密云水库上游土地利用与景观格局变化特征

基于遥感监测的多期土地利用/土地覆盖数据,详细分析了密云水库上游地区近10年土地利用类型的时空转变,并借助Fragstats软件分析了研究区景观格局的变化。研究结果表明：灌木林、有林地、中高覆盖草地始终是研究区的优势类型,维持着景观的基本功能,但土地利用与景观格局在近10年仍发生了较大的变化,2000年前有较多的林草地转变为耕地,之后,大量的耕地实现退耕,林草植被增加迅速。研究区整体景观格局破碎化有增加的趋势,但对水土保持与水源涵养有利的景观类型也在同步增加。     

基于多源遥感数据的区域景观格局尺度效应

无论在景观生态学还是在遥感领域,尺度问题都是非常重要的问题,目前已有的研究主要考虑景观的粒度效应,很少涉及遥感影像空间分辨率对景观格局的影响。在遥感和地理信息系统软件的支持下,利用多源遥感影像,结合研究区的特点进行了景观分类,并从不同遥感数据的空间分辨率角度进行空间粒度放大试验,探讨景观格局的尺度效应。研究结果表明：基于不同空间分辨率遥感影像的土地利用空间数据具有尺度效应,其所反映的区域土地利用景观格局在宏观上是一致的,但类型的边界、形状和数量均产生较大的差异;景观格局指数能反映不同遥感影像所记录的地表信息,从不同遥感数据源、不同空间分辨率的角度定量化判断尺度放大过程中区域土地利用景观特征信息的尺度效应。     

基于格网划分的城市区域土地利用景观格局时空变化遥感监测

城市化引起的土地利用变化已成为城市问题研究热点。多时相遥感变化检测能够监测到土地利用变化的数量,被广泛地用来进行城市扩张研究。对于城市化引起的城市空间结构变化,最新研究引入景观格局分析法,大量涌现的景观指标为景观格局定量化表达提供了基础。目前对于城市化过程中景观格局时空变化的描述过于笼统,一般是对整个研究区域提取全局景观格局及其时间变化。通过提出一种基于网格划分的景观格局提取与时空变化检测方法,并运用此方法研究了北京市城市化进程中景观格局的时空变化。结果表明:基于网格划分的景观格局变化检测方法能够检测出城市空间结构变化的数量、位置和模式,为理解城市扩张行为以及城市扩张建模提供了相比较于遥感土地利用变化检测之外的另一种知识。     

Effects of land‐use categorization on landscape metrics: A case study in urban landscape of Shenzhen,China

Using remotely sensed data, landscape pattern analysis based on landscape metrics has been one of the major topics of landscape ecology, and more attention has been focused on the effects of spatial scale and the accuracy of remotely sensed data on landscape metrics. However, few studies have been conducted to assess the change of landscape metrics under the influence of land‐use categorization. In this paper, we took the Bao'an district of Shenzhen city as the study area, to analyse how land‐use categorization would influence changes in 24 landscape metrics. The results showed a significant influence, and based on the characteristics of the response curves of landscape metrics associated with the change in land‐use categorization in regression analysis, and the predictability of these relations, the 24 landscape metrics fell into three groups. (1) Type I included 12 landscape metrics, and showed a strong predictability with changing of land‐use categorization with simple function relations in regression analysis. (2) Type II included seven indices, and exhibited complicated behaviours against changing of land‐use categorization. The response curves of these metrics, which were not easy to predict, consisted of two subsections and could not be described by a single function. (3) Type III included five indices, and showed unpredictable behaviours against the change of the land‐use categorization. Their response curves could not be described by a certain function. This study highlights the need for the analysis of effects of land‐use categorization on landscape metrics so as to clearly quantify landscape patterns, and provides insights into the selection of landscape metrics for comparative research on a given area under different land‐use categorizations.     

