共查询到19条相似文献，搜索用时 744 毫秒
1.
北京地区冬小麦冠层光谱数据与叶面积指数统计关系研究 总被引：4，自引：1，他引：3
以北京地区冬小麦为研究对象,利用TM传感器的光谱响应函数处理地面测量获得的冬小麦冠层光谱数据,得到对应于TM传感
器红光波段和近红外波段的反射率,进而计算出冬小麦冠层的归一化植被指数NDVI。建立了LAI与NDVI之间的不同经验关
系模型,对实验结果进行分析后得出,LAI与NDVI之间具有高度的指数相关性。 相似文献
2.
利用HR-768型便携式光谱仪,测定了不同大豆残茬覆盖度下的地面光谱,利用照相法获取对应的大豆残茬覆盖度。采用线性回归方法分析了单波段反射率、反射率一阶导数、归一化指数、比值指数与大豆残茬覆盖度的相关性,获取了不同覆盖度水平下大豆残茬的光谱响应特征,并结合MODIS、TM、HJ-1B星的波段响应函数建立了大豆残茬覆盖度最优估算模型。结果表明,在2050—2150nm和2250—2350nm两个波段范围内,大豆残茬与裸土的光谱差异最显著,可用于二者的区分;大豆残茬的光谱特征与玉米、小麦残茬的光谱特征相似,仅在920—967nm范围内存在特殊的吸收峰;以高光谱数据为数据源,941.6nm处的反射率、2151.8nm处反射率一阶导数、1461.3nm和2404.4nm反射率构建的归一化指数以及2247nm和608.6nm反射率构建的比值指数适宜用于作物残茬覆盖度估算,以宽波段数据为数据源,短波红外与红波段反射率构建的比值指数适宜用于大豆残茬覆盖度估算。 相似文献
3.
为拓展天绘一号多光谱数据定量化应用,本文采用基于准不变反射率目标物的交叉定标法,以HJ1ACCD2作为参考传感器,对天绘一号多光谱数据进行交叉定标处理。首先利用大气辐射传输模型(MODTRAN)对已知辐射定标系数的HJ1A-CCD2数据进行反射率反演,计算待定标数据相同准不变目标物的辐亮度,建立待定标数据辐亮度与DN值之间的线性关系得到辐射定标系数,并利用MODTRAN对天绘一号多光谱数据进行大气校正。对比准不变目标物光谱曲线,水体在红、近红外波段差异较大,裸露地和建筑物屋顶在4个波段吻合较好。误差分析结果表明除蓝波段外,准不变目标物在其他几个波段的相对误差均小于5%。 相似文献
4.
地表覆盖分类数据对区域森林叶面积指数反演的影响 总被引：2，自引：0，他引：2
以江西省吉安市为研究区,将5种全球地表覆盖分类数据(包括美国地质调查局(USGS)、马里兰大学(UMD)和波士顿大学(BU)生成的3套数据和欧洲生成的2套数据)以及由TM影像生成的区域地表覆盖分类数据,分别与MODIS1km反射率资料结合,利用基于4尺度几何光学模型的LAI反演方法生成研究区的LAI。在1km和4km两种尺度上将反演的LAI与TM资料生成的LAI进行比较,评价地表覆盖分类数据对LAI反演结果的影响。结果表明,TM和欧洲太空局的GLOBCOVER地表覆盖分类数据用于反演LAI的结果较好,在1km尺度上,反演的LAI与统计模型估算的TMLAI相关的R2分别为0.44和0.40,在4km尺度上的R2分别为0.57和0.54;其次为波士顿大学的MODIS地表覆盖分类数据,据其反演的LAI与TMLAI相关的R2在1km和4km尺度上分别为0.38和0.51;而马里兰大学的UMD和欧洲的GLC2000地表覆盖分类数据会导致反演的LAI存在较大误差,据其反演的LAI与TMLAI之间的一致性较差,在1km和4km两种尺度上平均偏低20%左右;LAI的反演结果对聚集度系数具有强的敏感性。该研究表明,为了提高区域/全球LAI反演精度,需要有高质量的地表覆盖分类数据。 相似文献
5.
