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1.
Mapping of vegetation in mountain areas based on remote sensing is obstructed by atmospheric and topographic distortions. A variety of atmospheric and topographic correction methods has been proposed to minimize atmospheric and topographic effects and should in principle lead to a better land cover classification. Only a limited number of atmospheric and topographic combinations has been tested and the effect on class accuracy and on different illumination conditions is not yet researched extensively. The purpose of this study was to evaluate the effect of coupled correction methods on land cover classification accuracy. Therefore, all combinations of three atmospheric (no atmospheric correction, dark object subtraction and correction based on transmittance functions) and five topographic corrections (no topographic correction, band ratioing, cosine correction, pixel-based Minnaert and pixel-based C-correction) were applied on two acquisitions (2009 and 2010) of a Landsat image in the Romanian Carpathian mountains. The accuracies of the fifteen resulting land cover maps were evaluated statistically based on two validation sets: a random validation set and a validation subset containing pixels present in the difference area between the uncorrected classification and one of the fourteen corrected classifications. New insights into the differences in classification accuracy were obtained. First, results showed that all corrected images resulted in higher overall classification accuracies than the uncorrected images. The highest accuracy for the full validation set was achieved after combination of an atmospheric correction based on transmittance functions and a pixel-based Minnaert topographic correction. Secondly, class accuracies of especially the coniferous and mixed forest classes were enhanced after correction. There was only a minor improvement for the other land cover classes (broadleaved forest, bare soil, grass and water). This was explained by the position of different land cover types in the landscape. Finally, coupled correction methods showed most efficient on weakly illuminated slopes. After correction, accuracies in the low illumination zone (cos β  0.65) were improved more than in the moderate and high illumination zones. Considering all results, best overall classification results were achieved after combination of the transmittance function correction with pixel-based Minnaert or pixel-based C-topographic correction. Furthermore, results of this bi-temporal study indicated that the topographic component had a higher influence on classification accuracy than the atmospheric component and that it is worthwhile to invest in both atmospheric and topographic corrections in a multi-temporal study.  相似文献   

2.
姜亢  胡昌苗  于凯  赵永超 《遥感学报》2014,18(2):287-306
地形校正可以减小地形起伏对地物光谱的影响,提高计算机分类在山区的精度。设计了针对全球土地覆盖分类的Landsat TM/ETM+数据地形校正方法 SCOS(Smoothed COS余弦),首先对地形的坡度角进行抹平处理,很大程度上削弱了地表非朗伯性对地形校正的影响,然后利用简单有效的余弦校正去除地形效应。该方法与其他常用地形校正算法的对比分析是通过对全球不同区域、不同地表覆盖的有代表性的6景Landsat TM/ETM+数据的试验,采用统计分析与目视判读的方式,从过度校正和类内均一性两个方面进行的。结果表明,该方法在目视效果和统计结果上优于常规方法,并且更加简单有效,无需复杂的大气参数及传感器参数,满足全球地表覆盖分类对地形校正的需求。  相似文献   

3.
Pixel-based image compositing enables production of large-area surface reflectance images that are largely devoid of clouds, cloud shadows, or haze. Change detection with spectral trend analysis uses a dense time series of images, such as pixel-based composites, to quantify the year, amount, and magnitude of landscape changes. Topographically-related shadows found in mountainous terrain may confound trend-based forest change detection approaches. In this study, we evaluate the impact of topographic correction on trend-based forest change detection outcomes by comparing the amount and location of changes identified on an image composite with and without a topographic correction. Moreover, we evaluated two different approaches to topographic correction that are relevant to pixel-based image composites: the first corrects each pixel according to the day of year (DOY) the pixel was acquired, whilst the second corrects all pixels to a single reference date (August 1st), which was also the target date for generating the pixel-based image composite. Our results indicate that a greater area of change is detected when no topographic correction is applied to the image composite, however, the difference in change area detected between no correction and either the DOY or the August 1st correction is minor and less than 1% (0.54–0.85%). The spatial correspondence of these different approaches is 96.2% for the DOY correction and 97.7% for the August 1st correction. The largest differences between the correction processes occur in valleys (0.71–1.14%), upper slopes (0.71–1.09%), and ridges (0.73–1.09%). While additional tests under different conditions and in other environments are encouraged, our results indicate that topographic correction may not be justified in change detection routines computing spectral trends from pixel-based composites.  相似文献   

