共查询到20条相似文献，搜索用时 421 毫秒
1.
面向对象和规则的高分辨率影像分类研究 总被引：1，自引：0，他引：1
随着航天遥感技术的发展,遥感数据的空间分辨率、光谱分辨率和时间分辨率极大提高,高效解译并处理海量的、具有空间几何信息和纹理信息的地物高分辨率遥感影像数据已成为遥感领域研究的重点与难点。对此,本文提出一种面向对象和规则的遥感影像数据的分类提取方法,即通过发现和挖掘高分辨率影像丰富的光谱和空间特征知识,建立影像对象多层次网络分割分类结构,实现对遥感影像准确快速的地物分类和精度评价。以藏南地区WorldView-2影像数据为试验研究对象,采用面向对象和规则的影像分类方法进行验证试验,即综合采用均值方差法、最大面积法、精度比较法进行分析,选择3种最佳分割尺度建立多层次影像对象网络层次结构进行影像分类试验。结果表明,采用面向对象规则分类方法对高分辨率影像进行分类,能使高分辨率影像分类结果近似于目视判读的结果,分类精度更高。面向对象规则分类法的综合精度和Kappa系数分别为97.38%、0.967 3;与面向对象SVM法相比,分别高出6.23%、0.078;与面向对象KNN法相比,分别高出7.96%、0.099 6。建筑物的提取精度、用户精度分别比面向对象SVM法高出18.39%、3.98%,比面向对象KNN法高出21.27%、14.97%。 相似文献
2.
针对湿地的类型多样和光谱特征不确定性,在高分辨遥感影像上可人工目视判读,而自动化解译困难。文章在面向对象技术支持下,提出了多特征融合的高分辨率遥感数据湿地信息分层提取。该方法首先通过面向对象分割技术转象元为基元,实现光谱相似象元的聚类;然后分析湿地景观格局依存关系和不同类型湿地的提取难以程度,决定提取的先后顺序;再挖掘不同类型湿地的光谱、空间形态、空间分布和空间关系等多种属性特征;最后通过分层分类,由易到难,融入空间知识,逐层构建规则集,实现高分辨率遥感影像湿地信息自动监测。通过高空间分辨率Quickbird卫星数据对玛纳斯国家湿地公园区进行遥感监测。试验结果表明：该方法能够快速实现区域范围内湿地信息自动识别和快速提取,总体分类精度达到了87.5%,Kappa系数超过0.83,基本满足应用的需求,可为同行领域应用提供技术参考。 相似文献
3.
高标准农田建后遥感监测方法 总被引：1，自引：0，他引：1
高标准农田建后常会有违规利用情况存在,如何实现对高标准农田建后实时、精准的遥感监测成为土地整治部门亟待解决的问题。全国高标准农田监测面积大,监测精度要求高,迫切需要一套适应于全国范围推广的高标准农田自动监测方法。以广东省东莞地区为研究区,对比了面向对象和最大似然2种自动遥感分类监测方法,面向对象总体精度达到98. 684 7%,Kappa系数为0. 983 3;而最大似然分类方法总体精度则为78. 587 1%,Kappa系数为0. 718 0。研究表明面向对象分类方法能较好地满足高标准农田建后利用情况遥感监测工作的需求,此方法可以为全国高标准农田建成后的实时监管提供高效、精准的决策信息,为国家耕地保护、粮食安全工作提供技术支撑。 相似文献
4.
为了自动快速提取无证矿山图斑信息,首先利用面向对象的技术对遥感影像进行分类,获取包括植被、水体、道路、居民地及裸地等分类成果图;然后通过图像差值变化检测方法对变化图斑进行提取,得到面向对象分类的二值图。在此基础上,叠加已有的矿权资料,获得疑似无证矿山图斑信息。最后通过目视判读和野外验证的方法对提取的疑似无证矿山图斑进行筛选,最终确认无证矿山图斑。从本文的研究结果来看,结合变化检测的面向对象分类方法对目标图斑的提取具有一定的可行性. 相似文献
5.
面向对象标准最邻近分类法在地理国情监测中的应用 总被引：1，自引：0，他引：1
地理国情监测项目范围大,遥感影像分辨率高,信息提取精度要求高,人工解译任务繁重,急需利用自动解译技术来提高效率。面向对象的标准最邻近分类法可针对地表覆盖信息实现数据的自动快速提取,相比于人工分类方法所提取的结果,该方法具有较高的精度,并且可大幅度提高地理国情监测地表覆盖信息提取的生产效率。 相似文献
6.
