共查询到19条相似文献，搜索用时 156 毫秒
1.
改进Sobol算法支持下的PROSAIL模型参数全局敏感性分析 总被引：2，自引：0，他引：2
定量分析模型参数的敏感性是构建参数反演模型的关键步骤。本文采用改进Sobol全局敏感性分析算法,对PROSAIL模型的输入参数进行全局敏感性分析。结果表明:①在可见光波段430~760 nm范围内,叶绿素含量的总敏感度约为80%;②在近红外波段800~1100 nm范围内,平均叶倾角、叶片干物质含量和LAI是影响冠层反射率的3个最重要的参数;③在短波红外波段1100~2500 nm范围内,叶片含水量逐渐成为影响冠层反射率的主要参数。叶绿素、水和干物质等参数吸收系数的变化及相对大小的不同是造成以上变化的主要原因。该研究可以为植被生化参数的反演提供理论基础。 相似文献
2.
二向反射分布函数包含地表反射的方向性特征信息。研究二向反射分布函数BRDF(Bidirectional Reflectance Distribution Function)形状对植被结构参数的敏感性,有助于理解植被的二向性反射规律,进而反演植被参数。本文耦合双冠层反射率模型和核驱动的罗斯厚核-李氏稀疏互易核模型,利用EFAST全局敏感性分析方法,以各向异性平整指数为BRDF形状变化的衡量指标,研究了不同天空光比例(SKYL)下,各向异性平整指数AFX对植被参数敏感度的变化,以及SKYL=0.1时AFX的敏感性。结果表明:(1)在红波段,上、下层叶面积指数、上层叶绿素含量,以及上层叶倾角分布是AFX的敏感参数,在近红外波段,上、下层叶面积指数LAI是AFX的敏感参数。(2)冠层尺度上的参数敏感度总体大于叶片尺度。(3)晴天时(SKYL=0.1),红波段主敏感度较大的参数分别是上层LAI、上层叶倾角分布和下层叶片结构参数,近红外波段主敏感度较大的参数主要是上、下层LAI。 相似文献
3.
针对三江平原洪河湿地保护区内主要特征植被冠层的叶绿素含量,采用PROSAIL模型从物理角度进行反演。首先将叶面积指数、叶片结构参数、等价水厚度、叶绿素实测含量等一些植被理化参数的实测值输入模型得到模拟光谱数据,然后与实测光谱数据对比验证其准确性。在模型中,通过固定其他参量不变,取叶绿素含量为唯一值时,考察在不同叶面积指数下叶绿素含量对冠层反射率的影响。结果显示,植被冠层叶绿素含量的敏感波段为555nm和720nm。基于PROSAIL模型的叶绿素反演方法较传统的统计模型相比是较好且稳健的方法。 相似文献
4.
基于TM的辐射传输模型反演叶面积指数可行性研究 总被引：4，自引：1，他引：4
基于PROSAIL辐射传输模型，引入土壤反射指数SRI来简化模型，提出直接从反射率计算SRI的方法； 同时，针对不同的植被状况，采取不同波段组合对模型的参数进行敏感性分析，确定自由参数与反演波段组合，提出一种基于不同植被状况的叶面积指数反演策略； 最后，应用遗传算法对模拟的TM光谱反射数据进行实验。结果表明，对于LAI＜3的植被，反演精度较高； 但是对于LAI＞3的植被，反演精度较低，其原因主要是冠层反射对LAI不再敏感。因此，辐射传输模型反演LAI有一定适用范围，只有在此范围内LAI的反演精度才可靠。 相似文献
5.
基于PROSPECT＋SAIL模型的遥感叶面积指数反演 总被引：4，自引：1，他引：4
以PROSPECT+SAIL模型为基础，从物理机理角度反演植被叶面积指数(LAI)。首先，通过FLAASH模型进行大气校正，使得图像像元值表达植被冠层反射率； 然后，根据LOPEX 93数据库和JHU光谱数据库选择植物生化参数和光谱数据，以PROSPECT模型模拟出的植物叶片反射率和透射率作为SAIL模型的输入参数，得到植被冠层反射率，将结果与遥感影像的植被冠层反射率对应，回归出植被LAI； 最后，以地面实测数据对遥感反演数据进行验证，并分析了误差的可能来源。 相似文献
6.
