共查询到20条相似文献，搜索用时 93 毫秒
1.
基于区间值模糊C-均值算法的土地覆盖分类 总被引：1，自引：0，他引：1
用区间值数据描述聚类原型特征更符合遥感数据的模糊性特点,即传感器获取的地物反射光谱的不确定性和不均匀性在影像上的反映.本文以遥感影像数据为基础构建了区间值数据模型,并提出一种区间最大相异度量方法,进而进行基于区间值数据的模糊C-均值聚类.利用珠三角地区SPOT5卫星和青海玉树附近的TM影像数据进行基于区间值模糊C-均值算法的土地覆盖分类实验.结果表明区间值数据的模糊C-均值算法兼顾了模糊聚类的泛函特性和地物反射光谱的条带特点,从而可以明显改善聚类效果,尤其可以降低"同物异谱"现象对聚类结果的不利影响,而区间最大相异度量可实现基于多波段遥感影像构建的区间向量的最大可分离度,有效抑制类间光谱混叠造成的错分现象,进一步改善聚类效果,最终结果明显优于传统的模糊C-均值聚类方法. 相似文献
2.
基于面向对象的无监督分类的遥感影像自动分类方法 总被引：3，自引：0，他引：3
为了实现无任何先验知识的高分辨率遥感数据的自动分类,并进一步提高自动分类精度和效率,提出了一种基于面向对象的无监督分类方法(Object Oriented Unsupervised Classification).具体步骤如下:首先对遥感影像进行分割,得到一系列空间上相邻、同质性较好的分割单元,然后对分割单元进行特征提取,得到分割单元的对象特征(光谱特征、纹理特征等多特征信息),进而对分割单元进行基于对象特征马氏距离聚类.最后,通过分类后处理(类别合并、错分类别调整等)得到最终的分类结果.通过实验表明:本文提出的方法不仅能够利用影像中更多的特征信息进行聚类而且还可以有效地减少聚类对象的个数,从而使自动分类的精度和效率都得到较大的提升. 相似文献
3.
一种基于生物群集智能优化的遥感分类方法 总被引：3，自引：0，他引：3
提出了一种基于生物群集智能(swarm intelligence-based)的遥感影像分类新方法. 智能式分类是遥感研究的热点和趋势. 设计出一种新的实数制编码的粒子群遥感影像分类器(PSO-Miner), 在分类规则提取时, 粒子能自动寻找各个波段的最优分割点. 并且该方法所提取的分类规则毋需通过数学公式来表达, 能更方便和准确地描述自然界中的复杂关系, 比数学公式更容易让人理解. 将该方法应用于番禺地区的遥感影像, 取得了较好的分类结果. 并与See5.0决策树方法进行了对比研究, 实验结果表明, 基于群集智能方法的分类精度比决策树方法的精度更高. 相似文献
4.
《中国科学:地球科学》2016,(9)
选取适当生态地理边界对遥感影像进行分割,降低分区单元内土地覆盖复杂程度,可有效提高遥感土地覆盖分类精度.本研究将气象、高程、土壤等环境数据与季节性植被遥感信息相结合,利用典范对应分析(CCA)和k均值聚类等进行生态地理分区的划分,旨在提出适用于区域遥感地表分类的生态地理分区方案.以我国为例的研究结果表明,季节性植被遥感信息与CCA相结合,能够有效筛选出区域生物地理格局主导环境因子,可将这些主导因子作为生态地理分区的区划指标.本研究中,温度要素是我国生物地理格局的主导驱动力,水分要素次之.以MODIS MCDl2C1(2005年)和GlobCover(2004~2006年)全球土地覆盖分类产品来评价生态地理分区内土地覆盖复杂程度,结果表明,本研究的生态地理分区在土地覆盖类型均数、主要土地覆盖类型面积比例以及主、次要土地覆盖类型面积比例之和等方面,均优于已有研究结果,且主、次要土地覆盖类型的植物物种和性状特征差异比较明显,表明利用表征植被季节特征的环境主导因子进行生态地理区划,可以有效降低生态地理分区内地表覆盖复杂程度,更利于地表覆盖遥感分类. 相似文献
5.
6.
7.
8.
基于乌兰浩特地震台监测区域的遥感影像，使用最大似然分类算法对影像进行6种地表物的分类，采用辐射传输方程算法进行地表温度的定量反演，根据影像提取的植被覆盖度，总结研究区域地表温度异常、植被覆盖度与地震间的相关性。 相似文献
9.
10.