4.
The recent free availability of Landsat historical data provides new potentials for land-cover change studies. Multi-temporal studies require a previous radiometric and geometric homogenization of input images, to better identify true changes. Topographic normalization is one of the key steps to create consistent and radiometricly stable multi-temporal time series, since terrain shadows change throughout time. This paper aims to evaluate different methods for topographic correction of Landsat TM-ETM+ data. They were assessed for 15 ETM+ images taken under different illumination conditions, using two criteria: (a) reduction of the standard deviation (SD) for different land-covers and (b) increase in temporal stability of a time series for individual pixels. We observed that results improve when land-cover classes where processed independently when applying the more advanced correction algorithms such as the C-correction and the Minnaert correction. Best results were obtaining for the C-correction and the empiric–statistic correction. Decreases of the SD for bare soil pixels were larger than 100% for the C-correction and the empiric–statistic correction method compared to the other correction methods in the visible spectrum and larger than 50% in the IR region. In almost all tests the empiric–statistic method provided better results than the C-correction. When analyzing the multi-temporal stability, pixels under bad illumination conditions (northern orientation) improved after correction, while a deterioration was observed for pixels under good illumination conditions (southern orientation). Taken this observation into account, a simple but robust method for topographic correction of Landsat imagery is proposed.  相似文献   

5.
本文提出一种新的半经验地形校正模型SCEDIL(Simple topographic Correction using Estimation of Diffuse Light),该模型通过结合DEM与光学影像数据寻找局部区域内完全光照和阴影的水平像元,并以光照、阴影水平像元的平均反射率值估算局部区域散射辐射比,提高了陡峭山区影像的地形校正精度。以高分一号卫星和Landsat ETM+影像为例,从目视判读和定量分析两个方面,比较分析该算法与传统半经验地形校正算法(C、SCS+C)的校正结果。结果表明:(1)对较为平坦的地形,SCEDIL和C、SCS+C校正都有较好的目视结果;对地面起伏较大的陡峭地形,C、SCS+C校正后,原阴影区域易呈现破碎化特征,SCEDIL校正后,原阴影区域过渡较为平滑。(2)SCEDIL校正后,各波段反射率的均值和标准差优于C、SCS+C校正,SCEDIL校正后,影像总分类精度与同类地物光谱信息均一性均优于C和SCS+C校正。SCEDIL半经验地形校正方法能有效地去除影像中的地形干扰,尤其对陡峭地形的校正效果,优于常规地形校正模型。  相似文献   

6.
The uneven distribution of solar radiation due to topographic relief can significantly change the correlation between reflectance and other features such as biomass in rugged terrain regions. In this article, we use the transfer theory to improve the Minnaert approach. After comparing topographic correction methods for Landsat 8 Operational Land Imager (OLI) and EO-1 Advanced Land Imager (ALI) imagery acquired from the mountainous region in Beijing, China, we used visual inspection, statistical analysis, and correlation analysis to evaluate the algorithms and performance of the proposed Minnaert-E approach. The results indicate that corrections based on non-Lambertian methods have better performance than those based on the Lambertian assumption. The correction performances can be ranked as the Minnaert-E, followed by the Minnaert and the SCS+C corrections, and, finally, the C-HuangWei correction, which performed the worst. We found that the Minnaert-E approach can effectively weaken the influence of terrain relief on pixels and restore the true reflectance of the pixels in the relief area. Further analysis indicates that the Minnaert-E has a better effect on image processing where the slope gradient is restricted to less than 10° or between 30° and 43°.  相似文献   

7.
一种顾及空间相关性遥感影像辐射度的地形校正算法   总被引:7,自引:1,他引:6  
黄微  张良培  李平湘 《测绘学报》2006,35(3):285-290
地形校正的目的是消除太阳光照对不规则地面地物辐射值的影响。这种影响会使相似植被类型地物的辐射值发生很大的变化。因此,在地形复杂的地区,地形校正是影像预处理的一个重要步骤。传统的基于单像素的地形校正方法,虽然减小了辐射值的变化,但在太阳入射角低的地区常常出现校正过度的情况。针对这种误差进行分析,提出一种考虑了空间相关性的校正算法,并且利用鄂西地区的Landsat7卫星影像进行的试验证明,该算法优于传统的地形校正模型。  相似文献   

