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1.
以新疆准噶尔盆地古尔班通古特沙漠为研究区,以中等分辨率成像光谱仪(MODIS 1B)数据为例,辅以MODIS光谱响应函数(SRF)和全波段光谱仪(ASD)准同步采集的雪面反射光谱,运用线性光谱混合模型(LSMM)实现了稀疏植被区积雪遥感信息提取.结果表明:①利用SRF对雪面反射光谱进行端元光谱到像元光谱的转换,生成对应于MODIS1-7波段的离散光谱,将其与用最小噪声分离(MNF)变换和像元纯度指数(PPI)法获得的MODIS影像端元光谱进行对比,发现MODIS1波段光谱值远大于转换光谱值,MODIS2-7波段光谱值与转换光谱值接近;②MODIS2-7波段影像端元光谱值适用于LSMM估算稀疏植被区积雪分量,积雪分量估算值与归一化差分积雪指数(NDSI)拟合结果显示,剔除MODIS1波段后估算的积雪分量与NDSI的相关性显著提高,表明所提取的积雪分量可以作为估算积雪的典型指数.  相似文献   

2.
纯净像元指数改进的N-FINDR高光谱端元提取算法   总被引:2,自引:0,他引:2  
为了有效解决遥感影像中普遍存在的混合像元导致遥感影像定量解译精度低的问题,对两种不同混合像元端元提取算法进行了比较分析。纯净像元指数算法随着迭代次数的增加时间效率大大降低,而经典的N-FINDR算法初始端元数目选择的任意性会导致像元解混的精度不一,因此本文提出了一种基于纯净像元指数改进的N-FINDR算法。改进的N-FINDR算法相较于传统的N-FINDR算法能够准确构建候选端元集合并求得最优解。该算法结合高光谱影像数据的特点,首先利用纯净像元指数求取备选端元数目;然后以此为基础运用经典的N-FINDR算法求解最大的单形体顶点,将求解后顶点作为纯净像元,并完成丰度反演;最后使用ENVI产品中自带的经过大气校正的航空高光谱数据cup95eff.int对算法进行验证。试验结果表明,以纯净像元指数改进的N-FINDR算法在整体精度方面优于传统的N-FINDR算法。  相似文献   

3.
传统的混合像元分解算法认为每个像元都包含图像中所能提取的全部端元组分,但这并不符合实际情况。实际上图像中大多数混合像元仅由少部分端元混合而成。由于端元提取精度及噪声的影响,采用全部端元对混合像元进行分解,会使得混合像元中实际并不存在的端元的丰度估计值不为零,分解结果存在较大误差。由于混合像元大多存在于不同地物的交界处,基于此,本文提出了一种结合图像的空间信息选取混合像元最优端元子集的方法。利用一个空间结构元素,从混合像元的附近邻域开始搜索,将搜索到的纯净像元光谱与所提取的图像端元光谱进行对比,并确定混合像元的端元子集进行分解。根据RMSE大小和变化情况,逐步扩大结构元素的大小,不断调整搜索范围,直至得到最优端元组合。模拟数据和真实数据的试验结果表明,该方法相比传统的全端元光谱分解方法,在总体上获得了更好的分解效果。  相似文献   

4.
天山典型林带积雪的多角度遥感识别   总被引:1,自引:1,他引:0  
汪凌霄  肖鹏峰  冯学智 《遥感学报》2012,16(5):1035-1053
天山中段的山地针叶林带很大程度上影响了该地区整体卫星雪盖的识别精度,多角度卫星遥感技术的发展为林区积雪识别提供了新的途径。本文选取了2000年4月至2001年6月,10个时段研究区内无云覆盖的(Multi-angle Imaging Spectro Radiometer)MISR多角度数据,首先对红光波段不同角度观测结果组成的角度谱图像进行非监督分类,以确定天山林带的分布区域,然后在玛纳斯河中下游与那拉提山东部选取典型像元,分析这些像元红光波段各角度反射率在林区不同积雪覆盖状况下的表现差异。研究发现,若林区存在积雪,0°,±26.1°,±45.6°五个观测角度反射率的平均值大于0.1,在部分降雪月份,后向45.6°观测的反射率大于天顶方向观测的2.5倍。根据这一结论,给出基于MISR数据的研究区不同时段的积雪识别结果。结果表明,MISR红光波段对林区积雪反应敏感,不同角度观测的反射率在林区有雪和无雪时差异较大,故可利用多角度遥感信息进行林区积雪识别。  相似文献   