遥感影像空间分辨率变化对湖泊水体提取精度的影响 总被引：1，自引：1，他引：0
湖泊面积是表征湖泊水情变化的重要指示因子,如何从不同空间分辨率遥感数据中获取客观准确的水面信息,是当前遥感应用研究中的难点问题.本文以鄱阳湖为例,通过选用丰水期和枯水期代表性Landsat ETM+遥感影像,采用最邻近法(NN)和像元聚合法(PA)两种重采样方法,分别获取分辨率逐渐降低的不同分辨率的影像数据,结合归一化差异水指数法研究水域面积随遥感影像分辨率降低的变化趋势及其误差变化特征,同时深入分析不同影响因素对水体提取精度的差异.研究结果表明:(1)空间分辨率是影响鄱阳湖水体提取精度的重要因素之一,随着遥感影像空间分辨率的降低,提取水域面积的精度相对30 m分辨率时呈逐渐降低的趋势,但整体精度较高,最低精度在67.64%以上;(2)NN重采样方法对遥感影像波段亮度值的均值影响不大,但PA重采样后影像的均值和标准差随分辨率逐渐降低且变化更有规律;(3)水体阈值在PA重采样后变化较大,NN重采样后变化较小,因而采用30 m分辨率时获取的阈值提取PA重采样后鄱阳湖水体误差较大,提取NN重采样后的湖泊水体误差较小.本研究结果对于全球变化影响下湖泊水体信息遥感精确提取具有重要的参考价值. 相似文献
11.
Land cover classification of remote sensing imagery based on interval-valued data fuzzy c-means algorithm 总被引：1，自引：0，他引：1
There is a certain degree of ambiguity associated with remote sensing as a means of performing earth observations.Using interval-valued data to describe clustering prototype features may be more suitable for handling the fuzzy nature of remote sensing data,which is caused by the uncertainty and heterogeneity in the surface spectral reflectance of ground objects.After constructing a multi-spectral interval-valued model of source data and defining a distance measure to achieve the maximum dissimilarity between intervals,an interval-valued fuzzy c-means(FCM)clustering algorithm that considers both the functional characteristics of fuzzy clustering algorithms and the interregional features of ground object spectral reflectance was applied in this study.Such a process can significantly improve the clustering effect;specifically,the process can reduce the synonym spectrum phenomenon and the misclassification caused by the overlap of spectral features between classes of clustering results.Clustering analysis experiments aimed at land cover classification using remote sensing imagery from the SPOT-5 satellite sensor for the Pearl River Delta region,China,and the TM sensor for Yushu,Qinghai,China,were conducted,as well as experiments involving the conventional FCM algorithm,the results of which were used for comparative analysis.Next,a supervised classification method was used to validate the clustering results.The final results indicate that the proposed interval-valued FCM clustering is more effective than the conventional FCM clustering method for land cover classification using multi-spectral remote sensing imagery. 相似文献
12.
It is well known that there is a degree of fuzzy uncertainty in land cover classification using remote sensing (RS) images. In this article, we propose a novel fuzzy uncertainty modeling algorithm for representing the features of land cover patterns, and present an adaptive interval type-2 fuzzy clustering method. The proposed fuzzy uncertainty modeling method is performed in two main phases. First, the segmentation units of the input multi-spectral RS image data are subjected to objectbased interval-valued symbolic modeling. As a result, features for each land cover type are represented in the form of an intervalvalued symbolic vector, which describes the intra-class uncertainty better than the source data and improves the separability between different classes. Second, interval type-2 fuzzy sets are generated for each cluster based on the distance metric of the interval-valued vectors. This step characterizes the inter-class high-order fuzzy uncertainty and improves the classification accuracy. To demonstrate the advantages and effectiveness of the proposed approach, extensive experiments are conducted on two multispectral RS image datasets from regions with complex land cover characteristics, and the results are compared with those given by well-known fuzzy and conventional clustering algorithms. 相似文献
13.
