Wavelet-based detection of bush encroachment in a savanna using multi-temporal aerial photographs and satellite imagery     

《International Journal of Applied Earth Observation and Geoinformation》2015

Although increased woody plant abundance has been reported in tropical savannas worldwide, techniques for detecting the direction and magnitude of change are mostly based on visual interpretation of historical aerial photography or textural analysis of multi-temporal satellite images. These techniques are prone to human error and do not permit integration of remotely sensed data from diverse sources. Here, we integrate aerial photographs with high spatial resolution satellite imagery and use a discrete wavelet transform to objectively detect the dynamics in bush encroachment at two protected Zimbabwean savanna sites. Based on the recently introduced intensity-dominant scale approach, we test the hypotheses that: (1) the encroachment of woody patches into the surrounding grassland matrix causes a shift in the dominant scale. This shift in the dominant scale can be detected using a discrete wavelet transform regardless of whether aerial photography and satellite data are used; and (2) as the woody patch size stabilises, woody cover tends to increase thereby triggering changes in intensity. The results show that at the first site where tree patches were already established (Lake Chivero Game Reserve), between 1972 and 1984 the dominant scale of woody patches initially increased from 8 m before stabilising at 16 m and 32 m between 1984 and 2012 while the intensity fluctuated during the same period. In contrast, at the second site, which was formely grass-dominated site (Kyle Game Reserve), we observed an unclear dominant scale (1972) which later becomes distinct in 1985, 1996 and 2012. Over the same period, the intensity increased. Our results imply that using our approach we can detect and quantify woody/bush patch dynamics in savanna landscapes.  相似文献   

基于小波变换和HIS变换的海冰SAR与光学遥感影像融合方法研究   总被引：3，自引：2，他引：1  

刘眉洁  戴永寿  张杰  张晰  孟俊敏  谢钦川 《海洋学报(英文版)》2015,34(3):59-67

Sea ice as a disaster has recently attracted a great deal of attention in China. Its monitoring has become a routine task for the maritime sector. Remote sensing, which depends mainly on SAR and optical sensors, has become the primary means for sea-ice research. Optical images contain abundant sea-ice multi-spectral information, whereas SAR images contain rich sea-ice texture information. If the characteristic advantages of SAR and optical images could be combined for sea-ice study, the ability of sea-ice monitoring would be improved. In this study, in accordance with the characteristics of sea-ice SAR and optical images, the transformation and fusion methods for these images were chosen. Also, a fusion method of optical and SAR images was proposed in order to improve sea-ice identification. Texture information can play an important role in sea-ice classification. Haar wavelet transformation was found to be suitable for the sea-ice SAR images, and the texture information of the sea-ice SAR image from Advanced Synthetic Aperture Radar(ASAR) loaded on ENVISAT was documented. The results of our studies showed that, the optical images in the hue-intensity-saturation(HIS) space could reflect the spectral characteristics of the sea-ice types more efficiently than in the red-green-blue(RGB) space, and the optical image from the China-Brazil Earth Resources Satellite(CBERS-02B) was transferred from the RGB space to the HIS space. The principal component analysis(PCA) method could potentially contain the maximum information of the sea-ice images by fusing the HIS and texture images. The fusion image was obtained by a PCA method, which included the advantages of both the sea-ice SAR image and the optical image. To validate the fusion method, three methods were used to evaluate the fused image, i.e., objective, subjective, and comprehensive evaluations. It was concluded that the fusion method proposed could improve the ability of image interpretation and sea-ice identification.  相似文献   

2008年中国沿岸冬季寒潮激发陆架波的小波分析   总被引：1，自引：0，他引：1  

李君益  郑全安  胡建宇  范振华  朱佳  陈涛  朱本璐  徐莹 《海洋学报(英文版)》2015,34(11):22-31

This study applies the wavelet analysis to the tidal gauge records, alongshore winds, atmospheric temperature and pressure along the China coast in winter 2008. The analysis results show three events of sea level oscillations(SLOs) on the shelf induced by winter storms. The first event occurred from January 9 to 21. The SLO periods were double-peaked at 1.6–5.3 and 7.0–16.0 d with the power densities of 0.04–0.05 and 0.10–0.15 m2·d, respectively.The second event occurred from February 5 to 18. The SLO period was single-peaked at 2.3–3.5 d with power density of 0.03–0.04 m2·d. The third event occurred from February 20 to March 8. The SLO periods were doublepeaked at 1.5–4.3 and 6.1–8.2 d with the power densities of 0.08–0.11 and 0.02–0.08 m2·d, respectively. The SLOs propagated along the coast from Zhejiang in north to Guangdong in south. The phase speeds ranged about 9–29m/s from Kanmen to Pingtan, 5–11 m/s from Xiamen to Huizhou and 11–22 m/s from Huizhou to Shuidong. The dispersion relation of the SLOs shows their nature of coastal-trapped wave.  相似文献   

