共查询到18条相似文献，搜索用时 125 毫秒
1.
多角度遥感观测是研究植被冠层BRDF (Bidirectional Reflectance Distribution Function)特性的重要手段,但目前对森林冠层进行连续间隔采样的多角度遥感观测及数据较少,热点方向的观测尤为缺乏。本研究基于无人机多角度高光谱成像系统,在主平面上对针叶林冠层以等角度连续间隔采样进行多角度观测,获取了主平面上多角度(包括热点和暗点)高光谱影像,并将观测结果与四尺度几何光学模型模拟结果进行对比分析。多角度观测获取的植被冠层反射率呈现出典型的植被方向反射特征,后向大部分角度观测的冠层反射率高于前向,在热点处出现峰值,在暗点附近方向出现最低值,观测天顶角VZA (View Zenith Angle)较大时表现出明显的"碗边效应"。结果表明:(1)观测的针叶林冠层反射率及BRDF特性与四尺度模型模拟基本一致,但红光波段模拟的热点反射率稍低于观测,前向观测VZA较大时模拟与观测结果差异稍大;(2)冠层结构及叶片光学特性的差异会导致观测到的BRDF特征不同;(3)观测的针叶林冠层BRDF呈现明显的光谱效应,不同波段呈现的各向异性特性不同,红光波段各向异性最强,近红外波段最弱;(4) BRDF的光谱效应差异导致观测到的植被指数也表现出各向异性,NDVI (Normalized Difference Vegetation Index)、PRI (Photochemical Reflectance Index)和MTCI(MERIS Terrestrial Chlorophyll Index)在热点方向最低,EVI (Enhanced Vegetation Index)在热点方向最高。本研究中无人机多角度成像观测提供的角度和高光谱信息,尤其是热点和暗点信息,在地物识别及分类、植被冠层结构反演及碳循环关键参数获取等研究方面具有较好的应用前景,在其它地物反射或热辐射等方向性特性研究中也具有较大的潜力。 相似文献
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半干旱草场的多角度多波段反射率遥感模型 总被引：1，自引：0，他引：1
从几何光学(GO)模型出发,针对半干旱的草场植被,引入了多光谱冠层反射模型MSRM、土壤反射光谱Price模型以及土壤方向性反射Walthall模型,提出一种适用于区域尺度的多角度多波段反射率模型,并采用MISR和MODIS卫星数据进行验证,验证结果表明模型有较好的适用性。这为多角度、多波段遥感数据用于半干旱草场植被的定量研究提供了新的方法。 相似文献
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航天高光谱遥感器CHRIS的水体图像大气校正 总被引：2，自引：0，他引：2
CHRIS(Compact High Resolution Imaging Spectrometer)是欧空局于2001年10月发射的PROBA-1卫星上搭载的探索性高光谱遥感器,它具备高空间分辨率、多角度观测、高光谱成像等特点,为水质遥感监测提供不可多得的数据源。基于卫星遥感图像定量监测水质,一个关键步骤就是进行精确的大气校正,提取水面反射率。相比陆地遥感图像,水面反射率是弱信号,对大气校正的要求更高。6S(Second Simulation of SatelliteSignal in the Solar Spectrum)和MODTRAN(MOderate resolution TRANsmittance code)是两种常用的大气辐射传输模型。本文选取基于6S的REMS(Remote Sensing Environmental Monitoring System)和基于MODT-RAN的ACORN(Atmospheric CORrection Now)两种大气校正软件,对太湖梅梁湾的三景不同成像角度CHRIS图像进行大气校正,将大气校正后的图像水体反射率与地面同步实测水体反射率进行比较分析。结果表明,经过大气校正的CHRIS图像得到的水面反射率与实测反射率波形十分地接近,在全部波长范围内的相关系数达到90%。分析实测的水体反射率角度特征,发现图像的角度特征更明显。三个观测角度下反射率之间的各差值都呈现出在绿光波段较大,在红光和近红外波段偏小的特点,这和实测结果相符。ACORN校正后的图像的角度特征更好地与实测结果吻合。 相似文献
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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