Carsten Montzka Morton Canty Ralf Kunkel Gunter Menz Harry Vereecken Frank Wendland 《Journal of Hydrology》2008,353(3-4):322-334
Hydrological modelling of mesoscale catchments is often adversely affected by a lack of adequate information about specific site conditions. In particular, digital land cover data are available from data sets which were acquired on a European or a national scale. These data sets do not only exhibit a restricted spatial resolution but also a differentiation of crops and impervious areas which is not appropriate to the needs of mesoscale hydrological models. In this paper, the impact of remote sensing data on the reliability of a water balance model is investigated and compared to model results determined on the basis of CORINE (Coordination of Information on the Environment) Land Cover as a reference. The aim is to quantify the improved model performance achieved by an enhanced land cover representation and corresponding model modifications. Making use of medium resolution satellite imagery from SPOT, LANDSAT ETM+ and ASTER, detailed information on land cover, especially agricultural crops and impervious surfaces, was extracted over a 5-year period (2000–2004). Crop-specific evapotranspiration coefficients were derived by using remote sensing data to replace grass reference evapotranspiration necessitated by the use of CORINE land cover for rural areas. For regions classified as settlement or industrial areas, degrees of imperviousness were derived. The data were incorporated into the hydrological model GROWA (large-scale water balance model), which uses an empirical approach combining distributed meteorological data with distributed site parameters to calculate the annual runoff components. Using satellite imagery in combination with runoff data from gauging stations for the years 2000–2004, the actual evapotranspiration calculation in GROWA was methodologically extended by including empirical crop coefficients for actual evapotranspiration calculations. While GROWA originally treated agricultural areas as homogeneous, now a consideration and differentiation of the main crops is possible. The accuracy was determined by runoff measurements from gauging stations. Differences in water balances resulting from the use of remote sensing data as opposed to CORINE were analysed in this study using a representative subcatchment. Resulting Nash–Sutcliff model efficiencies improved from 0.372 to 0.775 and indicate that the enhanced model can produce thematically more accurate and spatially more detailed local water balances. However, the proposed model enhancements by satellite imagery have not exhausted the full potential of water balance modelling, for which a higher temporal resolution is required. 相似文献
14.
This paper puts together some techniques that have been previously developed by the authors, but separately, relative to fuzzy
classification within a remote sensing setting. Considering that each image can be represented as a graph that defines proximity
between pixels, certain distances between the characteristic of contiguous pixels are defined on such a graph, so a segmentation
of the image into homogeneous regions can be produced by means of a particular algorithm. Such a segmentation can be then
introduced as information, previously to any classification procedure, with an expected significative improvement. In particular,
we consider specific measures in order to quantify such an improvement. This approach is being illustrated with its application
into a particular land surface problem. 相似文献
15.
Spatially distributed hydrological models require information on the land cover pattern, as it directly influences the generation of run‐off. However, it is not clear which detail of land cover information is suitable for simulating the catchment hydrology. A better understanding of the relationship between the land cover detail and the hydrological processes is therefore required as it would enhance a successful application of the hydrological model. This study investigates the relevance of accurate information about the crop types in the catchment for the simulation of run‐off, baseflow and evapotranspiration. Results reveal that adding knowledge about the crop type in the model simulation is redundant when area‐averaged water flux predictions are intended. On the contrary, when a spatial distribution of water flux predictions is desired, it is meaningful to increase the land cover detail because an increased heterogeneity in the land cover map induces an increased heterogeneity in the hydrological response and locally reduces the uncertainty in the model prediction up to 50%. To assess the land cover uncertainty and to locate the regions for which the reduction in prediction uncertainty is the highest, the thematic uncertainty map (constructed through fuzzy logic) is shown to be a useful tool. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
16.
Improvement of ecological geographic regionalization based on remote sensing and canonical correspondence analysis: A case study in China 总被引：1，自引：0，他引：1
JiaXin Jin Ying Wang Hong Jiang Yan Kong XueHe Lu XiuYing Zhang 《中国科学:地球科学(英文版)》2016,59(9):1745-1753
Ecological geographic regions, also called eco-regions, can be used to divide a remotely sensed image, which is helpful for reducing the complexity of land cover types within eco-regions and for improving the classification accuracy of land cover. In this case study in China, we improved a method of ecological geographic regionalization that is more suitable for remote sensing mapping of regional land cover, and we obtained new eco-regions. The canonical correspondence analysis (CCA) and k-means clustering were adopted in the ecological geographic regionalization using both seasonal remotely-sensed vegetation information and environmental data including climate, elevation and soil features. Our results show that the combination of seasonal vegetation information and the CCA performed well in the selection of the dominant environmental factor of the biogeographic pattern, and it can be used as regionalization indicators of eco-regions. We found that thermal factors are the most important driving forces of the biogeographic pattern in China, which followed by moisture factors. Two global land cover products (MODIS MCD12C1 and GlobCover) were used to assess our eco-regions. The results show that our eco-regions performed better than that of a previous study regarding the complexity of land cover types, such as in the number of types and the proportional area of the major/secondary type. These results indicate that the method of ecological geographic regionalization, which is based on environmental factors associated with seasonal vegetation features, is effective for reducing the regional complexity of land cover. 相似文献
17.
