共查询到20条相似文献，搜索用时 93 毫秒
1.
Hatice Catal Reis Bülent Bayram Salih Bozkurt Abdulkadir Ince Nusret Demir Dursun Zafer Seker 《Journal of the Indian Society of Remote Sensing》2018,46(8):1223-1232
This study presents an extended shoreline detection approach from pansharpened images of Turkish RASAT satellite which covers red, green and blue bands of the optical spectrum with 15 m ground resolution and panchromatic band with 7.5 m spatial resolution. The Lake Ercek of Turkey has been selected as the study area, which is a tectonic lake and home to a variety of water birds. The satellite images of the lake taken in 2013 and 2014 were considered for analysis. The proposed shoreline extraction system consists of a sequence of image processing steps in which simple linear clustering (SLIC) and particle swarm optimization (PSO) are the main components. SLIC was used to create superpixels that form basis for object-based image analysis while PSO was employed for classifying objects into corresponding classes. The resulting images still contained unwanted artefacts; therefore, a post-processing step was performed to improve the accuracy of segmentation by applying thresholding, morphological processing, and manual editing for noise removal. The proposed framework was applied on two temporal RASAT images to test the variations of defined parameter settings. The success of the proposed system was to obtain shorelines with satisfying accuracy without using NIR band. Finally, the extracted shorelines were vectorised and compared with manually digitized shorelines from pansharpened satellite images for accuracy assessment. 相似文献
2.
Soe Win Myint 《国际地球制图》2013,28(4):29-40
Abstract Attempts to analyze urban features and to classify land use and land cover directly from high‐resolution satellite data with traditional computer classification techniques have proven to be inefficient for two primary reasons. First, urban landscapes are composed of complex features. Second, traditional classifiers employ spectral information based on single pixel value and ignore a great amount of spatial information. Texture plays an important role in image segmentation and object recognition, as well as in interpretation of images in a variety of applications. This study analyzes urban texture features in multi‐spectral image data. Recent developments in the very powerful mathematical theory of wavelet transforms have received overwhelming attention by image analysts. An evaluation of the ability of wavelet transform in urban feature extraction and classification was performed in this study, with six types of urban land cover features classified. The preliminary results of this research indicate that the accuracy of texture analysis in classifying urban features in fine resolution image data could be significantly improved with the use of wavelet transform approach. 相似文献
3.
Poonam S. Tiwari H. Pande Ashwini Kumar Pandey 《Journal of the Indian Society of Remote Sensing》2009,37(2):223-231
Automatic road extraction from remotely sensed images has been an active research in urban area during last few decades. But
such study becomes difficult in urban environment due to mix of natural and man-made features. This research explores methodology
for semiautomatic extraction of urban roads. An integrated approach of airborne laser scanning (ALS) altimetry and high-resolution
data has been used to extract road and differentiate them from flyovers. Object oriented fuzzy rule based approach classifies
roads from high resolution satellite images. Complete road network is extracted with the combination of ALS and high-resolution
data. The results show that an integration of LiDAR data and IKONOS data gives better accuracy for automatic road extraction.
The method was applied on urban area of Amsterdam, The Netherlands. 相似文献
4.
A. Mohammadzadeh M. J. Valadan Zoej A. Tavakoli 《Journal of the Indian Society of Remote Sensing》2009,37(2):173-184
Manual extraction of road network by human operator is an expensive and time-consuming procedure. Alternatively, automation
of the extraction process would be a great advancement. For this purpose, an automatic method is proposed to extract roads
from high resolution satellite images. In this study, using few samples from road surface, a particle swarm optimization is
applied to a fuzzy-based mean calculation system to obtain road mean values in each band of high resolution satellite colour
images. Then, the images are segmented using the calculated mean values from the fuzzy system. Optimizing the fuzzy cost function
by particle swarm optimization enables the fuzzy approach to be the best mean value of road with sub-grey level precision.
Initially, this method was applied to simulated images where the calculated mean values are consistent with the hypothetic
mean values. Application of the method to IKONOS satellite images has shown a prospective outcome for automatic road extraction.
