排序方式： 共有18条查询结果，搜索用时 15 毫秒
1.
This paper presents a new approach to estimate spatial Sun-Induced Fluorescence (SIF) using the empirical relationship between simulated Canopy Chlorophyll Concentration (CCC) and simulated SIF. PROSAIL model [PROpriétésSPECTrales (PROSPECT) and Scattering by Arbitrarily Inclined Leaves (SAIL) models] was used to simulate CCC. CCC maps were generated through an Automated Radiative Transfer Model Operator (ARTMO) using the PROSAIL model and Sentinel-2 Multi-Spectral Imager (MSI) imagery. The Soil Canopy Observation, Photochemistry, and Energy fluxes (SCOPE) model was used to simulate SIF emitted at 740 nm (SIF740), at 760 nm (SIF760), and top of canopy (SIFTOC) (640-850 nm). The SCOPE model, configured with the specification of the Sentinel-2 sensor, simulates SIF within the spectrum range of 640-850 nm. A non-linear logarithmic relationship (R2>0.9, p < 0.05) was observed between simulated SIF and simulated CCC. Simulated CCC was linearly related to observed CCC with R2 0.88, 0.92 and 0.89 and RMSE = 0.04, 0.17 and 0.09 gm/m2 at p < 0.05 for summer, post-monsoon and early winter respectively. Whereas, the simulated CCC did not capture the full range of CCC variability for the post-monsoon season. Simulated SIF (SIF760) was well correlated with SIF from Orbiting Carbon Observatory-2 (OCO-2) satellite with R2 0.68, 0.73 and 0.73 (RMSE = <1 W/m2/sr/μm, p < 0.05) for the month of summer (April), pre-monsoon (May) and early winter season (November) respectively. Temporal SIFTOC effectively captured the seasonal variability associated with the phenology of deciduous tree species. Among various Sentinel-2 MSI derived VIs, Red Edge NDVI (RENDVI) exhibited maximum sensitivity with SIF (highest monthly average R2> 0.6, p < 0.05). The spatial SIF would serve as an useful link between airborne /satellite derived SIF and in-situ fluorescence measurements to understand multiscale SIF variability of terrestrial vegetation. 相似文献
2.
Elizabeth J. Botha Brigitte Leblon Bernie Zebarth James Watmough 《International Journal of Applied Earth Observation and Geoinformation》2007,9(4):360-374
Optimizing nitrogen (N) fertilization in crop production by in-season measurements of crop N status may improve fertilizer N use efficiency. Hyperspectral measurements may be used to assess crop N status by estimating leaf chlorophyll content. This study evaluated the ability of the PROSAIL canopy-level reflectance model to predict leaf chlorophyll content. Trials were conducted with two potato cultivars under different N fertility rates (0–300 kg N ha−1). Canopy reflectance, leaf area index (LAI) and leaf chlorophyll and N contents were measured. The PROSAIL model was able to predict leaf chlorophyll content with reasonable accuracy later in the growing season. The low estimation accuracy earlier in the growing season could be due to model sensitivity to non-homogenous canopy architecture and soil background interference before full canopy closure. Canopy chlorophyll content (leaf chlorophyll content × LAI) was predicted less accurately than leaf chlrophyll content due to the low estimation accuracy of LAI for values higher than 4.5. 相似文献
3.
冠层反射光谱对植被理化参数的全局敏感性分析 总被引：1，自引：0，他引：1
植被理化参数与许多有关植物物质能量交换的生态过程密切相关,定量分析植被反射光谱对理化参数的敏感性是遥感反演理化参数含量的前提。本文采用EFAST(Extended Fourier Amplitude Sensitivity Test)全局敏感性分析方法,利用PROSAIL辐射传输模型分析了冠层疏密程度对叶片生化组分含量、冠层结构以及土壤背景等多种参数敏感性的影响,并对植被理化参数反演所需先验知识的精度问题进行了初步探讨。研究表明:(1)对于较为稠密的冠层,可见光波段的冠层反射率主要受叶绿素含量的影响,近红外和中红外波段的冠层反射率主要受干物质量和含水量的影响;(2)对于稀疏的冠层,LAI是影响400—2500 nm波段范围内冠层反射率的最重要参数,土壤湿度次之,叶片生化参数对冠层反射率的敏感性较低;(3)在已知稀疏冠层LAI的情况下进一步确定土壤的干湿状态,可显著提高冠层反射率对叶绿素含量的敏感度,有助于稀疏冠层叶绿素含量的反演。 相似文献
4.
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
5.
