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青海三江北段是我国重要的多金属成矿区带,具有形成大型、特大型金属矿床的赋存条件及地质背景。纳日贡玛矿床是该区带中最为典型的斑岩型Cu–Mo矿床。针对斑岩型矿床的典型蚀变分带特征,利用ASTER数据,采用Crosta技术和比值法进行高岭石化、青磐岩化、黄铁矿化和硅化等遥感蚀变异常信息的提取;通过对ASTER和QuickBird图像的遥感解译,获得花岗斑岩体和断裂构造的空间分布图;根据纳日贡玛矿床的成矿规律和控矿要素,利用遥感数据获得的找矿预测因子,圈定了8个具有良好找矿前景的遥感找矿预测区,并总结出纳日贡玛的遥感蚀变异常分带规律,可为三江北段成矿带中其他斑岩型Cu–Mo矿床的找矿勘查提供重要参考信息。 相似文献
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付洪波 《测绘与空间地理信息》2011,(6):82-84
借用光谱角制图法,依据所用数据与参考端元矢量之间的夹角不同,对研究区进行空间区域划分,在不同空间区域采用不同方法和参数提取遥感异常信息,所得结果结合遥感地质解译（岩性、构造）圈定出研究区内的找矿远景区。 相似文献
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《国土资源遥感》2020,(1)
高空间分辨率遥感(以下简称"高分遥感")数据信息丰富,能较好地用于识别微观岩性、构造等控矿信息。为了开展高分遥感数据在海拔高、基岩裸露的西藏荣勒地区的控矿信息提取研究,首先利用WorldView-2高分遥感数据确定最佳波段组合,在此基础上,对该地区地层、岩性、岩体、构造、接触带等与铜多金属成矿密切相关的控矿信息进行解译;然后,利用ASTER数据,采用主成分分析法提取与矿化相关的铁染、铝羟基和镁羟基等遥感蚀变异常信息;最后,综合区域铜矿成矿规律,通过人机交互解译,构建了岩浆热液型铜矿控矿信息遥感找矿模式,圈定出5个找矿靶区并通过野外查证发现了较好的矿化线索,为推进当地找矿进程提供了基础资料和参考依据。研究结果表明,高分遥感数据可以满足我国西部高海拔环境恶劣地区的矿产资源勘查和资源评价需求,彰显了高分遥感快速、高效、可靠的应用优势。 相似文献
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遥感构造蚀变异常信息提取及找矿预测——以老挝为例 总被引：1，自引：0，他引：1
遥感地质异常信息提取是遥感地质学的重要研究内容之一.以老挝为例,对研究区ETM+遥感图像采用几何纠正、图像镶嵌、彩色合成、空间变换、图像增强等技术手段,提取地质构造信息;利用掩模技术去除干扰信息,采用主成分分析和阈值分割技术进行铁染和羟基蚀变异常信息提取;结合区域地质、地球物理、地球化学等多元地学信息综合分析,开展研究区遥感找矿预测,圈定了5处遥感找矿远景区.研究成果为加快老挝地质找矿工作提供了基础数据和决策依据. 相似文献
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遥感找矿模型的研究进展与评述 总被引：2，自引：0，他引：2
在遥感找矿模型研究现状分析的基础上,对当前研究中存在的一些问题进行了探讨,指出遥感找矿模型的研究应注重矿床形成和保存两方面的信息,尤其是矿床保存方面的信息。遥感找矿模型是在当前技术条件下,描述一类矿床形成和保存的一系列遥感找矿标志的组合,应包括遥感地质找矿标志、遥感蚀变信息标志和矿床改造信息标志等几个方面的内容。 相似文献
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板桥稀土矿遥感找矿信息提取与矿产预测研究 总被引：1，自引：0，他引：1
通过对离子吸附型稀土矿成矿规律的分析,从浙江省板桥地区的遥感地质特征研究入手,在研究区地表范围内进行稀土遥感找矿信息的提取。首先利用SPOT图像和DEM数据构建的坡度数据对与稀土成矿相关的地貌单元进行解译;然后通过光谱特征分析和基于ASTER图像的矿物遥感异常提取,获取与成矿相关的高岭土、绢云母、绿泥石等风化特征矿物的分布信息;最后叠合分析地貌、坡度及异常提取结果,进行稀土遥感找矿预测。与地质调查资料及化探数据的对比分析证实,上述方法对圈定1∶5万的大比例尺离子吸附型稀土矿分布范围是有效的,可为更详细的稀土矿产资源潜力评价提供依据。 相似文献
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高分辨率影像解译理论与应用方法中的一些研究问题 总被引：36，自引：4，他引：36
近年来，不断发展的遥感技术使遥感数据呈现出高空间分辨率、高光谱分辨率和高时间采集频率的特点。卫星图像空间分辨率已经提高到0．6m级，而航空遥感数字影像分辨率高达0．1m以上。光谱分辨率高达3—4nm。不断发展的高分辨率遥感数据能够提高信息提取和监测精度，并拓展遥感数据的应用范围。目前，国外已经加快对高分辨率图像，特别是高空间分辨率影像，在城市环境、精准农业、交通及道路设施、林业测量、军事目标识别和灾害评估中的应用。但是总的情况是自动化程度不高。介绍高空间分辨率影像信息提取、高光谱和偏振影像信息提取、影像数据融合和高分辨率遥感变化探测等方面迫切需要研究的一些科学问题及其意义。建议建立图像知识库，改善数据共享环境，为有志于从事这方面研究的学者提供参考。 相似文献
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有效监测人工水产养殖水面的分布变化对于海洋资源管理、生态环境保护、防灾减灾具有重要意义。本文以Landsat 5、SPOT 5和GF-1卫星影像为数据源,选择广东省北莉岛为研究区,使用线性光谱解混方法获取中等空间分辨率卫星影像的人工水产养殖水面面积,通过面向对象多尺度分割的方法结合支持向量机分类算法提取高空间分辨率卫星影像的人工水产养殖水面分布。研究结果表明,与单一卫星影像相比,综合多源中高空间分辨率卫星数据延长了人工水产养殖水面变化分析可追溯的时间跨度,提高了监测精度;联合光谱解混和面向对象分类方法开展人工水产养殖长时序遥感监测是可行的。近20多年来,北莉岛人工水产养殖水面的面积经历了先增加后缓慢减少的变化过程,1995—2000年平均增速为23.39 hm2/a,2000—2006年平均增速为23.95 hm2/a,2006—2019年平均减少速度为1.96 hm2/a。 相似文献
