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1.
珊瑚礁对于海洋生态环境研究具有重要意义,通过分析珊瑚礁底栖物质的分布及健康状况,可以对珊瑚礁生态环境进行评估。本文提出了一种基于面向对象的图像分类方法,通过试验确定不同地貌的最优分割尺度,其中陆地和深海的最优分割尺度为150,各类底栖物质的最优分割尺度为30。以Sentinel-2A卫星遥感影像为例,提取海南三亚珊瑚礁自然保护区的珊瑚礁底栖物质,并使用混淆矩阵对提取结果进行精度评估。结果表明,底栖物质提取总体分类精度为87.91%,Kappa系数为0.83。面向对象分类方法可有效结合珊瑚礁底栖物质的纹理特征和光谱特征,并充分利用遥感影像不同波段的组合特性,可为三亚珊瑚礁保护管理提供方法支撑。 相似文献
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A global inventory of coral reef stressors based on satellite observed nighttime lights 总被引：1，自引：0，他引：1
In this article, we present a satellite-based approach to gather information about the threat to coral reefs worldwide. Three chosen reef stressors – development, gas flaring and heavily lit fishing boat activity – are analysed using nighttime lights data derived from the Defense Meteorological Satellite Program (DMSP) produced at the National Oceanic & Atmospheric Administration, National Geophysical Data Center (NOAA/NGDC). Nighttime lights represent a direct threat to coral reef ecosystems and are an excellent proxy measure for associated human-caused stressors. A lights proximity index (LPI) is calculated, measuring the distance of coral reef sites to each of the stressors and incorporating the stressor's intensity. Colourized maps visualize the results on a global scale. Area rankings clarify the effects of artificial night lighting on coral reefs on a regional scale. The results should be very useful for reef managers and for state administrations to implement coral reef conservation projects and for the scientific world to conduct further research. 相似文献
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珊瑚礁遥感研究进展 总被引：1，自引：0，他引：1
珊瑚礁是生物多样性和初级生产力最高的海洋生态系统之一,对人类社会与海洋生态环境的健康和可持续发展有重要作用,而珊瑚礁又是中国南海主要的国土类型,国家因此越来越重视对南海珊瑚礁的规划、管理、建设与保护。珊瑚礁的调查与探测则是进行珊瑚礁活动的基础与依据,而遥感则在珊瑚礁的大范围探测方面具有很大的潜力,所以国内外已经存在很多利用遥感对珊瑚礁进行调查与探测的研究与应用。本文将按照被动遥感和主动遥感的顺序,客观地阐述国内外珊瑚礁遥感研究与应用的进展,探讨珊瑚礁遥感研究与应用的发展趋势,并尝试总结中国珊瑚礁遥感的机遇和挑战。其中被动遥感包括珊瑚礁地形与水深的遥感、珊瑚礁底质与地貌的遥感、珊瑚礁岸线变化与稳定性的遥感以及珊瑚礁环境的遥感等,而主动遥感则包括珊瑚礁水深的机载激光雷达遥感、珊瑚礁地貌的船载声学遥感和珊瑚礁地形的星载微波遥感等。结果发现,国内珊瑚礁遥感研究与应用的整体水平落后于国外:虽然在部分数据处理方面具有比国外更先进的技术,但相应的应用基础研究仍然达不到国外的广度与深度。因此,国内的珊瑚礁遥感研究仍需要鼓励珊瑚礁学者更多的参与与合作,以便在硬件设备和数据处理等方面加强针对珊瑚礁遥感的研究,进而融合多种手段而实现珊瑚礁遥感的工程化应用。 相似文献
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如何将各种不同传感器获得的遥感数据结合起来,通过图像融合来提高图像的信息量,从中挖掘更深层次的信息,以更充分地识别和解译有关专题信息,受到国内外科研工作者的重视,研究了超分辨率贝叶斯方法--PanSharpening方法,该方法利用全波段增强多光谱遥感影像,合并传感器特性模拟了全波段和多波段影像的观测过程.这种方法使全波段数据与多光谱波段数据自动对齐,成功地保留了光谱信息,同时增加了空间分辨率,丰富了地面信息.以IKONOS全波段和多波段影像为例进行了深入的探讨.并对自动融合的结果进行了定性和定量分析. 相似文献
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黑土区田块尺度遥感精准管理分区 总被引：2，自引：0，他引：2
基于格网采样与空间插值的精准管理分区方法精度高,但时效性差、成本高。本文以东北农垦地区红星农场农田为研究对象,提出一种基于遥感影像的精准管理分区方法:以裸土高空间分辨率遥感影像作为数据源,结合田间格网采样数据,基于裸土反射光谱特征与黑土主要理化性质的显著相关关系,运用面向对象分割、空间统计分析方法,对典型黑土区田块进行精准管理分区研究,并利用土壤理化性质和农作物生理参数,对分区结果进行评价。得出如下结论:(1)典型黑土区田块内部土壤养分含量空间变异显著;(2)基于裸土影像与面向对象的精准管理分区方法精度高,增强了分区之间的土壤养分与归一化植被指数(NDVI)差异性、分区内部各属性的一致性;(3)基于2015年4月1日和2015年5月20日单期影像分区和两期影像波段叠加(Layer stacking)分区,区间变异系数与区内变异系数之比分别为1.42、1.39和7.63,基于两期影像综合信息的分区结果显著优于基于单期影像分区;(4)基于裸土影像面向对象分割的精准管理分区方法时效性强、成本低、精度高。研究成果为田间变量施肥、发展精准农业、实现农业可持续发展提供依据。 相似文献
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Anjali Bahuguna Shailesh Nayak Dam Roy 《International Journal of Applied Earth Observation and Geoinformation》2008,10(2):229-1