7.
ADS80影像具有红、绿、蓝、近红外等多波段影像信息。本文以ADS80影像为数据源,采用面向对象的分类方法对遥感影像进行自动提取分类研究。研究表明,采用ADS80影像与面向对象分类相结合的方法,可充分发掘影像中的形状、纹理、结构等几何特征信息,显著提高影像的分割精度,使分类后的影像具有更丰富而准确的信息,在地理国情普查及监测中具有较高的应用价值。 相似文献
8.
针对高分一号遥感数据铁尾矿信息提取精度较低的问题,文中分析了铁尾矿高分遥感图像光谱、纹理及空间特征,构建了铁尾矿遥感光谱特征强化的数学模型RTI和IOT,建立了面向对象的铁尾矿高分遥感信息提取的技术流程。并以唐山典型矿山地区为研究对象,进行了铁尾矿遥感信息的提取实验和精度分析,验证了RTI和IOT强化数学模型在面向对象决策分类规则中的有效性,为铁尾矿资源的目标提取和自动监测提供了一种新的处理方法。 相似文献
9.
基于面向对象的黄土丘陵沟壑区梯田信息提取研究 总被引：1，自引：0，他引：1
研究区位于黄土丘陵沟壑区第二副区的彭阳县,以国产GF-2影像为数据源,首先按地形复杂度生态分区,选取4个典型试验区;其次应用多尺度分割和光谱差异分割相结合的方法,对试验区影像进行分割;然后重点基于面向对象分类方法,实现梯田信息的自动提取;最后采用参考对象一致性误差(OCE)分割评价准则,以目视解译结果为参考对象,对梯田提取结果进行精度评价。结果表明,基于面向对象分类,不同生态分区遥感影像在最优分割阈值时,梯田信息自动提取精度均达到65%以上,结合后期处理,可以高效、准确地从国产GF-2影像中提取复杂地貌区的梯田及空间分布等相关信息,为黄土丘陵沟壑区农业生产规划、水土流失防治提供基础数据,也提供了新的思路和合理的技术方法。 相似文献
10.
11.
基于eCognition的遥感图像面向对象分类方法研究 总被引：1，自引：0，他引：1
随着高分辨率遥感图像越来越普及,传统的面向像元的图像分类方法不能满足对高分辨率遥感图像区域分类的需求,高分辨率遥感图像对图像处理的软件与硬件都有了更高的要求,因此,出现了相较于面向像元有着更高精度更为合理的面向对象分类方法,也更加适用于高分辨率遥感影像。本文通过采用面向对象分类的基本方法,运用eCognition软件,以山东省胶州市地区遥感影像为例,进行多尺度分割和面向对象分类。并用ENVI做监督分类,基于目视解译精度评定,对不同方法作出分析评价。结果表明:面向对象分类方法精度更高,更具有可靠性。 相似文献
12.
Arpita Pankaj Pankaj Kumar Ajai Mishra 《Journal of the Indian Society of Remote Sensing》2012,40(4):725-734
Tons basin has the maximum share of glaciers, more than 50 glaciers, as well as glacierised area in Uttarakhand and Himachal Pradesh and the majority of the glaciers are of valley type. One of the important features of the glaciers of Tons valley is the presence of a thick mantle of supraglaciers moraine cover which can be attributed to the terrain characteristics, besides, the avalanche fed nature of the glaciers. The present study is the extraction of Glacio-geomorphological unit of Tons River basin based on the visual interpretation of remote sensing data. It was very much difficult in field, to extract all glacio-geomorphological units in glaciated area, but based on the remote sensing data, it becomes easy to identify. With the help of glacio-geomorphological map it has been found that four most important glaciers which fed the Tons River are Bandarpunch Glacier, Jaundar Bamak glacier, Jhajju Bamak and Tilku glacier. The tributaries of Tons River i.e. Harkidun Gad, Rupin Nadi and Supin Nadi are mainly fed by the mountain glaciers, valley glaciers and glacier lakes. The erosional terraces, glacio-fluvial terraces, open ??U?? shaped valleys, proglacial lake, lateral moraines, terminal moraines, palaeo-cirque and debris/talus cones are well developed in this glaciated regions. Glacio-geomorphic features are very much significant for palaeo-climatic reconstruction, showing variations, temporally and spatially. At the same time, these landforms, which are also altered by processes prevailing during interglacial period, helps in the geo-environment studies and glacier related problems like avalanches, global warming and cloudburst etc. 相似文献
13.
