共查询到19条相似文献，搜索用时 156 毫秒
1.
基于MODIS数据的Landsat-7 SLC-off影像修复方法研究 总被引：2，自引：0，他引：2
研究如何修复由于扫描行校正器SLC故障而造成的数据坏行,成为国际遥感研究的热点.文章在总结现有的修复方法基础上提出用相同时相的MODIS09数据修复SLC-off数据的方法.该方法采用时空自适应反射率融合模型(STARFM)算法实现MODIS09数据和TM/ETM+数据的融合,获得与SLC-off数据相同时相和空间分辨率的融合数据,然后采用局部线性直方图匹配完成对SLC-off数据填充.实验证明该方法修复效果明显好于传统方法,解决了传统修复方法中存在的一些问题,一定程度上提高了ETM+SLC-off数据的利用率. 相似文献
2.
全球地表覆盖遥感制图与关键技术研究项目要求对两个基准年度(2000年,2010年)的全球覆盖30 m分辨率遥感数据进行辐射处理,转换到地表反射率,数据以Landsat TM/ETM+为主,HJ-1A/B CCD数据为补充。海量数据中有些不适宜进行绝对大气校正,为了保证全球覆盖,对这些数据设计开发了一套自动的相对辐射处理及精度验证流程算法,利用相邻数据重叠区域进行相对辐射校正的方式,将数据由Oigital Number(DN)值直接转换为地表反射率,精度验证以MODIS地表反射率产品MOD09GA作为参考,比较对应波段数据的相对一致性,算法采用了图像分块处理技术及OpenMP加速技术提高效率,实际应用结果表明该算法流程可以满足项目对辐射处理精度、速度及自动化程度的要求。 相似文献
3.
地表温度（land surface temperature,LST）是反映地表能量和水平衡物理过程的一个重要参数,受限于载荷量的限制以及传感器的技术瓶颈,当前的卫星平台均难以获取同时具有较高空间和时间分辨率的遥感地表温度影像,客观上影响了遥感地表温度影像的应用。针对地表异质性较高的城市区域,选取覆盖武汉城区的中分辨率成像光谱仪（Moderate-Resolution Imaging Spectroradiometer,MODIS）和增强型专题绘图仪（Enhanced Thematic Mapper Plus,ETM+）数据,结合时空反射率融合模型（enhanced spatial and temporal adaptive reflectance fusion model,ESTARFM）和非线性辐射温度分解算法（non-linear disaggregation procedure for radiometric surface temperature,NL-DisTrad）对地表温度影像进行时空融合研究,最终生成60 m空间分辨率的逐日地表温度融合影像。将融合影像与2002-07-09和2002-10-13的ETM+实际地表温度影像进行融合精度验证分析,其决定系数R2分别为0.80和0.86,均方根误差（root mean square error,RMSE）分别为2.65 K和1.78 K。实验结果表明,所提出的地表温度时空融合模型在城市区域的地表温度时空融合应用中具有潜在的应用前景。 相似文献
4.
全球地表覆盖遥感制图与关键技术研究项目要求对两个基准年度(2000年、2010年)全球30 m分辨率的多光谱遥感数据进行辐射处理和几何精纠正处理,为地表覆盖制图完成数据准备。数据以Landsat TM/ETM+为主,HJ-1A/B CCD数据为补充,共计2万多景影像需要进行辐射处理,有1000多景HJ-1A/B CCD影像需要几何精纠正。如此大规模的数据处理,自动化处理是必然的选择。本文介绍了HJ-1A/B CCD图像几何精纠正自动化实现中关键问题的解决方法和精度评价结果,Landsat TM/ETM+和HJ-1A/B CCD图像自动化辐射校正中关键问题的解决方法和精度评价结果,以及大规模的数据处理活动引发的一些思考。 相似文献
5.
Sentinel-2A与Landsat 8O LI逐像元辐射归一化方法研究 总被引：1，自引：0，他引：1
考虑不同传感器光谱响应函数差异及不同地物类型反射率光谱的差异,提出了一种逐像元辐射归一化方法,并以2017年7月17日内蒙古达里诺尔湖地区准同步过境的Sentinel-2A及Landsat 8数据为例,对两类数据可见-近红外波段（VNIR）地表反射率结果进行归一化。首先采用Sen2cor方法及NASA官方提供大气校正算法,分别对Sentinel-2A及Landsat 8 OLI影像进行大气校正并重采样到同一空间分辨率;然后基于光谱库计算匹配因子并构建图像与光谱库之间的匹配转换模型,实现像元尺度上从Sentinel-2影像到Landsat 8影像地表反射率相似波段之间的转换。结果表明,经逐像元归一化的影像相比原始影像及经HLS光谱归一化的影像,与Landsat 8 VNIR波段的相关性明显提高,辐射一致性增强。该转换模型为多源中高分辨率遥感图像高精度辐射归一化提供了新思路。 相似文献
6.
