A new approach for vegetation change detection in urban areas

Because of complex change in urban areas, modified CVA application based on mask techniques can minify the effect of non-vegetation changes and improve upon efficiency to a great extent. Moreover, drawing from methods in polar plots, the technique measures changes with absolute angular and total magnitude of PVI calculated on the basis of linear fit with least-square estimation and GVI calculated using 3D G-S transformation. Finally, this application is performed with Landsat ETM+ imageries of Wuhan in 2002 and 2005, and assessed by error matrix, in the way it could detect change pixels 94.91% correct, and the total consistent coefficient Kappa and could reach to 0.85. The evaluation result demonstrates this new application trends as an efficient and effective alternative to urban vegetation change extraction.     

A framework for automated change detection system

To enhance the ability of remote sensing system to provide accurate, timely, and complete geo-spatial information at regional or global scale, an automated change detection system has been and will continue to be one of the important and challenging problems in remote sensing. In this paper, the authors propose a framework for automated change detection system at landscape level using various geo-spatial data sources including multi-sensor remotely sensed imagery and ancillary data layers. In this framework, database is the central part and some associated techniques are discussed. These techniques includes five subsystems: automated feature-based image registration, automated change finding, automated change feature extraction and identification, intelligent change recognition, change accuracy assessment and database updating and visualization.     

A FRAMEWORK FOR AUTOMATED CHANGE DETECTION SYSTEM

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SAR polarimetric change detection for flooded vegetation

Abstract

Due to spatial and temporal variability an effective monitoring system for water resources must consider the use of remote sensing to provide information. Synthetic Aperture Radar (SAR) is useful due to timely data acquisition and sensitivity to surface water and flooded vegetation. The ability to map flooded vegetation is attributed to the double bounce scattering mechanism, often dominant for this target. Dong Ting Lake in China is an ideal site for evaluating SAR data for this application due to annual flooding caused by mountain snow melt causing extensive changes in flooded vegetation. A curvelet-based approach for change detection in SAR imagery works well as it highlights the change and suppresses the speckle noise. This paper addresses the extension of this change detection technique to polarimetric SAR data for monitoring surface water and flooded vegetation. RADARSAT-2 images of Dong Ting Lake demonstrate this curvelet-based change detection technique applied to wetlands although it is applicable to other land covers and for post disaster impact assessment. These tools are important to Digital Earth for map updating and revision.     

地质灾区光学立体影像植被与3维地形定量变化检测

当前,经典的2维遥感变化检测方法不再适用于地质灾害引起的地表3维变化。此外,一般植被提取依赖近红外波段,而近红外影像未必能获取。因此,针对2010年和2011年汶川映秀地区的可见光航空立体像对,提出了一种检测植被和3维地形变化的方法。首先,生成研究区两个不同时期的DEM和DOM并完成配准,再利用CIE Lab色彩空间和Otsu分割算法对可见光DOM进行植被变化检测。然后,基于概率统计理论对新旧时期差分DEM提出了3维变化检测的自适应阈值确定方法,在高概率置信域条件下提取出地质灾害的高危区域。最后,对高危区域运用离散化积分方法估算出土方量的3维变化量。实验结果表明了所提出方法的可行性,有效性和实用性。本文不仅将常规遥感的2维变化检测升华至3维空间,而且对变化的3维地形进行了定量估计,可应用于地质灾害的遥感动态监测和评估。     

Soil salinity and vegetation cover change detection from multi-temporal remotely sensed imagery in Al Hassa Oasis in Saudi Arabia

Detecting soil salinity changes and its impact on vegetation cover are necessary to understand the relationships between these changes in vegetation cover. This study aims to determine the changes in soil salinity and vegetation cover in Al Hassa Oasis over the past 28 years and investigates whether the salinity change causing the change in vegetation cover. Landsat time series data of years 1985, 2000 and 2013 were used to generate Normalized Difference Vegetation Index (NDVI) and Soil Salinity Index (SI) images, which were then used in image differencing to identify vegetation and salinity change/no-change for two periods. Soil salinity during 2000–2013 exhibits much higher increase compared to 1985–2000, while the vegetation cover declined to 6.31% for the same period. Additionally, highly significant (p < 0.0001) negative relationships found between the NDVI and SI differencing images, confirmed the potential long-term linkage between the changes in soil salinity and vegetation cover.     