基于PSI技术的芜湖市地面沉降时空特征分析

城市的沉降监测有利于了解区域实时高程,可为地质灾害与防护部门提供数据依据,避免因高程损失而带来的地质灾害。基于2016年1月至2017年12月共22景Sentinel-1A干涉宽幅模式影像数据,利用永久散射体合成孔径雷达干涉测量技术以及合成孔径雷达差分干涉测量技术进行芜湖市地表形变监测,并分析研究区地面沉降的时空分布特征。空间上,阐述芜湖市地面沉降的整体格局,再以道路为专题,分析了道路的沉降分布格局。时间上,以时间为基线,逐月分析地面沉降部分在年内的具体变化。结果表明：空间上,芜湖市地面沉降主要集中在长江以东的范围,呈现出由西向东逐渐增加的趋势,长江以西呈现零星漏斗式沉降分布,其中,沉降累积量也与道路的密度与建设相关,道路汇集区与修建区域的沉降累积量较大;时间上,研究区整体沉降量各月变化较均匀,其中,沉降量变化范围在6月最大,10月与11月最小。     

Comparison of landscape patterns between metropolises and small-sized cities: a gradient analysis with changing grain size in Shanghai and Zhangjiagang,China

Quantifying the urban landscape pattern and its change is fundamental for monitoring and assessing the ecological and socio-economic consequences of urbanization. Using Indian Remote Sensing Panchromatic (IRS-PAN) imagery of 2002 and combining gradient analysis with landscape metrics, we compared the landscape patterns between metropolises and small-sized cities with increasing grain size. Landscape metrics were computed along a 51?×?9 km transect cutting across Shanghai and a 16?×?2 km transect cutting across Zhangjiagang with a moving window. The results showed that fragmentation indices (patch density (PD), total edge (TE), landscape division (LD)) in land use transects of the two cities had many similarities, indicating the common characteristics of urbanization in different-sized cities. There were, however, some striking dissimilarities between the two cities, which did not support the hypothesis that PD increases exponentially along a landscape modification gradient. These differences may have three explanations: the proportion of urban roads area, the width of urban roads and land use change in suburban and rural areas. The proportion of urban road area and the width of urban roads, which should be considered in future research, are two main factors that have been identified to influence the landscape pattern analysis. In younger and smaller cities, spatial competition between local interest groups and imperfect land managerial systems result in an increase in fragmentation in the suburbs, and policymakers should pay more attention to future city planning and management. A bridge linking the urbanization landscape pattern and the process of urban fragmentation will be a key to urban landscape studies and planning.     

基于PSI技术的芜湖市地面沉降时空特征分析

城市的沉降监测有利于了解区域实时高程，可为地质灾害与防护部门提供数据依据，避免因高程损失而带来的地质灾害。基于2016年1月至2017年12月共22景Sentinel-1A干涉宽幅模式影像数据，利用永久散射体合成孔径雷达干涉测量技术以及合成孔径雷达差分干涉测量技术进行芜湖市地表形变监测，并分析研究区地面沉降的时空分布特征。空间上，阐述芜湖市地面沉降的整体格局，再以道路为专题，分析了道路的沉降分布格局。时间上，以时间为基线，逐月分析地面沉降部分在年内的具体变化。结果表明：空间上，芜湖市地面沉降主要集中在长江以东的范围，呈现出由西向东逐渐增加的趋势，长江以西呈现零星漏斗式沉降分布，其中，沉降累积量也与道路的密度与建设相关，道路汇集区与修建区域的沉降累积量较大；时间上，研究区整体沉降量各月变化较均匀，其中，沉降量变化范围在6月最大，10月与11月最小。     

Spatio-temporal pattern of urban land cover evolvement with urban renewal and expansion in Shanghai based on mixed-pixel classification for remote sensing imagery

Research into pixel unmixing in remote sensing imagery led to the development of soft classification methods. In this article, we propose a possibilistic c repulsive medoids (PCRMdd) clustering algorithm which attempts to find c repulsive medoids as a minimal solution of a particular objective function. The PCRMdd algorithm is applied to predict the proportion of each land use class within a single pixel, and generate a set of endmember fraction images. The clustering results obtained on multi-temporal Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper plus (ETM+) images of Shanghai city in China reveal the spatio-temporal pattern of Shanghai land use evolvement and urban land spatial sprawl in course of urbanization from 1989 to 2002. The spatial pattern of land use transformation with urban renewal and expansion indicates the urban land use structure is gradually optimized during vigorous urban renewal and large-scale development of Pudong area, which will have an active influence on improving urban space landscape and enhancing the quality of the ecological environment. In addition, accuracy analysis demonstrates that PCRMdd represents a robust and effective tool for mixed-pixel classification on remote sensing imagery to obtain reliable soft classification results and endmember spectral information in a noisy environment.     

