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1.
针对夜间云检测问题,本文基于静止气象卫星Himawari-8影像数据,分析了云像元光谱特征与图像特征,提出了融合光谱阈值与图像技术的静止卫星夜间云检测方法,实现了静止卫星夜间云的快速、准确检测。利用MODIS云产品和CALIPSO雷达数据,对云检测结果进行定性分析与定量验证。结果表明：(1)云检测结果与MODIS的云产品MYD06分布基本一致;(2)算法夜间平均云检测精度达到80.3%;(3)不同季节夜间的云检测精度随季节变化较明显,夏季最高达到83.3%,可以区分不同季节夜间的云与非云区域。因此,融合光谱阈值与图像技术的静止卫星夜间云检测方法能有效实现夜间云检测,为夜间云检测应用提供了新思路。  相似文献   

2.
陈洁  郑伟  刘诚  唐世浩 《遥感学报》2021,25(10):2095-2102
随着新一代静止气象卫星的发射,高频次和高时效的观测特性对于火点探测具有独特优势。本文基于Himawari-8新一代静止气象卫星高频次观测特点,提出有利于火情初期火点判识的时序探测方法。与传统的极轨气象卫星遥感火情监测采用的上下文法不同,时序探测法判识火点的方法依据为探测像元亮温在观测时间上的差异。研究结果显示,在无云及无异常热源条件下,相邻时次中红外亮温差异较小,当前后时次亮温差达到3K时,可判识出火点,而上下文法的阈值均在6 K以上,时序法的火点判识阈值较上下文法明显降低,探测相应的亚像元火点面积减小一倍以上,从而提高了火情判识的灵敏度,实现火点早期发现。本文介绍了时序法火点判识方法,并以黑龙江桦川县的星地同步观测实验进行验证,研究表明,时序法较上下文法在初发火点探测灵敏度方面有明显优势,时序法和上下文法的结合可提高气象卫星对火情发展过程的监测能力。  相似文献   

3.
在叶面积指数LAI(Leaf Area Index)产品真实性检验中,地面站点的多时相连续观测LAI数据是重要的验证数据来源。当站点观测范围与产品像元尺度不一致时,站点观测LAI直接用于产品验证可能为验证结果带来误差。因此,在验证之前需要分析站点观测对像元尺度的空间代表性,选择空间代表性好的观测来验证产品,从而减小尺度效应带来的验证误差。以往的研究只是简单的定性说明研究区域,并直接用站点测量数据对产品进行验证,缺少一套系统的站点观测在产品像元尺度内空间代表性评价的方法体系。本文提出了站点LAI观测的空间代表性评价方法,建立了评价指标DVTP(Dominant Vegetation Type Percent)、RSSE(Relative Spatial Sampling Error)和CS(Coefficient of Sill),构建了空间代表性评价分级体系。以中国生态系统研究网络CERN(Chinese Ecosystem Research Network)农田站和森林站LAI观测为例,对站点观测在1 km产品像元尺度内空间代表性进行评价,并分析评价前后站点观测对MODIS LAI产品验证精度的影响。结果显示,本文提出的方法能够有效地对不同站点LAI观测在产品像元尺度内空间代表性进行质量分级,且年际间的站点观测空间代表性较为一致。评价方法能够去掉在特定产品像元尺度下空间代表性不好的观测数据,一定程度上提高验证数据集对产品验证精度的可靠性。  相似文献   

4.
选取2018年10月1日—2019年4月30日作为积雪研究期,利用青藏高原地区118个气象台站的积雪观测数据,对风云三号C星(FY-3C)多仪器融合的雪盖(multi-sensor synergy snow cover,MULSS_SNC)和微波成像仪的雪水当量(microwave radiation imager snow water equivalent,MWRIX_SWE)产品进行评估,以了解产品的区域可靠性。结果表明:MULSS_SNC和MWRIX_SWE雪盖判识准确率分别为87.18%和72.32%,召回率分别为66.67%和49.63%,误判率分别为12.81%和27.68%,漏判率分别为33.33%和50.37%;对于积雪混合像元或积雪深度不足0.5 cm的卫星像元,MULSS_SNC和MWRIX_SWE都倾向于无雪判识,1 cm以下雪盖漏判率高达60%以上; MULSS_SNC在积雪深度达2 cm以上时,召回率可达到89.09%,而MWRIX_SWE产品在积雪深度达5 cm以上时,积雪判识召回率才达到63.37%。MWRIX_SWE反演的青藏高原地区雪深与地面观测值误差很大,不存在线性正相关关系,不建议直接使用。  相似文献   

