退耕还林不同人工林类型对土壤养分的影响

对内蒙古敖汉旗2006年退耕还林的樟子松纯林、山杏纯林、山杏沙棘混交林和荒草地（对照）不同深度的土壤养分状况进行研究,结果表明：3种人工林的土壤有机质和碱解氮含量明显增加,山杏沙棘混交林中沙棘林带表层的速效磷含量明显增加,山杏纯林浅层的速效钾含量明显增加;3种人工林和荒草地的土壤养分随着土壤深度的增加而降低,表层土壤养分条件较好,说明土壤养分具有很强的表聚性;3种人工林与荒草地相比都不同程度地提高了土壤养分水平,樟子松纯林和山杏沙棘混交林中沙棘林带的土壤养分条件较好.     

Uncertainty analysis in data processing on the estimation of net carbon exchanges at different forest ecosystems in China

Information about the uncertainties associated with eddy covariance observations of surface-atmosphere CO₂ exchange is of importance for model-data fusion in carbon cycling studies and the accurate evaluation of ecosystem carbon budgeting. In this paper, a comprehensive analysis was conducted to investigate the influence of data processing procedures, focusing especially on the nocturnal data correction and three procedures in nonlinear regression method of gap filling [i.e., the selection of respiration model (REM), light-response model (LRM) and parameter optimization criteria (POC)], on the annual net ecosystem CO₂ exchange estimation at three forest ecosystems in ChinaFLUX with three yearly datasets for each site. The results showed that uncertainties caused from four methodological uncertainties were between 61 and 108?g?C?m^?2?year^?1, with 61?C93?g?C?m^?2?year^?1 (21?C30%) in a temperate mixed forest, 80?C107?g?C?m^?2?year^?1 (19?C21%) in a subtropical evergreen coniferous plantation and 77?C108?g?C?m^?2?year^?1 (16?C19%) in a subtropical evergreen broad-leaved forest. Factorial analysis indicated that the largest uncertainty was associated with the choice of POC in the regression method across all sites in all years, while the influences of the choice of models (i.e., REM and LRM) varied with climate conditions at the measurement station. Furthermore, the uncertainty caused by data processing procedures was of approximately the same magnitude as the interannual variability in the three sites. This result stressed the importance to understand the uncertainty caused by data processing to avoid the introduction of artificial between-year and between-site variability that hampers comparative analysis.     

Estimating forest area at the year 1990 by two-phase sampling on historical remotely sensed imagery in Italy

Forest area in the year 1990 is a figure of great interest under the Kyoto Protocol. This note is devoted to a scientific exercise for the probabilistic ex post assessment of such a figure in Italy. Estimation was performed by two-phase point sampling, which made use of historical remotely sensed imagery. In the first phase, a sample of 12 089 points was selected according to an unaligned systematic sampling and the selected points were classified in land-use categories by Landsat 5 TM imagery. In the second phase, a sample of 3000 points was selected by stratified sampling in which the strata were determined by the satellite classification and the selected points were classified by aerial photos, assumed as ground truth. A two-phase estimate of land-use coverage partitioning the Italian territory was obtained together with a conservative estimate of the sampling variance-covariance. The procedure has proved to be of relatively easy implementation and objective repeatability.     

Estimating models of vegetation fractional coverage based on remote sensing images at different radiometric correction levels

The images of post atmospheric correction reflectance (PAC), top of atmosphere reflectance (TOA), and digital number (DN) of a SPOT5 HRG remote sensing image of Nanjing, China were used to derive four vegetation indices (VIs), that is, normalized difference vegetation index (NDVI), transformed vegetation index (TVI), soil-adjusted vegetation index (SAVI), and modified soil-adjusted vegetation index (MSAVI). Based on these VIs and the vegetation fractional coverage (VFC) data obtained from field measurements, thirty-six VI-VFC relationship models were established. The results showed that cubic polynomial models based on NDVI and TVI from PAC were the best, followed by those based on SAVI and MSAVI from DN, with their accuracies being slightly higher than those of the former two models when VFC>0.8. The accuracies of these four models were higher in medium densely vegetated areas (VFC = 0.4–0.8) than in sparsely vegetated areas (VFC = 0–0.4). All the models could be used elsewhere via the introduction of a calibration model. In VI-VFC modeling, using VIs derived from different radiometric correction levels of remote sensing images could help explore and show valuable information from remote sensing data and thus improve the accuracy of VFC estimation.     