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针对实现卫星对地观测的自适应多模态,需要根据先验判定卫星成像区域内地表覆盖类型及其反射率状况建立与太阳光照条件、地表覆盖类型、反射率相关的成像载荷积分时间、不同压缩比的成像参数设置模型,以选择最优的观测模式的问题,该文以中分辨率成像光谱仪(MERIS)地表反射率影像和GlobCover全球陆地覆盖分类图为数据源,建立了地表覆盖分类图及其反射率影像矢量化处理的技术流程,构建了以冰雪、沙漠、裸土、岩石、农作物、森林、草地、水体等不同地表覆盖类型及其在不同季节蓝、绿、红、近红外波段的地物反射率数据库。以此作为遥感卫星成像任务规划的技术支撑,构建自适应选择最优的观测模式,提升遥感图像的质量。 相似文献
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以古尔班通古特沙漠为研究区,以中分辨率成像光谱仪（MODIS）为遥感数据源,结合ASD FieldSpec准同步实测积雪反射光谱数据对FLAASH大气校正能力进行了评价。研究表明： ①校正后的MODIS各波段积雪反射率与准同步实测积雪反射率波形相似, 在第1～7波段整体相关系数达0.82,表明FLAASH大气校正能极大地提高MODIS地物识别能力; ②校正后的MODIS 第6波段反射率和归一化差值积雪指数（NDSI）与实测雪密度呈线性相关,可用回归拟合构建MODIS雪密度遥感计算模式。 相似文献
7.
高分五号（GF-5）号卫星所搭载的大气多角度偏振探测仪（DPC）能够对地球进行多波段,多角度和的连续观测,其数据对研究全球大气云分布及云辐射反馈作用提供新的视角。本文通法国多角度偏振载荷POLDER（POLarization and Directionality of the Earth’s Reflectances）云检测算法为参考,结合DPC多波段反射率、偏振反射率、表观压强等信息开发了一个适用于DPC的云检测算法。算法主要分为3个部分：首先是阈值方法对云像元进行检测,同时引入表观压强对不同高度的云（如卷云、层积云等）进行进一步的条件约束,然后利用865 nm波段偏振反射率对海表反射的太阳耀斑区进行识别,修正了反射率阈值识别云像元时受到的太阳耀斑干扰。为了验证算法的准确性,利用2018-10-01的MODIS的MOD06云掩码产品与本文云检测算法结果进行定性分析,从目视判读结果可以看出本文云检测结果与MOD06产品具有较高的吻合度;随后又利用2018-10-01—04的CALIPSO-VFM数据与本文云检测结果和MYDO6云掩码产品进行定量分析,分别计算了中低纬度区域（60°N—60°S）的云/晴空像元命中率和云/晴空像元错误预报率,计算结果显示算法云命中率均值相较MYD06云掩码产品高出13.501%的前提下云错误预报率仅高出3.561%,可表明该算法在全球中低纬度区域有着良好的云检测效果。本文提出的云检测算法,可为后续DPC的云参数、水汽、气溶胶等研究提供重要数据支撑。 相似文献
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提出了在HJ-1 CCD自带卫星观测角度数据的基础上,结合卫星自带几何解算参数推算连续像元的太阳天顶角、方位角,并将原始卫星观测角度、推算几何角度数据生成对应四波段合成数据的改进算法,以提高反演数据的精度.结合Kaufman暗目标法和改进算法后对应连续像元几何数据的6S模型调用表,对南宁市中心城区2018年8月、9月、... 相似文献
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研究利用CBERS02B卫星的CCD传感器数据反演陆地气溶胶的方法。采用的方法是暗像元法。具体步骤为: 根据地面采集的植被光谱数据, 结合CCD传感器特点, 建立浓密植被(暗像元)红蓝波段(CCD传感器的第三和第一波段)反射率与地表反射率之间的关系, 确定了暗像元识别的阈值, 讨论气溶胶光学厚度对暗像元识别的影响以及消除这种影响的方法; 利用6S进行辐射传输运算, 构建查找表; 根据CBERS02B卫星的CCD传感器数据, 从查找表插值得到气溶胶光学厚度, 并进行了算法的误差分析。用广西南宁市及北京地区附近的两景数据进行了实际的反演试验, 使用MODIS的气溶胶产品与反演结果进行比对。结果显示, CBERS02B卫星的CCD传感器数据能够较好的反演陆地气溶胶。 相似文献
11.