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森林火灾是最为常见的灾害之一,严重危及人类生命安全。及时准确监测森林火灾的发生及火场状况,对应对火灾及减少损失至关重要。当前,森林火灾卫星遥感监测主要以低空间分辨率的卫星遥感为主,空间分辨率过低导致无法探测规模较小火灾及掌握详细火场态势。针对这一问题,结合近些年中高空间分辨率卫星观测、共享及处理能力的发展,本文从森林火灾卫星遥感监测的基本原理、当前可用中高空间分辨率卫星数据及其特点、中高分辨率森林着火区监测算法,以及数据共享与云端存储与计算等4个技术环节,对森林火灾中高分辨率卫星遥感监测当前研究现状与存在问题进行了总结,阐述了近实时中高空间分辨率森林火灾监测系统的可行性。近实时中高空间分辨率森林火灾监测系统可对已有低空间分辨率森林火灾监测体系形成重要补充,依托其空间分辨率的优势有助于及早、准确发现小规模火情,进而为森林火灾的防治与管理提供更好支撑。 相似文献
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地表参数定量遥感反演是遥感科学研究的重要环节.21世纪以来,地球静止气象卫星数据在地表参数遥感反演中受到越来越多的重视.本文对利用地球静止气象卫星进行地表参数遥感反演研究的进展进行了综述.文章首先简单介绍了当前正在运行的欧盟Meteosat、美国GOES-R、日本葵花和中国风云静止卫星系统,随后详细总结了不同卫星系统估... 相似文献
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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
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Automatic Road Extraction from High Resolution Satellite Image using Adaptive Global Thresholding and Morphological Operations 总被引：2，自引：0，他引：2
Road network extraction from high resolution satellite images is one of the most important aspects. In the present paper, research experimentation is carried out in order to extract the roads from the high resolution satellite image using image segmentation methods. The segmentation technique is implemented using adaptive global thresholding and morphological operations. Global thresholding segments the image to fix the boundaries. To compute the appropriate threshold values several problems are also analyzed, for instance, the illumination conditions, the different type of pavement material, the presence of objects such as vegetation, vehicles, buildings etc. Image segmentation is performed using morphological approach implemented through dilation of similar boundaries and erosion of dissimilar and irrelevant boundaries decided on the basis of pixel characteristics. The roads are clearly identifiable in the final processed image, which is obtained by superimposing the segmented image over the original enhanced image. The experimental results proved that proposed approach can be used in reliable way for automatic detection of roads from high resolution satellite image. The results can be used in automated map preparation, detection of network in trajectory planning for unmanned aerial vehicles. It also has wide applications in navigation, computer vision as a predictor-corrector algorithm for estimating the road position to simulate dynamic process of road extraction. Although an expert can label road pixels from a given satellite image but this operation is prone to errors. Therefore, an automated system is required to detect the road network in a high resolution satellite image in a robust manner. 相似文献
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A leaf area index is a key parameter reflecting the growth changes of vegetation and one of the most important canopy structural parameters for performing quantitative analyses of many ecological and climate models. Although using high-resolution satellite data and the radiative transfer model (RTM) can be used to generate high resolution LAI products, the RTM method has some problems because its temporal resolution is low, the input parameters are more appropriate for a