共查询到20条相似文献，搜索用时 15 毫秒
1.
《The Professional geographer》2013,65(3):371-386
Urbanization and the ability to manage for a sustainable future present numerous challenges for geographers and planners in metropolitan regions. Remotely sensed data are inherently suited to provide information on urban land cover characteristics, and their change over time, at various spatial and temporal scales. Data models for establishing the range of urban land cover types and their biophysical composition (vegetation, soil, and impervious surfaces) are integrated to provide a hierarchical approach to classifying land cover within urban environments. These data also provide an essential component for current simulation models of urban growth patterns, as both calibration and validation data. The first stages of the approach have been applied to examine urban growth between 1988 and 1995 for a rapidly developing area in southeast Queensland, Australia. Landsat Thematic Mapper image data provided accurate (83% adjusted overall accuracy) classification of broad land cover types and their change over time. The combination of commonly available remotely sensed data, image processing methods, and emerging urban growth models highlights an important application for current and next generation moderate spatial resolution image data in studies of urban environments. 相似文献
2.
Modeling Spatial Processes of Urban Growth in African Cities: A Case Study of Nairobi City 总被引：1，自引：0，他引：1
《Urban geography》2013,34(2):259-272
Africa's urban population growth has been especially rapid, averaging about 5% per year over the past two decades. As a result, many urban areas have experienced dramatic growth that is seriously outstripping the capacity of most cities to provide adequate services for their residents. Although population growth and urbanization rates in Africa have slowed recently due to a number of factors including HIV/AIDS, urban growth is still expected to double by 2030, leading to dramatic sprawl with serious environmental and social consequences. Using Nairobi as an example of a rapidly urbanizing African city, we studied the dynamics of land use and land cover change using satellite data and addressed the need for models and urban management tools that can guide sustainable urban planning policies. Cellular Automata, which integrate biophysical factors with dynamic spatial modeling, are used in this study. The model was calibrated and tested using time series of urbanized areas derived from land use/cover maps, produced from remotely sensed imagery, with future urban growth projected to 2030. Model assessment results showed high levels of accuracy, indicating that simulation findings were realistic, thereby confirming the effectiveness of the model. Results further showed that the model is a useful and effective tool to foresee the spatial consequences of planning policies in the context of many African cities. The forecast for Nairobi showed unsustainable sprawl. 相似文献
3.
A. J. Tatem H. G. Lewis P. M. Atkinson M. S. Nixon 《International journal of geographical information science》2013,27(7):647-672
Land cover class composition of remotely sensed image pixels can be estimated using soft classification techniques increasingly available in many GIS packages. However, their output provides no indication of how such classes are distributed spatially within the instantaneous field of view represented by the pixel. Techniques that attempt to provide an improved spatial representation of land cover have been developed, but not tested on the difficult task of mapping from real satellite imagery. The authors investigated the use of a Hopfield neural network technique to map the spatial distributions of classes reliably using information of pixel composition determined from soft classification previously. The approach involved designing the energy function to produce a ‘best guess’ prediction of the spatial distribution of class components in each pixel. In previous studies, the authors described the application of the technique to target identification, pattern prediction and land cover mapping at the sub-pixel scale, but only for simulated imagery. We now show how the approach can be applied to Landsat Thematic Mapper (TM) agriculture imagery to derive accurate estimates of land cover and reduce the uncertainty inherent in such imagery. The technique was applied to Landsat TM imagery of small-scale agriculture in Greece and largescale agriculture near Leicester, UK. The resultant maps provided an accurate and improved representation of the land covers studied, with RMS errors for the Landsat imagery of the order of 0.1 in the new fine resolution map recorded. The results showed that the neural network represents a simple efficient tool for mapping land cover from operational satellite sensor imagery and can deliver requisite results and improvements over traditional techniques for the GIS analysis of practical remotely sensed imagery at the sub pixel scale. 相似文献
4.