高时空分辨率的植被指数VI(Vegetation Index)数据是农业和生态研究的重要基础数据集,目前常用的VI数据的时空分辨率存在不可调和矛盾。考虑VI时序变化对数据融合的影响,提出一种新的VI数据时空融合模型VISTFM(Vegetation Index Spatial and Temporal Fusion Model),VISTFM采用模糊C聚类算法,对存量时序VI数据按土地利用类型划分为若干子类,从高低分辨率影像中随土地覆被类的变化规律提取子类,结合低分辨率影像提取的土地覆被类变化规律融合生成高时空分辨率的VI数据。用常用的Landsat和MODIS数据验证该算法,测试表明,VISTFM能够较好的捕获VI的中间变化过程,与常用的基于线性混合模型的模型和时空自适应反射率融合模型及其改进模型相比,利用VISTFM获得的植被指数数据集具有更高的时空分辨率。 相似文献
7.
以洞庭湖区典型的产量大县——南县为研究区,针对Landsat回访周期较长及长江中下游阴雨天气较多的特点,利用STARFM模型融合高时间分辨率的MODIS数据与中等空间分辨率的Landsat TM数据,获取融合时间特征的Landsat TM时序数据,基于作物物候特征提取水稻的种植面积,并与单时相Landsat TM影像分类结果进行对比分析。结果表明,基于时序Landsat NDVI数据的水稻作物分类精度较之单时相Landsat TM影像分类结果有较大的提高。 相似文献
8.
Landsat长时间序列数据格式统一与反射率转换方法实现 总被引：1，自引：0，他引：1
介绍了一种长时间序列遥感影像预处理程序,即陆地卫星生态系统干扰自适应处理系统(landsat ecosystem disturbance adaptive processing system,LEDAPS)。该程序通过使用MODTRAN太阳能输出模型,校正太阳方位、日地距离、TM或ETM+带通以及太阳辐照度,将定标影像转换为表观(top-of-atmosphere,TOA)反射率影像,并将通过浓密植被(dark dense vegetation,DDV)算法插值生成的气溶胶光学厚度(aerosol optical thickness,AOT)以及通过相关资料获得的臭氧(O3)浓度、大气压及水汽值等用于6S辐射传输模型,生成地表反射率产品。以LEDAPS可处理的标准数据Landsat7 ETM+和统一格式后的非标准数据Landsat5 TM影像为例,介绍了长时间(1987—2011年)序列数据的选择、格式统一以及算法的实现过程,同时给出了校正后影像效果评价的方法。结果表明,标准数据和非标准数据经过LEDAPS处理后生成的地表反射率产品能有效降低大气中O3、水汽及气溶胶等对影像真实反射率的影响,为土地覆盖变化和干扰因素等的长时间序列监测和生物物理参数的遥感反演提供科学产品,有助于在国内形成处理长时间序列影像数据的准则。 相似文献
9.
中国陆域1∶100万植被指数UNVI（Universal Normalized Vegetation Index）多维数据集（2017）是在分析MODIS地表反射率产品数据MOD09GA特点,参照传统的植被指数合成算法,为了满足植被长时间序列变化研究需要而生成的16 d合成UNVI数据集。本研究合成的UNVI数据集在反映植被密度、植被覆盖度、植被光合作用速率,以及反演植被理化参数方面,与传统的NDVI和EVI合成数据集相比,具有明显的优势。合成算法主要分为两步：首先对16 d合成周期内存在无效值和反射率负值的MODIS数据进行筛选处理;然后读取合成周期内的质量控制波段数据统计“无云”数据的天数,并根据“无云”数据的天数选择相应合成算法进行UNVI的16 d合成,从而获得2017年中国陆域时间分辨率为16 d,空间分辨率约为0.00286°的UNVI时间序列影像。基于本文提出的合成算法生成的中国陆域UNVI数据集,采用1∶100万标准经纬线分幅,共64景（Tile）,每景所覆盖的经纬度范围为6°×4°,为方便起见,数据集采用MDD多维数据格式（Multi-Dimensional Dataset）存储,每个.mdd文件下存放每景2017年所有时相的影像数据。同时为便于数据下载,全部数据按照分幅压缩为64个.zip文件,压缩后的数据量约为3.78 GB。本数据集能为从事全球变化研究的科研人员提供更方便的植被指数长时间序列数据产品。 相似文献
10.