Mathematical morphology is subsequently used to extract an initial main road centreline from the segmented image. Then, small
redundant segments are automatically removed. The quality of the extracted road centreline indicates the effectiveness of
the proposed approach. 相似文献
5.
6.
高分三号卫星全极化SAR影像九寨沟地震滑坡普查 总被引：1，自引：1，他引：0
基于光学遥感影像的区域滑坡普查易受云雾天气的影响,存在滑坡体调查不全面的问题,无法满足震后应急调查与恢复重建的需求。本文提出了一种极化SAR卫星数据滑坡普查方法,采用高分三号全极化SAR卫星影像数据,以九寨沟地震震区为实验区,在深入分析滑坡体和其他地物类型散射特征的基础上,融合极化特征、纹理特征和地形特征等多维特征信息,结合高分二号影像获取的训练样本,构建基于BP神经网络的全极化SAR数据滑坡自动识别模型,实现滑坡体的自动快速识别。与高分辨率光学影像与无人机航空影像目视解译结果相比较,总体识别精度为92.8%,Kappa系数为0.715,识别准确度满足地震应急实际应用的需求。研究成果可用于震区大区域滑坡体的普查,为后续开展无人机高分辨率影像滑坡体详查、灾后应急与景区恢复提供辅助信息支撑,并促进国产高分SAR卫星数据在防震减灾中的应用。 相似文献
7.
Shoreline Change Analysis at Chilika Lagoon Coast,India Using Digital Shoreline Analysis System 总被引：1，自引：0，他引：1
Rakesh Baral Subhasis Pradhan Rabindro Nath Samal Sujit Kumar Mishra 《Journal of the Indian Society of Remote Sensing》2018,46(10):1637-1644
Shoreline is the dynamic interfaces of both terrestrial and marine environment, which constantly affected by natural coastal processes includes wave, tide, littoral drift and cyclonic storms as well as coastal development. Wave induced littoral drift and fluvial discharge causing the gradual inlet migration and has the concurrent impact on shoreline of Chilika lagoon. This study is to determine the long-term shoreline changes along the coast of Chilika lagoon. Historical satellite images were used to analyse the shoreline erosion and accretion based on statistical approach. The satellite data from 1975 to 2015 were processed by using ERDAS Imagine and the shorelines are extracted. The shoreline oscillation was analysed at an interval of 100 m along the coast of Chilika lagoon using DSAS software. Most commonly used statistical methods such as end point rate and linear regression rate are used. The shoreline change analysis for entire coast of the lagoon since 40 years (1975–2015) indicates that 62% is of accretion, 25% is under stable coast and erosion is 13%. The result reveals that the lagoon coast shows high accretion of 9.12 m/year at updrift side of the lagoon inlet whereas the downdrift side shows high erosion of ??10.73 m/year due to the wave induced northeasterly longshore sediment transport round the year and riverine discharge. This study would provide the potential erosion and accretion area at Chilika lagoon coast and would help in adaptive shoreline management plan. 相似文献
8.
以国产GF-1卫星影像为数据源，选取皇甫川流域内山区细小河流密集的上游1421 km2作为研究区域，针对因山区河流河道狭窄、形态复杂等导致的河流边界提取难度大、精度差、河宽无法自动提取的难题，首先利用改进的变异系数法筛选水体指数，再采用改进的决策树法结合DEM河网精确获取河流边界，最后通过自动化河宽提取算法实现对山区细小河流及其河宽的自动提取。结果表明，本文方法对山区河流判别的总体精度为89.5%，有效地排除了山体阴影等地物的干扰。对河宽为0~10 m的极细河流，本文方法提取河宽的误差为18.54%；10~30 m的细小河流，提取误差为12.07%。 相似文献
9.
《International Journal of Digital Earth》2013,6(2):186-193
Abstract According to the features of high-resolution panchromatic imagery of Beijing-1 small satellite, an approach to extracting information of residential areas is proposed in this paper based on Gabor texture segmentation. The algorithm extracts the features in different directions and different scales by building the Gabor filter, uses cluster analysis of multiple features to segment the image, and performs the fusion processing based on morphological scale space. It solves the problems in image processing resulting from low contrast between remote sensing objects and background, the blurring of image edges and high noise. It has the benefits of direction selection and frequency selection with strong self-adaptive ability. Our experiments prove the effectiveness of the approach for extracting information of residential areas from Beijing-1 high-resolution imagery. 相似文献
10.
