城市模拟目标的3维热辐射方向性模型

以城市3维结构场景为研究目标,考虑其光影遮蔽关系,模拟传感器视场内目标的可见表面,实现视场尺度内城市模拟目标方向亮温的准确模拟。利用地面试验观测数据对3维热辐射方向性模型进行验证。结果表明,该模型对城市3维结构目标的方向亮温具有较好的模拟精度,均方根误差为0.7K,能够描述微观尺度下城市3维模拟目标的热辐射方向性。利用该热辐射方向性模型对城市区域物理模型的方向亮温进行模拟,发现城市区域物理模型热辐射存在显著的方向差异,并伴有热点效应产生。     

3维场景植被冠层多波段模拟研究进展

植被冠层辐射散射信号中蕴含了丰富的植被信息,通过构建植被冠层辐射散射模型,可以实现植被结构等生物物理参数的遥感定量反演。迄今为止,可见光/近红外、热红外、微波波段均已发展了大量的模型,这些模型在参数反演方面各具优势,但不同波段的模型又有其自身的局限性。跨波段的联合模拟可以实现模型间的优势互补,进而提高地表参数的反演精度,近年来已有学者专注于可见光/近红外与热红外模型,热红外与微波模型,主被动微波模型,以及可见光/近红外与微波模型的联合模拟和协同反演,但多是两两联合,且主要是基于经验模型或解析模型。基于3维场景的植被冠层辐射散射特性模拟模型可以细致刻画不同组分的结构和空间分布特征,对于由植被结构引起的多次散射和组分比例变化的考虑具有优势。本文主要介绍了3维模拟模型在可见光/近红外、热红外和微波波段,以及跨波段联合模拟方面的研究进展,从模型机理、场景统一、以及组分理化参数的统一的角度,探讨了构建多波段3维模拟系统的可行性,展望了多波段3维模拟模型的发展趋势。     

热红外核驱动模型在垄行植被热辐射方向性特征拟合中的精度分析

垄行种植是果园及农作物的常见种植结构,其冠层比连续和离散植被冠层具有更强的热辐射各向异性,开展垄行植被冠层的热辐射方向性校正对干旱监测等应用具有重要意义.热红外核驱动模型是热辐射方向性校正的基础,但现有核驱动模型在垄行植被冠层中的拟合精度未被讨论过.本文以在法国波尔多获取的两组不同朝向葡萄园冠层航空实测方向性特征为基础...     

基于3D真实植被场景的全波段辐射传输模型研究

本文基于3D真实场景CLAMP模型模拟的植被冠层，对冠层在可见一近红外波段和热红外波段的辐射传输进行了综合建模。针对CLAMP模型生成场景的通用和近似特征，在可见一近红外波段，对植被和土壤的单次散射贡献利用光子逆向追踪算法进行了精确计算，多次散射的贡献则采用四流近似理论来计算，以提高运算效率。模型结果与SAILH模型结果进行了比较，具有较好的一致性，并且体现出了优于一维辐射传输模型的模拟结果。在热红外波段，采用几何光学原理，冠层方向亮度温度由可视光照叶片、遮荫叶片、光照土壤和遮荫土壤的比例与对应组分亮温乘积之和得到，模拟结果体现了合理的变化趋势。对冠层主要结构参数LAI和ALA的敏感性进行了比较分析，不同波段模型模拟的方向性辐射结果，很好地反映了结构参数对冠层辐射特性的影响。     

发展几何光学遥感建模理论，推动定量遥感科学前行——深切缅怀李小文院士

李小文长期致力于遥感基础研究,是植被几何光学遥感建模的先驱。他创建了Li-Strahler几何光学模型,论文入选"国际光学工程学会(SPIE)"里程碑系列文集。以李小文为首席科学家,带领国内外科学团队,在植被二向性反射建模、热红外遥感辐射方向性建模、遥感信息尺度效应、定量遥感综合实验与真实性检验方面做出了卓越成就。本文总结了李小文的主要学术思想,对定量遥感相关研究进展进行了总结和回顾,对遥感科学及相关领域具有重要的借鉴和参考意义。     

博尔塔拉蒙古自治州植被覆盖度估算

针对传统植被覆盖度估算方法只能估算高密度覆盖的绿色光合植被的问题,该文提出了一种可进行绿色光合植被、非绿色光合植被和裸地覆盖度估算的方法,选取博尔塔拉蒙古自治州2010年和2016年的LandsatTM/OLI影像,通过构建NDVI-DFI特征空间提取端元特征值,运用像元三分模型估算,并与像元二分模型估算结果和实地采样估算结果对比。结果表明:像元三分模型估算与实际情况相符,且精度较好。2016年博州地区植被覆盖度较2010年增长显著,生态环境得到明显改善。像元三分模型能够较好地估算光合/非光合植被覆盖度,提高遥感获取植被信息的能力,为科学评估生态环境质量提供参考。     