融合Landsat ETM+和MODIS数据估算高时空分辨率地表短波反照率 总被引：2，自引：0，他引：2
提出一种通过融合高空间低时间分辨率、低空间高时间分辨率地表短波反照率,来估算高时空分辨率地表短波反照率的方法。首先,利用Landsat ETM+数据,通过窄波段到宽波段的转换得到一景或多景空间分辨率较高的ETM+蓝天空短波反照率;然后,在MODIS短波反照率产品基础上,以天空光比例因子为权重,得到空间分辨率较低的MODIS蓝天空短波反照率;最后,利用STARFM(Spatial and Temporal Adaptive Reflectance Fusion Model)模型融合ETM+短波反照率的空间变化信息和MODIS短波反照率的时间变化信息,得到高时空分辨率的地表短波反照率。针对STARFM模型在异质性区域估算精度降低的问题,通过以MODIS反照率影像各像元的端元(各地类)反照率取代MODIS像元反照率来提取时空变化等信息参与STARFM模型的融合过程,达到提高异质性区域估算精度的目的。结果显示,直接利用STARFM模型估算得到的高空间分辨率地表短波反照率处在合理的精度范围内(RMSE0.02),用改进后的STARFM模型估算得到的异质性区域短波反照率和真实ETM+短波反照率间的相关系数增大。 相似文献
11.
《International Journal of Digital Earth》2013,6(6):157-171
The Moderate Resolution Imaging Spectroradiometer (MODIS)-Terra surface reflectance product (MOD09A1), with bands 1 to 7, is a gridded, eight-day composite product derived from the MODIS-Terra top of atmosphere reflectance swaths. It performs cloud detection and corrects for the effects of atmospheric gases and aerosols. The cloud mask (CM) algorithms for MODIS are based on empirical thresholds on spectral reflectance and brightness temperature. Since the spatial resolution of the thermal band is 1000 m, while that of MOD09A1 is 500 m, many undetected and false clouds are observed in MOD09A1. These errors always result in temporal and spatial inconsistencies in higher-level products. In this paper, a cloud detection algorithm (TSCD) based on a MOD09A1 time series is introduced. Time series cloud detection (TSCD) algorithm is based on the relative stability of ground reflectance and the sudden variations in reflectance that result from cloud cover. The algorithm first searches the clear-sky reference data, and then discriminates clouded and unclouded pixels by detecting a sudden change of reflectance in the blue wavelength and spectral correlation coefficient at the pixel level. Compared with cloud cover assessments obtained from MODIS' original CM, TSCD provides similar or better discrimination in most situations when the land surface changes slowly. 相似文献
12.
Pavel Propastin Stefan Erasmi 《International Journal of Applied Earth Observation and Geoinformation》2010
A time series of leaf area index (LAI) has been developed based on 16-day normalized difference vegetation index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m resolution (MOD250_LAI). The MOD250_LAI product uses a physical radiative transfer model which establishes a relationship between LAI, fraction of vegetation cover (FVC) and given patterns of surface reflectance, view-illumination conditions and optical properties of vegetation. In situ measurements of LAI and FVC made at 166 plots using hemispherical photography served for calibration of model parameters and validation of modelling results. Optical properties of vegetation cover, summarized by the light extinction coefficient, were computed at the local (pixel) level based on empirical models between ground-measured tree crown architecture at 85 sampling plots and spectral values in Landsat ETM+ bands. Influence of view-illumination conditions on optical properties of canopy was simulated by a view angle geometry model incorporating the solar zenith angle and the sensor viewing angle. The results revealed high compatibility of the produced MOD250_LAI data set with ground truth information and the 30 m resolution Landsat ETM+ LAI estimated using the similar algorithm. The produced MOD250_LAI was also compared with the global MODIS 1000-m LAI product (MOD15A2 LAI). Results show good consistency of the spatial distribution and temporal dynamics between the two LAI products. However, the results also showed that the annual LAI amplitude by the MOD15A2 product is significantly higher than by the MOD250_LAI. This higher amplitude is caused by a considerable underestimation of the tropical rainforest LAI by the MOD15A2 during the seasonal phases of low leaf production. 相似文献
13.