8.
Canopy shadowing mediated by topography is an important source of radiometric distortion on remote sensing images of rugged terrain. Topographic correction based on the sun–canopy–sensor (SCS) model significantly improved over those based on the sun–terrain–sensor (STS) model for surfaces with high forest canopy cover, because the SCS model considers and preserves the geotropic nature of trees. The SCS model accounts for sub-pixel canopy shadowing effects and normalizes the sunlit canopy area within a pixel. However, it does not account for mutual shadowing between neighboring pixels. Pixel-to-pixel shadowing is especially apparent for fine resolution satellite images in which individual tree crowns are resolved. This paper proposes a new topographic correction model: the sun–crown–sensor (SCnS) model based on high-resolution satellite imagery (IKONOS) and high-precision LiDAR digital elevation model. An improvement on the C-correction logic with a radiance partitioning method to address the effects of diffuse irradiance is also introduced (SCnS + C). In addition, we incorporate a weighting variable, based on pixel shadow fraction, on the direct and diffuse radiance portions to enhance the retrieval of at-sensor radiance and reflectance of highly shadowed tree pixels and form another variety of SCnS model (SCnS + W). Model evaluation with IKONOS test data showed that the new SCnS model outperformed the STS and SCS models in quantifying the correlation between terrain-regulated illumination factor and at-sensor radiance. Our adapted C-correction logic based on the sun–crown–sensor geometry and radiance partitioning better represented the general additive effects of diffuse radiation than C parameters derived from the STS or SCS models. The weighting factor Wt also significantly enhanced correction results by reducing within-class standard deviation and balancing the mean pixel radiance between sunlit and shaded slopes. We analyzed these improvements with model comparison on the red and near infrared bands. The advantages of SCnS + C and SCnS + W on both bands are expected to facilitate forest classification and change detection applications.  相似文献   

9.
SCS+C地形辐射校正模型的应用分析研究   总被引:1,自引:0,他引:1  
在对有森林覆盖的山区影像进行地形辐射校正时,基于太阳-冠层-传感器(SCS)几何关系的校正模型优于基于太阳-地形-传感器(STS)几何关系的模型。SCS校正模型解释了树木不依赖于地形、观测角和光照入射角而具有向地性生长的本质特性,但在某些地形区域,SCS与余弦校正同样存在过度校正的问题。为了解决这个问题,研究者在SCS校正模型中引入C校正系数来解释散射辐射项,提出了SCS+C校正模型。以北京密云Landsat 5影像为数据源,通过目视判别、直方图、定量的统计参数和地物光谱曲线对比等方法,对SCS+C校正模型与传统的余弦校正、C校正和SCS校正模型进行了对比。结果表明,4种方法均能在很大程度上消除地形阴影,更好地反映阴影区域的细节信息; 从总体的光谱特性保真程度来说,余弦和SCS校正都因过度校正问题表现较差,SCS+C校正最好,C校正次之。  相似文献   

10.
为纠正航片或卫星影像反立体现象,提出在PhotoShop下通过DEM与航片套合进行反立体纠正的方法。以兰州市地形图为例,将航片的反立体纠正为正立体。实验表明该方法可以较好的对影像图进行纠正。  相似文献   

11.
Abstract

This study advocates the use of GIS and remote sensing technologies to establish urban evolution maps and assess the impact of urbanization on agricultural areas over the last three decades. The target area is the city of Béni‐Mellal, located in central Morocco. The methodology adopted makes use of panchromatic SPOT images to survey the urban areas during the 1980s and 1990s. Available topographic maps provided the information for the 1970s. Maps and statistics of land use and urban growth for Béni Mellal were established after manually classifying images on a per-polygon basis and digitizing topographic maps using GIS capabilities. The results show an increase in dense urban area by 980.7 ha from the 1970s to the 1990s. This increase occurred at the expense of forests (24.7 ha), plantations (752.3 ha), rangeland (113.4 ha), non‐irrigated land (69.7 ha), and irrigated land (20.6 ha). During this period, scattered urban areas, predominantly suburbs, increased by 755.9 ha to the detriment of forests (14.9 ha), plantations (109.8 ha), rangeland (138.9 ha), non‐irrigated land(400.5 ha), and irrigated land (91.9 ha). These cartographic and statistic results are efficient decision‐making tools for protecting agricultural land and planning urban and suburban areas.  相似文献   