Elizabeth A. Wentz Donna J. Peuquet Sharolyn Anderson 《International journal of geographical information science》2013,27(9):1309-1325
The availability of spatial data on an unprecedented scale as well as advancements in analytical and visualization techniques gives researchers the opportunity to study complex problems over large urban and regional areas. Nevertheless, few individual data sets exist that provide both the requisite spatial and/or temporal observational frequency to truly facilitate detailed investigations. Some data are collected frequently over time but only at a few geographic locations (e.g., weather stations). Similarly, other data are collected with a high level of spatial resolution but not at regular or frequent time intervals (e.g., satellite data). The purpose of this article is to present an interpolation approach that leverages the relative temporal richness of one data set with the relative spatial richness of another to fill in the gaps. Because different interpolation techniques are more appropriate than others for specific types of data, we propose a space–time interpolation approach whereby two interpolation methods – one for the temporal and one for the spatial dimension – are used in tandem to increase the accuracy results. We call our ensemble approach the space–time interpolation environment (STIE). The primary steps within this environment include a spatial interpolation processor, a temporal interpolation processor, and a calibration processor, which enforces phenomenon-related behavioral constraints. The specific interpolation techniques used within the STIE can be chosen on the basis of suitability for the data and application at hand. In this article, we first describe STIE conceptually including the data input requirements, output structure, details of the primary steps, and the mechanism for coordinating the data within those steps. We then describe a case study focusing on urban land cover in Phoenix, Arizona, using our working implementation. Our empirical results show that our approach increased the accuracy for estimating urban land cover better than a single interpolation technique. 相似文献
5.
土地利用/覆盖变化空间变异特征与遥感影像空间分辨率的选取——以北京地区为例 总被引：1，自引：0，他引：1
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
6.
土地变化模型方法综述 总被引：3，自引：2，他引：1
土地系统变化长期以来不仅是地理学研究热点,也是资源环境经济学、生态学、城市规划等多学科领域关注的主题。构建模型模拟土地变化能够促进理解人地相互作用机制,模拟结果可为土地资源优化与资源环境政策制定提供依据。不同研究者基于不同学科理论、应用多种方法构建土地变化模型,模型从早期关注自然覆被类型变化发展到对人类决策行为的刻画,从统计方法发展到更突出空间分布的元胞自动机方法,以及更聚焦土地变化过程的经济学方法和多主体方法。未来土地变化模型发展方向为：在多尺度进行多方法耦合,对土地变化过程进行更为明晰地刻画,将土地变化模型与其他地球系统模型耦合等方面,进一步能够促进解释复杂人地系统,并推进模型在决策支持层面的应用。 相似文献
7.
Bo Huang Li Zhang Bo Wu 《International journal of geographical information science》2013,27(3):379-398
Understanding the complexity of urban expansion requires an analysis of the factors influencing the spatial and temporal processes of rural–urban land conversion. This study aims at building a statistical land conversion model to assist in understanding land use change patterns. Specifically, GIS coupled with a logistic regression model and exponential smoothing techniques is used for exploring the effects of various factors on land use change. These factors include population density, slope, proximity to roads, and surrounding land use, and their influence on land use change is studied for generating a predictive model. Methods to reduce spatial autocorrelation in a logistic regression framework are also discussed. Primarily, an optimal sampling scheme that can eliminate spatial autocorrelation while maintaining adequate samples to allow the model to achieve the comparable accuracy as the spatial autoregressive model is developed. Since many of the previous studies on modeling the spatial complexity of urban growth ignored temporal complexity, a modified exponential smoothing technique is employed to produce a smoothed model from a series of bi‐temporal models obtained from different time periods. The proposed model is validated using the multi‐temporal land use data in New Castle County, DE, USA. It is demonstrated that our approach provides an effective option for multi‐temporal land use change modeling and the modeling results help interpret the land use change patterns. 相似文献
8.
应用线性光谱分离技术研究喀斯特地区土地覆被变化——以贵州省关岭县为例 总被引：24，自引：3，他引：21
喀斯特地区土地覆被主要类型除了和非喀斯特地区一样的植被和裸露土壤外,还存在一个广泛分布的裸露基岩,一般遥感处理方法不具备直接定量提取这三类土地覆被参数的能力。基于地物光谱线性混合模型的线性光谱分离技术,可以在亚象元的尺度上直接获取植被覆盖、裸露土壤和裸露基岩等在各象元区域内的比例,非常适合用于喀斯特地区的土地覆被变化的研究。本文利用1987年2月17日和1999年12月27日LandsatTM各6波段遥感影像,使用ENVI软件,分离出植被、裸露土壤、裸露岩石和阴影等土地覆被丰度和RMS的空间分布。对比结果表明,研究区1987～1999年,植被覆盖率上升593%,裸露土壤面积下降1215%,裸露基岩面积上升408%。表明研究区尽管植被在恢复、水土流失总量在减少,但石漠化面积在明显上升,生态形势依旧严峻。 相似文献
9.