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
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利用激光雷达和多角度频谱成像仪数据估测森林垂直参数 总被引：3，自引：0，他引：3
植被的结构参数如植被高度、生物量、水平和垂直分布等，是影响陆地与大气能量交换乃至生物圈多样性的重要因素。多数遥感系统虽然可以提供植被水平结构的图像，但是不能提供植被成分垂直分布的信息。大尺度激光雷达仪器如LVIS产生的激光雷达信号，已成功地用于估计树高和森林生物量，然而大多数激光雷达仪器不具备图像能力，只能提供一个区域内的采样数据。其他的遥感数据如多角度高光谱、多频率多时相辐射计或雷达数据，可根据GLAS（Geoscience Laser Altimeter System）采样的测量用来推断出连续的森林结构区域覆盖参数。
MISR（Multi-angle Imaging Spectrometer）对陆表多角度的成像能力，可以通过BRDF的各向异性提供植被的结构信息。结合激光雷达的垂直采样和MISR的图像，区域内乃至全球性的森林空间参数的成像是可能的。ICESat卫星上的GLAS数据、Terra卫星上的MISR数据为区域或全球性森林结构参数提供了可能。本文的研究目的是评估GLAS数据，分析类似于MISR的数据对森林结构参数的估计能力。本文中使用了LVIS、AirMISR和GLAS数据。通过对GLAS树高的测量与GLAS像元内来自LVIS的平均树高对比，发现它们是高度相关的。同时还探讨了多角度频谱成像仪数据预测树高信息的能力，这将在今后区域内森林结构参数映射加以研究。 相似文献
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Rahul Tripathi Rabi N. Sahoo Vinay K. Sehgal R. K. Tomar Debashish Chakraborty S. Nagarajan 《Journal of the Indian Society of Remote Sensing》2012,40(1):19-28
The current development of satellite technology particularly in the sensors like POLDER and MISR, has emphasized more on directional
reflectance measurements (i.e. spectral reflectance of the target measured from different view zenith and azimuth angles)
of the earth surface features mainly the vegetation for retrieval of biophysical parameters at regional scale using radiative
transfer models. This approach being physical process based and uses directional reflectance measurement has been found to
better and more reliable compared to the conventional statistical approach used till date and takes care of anisotropic nature
(i.e. reflectance from the target is different if measured from different view angles) of the target. Keeping this in view
a field experiment was conducted in mustard crop to evaluate the radiative transfer model for biophysical parameter retrieval
through its inversion with the objectives set as (i) to relate canopy biophysical parameters and geometry to its bidirectional
reflectance, (ii) to evaluate a canopy reflectance model to best represent the radiative transfer within the canopy for its
inversion and (iii) to retrieve crop biophysical parameters through inversion of the model. Two varieties of the mustard crop
(Brassica juncea L) were grown with two nitrogen treatments. The bidirectional reflectance data obtained at 5 nm interval
for a range of 400–1100 nm were integrated to IRS LISS–II sensor’s four band values using Newton Cotes Integration technique.
Biophysical parameters like leaf area index, leaf chlorophyll content, leaf length, plant height and average leaf inclination
angle, biomass etc were estimated synchronizing with the bi-directional reflectance measurements. Radiative transfer model PROSAIL model was
validated and its inversion was done to retrieve LAI and ALA. Look Up Table (LUT) of Bidirectional reflectance distribution
function (BRDF) was prepared simulating through PROSAIL model varying only LAI (0.2 interval from 1.2 to 5.4 ) and ALA (5°
interval from 40° to 55°) parameters and inversion was done using a merit function and numerical optimization technique given
by Press et al. (1986). The derived LAI and ALA values from inversion were well matched with observed one with RMSE 0.521
and 5.57, respectively. 相似文献
15.
