑用地信息快速准确提取的原理和方法。通过对归一化差异型指数构成原理的分析以及对同名异义和异名同义现象的甄别,选取了归一化差异建筑指数(NDBI)、修正归一化差异水体指数(MNDWI)和土壤调节植被指数(SAVI)来代表城市建成区的三种最主要的土地利用类型--建筑用地、水体和植被。在此基础上进一步对这三个新的指数波段进行谱间特征分析,最后利用基于规则的逻辑判别运算将城市建筑用地信息提取出来。研究表明这一方法可以使繁杂的多波段谱间分析得以简化, 是一种快速准确、未经人工干预的建筑用地信息提取方法。本文还探讨了在城市建成区的研究中采用SAVI指数替代NDVI指数的优点。  相似文献   

16.
The excessive expansion of urbanized areas has resulted in haphazard land utilization, immoderate consumption of superior agricultural land and water resources, significant fragmentation of agricultural landscape, and gradual deterioration of the agro-ecological environment. Combined, these factors cause poor land use efficiency. Under these circumstances, comprehensively assessing land use efficiency for urban agriculture is a key issue in land use research. Currently, evaluation methods for agricultural land use efficiency narrowly concentrate on aspects of economic input and output. However, urban agro-ecosystems can provide diverse economic, social, and ecological services and functions. In particular, the social and ecological services and functions originating from agricultural land, which have a higher value than economic services, play a significant role in ensuring regional social, ecological, and environmental security. However, recent research has rarely taken these benefits into consideration. Therefore, land use value has been greatly underestimated, which has resulted in mishandled and poor land use policies. In this study, we apply Landsat imagery and social and economic statistical data for the Xi’an metropolitan zone (XMZ) to investigate agricultural multi-functionality. We develop an evaluation framework for urban agricultural land use efficiency and identify agro-ecosystem services and functions as important outputs from agricultural land. The land use efficiency of urban agriculture is then evaluated using ecosystem services models, providing a mechanism for assessing spatial-temporal changes in land use efficiency in the XMZ from 1999 to 2015. Four important conclusions are reached from this analysis. First, the rapid urbanization and agricultural transformation from traditional cereal cultivation to modern urban agriculture has resulted in steadily increasing costs, outputs, and land use efficiency of urban agriculture. The total output value increased 41% and land use efficiency per hectare increased by 33.13% on average. Second, the spatial patterns of comprehensive output and land use efficiency were dominated by economic outputs from agricultural land. Areas near cities, which are dominated by orchard and arable land, provide more economic functions. These areas support and regulate services due to the transformation from extensive cereal production to intensive modern urban agriculture; therefore, they have higher output value and land use efficiency. In contrast, areas distant from cities, towns, and high traffic roads, namely, remote rural areas, provide more support and regulating services, but have relatively lower economic function due to inaccessibility to urban markets and slow agricultural transformation. Therefore, these areas have lower output value and land use efficiency. The spatial change in agricultural output and land use efficiency in urban areas is strongly dependent on the degree of urbanization and agricultural transformation. Third, the total output value and land use efficiency of urban agriculture measured with our approach are much higher than evaluations using traditional methods. However, the spatial patterns measured using the two approaches are in agreement. The evaluation framework integrates ecological services and economic and social functions into a comprehensive output from agricultural land. This approach is more methodical and accurate for evaluating the comprehensive efficiency of land use based on quantities and spatial scale because they are at the pixel scale. Finally, the evaluation results have important implications for enhancing current agricultural subsidies and even implementing ecological payment policies in China. Most importantly, they can be directly applied to agricultural transformation regulations, decision- making, and guidance for rational land utilization.  相似文献   

17.
ABSTRACT

The investigation of human activity patterns from location-based social networks like Twitter is an established approach of how to infer relationships and latent information that characterize urban structures. Researchers from various disciplines have performed geospatial analysis on social media data despite the data’s high dimensionality, complexity and heterogeneity. However, user-generated datasets are of multi-scale nature, which results in limited applicability of commonly known geospatial analysis methods. Therefore in this paper, we propose a geographic, hierarchical self-organizing map (Geo-H-SOM) to analyze geospatial, temporal and semantic characteristics of georeferenced tweets. The results of our method, which we validate in a case study, demonstrate the ability to explore, abstract and cluster high-dimensional geospatial and semantic information from crowdsourced data.  相似文献   

18.
孟祥锐  张树清  臧淑英 《地理科学》2018,38(11):1914-1923
以洪河国家级自然保护区为研究对象,应用卷积神经网络（CNN）方法进行高分辨率湿地遥感影像的分类研究,并与基于光谱支持向量机（SP-SVM）的方法和基于纹理及光谱的支持向量机（TSP-SVM）的方法进行了对比。结果显示,对于所选取的2个研究区域,CNN分类方法的全局精度高于SP-SVM方法5.61%和5%,高于TSP-SVM方法4.18%和4.15%。尤其对于部分湿地植被的分类精度明显高于SP-SVM和TSP-SVM方法。研究表明,卷积神经网络为湿地识别的精细划分提供了有利的手段。  相似文献   

19.
基于多源遥感数据的城市变化监测研究——以郑州市为例   总被引：2，自引：0，他引：2  
遥感技术以其具有宏观、快速、准确、及时等特点为城市变化趋势分析提供了快速便捷的途径。选取郑州市1988年TM、2001年ETM+和2007年CBERS遥感数据,经过一系列数据预处理后,采用决策树分类算法,进行基于知识遥感分类及专题图的制作。对分类结果利用土地利用结构变化、动态变化率、转移矩阵等指标进行变化分析,分析结果揭示了不同时期城市扩张与植被、水体和农村居民点的变化关系,对于地区土地可持续利用具有重要参考作用。研究数据表明,20年来郑州市城市用地以年均8%的速度增长,植被减少25%,水体减少30%。  相似文献   

20.
城市空间分异研究对城市规划、旅游地资源配置、公共交通优化等具有重要意义。该文基于2016年北京市核心六区微博签到数据,根据游客和当地居民签到行为差异,依据时间特征、空间特征和签到比率特征,通过机器学习方法对游客与当地居民进行分类,利用局部莫兰指数和基于签到POI类型的层次聚类法实现细粒度的签到聚集区类型识别,并探究两类人群签到聚集区空间分布与签到类型的差异。结果表明:该文分类模型各项评价指标均在0.9以上,较前人分类结果有较大提升;基于该分类模型所得游客和居民社交媒体签到特征差异显著,游客签到主要集中在故宫周边,以风景名胜、体育休闲和餐饮服务类型为主,居民签到较分散且科教文化服务、商务住宅类型突出,同时发现“菖蒲河公园”等居民签到多而游客签到少的显著差异地区。利用社交媒体数据进行人群异质性角度下的空间分异研究,有助于准确捕捉不同人群在城市中的活动类型、特征并探究城市内部活动规律。  相似文献   

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