植被冠层含水量CWC (Canopy Water Content)和植被地上部分含水量VWC (Vegetation Water Content)对于植被健康状况和土壤干旱监测具有重要意义。本文联合PROSAIL辐射传输模型和植被水分指数NDWI(Normalized Difference Water Index),发展了一种简单、通用性较好的低矮植被CWC和VWC反演方法,可实现中、高空间分辨率下的CWC和VWC估算。首先对PROSAIL模型输入参数进行敏感性分析,明确各参数对模型输出反射率的影响机制,以优化PROSAIL模型输入参数设置并生成低矮植被的反射率模拟数据。基于模拟数据,计算了4个植被水分指数NDWI_((860,1240))、NDWI_((860,1640))、NDWI_((1240,1640))和NDWI_((860,970))用于反演低矮植被CWC和VWC。基于模拟数据的结果表明,4个植被水分指数与ln (CWC)都存在明显的线性关系,基于该关系建立了CWC估算模型。该模型可以直接用于低矮植被CWC估算,并通过VWC与CWC之间的经验关系间接计算得到VWC。模型模拟结果也表明,由于NDWI_((860,1640))和NDWI_((1240,1640))高度相关(R~2=0.99),两者可以提供相似且相对较好的低矮植被CWC估算精度。基于地面实测数据的验证结果与基于模拟数据的结果表现出很好的一致性,即基于NDWI_((860,1640))和NDWI_((1240,1640))估算的VWC都有相似且较高的精度,决定系数(R~2)都为0.88,均方根误差(RMSE)分别为0.4558 kg/m~2和0.4380 kg/m~2。利用Landsat 5 TM数据对NDWI_((860,1640))估算效果的验证结果显示,模型估算CWC与地面实测CWC的R~2为0.84,RMSE为0.1342 kg/m~2,估算VWC的RMSE为0.5651 kg/m~2。本文提出的基于NDWI_((860,1640))和NDWI_((1240,1640))的CWC/VWC估算模型可被用于低矮植被的长势监测和干旱监测,为低矮植被覆盖地表的土壤水分反演提供高质量的植被水分信息。 相似文献
6.
7.
PROSAIL模型模拟下的植被指数土壤调节能力比较与适用环境分析 总被引：1，自引：0，他引：1
为了消除土壤背景信息对植被指数的影响,近几十年发展了土壤调节植被指数系列(SAVI family)。在不同环境条件下,不同指数抗土壤影响的能力不同。在总结了以消除土壤影响为目的的植被指数建立过程的基础上,利用PROSAIL辐射传输模型模拟的两组数据集,比较分析了NDVI、SAVI、TSAVI、MSAVI、OSAVI和GESAVI在不同叶面积指数(LAI)对应不同土壤背景的情况下抗土壤干扰、表达植被信息的能力,指出了不同植被指数应用的最适环境条件。结合植被指数—信噪比图,将这6种植被指数分成3类:在中低LAI值下,若植被覆盖度均匀,OSAVI和TSAVI有较强的消除土壤影响、表达植被信息的能力;当区域LAI分布不均、植被类型混杂时,MSAVI在表达植被信息时具有较好的稳定性。根据每类植被指数的特征,利用MODIS-VI和MODIS-LAI产品初步验证了上述结论的有效性。 相似文献
8.
植被覆盖动态监测及与生态环境变化的响应是陆地生态系统研究的重要内容。本文以不同时相的TM遥感影像为信息源,基于辐射传输模型PROSAIL,定量反演了不同时期高速公路两侧植被的叶面积指数,以反演的叶面积指数作为路域植被生长状况的监测指标,对实验区路域植被的生长状况进行了时空格局变化的动态遥感监测研究。研究表明：① 在时间上,路域植被的生长状况在高速公路开通后5年内受到的影响相对最大;② 在空间上,离高速公路越近的植被的生长状况受到的影响较大,离高速公路越远的植被的生长状况受到的影响较小。本研究为监测路域植被生长状况提供了重要的方法,为指导路域植被的生态恢复与保护提供了可靠的基础。 相似文献
9.
10.
光学与微波植被指数协同反演农作物叶面积指数的可行性分析 总被引：1，自引：0，他引：1
光学遥感是目前反演植被叶面积指数LAI（Leaf Area Index）的主要手段,但是当叶面积指数较大时存在光学遥感信息饱和、反演精度显著降低的问题。叶面积指数和平均叶倾角对光学、微波波段范围内反射和散射特性都有重要影响,主要表现在植被结构参数的变化可以引起冠层孔隙率和消光截面大小的改变。本文以典型农作物玉米为例,通过构建统一的PROSAIL和MIMICS模型输入参数,生成一套玉米全生长期光学二向反射率和全极化微波后向散射系数模拟库和冠层参数库。通过对模拟数据与LAI敏感性和相关性分析得出：（1）光学植被指数MNDVI(800 nm,2000 nm),在LAI为0—3时敏感,基于MNDVI与LAI的回归模型可以估算LAI变化 0.4的情况,RMSE是0.33,R2是0.958。（2）微波植被指数SARSRVI(1.4 GHz HH,9.6 GHz HV),在LAI为3—6时敏感,基于SARSRVI与LAI的回归模型可以估算LAI变化1的情况,RMSE为0.22,R2是0.9839。研究表明,采用分段敏感的植被指数,协同光学和微波遥感反演玉米全生长期叶面积指数是可行的。 相似文献