5.
高光谱图像端元提取算法研究进展与比较   总被引:2,自引:0,他引:2  
高光谱图像中混合像元的存在不仅影响了基于遥感影像的地物识别和分类精度,而且已经成为遥感科学向定量化方向发展的主要障碍。本文分析和研究了现有的典型端元提取算法,在此基础上,对这些算法进行归纳总结,从是否假定纯像元存在角度将其分为两类:端元识别算法和端元生成算法,并就两种分类方法选取了具有代表性的6种典型端元提取算法:N-FINDR、VCA、SGA、OSP、ICE和MVC-NMF算法进行分析和实验。通过对这6种方法的实验比较,得出两种端元提取分类方法的优点与不足,并对今后的研究工作提出展望。  相似文献   

6.
针对无约束最小二乘混合像元分解算法提取地物端元丰度出现的局限性问题,通过野外实地采集的地物光谱数据建立研究区典型的地物波谱库,以Landsat OLI影像作为主要数据源,在经过Gram-Schmidt(GS)影像融合的基础上,利用纯净像元指数(PPI)及基于几何顶点的端元提取技术提取研究区典型地物端元,最后通过完全约束的最小二乘混合像元分解算法完成对研究区典型地物端元丰度的提取。结果较好地解决了无约束最小二乘混合像元分解算法提取的端元丰度信息出现负值的情况,并且提高了典型地物丰度信息提取的精度。完全约束最小二乘混合像元分解算法的RMSE误差均控制在0.174 913左右,在很大程度上提高了混合像元分解精度及实用性。  相似文献   

7.
张娜  王萍  桑会勇  严海英  翟亮 《测绘科学》2019,44(2):164-170
针对MODIS影像中普遍存在的混合像元问题,该文基于MYD09GA地表反射率数据,实现了洪水淹没的亚像元级别的空间细节定位,并加入数字高程模型(DEM)高程信息修正了亚像元制图结果,两结果与传统硬分类法提取结果进行了比较。结果表明,亚像元制图算法较传统硬分类法对洪水淹没范围提取精度更高,能够很好地保持水体空间细节特征,DEM修正后的亚像元定位结果精度进一步提高。  相似文献   

8.
徐君  王彩玲  王丽 《测绘学报》2019,48(8):996-1003
自动形态学端元提取(automated morphological endmember extraction,AMEE)算法将结构元素内最纯像元与混合度最大的像元之间的光谱角距离定义为形态学离心率指数(morphological eccentricity index,MEI)来定量化地表示像元的纯净度。然而作为参考标准的混合度最大的像元在不同的结构元素内也是不同的,尤其是当结构元素内的纯净像元占大多数时,像元的均值光谱将更接近纯像元,此时像元的MEI越高,纯度反而越低。针对这一问题,本文提出一种像元纯度指数(pure pixel index,PPI)算法与AMEE算法相结合的端元提取算法PPI-AMEE。在结构元素内,利用PPI指数代替AMEE算法中的MEI指数来寻找最纯像元。变换结构元素时,只有最纯净的像元始终能够投影到随机生成的直线的两端,其PPI值会不断累计增大,而其他像元的PPI值则无法持续增大。累计记录每个像元的PPI值,直至满足迭代终止条件,最终形成一幅PPI图像,端元将在PPI值较大的像元中选取。PPI-AMEE算法只在相对较小的结构元素内运行PPI算法,然后再结合数学形态学中的膨胀操作对整幅图像进行处理,其同时兼顾了图像的光谱信息和空间信息。最后,采用模拟数据及美国内华达州Cuprite地区的机载可见光/红外成像光谱仪(airborne visible infrared imaging spectrometer,AVIRIS)高光谱数据对提出的PPI-AMEE算法进行试验验证。试验结果表明,PPI-AMEE算法的端元提取精度总体上优于AMEE算法和PPI算法。  相似文献   

