类多变量输出误差系统的耦合多新息辨识方法

辅助模型辨识思想、多新息辨识理论、耦合辨识概念是研究复杂多变量系统辨识的新理念和原理.将它们结合起来研究类多变量输出误差系统的辨识问题,提出了多元辅助模型辨识方法、多元辅助模型多新息辨识方法、变递推间隔多元辅助模型多新息辨识方法.为减小算法的计算量和提高参数估计精度,将系统模型分解为一些子辨识模型,应用辅助模型辨识思想、多新息辨识理论、耦合辨识概念,研究和推导了部分耦合辅助模型辨识方法、部分耦合辅助模型多新息辨识方法.讨论了几个典型辨识算法的计算量,给出了参数估计的计算步骤和计算流程图.     

Soil respiration mapped by exclusively use of MODIS data for forest landscapes of Saskatchewan,Canada

Soil respiration (R_s) is of great importance to the global carbon balance. Remote sensing of R_s is challenging because of (1) the lack of long-term R_s data for model development and (2) limited knowledge of using satellite-based products to estimate R_s. Using 8-years (2002–2009) of continuous R_s measurements with nonsteady-state automated chamber systems at a Canadian boreal black spruce stand (SK-OBS), we found that R_s was strongly correlated with the product of the normalized difference vegetation index (NDVI) and the nighttime land surface temperature (LSTn) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The coefficients of the linear regression equation of this correlation between R_s and NDVI × LSTn could be further calibrated using the MODIS leaf area index (LAI) product, resulting in an algorithm that is driven solely by remote sensing observations. Modeled R_s closely tracked the seasonal patterns of measured R_s and explained 74–92% of the variance in R_s with a root mean square error (RMSE) less than 1.0 g C/m²/d. Further validation of the model from SK-OBS site at another two independent sites (SK-OA and SK-OJP, old aspen and old jack pine, respectively) showed that the algorithm can produce good estimates of R_s with an overall R² of 0.78 (p < 0.001) for data of these two sites. Consequently, we mapped R_s of forest landscapes of Saskatchewan using entirely MODIS observations for 2003 and spatial and temporal patterns of R_s were well modeled. These results point to a strong relationship between the soil respiratory process and canopy photosynthesis as indicated from the greenness index (i.e., NDVI), thereby implying the potential of remote sensing data for detecting variations in R_s. A combination of both biological and environmental variables estimated from remote sensing in this analysis may be valuable in future investigations of spatial and temporal characteristics of R_s.     

Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation

The urban heat island (UHI) refers to the phenomenon of higher atmospheric and surface temperatures occurring in urban areas than in the surrounding rural areas. Mitigation of the UHI effects via the configuration of green spaces and sustainable design of urban environments has become an issue of increasing concern under changing climate. In this paper, the effects of the composition and configuration of green space on land surface temperatures (LST) were explored using landscape metrics including percentage of landscape (PLAND), edge density (ED) and patch density (PD). An oasis city of Aksu in Northwestern China was used as a case study. The metrics were calculated by moving window method based on a green space map derived from Landsat Thematic Mapper (TM) imagery, and LST data were retrieved from Landsat TM thermal band. A normalized mutual information measure was employed to investigate the relationship between LST and the spatial pattern of green space. The results showed that while the PLAND is the most important variable that elicits LST dynamics, spatial configuration of green space also has significant effect on LST. Though, the highest normalized mutual information measure was with the PLAND (0.71), it was found that the ED and PD combination is the most deterministic factors of LST than the unique effects of a single variable or the joint effects of PLAND and PD or PLAND and ED. Normalized mutual information measure estimations between LST and PLAND and ED, PLAND and PD and ED and PD were 0.7679, 0.7650 and 0.7832, respectively. A combination of the three factors PLAND, PD and ED explained much of the variance of LST with a normalized mutual information measure of 0.8694. Results from this study can expand our understanding of the relationship between LST and street trees and vegetation, and provide insights for sustainable urban planning and management under changing climate.     

Effects of meridional sea surface temperature changes on stratospheric temperature and circulation

Using a state-of-the-art chemistry-climate model,we analyzed the atmospheric responses to increases in sea surface temperature （SST）.The results showed that increases in SST and the SST meridional gradient could intensify the subtropical westerly jets and significantly weaken the northern polar vortex.In the model runs,global uniform SST increases produced a more significant impact on the southern stratosphere than the northern stratosphere,while SST gradient increases produced a more significant impact on the northern stratosphere.The asymmetric responses of the northern and southern polar stratosphere to SST meridional gradient changes were found to be mainly due to different wave properties and transmissions in the northern and southern atmosphere.Although SST increases may give rise to stronger waves,the results showed that the effect of SST increases on the vertical propagation of tropospheric waves into the stratosphere will vary with height and latitude and be sensitive to SST meridional gradient changes.Both uniform and non-uniform SST increases accelerated the large-scale Brewer-Dobson circulation （BDC）,but the gradient increases of SST between 60°S and 60°N resulted in younger mean age-of-air in the stratosphere and a larger increase in tropical upwelling,with a much higher tropopause than from a global uniform 1.0 K SST increase.     