南京市六合区基于0.5m分辨率影像的林地落界及分析

林地落界是为了掌握林地的现有状况,为林地的保护利用规划提供重要的基础数据。高空间分辨率的遥感影像很大幅度地提高了室内林地落界的精度。该文是以高空间分辨率遥感影像为底图,在目视解译的方法上,结合二类调查基础数据,通过建立高清影像的判读解译标志,提取六合区林地,得到南京市六合区林地分布图,与基于中分辨率影像,采用面向对象的方法提取的林地分布图比较,并选取六合区龙袍镇为对象,分析比较了本次林地落界数据和二类调查数据的林地变化率和林地小班的差值变化。结果表明:0.5 m分辨率的影像能够达到将林地落实到田间地块的目的;六合区龙袍镇林地落界由林地到非林地变化率是15%,林地小班差值D的均值为0.24,说明利用高空间分辨率的遥感影像作为目视解译的底图,在林地地类识别和落界精度上都有较大的提高。     

Monitoring managed forest structure at the compartment-level under different silvicultural heritages: An exploratory data analysis in Italy

ABSTRACT

The more and more diffused multifunctional role addressed nowadays to public forests, calls for targeted analysis aimed at highlighting the overall outcome of different practices implemented on the same forest compartment, according to the locally prevailing function. This study was carried out in four Italian beech forests across a latitudinal gradient representative of multiple management history, stand structure, and dominant stand age. We analyze forest structure at the compartment scale before and after silvicultural practices. We aim to explore relationships and similarities between 10 stand attributes (mensurational and structural variables) to identify relevant indicators for the monitoring and management of forest ecosystems. Results indicate changing patterns of correlation and similarity among mensurational variables following practice implementation. A sensitivity gradient to silvicultural practice was finally identified within the four sites investigated as a result of the diverging stand structure. Our approach suggests a way and provides an insight for the design of adaptive forestry management practices required to meet environmental targets, in addition to the already acknowledged supply of primary goods and services.     

TM遥感数据在森林资源调查中图斑目视判读区划实例分析（续）

在现地验证之前,必须进行一致率统计,当一致率达到９０%以上,方能进行现地验证。目视判读采取一人判读、区划,另一人复核判读,复核者“背靠背”重新判读,     

Neutral and accumulator species in determining the spatial structure of tree species at different spatial scales

In 2014, a 40-ha undisturbed plot was established in the Beijing Songshan Nature Reserve. The spatial distribution and spatial associations of five dominant tree species of different height classes were examined using spatial point pattern analysis and the effects of these species on local community diversity assemblages were examined using the ISAR method. The dominant species were characterized by an aggregated distribution at spatial scales of 0–50 m. At smaller spatial scales, trees in larger height classes had significant positive and negative effects on the diversity of the lower height classes. However, at larger spatial scales this effect was diminished. At small scales(0–10 m), accumulator species had positive effects on species diversity, maintained an over-representative proportion of diversity in their proximity, and supported the ecological niche theory. At the larger scale(10–50 m),neutral species were dominant and had positive effects on species diversity, though repeller species, which had negative effects on species diversity, also contributed to diversity. Neutral and accumulator species together determined local species diversity, but the relative importance of the two was closely related to spatial scale. A combination of the ecological niche theory and neutral processes together determines species coexistence and biodiversity of an undisturbed pine forest.     

