卫星像片估测森林蓄积量的方法初探

根据分层抽样设计理论,结合卫星像片的分辩能力,将调查地区现实林分出若干种森林类型,利用ＴＭ卫星影像图判读求算出该地区各森林类型（层）的面积,面积权重,并逐层布设样地,实测样地蓄积,并用层抽样蓄积估测核该层蓄积量,汇总各层估测蓄积量即为该调查地区活立木的总蓄积量。     

湖南省森林资源连续清查遥感抽样技术的对比分析

以湖南省2004年森林资源连续清查遥感样地为研究对象,在抽样可靠性指标为95%的情况下开展遥感抽样技术研究,采用分层抽样与系统抽样进行比较。抽样点间隔为4 km×8 km,4 km×4 km,4 km×2 km,2 km×4 km,2 km×2 km 5种方式。结果表明:(1)抽样强度相同情况下,分层抽样精度大于系统抽样;(2)抽样点间隔越小系统抽样精度、分层抽样精度越高;(3)抽样点间隔对样本数量少的地类抽样精度影响最大;(4)抽样总体精度以抽样点间隔2 km×2 km分层抽样最大。     

湘西州森林生态系统服务价值评估初探

根据中华人民共和国林业行业标准《森林生态系统服务功能评估规范》所提供的方法和参数,采用湘西自治州＂十五＂森林资源清查数据和国内有关专家的研究成果,综合运用市场价值法、费用代替法、替代工程法等方法,对湘西州森林生态系统的服务价值进行定量评定估算,得出该地区森林生态系统涵养水源价值319.08亿元·a^-1,保育土壤价值53.60亿元·a^-1,固碳释氧价值59.12亿元·a^-1,林分营养积累价值3.10亿元·a^-1,净化大气环境价值27.64亿元·a^-1,生物多样性保护价值49.13亿元·a^-1,森林生态系统服务总价值511.67亿元·a^-1。评估结果表明：森林在为人类生存提供大量的直接产品的同时,还为人类提供了巨大的间接服务。     

The national forest inventory in China:history-results-international context

Background:National forest resource assessments and monitoring,commonly known as National Forest Inventories(NFI's),constitute an important national information infrastructure in many countries.Methods:This study presents details about developments of the NFI in China,including sampling and plot design,and the uses of alternative data sources,and specifically· reviews the evolution of the national forest inventory in China through the 20 th and 21 st centuries,with some reference to Europe and the US;· highlights the emergence of some common international themes:consistency of measurement; more efficient sampling designs; implementation of improved technology; expansion of the variables monitored; scientific transparency;· presents an example of how China's expanding NFI exemplifies these global trends.Results:Main results and important changes in China's NFI are documented,both to support continued trend analysis and to provide data users with historical perspective.Conclusions:New technologies and data needs ensure that the Chinese NFI,like the national inventories in other countries,will continue to evolve.Within the context of historical change and current conditions,likely directions for this evolution are suggested.     

Possibilities for harmonizing national forest inventory data for use in forest biodiversity assessments

Representatives of the national forest inventories (NFIs) of27 European countries and the USA evaluated possibilities fora common approach to forest biodiversity reporting. The projectwas conducted under the auspices of COST (European Cooperationin the field of Scientific and Technical Research) Action E43,‘Harmonisation of National Forest Inventories in Europe:Techniques for Common Reporting’. Based on the analysisof responses to an initial questionnaire regarding the mostecologically important and technically feasible variables formonitoring forest biodiversity using NFI data, 16 key variableswere selected. Responses to a second questionnaire consistingof six questions regarding assessment of the 16 key variablesrevealed that the NFIs of most responding countries alreadyassess a large proportion of these variables. Each of the 16variables is assessed in at least eight NFIs. However, the responsesregarding assessment methods and necessary field crew expertisevaried considerably. As a first example, although tree diametersat breast height (d.b.h.) are assessed by every country, thereis a wide range of minimum d.b.h. thresholds from 0 mm in Finlandto 12 cm in Cyprus and Switzerland. As a second example, eightcountries estimated that almost all inventory variables requirehighly skilled forest staff with specialized training, but mostcountries agree that a middle level of expertise is sufficient.Despite differences in current NFI methods, overall, the resultsof the study indicate positive possibilities for achieving amoderate level of European-wide harmonization.     

