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地图比例尺与遥感影像分辨率的关系探讨 总被引：2，自引：0，他引：2
探讨地图比例尺与遥感影像分辨率的关系,为特定比例尺制图选择适宜分辨率的遥感影像在遥感影像制图中极为重要。本文分析了人眼分辨率和比例尺精度、地图比例尺和影像分辨率之间的关系,以30 m分辨率的landsat5遥感影像、2.1 m分辨率的ZY-3遥感影像及0.5 m分辨率的Word View-2遥感影像进行实验,探讨了不同人眼分辨率下的遥感影像成图质量。得到了1∶M比例尺制图时的遥感影像分辨率的选择范围为(1×10~(-4)M,5×10~(-4)M),最佳遥感影像分辨率为2.5×10~(-4)M的结论,并用已有应用实例对其可靠性进行了检验,进而为我国基本比例尺制图遥感影像的选择提供了依据。 相似文献
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《测绘与空间地理信息》2020,(8)
立足于某省域范围内高分辨率卫星遥感影像制作过程,提出了一套针对卫星遥感影像预处理方案,目的在于解决不同条带、不同时相卫星遥感影像在省域范围内基础数据生产中的匀光、匀色、雾气去除和噪声消除等问题,提高影像数据质量,为影像后期制图和数据深层次应用提供技术支撑。 相似文献
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自20世纪90年代末期,高分辨率遥感卫星在民用和商业领域取得了突破性发展。亚米级超高分辨率遥感卫星影像数据已在城市测绘、规划与管理领域取得广泛应用。本文结合笔者多年从事城市遥感工作的实践,总结了高分辨率卫星遥感技术在城市规划管理领域从日常工作、专题信息获取到规划成果表达等方面的应用。 相似文献
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刘丽 《测绘与空间地理信息》2013,36(7):157-159,164
随着地球空间信息科学技术的飞速发展,高分辨率卫星遥感技术逐渐成为主流的对地观测手段之一。其生产的高分辨率遥感影像具有数据获取迅速、成本低、不受地域限制等诸多优点,广泛应用于国土、石油、电力、林业等行业部门。但由于其出现年代较新、数据量庞大、分辨率高,高分辨率遥感影像的数据处理与应用尚无完整的理论和方案指导,导致其在电力等行业的应用长期处于探索阶段。本文针对高分辨率遥感影像的关键处理难点,结合电力工程实际需求,提出了一整套数据处理及应用方案,为高分辨率遥感影像数据处理及其电力工程应用提供了技术支持和实践经验。 相似文献
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正异源高分辨率卫星影像匹配是高分辨率卫星影像处理的技术关键,也是实现三维重建、信息提取、变化监测等应用研究工作的技术基础。研究表明在地面覆盖相同的情况下,随着空间分辨率的提高,卫星影像数据量急剧增加,并由此产生了几何噪声增大、阴影变化影响、局部形变加剧、纹理相似性降低等异源高分辨率影像特有的问题。传统同(异)源遥感影像匹配方法多数着眼于低、 相似文献
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近年来,高分辨率卫星遥感影像因具有地物纹理信息丰富、光谱波段多、重访时间短等特征,在自然资源动态变化监测等对地观测应用方面已突显出越来越大的优势。本文主要研究基于多源的高分辨率卫星遥感影像的区域网平差方法,对比影像精度,以提高卫星遥感影像在实际生产中的应用效果。 相似文献
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杜慧 《测绘与空间地理信息》2019,42(5)
我国第一颗自主研制的吉林一号(Jilin-1)高分辨率商业光学遥感卫星,其空间多光谱分辨率为2.88 m分辨率和全色分辨率为0.72 m。针对吉林一号卫星影像成像的方式,采用合适的遥感影像融合算法,能够增强多光谱影像的空间质量,提高影像应用的层次。本文尝试CN融合、Brovey融合、Gram-Schmidt融合、NearestNeighbor Diffusion等4种新的高保真算法对吉林一号卫星影像进行融合实验,并对融合后多光谱影像的质量进行定性分析与定量评价。结果表明:4种融合方法对影像空间信息和光谱信息都具有较高的保真度,而基于Nearest-Neighbor Diffusion方法融合产生的影像在增强了高分辨率空间纹理细节的同时,光谱信息失真度最小,更适合于吉林一号影像的融合。本结论对利用吉林一号遥感数据开展定量研究具有重要意义。 相似文献
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With the high deforestation rates of global forest covers during the past decades, there is an ever-increasing need to monitor forest covers at both fine spatial and temporal resolutions. Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat series images have been used commonly for satellite-derived forest cover mapping. However, the spatial resolution of MODIS images and the temporal resolution of Landsat images are too coarse to observe forest cover at both fine spatial and temporal resolutions. In this paper, a novel multiscale spectral-spatial-temporal superresolution mapping (MSSTSRM) approach is proposed to update Landsat-based forest maps by integrating current MODIS images with the previous forest maps generated from Landsat image. Both the 240 m MODIS bands and 480 m MODIS bands were used as inputs of the spectral energy function of the MSSTSRM model. The principle of maximal spatial dependence was used as the spatial energy function to make the updated forest map spatially smooth. The temporal energy function was based on a multiscale spatial-temporal dependence model, and considers the land cover changes between the previous and current time. The novel MSSTSRM model was able to update Landsat-based forest maps more accurately, in terms of both visual and quantitative evaluation, than traditional pixel-based classification and the latest sub-pixel based super-resolution mapping methods The results demonstrate the great efficiency and potential of MSSTSRM for updating fine temporal resolution Landsat-based forest maps using MODIS images. 相似文献
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对月球探测任务、月球遥感制图技术与产品进行综述。从1958年开始,全世界已开展126次(其中70次成功)月球探测工程任务,其中月球遥感制图是其必需的基础性工作。由于月球环境的特殊性,其遥感制图技术与对地观测制图相比具有很大的挑战和更大的难度。目前,中国嫦娥二号轨道器获取的7 m分辨率立体影像是覆盖全月球分辨率最高的立体影像数据,美国月球侦察轨道器LRO任务的激光雷达高度计LOLA数据是精度和密度最高的激光测高数据,LRO NAC影像的分辨率最高(0.5—2 m)但未覆盖全球。在各个探测任务中,基于月球遥感数据和摄影测量技术,已经制作了大量的全球及区域的影像拼图、正射影像图和数字高程模型等制图产品。对月球遥感制图技术发展进行展望,探讨了利用国际多探测任务数据建立新一代控制网和进行精细制图的必要性及技术思路。 相似文献