Tsunami waves struck the Indian coast on 26th December 2004 affecting the Andaman and Nicobar group of islands. A quick assessment of the status of the vital coastal ecosystems has been made using pre- and post-tsunami Advance Wide Field Sensor (AWiFS) data of Indian satellite RESOURCESAT with an accuracy of 87–90% and the Kappa ranging from 0.8696 to 0.9053. Among the coastal ecosystems the coral reefs have suffered the maximum with the Nicobar reefs (69% eroded and 29% degraded) bearing the brunt more than the Andaman reefs (54% eroded and 22% degraded). Significant improvement to the condition of the reef damaged due to backwash has been noted. About 41% of the Sentinel reef area has undergone significant improvement. The continuance of the erosion of the southwestern Andaman reefs is due to the impact of recurring earthquakes. The impact on mangroves of both the groups of islands has been due to uprooting as well as inundation of seawater and resulting stagnation. Changes are expected in community structure of mangroves as a result of tsunami. 相似文献
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合成孔径雷达SAR（Synthetic Aperture Radar）是开展城市建筑区信息获取与动态监测的重要数据源。本文建立了一个面向深度学习建筑区提取的中高分辨率SAR建筑区数据集SARBuD1.0 （SAR BUilding Dataset）。该数据集包含了覆盖中国不同区域的27景高分三号（GF-3）精细模式SAR图像,并从中获取了建筑区共计60000个SAR样本数据,结合光学图像与专家解译,制作了与样本数据对应的标签图像。SARBuD1.0数据集包含了不同地形场景类型、不同分布类型、不同区域的建筑区。该数据集可支持研究者对建筑区进行图像特征分析、辅助图像理解,并可对当前热点深度学习方法提供训练、测试数据支持。本文以山区建筑为例,使用传统纹理特征与深度学习特征对建筑区进行了特征分析与比较,相比于传统的人工设计的纹理特征,卷积神经网络具有更深、更多的特征,利用网络模型浅层的不同卷积核采样可得到各种纹理特征,在网络的深层卷积结构中可获取代表着类别的深层语义特征,使得分类器能更好地检测并提取图像中指定的目标。基于本数据集利用深度学习方法对不同地形区域的建筑区进行提取实验。实验结果表明基于本数据集训练的深度学习模型,对建筑区提取可以取得良好的结果,说明该数据集可以很好支持面向大数据的深度学习方法。其他学者可以基于SARBuD1.0数据集开展建筑区图像特征分析与语义分割提取等方面的研究。 相似文献
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R. Sridhar T. Thangaradjou L. Kannan S. Astalakshmi 《Journal of the Indian Society of Remote Sensing》2010,38(3):565-575
Coastal resources viz., coral reefs, seagrasses, mangroves, and coastal land features viz., sandy beach, mudflats and salt
pan/aquaculture ponds were classified and assessed in the Palk Bay region of the south-east coast of India using IRS LISS
III satellite image (1996, 2000, 2002 and 2004). The study recorded an areal coverage of 286.95 ha of reef area during 2004,
which is 177.54 ha lesser than that of the reef area of 1996. The reef vegetation composed mainly of seaweeds has gained over
29.44 ha during the same period. Likewise, sand over reef area has also increased alarmingly i.e. 120.34 ha between 1996 and
2004. The seagrass beds of Munaikkadu region of the Palk Bay are comparatively protected and have gained over 7.5 ha between
1996 and 2004. It has been found that both the dense (2.99 ha) and sparse (36.45 ha) mangroves have gained their areal coverage
considerably between 1996 and 2004. Whereas in Devipattinam region, many anthropogenic pressures are exerted only on the seagrass
resources which has led to the reduction of over 785.5 ha of dense seagrass beds between 1996 and 2004. The study clearly
indicated that the resources are under the pressures of low to high threats, especially the coral reefs and seagrasses, if
the pressures continue, coastal resources of the Palk Bay may face serious threats of destruction in this part of the Bay
in the years to come. 相似文献