Mapping and spatial uncertainty analysis of forest vegetation carbon by combining national forest inventory data and satellite images

Forests play an important role in carbon sinks and mitigation of atmospheric concentrations of carbon dioxide and greenhouse effect. Given that sample plots used for collection of forest carbon observations are often much smaller than the map units of forest carbon at regional, national, and global scales, scientists are currently experiencing two challenges. The first challenge is to produce reliable maps of forest carbon using the data from inconsistent sizes of plots and image pixels. Also, because estimates of forest carbon normally contain uncertainties, the second challenge is to accurately model propagation of uncertainties from input data to output results. In this study, a methodology for mapping and analyzing spatial uncertainty of forest carbon estimates was developed to address these challenges. The methodological framework consisted of two methods. The first one was up-scaling method that combined and scaled up existing national forest inventory plot data and satellite images from smaller sample plots and image pixels to larger map units. The second one was spatial uncertainty analysis and error budget method that entailed modeling propagated uncertainties through a geostatistical mapping system. A case study using 46 permanent national forest inventory plots from Wu-Yuan County, Jiangxi, China, was undertaken to test this methodology. The results showed that this method reproduced not only the spatial distribution of forest carbon but also the spatial pattern of variances of its estimates and was able to quantify the contributions of uncertainties from the field plot data and satellite images to the uncertainties of forest carbon estimates. Thus, this study, to some extent, overcame the gaps that currently exist in the generation and assessment of forest carbon estimation maps. Moreover, the results showed that in this case study, the variation of the band ratio defined as (TM2 + TM3 + TM5)/TM7 contributed more uncertainties to the estimates of forest carbon than the variation of the plot data. In addition, we also found out that the product of the input plot forest carbon variance and the band ratio variance, implying the interaction between these two variables, reduced the uncertainties of the forest carbon estimates.     

Mapping and modeling forest tree volume using forest inventory and airborne laser scanning

In this paper, we present a study on the efficiency of multi-return LIDAR (Light Detection Ranging) data in the estimation of forest stem volume over a multi-layered forest area in the Italian Alps. The goals of this paper are (1) to verify the usefulness of multi-return LIDAR data compared to single-return data in forest volume estimation and (2) to define the optimal resolution of a stem volume distribution raster map over the investigated area. To achieve these goals, raw data were segmented into a net, and different cell dimensions were investigated to maximize the relationship between the LIDAR data and the ground-truth information. Twenty predicting variables (e.g., mean height, coefficient of variation) have been extracted from multi-return LIDAR data, and a multiple linear regression analysis has been used for predicting tree stem volume. Experimental results found that the optimal resolutions of the net square cells were 40 m. The analysis indicated that in a mixed multi-layered forest, characterized by a complex vertical structure, the correct selection of the map spatial resolution and the inclusion of the secondary-return data were important factors for improving the effectiveness of the laser scanning approach in forest inventories. The experimental tests showed that the chosen model is effective for the estimation of stem volume over the analyzed area, providing good results on all the three considered validation methods.     

Remote sensing and forest inventory for wildlife habitat assessment

Researchers and managers undertaking wildlife habitat assessments commonly require spatially explicit environmental map layers such as those derived from forest inventory and remote sensing. However, end users of geospatial products must often make choices regarding the source and level of detail required for characterizing habitat elements, with few published resources available for guidance. We appraised three environmental data sources that represent options often available to researchers and managers in wildlife ecological studies: (i) a pre-existing forest inventory; (ii) a general-purpose, single-attribute remote sensing land cover map; and (iii) a specific-purpose, multi-attribute remote sensing database. The three information sources were evaluated with two complementary analyses: the first designed to appraise levels of map quality (assessed on the basis of accuracy, vagueness, completion, consistency, level of measurement, and detail) and the second designed to assess their relative capacity to explain patterns of grizzly bear (Ursus arctos) telemetry locations across a 100,000-km² study area in west-central Alberta, Canada. We found the forest inventory database to be reasonably functional in its ability to support resource selection analysis in regions where coverage was available, but overall, the data suffered from quality issues related to completeness accuracy, and consistency. The general-purpose remote sensing land cover product ranked higher in terms of overall map quality, but demonstrated a lower capacity for explaining observed patterns of grizzly bear habitat use. We found the best results using the specific-purpose, multi-attribute remote sensing database, and recommend that similar information sources be used as the foundation for wildlife habitat studies whenever possible, particularly those involving large areas that span jurisdictional boundaries.     