将植物叶片光谱模型PROSPECT、植被冠层光谱模型SAIL与大气辐射传输模型6S进行耦合,模拟不同参数条件下植被星上光谱信息在400～ 900 nm谱段的变化,并分析从地表植物叶片光谱、冠层光谱到卫星入瞳处光谱的过程中,植物叶片的叶肉结构参数、叶绿素含量、干重、叶片含水量和植物冠层的叶面积指数(LAI)、太阳天顶角、气溶胶光学厚度、地表邻近效应以及混合像元等参数对植物光谱的影响.研究结果表明,由大气引起的误差要远大于由植物本身的各种生化参数引起的误差;在叶片尺度上引起反射率发生变化的主要因素是叶绿素含量和叶肉结构参数,含水量的影响非常小,可以忽略;在冠层尺度上引起光谱发生变化的因素主要有LAI和叶片倾角. 相似文献
7.
估算混合植被叶绿素含量的理想波段分析 总被引：2，自引：1，他引：1
应用Lopex数据库评价了19个波谱指数对物种的敏感性, 分析了叶绿素含量与波谱反射率以及波谱导数的相关性, 目的在于探寻对叶绿素含量变化的敏感性, 对物种和叶片结构变化不敏感的理想波段, 应用大尺度遥感数据估算混合植被冠层叶绿素含量。分析结果表明：红边指数对混合植被的叶绿素含量具有较好的指示作用；估算冠层叶绿素含量的理想波段为698—710nm附近较窄的波段范围；对于波谱导数, 估算混合植被叶绿素含量的理想波段范围为720—735nm和535—550nm附近波谱导数。 相似文献
8.
山地叶面积指数反演理论、方法与研究进展 总被引：2，自引：0，他引：2
叶面积指数LAI（Leaf Area Index）是表征叶片疏密程度和冠层结构特征的重要植被参数，在气候变化、作物生长模型以及碳、水循环研究中发挥着重要作用。遥感是获取区域及全球尺度LAI的一个重要手段，当前LAI产品主要基于遥感数据反演得到，但是多数LAI产品算法并未考虑地形特征的影响，导致山地LAI遥感反演精度不确定性大。提高山地LAI遥感反演精度亟需考虑地形因子对冠层反射率的影响，其中山地冠层反射率模型和遥感数据地形校正是提升山地LAI遥感反演精度的关键。本文围绕山地LAI遥感反演理论与方法，综合分析了国内外山地冠层反射率模型和地形校正模型的研究进展，总结了目前山地LAI遥感反演存在的问题，并讨论了未来研究的发展趋势。 相似文献
9.
10.
叶绿素是植被光合作用的主要物质,准确估算叶绿素含量对植被生长健康状况和生态环境研究具有重要意义。本文利用辐射传输机制的PRO4SAIL模型模拟植被冠层光谱,以TM影像为数据源,分析物理模型模拟反射率和遥感影像反射率与叶绿素含量之间的相关性,研究利用多光谱信息定量反演路域植被叶绿素含量的可行性。研究结果表明,植被光谱反射率与叶绿素含量之间有较强的相关性;利用PRO4SAIL模型模拟的冠层反射率反演叶绿素含量具有一定可行性。该研究成果为大面积路域植被冠层叶绿素含量遥感监测提供理论依据与参考。 相似文献
11.
A simulation study has been carried out to investigate the Principal Component Inversion (PCI) technique for the retrieval of leaf area index (LAI). The PROSAIL model has been used for the forward analysis, i.e., estimation of reflectance for various combinations of LAI, soil reflectance, leaf angle distribution (ø1), chlorophyll a+b concentration (Cab), etc. Independent test on sample with LAI range 0.1-7.0 indicated that the retrieved LAI from PCI has higher accuracy (RMSE=0.137) than the classical NDVI-LAI empirical approach (RMSE=1.139). The study needs to be extended to cover retrieval from different types of soil and simultaneous retrieval of different biophysical parameters viz., LAI, Cab, ø1 to test the wider applicability of the PCI technique. 相似文献
12.
