极化干涉SAR森林树高提取算法的对比分析

在对极化干涉SAR森林树高反演的DEM差值算法、相干相位-幅度综合反演算法进行分析的基础上,对基于极化干涉相干优化方法的改进算法进行了探讨。利用黑龙江大兴安岭地区的一对ALOS全极化干涉SAR数据进行实验,并对比分析各算法的反演结果。结果表明,在使用改进的算法进行森林树高反演时可以获取精度较高的反演结果,并且在一定程度上提高了森林树高反演的稳定性,为森林树高反演工作的业务化运行提供一定的依据。     

Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US

Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.     

Upper-Tropospheric Environment–Tropical Cyclone Interactions over the Western North Pacific: A Statistical Study

Based on 25-year(1987–2011) tropical cyclone(TC) best track data, a statistical study was carried out to investigate the basic features of upper-tropospheric TC–environment interactions over the western North Pacific. Interaction was defined as the absolute value of eddy momentum flux convergence(EFC) exceeding 10 m s~(-1)d~(-1). Based on this definition, it was found that 18% of all six-hourly TC samples experienced interaction. Extreme interaction cases showed that EFC can reach~120 m s~(-1)d~(-1) during the extratropical-cyclone(EC) stage, an order of magnitude larger than reported in previous studies.Composite analysis showed that positive interactions are characterized by a double-jet flow pattern, rather than the traditional trough pattern, because it is the jets that bring in large EFC from the upper-level environment to the TC center. The role of the outflow jet is also enhanced by relatively low inertial stability, as compared to the inflow jet. Among several environmental factors, it was found that extremely large EFC is usually accompanied by high inertial stability, low SST and strong vertical wind shear(VWS). Thus, the positive effect of EFC is cancelled by their negative effects. Only those samples during the EC stage, whose intensities were less dependent on VWS and the underlying SST, could survive in extremely large EFC environments, or even re-intensify. For classical TCs(not in the EC stage), it was found that environments with a moderate EFC value generally below ~25 m s~(-1)d~(-1) are more favorable for a TC's intensification than those with extremely large EFC.     

Sources of anthropogenic fire ignitions on the peat-swamp landscape in Kalimantan,Indonesia

Fire disturbance in many tropical forests, including peat swamps, has become more frequent and extensive in recent decades. These fires compromise a variety of ecosystem services, among which mitigating global climate change through carbon storage is particularly important for peat swamps. Indonesia holds the largest amount of tropical peat carbon globally, and mean annual CO₂ emissions from decomposition of deforested and drained peatlands and associated fires in Southeast Asia have been estimated at ∼2000 Mt y-1. A key component to understanding and therefore managing fire in the region is identifying the land use/land cover classes associated with fire ignitions. We assess the oft-asserted claim that escaped fires from oil palm concessions and smallholder farms near settlements are the primary sources of fire in a peat-swamp forest area in Central Kalimantan, Indonesia, equivalent to around a third of Kalimantan's total peat area. We use the MODIS Active Fire product from 2000 to 2010 to evaluate the fire origin and spread on the land use/land cover classes of legal, industrial oil palm concessions (the only type of legal concession in the study area), non-forest, and forest, as well as in relation to settlement proximity. We find that most fires (68–71%) originate in non-forest, compared to oil palm concessions (17%–19%), and relatively few (6–9%) are within 5 km of settlements. Moreover, most fires started within oil palm concessions and in close proximity to settlements stay within those boundaries (90% and 88%, respectively), and fires that do escape constitute only a small proportion of all fires on the landscape (2% and 1%, respectively). Similarly, a small proportion of fire detections in forest originate from oil palm concessions (2%) and within close proximity to settlements (2%). However, fire ignition density in oil palm (0.055 ignitions km⁻²) is comparable to that in non-forest (0.060 km-2 ignitions km-²), which is approximately ten times that in forest (0.006 ignitions km⁻²). Ignition density within 5 km of settlements is the highest at 0.125 ignitions km⁻². Furthermore, increased anthropogenic activity in close proximity to oil palm concessions and settlements produces a detectable pattern of fire activity. The number of ignitions decreases exponentially with distance from concessions; the number of ignitions initially increases with distance from settlements, and, around from 7.2 km, then decreases with distance from settlements. These results refute the claim that most fires originate in oil palm concessions, and that fires escaping from oil palm concessions and settlements constitute a major proportion of fires in this study region. However, there is a potential for these land use types to contribute substantially to the fire landscape if their area expands. Effective fire management in this area should therefore target not just oil palm concessions, but also non-forested, degraded areas where ignitions and fires escaping into forest are most likely to occur.     

