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.     

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.     

SAR图像海岸线检测的区域距离正则化几何主动轮廓模型

合成孔径雷达(SAR)卫星遥感图像可以极大地提高全国海岸线覆盖频率,然而受到海洋波浪所引起的随机海水表面粗糙度的影响,海岸目标与海水背景边界易混淆不清,因此本文提出了基于区域距离正则化几何主动轮廓模型(RDRGAC),引入距离正则项,解决重复初始化水平集函数为符号距离函数的问题,提高了算法收敛速度。此外,将区域面积项系数与SAR图像等效视数(ENL)建立非线性拟合关系,实现RDRGAC模型根据不同SAR遥感图像的自适应调整,改善海岸线自动提取精度。通过河北省北戴河和大连市金州湾SAR数据海岸线提取对比试验,验证了所提方法的有效性。     

热红外与可见光数据的云边缘高度匹配

高分辨率数据中云高度的差异性突显,特别是边缘处高度在云阴影识别和地表辐射估算等方面成为需要考虑的重要因素。热红外数据获取云高度分辨率较低、缺乏细部差异性特征,为解决这一问题,首先将对应的热红外和可见光数据进行特征点配准,再将基于热红外数据计算的云高度重采样至高分辨率,然后以基于欧式距离变换的围线搜索方法及距离加权将热红外云边缘高度匹配至对应的可见光图像,最后根据云阴影的相似度匹配方法确定真实云高度。结果表明,算法在遵循热红外云高信息分布变化规律的同时,可以得到较准确的高分辨率云边缘高度,一定程度上解决了热红外技术获取云高在分辨率上的局限,扩展了其在云高反演方面的作用。     

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.     

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。     

Stability and capsizing analysis of nonlinear ship rolling in wind and stochastic beam seas

Considering the actual seaway condition, stability and capsizing of nonlinear ship rolling system in stochastic beam seas is of significant importance for voyage safety. Safe zone are defined in the phase space plan of the unperturbed Hamilton system to qualitatively distinguish ship motions as capsize and noncapsize. Capsize events are defined by solutions passing out of the safe zone. The probability of such an occurrence is studied by virtue of the random Melnikov function and the concept of phase space flux. In this paper, besides conventional wave excitation, the effect of wind load is also taken into account. The introduction of wind load will lead to asymmetry, in other words, it transforms the symmetric heteroclinic orbits into asymmetric homoclinic orbits. For asymmetric dynamical system, the orbital analytic solutions and its power spectrum are not readily available, and the technique of discrete time Fourier transformation (DTFT) is used. In the end, as verification of theoretical critical significant wave height, capsizing probability contour diagram is generated by means of numerical simulation. The contour diagram shows that these analytical methods provide reliable and predictive results about the likelihood of a vessel capsizing in a given seaway condition.     

Possibilities of land use change analysis in a mountainous rural area: a methodological approach

Decreasing population density is a current trend in the European Union, and causes a lower environmental impact on the landscape. However, besides the desirable effect on the regeneration processes of semi-natural forest ecosystems, the lack of traditional management techniques can also lead to detrimental ecological processes. In this study we investigated the land use pattern changes in a micro-region (in North-Eastern Hungary) between 1952 and 2005, based on vectorised land use data from archive aerial photos. We also evaluated the methodology of comparisons using GIS methods, fuzzy sets and landscape metrics. We found that both GIS methods and statistical analysis of landscape metrics resulted in more or less the same findings. Differences were not as relevant as was expected considering the general tendencies of the past 60 years in Hungary. The change in the annual rate of forest recovery was 0.12%; settlements extended their area by an annual rate of 3.04%, while grasslands and arable lands had a net loss in their area within the studied period (0.60% and 0.89%, respectively). The kappa index showed a smaller similarity (~60%) between these dates but the fuzzy kappa and the aggregation index, taking into account both spatial and thematic errors, gave a more reliable result (~70–80% similarity). Landscape metrics on patch and class level ensured the possibility of a detailed analysis. We arrived at a similar outcome but were able to verify all the calculations through statistical tests. With this approach we were able to reveal significant (p < 0.05) changes; however, effect sizes did not show large magnitudes. Comparing the methods of revealing landscape change, the approach of landscape metrics was the most effective approach, as it was independent of spatial errors and ensuring a multiple way of interpretation.