基于多端元光谱混合分析方法的大兴安岭火后植被盖度恢复研究

火干扰是北方针叶林结构、功能及动态的主要调节因子之一。研究火后植被恢复对理解火干扰和生态系统的交互作用具有重要意义。火烧迹地通常由植被与基质混合组成,在中低分辨率（ > 10 m）遥感影像中表现为混合像元,因此研究亚像元尺度上植被的恢复是精确量化植被恢复的关键。本研究以2000年大兴安岭呼中自然保护区中8700 hm²火烧迹地为研究区,以两期（2014年6月1日和2010年6月22日）中分辨率Landsat ETM+影像（30 m）为基础数据,比较多端元光谱混合分析（Multiple Endmember Spectral Mixture Analysis,MESMA）和归一化植被指数（Normalized Difference Vegetation Index,NDVI）获得的植被盖度,以高分辨率（2 m）WorldView-2影像（2014年7月1日）为验证数据,对两种方法计算的植被盖度精度进行比较。结果表明,MESMA方法获得的植被盖度（R²=0.691）与传统的NDVI获得的植被盖度（R²=0.700）精度无统计差异,中烈度下获得的植被覆盖精度高于低、高火烧烈度。为验证同一端元能否运用到不同时相的Landsat影像中,本研究将从2014年影像中获取的最佳端元运用到2010年影像中获得植被盖度图,结果表明2014年与2010年得到的RMSE（均方根误差）均值分别为0.0015和0.0065,说明最佳端元可用于不同时相的影像分解。本研究表明MESMA方法可有效监测北方针叶林中火后植被盖度恢复,并可运用于时间序列遥感影像监测植被恢复动态。     

基于实测光谱混合像元分解的苹果园地遥感提取技术

以山东省栖霞市为研究区,对苹果花期的TM影像进行混合像元分解,提取苹果园地信息.基于实测地物光谱端元,利用小波变换对线性分解模型进行改进,采用实测端元改进后线性分解模型、实测端元线性分解模型、TM影像端元线性分解模型分别提取研究区苹果园地信息,并以ALOS数据进行精度评价.结果表明:经过精确的大气及地形校正后,可以利用实测光谱端元进行混合像元分解,面积精度＞97％,对丰度图像的归一化植被指数(NDVI)值与ALOS数据的平均NDVI值进行回归分析,R2＞0.8;利用小波变换对线性分解模型进行改进,可在一定程度上提高分解精度.     

多尺度遥感数据协同的干旱地区植被覆盖度提取

纯植被像元获取是植被覆盖信息遥感反演的必要环节。干旱地区植被分布零散稀疏,使用中、低分辨率遥感数据提取植被覆盖度时,难以获取纯植被像元,致使植被覆盖度提取精度较低。针对上述问题,本文提出一种基于多尺度遥感数据协同的干旱区植被覆盖度反演方法。该方法利用空间分辨率较高的Landsat-8 OLI数据确定纯植被像元,考虑到不同传感器之间的光谱差异,使用实测地物光谱数据进行光谱转换,代替中等分辨率MODIS数据的纯植被像元,应用于像元二分模型,选择典型的干旱区新疆阜康市为研究区,进行植被覆盖度反演实验,最后使用无人机航拍影像对反演结果进行精度验证。结果表明,植被覆盖度反演结果精度较高,与实测值间存在较高的相关性(R2=0.75),均方根误差较低(RMSE=0.10)。该方法能够有效提高干旱区植被覆盖度反演精度,可为利用中低分辨率数据研究干旱地区生态环境变化提供一种新思路。     

林火干扰对土壤性质及温室气体通量的影响

林火干扰是森林生态系统重要的干扰因子。林火的发生烧毁大量的森林资源,释放温室气体到大气当中,同时林火对土壤物理、化学性质以及土壤微生物都会产生一定的影响,进而影响到地-气主要温室气体的释放。本文综述了不同强度的森林火灾对土壤物理、化学性质以及土壤微生物的影响;森林火灾发生后的不同时间序列上地-气主要温室气体CO2、CH4、N2O通量的变异;尤其是在全球气候变暖背景下,冻土区森林火灾发生后,随冻土的融化,温室气体排放;林火发生时高温缺氧环境下往往会形成燃烧程度不同的木炭;本文还综述了火烧迹地木炭的不同管理方式如火场清理或就地掩埋,及其对火烧迹地土壤性质以及温室气体通量的影响。最后,提出今后应该注意的几个问题,并指出未来可能的研究拓展方向。     