Evaluation of tree and stand-level growth models using national forest inventory data

Two models, Carbware (CW) and Growfor (GF), of different resolution and based on different frameworks were evaluated in relation to stand-level forecasts of volume and basal area using Ireland’s National Forest Inventory (NFI) data. CW is a distance-independent single-tree model that is based on diameter increment. GF is a stand-level dynamic empirical model that uses the von Bertalanffy–Richards growth equation in a state-space framework. NFI data were used as input to the models, and each model’s projections were compared to NFI data at the next measurement cycle. The NFI is a permanent sampling system with the objective to assess the composition and extent of the forest estate. A subset of the NFI was used in the study, single-species even-aged plots comprising Sitka spruce and lodgepole pine. The accuracy and performance of the CW and GF models were analysed using residual analysis and standard statistical techniques. Results show that both models require improvement, though the study has raised concerns regarding the suitability of the NFI data for this type of investigation.     

Effects of forest management on the amount of deadwood in Mediterranean oak ecosystems

Context

Deadwood is an important habitat for vertebrate and invertebrate species, a key factor in the nutrient cycle and a valuable carbon pool. Difference in the deadwood C stock depends on many variables such as forest type, microclimate and forest management.

Aims

We investigated the relationship between C stock in deadwood and forest management in oak stands of southern Italy.

Methods

Deadwood C stock was quantified in 74 forest stands under intensive, extensive or multifunctional management. The relationship between management and C stock in deadwood was assessed taking into account the decay class and the type of deadwood (snags, stumps and logs).

Results

Intensively managed forests are characterized by significantly lower mean levels of deadwood C than the other forms of management. Multifunctional management resulted in the highest level of C, mainly in logs and snags, while extensive management resulted in high levels of C storage concentrated in snags.

Conclusion

Results of the research highlight that forest management practices greatly influence the quantitative and qualitative presence of deadwood in forests.     

基于CASIO fx-5800P计算器的森林资源规划设计调查蓄积量计算

基于CASIOfx-5800P计算器的可编程功能,以及其所具有的便携性、持久续航性和广泛应用性等特点,实现新一轮森林资源规划设计调查相关蓄积的自动化计算,蓄积计算类型包括标准地蓄积、控制样地蓄积和小班蓄积计算。本文分别给出三种蓄积计算的全部程序代码和使用说明。     

Effect of cluster configuration and auxiliary variables on the efficiency of local pivotal method for national forest inventory

ABSTRACT

Planning a forest inventory comprises making decisions related to the sampling strategy: cluster configuration, sample size and sample allocation within the survey area. Cluster configuration includes deciding on the number of sample plots within the cluster and distances between them. Available resources set the limit for field work in terms of man-days. If the time consumption for measurements is known, the sample size can be determined under the constraint. In this study, we simulated the second phase of inventory sampling with fixed time resources by replicating sample selection with a spatially balanced sampling utilizing local pivotal method (LPM) for different cluster configurations to find the most efficient. As a result, the temporary cluster configuration was changed from 9 to 5-sample plot configuration in a pilot inventory. Further, the sample selection was performed with LPM having total growing stock volume and broadleaf volume proportion as auxiliary information. The pilot results were aligned with the time series in respect to forest area and total growing stock volume, but in tree species groups deviations were observed in growing stock volume. A more comprehensive optimization should include the travelling routes, the plot-to-plot distances and the plot design. In any case, the result is region specific.     

