垄行结构玉米冠层方向亮温模型研究

基于热红外成像仪获取的玉米冠层图像，对垄行结构玉米的方向亮温（DBT）进行模型化描述并开展了初步验证工作。模型中假设某一方向上的冠层DBT是组分亮温及各组分在视场中所占面积权重的函数，它们在视场中的比例依赖太阳与传感器的几何位置关系，以及在作物行内，作物行与行之间孔隙的分布。对于玉米冠层的几何特征，简化为横截面是矩形的、其中有空隙透光的一组无限长的平行立方体；立方体内双向孔隙率的方向变化由Kuusk函数来描述。模型模拟表明，玉米亮温组分在视场中的权重具有垄行特性。中午前后，通过对中等密度的冠层DBT模拟，在DBT极坐标图形上发现了一个明显位于垄行方向的热条带的出现，热点出现在太阳位置的周围。最后，利用实地观测的结果与模型模拟结果作对比，对该模型的不足和以后的改进作了初步分析。     

垄行作物玉米方向亮温野外测量中视场角影响的简单分析

基于透视原理、地面试验中对于较高目标的观测存在着一定的偏差。这种偏差随传感器高度、观测角度、视场角大小、观测位置等多个因素改变。由于垄行作物空间结构和温度分布的复杂性 ,在采用较大视场角测量方向亮温的地面实验中 ,将不可避免地存在着误差。采用一个简化的三分量二维结构模型对这种误差进行初步的分析与估算。亮温三分量分别为植被、被阳光照到的亮土和植被阴影下的暗土。作物的结构简化为剖面为矩形的无限长平行体。通过对这三个分量在传感器视场中面积权重的计算来模拟目标结构、传感器高度、位置、视场角大小、观测角度等因素对测量结果产生的影响。模拟结果表明 ,在垂直观测中 ,视场中的植被权重往往被高估 ,偏差随传感器高度的降低急剧增加。在倾斜观测中 ,由于一种互补效应的产生 ,偏差被限制在一个较低的范围内。经过分析 ,减小误差的最有效办法是提高传感器高度。最后 ,实验数据与模拟结果进行了比较。恰当地选取模型输入 ,两种数据能非常好的吻合。     

POV-ray应用于冠层可视光照和阴影组分比例变化分析

利用POV-ray快速计算三维冠层的四分量比例及孔隙率,在与计算机模拟模型对比结果、验证其可靠性的基础上,针对植被真实结构模型的主要参数对冠层四分量比例和孔隙率的敏感性进行分析。敏感性分析结果表明:当冠层为垄行结构时,相对于其他因素,行结构对四分量比例和孔隙率的影响占主导,因此当植被冠层为垄行结构时,四分量比例和孔隙率的变化较连续冠层更加复杂;集聚指数可以有效的控制叶片的空间分布模式,进而影响到视场中植被与土壤的相对面积比例,对于四分量比例和孔隙率结果有较大影响;叶倾角分布类型对四分量比例和孔隙率结果的各向异性特征影响明显;同时,通过对垄行作物3个典型生长期的四分量比例和孔隙率结果分析得出,在作物生长初期土壤对结果影响更大,在作物生长后期植被对结果的影响占主导,亮叶分量比例各向异性特征较为明显。研究表明,POV-ray是进行植被定量遥感研究的有利工具,具有较好的应用前景。     

暗目标法的Himawari-8静止卫星数据气溶胶反演

Himawari-8(H8)是由日本气象厅发射的新一代静止气象卫星,可实现10 min/次的高频次对地观测,搭载的AHI(Advanced Himawari Imager)传感器设置有与MODIS暗目标气溶胶反演算法所需的类似波段。本文参考暗目标算法构建了针对该卫星传感器的陆地气溶胶反演算法:首先,通过基于地基站点观测数据的精确大气校正,统计得到短波红外与可见光波段的地表反射率比值关系,将此作为先验知识用于地—气解耦时的反射率估计;然后,初步假设大陆型气溶胶类型,利用辐射传输模型建立查找表;最后,通过模拟与卫星观测的表观反射率误差最小实现气溶胶光学厚度反演解算。选取2016年5月覆盖京津冀地区的观测数据进行测试,将反演结果与对应时间的MODIS气溶胶光学厚度产品进行对比验证,空间分布趋势一致、相关性较高,相关系数R达到0.852;通过与地基观测网AERONET站点实测数据对比验证,所有站点的相关系数R~2均大于0.88,精度较高。利用反演的高时间分辨率产品,分析了京津冀地区的大气空间分布和日变化情况,结果表明:采用暗目标法对H8静止卫星陆地气溶胶光学厚度反演具有一定的潜力和可行性,能反映气溶胶的高时间变化信息,有望成为大气环境污染变化监测新的重要手段。     