利用4种地表类型共16个地面站点的MISR 9个角度反射率数据产品和MODIS反射率数据产品(MOD09A1), 对比两种传感器获取的地表方向反射观测数据和用BRDF模型参数产品计算的方向反射数据, 分析了这两种BRDF模型参数的外推能力。研究结果表明: (1) MISR和MODIS BRDF模型参数数据产品都具有一定的对观测数据以外方向反射的外推能力, 相比用MISR BRDF模型参数数据外推到相应MODIS观测角度方向反射的结果一致性较强。(2) 采用两种BRDF模型参数推算的方向反射率与观测数据的接近程度有随观测天顶角的增大而减弱的趋势, 在观测天顶角较小时一致性较好。(3) 所用数据处理结果显示, MODIS BRDF模型参数数据产品在近垂直主平面方向反射率推算结果相比近主平面方向的推算结果更接近观测数据。 相似文献
6.
7.
联合HJ-1/CCD和Landsat8/OLI数据反演黑河中游叶面积指数 总被引：1，自引：0，他引：1
目前制约30 m分辨率地表参数遥感提取的主要因素是有限的观测个数,而联合多传感器观测是提高单位时间观测频次的一个有效途径。本文以黑河中游为研究区,利用HJ-1/CCD和Landsat 8/OLI传感器构建多传感器观测数据集。对多传感器观测数据集在观测周期内的有效观测个数、观测角度和双向反射分布函数BRDF分布特征、以及经过预处理后的多传感器数据一致性等问题进行分析。不同传感器观测数据质量差异是多传感器联合反演的主要问题,因此本文首先制定了多传感器数据质量控制方案,然后利用统一模型查找表反演单传感器叶面积指数LAI结果,对10天观测周期内经过质量筛选的单传感器反演结果采用平均方法合成LAI产品。结果表明,LAI有效反演像元占总反演像元比例由单传感器的6.4%—49.7%提高到多传感器的75.9%。利用地面测量数据进行验证分析,LAI反演结果与地面实测数据的均方根误差RMSE均值为0.71。利用30 m分辨率的HJ-1/CCD和Landsat 8/OLI传感器数据可以生产精度可信、时间分辨率连续的LAI产品。 相似文献
8.
环境星CCD数据大气校正研究 总被引：1，自引：0，他引：1
利用6S模型和同步气象资料,对国产环境与灾害监测预报小卫星HJ-1 A的CCD1传感器数据进行了大气校正和反射率反演。同时对CCD1传感器1～4波段大气校正前后的反射率变化进行了对比研究,发现大气校正后的1～3波段的地面反射率明显降低,4波段的地面反射率升高;利用同步野外实测地面数据对大气校正后的反射率数据进行了检验,两者结果基本一致;此外,还进行了定量化误差分析,以同步野外实测地面数据作为标准,将大气校正后的反射率数据与之对比,分析了可能带来误差的原因。结果表明,利用6S大气校正方法能够有效去除HJ-1 A星CCD图像的大气影响,获取地物绝对反射率。 相似文献
9.
目前, 针对太湖水体的叶绿素波段敏感性的分析, 大多集中在实测的高光谱反射率数据或者图像提取反射率与叶绿素浓度的统计分析结果上, 缺乏基于水体光学特性的研究, 并且两者之间的一致性也一直缺少论证。研究中采用2004 年4 月和2007 年8 月的两期数据, 首先从水质参数的生物光学特性入手, 基于生物光学模型, 利用叶绿素和其他水质参数的吸收和后向散射系数, 模拟计算其他水质参数不变, 叶绿素浓度处于不同水平时的水面反射率, 分析实测反射率对叶绿素浓度变化的响应; 利用MODIS 的波段响应函数把实测光谱模拟成宽波段的MODIS 反射率, 以此作为桥梁进而对实测的高光谱反射率和MODIS 图像提取反射率与叶绿素浓度的相关程度的一致性进行分析, 为利用MODIS 图像进行水质参数反演时的反演因子选择提供了依据。 相似文献
10.
