共查询到17条相似文献，搜索用时 140 毫秒
1.
极区海冰密集度AMSR-E数据反演算法的试验与验证 总被引：2，自引：2，他引：2
海冰密集度是极区海冰监测的重要参数,目前分辨率最高的微波海冰密集度产品为德国Bremen大学发布的针对AMSR-E 89 GHz频段数据利用ASI算法反演的网格数据。为实现中国极区遥感产品从无到有的战略步骤,本文针对AMSR-E 89GHz频段微波数据的ASI算法,进行了插值算法、系点值和天气滤波器一系列试验。针对北极海区,着重对影响反演结果的主要参数——纯冰和纯水的亮温极化差异阈值,即系点值(P1和P0)进行了2009年全年的统计分析。研究表明,2009年北极纯冰和纯水的代表区域P1和P0年平均值分别为10.0 K和46.67 K;2 K以上的系点值差异引起的海冰密集度差别较为显著;同样的系点值差异在不同极化差异P取值范围对海冰密集度的影响也不同。通过统计确定的系点值推算并修正了海冰密集度反演公式,对2009年全年北极海冰密集度进行了反演,并与Bremen大学产品进行了比较。继而对白令海和楚科奇海12个晴空下MODIS可见光样本数据进行反演,以验证AMSR-E冰密集度反演结果,并对误差原因进行了分析。本研究反演结果与MODIS样本比对的误差略小于Bremen大学的反演产品,空间平均误差为3.84%,空间平均绝对误差10.83%。 相似文献
2.
本文对2011-07-01—2011-09-30风云三号B星(FY-3B)搭载的微波成像仪MWRI(Microwave Radiometer Imager)和Aqua卫星搭载的微波扫描辐射计AMSR-E(Advanced Microwave Scanning Radiometer for Earth Observing System)观测数据获取的海冰密集度产品进行比较及印证。首先,逐日比较FY-3B/MWRI和Aqua/AMSR-E区域平均海冰密集度;其次,逐月比较FY-3B/MWRI和Aqua/AMSR-E月平均海冰密集度;最后,使用Aqua卫星搭载的中等分辨率成像光谱辐射计MODIS数据进行印证。MWRI和AMSR-E比较结果为(1)MWRI与AMSR-E逐日区域平均海冰密集度变化趋势一致,MWRI海冰密集度均高于AMSR-E,7—9月MWRI与AMSR-E逐日平均偏差月平均值分别为8.55%、7.67%、2.58%,逐日标准差月平均值分别为12.16%、12.08%、10.43%,二者差异逐月减小。(2)MWRI与AMSR-E月平均海冰密集度差呈现逐月递减趋势,7—9月MWRI与AMSR-E逐月平均偏差分别为7.37%、6.53%、1.51%,逐月标准差分别为4.61%、4.36%、3.64%,MWRI与AMSR-E差异逐月减小的原因是二者在密集度较低的边缘区域差异较大,而夏季随着边缘区域海冰的融化,二者差异逐渐减小。MWRI和AMSRE海冰密集度与MODIS印证结果为:(1)密集度小于95%情况下,MWRI与AMSR-E海冰密集度均比MODIS偏高,AMSR-E更接近MODIS,MWRI高估,误差较大。(2)密集度大于等于95%情况下,MWRI与AMSR-E海冰密集度均比MODIS偏低,AMSR-E偏低更多,MWRI结果更好。 相似文献
3.
《武汉大学学报(信息科学版)》2016,(4)
根据海冰船测目视观测标准在MODIS影像上提取模拟的海冰边界,并利用相应的MODIS海冰密集度验证AMSR-E海冰密集度产品在海冰边界的精度。研究结果表明,海冰边界像素上,AMSR-E海冰密集度的平均值与15%阈值存在显著差异,且AMSR-E与MODIS海冰密集度的相关性很弱(R2≤0.2),基于ASI的海冰反演算法在夏季低估边界海冰密集度。考虑整个冰区(包括多年冰、一年冰、新冰和开阔海域)的截线分析显示,AMSR-E与MODIS海冰密集度存在较好的线性关系(夏季R2=0.82,冬季R2=0.81),AMSR-E海冰密集度在20%~30%区间的误差最大。 相似文献
4.
2002年——2011年北极海冰时空变化分析 总被引：7，自引：0，他引：7
基于2002年-2011年AMSR-E海冰密集度数据, 分析了北极海冰的时空变化特征及其原因。结果表明海冰外缘线面积每年减小8.28×104 km2, 下降趋势最快的季节为夏季, 下降速度是1979年-2006年的两倍多, 而且海冰密集度也在降低。2003年、2004年的冰情相对较重, 2007年海冰面积最小。长期冰在2002年-2010年间减少了近30%, 减少的区域主要在波弗特海、楚科奇海、东西伯利亚海、拉普贴夫海、喀拉海以及由这些边缘海向北极方向延伸的北冰洋的广大区域, 长期冰减少的地方大部分为季节性海冰增加的地方。海冰面积与年平均气温之间有显著的负相关关系, 随着全球气候变暖的加剧, 这种减小趋势将会持续。 相似文献
5.