Landscape evolution in the Yellow River Basin using satellite remote sensing and GIS during the past decade

Over the past decade, rapid landscape pattern change has taken place in many arid and semi-arid regions of China, such as the Yellow River Basin. In this paper, landscape evolution was investigated by the combined use of satellite remote sensing, geographic information system (GIS) and landscape modelling technologies. The aim was to improve our understanding of landscape changes so that sustainable land use could be established. First, the changes in various landscape metrics were analysed using the landscape structure analysis programme. Second, the mathematical methodology was explored and developed for landscape pattern change, which included: the status and trends change model for individual landscape types, the 1-km² area percentage data model and the transition matrix of landscape types. The results show that the area of the Yellow River Basin was about 794 000 km² during the period from 1990 to 2000; cropland, built-up land and unused land expanded significantly whereas woodland, grassland and water bodies contracted substantially. The area of cropland increased dramatically by 2817 km², and the areas of grassland and woodland decreased by 4669 and 33 km², respectively. Meanwhile, the landscape pattern in the study area also experienced numerous changes over the past decade. The major factors that caused the landscape changes in this area over the past decade were found to be governmental policies for environmental protection, population growth, and meteorological and environmental conditions.     

Characterizing urban sprawl using multi-stage remote sensing images and landscape metrics

This study intends to explore the spatial analytical methods to identify both general trends and more subtle patterns of urban land changes. Landsat imagery of metropolitan Kansas City, USA was used to generate time series of land cover data over the past three decades. Based on remotely sensed land cover data, landscape metrics were calculated. Both the remotely sensed data and landscape metrics were used to characterize long-term trends and patterns of urban sprawl. Land cover change analyses at the metropolitan, county, and city levels reveal that over the past three decades the significant increase of built-up land in the study area was mainly at the expense of non-forest vegetation cover. The spatial and temporal heterogeneity of the land cover changes allowed the identification of fast and slow sprawling areas. The landscape metrics were analyzed across jurisdictional levels to understand the effects of the built-up expansion on the forestland and non-forest vegetation cover. The results of the analysis suggest that at the metropolitan level both the areas of non-forest vegetation and the forestland became more fragmented due to development while large forest patches were less affected. Metrics statistics show that this landscape effect occurred moderately at the county level, while it could be only weakly identified at the city level, suggesting a scale effect that the landscape response of urbanization can be better revealed within larger spatial units (e.g., a metropolitan area or a county as compared to a city). The interpretation of the built-up patch density metrics helped identify different stages of urbanization in two major urban sprawl directions of the metropolitan area. Land consumption indices (LCI) were devised to relate the remotely sensed built-up growth to changes in housing and commercial constructions as major driving factors, providing an effective measure to compare and characterize urban sprawl across jurisdictional boundaries and time periods.     

基于遥感的土地利用空间格局分布与地表温度的关系

近年由于经济的高速发展,土地利用与覆盖变化很大,促使城市的地表温度值正在逐步升高,城市热岛现象也更加突出。先利用监督分类的最大似然算法对武汉市的ETM影像进行分类,并计算各土地利用类型空间格局分布指数。然后用ETM热红外波段根据单窗算法反演武汉市的地表温度分布,并分别计算各土地利用类型的平均地表温度。最后利用灰色相关分析方法定量分析土地利用空间格局分布指数对地表温度的影响。结果表明武汉市土地利用类型的空间格局分布指数与地表温度有较好的相关性,其中地表温度与散布与并列指数(IJI)、同类斑块相邻百分数指数(PLADJ)和最大斑块所占景观面积比例指数(LPI)的灰色关联度较高,说明地表温度的分布不仅受到各类型斑块与其它斑块相邻情况的影响较大,还受到最大斑块所占的总土地面积比例的影响。     

基于TM影像的城郊景观土地利用初步研究--以北京昌平沙河区为例

北京市是全国的政治、经济和文化中心，城镇扩张速度较快。中国加入世界贸易组织和北京申办奥运会的成功，将使城镇进一步扩展。随着城市向郊区的扩张，城郊景观成为城市和郊区的过渡带，该过渡带的景观土地利用发生了巨大变化。借助TM遥感影像采用两种方法来解译北京昌平沙河区景观土地利用：其一是利用TM影像的4、5、3波段的假彩色合成来该地区的土地利用解译；其二是借助TM影像3和4波段计算的NDVI来判定土地利用，并与土地统计数据对比，结果表明第一种方法解译城郊景观的土地利用类型效果较好，而第二种方法对有植被覆盖的土地利用类型解译较好。     