A multi-scale spatiotemporal modeling approach to explore vegetation dynamics patterns under global climate change

Given the complexity of vegetation dynamic patterns under global climate change, multi-scale spatiotemporal explicit models are necessary in order to account for environmental heterogeneity. However, there is no efficient time-series tool to extract, reconstruct and analyze the multi-scale vegetation dynamic patterns under global climate change. To fill this gap, a Multi-Scale Spatio-Temporal Modeling (MSSTM) framework which can incorporate the pixel, scale, and time-specific heterogeneity was proposed. The MSSTM method was defined on proper time-series models for multi-temporal components through wavelet transforms. The proposed MSSTM approach was applied to a subtropical mountainous and hilly agro-forestry ecosystem in southeast China using the moderate resolution imaging spectroradiometer enhanced vegetation index (EVI) time-series data sets from 2001 to 2011. The MSSTM approach was proved to be efficient in characterizing and forecasting the complex vegetation dynamic patterns. It provided good estimates of the peaks and valleys of the observed EVI and its average percentages of relative absolute errors of reconstruction was low (6.65). The complexity of the relationship between vegetation dynamics and meteorological parameters was also revealed through the MSSTM method: (1) at seasonal level, vegetation dynamic patterns are strongly associated with climatic variables, primarily the temperature and then precipitation, with correlations slight decreasing (EVI–temperature)/increasing (EVI–precipitation) with altitudinal gradients. (2) At inter-annual scale, obvious positive correlations were primarily observed between EVI and temperature. (3) Despite very low-correlation coefficients observed at intra-seasonal scales, considerable proportions of EVI anomalies are associated with climatic variables, principally the precipitation and sunshine durations.     

Change detection based on DSM and image features in urban areas

On the basis of atereo image analysis,the change detection of man-made objects in urban areas is in-troduced. Information of the height of man-made objects can be applied to reinforce their change detection. By comparison between the new and old DSMs, the changed regions are extracted. However, our aim is to detect changes of man-made objects in urban area and further in the potental areas by the means of line-feature matching and gradient direction histogram. The experiments based on the aerial images from Japan have proven that the algorithm is correct and efficient.     

House change detection based on DSM of aerial image in urban area

The change of house often brings on the change of DSM in an area over different periods. If we can apply information of the height of houses to reinforce the house change detection, the reliability and efficiency of detection methods will be improved greatly.From this viewpoint, a new approach taking advantage of both height data from an image pair and image data is proposed to detect the house change in urban area and is called "data fusion technology".     

基于光谱和空域信息的城区变化检测方法研究

目前的变化检测研究主要集中在利用中、小比例尺遥感图像进行自然环境等方面的变化检测,如草场的季节性变化、灾害检测、植被分布变化、土地使用规划等。然而随着城市的快速发展,为了满足城区管理规划中对道路、房屋等变化细节进行分析的需求,并由于高分辨率卫星诸如Ikonos,Quickbird等的出现,我们有必要并且有可能开发出一套实用、有效的、可靠的城区自动变化检测系统。针对城市区域的复杂性及其高分辨率卫星影像的配准误差问题,本文提出一种通过模糊逻辑结合光谱特征和空域特征的城区变化检测方法,以期望减小图像整体及局部配准误差对变化检测精度的影响。     

基于高斯过程的高分辨率遥感图像变化检测

本文首先通过理论分析,探讨了高斯过程分类器在高分辨率遥感图像变化检测应用中的优势与不足,并针对高斯过程分类器的不足给出了相应的解决方法;其次,提出了一种基于空间上下文相关的高斯过程变化检测方法;最后,通过多个高分辨率遥感实验数据集上的实验设计与分析,验证了高斯过程分类器在高分辨率遥感图像变化检测中的应用能力,并证明了本文提出的解决方法的有效性.     