面向对象的遥感影像多层次迭代分类方法研究 总被引：3，自引：0，他引：3
在分析应用对象化分析方法改进高空间分辨率遥感影像分类技术的基础上,提出了应用多层次的迭代模型改进分类流程,在自适应的迭代过程中有效地结合主导类别选择、高级对象特征计算、基于互信息的特征选择等技术提高对象化方法中丰富的影像特征的利用效率,同时,有机结合像素级特征信息弥补对象化特征。通过对SPOT5影像与航空影像两种数据源... 相似文献
11.
针对高分辨率卫星影像,提出一种特征分量构建与面向对象结合的阴影提取方法。分析遥感阴影光谱特性,构建彩色不变特征C3、亮度特征I、主成分第一特征量PC1以及蓝色波段和近红外波段归一化比率特征RATIOb_nir,增强阴影信息。采用线性变换将几个特征分量Digital Number(DN)值归一化到相同范围,对这几个分量进行综合分析。以I和PC1分量为输入对影像进行多尺度分割,建立包括波段均值、标准差、最大差异等特征的规则集,实现面向对象的阴影信息提取。选取20幅QuickBird影像为例进行阴影提取实验,平均总体精度为97%,平均用户精度为96%,平均Kappa系数为0.94。实验结果表明,相对传统基于像素信息提取方法,本文方法提取阴影斑块完整,无破碎图斑;相对基于原始光谱的面向对象方法,本文方法提取精度更高。 相似文献
12.
ABSTRACTResearchers are continually finding new applications of satellite images because of the growing number of high-resolution images with wide spatial coverage. However, the cost of these images is sometimes high, and their temporal resolution is relatively coarse. Crowdsourcing is an increasingly common source of data that takes advantage of local stakeholder knowledge and that provides a higher frequency of data. The complementarity of these two data sources suggests there is great potential for mutually beneficial integration. Unfortunately, there are still important gaps in crowdsourced satellite image analysis by means of crowdsourcing in areas such as land cover classification and emergency management. In this paper, we summarize recent efforts, and discuss the challenges and prospects of satellite image analysis for geospatial applications using crowdsourcing. Crowdsourcing can be used to improve satellite image analysis and satellite images can be used to organize crowdsourced efforts for collaborative mapping. 相似文献
13.
An improved Bag-of-Words framework for remote sensing image retrieval in large-scale image databases
《International Journal of Digital Earth》2013,6(4):273-292
Due to advances in satellite and sensor technology, the number and size of Remote Sensing (RS) images continue to grow at a rapid pace. The continuous stream of sensor data from satellites poses major challenges for the retrieval of relevant information from those satellite datastreams. The Bag-of-Words (BoW) framework is a leading image search approach and has been successfully applied in a broad range of computer vision problems and hence has received much attention from the RS community. However, the recognition performance of a typical BoW framework becomes very poor when the framework is applied to application scenarios where the appearance and texture of images are very similar. In this paper, we propose a simple method to improve recognition performance of a typical BoW framework by representing images with local features extracted from base images. In addition, we propose a similarity measure for RS images by counting the number of same words assigned to images. We compare the performance of these methods with a typical BoW framework. Our experiments show that the proposed method has better recognition performance than that of the BoW and requires less storage space for saving local invariant features. 相似文献
14.