基于遥感和GIS的西安市土地利用时空变化研究

利用2000和2007年两期TM遥感影像,通过最大似然法、地理信息系统空间分析方法以及数理统计方法,借助Erdas Imagine 9.0、ArcGIS 9.2和Matlab软件平台,计算出西安市土地利用类型的动态转移矩阵;构建了土地利用程度变化指数、土地利用变化类型的多度和重要度指数等区域土地利用变化的指数模型,定量分析西安市土地利用时空变化。揭示了西安市土地利用差异以及土地利用空间变化的主要类型、分布特征和区域方向,阐明了西安市土地利用变化的区域特点,为土地可持续利用提供有效的决策支持。     

A Breakpoints based Spatio-temporal Analysis of Tibetan Plateau Vegetation

Due to the fragile ecosystem and unique geographical environment on the TP，the vegetation strongly responds to climatic shifts.Therefore，it is of great significance to discuss the spatiotemporal trend shift of vegetation，to evaluate the climate change of the plateau and to predict regional ecological development.Using the GIMMS NDVI3g dataset from 1982 to 2012 to extract the NDVI information of the TP，as well as establishing seasonal trend model to classify research through the seasonal trend analysis and breakpoints detection method，reveals the spatiotemporal pattern of the trend shifts of plateau vegetation at both ends of the breakpoints combining the classification of land cover.The results shows that conclusions.(1) The seasonal trend model can effectively identify the breakpoints of vegetation time series，moreover the time span of the breakpoints were large and the spatial heterogeneity were strong.(2) The trend of vegetation degeneration in the western part of the Tibetan Plateau was small，vegetation degeneration in the south and northeast regions was obvious，and vegetation in the central and eastern regions has improved.58.93% of the vegetation status tends to be stable.The area where the vegetation status changes significantly accounts for about 32.3% of the entire plateau.(3) In the area where the vegetation status is generally or significantly changed，the vegetation improvement of monotonous trend and interruption trend were more than that of degradation，and the degenerative situation in the reverse trend were more than the improvement.Monotonous trend changed in 3.14% of the regions，58.36% of the regions occurred interruption trend changes，and 38.50% of regions occurred reverse trends.The time distribution of the monotonous trend and the interruption trend were more concentrated，while the reverse trend covered the entire time series.(4) The vegetation improvement and degradation in different land cover types were various conditions.The type with the highest rate of improvement was desert(53.30%)，and the type with the highest rate of degradation was sparse vegetation(60.14%).Overall，the vegetation in Tibetan plateau tends to be greening，but the spatial heterogeneity remains significant.     

河谷型城市土地利用类型及格局的热环境效应遥感分析——以兰州市为例

以河谷型城市兰州为例,采用Landsat ETM+遥感影像为基本数据源,定量反演了地表温度（LST）和植被指数（NDVI）,利用GIS空间分析方法,分析了LST和NDVI 在不同土地利用类型之间的差异以及二者之间的定量关系,并引入多样性和聚集度指数,讨论了在不同土地利用的空间组合下,LST和NDVI 的空间差异及相互关系。结果显示:LST和NDVI具有明显的相关性,中心城区LST表现出热岛效应,而NDVI则为低谷效应;土地利用斑块和类型两种尺度水平上LST和NDVI均具有明显负相关的线性关系,城市内部不同土地类型所产生的热环境效应不同;土地利用多样性越丰富、聚集度越小的区域,其温度对地表植被覆盖的敏感性越弱。     

Spectral analysis of civil conflict-induced forced migration on land-use/land-cover change: the case of a primate and lower-ranked cities in Sierra Leone

Involuntary migration triggered by war has the capacity to generate substantial socioeconomic and environmental changes in cities of developing countries, resulting in aberrant alterations to land use and land cover (LULC). This scenario has the potential to diminish the quality of life of inhabitants of a city and present administrative challenges for government and other officials. Gauging the scope and trajectory of urban LULC changes in a war-related environment is pivotal for urban and regional planning, the sustainability of natural resources, and information needs of policy makers. Scholarships that link remote sensing to social science mostly focus on a non-conflict environment, resulting in little or no information on the ramifications of conflict-induced forced migration on changes in LULC. As a result, the role of civil conflict-induced forced migration on the composition and configuration of urban landscape in developing countries remains elusive. This study employs a dense time stack of Landsat-5 Thematic Mapper (TM) images and a hybrid classification approach that integrates linear spectral unmixing and an ensemble decision-tree classifier to characterize LULC in a primate city and two lower-ranked cities in Sierra Leone. The study examined three time-steps which span 1986–1991, 1991–2002, and 2002–2010 with the overarching goal of elucidating changes in LULC conditioned by civil conflict. Image classification accuracy (overall accuracy) ranged between 84.0% and 90.2%. The study demonstrated that civil conflict has the capacity to trigger notable growth in urban agricultural land (37.4%) in a primate city, while the expansion of residential (112.7%) and industrial/commercial (18.7%) lands is more prominent in a lower-ranked city. The study further revealed that population expansion does not necessarily result in significant growth in residential area in a primate city that has experienced civil conflict.     

