Decomposition of Time Series Dynamic Linear Models

This paper derives the admissible decompositions for a time series dynamic linear model, assuming only that the model is observable. The decompositions depend on factorizations of the characteristic polynomial of the state evolution matrix G into relatively prime factors. This generalizes the method of West (1997 ) which considers one decomposition in the particular case where G is diagonalizable. Conditions are derived for a decomposition to be independent. These results show that no autoregressive process of order d has an independent decomposition for any integer d . Two illustrations of this procedure are discussed in detail.     

Agricultural land-use change in Brazilian Amazônia between 1980 and 1995: Evidence from integrated satellite and census data

As cropland and pasture have replaced forest and cerrado in Brazilian Amazônia, concern has mounted over the effects of changing the biogeochemical and hydrological properties of one of the world's great storehouses of biomass and biodiversity. Although much recent effort has focused on the location, effects, and causes of deforestation and cerrado conversion, much less is known about the basin-wide spatial distribution and density of the land use following conversion for crops or pasture.In this paper, we use census and satellite records to develop maps of the distribution and abundance of major agricultural land uses across 4.5×10⁸ ha of Brazilian Amazônia in 1980 and 1995. Results indicate an overall expansion of 7.0×10⁶ ha in total agricultural area in Brazilian Amazônia between 1980 and 1995. The net change during this period is estimated for three different land-use types: croplands (an increase of 0.8×10⁶ ha), natural pastures (a decrease of 8.4×10⁶ ha), and planted pastures (an increase of 14.7×10⁶ ha). These estimates, the first spatially explicit quantifications of agricultural land-use activities in 1980 and 1995 across Brazilian Amazônia, are shown to be consistent with the results of applying a land use change and secondary regrowth model to published deforestation rates for the period.The resulting time slices, presented for each land-use category at 5-min (∼9 km) spatial resolution, allow for the quantification of land-use changes in this region for biogeochemical, demographic and economic models. Several foci of agricultural change existed within Brazilian Amazônia during this period: in the state of Pará, cropland was lost and planted pasture increased markedly; in Mato Grosso, both cropland and planted pasture increased; in Rondônia, planted pasture replacing forest was the primary route to agricultural expansion.     

The performance of foliage mass and crown radius models in forming the input of a forest reflectance model: A test on forest growth sample plots and Landsat 7 ETM+ images

Several published foliage mass and crown radius regression models were tested on the preparation of the input for the reflectance model of Kuusk and Nilson [Kuusk, A. and Nilson, T. (2000), A directional multispectral forest reflectance model. Remote Sensing of Environment, 72(2):244–252.] for 246 forest growth sample plots in Estonia. In each test, foliage mass and crown radius for trees in the sample plots were predicted with a particular pair of allometric regression models. The forest reflectance model was then run using the estimated foliage mass and crown radius values. Reflectance factors were simulated and compared with the reflectance values obtained from three atmospherically corrected Landsat 7 Enhanced Thematic Mapper (ETM+) scenes. The statistics of linear regression between the simulated and measured reflectance factors were used to assess the performance of foliage and crown radius models. The hypothesis was that the best allometric regression models should provide the best fit in reflectance. The strongest correlation between the simulated and measured reflectance factors was found in the short-wave infrared band (ETM + 5) for all the images. The highest R² = 0.71 was observed in Picea abies dominated stands. No excellent combination of foliage mass and crown radius functions was found, but the ranking based on determination coefficients showed that some linear crown radius models are not applicable to our data. Processing of raster images, reflectance measurement for small sample plots, usage of tree-species-specific fixed parameters (specific leaf area, etc.), and the ignored influence of phenology introduced additional variation into the relationships between simulated and measured reflectance factors. Further studies are needed, but these preliminary results demonstrate that the proposed method could serve as an effective way of testing the performance of foliage mass and canopy cover regressions.     