Roshanak Darvishzadeh Andrew Skidmore Clement Atzberger Sip van Wieren 《International Journal of Applied Earth Observation and Geoinformation》2008
The retrieval of canopy biophysical variables is known to be affected by confounding factors such as plant type and background reflectance. The effects of soil type and plant architecture on the retrieval of vegetation leaf area index (LAI) from hyperspectral data were assessed in this study. In situ measurements of LAI were related to reflectances in the red and near-infrared and also to five widely used spectral vegetation indices (VIs). The study confirmed that the spectral contrast between leaves and soil background determines the strength of the LAI–reflectance relationship. It was shown that within a given vegetation species, the optimum spectral regions for LAI estimation were similar across the investigated VIs, indicating that the various VIs are basically summarizing the same spectral information for a given vegetation species. Cross-validated results revealed that, narrow-band PVI was less influenced by soil background effects (0.15 ≤ RMSEcv ≤ 0.56). The results suggest that, when using remote sensing VIs for LAI estimation, not only is the choice of VI of importance but also prior knowledge of plant architecture and soil background. Hence, some kind of landscape stratification is required before using hyperspectral imagery for large-scale mapping of vegetation biophysical variables. 相似文献
13.
In this paper, we focused on the retrieval of the LAI in an alpine wetland located in western part of China in late August and early July 2011. A two-layer canopy reflectance model (ACRM) was used to establish the relationships between the LAI and the reflectance of near-infrared (NIR) and red (RED) wavebands. The reflectance data were derived from Landsat TM L1T product and the Terra and Aqua MODIS 16-day and 8-day composite reflectance products (MOD/MYD09) at 250 m resolution. Due to the lack of the information about some major input parameters for ACRM, which are sensitive to model outputs in the reflectance of NIR and RED wavebands, the inverse problem was ill-posed. To overcome this problem, a method of increasing the sensitivity of the LAI while reducing the influence of other model free parameters based on the study of free parameters’ sensitivity to the ACRM outputs and the region’s features was studied. The area of interest was divided into two parts using the approximately statistic normalized difference vegetation index (NDVI) value around 0.5. One part was sparse vegetation (0.1 < NDVI < 0.5), which is more sensitive to soil background effects and less sensitive to the canopy biophysical and biochemical variables. The other part was dense vegetation (0.5 ≤ NDVI < 1.0), which is less sensitive to soil background effects and more sensitive to plant canopies and leaf parameters. Then, the relationships of ρnir–LAI and ρred–LAI were established using a look-up table algorithm for the two parts. Furthermore, a regularization technique for fast pixel-wise retrieval was introduced to reduce the elements of LUT sets while maintaining a relatively high accuracy. The results were very promising compared to the field measured LAI values that the correlation (R2) of the measured LAI values and retrieved LAI values reached 0.95, and the root-mean-square deviation (RMSD) was 0.33 for late August, 2011, while the R2 reached 0.82 and RMSD was 0.25 for early July 2011. 相似文献
14.
Janne Heiskanen Miina Rautiainen Lauri Korhonen Matti Mõttus Pauline Stenberg 《International Journal of Applied Earth Observation and Geoinformation》2011
Spectral invariants provide a novel approach for characterizing canopy structure in forest reflectance models and for mapping biophysical variables using satellite images. We applied a photon recollision probability (p) based forest reflectance model (PARAS) to retrieve leaf area index (LAI) from fine resolution SPOT HRVIR and Landsat ETM+ satellite data. First, PARAS was parameterized using an extensive database of LAI-2000 measurements from five conifer-dominated boreal forest sites in Finland, and mixtures of field-measured forest understory spectra. The selected vegetation indices (e.g. reduced simple ratio, RSR), neural networks and kNN method were used to retrieve effective LAI (Le) based on reflectance model simulations. For comparison, we established empirical vegetation index-LAI regression models for our study sites. The empirical RSR–Le regression performed best when applied to an independent test site in southern Finland [RMSE 0.57 (24.2%)]. However, the difference to the best reflectance model based retrievals produced by neural networks was only marginal [RMSE 0.59 (25.1%)]. According to this study, the PARAS model provides a simple and flexible modelling tool for calibrating algorithms for LAI retrieval in conifer-dominated boreal forests. The advantage of PARAS is that it directly uses field measurements to parameterize canopy structure (LAI-2000, hemispherical photographs) and optical properties of foliage and understory. 相似文献
15.