9.
田玉刚  杨贵 《测绘学报》2015,44(2):214-219
由于数据量大,目前大多数端元提取算法均需较长的计算时间,限制了这些算法的有效应用。本文提出了以光谱梯度特征为搜索条件的快速端元提取方法,其核心包括基于光谱梯度特征的候选端元快速筛选和基于光谱解混误差的端元识别两部分。由于能够从影像中快速筛选出少量的像元光谱作为候选端元,故具有较好的计算性能;同时由于避免了非端元光谱参与端元识别,使得识别的结果具有更高的精度。试验表明,相比经典的IEA算法和ECHO算法,该算法不仅能大幅度提高端元提取速度,而且具有更准确的端元识别能力。同时,基于该算法原理,也可对现有各种算法进行改进,提升现有的各种端元提取算法的运算速度。  相似文献   

10.
利用卡方分布改进N-FINDR端元提取算法   总被引:3,自引:0,他引:3  
丁海勇  史文中 《遥感学报》2013,17(1):122-137
针对N-FINDR算法计算速度慢、搜索范围较大的特点,提出改进的快速N-FINDR算法,通过提供一个像元个数较少的候选端元集合,为N-FINDR算法提供一个较小的搜索范围。在N-FINDR算法中,所有的端元被认为是处于所有像元构成的单形体的顶点位置,表示这些像元远离像元聚类中心。因此,利用卡方分布的分位点可以分离出这些像元,形成数量较少的候选端元集合。利用合成的和真实的高光谱数据对该算法的性能进行了验证。实验表明,在与N-FINDR算法有相同的端元提取精度的前提下,该算法计算速度更快。  相似文献   

11.
The Qinghai-Tibetan Plateau (QTP) snow cover information acquisition of the high precision spatial and temporal characteristics is of great significance for the research on its land surface atmosphere coupled system and global climate change effects. The Moderate Resolution Imaging Spectro-radiometer (MODIS) daily snow cover products (MOD10A1 and MYD10A1) have been widely used in long time series of spatial and temporal variation analysis, but they are limited to be used because of high cloud cover ratio. In this paper, a 7-day rolling combination algorithm was presented to eliminate cloud obscuration, and the whole cloud amount falls below 7 %. The ground station in situ measurements verify that the overall precision is more than 90 %. The presented algorithm guaranteed the same spatial resolution and temporal resolution, and has higher precision than products MOD10A1 and MYD10A1. The MODIS 7-day rolling combination snow cover datasets products were obtained between 2003 and 2014 in the QTP, and the snow cover area of spatial and temporal variation was analyzed. The change characteristics of snow cover duration was also studied combining with the Digital Elevation Model data. Results show that the snow cover area of the whole QTP has a slowly decreased trend, but increases in autumn. Thus, the snow cover proportion of annual periodic and unstable in different elevations has the highest correlation with area of the elevation.  相似文献   

12.
高光谱遥感积雪制图算法及验证   总被引:8,自引:0,他引:8  
李震  施建成 《测绘学报》2001,30(1):67-73
雪盖面积是高山地区和季节雪盖区水文和气象模型的重要输入因子。机载和星载遥感数据提取的雪盖面积是融雪径流模型的重要组成部分。对应不同传感器件的光谱特征,多种分类方法被相继提出。但是,缺乏相对独立的验证手段来评价各种分类方法,其主要原因是缺乏地面真实状态。针对该现状,本研究利用高光谱图像的细分光谱特征,建立高光谱影像及其对应“地面真相”的像对数据库来发展和验证积雪制图算法,并展示MODIS积雪制图算法验证和ASTER混合像元分解雪盖制图算法研究的应用实例。  相似文献   