Peri-urban areas are usually a heterogeneous mosaic of rural, urban and natural systems which are quite dynamic across time. In this paper we contrast a static and a dynamic-based classification of local administrative units (LAU) in the Lisbon Metropolitan Area (LMA) to gain further insights onto the current land cover patterns and recent land cover changes in urban and peri-urban areas of the LMA. Using 16 landscape pattern indicators, we characterized the 211 LAU in the region contrasting a static (2006 data) and a dynamic-based (changes during the period 1990–2006) approach, and used cluster analyses to identify LAU typologies. Using the static approach we identified seven types of LAU, of which two were clearly urban, two could be considered rural, and three could be considered peri-urban. These latter could be distinguished among themselves by the landscape matrix type where urban areas were inserted. The dynamic-based approach yielded five types of LAU with specific trajectories in time, ranging from stable to highly dynamic. The frequency of the different dynamic typologies was not independent from the static ones, with typically urban areas being predominantly stable and rural areas having characteristic and exclusive trajectories of change. Peri-urban LAU were mostly moderately dynamic but shared a typology profile mixing highly dynamic LAU with moderately dynamic and stable ones. The combination of a static and dynamic view provides added value for the formulation of spatial planning policies in peri-urban areas. 相似文献
10.
珠江三角洲土地覆盖变化对地表温度的影响 总被引：35，自引：0，他引：35
由于经济的快速增长,1978年以来的25年中,珠江三角洲地区的土地覆盖变化,特别是城市扩展速度非常之快。通过把遥感和地理信息系统相结合,研究了土地覆盖变化及城市增长状况,并且评估了城市增长对地表温度的影响。利用陆地卫星多时段数据监测了土地利用和土地覆盖变化;通过陆地卫星热红外单波段反演了地表温度,研究了土地覆盖变化特别是城市增长对地表温度的影响。结果发现,珠江三角洲地区土地覆盖变化明显,城市增长显著且不平衡。城市的发展使城市化地区的地表温度提高了8.9K。研究表明,遥感和地理信息系统的结合,在监测和分析土地覆盖变化,特别是城市增长状况以及评估城市化对地表温度的影响方面,是十分有效的。 相似文献
11.
12.
巴西土地利用/覆盖变化时空格局及驱动因素 总被引：6，自引：1，他引：5
土地利用/覆盖变化(LUCC)是全球变化研究的热点问题之一。本文采用人机交互方法基于2005 年基准年的Landsat TM/ETM遥感影像修正欧空局GlobalCover 2005 年土地利用数据,进而采用逆时相目视解译法从1980年基准年的Landsat MSS/TM遥感影像数据提取1980-2005 年土地利用/覆盖变化信息,分析其变化的时空格局及驱动因素。结果表明:1980-2005年的25年间,巴西土地利用/覆盖变化面积达79.43万km2,占土地总面积的9.33%。其中,单纯耕地像元面积增加了20.18 万km2;耕地/自然植被镶嵌混合像元区面积增加了10.70 万km2;林地面积减少了53.12 万km2;灌丛与草地净增加21.10 万km2;水体面积增加0.46 万km2;城乡建设用地面积增加7573.87 km2。由此导致热带和亚热带湿润阔叶林生态地理区、热带和亚热带干旱阔叶林生态地理区、热带及亚热带草原生态地理区、草原和沼泽湿地生态地理区、沙漠和旱生植物生态地理区以及红树林生态地理区内分别呈现不同的土地利用/覆盖变化特征。近25 年间,地形地貌、气候、植被等自然地理条件深刻影响着土地利用的宏观格局,而土地利用政策调控、经济及对外贸易发展、人口增加及空间迁移、道路修建等是导致巴西土地利用变化的主要原因。 相似文献
13.