《武汉大学学报(信息科学版)》2016,(11)
以贡嘎山地区为研究区,选取HJ-1BCCD2和SPOT4HRVIR为数据源,结合地面同步实测数据,分别采用植被指数法和主成分分析法对森林地上生物量进行估算,并基于交叉验证的方法对比分析了两种传感器估算贡嘎山森林地上生物量的效果:针对单一植被指数,基于比值植被指数构建的生物量反演模型明显优于其他植被指数,且HJ-1BCCD2的表现好于SPOT4HRVIR;在联合多种植被指数建立的生物量反演模型方面,两种数据源的估算能力基本相当,交叉验证的相关系数分别为0.545 8和0.563 4,均方根误差分别为27.811 4t·ha和27.169 6t·ha;主成分分析法则为HJ-1BCCD2传感器的表现优于SPOT4HRVIR。 相似文献
11.
A time series of leaf area index (LAI) of a managed birch forest in Germany (near Dresden) has been developed based on 16-day normalized difference vegetation index (NDVI) data from the Landsat ETM+ sensor at 30 m resolution. The Landsat ETM+ LAI was retrieved using a modified physical radiative transfer (RTM) model which establishes a relationship between LAI, fractional vegetation cover (fC), and given patterns of surface reflectance, view-illumination conditions and optical properties of vegetation. In situ measurements of photosynthetically active radiation (PAR) and vegetation structure parameters using hemispherical photography (HSP) served for calibration of model parameters, while data from litter collection at the study site provided the ground-based estimates of LAI for validation of modelling results. 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. Effects of intra-annual and inter-annual variability of structural properties of the canopy on the light extinction coefficient were simulated by implementing variability of the leaf inclination angle (LIA), which was confirmed in the study site. The results revealed good compatibility of the produced Landsat ETM+ LAI data set with the litter-estimated LAI. The results also showed high sensitivity of the LAI retrieval algorithm to variability of structural properties of the canopy: the implementation of LIA dynamics into the LAI retrieval algorithm significantly improved the model accuracy. 相似文献
12.
M. R. Pandya R. P. Singh K. N. Chaudhari K. R. Murali A. S. Kirankumar V. K. Dadhwal J. S. Parihar 《Journal of the Indian Society of Remote Sensing》2007,35(4):333-350
This paper reports the results of a modeling study carried out with two objectives, (1) to estimate and compare effective spectral characteristics (central wavelength, bandwidth and bandpass exo-atmospheric solar irradiance Eo) of various spectral channels of LISS-III, WiFS, LISS-III*, LISS-IV and AWiFS onboard Indian Remote Sensing Satellites IRS-ID and P6 using moment method based on the laboratory measurements of sensor spectral response, and (2) to quantify the influence of varying sensor spectral response on reflectance and Normalized Difference Vegetation Index (NDVI) measurements using surface reflectance spectra corresponding to different leaf area index conditions of crop target obtained through field experiment. Significant deviation of 4 to 14 nm in central wavelength and 1.6 to 14.07 nm in spectral width was observed for the corresponding channel of IRS sensors. Coefficient of variation of the order of 0.1 to 1.11% was noticed in Eo among various IRS sensors, which could induce a difference of 0.72 to 3.35% in the estimation of top of atmosphere reflectance for crop target. The variation in spectral response of IRS sensors implied a relative difference of the order of 0.91 to 3.38% in surface reflectance and NDVI measurements. Polynomial approximations are also provided for spectral correction that can be utilized for normalizing the artifacts introduced due to differences in spectral characteristics among IRS sensors. 相似文献
13.
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
14.
植被结构及太阳／观测角度对NDVI的影响 总被引：1，自引：0，他引：1
在文献［１］中作者建立了计算多组分植被方向反射系数（ＢＲＦ）的综合解析模型。本文采用该模型研究植被空间结构对常用的归一化植被指数（ＮＤＶＩ）的影响，文中讨论了ＮＤＶＩ与叶（或植被其它组分）角分布（ＬＡＤ）、植被组分（如叶片）的特征尺度和它们在空间的散布方式，以及非叶器官面积在总面积中所占比例间的依赖关系，同时给出了ＮＤＶＩ随太阳／观测角度的变化情况。结果表明即使在叶面积指数（ＬＡＩ）固定不变时，冠层结构及植被组分光学性质的空间非均匀性对ＮＤＶＩ的大小及角分布也有十分显著的影响。通常ＮＤＷ随角度的变化是很大的，如果植被不同组分的光学性质差异很大，且事先不知道它们的空间散布方式时，那么利用ＤＮＶＩ就无法准确地估算出ＬＡＩ。但是对于组分随机分布的植被，利用远离“热点”区域的光谱资料可以使冠层其它结构参数的影响减至最小。 相似文献
15.