兴安落叶松林火烧迹地土壤有效磷与土壤微生物生物量磷时空演变特征

野火是大兴安岭活跃的生态干扰因子，显著影响火烧迹地土壤有效磷(AP, Available Phosphorus)和土壤微生物生物量磷(MBP, Microbial Biomass Phosphorus),本文旨在了解兴安落叶松林火烧迹地AP、MBP的时空演变特征，并在此基础上探究两者间的偶联机制。采用“以空间换时间”的研究方法，于大兴安岭塔河地区兴安落叶松林火烧迹地选取实验样地，于未过火兴安落叶松林选取对照样地，踏查每个样地的海拔、坡度、坡向、坡位信息，测定火烧迹地土壤AP、MBP含量，分析兴安落叶松林火烧迹地AP与MBP的时空演变特征。火干扰后，火烧迹地土壤AP、MBP含量均随恢复时间表现出先减少后增加的趋势，恢复初期火烧迹地MBP含量显著低于未过火样地，AP含量显著高于未过火样地(P<0.05);不同海拔火烧迹地AP、MBP含量差异显著(P<0.05),不同海拔未过火样地AP、MBP含量均无显著差异(P>0.05)。火烧迹地土壤MBP、AP的随机森林回归模型的模型总解释度约为84%,而未过火样地的模型总解释度约为60%,两个模型均达到了极显著水平(P<0.0...     

黑龙江省大兴安岭林区火烧迹地森林更新及其影响因子

林火干扰是大兴安岭森林更新的影响因子之一,研究火烧迹地森林更新的影响因子(立地条件、火前植被、火干扰特征)对理解生态系统的结构、功能和火后演替轨迹具有重要意义。选取呼中及新林林业局55个代表性火烧样地,利用增强回归树分析法分析了火烧迹地森林更新的影响因素。结果表明:(1)立地条件是影响针、阔叶树更新苗密度的主要因素;海拔对针叶树更新苗密度的影响最大;坡度对阔叶树更新苗密度影响最大;(2)距上次火烧时间对针叶树更新苗比重影响最大,其次是林型;(3)中度林火干扰后森林更新状况好于轻度和重度火烧迹地。根据火烧迹地森林更新调查分析可知:林型影响火后演替模式,火前为针叶树或阔叶树纯林,火后易发生自我更新(火后树种更新组成与火前林型相同),而针阔混交林在火干扰影响下易于发生序列演替(火后初期以早期演替树种更新为主)。     

火干扰对苍山云南松林步甲群落的影响

在云南省大理市苍山火烧迹地采用陷阱法初步研究了火干扰对苍山云南松林步甲群落的影响.其中未火烧迹地步甲群落由7属14种组成;火烧迹地步甲群落由6属8种组成,样地同多度没有显著差异.未火烧迹地步甲群落物种组成不同于火烧迹地,但部分火烧迹地与未火烧迹地接近;健步甲Carabus solidior是森林生境良好的指示物种(IndVal=0.9489,P=0.001).研究显示,火干扰已经改变了云南松林步甲群落组成,降低了步甲群落的多样性.     

不同火烈度火烧迹地内油松叶功能性状的变化

叶功能性状对林火的响应是林火生态领域的研究热点之一,研究火后油松叶功能性状变化能够揭示油松为适应火环境形成的生长策略,为促进油松火后恢复提供参考。以山西省沁源县火烧迹地内油松为研究对象,选择当年生叶片分析叶功能性状在不同火烈度(未过火、轻度火烧、中度火烧)火烧迹地间的变化规律,并研究不同火烧迹地内叶经济谱的变化特征。结果表明: 除氮磷比外,叶功能性状在不同火烈度的火烧迹地间存在显著差异,其中,叶面积的差异最为明显,是最敏感的性状。随火烧迹地内火烈度的增加,叶面积、叶厚度、叶干物质含量、叶氮含量和叶磷含量升高,比叶面积、叶有机碳含量降低。部分叶功能性状间存在显著的相关关系,但其相关性在不同火烈度的火烧迹地间存在差异。叶经济谱沿着“未过火-轻度火烧-中度火烧”的火烧迹地环境总体向“快速投资-收益型”的资源权衡策略移动,低烈度火烧迹地内油松的生长恢复会加快。     