5.
利用我国自主研制的风云二号静止气象卫星资料,结合地面自动气象站能见度资料,通过对大量不同时相卫星资料的试验分析,找出台湾海峡海雾、云以及晴空海表等典型下垫面的可见光、热红外和中红外3个通道的光谱特征和变化规律,在此基础上运用反射率阈值实现云雾与海洋表面的自动分离,用亮温阈值实现海雾和低云与中高云的自动分离,用中红外和热红外通道的归一化差值指标实现夜间海雾的自动识别,最后建立台湾海峡海雾自动监测业务软件系统,并选择2015年和2016年地面实测资料对遥感监测结果进行精度验证。研究结果表明:风云静止卫星逐时海雾产品能有效地弥补极轨卫星在监测时次上的不足,很好地为台湾海峡海雾动态监测业务提供数据支持;遥感监测结果与地面观测结果相吻合,总体上较为理想,海雾监测平均准确率白天超过70%,但夜间判识精度低于白天;但同时风云静止卫星遥感技术在海雾和低云的有效分离方面仍然存在局限性。  相似文献   

6.
在积雪深度研究中,地面资料插值产生的平滑效应以及遥感空间分辨率不足的问题,在很大程度上影响着积雪深度的估计精度。本文采用中高分辨率成像光谱仪(moderate resolution imaging spectro-radiometer,MODIS)和微波扫描辐射计(advanced microwave scanning radiometer-EOS,AMSR-E)融合后的无云积雪面积产品构建虚拟站点,弥补了气象站点少且不均匀的不足,修正雪深克里金插值产生的平滑效应。同时,提出了基于数据同化算法融合以地面观测资料为基础的克里金空间插值雪深、MODIS积雪面积产品和AMSRE微波反演雪深产品的雪深估计方法。以新疆北疆地区为研究区域进行了算法应用及验证,并选取不同海拔的站点观测资料对融合结果进行验证分析,通过均方根、偏差和相关性系数指标检证了该方法能够有效地提高雪深估计精度。  相似文献   

7.
暗目标法的Himawari-8静止卫星数据气溶胶反演   总被引：1，自引：0，他引：1  
Himawari-8(H8)是由日本气象厅发射的新一代静止气象卫星,可实现10 min/次的高频次对地观测,搭载的AHI(Advanced Himawari Imager)传感器设置有与MODIS暗目标气溶胶反演算法所需的类似波段。本文参考暗目标算法构建了针对该卫星传感器的陆地气溶胶反演算法:首先,通过基于地基站点观测数据的精确大气校正,统计得到短波红外与可见光波段的地表反射率比值关系,将此作为先验知识用于地—气解耦时的反射率估计;然后,初步假设大陆型气溶胶类型,利用辐射传输模型建立查找表;最后,通过模拟与卫星观测的表观反射率误差最小实现气溶胶光学厚度反演解算。选取2016年5月覆盖京津冀地区的观测数据进行测试,将反演结果与对应时间的MODIS气溶胶光学厚度产品进行对比验证,空间分布趋势一致、相关性较高,相关系数R达到0.852;通过与地基观测网AERONET站点实测数据对比验证,所有站点的相关系数R~2均大于0.88,精度较高。利用反演的高时间分辨率产品,分析了京津冀地区的大气空间分布和日变化情况,结果表明:采用暗目标法对H8静止卫星陆地气溶胶光学厚度反演具有一定的潜力和可行性,能反映气溶胶的高时间变化信息,有望成为大气环境污染变化监测新的重要手段。  相似文献   

8.
云检测是气象卫星各类定量遥感产品的基础,无论是以云图为基础的天气分析还是以去云为前提的各类大气和地表参数反演、沙尘火情等灾害检测,都需要对遥感影像中的云进行准确识别,尤其是薄云和云边缘等细节识别。针对静止气象卫星(以Himawari-8为例)精细化云检测,本文提出了一种基于多尺度视网膜图像增强的动态云检测算法。该算法基于云层与背景信息辐射特征不同的原理,构建可见光和红外波段的晴空辐射背景场,通过多尺度图像增强和最大类间差方法对辐射差值进行云细节信息的增强和提取。利用2021-2022年的75景MODIS云检测产品作为验证数据进行算法精度验证,整体上算法精度达到91.13%,召回率为94.02%,精确率为86.71%,有较强的适用性和稳健性,且已经较好地支撑了近两年的定量遥感产品业务化应用。  相似文献   

9.
为降低云对MODIS逐日积雪覆盖产品MOD10A1和MYD10A1在新疆积雪实时监测与研究中的影响,引入交互式多传感器雪冰制图系统(interactive multi-sensor snow ice mapping system,IMS)等多源遥感数据和地面实测资料,综合时间滤波法、空间滤波法及多传感器融合法等不同的去云技术,建立基于多源数据的去云方法,生成新疆地区2002—2016年近15 a间逐日无云积雪覆盖产品数据,并利用实测资料对生成的产品数据进行精度评价及结果验证。结果表明,去云后积雪覆盖产品在新疆积雪覆盖的总体监测精度为90.61%,接近于去云前MODIS晴空积雪覆盖产品在新疆的总体监测精度(93.3%)。  相似文献   