数字滤波技术在潮汐观测中的应用研究     

闫秦  成方林  郭海  叶颖  王斌 《海洋技术学报》2015,34(4):28-32

潮汐是重要的海洋物理要素。瞬时变化的海面高度信息除了包含潮汐信息外,还包括波浪等高频干扰信息,因此需要对干扰信息进行滤除。如何从获取到的海面瞬时高度变化中提取出潮汐信息就成为一个关键问题。海洋学中通常是通过低通滤波来获取低频的潮汐信息。通过分析常用的3种低通数字滤波的方法,即滑动平均法、快速傅里叶变换法和小波变换法,对3种低通滤波方法应用于潮汐数据处理的效果进行了比较分析,得出滑动平均法在潮汐信息提取中具有较高应用价值的结论。  相似文献   

基于势函数点分布调整的SIFT图像配准算法     

孙彬  边辉  王培忠 《国土资源遥感》2015,(3)

尺度不变特征转换(scale invariant feature transform,SIFT)是一种广泛应用于图像配准领域的点特征提取算法。针对基于SIFT的图像自动配准算法存在的特征点分布不均匀问题,提出了一种基于势函数点分布调整的图像配准方法。该方法解决了SIFT算法不能针对特征点的分布情况进行优化的问题。通过调整SIFT的比值阈值,增加配准点的数目;通过引入分子力学中的势函数概念,对特征点分布情况进行优化;通过局部互信息精纠正,微调特征点位置,以提高特征配准点的配准精度;最终实现高质量(空间分布均衡,配准精度高)的图像自动配准。  相似文献   

视觉感受与Markov随机场相结合的高分辨率遥感影像分割法   总被引：2，自引：0，他引：2  

许妙忠  丛铭  万丽娟  解天鹏  朱晓玲 《测绘学报》2015,44(2):198-205

鉴于视觉感受对外界强大的感知与识别能力,模拟视觉神经感知的工作机制,并结合Markov随机场模型,提出一种影像分割方法。首先,分析视觉感知系统的工作机制,将其特性归纳为等级层次性、学习能力、特征检测能力和稀疏编码特性,继而利用小波变换、非监督聚类、特征分析和Laplace分布模拟视觉工作机制,然后结合Markov随机场模型实现高分辨率遥感影像的分割。通过不同卫星的真实遥感影像进行了相关试验。试验结果表明本文提出的方法在高分辨率遥感影像分割任务中有非常良好的表现。  相似文献   

IGS跟踪站的大地高时间序列特征分析     

徐克红  程鹏飞  汉江 《测绘工程》2015,(5)

应用国内几个IGS跟踪站在U方向的观测数据,分析研究跟踪站大地高的变化趋势。通过对时间序列进行奇异谱分析和傅立叶变换分析,表明大地高时间序列具有一定的周期性,且周期特性明显,时间序列的时频特性表现出明显的区域性。  相似文献   

基于小波特征融合的Hyperion影像降维方法     

孙小芳 《测绘工程》2015,(8):11-15

根据影像中地物光谱曲线的小波特征点确定地物识别的合适光谱分辨率,通过融合原先若干窄波段生成具有适合地物识别光谱分辨率的宽波段数据,达到降维高光谱数据的目的。文中对hyperion影像进行坏线和Smile效应去除,经过FLAASH大气校正,得到155个波段。对提取的八类地物的样本平均光谱进行DB4小波分解,计算小波细节系数方差;以小波细节系数信息熵作为特征点,得出不可渗透表面、居民地、水田、裸土4类地物识别适宜光谱分辨率为80nm,其余地物识别适宜光谱分辨率为160nm。以窄波段间的活跃度为指标进行融合,生成降维后的宽波段分别是21个波段和11个波段。8类地物在3尺度和4尺度下的分类结果说明降维影像能满足应用需求,提出的降维方法可行。  相似文献   

基于小波分析的灰色-神经网络组合模型在大坝变形预测中的应用     

沈哲辉  黄腾  葛文  孟庆年 《测绘工程》2015,(11):51-53

监测序列经小波分解后可以得到各层分量。对低频分量采用灰色GM(1,1)模型进行建模预测,对高频分量采用BP神经网络进行建模预测,最后将各分量进行小波重构,得到监测序列的预测值。将预测值分别与没有进行小波分解直接用GM(1,1)模型预测的值和经小波分解的低、高频系数都采用GM(1,1)模型预测的值进行对比,发现经小波分解的灰色-神经网络组合模型预测精度更高。  相似文献   

资源三号影像中城市高大地物阴影检测方法   总被引：3，自引：0，他引：3  

杨兴旺  杨树文  刘正军  姚花琴  李轶鲲 《测绘科学》2015,(9):98-101

针对遥感影像处理中阴影检测和信息补偿不准确的问题,该文在研究已有阴影检测算法的基础上,结合资源三号(ZY-3)影像数据的特性,构建了阴影检测方法:首先对原始图像分别做差值运算和主成分变换,并利用多峰阈值自动提取算法检测出阴影区域;其次将差值运算提取的粗阴影区域与主成分变换提取的阴影区域做并运算生成一个新的阴影区域;然后判断影像中是否含有水体,如果含有水体则利用多峰阈值自动提取算法检测出水体并与新合并的阴影区域影像做布尔运算得到完整的阴影区域,反之则新合并的区域即为完整的阴影区域。实验结果表明该方法针对ZY-3具有较好的普适性、较高的提取精度和提取效率。  相似文献