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Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images 总被引：1，自引：0，他引：1
Juan P. Ardila Valentyn A. Tolpekin Wietske Bijker Alfred Stein 《ISPRS Journal of Photogrammetry and Remote Sensing》2011,66(6):762-775
Identification of tree crowns from remote sensing requires detailed spectral information and submeter spatial resolution imagery. Traditional pixel-based classification techniques do not fully exploit the spatial and spectral characteristics of remote sensing datasets. We propose a contextual and probabilistic method for detection of tree crowns in urban areas using a Markov random field based super resolution mapping (SRM) approach in very high resolution images. Our method defines an objective energy function in terms of the conditional probabilities of panchromatic and multispectral images and it locally optimizes the labeling of tree crown pixels. Energy and model parameter values are estimated from multiple implementations of SRM in tuning areas and the method is applied in QuickBird images to produce a 0.6 m tree crown map in a city of The Netherlands. The SRM output shows an identification rate of 66% and commission and omission errors in small trees and shrub areas. The method outperforms tree crown identification results obtained with maximum likelihood, support vector machines and SRM at nominal resolution (2.4 m) approaches. 相似文献
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结合遥感数据与地统计学方法的海岸线超分辨率制图 总被引：1，自引：0，他引：1
使用黄河三角洲海岸Landsat卫星遥感数据,基于研究区域低分辨率6波段的海陆类型软分类结果及其变差函数,以高分辨率8波段的指示变差函数为精细尺度先验信息模型,采用数据探索性分析、协同指示克里格和序贯指示协同模拟技术,生成海陆类型发生概率模拟图像,通过等值线法提取海岸线空间分布特征。实验表明,基于地统计学方法的超分辨率制图技术在低分辨率遥感数据中融合高分辨率空间结构先验模型,可以较好表达精细尺度上的海岸线空间分布特征,同时保持原始数据的海陆类型组分信息及其空间结构特征。地统计学方法集成多尺度乃至多源空间信息的潜力通过海岸线超分辨率制图形式得到展示。 相似文献
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Downscaling has an important role to play in remote sensing. It allows prediction at a finer spatial resolution than that of the input imagery, based on either (i) assumptions or prior knowledge about the character of the target spatial variation coupled with spatial optimisation, (ii) spatial prediction through interpolation or (iii) direct information on the relation between spatial resolutions in the form of a regression model. Two classes of goal can be distinguished based on whether continua are predicted (through downscaling or area-to-point prediction) or categories are predicted (super-resolution mapping), in both cases from continuous input data. This paper reviews a range of techniques for both goals, focusing on area-to-point kriging and downscaling cokriging in the former case and spatial optimisation techniques and multiple point geostatistics in the latter case. Several issues are discussed including the information content of training data, including training images, the need for model-based uncertainty information to accompany downscaling predictions, and the fundamental limits on the representativeness of downscaling predictions. The paper ends with a look towards the grand challenge of downscaling in the context of time-series image stacks. The challenge here is to use all the available information to produce a downscaled series of images that is coherent between images and, thus, which helps to distinguish real changes (signal) from noise. 相似文献
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Trylee Nyasha Matongera Onisimo Mutanga Timothy Dube Romano Trent Lottering 《国际地球制图》2018,33(3):209-224