Understanding the relationship between vegetation and climate is essential for predicting the impact of climate change on broad-scale landscape processes. Utilizing vegetation indicators derived from remotely sensed imagery, we present an approach to forecast shifts in the future distribution of vegetation. Remotely sensed metrics representing cumulative greenness, seasonality, and minimum cover have successfully been linked to species distributions over broad spatial scales. In this paper we developed models between a historical time series of Advanced Very High Resolution Radiometer (AVHRR) satellite imagery from 1987 to 2007 at 1 km spatial resolution with corresponding climate data using regression tree modeling approaches. We then applied these models to three climate change scenarios produced by the Canadian Centre for Climate Modeling and Analysis (CCCma) to predict and map productivity indices in 2065. Our results indicated that warming may lead to increased cumulative greenness in northern British Columbia and seasonality in vegetation is expected to decrease for higher elevations, while levels of minimum cover increase. The Coast Mountains of the Pacific Maritime region and high elevation edge habitats across British Columbia were forecasted to experience the greatest amount of change. Our approach provides resource managers with information to mitigate and adapt to future habitat dynamics. Forecasting vegetation productivity levels presents a novel approach for understanding the future implications of climate change on broad scale spatial patterns of vegetation. 相似文献
14.
城市用地景观对理解城市扩张过程中土地利用的内部特征及其动态变化具有重要意义。利用2001年Landsat7和2007年Spot4影像,采用人工神经网络方法,提取郑州市土地覆被变化信息;并利用景观指数中的平均斑块面积指数、景观形状指数、平均分维指数和平均连接度指数对土地利用景观沿主要方向进行梯度分析。揭示了城市扩张与土地利用的景观变化是一个过程的两个方面;主要经济发展区已成为城市空间扩张的推动力,在提高平均地块面积和地块连通性方面起到一定积极作用,在距市中心10 km范围内紧凑度提高,整体上松散式和紧凑式扩张并存。 相似文献
15.
Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization 总被引：12，自引：0，他引：12
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
16.
城市土地利用变化模拟是优化土地资源配置的科学依据,提高其精细化程度和可靠性有助于准确把握城市用地发展趋势,对城市土地资源精准调控具有重要意义。基于宏观遥感分类的土地利用变化模拟,难以在街区尺度上揭示城市用地社会功能变化及精细化模拟中空间尺度效应来源和作用机理。本文联合遥感影像和POI数据识别出城市土地利用精细化特征,运用响应面法率定土地利用精细化模拟的最优空间尺度组合,在此基础上,利用CA-Markov模型开展了未来土地利用变化的精细化模拟。以武汉市中心城区为应用案例,研究结果表明：基于POI 的城市土地利用精细化识别方法,可以深度解析城市建设用地的社会功能,极大改善了传统基于遥感的土地覆被宏观解译效果;研究区土地利用变化元胞自动机精细化模拟的最优空间尺度组合是30 m元胞、7×7邻域以及冯诺依曼邻域类型,采用最优空间尺度组合能够提高土地利用变化精细化模拟的可靠性。响应面试验设计结果可有效识别精细化模拟过程中空间尺度效应的主要来源,并区分其对模拟精度的影响程度与正负效应;预计到2025年,研究区建设用地范围将继续向周边扩张,各类型用地之间互为交织,土地利用空间格局将呈更加破碎化趋势。 相似文献
17.
Land cover change is one of the major contributors to global change, but long-term, broad-scale, detailed and spatially explicit assessments of land cover change are largely missing, although the availability of historical maps in digital formats is increasing. The problem often lies in efficiency of analyses of historical maps for large areas. Our goal was to assess different methods to reconstruct land cover and land use from historical maps to identify a time-efficient and reliable method for broad-scale land cover change analysis. We compared two independent forest cover reconstruction methods: first, regular point sampling, and second, wall-to-wall mapping, and tested both methods for the Polish Carpathians (20,000 km2) for the 1860s, 1930s and 1970s. We compared the two methods in terms of their reliability for forest change analysis, relative to sampling error, point location and landscape context including local forest cover, area of the spatial reference unit and forest edge-to-core ratio. Our results showed that the point-based analysis overestimated forest cover in comparison to wall-to-wall mapping by 1–3%, depending on the mapping period. The reasons for the differences were mainly the backdating approach and map generalisation rather than the point grid position or sampling error. When we compared forest cover trajectories over time, we found that the point-based reconstruction captured forest cover dynamics with a comparable accuracy to the wall-to-wall mapping. More broadly, our assessment showed that historical maps can provide valuable data on long-term land cover trends, and that point-based sampling can be an efficient and accurate way to assess forest area and change trends. We suggest that our point-based approach could allow land cover mapping across much of Europe starting in the 1800s. Our findings are important because they suggest that land cover change, a key component of global change, can be assessed over large areas much further back in time than it is commonly done. This would allow to truly understand path dependencies, land use legacies, and historical drivers of land cover change. 相似文献
18.