北极遥感海冰密集度数据的比较和评估 总被引：1，自引：0，他引：1
本文利用2012年夏季中国第五次北极科学考察期间雪龙船在北极东北航道走航观测的海冰密集度数据(OBS-SIC),初步评估了7种基于被动微波遥感的海冰密集度产品(PM-SIC)。7种PM-SIC因传感器和反演方法不同,分辨率差异较大(4—25 km)。在海盆尺度的海冰范围反演上7种PM-SIC基本相同,但对小范围浮冰区的反演差异较大。与MODIS可见光图像对比发现,MASAM数据(4 km)对局部小区域海冰刻画较好,是研究近岸区域或海峡岛屿海冰覆盖范围或面积时的首选产品;7种PM-SIC纬向平均后对比分析显示,不同PM-SIC对网格内是否存在海冰的判断基本一致,但对网格内海冰所占的比例(密集度)判断差异较大。结合OBS-SIC按航线、区域、密集度大小3种不同情况对7种PM-SIC进行分类定量评估,结果表明基于AMSR2传感器的AMSR2/ASI和AMSR2/Bootstrap数据与OBS-SIC偏差较小,平均偏差约±1%,均方根偏差仅11%和12%;而SSMIS/NT数据的偏差最大,平均偏差约–15%,均方根偏差为21%,其严重低估了网格内的海冰密集度值;因此具有更高分辨率的AMSR2/ASI数据(6.25 km)是关注海冰密集度大小时的首选产品。 相似文献
6.
海冰外缘线是一个描述北极海冰快速变化的重要指示参数,对近岸冰区航行保障和海冰灾害预警具有实际意义。本文首先基于形态学中的方法分别识别数据中的主体冰域、主体水域和碎冰区。其次利用可变图像闭运算方法将较大碎冰与主体冰区合并,最后再利用连通域方法提取海冰外缘线。该方法可适用于任何冰水二值数据集,包括海冰密集度产品数据、卫星图像、航拍图像以及其他冰水混合数据。本文基于AMSR-E海冰密集度数据,利用此方法提取了北冰洋10个区域的海冰外缘线,与15%海冰密集度等值线比较表明,本文方法能够保留较大面积的碎冰区域,并将其与主体冰域合并处理,因此所提取的海冰外缘线在衡量大尺度海冰范围方面更为合理。 相似文献
7.
南极海冰范围变化与大气、海洋等环境变化直接相关,对人类的实践活动有重要的影响。而计算机和对地观测技术的发展,使得遥感技术已经成为研究南极海冰变化最重要的方式之一。本文通过对多源遥感数据进行交叉定标,获取连续15年的南极长时序被动微波遥感亮温数据。在此基础上,通过BST算法反演了海冰密集度,分析了南极海冰范围的变化情况,从而为更好地认识南极海冰变化与全球气候环境变化的关系提供依据和参考。 相似文献
8.
海冰密集度对全球气候变化研究有重要的意义,其反演结果的验证工作也被广泛关注,但结合多源数据反演,同时对两种算法验证的研究较少的现状,该文利用ASPeCt船测海冰密集度数据对Bootstrap算法和NASA Team(NT)算法基于SSM/I数据估算的海冰密集度精度进行验证,并与MODIS影像反演获得的海冰密集度进行对比。研究结果显示两种海冰密集度算法获得的反演结果与ASPeCt船测值偏差分别为2.26%和7.27%,均方根误差分别为11.39%和12.32%。相比之下,MODIS结果与ASPeCt船测海冰密集度比较得到偏差为3%,均方根误差为5.21%。Bootstrap算法、NT算法与ASPeCt船测值比较的偏差和均方根误差显示两种算法精度相近;由于MODIS数据分辨率与ASPeCt船测数据相近,所以其反演精度较优;但因时空分辨率的限制,各种结果都具有一定的不确定性。 相似文献
9.
海冰表面积雪厚度是冰冻圈和全球气候系统的重要组成部分,在海洋、海冰和大气的能量传输中起着关键的作用。针对目前缺乏南极海冰表面积雪厚度国产卫星遥感数据产品的问题,本文探索应用FY-3B MWRI被动微波亮温数据开展南极海冰表面积雪厚度的遥感反演研究。结果表明基于2016年FY-3B MWRI 18.7 GHz、36.5 GHz垂直极化亮温及海冰密集度数据,采用Comiso03模型反演的积雪厚度结果较Markus98更好,与AWI2016年部署在威德尔海的浮标(2016S31、2016S37、2016S40)观测的积雪厚度同日同像元对比的偏差为-1.72 cm。FY-3B MWRI反演的2016年南极海冰表面积雪厚度与美国雪冰数据中心发布的GCOM-W1 AMSR-2积雪厚度产品整体上具有较好的一致性(时空平均偏差为-0.11 cm、相关系数为0.90),积累期和稳定期(4—10月)两者差异较小(时空平均偏差为-0.81 cm,相关系数为0.93),消融期(11月—次年3月)差异较大(时空平均偏差为2.76 cm,相关系数为0.85),差异主要分布在威德尔海北部和东南极冰边缘区。开展FY-... 相似文献
10.
