基于图像阈值法的森林雪灾损失遥感估测——以云南省为例

雪灾是森林生态系统的严重生态干扰之一, 会严重影响林木生长并降低生态系统功能。利用2000-2011年SPOT NDVI长时间序列影像数据, 基于SG滤波函数进行时序重建, 采用灾后同期影像的图像阈值法, 以常年多灾的云南省2008 年雪灾为例, 进行雪灾森林植被受损评估。评估结果与全国灾情月报中的云南省雪灾范围基本一致, 全省森林雪灾受损面积达12.09%, 主要分布在滇西北的迪庆州、怒江州。对森林雪灾受损程度分析表明, 全省重度受灾县7 个, 中度受灾县13 个, 轻度受灾县45 个。对海拔、坡度、坡向、坡位等地形条件的叠加分析表明, 海拔3300~4000 m、坡度5~15°、处于东坡或东北坡中坡位的森林植被受损最严重。本研究有助于实现森林雪灾损失的快速评估, 对有效规避次生灾害、开展灾后恢复重建规划具有重要意义。     

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SAR图像斑点噪声的小波软门限滤除算法

本文介绍利用小波分析和软门限对合成孔径雷达（ＳＡＲ）图像斑点噪声（Ｓｐｅｃｋｌｅ）进行抑制与滤除的算法。首先选择合适的小波基对合成孔径雷达（ＳＡＲ）图像进行小波分解,应用Ｄａｖｉｄ Ｌ．Ｄｏｎｏｈｏ软门限理论,并且将其推广到２维信号。针对ＳＡＲ图像斑点噪声的特殊性,即在小波变换域内图像和斑点噪声的奇异性不同,选取合适的门限在小波域内滤波。最后进行小波反变换得到去噪后的ＳＡＲ图像。实验证明,该算法能     

图像小波域维纳滤波去噪算法的改进

介绍了小波变换和维纳滤波相结合的图像小波域维纳滤波去噪算法，在分析该算法最小均方误差期望的基础上提出一种改进算法。指出在进行维纳滤波之前，阈值化处理可以有效提高维纳滤波的性能。用标准测试图像的处理结果来比较改进前后两种算法的效果。     

基于三维相空间法和稳健估算法的ADV流速数据后置处理效果研究

水流是影响藤壶、牡蛎、藻类等水生生物能否成功附着在渔业装备上的重要环境因素,水体流速的变化会改变藻类新陈代谢过程,制约藤壶与牡蛎幼虫大面积扩散。流速测量数据的准确性对研究渔业装备上附着生物的附着机制起到至关重要的作用。声学多普勒流速仪(ADV)是测量水体流速的重要设备。然而,水体中的气泡、大颗粒悬浮物等因素会影响ADV的相关系数和信噪比,从而导致流速数据中产生野点,降低了数据的准确性。本文基于国内外主流算法稳健估算法与三维相空间法,以ADV实际测量的流速数据为例,对比研究两种后置处理方法的检测效果。结果显示,稳健估算法平均检出率为4.95%,峰度系数平均下降77.71%,三维相空间法平均检出率为14.60%,峰度系数平均下降84.05%。综合分析,三维相空间法处理效果较好,其检测准确性高于稳健估算法,但存在过处理现象。建议在处理野点含量低于5%的数据时选用相空间法,而对于野点偏离样本平均值较远的数据时,可以选用稳健估算法。本文对减小流速数据误差,为准确定量研究水流对渔业装备附着生物的附着量与种类影响有着重要的意义。     

Large‐scale regional delineation of riparian vegetation in the arid and semi‐arid Pilbara region,WA

Multiscene Landsat 5 TM imagery, Principal Component Analysis, and the Normalized Difference Vegetation Index were used to produce the first region‐scale map of riparian vegetation for the Pilbara (230,000 km²), Western Australia. Riparian vegetation is an environmentally important habitat in the arid and desert climate of the Pilbara. These habitats are supported by infrequent flow events and in some locations by groundwater discharge. Our analysis suggests that riparian vegetation covers less than 4% of the Pilbara region, whereas almost 10.5% of this area is composed of groundwater dependent vegetation (GDV). GDV is often associated with open water (river pools), providing refugia for a variety of species. GDV has an extremely high ecological value and are often important Indigenous sites. This paper demonstrates how Landsat data calibrated to Top of Atmosphere reflectance can be used to delineate riparian vegetation across 16 Landsat scenes and two Universal Transverse Mercator spatial zones. The proposed method is able to delineate riparian vegetation and GDV, without the need for Bidirectional Reflectance Distribution Function correction. Results were validated using ground truth data from local and regional scale vegetation surveys.     

自适应Canny边缘检测算法研究

在分析传统Canny算子边缘检测原理的基础上,提出了一种自适应Canny边缘检测方法。文中方法在保持了传统Canny算子原有的信噪比高、定位准确和单边缘响应优点基础上,提高了抑制虚假边缘的能力,并且利用全局阈值分割方法自适应确定动态阈值,提高了边缘检测的自动化程度,在实际应用中取得了良好的效果,通过实验证明了自适应Canny边缘检测方法是一种有效的边缘检测改善方法。     

一种阈值函数与灰预测的组合去噪方法

针对传统的灰色预测模型预测精度随步长的增加而逐渐降低的问题,该文采用一种新的阈值及阈值函数对原始数据(信号)进行小波去噪处理,以期增强建模数据(信号)的可靠性,延长模型的预测步长:通过与传统的硬阈值(函数)和软阈值(函数)的比较,验证新阈值及函数对信号的去噪效果;用去噪处理前后的数据分别建立灰预测模型,通过相应的检验指标来判断两函数的预测精度高低。实验结果表明,该阈值及函数与灰预测的组合预测方法是完全可行的,能够在一定程度上提高模型预测的精度和步长。     

Delineation of riparian vegetation from Landsat multi‐temporal imagery using PCA

A deficiency in crucial digital data, such as vegetation cover, in remote regions is a challenging issue for water management and planning, especially for areas undergoing rapid development, such as mining in the Pilbara, Western Australia. This is particularly relevant to riparian vegetation, which provides important ecological services and, as such, requires regional protection. The objective of this research was to develop an approach to riparian vegetation mapping at a regional scale using remotely sensed data. The proposed method was based on principal component analysis applied to multi‐temporal Normalized Difference Vegetation Index datasets derived from Landsat TM 5 imagery. To delimit the spatial extent of riparian vegetation, a thresholding method was required and various thresholding algorithms were tested. The accuracy of results was estimated for various Normalized Difference Vegetation Index multi‐temporal datasets using available ground‐truth data. The combination of a 14‐dry‐date dataset and Kittler's thresholding method provided the most accurate delineation of riparian vegetation.     

基于样条小波和Gabor小波的边缘检测

提供了对图像边缘的两步检测法.先利用样条小波变换模极大值法对图像进行处理,接着利用Otsu的阀值法把模值分为边缘点,非边缘点和待选边缘点.对待选边缘点进行Gabor小波分解,再对其系数进行单阀值处理,就可得到不同尺度下较精确的图像边缘.用小波变换对图像进行边缘检测可以很好地抑制噪声,但其缺点是边缘存在不连续的现象.提供的方法保留了小波变换的优点又进一步提高了检测的精确度和图像边缘的连续性.