1998-2009年间台风不活跃期间热带云团活动分析

热带云团是台风生成的前兆,虽然一些研究将近20 a来台风不活跃与大尺度环境场相联系,但是还没有人分析台风不活跃期热带云团的活动特点。本文利用目前仅有的1989-2009年全球热带云团资料,分析了西北太平洋热带云团近20 a的变化特征。1998年以后西北太平洋台风生成减少主要发生在7-10月,集中在南海（13～23°N,110～120°E）和西北太平洋台风活动区域的东部（13～23°N,145～170°E）。热带云团除1月外各月都有增加的趋势,特别是与台风生成显著减少区域相联系的热带云团活动具有显著的增加趋势。通过对NCEP/NCAR再分析资料分析发现,1998年后热带云团活动增加与环境风垂直切变增加有关,而增强的垂直切变不利于台风生成。     

Validation of MODIS Vegetation Continuous Fields for monitoring deforestation and forest degradation: two cases in Mexico

This study assesses whether MODIS Vegetation Continuous Fields percent tree cover (PTC) data can detect deforestation and forest degradation. To assess the usefulness of PTC for detecting deforestation, we used a data set consisting of eight forest and seven non-forest categories. To evaluate forest degradation, we used data from two temperate forest types in three conservation states: primary (dense), secondary (moderately degraded) and open (heavily degraded) forest. Our results show that PTC can differentiate temperate forest from non-forest categories (p = 0.05) and thus suggests PTC can adequately detect deforestation in temperate forests. In contrast, single-date PTC data does not appear to be adequate to detect forest degradation in temperate forests. As for tropical forest, PTC can partially discriminate between forest and non-forest categories.     

Forest fragmentation in Massachusetts,USA: a town-level assessment using Morphological spatial pattern analysis and affinity propagation

Forest fragmentation has been studied extensively with respect to biodiversity loss, disruption of ecosystem services, and edge effects although the relationship between forest fragmentation and human activities is still not well understood. We classified the pattern of forests in Massachusetts using fragmentation indicators to address these objectives: 1) characterize the spatial pattern of forest fragmentation in Massachusetts towns using Morphological Spatial Pattern Analysis (MSPA); and (2) identify regional trends using archetypal towns in relation to town history, geography and socioeconomic characteristics. Six fragmentation indicators were calculated using MSPA for each town to represent patterns and processes of fragmentation. We then used these indicators and the proportion of forested land to group towns across Massachusetts with similar patterns of fragmentation. Six representative towns typify different types of forest fragmentation, and illustrate the commonalities and differences between different fragmentation types. The objective selection of representative towns suggests that they might be used as the target of future studies, both in retrospective studies that seek to explain current patterns and in analyses that predict future fragmentation trends.     

中国大陆流域分区TRMM降水质量评价

根据中国境内2 257个气象站点1998-2013年逐日降水资料,结合流域分区,采用探测准确性、相关系数以及相对误差等指标,对热带降水测量（TRMM）降水精度和一致性进行系统评价。结果表明:① TRMM日降水准确性从东南沿海向西北内陆递减;② 气象站点年均降水日数显著大于TRMM年均降水日数;③ 西北片区以外气象站点降水量和TRMM降水量在月尺度和年尺度上均具有较好的相关关系;④ 各流域年均TRMM面降水量均高于气象站点面降水量,且TRMM面降水量相对误差雨季较小,枯季较大;⑤ 各流域TRMM面降水量与气象站点面降水量演变趋势基本一致,南方各流域年降水量均呈减少趋势,北方各流域年降水量均呈增加趋势,全国尺度上年降水量呈微弱的减少趋势。     

基于随机森林模型的云南元阳梯田地形因子分析

为探究地形因子对梯田空间分布的影响,以云南元阳梯田坝达流域为研究区,运用GeoEye-1遥感卫星数据(2010年,1 m分辨率)和数字高程模型(20 m分辨率),提取梯田空间分布信息以及海拔高程、地形坡度、地形坡向、地面曲率、高程变异系数、地形起伏度、地面粗糙度、地表切割度、到水系距离9个地形因子。采用随机森林(Random Forest)方法建模,结合ROC曲线和AUC值对模型进行精度评价,根据随机置换残差均方减少量和因子作用曲线,探讨地形因子对梯田分布的影响规律。研究结果表明:该流域内梯田总面积1 158395 hm2,模型AUC值为0.947,海拔高度因子的随机置换残差均方减少量为38814,到水系距离因子为199.77,地面坡向因子为80.26,三者占总值的73.45%。由此可见,元阳梯田的空间分布主要受海拔高度、到水系距离、地面坡向3类地形因子的影响,其因子曲线表明梯田分布与地形因子间呈非线性关系。     

珠江流域降水集中度时空变化特征及成因分析

基于珠江流域内43个常规气象站点1960~2012年的逐日降水资料,计算了流域内各站点长期降水集中度(LCI)和逐年降水集中度(ACI);采用Mann-Kendall趋势检验法和Sen’s坡度检验法检测ACI时间上的变化趋势;同时采用反距离权重插值法(IDW)对LCI的区域特征和ACI的变化趋势进行空间插值以分析降水集中度的时空分布规律;采用随机森林(RF)算法对降水集中度的影响因子进行重要度分析。结果表明:(1)珠江流域逐年降水集中度ACI的年际变化不明显,东南部呈上升趋势,西北部呈下降趋势;(2)珠江流域西北部长期降水集中度LCI值偏小,即降水分布较平均;东南部长期降水集中度LCI值偏大,即降水较集中,表明该地区降水极值情况发生的几率相对较高,该空间分布趋势可能是受距离海洋的远近及海拔的影响;(3)众多气候影响因子中,东亚夏季季风(EASMI)对珠江流域的降水集中度影响最明显。