以归一化雪被指数法为基础,根据南极的环境特点,提出了MODIS影像的0.86μm与1.24μm的新波段组合方法,分别实现了晴空与薄云下的海冰提取,大幅度地提高了南极海冰监测的效率与分辨率。结合AMSR-E微波数据进行了海冰变化研究,得到2002~2010年的全南极海冰范围与净冰面积都在2月份达到最小值,均值分别为3.17×106 km2与2.42×106 km2;都在9月份达到最大值,均值分别为18.40×106 km2与16.60×106 km2。而全南极海冰的年际变化可分为三个阶段:从2002~2004年,海冰基本持平;2005~2007年,海冰减少;2008~2010年,海冰重新增长,这与南极海冰20a长周期的推断相符合,但9年间的全南极海冰无明显的趋势性变化。 相似文献
11.
通过研究交叉检验船测样点上的7种不同尺度的海冰密集度数据,发现相同时间和相同空间尺度的海冰密集度值吻合度最高,不同时间不同尺度的海冰密集度值的相关性较弱。由数据获取时间不同引起的密集度差异在高分辨率数据上体现明显。真实船测点与伪船测点之间的吻合度不高,受观测者主观因素、天气条件、影像处理质量和伪船测点提取方法的影响。虽然伪船测点方法在海冰边界研究中具有快速、大面积提取边界点的优势,但需要控制提取算法中的误差传播。 相似文献
12.
为了提高南极海冰出水高度的估算精度,以威德尔海为例,基于CryoSat-2卫星测高数据,联合冰桥计划(IceBridge)机载测高数据和科考船走航观测数据,获取应用最低点高程法反演海冰出水高度的最佳估计参数,进而估算并分析了 2011-2017年,每年5月-10月威德尔海海冰出水高度的时空变化.结果表明,最佳的出水高度... 相似文献
13.
Wenting Quan 《Journal of the Indian Society of Remote Sensing》2014,42(3):539-548
To understand the absolute radiometric calibration accuracy of the HJ-A CCD-1 sensors, image from these sensors were compared to nearly simultaneously image from Landsat-7 ETM+ sensors. Although the HJ-A CCD-1 sensor has almost the same wavelength of each central band and band width as Landsat-7 ETM+ sensor, there is slightly difference in spectral response function (SRF). The impacts of SRF difference effects would produce ~2 % uncertainty in predicting reflectance of HJ-A CCD-1 sensor using Landsat-7 ETM+ sensor. The reflectance observed by satellite at top-of-atmosphere generally depends on its’ geometric conditions. The results reveal that the impacts of geometrical conditions would impact on the vicarious cross-calibration accuracy, which should be removed. The performances of cross-calibration are calibrated and validated by four image pairs collected from Yellow River Delta, China, and Qingdao City, China, at four independent times. The results indicate that the HJ-A CCD-1 sensors can be cross calibrated to the Landsat-7 ETM+ sensors to within an accuracy of 3.99 % (denoted by Relative Root Mean Square Error) of each other in all bands except band 4, which has a 6.33 % difference. 相似文献
14.
Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) has been used for the blending of Landsat and MODIS data. Specifically, the 30 m Landsat-7 ETM+ (Enhanced Thematic Mapper plus) surface reflectance was predicted for a period of 10 years (2000–2009) as the product of observed ETM+ and MODIS surface reflectance (MOD09A1) on the predicted and observed ETM+ dates. A pixel based analysis for six observed ETM+ dates covering winter and summer crops showed that the prediction method was more accurate for NIR band (mean r2 = 0.71, p ≤ 0.01) compared to green band (mean r2 = 0.53; p ≤ 0.01). A recently proposed chlorophyll index (CI), which involves NIR and green spectral bands, was used to retrieve gross primary productivity (GPP) as the product of CI and photosynthetic active radiation (PAR). The regression analysis of GPP derived from closet observed and synthetic ETM+ showed a good agreement (r2 = 0.85, p ≤ 0.01 and r2 = 0.86, p ≤ 0.01) for wheat and sugarcane crops, respectively. The difference between the GPP derived from synthetic and observed ETM+ (prediction residual) was compared with the difference in GPP values from observed ETM+ on the two dates (temporal residual). The prediction residuals (mean value of 1.97 g C/m2 in 8 days) was found to be significantly lower than the temporal residuals (mean value of 4.46 g C/m2 in 8 days) that correspondence to 12% and 27%, respectively, of GPP values (mean value of 16.53 g C/m2 in 8 days) from observed ETM+ data, implying that the prediction method was better than temporal pixel substitution. Investigating the trend in synthetic ETM+ GPP values over a growing season revealed that phenological patterns were well captured for wheat and sugarcane crops. A direct comparison between the GPP values derived from MODIS and synthetic ETM+ data showed a good consistency of the temporal dynamics but a systematic error that can be read as bias (MODIS GPP over estimation). Further, the regression analysis between observed evapotranspiration and synthetic ETM+ GPP showed good agreement (r2 = 0.66, p ≤ 0.01). 相似文献
15.