Liegang Xia Jiancheng Luo Weihong Wang Zhanfeng Shen 《Journal of the Indian Society of Remote Sensing》2014,42(3):505-515
This paper proposes an automatic framework for land cover classification. In majority of published work by various researchers so far, most of the methods need manually mark the label of land cover types. In the proposed framework, all the information, like land cover types and their features, is defined as prior knowledge achieved from land use maps, topographic data, texture data, vegetation’s growth cycle and field data. The land cover classification is treated as an automatically supervised learning procedure, which can be divided into automatic sample selection and fuzzy supervised classification. Once a series of features were extracted from multi-source datasets, spectral matching method is used to determine the degrees of membership of auto-selected pixels, which indicates the probability of the pixel to be distinguished as a specific land cover type. In order to make full use of this probability, a fuzzy support vector machine (SVM) classification method is used to handle samples with membership degrees. This method is applied to Landsat Thematic Mapper (TM) data of two areas located in Northern China. The automatic classification results are compared with visual interpretation. Experimental results show that the proposed method classifies the remote sensing data with a competitive and stable accuracy, and demonstrate that an objective land cover classification result is achievable by combining several advanced machine learning methods. 相似文献
14.
通过分析传统的遥感变化检测方法存在的问题,提出了面向对象的遥感变化检测方法。本文利用某地ETM+两个时相的遥感影像,将面向对象和传统变化检测方法进行定性定量的比较,从而得出面向对象的遥感变化检测方法的优势。该方法采用了基于相邻影像区域合并异质性最小的面向对象的多尺度分割方法和模糊分类的方法对变化检测图像进行处理,从而提高了变化检测结果的精度。最终得到较理想的实验分析结果。 相似文献
15.
沿海地区地表覆盖信息是全国地理国情普查的重要内容,遥感影像分类技术为沿海地区地表覆盖信息提供了一种重要方法。本文基于GF-1高分辨率遥感影像,建立了沿海地区地表覆盖分类系统,采用中国测绘科学研究院自主研发的面向对象GLC决策树分类方法和软件进行了地表覆盖分类。通过对某试验区进行分类试验,并结合该区地表覆盖标准分类图进行精度评价,验证了基于高分辨率影像,面向对象GLC决策树分类方法在沿海地区地表覆盖信息提取上的有效性及优越性,其总体分类精度和Kappa系数分别为87.201 8%、0.840 6,均高于SVM分类法。最后提出基于高分辨率遥感影像的沿海地区地表覆盖信息提取流程。 相似文献
16.
遥感技术因其较高的精确性和时效性已成为监测土地利用变化的重要手段。地理国情普查是一项非常重要的调查工程,起着为各级领导干部科学决策提供数据支持的作用。遥感影像解译是整个普查工作中的重要环节,而且工作量巨大。目前,地理国情普查的遥感影像解译环节主要采用人工解译和计算机自动解译相结合的方法,以提高效率。本文主要介绍一种面向对象分类的遥感影像自动解译方法,通过东莞市TM影像实验,总结该方法的解译特点,并介绍其在地理国情普查中的应用。 相似文献
17.
Praveen K. Thakur S. P. Aggarwal G. Arun Sahil Sood A. Senthil Kumar Sneh Mani D. P. Dobhal 《Journal of the Indian Society of Remote Sensing》2017,45(3):525-539
Snow physical properties, snow cover and glacier facies are important parameters which are used to quantify snowpack characteristics, glacier mass balance and seasonal snow and glacier melt. This study has been done using C-band synthetic aperture radar (SAR) data of Indian radar imaging satellite, radar imaging satellite-1 (RISAT)-1, to estimate the seasonal snow cover and retrieve snow physical properties (snow wetness and snow density), and glacier radar zones or facies classification in parts of North West Himalaya (NWH), India. Additional SAR data used are of Radarsat-2 (RS-2) satellite, which was used for glacier facies classification of Smudra Tapu glacier in Himachal Pradesh. RISAT-1 based snow cover area (SCA) mapping, snow wetness and snow density retrieval and glacier facies classification have been done for the first time in NWH region. SAR-based inversion models were used for finding out wet and dry snow dielectric constant, dry and wet SCA, snow wetness and snow density. RISAT-1 medium resolution scan-SAR mode (MRS) in HV polarization was used for first time in NWH for deriving time series of SCA maps in Beas and Bhagirathi river basins for years 2013–2014. The SAR-based inversion models were implemented separately for RISAT-1 quad pol. FRS2, for wet snow and dry snow permittivity retrieval. Masks for layover and shadow were considered in estimating final snow parameters. The overall accuracy in terms of R2 value comes out to be 0.74 for snow wetness and 0.72 for snow density based on the limited ground truth data for subset area of Manali sub-basin of Beas River up to Manali for winter of 2014. Accuracy for SCA was estimated to be 95 % when compared with optical remote sensing based SCA maps with error of ±10 %. The time series data of RISAT-1 MRS and hybrid data in RH/RV mode based decompositions were also used for glacier radar zones classification for Gangotri and Samudra Tapu glaciers. The various glaciers radar zones or facies such as debris covered glacier ice, clean or bare glacier ice radar zone, percolation/refreeze radar zone and wet snow, ice wall etc., were identified. The accuracy of classified maps was estimated using ground truth data collected during 2013 and 2014 glacier field work to Samudra Tapu and Gangotri glaciers and overall accuracy was found to be in range of 82–90 %. This information of various glacier radar zones can be utilized in marking firn line of glaciers, which can be helpful for glacier mass balance studies. 相似文献
18.