《地理信息系统科学与遥感》2013,50(3):321-337
The launch of the Very High Resolution (VHR) sensor satellites has paved the way for further exploitation of the capabilities of satellite stereo imaging for many applications. The objective of this paper is to evaluate the level of accuracy that can be achieved by using stereo satellite images for different applications involving significantly different types of terrain. Three mathematical models for satellite sensor modeling are used: Rational Function Model (RFM), 3D polynomial model, and 3D affine model. Three stereo pairs of image datasets are tested from different satellites for different areas: (a) Indian Remote Sensing (IRS)-1D stereo images for topographic mapping and digital terrain elevation modeling for an area in Egypt; (b) IKONOS stereo images for highway alignments extraction in Toronto, Canada; and (c) IKONOS stereo images for topographic mapping and geometric parameter extraction for highway alignments in Hong Kong, China. The accuracy was evaluated by comparing the results of the data extracted using stereo satellite images and those extracted from conventional techniques, including Global Positioning System, field measurements, and aerial photogrammetry. The accuracy of the extracted features was found to be within a pixel-level. The results of this paper should be of interest to professionals from different disciplines exploring the use and accuracy of satellite stereo images for topographic and transportation applications. 相似文献
15.
高分辨率遥感影像建筑物分级提取 总被引：1，自引：1，他引：0
高分辨率遥感影像建筑物信息自动提取是遥感应用研究中的一个热点问题,但由于受到成像条件不同、背景地物复杂、建筑物类型多样等多个因素的影响使得建筑物的自动提取仍然十分困难。为此,在综合考虑影像光谱、几何与上下文特征的基础上,提出了一种基于面向对象与形态学相结合的高分辨率遥感影像建筑物信息分级提取方法。该方法首先利用影像的多尺度及多方向Gabor小波变换结果提取建筑物特征点;然后采用面向对象的思想构建空间投票矩阵来度量每一个像素点属于建筑物区域的概率,从而提取出建筑物区域边界;最后在提取的建筑物区域内应用形态学建筑物指数实现建筑物信息的自动提取。实验结果表明,本文方法能够高效、高精度地完成复杂场景下的建筑物信息提取,且提取结果的正确性和完整性都优于效果较好的PanTex算法。 相似文献
16.
AbstractHyperspectral image provides abundant spectral information for remote discrimination of subtle differences in ground covers. However, the increasing spectral dimensions, as well as the information redundancy, make the analysis and interpretation of hyperspectral images a challenge. Feature extraction is a very important step for hyperspectral image processing. Feature extraction methods aim at reducing the dimension of data, while preserving as much information as possible. Particularly, nonlinear feature extraction methods (e.g. kernel minimum noise fraction (KMNF) transformation) have been reported to benefit many applications of hyperspectral remote sensing, due to their good preservation of high-order structures of the original data. However, conventional KMNF or its extensions have some limitations on noise fraction estimation during the feature extraction, and this leads to poor performances for post-applications. This paper proposes a novel nonlinear feature extraction method for hyperspectral images. Instead of estimating noise fraction by the nearest neighborhood information (within a sliding window), the proposed method explores the use of image segmentation. The approach benefits both noise fraction estimation and information preservation, and enables a significant improvement for classification. Experimental results on two real hyperspectral images demonstrate the efficiency of the proposed method. Compared to conventional KMNF, the improvements of the method on two hyperspectral image classification are 8 and 11%. This nonlinear feature extraction method can be also applied to other disciplines where high-dimensional data analysis is required. 相似文献
17.
Uwe Soergel Eckart Michaelsen Antje Thiele Erich Cadario Ulrich Thoennessen 《ISPRS Journal of Photogrammetry and Remote Sensing》2009,64(5):490-500
SAR stereo image analysis for 3D information extraction is mostly carried out based on imagery taken under same-side or opposite-side viewing conditions. For urban scenes in practice stereo is up to now usually restricted to the first configuration, because increasing image dissimilarity connected with rising illumination direction differences leads to a lack of suitable features for matching, especially in the case of low or medium resolution data. However, due to two developments SAR stereo from arbitrary viewing conditions becomes an interesting option for urban information extraction. The first one is the availability of airborne sensor systems, which are capable of more flexible data acquisition in comparison to satellite sensors. This flexibility enables multi-aspect analysis of objects in built-up areas for various kinds of purpose, such as building recognition, road network extraction, or traffic monitoring. The second development is the significant improvement of the geometric resolution providing a high level of detail especially of roof features, which can be observed from a wide span of viewpoints. In this paper, high-resolution SAR images of an urban scene are analyzed in order to infer buildings and their height from the different layover effects in views taken from orthogonal aspect angles. High level object matching is proposed that relies on symbolic data, representing suitable features of urban objects. Here, a knowledge-based approach is applied, which is realized by a production system that codes a set of suitable principles of perceptual grouping in its production rules. The images are analyzed separately for the presence of certain object groups and their characteristics frequently appearing on buildings, such as salient rows of point targets, rectangular structures or symmetries. The stereo analysis is then accomplished by means of productions that combine and match these 2D image objects and infer their height by 3D clustering. The approach is tested using real SAR data of an urban scene. 相似文献
18.