Coffee is a commodity of international trade significance, and its value chain can benefit from age-specific thematic maps. This study aimed to assess the potential of Landsat 8 OLI to develop these maps. Using field-collected samples with the random forest classifier, splitting coffee into three age classes (Scheme A) was compared with running the classification with one compound coffee class (Scheme B). Higher overall classification accuracy was obtained in Scheme B (90.3% for OLI and 86.8% for ETM+) than in Scheme A (86.2% for OLI and 81.0% for ETM+). The NIR band of OLI was the most important band in intra-class discrimination of coffee. Landsat 8 OLI mapped area closely matched farm records (R2?=?0.88) compared to that of Landsat 7 ETM+ (R2?=?0.78). It was concluded that Landsat 8 OLI data can be used to produce age-specific thematic maps in coffee production areas although disaggregating coffee classes reduces overall accuracy. 相似文献
16.
Nikos Koutsias Giorgos Mallinis Michael Karteris 《ISPRS Journal of Photogrammetry and Remote Sensing》2009,64(1):37-46
In this paper, principal component analysis (PCA), a dimensionality reduction method, has been applied successfully as an image enhancement technique to improve the spectral signal of burnt surfaces. Forward/backward PCA (F/B PCA) and image differencing, which the proposed method consists of, creates a new spectral space that preserves the original spectral patterns while enhancing particular structures of the original satellite data. Burnt surfaces constitute a spectrally enhanced feature after selective removal of spectral information from the original Landsat-7 Enhanced Thematic Mapper data.Improvement of the spectral separability of burnt surfaces is most evident in spectral channels ETM+4 and ETM+7, where burnt surfaces already compose distinct spectral objects, and channels ETM+2 and ETM+5. This improvement is reasonable since the third PC axis, which is not considered in the back-transformation, is composed mainly of the spectral information in these channels. Another benefit of the technique is a reduction of interband correlation in the satellite data.No clear differences between the standardized and non-standardized F/B PCA were identified to recommend the use of one over the other. Both methods show advances in certain aspects. Finally, an increase of the separability value between burnt areas and dry vegetated areas from 0.473 to 1.06 and 1.31 was obtained with the use of the standardized and non-standardized F/B PCA, respectively. 相似文献
17.
T. Moffiet J.D. Armston K. Mengersen 《ISPRS Journal of Photogrammetry and Remote Sensing》2010,65(1):26-41
A method is presented for the development of a regional Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper plus (ETM+) spectral greenness index, coherent with a six-dimensional index set, based on a single ETM+ spectral image of a reference landscape. The first three indices of the set are determined by a polar transformation of the first three principal components of the reference image and relate to scene brightness, percent foliage projective cover (FPC) and water related features. The remaining three principal components, of diminishing significance with respect to the reference image, complete the set.The reference landscape, a 2200 km2 area containing a mix of cattle pasture, native woodland and forest, is located near Injune in South East Queensland, Australia. The indices developed from the reference image were tested using TM spectral images from 19 regionally dispersed areas in Queensland, representative of dissimilar landscapes containing woody vegetation ranging from tall closed forest to low open woodland. Examples of image transformations and two-dimensional feature space plots are used to demonstrate image interpretations related to the first three indices. Coherent, sensible, interpretations of landscape features in images composed of the first three indices can be made in terms of brightness (red), foliage cover (green) and water (blue). A limited comparison is made with similar existing indices. The proposed greenness index was found to be very strongly related to FPC and insensitive to smoke. A novel Bayesian, bounded space, modelling method, was used to validate the greenness index as a good predictor of FPC. Airborne LiDAR (Light Detection and Ranging) estimates of FPC along transects of the 19 sites provided the training and validation data. Other spectral indices from the set were found to be useful as model covariates that could improve FPC predictions. They act to adjust the greenness/FPC relationship to suit different spectral backgrounds. The inclusion of an external meteorological covariate showed that further improvements to regional-scale predictions of FPC could be gained over those based on spectral indices alone. 相似文献