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Sreenivas Kandrika R. S. Dwivedi 《Journal of the Indian Society of Remote Sensing》2013,41(3):731-737
Information on the depth and bed width of ravines (network of gullies) at large scales is critical for their reclamation and management. Hitherto such information has been generated from aerial photographs and space borne stereo images with medium to coarse ‘z’ – axis resolution. The present study, aims at demonstrating the potential of Cartosat ?1 (an Indian Earth observations satellite) stereo images with 2.5 m spatial resolution in deriving morphometric information on ravines for their reclamative grouping. The study area is a part of Jhansi and Hamirpur districts of Uttar Pradesh, northern India. The approach involves acquiring precise ground control points using Differential GPS (DGPS), triangulation, DEM extraction and generation of ortho image as well as anaglyphs for stereo viewing. The depth and bed width of ravines were measured in the field for validation. A comparison with field observations reveal that the bed width of ravines and depth can be measured successfully with Carto-1 stereo data. The anaglyph data was used to delineate various categories of ravines based on their depth and bed width. Results indicate that the Cartosat-1 stereo images are quite suitable for delineation of three categories of ravines, namely shallow (<3 m deep and <18 m bed width), medium deep (3–9 m deep and >18 m bed width) and deep (>9 m deep) which are important for their reclamation. 相似文献
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《地理信息系统科学与遥感》2013,50(2):251-274
New methods are needed for the study of coral reefs, as they are changing rapidly. Satellite remote sensing has become a common method for benthic mapping with advances in satellites and sensors and as methods are devised to account for atmospheric and water-column effects. Images from the QuickBird satellite have proven useful in reef mapping. Sand was distinguished from coral with an overall accuracy of 75% on the shallow reef off of the Caribbean island of Bonaire. Coral and sand had user accuracies of 50% and 90%, respectively. Increased samples of field-collected data would further increase the accuracies of such classifications. 相似文献
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遥感影像融合作为影像处理领域中最具有挑战的工作,一直是学术界研究的热点。合成孔径雷达SAR（Synthetic Aperture Radar）具备全天时、全天候、穿透云雾等多种特点,却因存在相干斑噪声等问题,使得影像难以解译。相比之下,光学影像可以反映地物的光谱和空间信息,易于解译,但容易受到云雾干扰,造成信息丢失,将光学与SAR影像数据融合可以实现不同类型传感器成像之间的信息互补,能够更好地为后续的影像分析与解译提供方便。本文首先对光学和SAR影像融合进行了系统性回顾,包括传统融合方法和基于深度学习方法在影像融合方面的最新工作,重点阐述了卷积神经网络CNN（Convolutional Neural Network）、生成式对抗网络GAN（Generative Adversarial Networks）等框架在光学和SAR影像融合中的进展;然后总结了光学和SAR影像融合在深度学习领域开发的数据集,并做了简单介绍和说明;最后,从数据集、时间序列影像融合、融合评价体系和算法轻量化等4个方面对光学和SAR影像融合的未来发展趋势进行了展望。 相似文献
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Kátia Kellem da Rosa Cláudio Wilson Mendes Jr. Jorge Arigony-Neto Jefferson Cardia Simões 《国际地球制图》2016,31(9):1032-1043