Jida Wang 《International journal of geographical information science》2013,27(2):229-253
Urbanization is an important issue concerning diverse scientific and policy communities. Computational models quantifying locations and quantities of urban growth offer numerous environmental and socioeconomic benefits. Traditional urban growth models are based on a single-algorithm fitting procedure and thus restricted on their ability to capture spatial heterogeneity. Accordingly, a GIS-based modeling framework titled multi-network urbanization (MuNU) model is developed that integrates multiple neural networks. The MuNU model enables a filtering approach where input data patterns are automatically reallocated into appropriate neural networks with targeted accuracies. We hypothesize that observations classified by individual neural networks share greater homogeneity, and thus modeling accuracy will increase with the integration of multiple targeted algorithms. Land use and land cover data sets of two time snapshots (1977 and 1997) covering the Denver Metropolitan Area are used for model training and validation. Compared to a single-step algorithm – either a stepwise logistic regression or a single neural network – several improvements are evident in the visual output of the MuNU model. Statistical validations further quantify the superiority of the MuNU model and support our hypothesis of effective incorporation of spatial heterogeneity. 相似文献
19.
AutoLogistic 方法在土地利用格局模拟中的应用 —— 以张家界市永定区为例 总被引：7，自引：1，他引：6
土地利用/ 土地覆被变化(LUCC) 是当前研究全球变化的重要内容, 而区域土地利用 格局模拟是LUCC 研究的核心内容之一。以张家界市永定区为研究单元, 根据由2005 年土地 利用现状图和数字高程模型数据源得到的土地利用、地形、河流以及道路等空间数据, 对区 域土地利用类型空间格局的空间自相关性特征进行了建模研究, 并通过在传统Logistic 模型 中引入描述空间自相关性的成份, 实现了能够考虑自相关性因素的回归分析模型 (AutoLogistic 模型), 同时应用该模型对区域土地利用格局进行了模拟和分析。结果显示, 通 过与没有考虑空间自相关性的回归模型(传统Logistic 模型) 相比较, 该模型显示了更好的拟 合优度和更高的拟合准确率(耕地、林地、建设用地及未利用地的ROC 值分别从0.851、 0.913、0.877 和0.852 提高到0.893、0.940、0.907 和0.863)。研究结果说明了基于 AutoLogistic 方法的土地利用格局的相关性建模在一定意义上是合理的。同时研究结果也可以 为永定区及其相似地区的土地利用规划决策提供更为科学的依据。 相似文献
20.
城市土地利用/覆盖变化与热环境生态调控研究进展与展望 总被引：3，自引：3，他引：0
城市土地利用/覆盖变化(LUCC)与热环境生态调控是城市生态学和城市气候适应性关注的热点问题。在提出城市LUCC/空间结构与生态服务热调节功能连接的重要性的基础上,综述了城市土地利用变化、城市绿色基础设施在热岛减缓和气候适应性发挥的作用,评述了观测实验、定量遥感和过程模型方面以及热调控的进展情况。基于此认为,局地或区域尺度城市高精度结构组分高精度遥感探测方法、城市高精度下垫面多尺度(功能区/覆盖组分/构造或材质等)对局地气温和辐射能量平衡影响机理和定量贡献识别、城市生态系统热调节功能的城市地表结构组分调控阈值确定、以及区域或全球尺度城市土地利用/覆盖变化影响的生物地球物理机制定量化认知等,是未来重要的发展方向。 相似文献