利用MODIS BRDF估算中国东北森林背景反射率——以大兴安岭加格达奇地区为例

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。     

城市目标方向亮温观测的视场效应分析

基于简化的城市目标三维结构模型,利用计算机图形学中辐射度方法,对城市目标的热辐射方向性规律进行模拟。在传感器分别位于近地面和卫星轨道时,研究了城市目标各组分在视场内的权重随观测天顶角、方位角和观测距离改变的变化规律。结果表明:城市目标方向亮温地面辐射测量存在显著视场效应。当传感器位于近地面时,在垂直太阳主平面附近,视场效应达到最大。方向亮温随观测距离的改变有明显变化。随着观测距离的增加,视场效应急剧减小。将近地面测量得到的方向亮温与卫星影像计算所得的方向亮温对比时,视场效应是一个必须考虑的因素。     

基于微缩模型的森林BRF测量

利用林木微缩模型构建不同空间分布的林分,测量林分的双向反射率因子(bidirectional reflectance factor,BRF),并对其反射光谱进行了分析研究。结果显示:基于微缩模型得到的观测结果整体较符合实际森林的特征,与三维模型模拟结果一致;在近红外波段,光谱曲线呈典型的"碗边效应",在观测主平面"热点效应"较为明显。研究结果证实林木微缩模型可以用于森林BRF研究。对不同林木模型的分布状态与不同的地形条件的测量结果对比分析后发现,林木分布的密度和坡度是较为敏感的参数,其特征与规律性有助于建模反演地表信息。     

离散植被冠层的解析混合BRDF模型——MGeoSAIL

根据适合于垂直单角度观测的GeoSAIL模型,改进得到适合于各种角度观测的MGeoSAIL模型。它是几何光学模型和辐射传输模型的结合。具备两种模型的优点使MGeoSAIL模型更具准确性和实用性。其中几何光学模型用来计算场景内不同情况下阴影和光照成分的比例,辐射传输模型(SAIL)考虑冠层内的辐射传输计算得到树冠的反射率和投射率,将其权重加和生成场景反射率。模拟结果表明该模型简单实用,在可见光与近红外波段均能反映出"热点"效应,在近红外波段能描述出"碗边"效应,且更适合于低密度、大个体、不连续稀疏林分冠层的BRDF模拟。     

利用夜间热红外遥感影像研究玉米冠层孔隙率分布

为了测量高覆盖条件下(LAI=5)玉米冠层的方向孔隙率,利用一台基于工业用吊车平台的窄视角热红外成像仪开展测量。在此基础上建立了一个几何光学和辐射传输混合模型模拟半球空间的孔隙率分布。测量结果表明,大多数的孔隙出现在邻近的植株行之间,这导致了在热红外图像中,冠层还保持着垄行结构的特征。基于已经得到的几何参数,本研究发展的模型具有垄行作物孔隙率分布特征,模拟的孔隙率与被观测的孔隙率保持很好的一致。更进一步的改进,需通过计算机模拟以建立更加真实的作物结构描述,这也是以后的一个研究方向。     

基于植被二向性反射统一模型的高分五号FAPAR遥感反演算法

植被光合有效辐射吸收比率（FAPAR）是描述植被光合作用能量交换过程的重要参数，广泛应用于植被长势监测、植被生产力估算、全球变化等研究领域。遥感是大范围获取FAPAR的唯一途径，与多光谱传感器相比，高光谱传感器能更加精确、细致地观测植被的光谱特征，有利于分析植被冠层反射、吸收特性，进而反演植被冠层FAPAR。本文首先在植被BRDF统一模型和FAPAR-P模型的基础上，构建了BRDF-FAPAR统一模型UBFM (Unified BRDF-FAPAR Model)；进而基于高分五号高光谱传感器特征模拟了不同情况下植被冠层反射率和相应的FAPAR；然后运用改进的最佳指数法选择FAPAR反演的特征波段组合；在此基础上，将特征波段反射率与FAPAR模拟结果作为神经网络的输入参数，构建针对高光谱数据的FAPAR神经网络反演算法。研究结果表明，改进的最佳指数法能有效地筛选出FAPAR估算的敏感波段；综合考虑波段信息量和实际影像数据噪声影响，本研究针对高分五号高光谱传感器选择8个波段作为FAPAR反演特征波段。基于UBFM模型构建的神经网络反演精度较高，模拟实验算法误差约为0.014。选择内蒙古呼伦...     