土地覆被作为地表自然和人工建造物的综合体，是开展土地科学相关研究的重要基础，在遥感大数据背景下，准确、快速、自动化进行土地覆被提取技术一直是遥感研究中的重点。本文基于eCognition软件，采用面向对象的多尺度分割法，综合考虑地物在遥感影像上的光谱、形状和纹理特征，建立多种地物提取规则。通过模糊函数、支持向量机（SVM）和阈值法对研究区的土地覆被进行分类提取，并与研究区的FROM-GLC10数据和土地利用变更数据进行了对比分析。结果表明：①研究区土地覆被分类的总体精度为97%，Kappa系数为0.96，分类精度较高；②基于10 m分辨率影像，综合使用形状、纹理、光谱信息对于道路的提取具有较好的效果，道路提取Kappa系数为0.84；③分类结果在面积和空间分布上都优于FROM-GLC10数据，与研究区实际土地变更数据保持较好的一致性。基于面向对象与规则的分类方法提取地物能够有效利用多种遥感影像特征，分类精度高，对于处理高分辨率遥感数据具有很好的优势。 相似文献
19.
目前土地卫片执法中对影像变化图斑的提取主要依靠作业人员对两时相高分辨率卫星遥感影像的目视解译,以确定土地利用变化发生的空间位置。图斑的正确与否完全依靠解译人员的目视判读经验,容易产生错误。通用的检测流程针对特定遥感影像数据可以得到较好的检测结果,但是面对大面积、特征多样、分辨率较高的城市遥感影像时,应用效果可能不佳。融合流程优化思维,整合现有成熟的遥感影像变化检测相关技术,利用数字城市建设中积累的大量高精度GIS数据,并结合地物形状特征指数和检测人员的作业经验,进行变化检测自动化研究,包括人机交互检测和批量自动检测两个主要流程,并应用于深圳市土地卫片执法中的土地利用变化图斑提取环节,可提高其自动化程度,有效降低时间和人力成本,及时发现并阻止土地违法利用行为。 相似文献
20.
Har Amrit Singh Sandhu Hemendra Singh Gusain Manoj Kumar Arora Arun Bawa 《Journal of the Indian Society of Remote Sensing》2018,46(11):1835-1840
Dokriani Glacier is regarded as one of the important glaciers of Bhagirathi River basin, which fed river Ganges. The length of the glacier is about 4.6 km, and snout elevation is about 4028 m m.s.l. The mass balance of this glacier was calculated using field-based measurements for few years during 1994 to 2000. However, due to remote and poor accessibility, the field-based measurements could not continue; thus, remote sensing-based methods become useful tool to estimate the long-term mass balance of the glacier. In this study, glacier mass balance has been determined using accumulation area ratio (AAR) method. Remote sensing data sets, e.g. Landsat TM, ETM?+?and OLI, have been used to estimate AAR for different years from 1994 to 2014. An attempt has also been made to develop a mathematical relationship between remote sensing-derived AAR and field-observed mass balance data of the glacier. Further, this relationship has been used to estimate mass balance of the glacier for different years using remote sensing-derived AAR. Estimated mass balance was validated from ground-observed mass balance for few years. The field-observed and remote sensing-derived mass balance data are compared and showed high correlation. It has been observed that AAR for the Dokriani Glacier varies from 0.64 to 0.71. Mass balance of the glacier was observed between ??15.54 cm and ??50.95 cm during the study period. The study highlights the application of remote sensing in mass balance study of the glaciers and impact of climate change in glaciers of Central Indian Himalaya. 相似文献