不同程度马尾松毛虫危害对松林植被群落的影响

采用样点调查法对不同程度马尾松毛虫危害松林的植被群落进行了调查。结果表明:不同程度马尾松毛虫危害对松林林分密度的影响不显著,但对松树生长量有着不同程度的影响,中、重度危害可降低松树的高度和胸径(重度危害三年后高度、胸径分别下降0.34 m和1.8 cm),轻度危害则可促进松林的生长;马尾松毛虫危害可适度改变松林的郁闭度和地表植被的盖度(中、重度危害后三年盖度分别上升15%和20%),对林下植被的恢复与生长有一定的促进作用;松林植被物种多样性分析表明,中、重度马尾松毛虫危害可有效增加林地植被物种的多样性,轻度危害则对林地植被物种多样性影响不大。     

A case study using remote sensing data to compare biophysical properties of a forest and an urban area in Northern Alabama,USA

ABSTRACT

The quantification of major biophysical features of forest and urban areas is important for assessing ecological service from land use change and is necessary for sustainable regional planning. This study compares biophysical indicators related to local climate, air quality, and hydrology using remote sensing and derived data at a representative forest area to a nearby urban area located in Huntsville, Alabama. Results indicate that (a) there was a higher albedo, a lower average air temperature, and 10% more annual precipitation in the forest area; the assumed air conditioner working time was about 7 days more per year in the urban area; (b) there was better air quality in the forest area based on lower levels of PM2.5, PM10, and SO₂; and (c) there was a higher latent heat, more runoff per year (both aboveground and belowground runoff), and a greater soil water content at the forest area. Although Huntsville is a small city, there were some profound biophysical differences in this urban area compared to the nearby forest. These results are useful for analyzing sustainability, planning regional resources (e.g., energy, air, and water), and estimating ecological services from forests.     

Logistic regression models for human-caused wildfire risk estimation: analysing the effect of the spatial accuracy in fire occurrence data

About 90% of the wildland fires occurred in Southern Europe are caused by human activities. In spite of these figures, the human factor hardly ever appears in the definition of operational fire risk systems due to the difficulty of characterising it. This paper describes two spatially explicit models that predict the probability of fire occurrence due to human causes for their integration into a comprehensive fire risk–mapping methodology. A logistic regression technique at 1 × 1 km grid resolution has been used to obtain these models in the region of Madrid, a highly populated area in the centre of Spain. Socio-economic data were used as predictive variables to spatially represent anthropogenic factors related to fire risk. Historical fire occurrence from 2000 to 2005 was used as the response variable. In order to analyse the effects of the spatial accuracy of the response variable on the model performance (significant variables and classification accuracy), two different models were defined. In the first model, fire ignition points (x, y coordinates) were used as response variable. This model was compared with another one (Kernel model) where the response variable was the density of ignition points and was obtained through a kernel density interpolation technique from fire ignition points randomly located within a 10 × 10 km grid, which is the standard spatial reference unit established by the Spanish Ministry of Environment, Rural and Marine Affairs to report fire location in the national official statistics. Validation of both models was accomplished using an independent set of fire ignition points (years 2006–2007). For the validation, we used the area under the curve (AUC) obtained by a receiver-operating system. The first model performs slightly better with a value of AUC of 0.70 as opposed to 0.67 for the Kernel model. Wildland–urban interface was selected by both models with high relative importance.     

Development and assessment of a gap-type model to predict the effects of climate change on forests based on spatial forest data

A gap-model was modified in order to utilise ground-true forest data to predict the effect of climate change on forests in Finland. The model's resonse to climate change was evaluated by using test scenarios of changing temperature and precipitation in Finland. Model computations indicated that in Southern Finland conifers, Norway spruce in particular, suffered from rapidly increasing temperature (0.5°C in a decade), but Scots pine derived a small benefit from a temperature increase of 0.1°C in a decade. Pendula birch profited by increasing temperature. In Northern Finland all tree species (Scots pine, Norway spruce, Pendula birch and Pubescent birch) used in simulations increased their stand volume and total production due to increased temperature. Precipitation changes had only little effect on stand volume and total production of trees on sites with coarse moraine as soil texture. The effect of soil texture on model performance was examined at a southern site under current climate using moraine, sand and silt as soil textures. Stand volume and total production of coniferous trees remained at a lower level on sand than on moraine soils or on silt. Response of birches to soil texture was similar to that of the conifers, but differences in total production between soil textures remained smaller.     