基于NDVI及DEM的青海湖北岸景观格局空间自相关分析

本文以青海湖北岸为研究区,利用2006年Landsat-5 TM数据,结合植被类型图、SRTM高程数据、1∶5万地形图等数据,获取了该区12类景观类型,分类总体精度为82.91%,Kappa系数为0.81。以NDVI均值、坡向均值、高程均值为区域观测值,计算研究区景观类型的空间自相关性的Moran指数,再根据局部Moran指数的空间集聚分布特征,分析这些景观类型之间的结构稳定性,表现为如下特征:第一,较稳定景观,格局类型包括河谷灌丛、山地灌丛、高寒沼泽、高寒草甸、河流、裸岩;第二,欠稳定景观,格局类型包括湖泊、温性草原、湖滨沼泽;第三,极不稳定景观,格局类型有沙地、石砾地、裸土地,如鸟岛、金沙湾,尕海地区的沙地。     

The effects of sensor spatial resolution and changing grain size on fragmentation indices in urban landscape

Satellite images are now used as the primary source of spatial information for landscape pattern analysis. Choosing data of proper resolution has always been a big problem for landscape pattern analysis using satellite images. However, the effects of remote sensor spatial resolution on urban landscape fragmentation have never been reported. In this study, landscape fragmentation of Shanghai was analysed using land use maps produced from TM and IRS‐PAN images, attempting to discover the effects of remote sensor spatial resolution on urban landscape fragmentation. Four landscape fragmentation indices were computed along a 51 km long and 9 km wide transect cutting across Shanghai with a moving window to detect the behaviour of landscape indices along the gradient of land use zones. The results showed that fragmentation indices were sensitive to varied spatial resolution and grain size, indicating that fine resolution data and small grain size of about 7.5 m might be optimal for urban fragmentation analysis. The behaviour of landscape indices along the gradient of land use zones suggests that urban fragmentation can be distinguished as occurring in two phases: dissection introduced by roads and shrinkage caused primarily by urban sprawl.     

基于RS和GIS的黄河下游沿岸县域土地利用与景观格局演变的驱动力研究 ——以河南省封丘县为例

以位于黄河下游沿岸的河南省封丘县为研究区域,通过遥感影像解译、地理信息系统和景观格局计算软件,分析了该区域1990、2000年土地利用和景观格局的变化特征,运用典型相关分析方法,找出土地利用和景观格局变化的驱动因子,结果如下：研究期间居民点与建设用地增加2 934.87 hm2,其它类型用地减少,尤其是旱地、水体分别减少1 084.81 hm2、1 717.92 hm2;以种植业用地为基质（旱地、水田用地比例之和近80%）的农业景观较为稳定,但农业结构单一、景观多样性较低;人口数量、粮食生产、对优越生活条件的追求等农业社会经济条件的变化是研究区土地利用与景观格局演变的驱动因子。     

Modelling of urban growth using spatial analysis techniques: a case study of Ajmer city (India)

The concentration of people in densely populated urban areas, especially in developing countries like India and China, calls for the use of sophisticated monitoring systems, like remote sensing and Geographical Information Systems (GIS). Time series of land use/cover changes can easily be generated using sequential satellite images, which are required for the prediction of urban growth, verification of growth model outputs, estimation of impervious area, parameterization of various hydrological models, water resources planning and management and environmental studies. In the present work, urban growth of Ajmer city (India) in the last 29 years has been studied at mid‐scale level (5–25 m). Remote sensing and GIS have been used to extract the information related to urban growth, impervious area and its spatial and temporal variation. Statistical classification approaches have been used to derive the land use information from satellite images of eight years (1977–2005). The Shannon's entropy and landscape metrics (patchiness and map density) are computed in order to quantify the urban form (impervious area) in terms of spatial phenomena. Further, multivariate statistical techniques have been used to establish the relationship between the urban growth and its causative factors. Results reveal that land development (200%) in Ajmer is more than three times the population growth (59%). Shannon's entropy and landscape metrics has revealed the spatial distribution of the sprawl.