基于MODIS二向反射分布函数(BRDF)模型参数产品数据,利用4-scale模型建立查找表,以中国东北大兴安岭加格达奇地区为研究区,反演森林背景反射率,并分析不同森林类型二向反射与背景反射率特性及其季节变化。研究结果表明:(1)研究区针叶林和混交林二向反射特征较为相似,夏季阔叶林在红光波段的二向反射率值均低于针叶林和混交林,而在近红外波段则相反;不同森林类型二向反射率均存在明显的季节变化,其中阔叶林二向反射率季节变化最为明显;(2)研究区夏季森林背景反射率在红光波段较低,均在0.1以下,近红外波段背景反射率普遍高于0.3,且空间差异较大;(3)不同森林类型的背景反射率季节变化趋势大致相同,但变化幅度存在差异:阔叶林的背景反射率值季节差异最大,尤其在近红外波段。 相似文献
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Lênio Soares Galvão Flávio Jorge PonzoniVeraldo Liesenberg João Roberto dos Santos 《International Journal of Applied Earth Observation and Geoinformation》2009
CHRIS/PROBA data collected in the Brazilian Amazônia in 4 view angles (−36°, nadir, +36°, +55°) and 62 bands (410–1000 nm range) were evaluated for the discrimination between primary forest and 3 stages of secondary succession after deforestation: initial (SS1; <5 years), intermediate (SS2; 5–15 years) and advanced (SS3; >15 years). Single view angle and multiangular approaches (nadir plus anisotropic information derived from reflectance ratios between view angles) were tested for discrimination. Both approaches used principal components analysis (PCA) applied to pixel spectra representative of each class in order to reduce data dimensionality at each dataset, to enhance separability between the classes, and to provide input variables for multiple discriminant analysis (MDA). The results showed that the off-nadir viewing improved discrimination between the successional stages. Discrimination between SS2 and SS3 was enhanced with PCA at +36° view angle. Primary forest and SS3 presented a more anisotropic behavior than SS2 and SS1, especially in the backward scattering direction (positive view angles) in which great amounts of sunlit canopy components were viewed by the sensor. MDA classification results showed that the multiangular approach produced an overall improvement in the discrimination. From the single (nadir) to the multiangular approach, classification accuracy using a separate set of pixels increased from 83.3% to 98.3% for SS1, 53.3% to 70.0% for SS2, and 58.3% to 76.7% for SS3. The nadir and multiangular classifications were statistically different at a 0.05% level of significance. Kappa statistics increased from 0.63 to 0.82. The results showed that multiangular data can improve the differentiation between primary forest and old stages of natural vegetation regrowth, which have been reported in the literature as the most difficult classes to be mapped in the Amazonian environment. 相似文献
17.
In this study, we tested whether the inclusion of the red-edge band as a covariate to vegetation indices improves the predictive accuracy in forest carbon estimation and mapping in savanna dry forests of Zimbabwe. Initially, we tested whether and to what extent vegetation indices (simple ratio SR, soil-adjusted vegetation index and normalized difference vegetation index) derived from high spatial resolution satellite imagery (WorldView-2) predict forest carbon stocks. Next, we tested whether inclusion of reflectance in the red-edge band as a covariate to vegetation indices improve the model's accuracy in forest carbon prediction. We used simple regression analysis to determine the nature and the strength of the relationship between forest carbon stocks and remotely sensed vegetation indices. We then used multiple regression analysis to determine whether integrating vegetation indices and reflection in the red-edge band improve forest carbon prediction. Next, we mapped the spatial variation in forest carbon stocks using the best regression model relating forest carbon stocks to remotely sensed vegetation indices and reflection in the red-edge band. Our results showed that vegetation indices alone as an explanatory variable significantly (p < 0.05) predicted forest carbon stocks with R2 ranging between 45 and 63% and RMSE ranging from 10.3 to 12.9%. However, when the reflectance in the red-edge band was included in the regression models the explained variance increased to between 68 and 70% with the RMSE ranging between 9.56 and 10.1%. A combination of SR and reflectance in the red edge produced the best predictor of forest carbon stocks. We concluded that integrating vegetation indices and reflectance in the red-edge band derived from high spatial resolution can be successfully used to estimate forest carbon in dry forests with minimal error. 相似文献
18.
The satellite digital vegetation index data has been correlated with the forest growing stock by fitting linear regression models. The goodness of fit was tested. The analysis showed that the vegetation index which is the ratio of reflectance of vegetation in near infrared band to red wave band of electromagnetic spectrum is highly correlated to forest growing stock and the same can be used to predict the volume in remote forest areas for quick assessment purpose. Implications for future forest inventory are discussed. 相似文献