面向对象的遥感影像变化检测方法

针对变化检测区域内变化区域与未变化区域面积比例较低时,通过常规的阈值计算无法在变化检测中确定准确的变化阈值问题,该文提出了一种带样本选择的面向对象遥感影像变化检测方法。该方法首先对多时相遥感影像进行多尺度分割获取像斑,并采用变化向量分析法计算像斑的差异度;然后,自适应选择训练样本,结合基于期望最大化算法和贝叶斯最小误差率理论的阈值计算方法,采用独立阈值法确定变化阈值;最后,利用变化阈值对差异影像进行二值分割,并获取变化检测结果。实验结果表明该文方法在变化检测精度上优于常规方法。     

遥感影像CVA变化检测的CUDA并行算法设计

随着遥感影像数据量以及复杂程度的日益增加,遥感图像的快速处理成为实际应用过程中亟需解决的问题。为了实现遥感影像的实时变化检测,针对基于变化矢量分析CVA的变化检测算法,设计了一种基于统一计算设备构架CUDA的并行处理模型。首先利用地理空间数据提取库GDAL实现大数据量遥感影像的分块读取、操作和保存;其次将基于变化矢量分析的变化检测过程分为变化强度检测、映射表构建和变化方向检测,并借助CUDA C将变化矢量分析算法的3个步骤嵌入到CPU和GPU组成的异构平台上进行实验;最后利用该模型对不同数据量的遥感影像进行CVA变化检测并作对比分析。实验结果表明:与CPU串行相比,基于GPU/CUDA的遥感影像CVA的变化检测速度提高了10倍左右;在一定程度上,达到了实时变化检测的效果。     

Implications of management strategies and vegetation change in the Mount St. Helens blast zone

The 1980 eruptions of Mount St. Helens provided an excellent opportunity for scientists to investigate the recovery of vegetation communities following a major geologic disturbance. An important and often overlooked aspect in these studies is the human factor in recovery processes, and specifically, the different management approaches taken towards re-establishment of vegetation on lands under the control of various owners. This study examines vegetation changes throughout the 1980 blast zone using a time series of Landsat-derived Normalized Difference Vegetation Index (NDVI) images and change detection methods to assess the changes over 25 years, from 1980 to 2005, as a function of human management combined with ecological factors. This long-term tracking of change indicates that differences in the speed of vegetation re-establishment and consequent rates of change substantially reflect human involvement and varying management strategies.     

Reclamation areas and their development studied by vegetation indices

Abstract

Large areas in the Czech Republic were used for open casts of brown coal mining. Many of them have been already closed. Reclamation of them and of their dumps is the next step intheir development. It is possible to divide used reclamations into the forest, hydrologic, agricultural and other ones – roads, etc. Their age varies from 45 years to as yet unfinished. Reclaimed areas are documented in reclamation projects. Information about age and land use determined groups of these areas to be evaluated by vegetation indices. 100 areas with forest type were evaluated. Eight vegetation indices (NDVI, DVI, RVI, PVI, SAVI, MSAVI, TSAVI and EVI) were calculated and their average value in each area in 1988, 1992 and 1998 Thematic Mapper data were compared. Changes over years showed close relation to precipitations of previous periods. This relation was confirmed by evaluation of forest areas situated near reclamation areas. Positive/negative changes of vegetation indices were different for different groups and different vegetation indices. An overview of results of vegetation indices is presented for individual areas whose land use comprised at least partly forest stand. Results in a 4-year period (1988–1992) were in many areas by many indices negative, changes in 10 years were in most areas by most vegetation indices positive. Changes, minimum values and maximum values in groups were compared. Evaluation of vegetation indices brought again various results. One vegetation index is not sufficient to prove improvement/deterioration of vegetation changes. Precipitation state before measurement should be controlled. Temporary shortage of precipitation can cause vegetation cover deterioration, which is also only temporary. The best development derived from vegetation indices evaluation was found at forest reclamation with mixed tree stand that was 10–20 years old. The method was derived as a tool for post-finishing control of vegetation development of reclamations performed in several year periods.     