12.
利用地形图对TM遥感影像进行几何精校正的方法研究   总被引:1,自引:0,他引:1  
遥感数据的几何精校正是生成遥感数据产品及将遥感数据用于进一步数据分析前重要的一步。几何精校正的效果将直接影响到影像地理参考的精度,进而影响到在许多遥感数据分析中都要用到的地物能否精确定位的问题。因此几何精校正是遥感科研工作中基础的必可可少的工作之一。本文介绍了利用1:100000比例尺地形图及ERDASIMAGINE8.6软件,采用2次多项式模型,对关中平原TM影像进行几何精校正的方法。结果表明:当保留25个控制点时,校正后误差为0.63个像元,校正后影像具有较高精度,可以用于遥感信息的提取以及为地理信息系统等提供可使用的数据。  相似文献   

13.
快速、精准的建筑物变化检测对城市规划建设等业务管理具有重要意义。随着卫星遥感技术的快速发展,基于高分辨率遥感影像的建筑物变化检测得到了广泛关注。针对像元级建筑物变化检测方法往往精度不足而目标级建筑物变化检测方法过程烦琐等问题,本文提出结合像元级和目标级的高分辨率遥感影像建筑物变化检测方法。首先综合高分辨率遥感影像的多维特征,利用随机森林分类器进行影像集分类,以获取像元级建筑物变化检测结果;然后对后时相遥感影像进行图像分割,获得影像对象;最后融合像元级建筑物变化检测结果和影像对象,识别变化的建筑物目标。利用双时相QuickBird高分辨率遥感影像进行建筑物变化检测试验,结果表明:本文提出的方法能够削弱光照、观测角度等环境差异对建筑物变化检测的影响,显著改善建筑物变化的检测精度。  相似文献   

14.
Abstract

Land use/land cover (LULC) classification with high accuracy is necessary, especially in eco-environment research, urban planning, vegetation condition study and soil management. Over the last decade a number of classification algorithms have been developed for the analysis of remotely sensed data. The most notable algorithms are the object-oriented K-Nearest Neighbour (K-NN), Support Vector Machines (SVMs) and the Decision Trees (DTs) amongst many others. In this study, LULC types of Selangor area were analyzed on the basis of the classification results acquired using the pixel-based and object-based image analysis approaches. SPOT 5 satellite images with four spectral bands from 2003 and 2010 were used to carry out the image classification and ground truth data were collected from Google Earth and field trips. In pixel-based image analysis, a supervised classification was performed using the DT classifier. On the other hand, object-oriented (K-NN) image analysis was evaluated using standard nearest neighbour as classifier. Subsequently SVM object-based classification was performed. Five LULC categories were extracted and the results were compared between them. The overall classification accuracies for 2003 and 2010 showed that the object-oriented (K-NN) (90.5% and 91%) performed better results than the pixel-based DT (68.6% and 68.4%) and object-based SVM (80.6% and 78.15%). In general, the object-oriented (K-NN) performed better than both DTs and SVMs. The obtained LULC classification maps can be used to improve various applications such as change detection, urban design, environmental management and zooning.  相似文献   

15.
章皖秋  岳彩荣  袁华 《遥感学报》2016,20(4):590-600
影像目视判读常会遇到山脊与沟谷的凹凸感与现实相反的反立体现象。消除反立体现象,能有效提高非专业人员对遥感影像的正确使用。立足于反立体现象的成因,本文采用地形正规化模型来校正影像的反立体现象,推导出Lambertian、Cosine-Civco、c校正、b校正这4种地形正规化模型的反立体校正式;对这4种地形正规化模型的反立体校正效果进行了对比,并且与其他5种校正法也进行了对比。通过3个实验区的校正发现,这4种地形正规化模型均能校正反立体现象,但校正影像存在色调偏差;Lambertian、Cosine-Civco的反立体校正影像立体感较强,但影像色调改变较大,视觉效果偏差;c校正、b校正的校正影像在视觉效果和定量指标上都比较接近,基本保持地物光谱信息,校正效果相对较好。从定量指标来看,b校正的反立体校正影像的各指标值整体最小,一定程度代表b校正能取得相对较好的反立体校正效果。与其他方法的对比表明,c校正和b校正的反立体校正不局限于波段个数,在有效消除反立体现象的同时,能相对较好的保留地物光谱信息,有利于影像的定量应用。  相似文献   