13.
Integration of the MODIS Snow Cover Produced Into Snowmelt Runoff Modeling   总被引:1,自引:0,他引:1  
Because of the difficulty of monitoring and measuring snow cover in mountainous watersheds, satellite images are used as an alternative to mapping snow cover to replace the ground operations in the watershed. Snow cover is one of the most important data in simulation snowmelt runoff. The daily snow cover maps are received from Moderate Resolution Imaging Spectroradiometer (MODIS), and are used in deriving the snow depletion curve, which is one of the input parameters of the snowmelt runoff model (SRM). Simulating Snowmelt runoff is presented using SRM model as one of the major applications of satellite images processing and extracting snow cover in the Ghara - Chay watershed. The first results of modeling process show that MODIS snow covered area product can be used for simulation and forecast of snowmelt runoff in Ghara - Chay watershed. The studies found that the SCA results were more reliable in the study area.  相似文献   

14.
Snow cover monitoring in the Qinghai-Tibetan Plateau is very important to global climate change research. Because of the geographic distribution of ground meteorological stations in Qinghai-Tibetan Plateau is too sparse, satellite remote sensing became the only choice for snow cover monitoring in Qinghai-Tibetan Plateau. In this paper, multi-channel data from Visible and Infrared Radiometer (VIRR) on Chinese polar orbiting meteorological satellites Fengyun-3(FY-3) are utilized for snow cover monitoring, in this work, the distribution of snow cover is extracted from the normalized difference snow index(NDSI), and the multi-channel threshold from the brightness temperature difference in infrared channels. Then, the monitoring results of FY-3A and FY-3B are combined to generate the daily composited snow cover product. Finally, the snow cover products from MODIS and FY-3 are both verified by snow depth of meteorological station observations, result shows that the FY-3 products and MODIS products are basically consistent, the overall accuracy of FY-3 products is higher than MODIS products by nearly 1 %. And the cloud coverage rate of FY-3 products is less than MODIS by 2.64 %. This work indicates that FY-3/VIRR data can be reliable data sources for monitoring snow cover in the Qinghai-Tibetan Plateau.  相似文献   

15.
青藏高原那曲地区MODIS 地表温度估算   总被引:3,自引:0,他引:3  
王宾宾  马耀明  马伟强 《遥感学报》2012,16(6):1289-1309
地表温度是区域和全球尺度陆面过程研究中的一个关键参数,利用遥感卫星资料反演得到的地表温度数据在气象、水文和生态领域研究中有重要作用.本文基于改进后的针对MODIS 数据的分裂窗口算法,对MODIS L1B 卫星数据进行实用而简便的云检测处理,并根据青藏高原陆地、水体和冰雪等常见下垫面状况的遥感影像分类结果,反演得到了2007-01-03 、04-18 、06-12 和10-02 四日的无云下垫面地表温度.最后,将Sobrino 结果在青藏高原那曲地区与MODIS 日地表温度产品及CAMP/Tibet 观测站地表温度数据进行了对比验证分析.结果表明,该方法得到的地表温度结果与MODIS 数据产品具有较好的一致性,并且地表温度结果与地面观测数据(去除可疑点后)的平均误差仅为1.435 K .  相似文献   

16.
Snow cover is an important variable for climatic and hydrologic models due to its effect on surface albedo, energy, and mass balance. Satellite observations successfully provide a global and comprehensive hemispheric-scale record of the short-term, as well as inter-seasonal variations in snow cover. Passive microwave sensors provide an excellent method to monitor temporal and spatial variations in large-scale snow cover parameters, overcoming problems of cloud cover. Using microwave remote sensing data, snow parameters (snow surface temperature, snow water equivalence, scattering index, emissivity, snow depth) have been retrieved to integrate with the snow cover simulation model developed by SASE for avalanche risk assessment on regional basis. Multispectral and multitemporal brightness temperature data obtained from the Special Sensor Microwave Imager (SSM/I), flown onboard the DMSP satellites, for the period November 2000 to April 2001 and from November 2001 to February 2002 have been analysed. A comparative data set on snow measurements and meteorological observations of a region covering large area of Pir-Panjal and the Greater Himalayan range, available on near real time basis from SASE field observatories were also used. Model calculations were carried out to study the effects of atmospheric transmission on the microwave radiation emitted from the snow covered and snow free ground and atmosphere. The sensitivity of combinations of the SSM/I channels at 19, 37 and 85 GHz, in both horizontal and vertical polarizations, in respect to snow depth, surface temperature of the snowpack have been carried out. Decision rule based algorithms are developed to identify snow cover and non-snow area.  相似文献   