10.
基于通用陆面模型(CoLM)和确定性集合卡尔曼滤波算法发展了一个考虑模型次网格变异性的MODIS雪盖同化方案,提高雪深模拟的估计精度。利用北疆阿勒泰地区5个气象站点2007年11月至2008年4月逐日雪深观测数据对同化结果进行了验证。结果表明,该同化方案不需要对MODIS雪盖观测数据进行扰动,能明显提高雪深模拟的精度。另外,雪深同化结果与地面观测雪深具有一致的时间变化趋势,能准确地反映积雪深度在各个不同时段的变化特性。  相似文献   

11.
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   

12.
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   

13.
基于MODIS影像的内蒙古草原积雪监测   总被引：2，自引：0，他引：2  
光学遥感源MODIS具有高光谱分辨率、高时间分辨率、高空间分辨率、全球范围内免费接收等优势,被广泛应用于洪涝、干旱、森林草原火灾、雪灾等自然灾害的动态监测领域。MODIS数据用于内蒙古草原积雪监测,提取积雪信息在国内尚属空白。本文利用MODIS L1B 500m分辨率数据,经过几何校正、去"双眼皮"预处理,根据归一化差分积雪指数(NDSI)算法和综合阈值判别法对内蒙古自治区2008年1月下旬大范围降雪进行积雪信息提取,制作积雪覆盖图。利用内蒙古生态与农业气象中心发布的雪情遥感监测信息验证积雪覆盖图的准确度。验证结果表明,MODIS数据用于大范围积雪监测非常有效。  相似文献   

14.
The MODIS snowcover product is one of many geophysical products derived from MODIS data. A cross‐validation of the MODIS snowcover daily products with data obtained from the meteorological network stations was conducted for the entire territory of Romania. The validation time interval covered the period between 29 October, 2004 and 1 May, 2005. The overall accuracy for the whole set of cloud‐free useful data proved to be 95%. The validation time interval included the three common snow situations: (1) late autumn months where 37.1% of the initial set of the data was used, and the overall accuracy was 98.6%; (2) the “winter” months where the clouds reduced the set of useful data – 31.75%– and the overall accuracy was 93.7%; and (3) the months of February and March which returned the highest accuracy (> 95%). Additionally, a cross‐validation using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) high‐resolution imagery was carried out. Furthermore, the MODIS, meteorological data and ASTER data were integrated into a Geographic Information System (GIS) environment to perform flexible and comprehensive cross‐checking followed by a thematic analysis based on additional sets of data such as digital elevation models (DEMs) and land‐cover datasets.  相似文献   

15.
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   

16.
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   

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.
云覆盖作为天气和气候变化的一个重要因子,对地表-大气能量平衡和水循环有着重要的影响,因此,快速、准确地利用卫星遥感技术检测云覆盖具有重要的实用价值和科学意义。利用卫星遥感数据,尤其是常用的Moderate Resolution Imaging Spectroradiometer(MODIS)影像数据,因其具有较高的光谱和时间分辨率,以及2330 km扫描幅宽,为大范围实时、准确地进行云检测提供了可能。目前,基于MODIS数据发展了大量的云检测方法,但因地表类型的多样性和大气状况(如空气污染和沙尘事件等)的复杂性,目前已有的云检测方法,检测精度通常具有较大的不确定性,且针对不同地表和大气状况缺乏普适性,同时也缺乏对检测精度的定量化评估。因此,本文首先比较了常用的3种云检测算法,并基于前人经验提出了两种改进方法(方法4和方法5),首先区分出云和冰雹,摒弃了不稳定的亮温波段,两种算法均适用于复杂地表和大气状况的云检测算法。结果显示,方法5可以较好地应用于基于MODIS数据的云检测,总体精度达92.6±7%,改进了现有基于MODIS数据的云检测算法;方法4平均总体精度82.9±13%,虽然精度相对较低,但云残留少,适合作为对云敏感度高的研究工作的云检测方法。  相似文献   

19.
Abstract

Land use/land cover monitoring and mapping is crucial to efficient management of the land and its resources. Since the late 1980s increased attention has been paid to the use of coarse resolution optical data. The Moderate Resolution Imaging Spectroradiometer (MODIS) has features, which make it particularly suitable to earth characterization purposes. MODIS has 10 products dedicated mainly to land cover characterization and provides three kinds of data: angular, spectral and temporal. MODIS data also includes information about the data quality through the ‘Quality Assessment’ product. In this paper, we review how MODIS data are used to map land cover including the preferred MODIS products, the preprocessing and classification approaches, the accuracy assessment, and the results obtained.  相似文献   

20.
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   

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