结合光谱和纹理特征的林地变更检测

开展林地变更调查,能够为森林执法督察、林地"一张图"更新等提供精准的空间信息和属性信息,对于林业资源的监测管理具有重要意义。针对大范围多时相遥感影像人工勾绘变化图斑耗时费力的现状,提出一种结合光谱和纹理特征的林地变更检测方法,并以灵山县东北部为例,利用20171209和20180201两个时期的高分二号遥感影像进行试验。结果表明,该方法在减少人力投入、降低时间成本的基础上,不仅将遥感影像的变化检测效率提高了一半以上,同时能达到77%以上的检测准确率,在森林资源普查中具有一定的应用价值。     

面向对象的多特征分级CVA遥感影像变化检测

变化矢量分析CVA方法在中低分辨率遥感影像变化检测中已得到广泛应用,但由于高分辨率遥感影像存在不同地物尺度差异大、不同类别地物光谱相互重叠的问题,因此对于高分影像的变化检测具有局限性。为提高高分影像变化检测精度,提出了一种面向对象的多特征分级CVA变化检测方法,首先,利用基于区域邻接图的影像分割方法分别对两时相遥感影像进行多尺度分割,提取分割图斑的光谱、纹理和形状特征;然后,在各级尺度下,分别运用随机森林方法进行特征选择,计算CVA变化强度图;最后,根据信息熵对多级变化强度图进行自适应融合,利用Otsu阈值法检测变化区域,并与仅考虑光谱特征的分级CVA变化检测方法、像元级多特征CVA变化检测方法以及仅考虑光谱特征的像元级CVA变化检测方法进行比较分析。实验表明:与比较方法相比,本文方法的变化检测精度较高,误检率和漏检率较低。     

A land-cover change detection method using data-oriented composite-kernel-based one-class support vector machine

In many change detection applications, the focus is often on one specific change class. The one-class support vector machine (OCSVM)-based change detection method has been proved effective for dealing with such problems, which only requires samples from the change class of interest as the training data. However, this classical method only uses a single kernel which limits its separating capabilities in real-world applications. To further improve the efficacy of the OCSVM-based change detection method, this paper proposes an improved change detection method that uses a data-oriented composite-kernel-based one-class support vector machine. It utilizes the feature information entropy of the training data to determine the kernel weights in constructing a composite kernel. Experimental results on two data-sets demonstrate that the proposed method outperforms the existing classical OCSVM-based change detection method and the traditional composite-kernel-based method with relatively few false alarm errors, and shows good potential for further applications.     

基于多源空间数据的河道水域变化监测方法研究

近年来,随着经济社会的快速发展,河道水域占用情况日益增多,严重影响河道防洪、排涝等正常水域功能的发挥。以浙江省省级河道为例,以覆盖浙江全省的高分辨率航片、省级基础地理信息数据等多源空间数据为基础,结合测绘和水利标准,提出基于多源空间数据的河道水域变化监测方法。方法充分利用高精度的基础测绘空间数据,保证成果的可靠性,同时符合水利部门的规定,能够满足水利部门的实际需要。研究结果表明,2008-2012年间,浙江省省级河道水域减少情况严重,主要减少类型为建设用地。方法为水利部门全面、客观地掌握水域的无序占用情况提供了一种有效手段。     

高分辨率遥感影像配准与变化检测一体化处理

为了克服高分辨率遥感影像配准与变化检测作为单独环节处理的局限,该文提出了一种基于变分理论的配准与变化检测一体化处理方法。该方法将配准误差作为一种光谱变化决策因子,变化信息以权值的方式迭代反馈给变分配准模型的解算过程。为了更准确地检测建筑物这个特定目标的真实变化,该文采用多尺度最大形态学轮廓建筑物检测指数的差异作为另外一个决策因子。最后将配准误差反映的变化和建筑物检测指数的差异这两个决策因子在D-S证据理论框架下建立概率模型进行融合处理,进而得到建筑物的变化检测结果。该文选取WorldView-2数据进行实验,实验结果表明,一体化处理思路可以有效地解决单独处理的局限,从根本上解决配准误差对变化检测结果的影响以及由于变化而使配准精度降低的问题,进而提高配准和变化检测的质量。