17.
Detection, monitoring and precise assessment of the snow covered regions is an important issue. Snow cover area and consequently the amount of runoff generated from snowmelt have a significant effect on water supply management. To precisely detect and monitor the snow covered area we need satellite images with suitable spatial and temporal resolutions where we usually lose one for the other. In this study, products of two sensors MODIS and ASTER both on board of TERRA platform having low and high spatial resolution respectively were used. The objective of the study was to modify the snow products of MODIS by using simultaneous images of ASTER. For this, MODIS snow index image with high temporal resolution were compared with that of ASTER, using regression and correlation analysis. To improve NDSI index two methods were developed. The first method generated from direct comparison of ASTER averaged NDSI with those of MODIS (MODISI). The second method generated by dividing MODIS NDSI index into 10 codes according to their percentage of surface cover and then compared the results with the difference between ASTER averaged and MODIS snow indices (SCMOD). Both methods were tested against some 16 MODIS pixels. It is found that the precision of the MODISI method was more than 96%. This for SCMOD was about 98%. The RMSE of both methods were as good as 0.02.  相似文献   

18.
An algorithm for retrieving global eight-day 5 km broadband emissivity (BBE) from advanced very high resolution radiometer (AVHRR) visible and near-infrared data from 1981 through 1999 was presented. Land surface was divided into three types according to its normalized difference vegetation index (NDVI) values: bare soil, vegetated area, and transition zone. For each type, BBE at 8–13.5 µm was formulated as a nonlinear function of AVHRR reflectance for Channels 1 and 2. Given difficulties in validating coarse emissivity products with ground measurements, the algorithm was cross-validated by comparing retrieved BBE with BBE derived through different methods. Retrieved BBE was initially compared with BBE derived from moderate-resolution imaging spectroradiometer (MODIS) albedos. Respective absolute bias and root-mean-square error were less than 0.003 and 0.014 for bare soil, less than 0.002 and 0.011 for transition zones, and ?0.002 and 0.005 for vegetated areas. Retrieved BBE was also compared with BBE obtained through the NDVI threshold method. The proposed algorithm was better than the NDVI threshold method, particularly for bare soil. Finally, retrieved BBE and BBE derived from MODIS data were consistent, as were the two BBE values.  相似文献   

19.
Snow cover mapping is important for snow and glacier-related research. The spatial and temporal distribution of snow cover area is a fundamental input to the atmospheric models, snowmelt runoff models and climate models, as well as other applications. Daily snow cover maps from Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite were retrieved for the period between 2004 and 2007, and pixels in these images were classified as cloud, snow or snow-free. These images have then been compared with ground snow depth (SD) measurements from the four observatories located at different parts of Himalayas. Comparison of snow maps with in situ data showed good agreement with overall accuracies in between 78.15 and 95.60%. When snow cover was less, MODIS data were found to be less accurate in mapping snow cover region. As the SD increases, the accuracy of MODIS snow cover maps also increases.  相似文献   

20.
Four up-to-date daily cloud-free snow products – IMS (Interactive Multisensor Snow products), MOD-SSM/I (combination of the MODIS and SSM/I snow products), MOD-B (Blending method basing on the MODIS snow cover products) and TAI (Terra–Aqua–IMS) – with high-resolutions over the Qinghai-Tibetan Plateau (QTP) were comprehensively assessed. Comparisons of the IMS, MOD-SSM/I, MOD-B and TAI cloud-free snow products against meteorological stations observations over 10 snow seasons (2004–2013) over the QTP indicated overall accuracies of 76.0%, 89.3%, 92.0% and 92.0%, respectively. The Khat values of the IMS, MOD-SSM/I, MOD-B and TAI products were 0.084, 0.463, 0.428 and 0.526, respectively. The TAI products appear to have the best cloud-removal ability among the four snow products over the QTP. Based on the assessment, an I-TAI (Improvement of Terra–Aqua–IMS) snow product was proposed, which can improve the accuracy to some extent. However, the algorithms of the MODIS series products show instability when identifying wet snow and snow under forest cover over the QTP. The snow misclassification is an important limitation of MODIS snow cover products and requires additional improvements.  相似文献   

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