Dengsheng Lu Guiying Li Emilio Moran Mateus Batistella Corina C. Freitas 《ISPRS Journal of Photogrammetry and Remote Sensing》2011,66(6):798-808
This research explored the integrated use of Landsat Thematic Mapper (TM) and radar (i.e., ALOS PALSAR L-band and RADARSAT-2 C-band) data for mapping impervious surface distribution to examine the roles of radar data with different spatial resolutions and wavelengths. The wavelet-merging technique was used to merge TM and radar data to generate a new dataset. A constrained least-squares solution was used to unmix TM multispectral data and multisensor fusion images to four fraction images (high-albedo, low-albedo, vegetation, and soil). The impervious surface image was then extracted from the high-albedo and low-albedo fraction images. QuickBird imagery was used to develop an impervious surface image for use as reference data to evaluate the results from TM and fusion images. This research indicated that increasing spatial resolution by multisensor fusion improved spatial patterns of impervious surface distribution, but cannot significantly improve the statistical area accuracy. This research also indicated that the fusion image with 10-m spatial resolution was suitable for mapping impervious surface spatial distribution, but TM multispectral image with 30 m was too coarse in a complex urban–rural landscape. On the other hand, this research showed that no significant difference in improving impervious surface mapping performance by using either PALSAR L-band or RADARSAT C-band data with the same spatial resolution when they were used for multi-sensor fusion with the wavelet-based method. 相似文献
14.
基于遥感的长沙市城市热岛与土地利用/覆盖变化研究 总被引：9，自引：0，他引：9
基于多时相Landsat TM/ETM+影像,首先计算长沙市地表亮度温度,然后利用NDVI(归一化植被指数)、MNDWI(改进
的归一化水体指数)、NDBI(归一化建筑指数)和NDBaI(归一化裸土指数)4个指数,采用决策树分类方法对长沙市影像进行
土地利用/覆盖分类。在此基础上,对长沙市城市热岛的空间分布特征、时空演变特征以及城市热岛与土地利用/覆盖变化和各种影
响因子之间的关系进行研究。结果表明,随着长沙市城区范围的不断扩张,城市热岛范围也不断增大; 土地利用/覆盖类型的变化
会改变地表温度的空间分布,城市用地和裸地是城市热岛强度的主要贡献因素,水体和林地具有较好的降温作用。地表温度与4种
归一化指数的回归分析表明,它们之间存在明显的相关性,不同土地利用/覆盖类型的地表温度存在较大差异。 相似文献
15.
Snow-covered area (SCA) is a key variable in the Snowmelt-Runoff Model (SRM) and in other models for simulating discharge from snowmelt. Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM + ) or Operational Land Imager (OLI) provide remotely sensed data at an appropriate spatial resolution for mapping SCA in small headwater basins, but the temporal resolution of the data is low and may not always provide sufficient cloud-free dates. The coarser spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) offers better temporal resolution and in cloudy years, MODIS data offer the best alternative for mapping snow cover when finer spatial resolution data are unavailable. However, MODIS’ coarse spatial resolution (500 m) can obscure fine spatial patterning in snow cover and some MODIS products are not sensitive to end-of-season snow cover. In this study, we aimed to test MODIS snow products for use in simulating snowmelt runoff from smaller headwater basins by a) comparing maps of TM and MODIS-based SCA and b) determining how SRM streamflow simulations are changed by the different estimates of seasonal snow depletion. We compared gridded MODIS snow products (Collection 5 MOD10A1 fractional and binary SCA; SCA derived from Collection 6 MOD10A1 Normalised Difference Snow Index (NDSI) Snow Cover), and the MODIS Snow Covered-Area and Grain size retrieval (MODSCAG) canopy-corrected fractional SCA (SCAMG), with reference SCA maps (SCAREF) generated from binary classification of TM imagery. SCAMG showed strong agreement with SCAREF; excluding true negatives (where both methods agreed no snow was present) the median percent difference between SCAREF and SCAMG ranged between −2.4% and 4.7%. We simulated runoff for each of the four study years using SRM populated with and calibrated for snow depletion curves derived from SCAREF. We then substituted in each of the MODIS-derived depletion curves. With efficiency coefficients ranging between 0.73 and 0.93, SRM simulation results from the SCAMG runs yielded the best results of all the MODIS products and only slightly underestimated discharge volume (between 7 and 11% of measured annual discharge). SRM simulations that used SCA derived from Collection 6 NDSI Snow Cover also yielded promising results, with efficiency coefficients ranging between 0.73 and 0.91.In conclusion, we recommend that when simulating snowmelt runoff from small basins (<4000 km2) with SRM, we recommend that users select either canopy-corrected MODSCAG or create their own site-specific products from the Collection 6 MOD10A1 NDSI. 相似文献
16.
