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Macroalgae plays an important role in coastal ecosystems. The accurate delineation of macroalgae areas is important for environmental management. This study compared the pixel- and object-based methods using Gaofen satellite no. 2 image to explore an efficient classification approach. Expert system rules and nearest neighbour classifier were adopted for object-based classification, whereas maximum likelihood classifier was implemented in the pixel-based approach. Normalized difference vegetation index, normalized difference water index, mean value of the blue band and geometric characteristics were selected as features to distinguish macroalgae farms by considering the spectral and spatial characteristics. Results show that the object-based method achieved a higher overall accuracy and kappa coefficient than the pixel-based method. Moreover, the object-based approach displayed superiority in identifying Porphyra class. These findings suggest that the object-based method can delineate macroalgae farming areas efficiently and be applied in the future to monitor the macroalgae farms with high spatial resolution imagery. 相似文献
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红树林的种间结构组成对红树林生态系统的健康和发展至关重要,而红树林种间分类问题一直以来都是基于遥感手段的红树林监测中的难点。针对该问题,以人工种植为特点的广西茅尾海红树林遥感种间分类为例,基于面向对象的分类思想,提出了一种现场样本与分割对象相结合的红树林种间分类方法。利用GF-2 PMS1高分辨率卫星遥感影像数据,开展了广西茅尾海红树林湿地典型植被精细分类和空间分布研究,并将分类结果与基于像素和传统面向对象SVM分类方法进行了对比。结果显示:总体上,面向对象分类方法更适合用于茅尾海红树林湿地典型植被分类;对于局部混生明显的区域使用基于像素SVM分类方法效果会更好;传统面向对象分类方法中将整个影像分割对象单元作为训练样本可能会在某种程度上造成负面影响。因此,使用文中提出的样本选择新方法进行面向对象分类精度最高,总体精度达到了93.13%,Kappa为0.89。 相似文献
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分形定量选择遥感影像最佳空间分辨率的方法与实验 总被引：1，自引：0，他引：1
遥感影像观测尺度是遥感信息提取研究的重要内容之一,也是遥感信息提取的焦点。以往,遥感影像尺度特征的分析大多基于地统计学,其主要体现遥感影像中的线性特征,而实质上遥感影像中既存在线性特征,又存在非线性特征。因此,在深入剖析遥感影像尺度效应及分形特征机理的基础上,本文探讨了分形理论定量选择遥感影像最佳空间分辨率（也称最佳像元观测尺度）的方法。以IKONOS全色影像的建筑用地、耕地、林地为研究对象,分别使用FBM、DBM、TPM 3种分形维数计算模型,实现了3种地物在不同空间分辨率下分形维数的计算。实验结果表明,每种地物的分形维数是随空间分辨率的增大,总体呈下降趋势,且在某些特征空间分辨率上会出现拐点。从遥感影像尺度效应分析可知,遥感影像空间格局随尺度的不同,其内部结构也不同。且随着尺度的增大,很多细节将会被忽略,影像的粗糙度也随着降低。而分形维数是目前为止描述对象自相似性和不规则度的唯一基本量化值,其直观上与物体表面的粗糙程度相吻合。因此,这些拐点对应的分形维数对地物的最佳空间分辨率的选择具有一定指示意义。通过本文研究可知,使用分形理论方法研究遥感影像最佳空间分辨率（或最佳像元观测尺度）,打破以往观测尺度方法研究范畴,从不同角度去分析遥感影像观测尺度问题对GIS研究与地学应用具有一定的理论和指导意义。 相似文献
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With the increasing availability of high-spatial-resolution remote sensing imageries and with the observed limitations of pixel-based techniques, the development and testing of geographic object-based image analysis (GEOBIA) techniques for image classification have become one of the main research areas in geospatial science. This paper examines and compares the classification performance of a pixel-based method and an object-based method as applied to high- (QuickBird satellite image) and medium- (Landsat TM image) spatial-resolution imageries in the context of urban and suburban landscapes. For the pixel-based classification, the maximum-likelihood supervised classification approach was employed. And for the object-based classification, the pixel-based classified maps were integrated with a set of image segments produced using various calibrations. The results show evidence that the object-based method can produce classifications that are more accurate for both high- and medium-spatial- resolution imageries in the context of urban and suburban landscapes. 相似文献
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多源遥感影像数据融合技术探讨 总被引：1，自引：0，他引：1
针对当前海量遥感数据与相对较低的数据利用率并存的现状,探讨了数据融合的概念,融合的3个层次:像素级、特征级和决策级融合,以及各层次的优缺点、流程和常用的融合方法;并详细阐述了融合影像的评价指标。进行了某地区的融合试验,从而得出对同一地区的遥感影像数据进行融合,可以产生更准确、更完全,更可靠的估计和判断的结论,为类似的工作提供了借鉴。 相似文献
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Regional operational forest species mapping is an active research topic that aims to provide the systematic and updatable information necessary for understanding and monitoring the rapidly changing forest environment. In this study, we investigated the potential of satellite hyperspectral imagery in regional forest species mapping by employing a pixel-based and an object-based nearest neighbour classifier in two different Mediterranean study areas. The overall thematic accuracy of the produced maps was assessed using reference data collected in the field and ranged between 0.72 and 0.83. No approach was found to be superior for the study areas. The McNemar test showed no statistically significant difference at the 95% confidence level in the classification accuracies achieved by the two approaches. Both pixel- and object-based approaches provide useful maps, suggesting that regional forest species mapping from space has much potential. 相似文献