偏振反射信息在植被遥感双向反射研究中的作用

本文基于菲涅尔反射公式,结合现有的偏振反射模型对单叶与植被多角度偏振测量结果与理论结合进行分析;通过研究发现,偏振反射在前向散射方向可以通过菲涅尔反射公式进行解释,但是,在后向散射方向则需要考虑其他物理机理。此外,传感器获取的植被偏振信息既可以作为一种"噪声"来剔除,剔除后在可见光波段将相对误差从原来的30%降低到20%以内,又可以作为额外有效的信息源表征植被的结构特征:通过模型参数的大小判断冠层形态的平整程度。本文可以作为植被偏振探测的系统化方法,并且给出植被固有的偏振反射效应规律,即植被越平展光滑,产生的偏振信息越多;同时也将偏振光遥感在植被监测中的有效性凸显出来,即偏振信息的剥离有助于提升双向反射模型的计算精度。     

岷江上游典型流域植被覆盖度的遥感模型及反演

本文在对岷江上游典型流域研究区实地踏勘和定位观测的基础上,综合利用Aster和ETM遥感数据、地面实测数据和常规观测数据等资料,研究了植被指数与植被覆盖度之间的相关性,确定了岷江上游典型流域植被覆盖度模型。以遥感图像中单个像元作为测算单位,对植被指数NDVI进行了计算,并对岷江上游毛儿盖地区植被覆盖度进行了反演。利用研究区实测数据、生态环境本底遥感调查数据和水文气象数据,对上述模型反演结果进行验证和精度分析。结果表明,模型反演结果精度较高,能较真实的反应研究区植被覆盖度实际状况。     

Implications of management strategies and vegetation change in the Mount St. Helens blast zone

The 1980 eruptions of Mount St. Helens provided an excellent opportunity for scientists to investigate the recovery of vegetation communities following a major geologic disturbance. An important and often overlooked aspect in these studies is the human factor in recovery processes, and specifically, the different management approaches taken towards re-establishment of vegetation on lands under the control of various owners. This study examines vegetation changes throughout the 1980 blast zone using a time series of Landsat-derived Normalized Difference Vegetation Index (NDVI) images and change detection methods to assess the changes over 25 years, from 1980 to 2005, as a function of human management combined with ecological factors. This long-term tracking of change indicates that differences in the speed of vegetation re-establishment and consequent rates of change substantially reflect human involvement and varying management strategies.     

Effects of prediction accuracy of the proportion of vegetation cover on land surface emissivity and temperature using the NDVI threshold method

Predicting land surface energy budgets requires precise information of land surface emissivity (LSE) and land surface temperature (LST). LST is one of the essential climate variables as well as an important parameter in the physics of land surface processes at local and global scales, while LSE is an indicator of the material composition. Despite the fact that there are numerous publications on methods and algorithms for computing LST and LSE using remotely sensed data, accurate prediction of these variables is still a challenging task. Among the existing approaches for calculating LSE and LST, particular attention has been paid to the normalised difference vegetation index threshold method (NDVI^THM), especially for agriculture and forest ecosystems. To apply NDVI^THM, knowledge of the proportion of vegetation cover (P_V) is essential. The objective of this study is to investigate the effect of the prediction accuracy of the P_V on the estimation of LSE and LST when using NDVI^THM. In August 2015, a field campaign was carried out in mixed temperate forest of the Bavarian Forest National Park, in southeastern Germany, coinciding with a Landsat-8 overpass. The P_V was measured in the field for 37 plots. Four different vegetation indices, as well as artificial neural network approaches, were used to estimate P_V and to compute LSE and LST. The results showed that the prediction accuracy of P_V improved using an artificial neural network (R²_CV = 0.64, RMSE_CV = 0.05) over classic vegetation indices (R²_CV = 0.42, RMSE_CV = 0.06). The results of this study also revealed that variation in the accuracy of the estimated P_V affected calculation results of the LSE. In addition, our findings revealed that, though LST depends on LSE, other parameters should also be taken into account when predicting LST, as more accurate LSE results did not increase the prediction accuracy of LST.     