Inversion of PROSAIL Model for Retrieval of Plant Biophysical Parameters

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.     

Ground Based Bistatic Scatterometer Measurement for the Estimation of Growth Variables of Ladyfinger Crop at X-Band

The present study describes the ground based bistatic scatterometer measurements of ladyfinger crop at its various growth stages in the specular direction with the azimuthal angle (\( \phi = 0 \)) for the angular incidence angle ranging from 20° to 60° at the interval of 10° at HH and VV polarization. An outdoor ladyfinger crop bed of an area 4 × 4 m² was specially prepared for the ground based bistatic scatterometer measurements. The crop growth variables like vegetation water content, leaf area index, fresh biomass, and plant height were also measured at the time of each bistatic scatterometer measurement. The specular bistatic scattering coefficients were found to be decreasing with the crop growth variables up to the maturity stage and then after it increased slightly. The linear regression analysis was carried out between specular bistatic scattering coefficient and crop growth variables at all the incidence angles for HH and VV polarization to select the optimum angle of incidence and polarization for the estimation of crop growth variables. The potential of subtractive clustering based adaptive neuro-fuzzy inference system was applied for the estimation of crop growth variables. The estimated values for different crop growth variables were found almost close to the observed values.     

Viewing Angle Effect on the Remote Sensing Monitoring of Wheat and Rice Crops

Abstract

Bidirectional reflectance characteristics of a wheat and a rice canopy were studied using radiometric measurements over the two canopies with an Exotech Radiometer Model 100AX. For both rice and wheat, the measurements exhibited significant variations in reflectance amplitude for varying viewing zenith angles and their values decreased from backward to forward scattering direction. Reflectance obtained its maximum value in the backscatter direction for the viewing angle that corresponds approximately to the solar zenith angle at the time of measurements. Canopy background condition (irrigated or non‐irrigated) was an important determining factor of canopy reflectance particularly in the near‐infrared region of the solar spectrum. Furthermore, bidirectional response characteristics of a vegetation canopy were influenced by the amount of vegetation cover.     

卫星遥感大气订正的参数化模式及其模拟应用

发展了一个用于卫星大气订正的参数化模式,包括一个新的程辐射亮度模式和一个参数化的朗伯地表一大气辐射耦合引起的亮度增量模式.应用最小二乘法,程辐射亮度被参数化为大气总光学厚度、一次散射反照率、太阳天顶角、视天顶角、方位角、大气不对称因子的函数.应用这一参数化的亮度模式进行大气订正应用的数值模拟,即进行卫星遥感地表光谱反照率的模拟试验.数值检验结果表明对于865 nm,670nm,550nm和412nm 4个MODIS通道,在0°-70°的太阳天顶角、0°-60°视观测角以及0.05-0.8的地表反照率条件下,参数化的向上辐射亮度的标准差小于4%,由该参数化亮度模式引起的地表反照率解的标准差小于0.03.     

植物单叶偏振反射特征研究

简明地阐述了植物单叶偏振反射特征以及影响植物单叶偏振反射的主要因素 ,这对偏振光遥感的深入研究具有一定的理论和实践意义     

利用夜间热红外数据求取玉米冠层孔隙率

孔隙率是光线透过冠层未被拦截到达地表的概率,是描述冠层结构和生物量空间分布的关键变量。已有研究证明,在夜间热红外图像上,玉米地各亮温组分比较稳定,并且温度均值有明显差异,易于区分。本研究的目的是利用2005年8月23日在怀来测得的夜间热红外数据求取中等密度的玉米冠层(LA I=3.64)在不同角度下的孔隙率。结果表明,在沿垄行方向,孔隙率随着天顶角变化缓慢;而在其他方向(45°和90°)变化较快,且变化趋势相似。将测得结构参数代入余涛的热红外方向辐射性模型,模拟出不同方向下的孔隙率。将测量值与模拟值进行对比,二者有一定的相似性,模型能较好地抓住玉米冠层孔隙率的主要特征。针对二者间的差异,初步分析是由测量中观测目标不完全一致、角度控制不精确、测量高度过低以及投影函数和丛生参数的选择等原因引起的。     