Recent studies in Amazonian tropical evergreen forests using the Multi-angle Imaging SpectroRadiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) have highlighted the importance of considering the view-illumination geometry in satellite data analysis. However, contrary to the observed for evergreen forests, bidirectional effects have not been evaluated in Brazilian subtropical deciduous forests. In this study, we used MISR data to characterize the reflectance and vegetation index anisotropies in subtropical deciduous forest from south Brazil under large seasonal solar zenith angle (SZA) variation and decreasing leaf area index (LAI) from the summer to winter. MODIS data were used to observe seasonal changes in the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Topographic effects on their determination were inspected by dividing data from the summer to winter and projecting results over a digital elevation model (DEM). By using the PROSAIL, we investigated the relative contribution of LAI and SZA to vegetation indices (VI) of deciduous forest. We also simulated and compared the MISR NDVI and EVI response of subtropical deciduous and tropical evergreen forests as a function of the large seasonal SZA amplitude of 33°. Results showed that the MODIS-MISR NDVI and EVI presented higher values in the summer and lower ones in the winter with decreasing LAI and increasing SZA or greater amounts of canopy shadows viewed by the sensors. In the winter, NDVI reduced local topographic effects due to the red-near infrared (NIR) band normalization. However, the contrary was observed for the three-band EVI that enhanced local variations in shaded and sunlit surfaces due to its strong dependence on the NIR band response. The reflectance anisotropy of the MISR bands increased from the summer to winter and was stronger in the backscattering direction at large view zenith angles (VZA). EVI was much more anisotropic than NDVI and the anisotropy increased from the summer to winter. It also increased from the forward scatter to the backscattering direction with the predominance of sunlit canopy components viewed by MISR, especially at large VZA. Modeling PROSAIL results confirmed the stronger anisotropy of EVI than NDVI for the subtropical deciduous and tropical evergreen forests. PROSAIL showed that LAI and SZA are coupled factors to decrease seasonally the VIs of deciduous forest with the first one having greater importance than the latter. However, PROSAIL seasonal variations in VIs were much smaller than those observed with MODIS data probably because the effects of shadows in heterogeneous canopy structures or/and cast by emergent trees and from local topography were not modeled. 相似文献
16.
不同传感器的模拟植被指数对水稻叶面积指数的估测精度和敏感性分析 总被引：5，自引：0，他引：5
本研究利用水稻冠层高光谱数据,模拟NOAA-AVHRR,Terra-MODIS和Landsat-TM的可见光波段反射率数据,计算各传感器的多种植被指数(NDVI,RVI,EVI,GNDVI,GRVI和Red-edge RVI),比较植被指数模型对水稻LAI的估测精度,分析不同植被指数对LAI变化的敏感性.相对于红波段植被指数,红边比值植被指数(Red-edge RVI)和绿波段指数GRVI与LAI有更好的线性相关关系,而GNDVI和LAI呈现更好的对数相关关系.MODIS的Red-edge RVI指数不仅模型拟合的精度最高,还有独立数据验证的估测精度也最高,而且它的验证精度较拟合精度下降幅度最小;其次是绿波段构建的GNDVI和GRVI植被指数的估测精度,再次是NDVI和EVI的估测精度,而RVI的估测精度最差.敏感性分析发现,13个植被指数对水稻LAI的估测能力都随着LAI的增加而下降,但归一化类植被指数和比值类植被指数对LAI变化反应的差异明显,归一化类植被指数在LAI较低时(LAI<1.5)对LAI变化的反应开始非常敏感,但迅速下降,而比值类植被指数在LAI较低时,明显小于归一化类植被指数,之后随着LAI的增大(LAI>1.5)比值类植被指数对LAI的变化敏感性,则明显高于归一化类植被指数.Red-edge RVI和绿波段指数GRVI和LAI不仅表现了很好的线性相关关系,而且在LAI大于2.9左右保持较高的敏感性. 相似文献
17.