FY-3B/MWRI与GCOM-W1/AMSR-2亮温数据在北极地区的交叉定标

为了使搭载在风云三号B星上的微波成像仪MWRI（Microwave Radiation Imager）与搭载在GCOM-W1(Global Change Observation Mission 1st-Water)卫星上的AMSR-2（Advanced Microwave Scanning Radiometer 2）的数据可以衔接使用,并为以后FY-3B/MWRI北极地区遥感参数反演研究提供基础,以GCOM-W1/AMSR-2数据为对比数据,北极海洋区域为研究区域,对两传感器对应的10个通道的升、降轨亮温数据进行交叉定标。首先,对MWRI和AMSR-2各通道逐月在研究区域进行偏差分析;其次,对MWRI和AMSR-2各通道逐月在海冰区域和开阔水域进行偏差分析;最后,对MWRI和AMSR-2各通道逐月在研究区域进行交叉定标,并对定标结果进行评价。研究结果表明：（1）MWRI各通道亮温数据小于AMSR-2,且相同频率下,垂直极化各通道逐月平均偏差的绝对值大于水平极化各通道,升、降轨数据在各通道的差异较小,逐月平均偏差的差值小于1 K;（2）在海冰区域,升、降轨各通道逐月平均偏差相差小于1 K,在开阔水域则介于0—1.5 K;（3）通过进行线性回归分析,MWRI和AMSR-2各通道相关系数大于0.99,具有强相关性,并得到升、降轨各通道各月份交叉定标的斜率和截距;（4）定标后MWRI的亮温值与AMSR-2的亮温值一致性较好,说明交叉定标的效果较好。     

A novel approach for predicting the spatial patterns of urban expansion by combining the chi-squared automatic integration detection decision tree,Markov chain and cellular automata models in GIS

Urban development is a continuous and dynamic spatio-temporal phenomenon associated with economic developments and growing populations. To understand urban expansion, it is important to establish models that can simulate urbanization process and its deriving factors behaviours, monitor deriving forces interactions and predict spatio-temporally probable future urban growth patterns explicitly. In this research, therefore, we presented a hybrid model that integrates the chi-squared automatic integration detection decision tree (CHAID-DT), Markov chain (MC) and cellular automata (CA) models to analyse, simulate and predict future urban expansions in Tripoli, Libya in 2020 and 2025. First, CHAID-DT model was applied to investigate the contributions of urban factors to the expansion process, to explore their interactions and to provide future urban probability map; second, MC model was employed to estimate the future demand of urban land; third, CA model was used to allocate estimated urban land quantity on the probability map to present future projected land use map. Three satellite images of the study area were obtained from the periods of 1984, 2002 and 2010 to extract land use maps and urban expansion data. We validated the model with two methods, namely, receiver operating characteristic and the kappa statistic index of agreement. Results confirmed that the proposed hybrid model could be employed in urban expansion modelling. The applied hybrid model overcame the individual shortcomings of each model and explicitly described urban expansion dynamics, as well as the spatio-temporal patterns involved.     

HJ-1B热红外辐射定标对地表温度反演的影响

辐射定标是地表温度反演的关键环节。在实际应用中,定标参数的选取直接影响辐射定标结果。由于卫星在轨定标系统的灵敏度会随时间发生改变,这使得实际的辐射定标存在不确定性。本文基于单波段热红外辐射传输方程给出了辐射定标影响地表温度反演的敏感性分析模型,并重点对HJ-1B热红外波段的辐射定标问题及其对地表温度反演的影响进行讨论和分析。敏感性分析模型显示,在一般的情形下,辐射定标偏差与地表温度反演误差的比值在数值上约为1∶11,即0.1个单位(W·m–2·sr–1·μm–1)的辐射定标偏差可能引起1.1 K左右的温度反演误差。由于对HJ-1B热红外波段定标参数的更新存在滞后,即使仅考虑相邻年份间的定标偏差,相应的地表温度平均绝对误差也在1.0—2.0 K左右。在更严重的情形下,因辐射定标偏差引起的地表温度误差甚至高达5.0 K以上。同时,分析结果也表明对HJ-1B的存档影像,无论使用其头文件中的定标参数还是当年公布的定标参数,定标后辐射亮度值的偏差均存在一定的不稳定性。针对当前在HJ-1B定标参数更新方面的不足,本文假定传感器辐射性能变化是匀速稳定的,相应地提出了线性内插修正法和线性外推法两个定标参数估计/修正方案。通过线性内插的方法进行辐射定标修正后,在一定程度上减小了误差的不稳定性,与MODIS B31波段的亮温相比,偏差在1.0 K以内(约为0.5 K)。当定标参数尚未公布时,由线性外推法修正后的辐射定标结果所得亮温的偏差约为1.0 K。与在大亚湾核电站附近海域进行的一次卫星同步观测(2011年12月18日)相比,经两个方案修正后的海表温度偏差分别约为0.2 K和0.7 K。案例分析的结果表明,在现阶段,线性内插修正法和线性外推法是简单有效的,可供用户在实际应用中参考和使用。