基于遥感估算方法的干旱区植被覆盖度适应性评价

与浓密植被覆盖区相比,半干旱、干旱地区因植被覆盖较少、空间分布零散的特点,致使利用遥感手段提取植被覆盖度(vegetation fractional coverage,VFC)的精度较低。针对上述问题,本文首先分别讨论了回归模型法、像元二分法和混合像元分解法3种典型的VFC提取方法在干旱区VFC反演应用中的适应性及限制性因素;然后通过分析干旱区纯土壤端元植被指数值(NDVIs)对植被覆盖度的敏感性,将基于地面光谱测量的NDVIs应用于传统方法进行改进,以新疆大黄山典型干旱区为例,使用Landsat-8 OLI数据,进行植被覆盖度反演实验,最后使用实测VFC数据对反演结果进行精度验证。验证结果表明:基于混合像元分解理论的全约束最小二乘法在干旱区植被覆盖度的反演精度最高,反演值与实测值间的相关性(R~2)达到0.989,其次为改进的像元二分法(R~2=0.848)和回归模型法(R~2=0.827)。     

基于C5.0的钱塘江流域地区土地利用/覆被信息提取研究

选取钱塘江中游地区约348 km²为实验区,综合归一化植被指数、纹理信息和数字地形模型(DEM)派生的高程、坡度等辅助数据,对SPOT5影像的光谱特征进行扩展,建立基于C5.0算法的模型,实现对土地利用信息的自动提取,并将分类结果与基于传统像元的最大似然分类结果作比较。结果表明,训练样本的有效性和辅助特征数据的参与可排除干扰信息;随着样点数量的增加,分类精度提高;决策树向决策规则的转化,能够在保证精度的基础上使规则更易理解;利用C5.0算法的总精度达到94.68%,较最大似然分类法提高了7.37%,有效实现了高精度分类,是保证钱塘江流域地区土地利用遥感信息快速准确提取的方法之一。     

Phenology-based,remote sensing of post-burn disturbance windows in rangelands

Wildland fire activity has increased in many parts of the world in recent decades. Ecological disturbance by fire can accelerate ecosystem degradation processes such as erosion due to combustion of vegetation that otherwise provides protective cover to the soil surface. This study employed a novel ecological indicator based on remote sensing of vegetation greenness dynamics (phenology) to estimate variability in the window of time between fire and the reemergence of green vegetation. The indicator was applied as a proxy for short-term, post-fire disturbance windows in rangelands; where a disturbance window is defined as the time required for an ecological or geomorphic process that is altered to return to pre-disturbance levels. We examined variability in the indicator determined for time series of MODIS and AVHRR NDVI remote sensing data for a database of ∼100 historical wildland fires, with associated post-fire reseeding treatments, that burned 1990–2003 in cold desert shrub steppe of the Great Basin and Columbia Plateau of the western USA. The indicator-based estimates of disturbance window length were examined relative to the day of the year that fires burned and seeding treatments to consider effects of contemporary variability in fire regime and management activities in this environment. A key finding was that contemporary changes of increased length of the annual fire season could have indirect effects on ecosystem degradation, as early season fires appeared to result in longer time that soils remained relatively bare of the protective cover of vegetation after fires. Also important was that reemergence of vegetation did not occur more quickly after fire in sites treated with post-fire seeding, which is a strategy commonly employed to accelerate post-fire vegetation recovery and stabilize soil. Future work with the indicator could examine other ecological factors that are dynamic in space and time following disturbance – such as nutrient cycling, carbon storage, microbial community composition, or soil hydrology – as a function of disturbance windows, possibly using simulation modeling and historical wildfire information.     

Spatial and temporal variability of fires in relation to ecosystems,land tenure and rainfall in savannas of northern South America

Fire is a predominant factor forcing global terrestrial biomass dynamics, with more than 30% of the land surface showing frequent burning, particularly in the tropics, where it mostly affects savannas ecosystems annually. Savannas, which cover approximately 269 million ha in South America, play a major role in the global carbon cycle. They are affected by increasing human pressures and global climate change. Using satellite data, this study quantifies vegetation burning in the Colombian Llanos savannas for the period 2000–2008, and analyzes how fire spatial pattern, frequency and extent vary with ecosystem type, land tenure and rainfall. On average 2.75±0.5 million ha (24±4.2%) of the savannas burn each year. Burned area is highly variable, with 3.4 million ha burned in 2002–2003 and <1.9 million ha in 2005–2006. However, during the 2000–2008 period near of 3.7 million ha (33.5%) of the savannas never burned. Compared with the average 8–10 years of fire return time for the tropics and subtropics, these savannas burn twice as often. In addition, the average burn size figure for tropical and subtropical grassland savannas (with <5% trees) of 7000 ha (median 5000 ha), is about seven times the average burned patch size we found in our study. Fires predominate in the well‐drained high plain savannas, lowest figures occurring along the Andean foothills, in forested areas and in pasture and croplands. Annual proportion burned varies with land tenure, being highest in National Parks. This study is the first complete regional map of fire disturbance in a South American savanna. This detailed regional data provides a unique opportunity for increasing the accuracy of global carbon emission calculations.     