内蒙古自治区森林资源监测管理信息系统数据更新流程探讨

文章明确了内蒙古自治区森林资源监测管理信息系统二类数据更新流程,规范了数据更新流程中各个环节和各级用户做什么、怎么做、在什么时间做。为提高数据更新效率,保证数据更新准确真实、有效可用提供参考。     

冀北山区不同森林类型林木胸径Weibull分布规律研究

林木胸径是林分结构的基本特征,在林分生长过程中,胸径分布遵循一定的变化规律。该文利用Weibull分布密度函数对冀北山区几种典型林分类型林木胸径分布规律进行拟合。结果表明:落叶松桦树混交林的胸径分布预测值曲线拟合度不高,山杨白桦混交林预测值曲线拟合度非常高,为具有正偏的曲线图。油松蒙古栎混交林预测值曲线拟合度较低,具有明显的偏峰,但是对于胸径在15cm以上的树种拟合度较好。     

不同施钾水平对油茶树体生长和林地养分含量的影响

为了确定油茶幼林钾肥最适施用量,从而为油茶的科学施肥提供理论依据,以‘赣无’系列的5年生油茶林分为试验对象,设置了5个钾素水平处理(K0、K1、K2、K3、K4),1个施用复合肥的对照处理(CKFHF)和1个不施肥的处理对照(CK0),就不同施肥处理对油茶树体生长、叶片养分积累和土壤养分含量的影响情况进行了试验、测定与分析。结果表明:施肥均能显著提高油茶树体各生长指标的增幅和叶片及土壤中各种养分的含量;随着施钾水平的提高,油茶树体各生长指标的增幅和叶片中各种养分的含量均随之增加,K3处理的达到最大值,复合肥处理的肥效小于K2处理;随着施钾水平的提高,油茶林地土壤中速效钾和有机质的含量均显著性增加,而土壤中碱解氮和有效磷的含量则随着施钾水平的提高均先减小后增加,K4处理的降到最小值;对油茶叶片中的钾含量、土壤中的速效钾含量与施钾量进行拟合,得出其响应曲线,并确定了对油茶幼树施用钾肥的最适用量范围为317.72~322.25 g/株。     

森林病虫害遥感监测研究的现状与展望

论述了森林病虫害遥感监测技术研究现状、内容及技术方法,并对今后遥感技术在森林病虫害监测上的应用前景作了展望.     

不同经济发展阶段下我国的森林资源利用与保护

森林资源是经济发展过程中重要的投入要素,不同经济发展水平下的森林资源利用与保护具有明显的阶段性特征,反映了人类对森林资源的认识程度和发展林业的核心目标。依据经济发展阶段划分的相关理论,本文将我国的经济发展划分为4个阶段,研究了各发展阶段森林资源利用与保护的特点。分析认为:随着经济总量增加和经济增长方式的转变,森林利用的形式从单一趋向综合,对森林质量的要求不断提高,并决定着森林保护的形式和力度。     

Evaluating the potential of sentinel-2, landsat-8, and irs satellite images in tree species classification of hyrcanian forest of iran using random forest

ABSTRACT

Spatially explicit information on tree species composition of any forest provides valuable information to forest managers as well as to nature conservationists. In this study, the potential of three spaceborne sensors: (1) Landsat-8, (2) Sentinel-2, and (3) IRS-Pansharpened were compared by applying Random Forest (RF) classification algorithms to classify the three most common tree species: Pinus taeda, Alnus spp., and Populus spp., in Hyrcanian forest of Iran. Three RF models with optimized parameters of mtry and ntree were used for the classification of trees species. Based on our Overall Accuracy (OA) and Kappa Coefficient (KC) analysis, IRS-Pansharpened data showed the highest accuracy (OA = 84.9% and KC = 79.7%), followed by Landsat-8 (OA = 78.2% and KC = 70.6%), and Sentinel-2 (OA = 77% and KC = 70%). According to the Mean Decrease in Accuracy (MDA) criterion delivered as an output of RF, the near-IR spectral band was found on the top rank (high variable importance) as compared to all other spectral bands for tree species classification. The findings of this study can be used by the researcher, forest managers, economists and policy and decision makers in the context of sustainable forest management of Hyrcanian forest resources.