16.
The launch of the Very High Resolution (VHR) sensor satellites has paved the way for further exploitation of the capabilities of satellite stereo imaging for many applications. The objective of this paper is to evaluate the level of accuracy that can be achieved by using stereo satellite images for different applications involving significantly different types of terrain. Three mathematical models for satellite sensor modeling are used: Rational Function Model (RFM), 3D polynomial model, and 3D affine model. Three stereo pairs of image datasets are tested from different satellites for different areas: (a) Indian Remote Sensing (IRS)-1D stereo images for topographic mapping and digital terrain elevation modeling for an area in Egypt; (b) IKONOS stereo images for highway alignments extraction in Toronto, Canada; and (c) IKONOS stereo images for topographic mapping and geometric parameter extraction for highway alignments in Hong Kong, China. The accuracy was evaluated by comparing the results of the data extracted using stereo satellite images and those extracted from conventional techniques, including Global Positioning System, field measurements, and aerial photogrammetry. The accuracy of the extracted features was found to be within a pixel-level. The results of this paper should be of interest to professionals from different disciplines exploring the use and accuracy of satellite stereo images for topographic and transportation applications.  相似文献   

17.
ABSTRACT

We propose a method for spatial downscaling of Landsat 8-derived LST maps from 100(30?m) resolution down to 2–4?m with the use of the Multiple Adaptive Regression Splines (MARS) models coupled with very high resolution auxiliary data derived from hyperspectral aerial imagery and large-scale topographic maps. We applied the method to four Landsat 8 scenes, two collected in summer and two in winter, for three British towns collectively representing a variety of urban form. We used several spectral indices as well as fractional coverage of water and paved surfaces as LST predictors, and applied a novel method for the correction of temporal mismatch between spectral indices derived from aerial and satellite imagery captured at different dates, allowing for the application of the downscaling method for multiple dates without the need for repeating the aerial survey. Our results suggest that the method performed well for the summer dates, achieving RMSE of 1.40–1.83?K prior to and 0.76–1.21?K after correction for residuals. We conclude that the MARS models, by addressing the non-linear relationship of LST at coarse and fine spatial resolutions, can be successfully applied to produce high resolution LST maps suitable for studies of urban thermal environment at local scales.  相似文献   

18.
大比例尺地形图数据库的更新是一项长期的重要任务。本文分析了1∶2000地形图数据库快速更新的难点,提出了一种航空摄影与卫星遥感、区域更新与要素更新相结合的大比例尺地形图数据库半自动快速更新方法。采用变化检测方法从更新前后卫星遥感影像中提取变化区域和变化要素,然后分别采用面向区域和面向要素的方法从高分辨率航空影像上测量变化地物,最后通过半自动空间实体匹配的方法建立现状库与历史库中要素的回溯关联,从而实现地形图数据库的半自动增量式快速更新。利用该方法对中山市东区的1∶2000地形图进行了更新试验。试验结果表明,引入卫星影像进行自动变化检测后,在航空影像上分区域和要素两种模式采集更新城市大比例尺地形图数据库,效率比传统方法提高25%。  相似文献   

19.
张猛  曾永年  朱永森 《遥感学报》2017,21(3):479-492
以洞庭湖流域为研究区,对大范围湿地信息遥感提取方法进行了研究。先基于时间序列MODIS EVI及物候特征参数,通过J-M(Jeffries-Matusita distance)距离分析,构建了MODIS(250 m)最佳时序组合分类数据;其次,通过Johnson指数确定了最佳分割尺度,采用面向对象的遥感分类方法(Random tree分类器)提取了洞庭湖流域的湿地信息,并验证该方法的适用性。研究结果表明,基于时序数据与面向对象的Random tree分类的总体精度和Kappa系数分别为78.84%和0.71,较之基于像元的相同算法的总体分类精度和Kappa系数分别提高了5.79%和0.04。同时,基于面向对象方法的湿地整体的用户精度与生产者精度较基于像元方法分别提高了4.56%和6.21%,可有效提高大区域湿地信息提取的精度。  相似文献   

20.
RASAT Earth Observation Satellite is the second remote sensing satellite of The Scientific and Technological Research Council of Turkey (TUBITAK) Space Technologies Search Institute (TUBITAK Space). Generally, the first step to utilize the satellite imagery in GIS applications is the accurate geometric correction of the imagery. But, the geometric correction process of RASAT images is somewhat difficult due to insufficient orbit data and lack of satellite imagery processing software with RASAT model. Although the geolocation of RASAT images is investigated in some recent studies, subpixel accuracies cannot be achieved. In this study, different geometric correction methods and combination of them are tested with a more interactive workflow that uses the results of other approaches. Results show that these approaches can be used for the geometric correction of RASAT like pushbroom satellite images with insufficient orbit data and better geolocation accuracies can be achieved by different geometric correction approaches.  相似文献   

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