基于室内光谱测量的玉米单叶偏振与二向性反射关系研究

本研究利用多角度光度计实测了玉米单叶的偏振反射比与二向反射比数据。该光度计能够在不同的观测天顶角、入射天顶角和方位角下测量目标物的偏振反射和二向反射,获得地物目标在2π空间的多角度观测数据。通过分析实测的偏振反射和二向反射数据,得出了玉米单叶的偏振反射与二向反射之间关系密切,最大与最小偏振反射比之和的平均数约等于同等观测条件下玉米叶片的二向反射比。该研究成果为植被遥感监测做出了一种新的尝试,并且对偏振光遥感、多角度遥感的深入研究与应用提供了依据。     

MISR和MODIS二向性反射数据产品的对比分析

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。     

Directional effects on NDVI and LAI retrievals from MODIS: A case study in Brazil with soybean

The Moderate Resolution Imaging Spectroradiometer (MODIS) is largely used to estimate Leaf Area Index (LAI) using radiative transfer modeling (the “main” algorithm). When this algorithm fails for a pixel, which frequently occurs over Brazilian soybean areas, an empirical model (the “backup” algorithm) based on the relationship between the Normalized Difference Vegetation Index (NDVI) and LAI is utilized. The objective of this study is to evaluate directional effects on NDVI and subsequent LAI estimates using global (biome 3) and local empirical models, as a function of the soybean development in two growing seasons (2004–2005 and 2005–2006). The local model was derived from the pixels that had LAI values retrieved from the main algorithm. In order to keep the reproductive stage for a given cultivar as a constant factor while varying the viewing geometry, pairs of MODIS images acquired in close dates from opposite directions (backscattering and forward scattering) were selected. Linear regression relationships between the NDVI values calculated from these two directions were evaluated for different view angles (0–25°; 25–45°; 45–60°) and development stages (<45; 45–90; >90 days after planting). Impacts on LAI retrievals were analyzed. Results showed higher reflectance values in backscattering direction due to the predominance of sunlit soybean canopy components towards the sensor and higher NDVI values in forward scattering direction due to stronger shadow effects in the red waveband. NDVI differences between the two directions were statistically significant for view angles larger than 25°. The main algorithm for LAI estimation failed in the two growing seasons with gradual crop development. As a result, up to 94% of the pixels had LAI values calculated from the backup algorithm at the peak of canopy closure. Most of the pixels selected to compose the 8-day MODIS LAI product came from the forward scattering view because it displayed larger LAI values than the backscattering. Directional effects on the subsequent LAI retrievals were stronger at the peak of the soybean development (NDVI values between 0.70 and 0.85). When the global empirical model was used, LAI differences up to 3.2 for consecutive days and opposite viewing directions were observed. Such differences were reduced to values up to 1.5 with the local model. Because of the predominance of LAI retrievals from the MODIS backup algorithm during the Brazilian soybean development, care is necessary if one considers using these data in agronomic growing/yield models.     

Determination of the crop row orientations from Formosat-2 multi-temporal and panchromatic images

This paper presents a technique developed for the retrieval of the orientation of crop rows, over anthropic lands dedicated to agriculture in order to further improve estimate of crop production and soil erosion management. Five crop types are considered: wheat, barley, rapeseed, sunflower, corn and hemp. The study is part of the multi-sensor crop-monitoring experiment, conducted in 2010 throughout the agricultural season (MCM’10) over an area located in southwestern France, near Toulouse. The proposed methodology is based on the use of satellite images acquired by Formosat-2, at high spatial resolution in panchromatic and multispectral modes (with spatial resolution of 2 and 8 m, respectively). Orientations are derived and evaluated for each image and for each plot, using directional spatial filters (45° and 135°) and mathematical morphology algorithms. “Single-date” and “multi-temporal” approaches are considered. The single-date analyses confirm the good performances of the proposed method, but emphasize the limitation of the approach for estimating the crop row orientation over the whole landscape with only one date. The multi-date analyses allow (1) determining the most suitable agricultural period for the detection of the row orientations, and (2) extending the estimation to the entire footprint of the study area. For the winter crops (wheat, barley and rapeseed), best results are obtained with images acquired just after harvest, when surfaces are covered by stubbles or during the period of deep tillage (0.27 > R² > 0.99 and 7.15° > RMSE > 43.02°). For the summer crops (sunflower, corn and hemp), results are strongly crop and date dependents (0 > R² > 0.96, 10.22° > RMSE > 80°), with a well-marked impact of flowering, irrigation equipment and/or maximum crop development. Last, the extent of the method to the whole studied zone allows mapping 90% of the crop row orientations (more than 45,000 ha) with an error inferior to 40°, associated to a confidence index ranging from 1 to 5 for each agricultural plot.