Occurrence of cloud cover over remotely sensed area is a significant limitation in the ocean colour and infra-red remote sensing applications, especially when operational use of such a data is considered. A method for the reconstruction of missing data in remote sensing images has been proposed. It is based on complementing satellite data with the corresponding information from other sources of data, in our tested case it was the ecohydrodynamic model. The method solves the problem the presence of a cloud cover also during an extended period. Unlike in many other similar methods, emphasis has been put on retaining remotely sensed information to a high degree and preserving local phenomena that are usually difficult to capture by other methods than satellite remote sensing. The method has been tested on the Baltic Sea. Sea surface temperature and chlorophyll a concentration estimated from satellite data, ecohydrodynamic models and merged product were compared with in situ data. The algorithm was optimized for the two parameters that are crucial for e.g. creating algae bloom forecasts. The root mean square error (RMSE) of the final product of sea surface temperature was 0.73 °C, whereas of the input satellite images 1.26 °C or 1.33 °C and of model maps 0.89 °C. The error factor of chlorophyll a concentration product was 1.8 mg m−3, in comparison to 2.55 mg m−3 for satellite input source and 2.28 mg m−3 for the model one. The results show that the proposed method well utilizes advantages of both satellite and numerical simulation data sources, at the same time reducing the errors of estimation of merged parameters compared to similar errors for both primary sources. It would be a valuable component of fuzzy logic and rule-based HABs prediction. 相似文献
19.
高分辨率遥感影像上细节信息繁杂、干扰物普遍存在,对其进行自动化道路识别与提取的相关研究仍处在探索阶段。在道路提取过程中引入矢量数据辅助,可解决初始信息获取的困难,得到可靠性较强的训练样本。为此,提出一种矢量数据辅助下的道路提取方法,能够筛选出矢量数据中包含的有效信息,引导实现对高分辨率遥感影像的道路自动提取。利用Mean-shift滤波对图像进行预处理后,首先从矢量数据获取候选种子点,并通过提炼同质区域的形状特征剔除错误候选点;然后,自动获取负样本点以进行朴素贝叶斯分类,并采用邻域质心投票算法从分类影像提取道路中心线;最后,结合像素跟踪与方向判断矢量化道路中心线,并提出一种基于矢量几何分析的断线连接与毛刺剔除方法,对提取结果进行信息修复与规整、优化。实验结果显示,该算法的提取质量达到80%以上,且具备较强的稳健性,能够适应具有不同道路辐射和分布特征的高分辨率遥感影像。 相似文献
20.
We present an automatic approach for object extraction from very high spatial resolution (VHSR) satellite images based on Object-Based Image Analysis (OBIA). The proposed solution requires no input data other than the studied image. Not input parameters are required. First, an automatic non-parametric cooperative segmentation technique is applied to create object primitives. A fuzzy rule base is developed based on the human knowledge used for image interpretation. The rules integrate spectral, textural, geometric and contextual object proprieties. The classes of interest are: tree, lawn, bare soil and water for natural classes; building, road, parking lot for man made classes. The fuzzy logic is integrated in our approach in order to manage the complexity of the studied subject, to reason with imprecise knowledge and to give information on the precision and certainty of the extracted objects. The proposed approach was applied to extracts of Ikonos images of Sherbrooke city (Canada). An overall total extraction accuracy of 80% was observed. The correctness rates obtained for building, road and parking lot classes are of 81%, 75% and 60%, respectively. 相似文献