Many real-world applications require remotely sensed images at both high spatial and temporal resolutions. This requirement, however, is generally not met by single satellite system. A number of spatiotemporal fusion models have been developed to overcome this constraint. Landsat and Visible Infrared Imaging Radiometer Suite (VIIRS) data have been extensively used for detection and monitoring of active fires at different scales. Fusing the data obtained from these sensors will, therefore, significantly contribute to the satellite-based monitoring of fires. Among the available spatiotemporal fusion methods, the spatial and temporal adaptive reflectance fusion model (STARFM) and enhanced STARFM (ESTARFM) algorithms have been widely used for studying the land surface dynamics in the homogeneous and heterogeneous regions. The present study explores the applicability of STARFM and ESTARFM algorithms for fusing the high spatial resolution Landsat-8 OLI data with high temporal resolution VIIRS data in the context of active surface coal fire monitoring. Further, a modified version of ESTARFM algorithm, referred as modified-ESTARFM, is developed to improve the performance of the fusion model. Jharia coalfield (India), known for widespread occurrences of coal fires, is taken as the study area. The qualitative and quantitative assessments of the predicted (synthetic) Landsat-like images from different algorithms (STARFM, modified-STARFM, ESTARFM, modified-ESTARFM) indicate that the modified-ESTARFM outperforms the other fusion approaches used in this study. Considering the advantages, limitations and performance of the algorithms used, modified-ESTARFM along with STARFM can be used for surface coal fire monitoring. The study will not only contribute to remote sensing based coal fire studies but also to other applications, such as forest fires, crop residue burning, land cover and land use change, vegetation phenology, etc. 相似文献
17.
利用Landsat TM数据和地面观测数据验证GLASS反照率产品 总被引：1，自引：0，他引：1
Global LAnd Surface Satellite Products System(GLASS)反照率产品基于Angular Bin(AB)算法,仅使用单一观测角度的地表或大气层顶反射率数据就能较为准确地反演地表宽波段反照率,具有较高的时间分辨率,可以反映降雪、融雪、收割等状况下地表反照率的快速变化。遵循"一检两恰"的验证流程对这一反照率产品进行验证,首先使用FLUXNET站点验证数据对AB算法反演的Landsat Thematic Mapper(TM)高分辨地表反照率数据进行验证,再将TM高分辨反照率聚合到GLASS像元尺度对GLASS反照率产品进行验证。挑选FLUXNET的5个站点,筛选无云条件下的TM高分辨率影像,共获得103组有效验证数据。验证结果表明,GLASS反照率产品具有较高的精度,总体误差约为0.0163,可以满足大多数应用的精度需求。 相似文献
18.
19.
作为驱动地表与大气之间能量交换的关键物理量,地表温度在众多领域中都发挥着重要作用,包括气候变化、环境监测、蒸散发估算以及地热异常勘探等。Landsat热红外数据因其时间连续性和高空间分辨率等特点被广泛应用于地表温度反演中。本文详细地介绍了Landsat热红外传感器及其可用的数据与产品的现状,梳理了2001年—2020年20年间基于Landsat热红外数据的地表温度遥感反演与应用的相关文献发表及互引情况,系统地综述了基于Landsat热红外数据的地表温度反演算法,包括基于辐射传输方程的算法、单窗算法、普适性单通道算法、实用单通道算法和分裂窗算法等。在此基础上,进一步介绍了每种算法的参数化方案,包括地表比辐射率和大气参数的估算方法。最后针对Landsat热红外数据地表温度遥感反演提出了未来可能的发展趋势与研究方向。 相似文献