Bo Zhong Peng Ma AiHua Nie AiXia Yang YanJuan Yao WenBo Lü Hang Zhang QinHuo Liu 《中国科学:地球科学(英文版)》2014,57(8):1790-1799
It is very difficult to have remote sensing data with both high spatial resolution and high temporal frequency; thus, two categories of land-use mapping methodology have been developed separately for coarser resolution and finer resolution data. The first category uses time series of data to retrieve the variation of land surface for classification, which are usually used for coarser resolution data with high temporal frequency. The second category uses fine spatial resolution data to classify different land surface. With the launch of Chinese satellite constellation HJ-1in 2008, four 30 m spatial resolution CCDs with about 360 km coverage for each one onboard two satellites made a revisit period of two days, which brought a new type of data with both high spatial resolution and high temporal frequency. Therefore, by taking the spatiotemporal advantage of HJ-1/CCD data we propose a new method for finer resolution land cover mapping using the time series HJ-1/CCD data, which can greatly improve the land cover mapping accuracy. In our two study areas, the very high resolution remote sensing data within Google Earth are used to validate the land cover mapping results, which shows a very high mapping accuracy of 95.76% and 83.78% and a high Kappa coefficient of 0.9423 and 0.8165 in the Dahuofang area of Liaoning Province and the Heiquan area of Gansu Province respectively. 相似文献
18.
S. Wang G. H. Huang H. W. Lu Y. P. Li 《Stochastic Environmental Research and Risk Assessment (SERRA)》2011,25(2):211-222
In this study, an interval-valued fuzzy linear programming with infinite α-cuts (IVFLP-I) method is developed for municipal
solid waste (MSW) management under uncertainty. IVFLP-I can not only tackle uncertainties expressed as intervals and interval-valued
fuzzy sets, but also take all fuzzy information into account by discretizing infinite α-cut levels to the interval-valued
fuzzy membership functions. Through adoption of the interval-valued fuzzy sets, IVFLP-I can directly communicate information
of waste managers’ confidence levels over various subjective judgments into the optimization process. Compared to the existing
methods in which only finite α-cut levels exist, IVFLP-I would have enhanced the robustness in the optimization efforts. A
MSW management problem is studied to illustrate the applicability of the proposed method. Four groups of optimal solutions
can be obtained through assigning different intervals of α-cut levels. The results indicate that wider intervals of α-cut
levels could lead to a lower risk level of constraint violation associated with a higher system cost; contrarily, narrower
intervals of α-cut levels could lead to a lower cost with a higher risk of violating the constraints. The solutions under
different intervals of α-cut levels can support in-depth analyses of tradeoffs between system costs and constraint-violation
risks. 相似文献
19.
LuanYun Hu YanLei Chen Yue Xu YuanYuan Zhao Le Yu Jie Wang Peng Gong 《中国科学:地球科学(英文版)》2014,57(10):2293-2304
Remote sensing based land cover mapping at large scale is time consuming when using either supervised or unsupervised classification approaches. This article used a fast clustering method—Clustering by Eigen Space Transformation(CBEST) to produce a land cover map for China. Firstly, 508 Landsat TM scenes were collected and processed. Then, TM images were clustered by combining CBEST and K-means in each pre-defined ecological zone(50 in total for China). Finally, the obtained clusters were visually interpreted as land cover types to complete a land cover map. Accuracy evaluation using 2159 test samples indicates an overall accuracy of 71.7% and a Kappa coefficient of 0.64. Comparisons with two global land cover products(i.e., Finer Resolution Observation and Monitoring of Global Land Cover(FROM-GLC) and GlobCover 2009) also indicate that our land cover result using CBEST is superior in both land cover area estimation and visual effect for different land cover types. 相似文献
20.
IINTRODUCTIONLanduse/coverisoneofthemostimportalfactorseffectingsoilandwaterloss.Researchonlanduse/coverandwaterandsoillosswithremotesensinghasbeendonemuchinthepast.Butremotelysensedimageryonlycarriestheinstantaneousandtwo-dimensionalinformationofitsprototypegeographicobjects(ChenandZhao,1990).Thereforemathematicalandphysicalprocessingonremotelysensedimageoftenproduceindefiniteandunreliableresult.Inordertoimprovetheprecisionofclassification,otherdatasetssuchastopographicmaps,thematicmaps… 相似文献