This work analysed the spatio-temporal variation of snow cover on the Kraków Ice Field, located in the King George Island, Antarctica. High spatial resolution images of COSMO-SkyMed were used in this study. These X-band images are vertically and horizontally co-polarized and their intensity data were converted to amplitude (dB). The COSMO-SkyMed images were classified by a minimum distance algorithm and post-classified based on knowledge of adjacency relationships of snow zones. Hypsometric, slope, aspect and solar radiation maps to support the interpretation of backscatter patterns in the COSMO-SkyMed images. Three radar zones were classified in these images: percolation, slush and wet snow radar zone. Positive surface air temperatures and rainfall events, registered from a meteorological station, lead to increase in wet snow and slush zones. The COSMO-SkyMed images and minimum distance algorithm were adequate to discriminate the snow cover and to assess the supraglacial melting pattern during the ablation season in the study area. 相似文献
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Thara Nair Latha James C. V. Rao A. V. V. Prasad B. Gopala Krishna V. K. Dadhwal 《Journal of the Indian Society of Remote Sensing》2017,45(5):873-885
Coral reefs are one of the most diverse of all marine ecosystems and are often referred to as the “rainforests of the sea”. Though they cover less than one per cent of Earth’s surface, they are home to one quarter of all ocean species by providing food and shelter to them. Optical remote sensing has been widely employed for mapping and monitoring coral reefs. But the application of microwave remote sensing has been an alternate domain in this area. This study explores the possibility of utilizing synthetic aperture radar (SAR) data of Radar Imaging Satellite-I, India’s first indigenous microwave satellite to delineate the coral reefs in Andaman and Lakshadweep Islands in the Indian Ocean. The dual polarized data, after reducing the speckle has been classified to delineate the coral reefs in the vicinity of both islands. SAR has a performance comparable with passive optical sensors under favourable conditions of imaging, viz. optimum tidal current and surface winds. The study results are compared with the international coral reef reference map and are found to be highly promising, with an overall accuracy of 98.3% and a Kappa coefficient of 0.944 for fringing reefs in Andaman region. For the atolls in Lakshadweep region, the overall accuracy is found to be 92.99% and the Kappa coefficient is estimated at 0.7377. This study tries to explore a different horizon for microwave remote sensing in coral reef studies. It is seen that, optical and microwave remote sensing can provide a mutually supporting platform in coral reef delineation, in terms of imaging depth as well as climatic conditions. 相似文献
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联合卷积神经网络与集成学习的遥感影像场景分类 总被引：1，自引：0，他引：1
针对人工设计的中、低层特征难以实现复杂场景影像的高精度分类以及卷积神经网络依赖大量训练数据等问题，结合迁移学习与集成学习，提出了一种联合卷积神经网络与集成学习的遥感影像场景分类算法。首先基于迁移学习的思想，利用在自然影像数据集上训练好的多个深层卷积神经网络模型作为特征提取器，提取图像多个高度抽象的语义特征；然后构建由Logistic回归和支持向量机组成的Stacking集成模型，对同一图像的多个特征分别训练Logistic模型，将预测概率结果融合构建概率特征；最后利用支持向量机对概率特征训练和预测，得到场景影像的分类结果。利用UCMerced_LandUse和NWPU-RESISC 45两种不同规模的遥感影像数据集进行试验，即使在只有10%的数据作为训练样本情况下，本文方法能够分别达到90.74%和87.21%的分类精度。 相似文献
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本义重点研究以遥感为主的多源信息综合处理技术，取得的主要成果是：对遥感数据采用特定的图像处理，减弱了植被、冻土带的干扰；开创性地从能谱图像中定性、定量地提取铀信息和从地球化学场角度揭示构造蚀变带；研究岩石反射光谱特征，突出找矿蚀变信息；利用重、磁图像挖掘深层构造信息及首次成功地研制出高几何配准精度的综合找矿预测影像图等。应用这些成果指导找矿，取得突破性进展，地表矿体和矿化体的揭露，显示出该项技术的科学性和实用价值。 相似文献
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