Bracken fern is one of the major invasive plants distributed all over the world currently threatening socio-economic and ecological systems due to its ability to swiftly colonize landscapes. The study aimed at reviewing the progress and challenges in detecting and mapping of bracken fern weeds using different remote sensing techniques. Evidence from literature have revealed that traditional methods such as field surveys and modelling have been insufficient in detecting and mapping the spatial distribution of bracken fern at a regional scale. The applications of medium spatial resolution sensors have been constrained by their limited spatial, spectral and radiometric capabilities in detecting and mapping bracken fern. On the other hand, the availability of most of these data-sets free of charge, large swath width and their high temporal resolution have significantly improved remote sensing of bracken fern. The use of commercial satellite data with high resolution have also proven useful in providing fine spectral and spatial resolution capabilities that are primarily essential to offer precise and reliable data on the spatial distribution of invasive species. However, the application of these data-sets is largely restricted to smaller areas, due to high costs and huge data volumes. Studies on bracken fern classification have extensively adopted traditional classification methods such as supervised maximum likelihood classifier. In studies where traditional methods performed poorly, the combination of soft classifiers such as super resolution analysis and traditional methods of classification have shown an improvement in bracken fern classification. Finally, since high spatial resolution sensors are expensive to acquire and have small swath width, the current study recommends that future research can also consider investigating the utility of the freely available recently launched sensors with a global footprint that has the potential to provide invaluable information for repeated measurement of invasive species over time and space. 相似文献
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Until recently, land surveys and digital interpretation of remotely sensed imagery have been used to generate land use inventories. These techniques however, are often cumbersome and costly, allocating large amounts of technical and temporal costs. The technological advances of web 2.0 have brought a wide array of technological achievements, stimulating the participatory role in collaborative and crowd sourced mapping products. This has been fostered by GPS-enabled devices, and accessible tools that enable visual interpretation of high resolution satellite images/air photos provided in collaborative mapping projects. Such technologies offer an integrative approach to geography by means of promoting public participation and allowing accurate assessment and classification of land use as well as geographical features. OpenStreetMap (OSM) has supported the evolution of such techniques, contributing to the existence of a large inventory of spatial land use information. This paper explores the introduction of this novel participatory phenomenon for land use classification in Europe's metropolitan regions. We adopt a positivistic approach to assess comparatively the accuracy of these contributions of OSM for land use classifications in seven large European metropolitan regions. Thematic accuracy and degree of completeness of OSM data was compared to available Global Monitoring for Environment and Security Urban Atlas (GMESUA) datasets for the chosen metropolises. We further extend our findings of land use within a novel framework for geography, justifying that volunteered geographic information (VGI) sources are of great benefit for land use mapping depending on location and degree of VGI dynamism and offer a great alternative to traditional mapping techniques for metropolitan regions throughout Europe. Evaluation of several land use types at the local level suggests that a number of OSM classes (such as anthropogenic land use, agricultural and some natural environment classes) are viable alternatives for land use classification. These classes are highly accurate and can be integrated into planning decisions for stakeholders and policymakers. 相似文献
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Landsat8和MODIS融合构建高时空分辨率数据识别秋粮作物 总被引：2，自引：0，他引：2
本文利用Wu等人提出的遥感数据时空融合方法 STDFA(Spatial Temporal Data Fusion Approach)以Landsat 8和MODIS为数据源构建高时间、空间分辨率的遥感影像数据。以此为基础,构建15种30 m分辨率分类数据集,然后利用支持向量机SVM(Support Vector Machine)进行秋粮作物识别,验证不同维度分类数据集进行秋粮作物识别的适用性。实验结果显示,不同分类数据集的秋粮作物分类结果均达到了较高的识别精度。综合各项精度指标分析,Red+Phenology数据组合对秋粮识别效果最好,水稻识别的制图精度和用户精度分别达到91.76%和82.49%,玉米识别的制图精度和用户精度分别达到85.80%和74.97%,水稻和玉米识别的总体精度达到86.90%。 相似文献