Climatology of Lightning Activity over the Indian Seas

The climatology of lightning activity over the Indian seas (Arabian Sea (AS) and Bay of Bengal (BoB)) has been studied using monthly satellite-based lightning flash count grid (0.5°?×?0.5°) data from 1998 to 2007. These data have been used to investigate the annual and seasonal variations in lightning activity over the Indian seas. It was found that annual variations in flash rate density and sea surface temperature (SST) show a bimodal pattern with the first peak occurring in May and the second in October. The correlation coefficients between flash rate density and SSTs are 0.76 and 0.65 for the AS and BoB, respectively. Further, the relationship between flash rate density and a low pressure system (LPS) over the BoB shows that the formation of severe tropical cyclonic storms starts during April with the maximum number of storms forming during August. The performance of monsoon on a seasonal and monthly basis depends on the total number of lows, the formation of a depression in the monsoon trough, and the number of days with an LPS. Secular decreases in the number of lows and monsoon depressions were observed in 2000, 2002, and 2004. Overall, results indicate that the peaks in SST during April and September/October over the AS and the BoB may be responsible for advancing the onset of the southwest and northeast monsoon by 30–40 days.     

基于北京二号影像辅助nDSM的建筑物自动提取

针对建筑物提取方法缺乏泛化性的问题,本文提出了将nDSM、北京二号影像、NDVI、BAI的七通道图像相结合作为数据源的提取方法。采用随机森林、梯度提升机、支持向量机、BP神经网络分类器对建筑物进行提取获取最佳分类器模型,并运用二值化与开闭运算,以建筑物面积与最小外接矩形面积的比值为阈值,对建筑物分别进行最小外接矩形、DP算法拟合,优化建筑物提取结果。试验结果表明,梯度提升机(GBDT)较其他分类模型在不同场景下综合效果较好,F-score精度更高。     

西安市浅层地温场垂向分布特征及其影响因素分析

根据西安市内布设的12口长观孔监测的一年内的月平均地温,绘制不同时期地温随深度变化曲线,系统分析西安市浅层地温场垂向上的分布特征及其影响因素。分析得出：西安市垂向上的分布特征有两种类型：渐变升温型和升温降温交替型。影响其分布的主要因素是地质构造、地下水活动以及岩性。在开发利用过程中要针对浅层地温场不同的变化类型因地制宜地进行调查评价工作,合理开发西安市浅层地温能。     

哈密地区平原区与山区气候变化差异性分析

利用水文气象站点数据采用线性趋势分析法和Mann-kendall检验法分析了哈密地区与水资源息息相关的山区与平原区气候要素变化的差异性。结果表明：山区与平原区实测站点气候要素多年平均月系列变化规律与趋势基本一致,在量上存在一定的差异;气象站点与水文站点降水要素均呈波动增加的趋势,总体不明显,山区与平原无明显的差别,相对以头道沟站降水增加较明显;气温均呈波动升高的趋势,并且受所处的地理位置影响较大,在相近经度方向上山区气温的升高幅度高于平原区;哈密气象站与头道沟水文站点降水以上世纪70年代增幅最明显,而伊吾气象站和苇子峡水文站以上世纪80-90年代降水增幅最明显;气温除伊吾气象站上世纪90年代升温明显外,其他各站点均以70-80年代升温最明显。     

基于嫦娥二号微波辐射计数据月球中低纬度亮温异常区地质分析研究

月球表面的微波辐射亮度温度与月表地质结构和月表物质的物理化学特性相关。为了对月球亮温分布异常区域进行地质分析,文章首先计算嫦娥亮温数据的时角,采用克里金插值的方法得到了不同频率不同时刻中低纬度的微波亮温图。结合奇异值分解(SVD)模型分析了月表亮温变化异常,结果表明风暴洋位置和靠近月海东北部的高地区域等存在亮温变化异常,月海区域(除风暴洋外)为3 GHz和37 GHz两个场的总体相关区域。通过对月球火山分布地区的区域亮温变化进行分析,发现这热异常可能是由于月球火山活动造成的。     

相干能量梯度与属性比例融合在断裂构造解释中的应用

相干能量梯度体现了相干数据的振幅变化,它比较有利于突出一些细小的地质特征变化,其属性比例融合是将两个数据体按照一定比例融合在一起生成新的数据体,而新数据体能更好的反映地质特征。实例表明,与相干属性相比,相干能量梯度属性对一些细小构造更敏感,而且可以根据不同方向、时间的切片对不同走向的断层进行追踪;与常规地震时间剖面相比,属性比例融合后的属性剖面,可以在剖面中显示两种属性体的断裂构造特性,减少单一属性体的不确定性。