M. Vohland S. Mader W. Dorigo 《International Journal of Applied Earth Observation and Geoinformation》2010
This study describes the retrieval of state variables (LAI, canopy chlorophyll, water and dry matter contents) for summer barley from airborne HyMap data by means of a canopy reflectance model (PROSPECT + SAIL). Three different inversion techniques were applied to explore the impact of the employed method on estimation accuracies: numerical optimization (downhill simplex method), a look-up table (LUT) and an artificial neural network (ANN) approach. By numerical optimization (Num Opt), reliable estimates were obtained for LAI and canopy chlorophyll contents (LAI × Cab) with r2 of 0.85 and 0.94 and RDP values of 1.81 and 2.65, respectively. Accuracies dropped for canopy water (LAI × Cw) and dry matter contents (LAI × Cm). Nevertheless, the range of leaf water contents (Cw) was very narrow in the studied plant material. Prediction accuracies generally decreased in the order Num Opt > LUT > ANN. This decrease in accuracy mainly resulted from an increase in offset in the obtained values, as the retrievals from the different approaches were highly correlated. The same decreasing order in accuracy was found for the difference between the measured spectra and those reconstructed from the retrieved variable values. The parallel application of the different inversion techniques to one collective data set was helpful to identify modelling uncertainties, as shortcomings of the retrieval algorithms themselves could be separated from uncertainties in model structure and parameterisation schemes. 相似文献
16.
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
17.
In this paper, we carried out a laboratory experiment to study changes in canopy reflectance of Tamarugo plants under controlled water stress. Tamarugo (Prosopis tamarugo Phil.) is an endemic and endangered tree species adapted to the hyper-arid conditions of the Atacama Desert, Northern Chile. Observed variation in reflectance during the day (due to leaf movements) as well as changes over the experimental period (due to water stress) were successfully modelled by using the Soil-Leaf-Canopy (SLC) radiative transfer model. Empirical canopy reflectance changes were mostly explained by the parameters leaf area index (LAI), leaf inclination distribution function (LIDF) and equivalent water thickness (EWT) as shown by the SLC simulations. Diurnal leaf movements observed in Tamarugo plants (as adaptation to decrease direct solar irradiation at the hottest time of the day) had an important effect on canopy reflectance and were explained by the LIDF parameter. The results suggest that remote sensing based assessment of this desert tree should consider LAI and canopy water content (CWC) as water stress indicators. Consequently, we tested fifteen different vegetation indices and spectral absorption features proposed in literature for detecting changes of LAI and CWC, considering the effect of LIDF variations. A sensitivity analysis was carried out using SLC simulations with a broad range of LAI, LIDF and EWT values. The Water Index was the most sensitive remote sensing feature for estimating CWC for values less than 0.036 g/cm2, while the area under the curve for the spectral range 910–1070 nm was most sensitive for values higher than 0.036 g/cm2. The red-edge chlorophyll index (CIred-edge) performed the best for estimating LAI. Diurnal leaf movements had an effect on all remote sensing features tested, particularly on those for detecting changes in CWC. 相似文献
18.
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
19.
Computer simulation models have seldom been applied for estimating the structural and biophysical variables of forest canopy. In this study, an approach for the estimation of leaf area index (LAI) using the information contained in hyperspectral, multi-angle images and the inversion of a computer simulation model are explored. For this purpose, L-systems combined with forest growth model ZELIG were applied to render 3-D forest architectural scenarios. The Radiosity-graphics combined model (RGM) was used to estimate forest LAI from the Compact High-Resolution Imaging Spectrometer/Project for On-Board Autonomy (CHRIS/PROBA) data. LAI inversion was performed using the look-up table (LUT) method. The estimated LAI was evaluated against in situ LAI measurement and compared against the LAI predictions from CHRIS data obtained using the Li-Strahler geometric-optical canopy reflectance model (GOMS). The results indicated that the method used in this study can be efficient strategy to estimate LAI by RGM model inversion. 相似文献