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Mapping and monitoring changes of geomorphological features over time are important for understanding fluvial process and effects of its controlling factors. Using high spatial resolution multispectral images has become common practice in the mapping as these images become widely available. Traditional pixel-based classification relies on statistical characteristics of single pixels and performs poorly in detailed mapping using high resolution multispectral images. In this work, we developed a hybrid method that detects and maps channel bars, one of the most important geomorphological features, from high resolution multispectral aerial imagery. This study focuses on the Big River which drains the Ozarks Plateaus region in southeast Missouri and the Old Lead Belt Mining District which was one of the largest producers of lead worldwide in the early and middle 1900s. Mapping and monitoring channel bars in the Big River is essential for evaluating the fate of contaminated mining sediment released to the Big River. The dataset in this study is 1 m spatial resolution and is composed of four bands: Red (Band 3), Green (Band 2), Blue (Band 1) and Near-Infrared (Band 4). The proposed hybrid method takes into account both spectral and spatial characteristics of single pixels, those of their surrounding contextual pixels and spatial relationships of objects. We evaluated its performance by comparing it with two traditional pixel-based classifications including Maximum Likelihood (MLC) and Support Vector Machine (SVM). The findings indicate that derived characteristics from segmentation and human knowledge can highly improve the accuracy of extraction and our proposed method was successful in extracting channel bars from high spatial resolution images. 相似文献
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The mixed pixel problem affects the extraction of land cover information from remotely sensed images. Super-resolution mapping (SRM) can produce land cover maps with a finer spatial resolution than the remotely sensed images, and reduce the mixed pixel problem to some extent. Traditional SRMs solely adopt a single coarse-resolution image as input. Uncertainty always exists in resultant fine-resolution land cover maps, due to the lack of information about detailed land cover spatial patterns. The development of remote sensing technology has enabled the storage of a great amount of fine spatial resolution remotely sensed images. These data can provide fine-resolution land cover spatial information and are promising in reducing the SRM uncertainty. This paper presents a spatial–temporal Hopfield neural network (STHNN) based SRM, by employing both a current coarse-resolution image and a previous fine-resolution land cover map as input. STHNN considers the spatial information, as well as the temporal information of sub-pixel pairs by distinguishing the unchanged, decreased and increased land cover fractions in each coarse-resolution pixel, and uses different rules in labeling these sub-pixels. The proposed STHNN method was tested using synthetic images with different class fraction errors and real Landsat images, by comparing with pixel-based classification method and several popular SRM methods including pixel-swapping algorithm, Hopfield neural network based method and sub-pixel land cover change mapping method. Results show that STHNN outperforms pixel-based classification method, pixel-swapping algorithm and Hopfield neural network based model in most cases. The weight parameters of different STHNN spatial constraints, temporal constraints and fraction constraint have important functions in the STHNN performance. The heterogeneity degree of the previous map and the fraction images errors affect the STHNN accuracy, and can be served as guidances of selecting the optimal STHNN weight parameters. 相似文献