民国时期书刊封面设计的发展

民国时期[1]书刊封面中的汉字设计风格丰富多样,兼具了传达功能与艺术美感,具有鲜明的民族性与时代特征。如杉浦康平先生所说,"为了前进一步,回首过去。"[2]民国时期的书刊封面的设计,在中国书籍发展史及平面设计史上具有重要的历史地位,归纳与梳理这一时期的发展脉络,对于研究封面中的汉字设计有着重要意义。所以本文以时间为线索,归纳从1912年至1949年之间的民国书籍封面。     

手势数据驱动的头部运动合成方法

非手部手势是手语表达中不可缺少的一部分,头部运动的实现并与手势进行协同表达是其重要研究内容。对真人手语表演数据中的手势与头部动作之间的关系进行了深入研究,提取二者的动作特征,利用核典型相关分析方法(kernel canonical correlation analysis,KCCA)建立起手势与头部动作之间的预测关系模型。动画合成结果以及评价实验表明,KCCA方法能更好地刻画手势与头部动作的协调性,实现虚拟人行为动作合成的逼真性。     

影响ETM影像土地利用/覆盖分类精度因素的研究

训练样本量、辅助数据和分类法是影响土地利用/覆盖分类精度的3个主要因素,通过找到这3个因素的最佳组合方式以提高分类精度,分别在25%、50%、75%、100%样本量下,加入NDVI、DEM和纹理均值特征作为辅助数据,比较了分类回归树、支持向量机、最大似然法3种分类法的效果,探讨了训练样本、辅助数据以及分类技术对土地利用/覆盖分类精度的影响。结果表明：支持向量机总体分类精度较高,在相同样本量和没有有效辅助数据的情况下,SVM可以获得最佳的分类结果,总体分类精度在85%以上;在进行分类时,加入NDVI和纹理均值特征使分类回归树分类精度提高了2.82%,说明该方法对有效辅助数据的加入较为敏感;在获取的训练样本集有限而可获取有效的辅助数据时,应优先考虑利用分类回归树进行土地利用/覆盖分类。     

拉萨河流域径流对土地利用和气候变化的响应分析

拉萨河流域处青藏高原中南部,因其独特的地理位置是对气候变化较为敏感的区域之一,同时也是青藏高原人口和耕地较为密集区域。在建立SWAT模型对拉萨河流域水循环过程进行模拟的基础上,通过设置不同气候情景与土地利用状况,分析近30 a来拉萨河流域径流变化的成因,并研究径流对气候因子变化的敏感性。结果表明:①气候变化与土地利用对径流影响占比分别约为82.95%和17.05%,主要原因在于近30 a拉萨河流域土地利用情况变化不大,而气温、降水则呈显著增加趋势;②降水每增加10%,流域径流约增加11.8%,且径流对降水变化敏感性的空间差异性较小;③气温每增加1 ℃,流域总径流约增加2.5%,但径流随气温变化的空间差异性较大,其中,中上游地区径流减小0.7%,下游地区径流约增加3.6%。     

基于时序特征的黄河三角洲土地覆盖动态及驱动力分析

综合不同土地利用类型的Landsat影像时序特征和面向对象分割方法,分析1985-2018年现代黄河三角洲土地覆盖时空特征,探讨土地覆盖变化的驱动机制。结果表明:1985-2018年间研究区天然湿地面积大幅减少,共减少9.9847×104 hm²,其中沼泽和草甸湿地面积减少尤为明显,而人工湿地面积则逐年增加,年平均增加率达54.66%,主要是盐田养殖场和水稻种植面积的增大;社会经济因素对研究区土地覆盖的影响程度高于水文因素;输沙量是影响研究区土地覆盖变化的主要水文因素,实测径流量的减少进一步导致天然湿地向旱地类型转化;人口和GDP变化对人工湿地面积增加的正相关作用比较显著,而天然湿地面积的减少则与该两个指标的负相关关系比较明显。