森林火灾碳排放计量模型研究进展

森林火灾是森林生态系统重要的干扰因子,是导致植被和土壤碳储量减少的重要途径之一.森林火灾含碳气体排放对大气碳平衡及全球气候变化具有重要影响,科学有效地对其进行计量,对了解森林火灾在全球碳循环和碳平衡中的地位具有重要意义.本文从3个方面阐述森林火灾碳排放计量模型的研究进展： 森林火灾直接排放总碳和含碳气体计量方法;森林火灾碳排放计量模型的影响因子及计量参数;森林火灾碳排放计量中不确定性原因剖析.最后提出了提高碳排放计量定量化的3种路径选择： 利用高分辨率遥感数据、改进算法、提高森林火灾面积的估测精度、结合有效可燃物计量模型,提高估测可燃物载量的准确率;使用高分辨率遥感影像,并结合室内控制实验、野外试验与火烧迹地调查确定燃烧效率;通过大量室内燃烧实验和野外空中采样来确定排放因子和排放比.     

Assessing the response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach

Fire is a common disturbance in the North American boreal forest that influences ecosystem structure and function. The temporal and spatial dynamics of fire are likely to be altered as climate continues to change. In this study, we ask the question: how will area burned in boreal North America by wildfire respond to future changes in climate? To evaluate this question, we developed temporally and spatially explicit relationships between air temperature and fuel moisture codes derived from the Canadian Fire Weather Index System to estimate annual area burned at 2.5° (latitude × longitude) resolution using a Multivariate Adaptive Regression Spline (MARS) approach across Alaska and Canada. Burned area was substantially more predictable in the western portion of boreal North America than in eastern Canada. Burned area was also not very predictable in areas of substantial topographic relief and in areas along the transition between boreal forest and tundra. At the scale of Alaska and western Canada, the empirical fire models explain on the order of 82% of the variation in annual area burned for the period 1960–2002. July temperature was the most frequently occurring predictor across all models, but the fuel moisture codes for the months June through August (as a group) entered the models as the most important predictors of annual area burned. To predict changes in the temporal and spatial dynamics of fire under future climate, the empirical fire models used output from the Canadian Climate Center CGCM2 global climate model to predict annual area burned through the year 2100 across Alaska and western Canada. Relative to 1991–2000, the results suggest that average area burned per decade will double by 2041–2050 and will increase on the order of 3.5–5.5 times by the last decade of the 21st century. To improve the ability to better predict wildfire across Alaska and Canada, future research should focus on incorporating additional effects of long‐term and successional vegetation changes on area burned to account more fully for interactions among fire, climate, and vegetation dynamics.     

Estimation of forest area and its dynamics in Russia based on synthesis of remote sensing products

We review up-to-date, open access remote sensing (RS) products related to forest. We created a hybrid forest/non-forest map using geographically weighted regression (GWR) based on a number of recent RS products and crowdsourcing. The hybrid map has spatial resolution of 230 m and shows the extent of forest in Russia in 2010. We estimate area of Russian forest as 711 million ha (in accordance with Russian national forest definition). Compared to official data of the State Forest Register (SFR), RS estimates the area of forest to be considerably larger in European part (+12.2 million ha or +8%) and smaller in Asian (–39.8 million ha or–7%) part of Russia. We report the changing forest area in 2001–2010 and discuss main drivers: wildfire and encroachment of abandoned arable land. The methodology used here can by applied for monitoring of forest cover and enhancing the forest accounting system in Russia.     

Human intervened post-fire forest restoration in the Northern Great Hing’an Mountains: a review

The devastating fire in May 1987 in the northern Great Hing’an Mountains created a mosaic of burned severity. Subsequent log harvesting and tree planting complicated the restoration process. Based on intensive field work and GIS analysis for the burned area, we studied the landscape pattern change in relation with its influencing factors, the restoration of some ecosystem functions and the long-term effect of human planting on vegetation restoration. A post-fire vegetation restoration process was also established using spatial series instead of temporal series. The results indicated that coniferous forest, broad-leaved forest and mixed forest increased obviously in the burned area. Factors influencing the restoration process are ranked as the burned severity, way of restoration (planting, promoted restoration or natural restoration) and topographical factors. The latter was further ranked as the slope, elevation, slope position and aspect. Primary productivity, hydrological functions, habitats for wild animals and permanent frozen soil of the area have all largely been restored to the pre-fire level after more than 15 years. Parameters demonstrated a transitional character of the forest from the early succession stage to middle stage. LANDIS simulation for the long-term forest succession under pure natural restoration and human-intervened restoration indicated that post-fire tree planting largely influenced the age structure, spatial pattern and timber stock of dominant species such as Larix gmelini, Betula platyphylla and Pinus sylvestris var. mongolica. In general, the influence of post-fire human planting can remain for more than 200 years.     