physics model, and some parameters are difficult to obtain. Problems that urgently need to be solved include improving the temporal-spatial resolution for LAI products and localizing LAI products. To explore an applicable method for the high-resolution LAI products in a small basin and to improve the inversion accuracy, we propose an approach for GF-1 WFV LAI retrieval using MOD15A2 data and the measured LAI of the Poyang Lake watershed. Empirical models were used to retrieve high resolution LAI values, and the results show that these models are well designed for analyzing time-series satellite data. Good correlations were obtained between the NDVI of the GF-1 WFV data, the retrieved LAI values and the MODIS LAI data from samples acquired in both summer and winter. The exponential NDVI model obtained the best LAI value estimation results from the GF-1 WFV data (R2 = 0.697, RMSE = 1.100); the best synthetic validation of the RMSE is 0.883, close to the optimum model. Therefore, the retrieval results more fully reflect the growth process of the different features. This study proposed an upscale method for developing a high spatial resolution GF-1 satellite standard LAI products retrieval model using MODIS data. The proposed method will be helpful for efficiently improving the temporal-spatial resolution of LAI products to benefit the extraction of vegetation parameter information and dynamic land use monitoring. 相似文献
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Study of Various Image Fusion Approaches for Extraction and Classification of Infrastructural Growth
Estimation of infrastructural growth is the key issue for planning and resource management. In this regard it is highly required to have a proper database and documentation. Remotely sensed data and its processing techniques are most important parameter to achieve this goal. In developing countries, the planning and resource management is still dependent on traditional methods, but integration of satellite data of high resolution and of multiple spectral bands with appropriate processing techniques, makes it possible to get optimal result in limited fiscal resources. The merging of multi resolution sensor data can be the best option instead of using costly data for low budget planning and development. This study aims to analyze the potentials of image fusion of multispectral and panchromatic satellite data with high ground resolution images and evaluating their significance in infrastructural classification. While the accuracy assessment tests of classification result, suggest the appropriate classification techniques. The Relevance of image fusion in auto vectorization has also been discussed in this paper. 相似文献
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针对遥感图像的"时空矛盾",评述了当前解决这一问题最主要的方法即遥感时空信息融合的方法,包括基于变化模型的融合、基于重建模型的融合以及基于学习模型的融合。通过分析各个模型的研究现状,指出了每种模型方法的优劣,特别重点介绍了影响较大的自适应时空融合方法的理论以及对其的改进算法。同时本文总结了当前时空融合模型在长时间序列模拟以及大区域数据集生成等方面的实际应用的效果,以及分析了影响时空融合结果的主要因素。最后基于这些问题和影响因素提出了今后时空融合模型发展的目标和方向。 相似文献