D. Barman V. K. Sehgal R. N. Sahoo S. Nagarajan 《Journal of the Indian Society of Remote Sensing》2010,38(1):35-44
The algorithms for deriving vegetation biophysical parameters rely on the understanding of bi-directional interaction of radiation
and its subsequent linkages with canopy radiative transfer models and their inversion. In this study, an attempt has been
made to define the geometry of sensor and source position to best relate plant biophysical parameters with bidirectional reflectance
of wheat varieties varying in canopy architecture and to validate the performance of PROSAIL (PROSPECT+SAIL) canopy radiative
transfer model. A field experiment was conducted with two wheat cultivars varying in canopy geometry and phenology. The bidirectional
measurements between 400nm–1100nm at 5nm interval were recorded every week at six view azimuth and four view zenith positions
using spectro-radiometer. Canopy biophysical parameters were recorded synchronous to bi-directional reflectance measurements.
The broadband reflectances were used to compute the NDVIs which were subsequently related to leaf area index and biomass.
Results showed that the bidirectional reflectance increased with increase in view zenith from 200 to 600 irrespective of the sensor azimuth. For a given view zenith, the reflectance was observed to be maximum at 1500 azimuth where the difference between the sun and sensor azimuth was least. For sun azimuth of 1600 and zenith of 520, the view geometry defined by 1500 azimuth and 500 zenith corresponded to hotspot position. The measured bidirectional NDVI had significant logarithmic relationship with LAI
and linear relationship with biomass for both the varieties of wheat and maximum correlation of NDVI with LAI and with biomass
was obtained at the hotspot position. The PROSAIL validation results showed that the model simulated well the overall shape
of spectra for all combination of view zenith and azimuth position for both wheat varieties with overall RMSE less than 5
per cent. The hotspot and dark spot positions were also well simulated and hence model performance may be suitable for deriving
wheat biophysical parameters using satellite derived reflectances. 相似文献
18.
《International Journal of Digital Earth》2013,6(5):351-372
This study compares the spectral sensitivity of remotely sensed satellite images, used for the detection of archaeological remains. This comparison was based on the relative spectral response (RSR) Filters of each sensor. Spectral signatures profiles were obtained using the GER-1500 field spectroradiometer under clear sky conditions for eight different targets. These field spectral signature curves were simulated to ALOS, ASTER, IKONOS, Landsat 7-ETM+, Landsat 4-TM, Landsat 5-TM and SPOT 5. Red and near infrared (NIR) bandwidth reflectance were re-calculated to each one of these sensors using appropriate RSR Filters. Moreover, the normalised difference vegetation index (NDVI) and simple ratio (SR) vegetation profiles were analysed in order to evaluate their sensitivity to sensors spectral filters. The results have shown that IKONOS RSR filters can better distinguish buried archaeological remains as a result of difference in healthy and stress vegetation (approximately 1–8% difference in reflectance of the red and NIR band and nearly 0.07 to the NDVI profile). In comparison, all the other sensors showed similar results and sensitivities. This difference of IKONOS sensor might be a result of its spectral characteristics (bandwidths and RSR filters) since they are different from the rest of sensors compared in this study. 相似文献
19.
This research, by use of RS image-simulating method, simulated apparent reflectance images at sensor level and ground-reflectance images of SPOT-HRV, CBERS-CCD Landsat-TM and NOAA14-AVHRR's corresponding bands. These images were used to analyze sensor's differences caused by spectral sensitivity and atmospheric impacts. The differences were analyzed on Normalized Difference Vegetation Index(NDVI). The results showed that the differences of sensors' spectral characteristics cause changes of their NDVI and reflectance. When multiple sensors' data are applied to digital analysis, the error should be taken into account. Atmospheric effect makes NDVI smaller, and atmospheric correction has the tendency of increasing NDVI values. The reflectance and their NDVIs of different sensors can be used to analyze the differences among sensor's features. The spectral analysis method based on RS simulated images can provide a new way to design the spectral characteristics of new sensors. 相似文献