Remote sensing approach to detect post-fire vegetation regrowth in Siberian boreal larch forest

Remote sensing with time series data offers considerable potential in the trajectory of post forest fire dynamics beyond the current monitoring of structural attributes that are displayed in the post-fire area. Many studies have addressed this topic by using time series remote sensing indices; however, this approach has sometimes been demonstrated as an unrealistic and biased representation of the post-fire forest patterns due to the saturation issues of vegetation indices. These saturation issues then lead to an underestimation of the forest successional stages and an overestimation of the forest recovery rate. This paper aims to develop a framework for trajectory of the post-fire forest patterns in the Siberian boreal larch forest (Larix sibirica) with the synergistic use of different remote sensing based vegetation-cover indicators derived from the Landsat time series and the WorldView-2 images. A time-series of the forest recovery index (FRI) and fractional vegetation cover (FVC) has been analyzed to estimate the rates of forest regeneration and vegetation recovery across different burn severity levels in the Siberian larch forest. The results showed that the FRI method can be used to observe the regrowth of the larch forest from the tenth year after the fire overlapping with the period of significant increase in the sapling stem volume. The post-fire larch forest canopy can fully recover to the pre-fire condition with respect to the magnitude of the FRI values after 30–47 years where the highest regeneration rate was observed in the moderate burn severity areas followed by the low and high burn severity. On the other hand, the FVC method was positively correlated with burn severity and more sensitive for evaluating the early stages of the forest succession in which the FVC dramatically increases after 5–6 years after the fire. The significant growth of FVC was accentuated by the maximum emergence of the sapling density as well as the rapid growth of herbaceous plants, grasses, shrubs, and shade-intolerant trees immediately after the fire, which could not be evaluated using the FRI. Both time series of the FRI and the FVC are valuable tools for determining the dominant stages of the post-fire larch forest succession in order to understand the relationships between fire disturbance and natural cycles of the boreal larch forest.     

Fire effects on the composition of a bird community in an Amazonian savanna (Brazil).

The effects of fire on the composition of a bird community were investigated in an Amazonian savanna near Alter-do-Ch?o, Pará (Brazil). Mist-net captures and visual counts were used to assess species richness and bird abundance pre- and post-fire in an approximately 20 ha area. Visual counts along transects were used to survey birds in an approximately 2000 ha area in a nearby area. Results using the same method of ordination analysis (multidimensional scaling) showed significant effects of fire in the 20 ha and 2000 ha areas and strongly suggest direct effects on bird community composition. However, the effects were different at different spatial scales and/or in different years, indicating that the effects of fire vary spatially and/or temporally. Bird community composition pre-fire was significantly different from that found post-fire. Using multiple regression analysis it was found that the numbers of burned and unburned trees were not significantly related to either bird species richness or bird abundance. Two months after the fire, neither bird species richness nor bird abundance was significantly related to the number of flowering trees (Lafoensia pacari) or fruiting trees (Byrsonima crassifolia). Since fire is an annual event in Alter-do-Ch?o and is becoming frequent in the entire Amazon, bird community composition in affected areas could be constantly changing in time and space.     

Assessment of forest recovery at Wu-Ling fire scars in Taiwan using multi-temporal Landsat imagery

Normalized Burn Ratio (NBR), a satellite-derived index widely used to map the burned area and to assess burn severity level, was reconceptualized to propose the indices of post-fire recovery condition and resilience. Time series Landsat imagery during 1994–2015 were used to observe the forest recovery of Wu-Ling fire scars in Taiwan. Burn Recovery Ratio (BRR) was newly developed as the indicator to better clarify the forest recovery status. Results show that BRR coupled with dNBR (bi-temporal NBR) could quantitatively describe the level of forest recovery through the heterogeneity of forest landscape which is confirmed by field investigation. Time of complete recovery (t_c), indicator of post-fire resilience, were predicted using curve-fitting of forest recovery trajectories to the exponential decay function. The spatial distribution of t_c could reveal the patterns of post-fire recovery across the fire scars. For wildfire prevention, the issue of fire recurrence should be concerned at the areas of fire-adapted species with low t_c value. For areas of deterioration sites with high t_c value, the rehabilitation project should be implemented to accelerate forest restoration.