森林资源续档和各项林业调查规划数据兼容的研究

在详细分折森资源续档数据和各项林业调查规划数据存在不兼容的问题原因基础上,进行深入地研究并提出解决对策,为林业生产提供决策服务。     

Improving the estimate of forest biomass carbon storage by combining two forest inventory systems

Quantifying forest carbon storage and its spatial distribution at regional scales is critical for the creation of greenhouse gases inventories, the evaluation of forest services and carbon-oriented forest management. The plot-based forest inventory (PBFI) and stand-based forest inventory (SBFI) collect extensive information on trees and stands respectively, and together, provide an opportunity to improve the regional estimates of forest carbon. In this study, we applied the SBFI to overcome the spatial extent limits of the PBFI in neighboring plots and improve the regional carbon estimation. We found that the forests in Sichuan Province reserved a total of 624.2?Tg?C in biomass and featured a large spatial heterogeneity, with high values in natural forests and low values in plantations. We found that the solo use of PBFI derived a slightly higher (46.63?Mg?C/ha) estimation on average compared with the integrated method (43.6?Mg?C/ha). However, when considering the spatial distribution, the PBFI generated an overestimation of young forests located between 3000and 4000?m in elevation, and an underestimation in mature forests. The spatially explicit biomass carbon estimation could be helpful in guiding regional forest management and biodiversity conservation.     

基于森林资源清样调查资料的森林生产力估算模式--以中国油松林为例

准确地评估森林净第一性生产力(NPP)对于评估全球收支有着十分重要的作用。本文充分利用森林资源清样调查资料,并动态地评估森林生产力,以油松林为例建立了反映生物因素(蓄积量V和林龄A)和气候因素(年实际蒸散E)综合影响的中国油松林生物气候生产力(NPPa)模型。基于所建模型和第四次我国油松林资源的清样调查资料(1989-1993年),估算了中国油松林的净第一性生产力,并借助于地理信息系统软件给出了中国油松林的分布格局。结果表明:我国油松林的平均净第一性生产力为7.82thm-2a-1,其变化幅度为3.32~11.87thm-2a-1。中国油松林净第一性生产力有明显的区域差异,表现为南高北低的分布趋势。山西和陕西为中国油松林的集中分布区,生产力水平处于中等,约为7.4thm-2a-1;油松林集中分布区的南部(四川、湖北、河南等省),生产力水平较高,均大于7.7thm-2a-1;而在油松林集中分布区的北部和西部(内蒙古、宁夏等省),生产力水平较低,NPP均低于5thm-2a-1。该研究为利用森林资源清样调查资料评估森林NPP的动态及研究其对气候变化的响应提供一个有效思路。图3表2参46。     

国家森林资源连续清查森林健康监测方法的探讨

对国家森林资源连续清查森林健康的监测方法进行分析,指出现行监测方法的局限性,并结合欧洲和美国森林健康监测指标体系和森林资源调查监测同行的专家意见,提出新的监测指标和评价方法,为进一步完善有关国家森林资源连续清查森林健康监测的技术标准和调查方法提供参考。     

A national level forest resource assessment for Burkina Faso - A field based forest inventory in a semiarid environment combining small sample size with large observation plots

Even though considerable parts of the global tropical forests are located in Africa, reliable data on African forest resources is limited. While this is widely recognized for tropical moist forests, it also holds for tropical dry forests. To partially fill the gap a forest inventory was carried out in Burkina Faso, West Africa. In this paper we present a methodological approach and sample based estimates of the tree and forest resources including estimates of (1) land cover classes, (2) species composition, and (3) above ground tree carbon stocks. Following the land classification of the Food and Agriculture Organization of the United Nations (FAO), the forest cover of Burkina Faso was estimated as 42.6% (116,847 km²). For the classes “other wooded land”, “other land” and “other land with tree cover” the estimates were 1.6%, 53.6%, and 9.1%, respectively. We found notable differences to the estimates published by FAO, in particular when considering the classes “forest” and “other wooded land” separately, but lesser so when the two classes are combined. That points to a major issue in applying these class definitions in semiarid environments. Given the relatively small sample size (n = 46 field observed plots), relative standard errors (SE%) of area estimates are high (around 9% for the larger area classes). Aboveground tree carbon stocks were estimated to be 6.640, 5.580 and 7.222 Mg ha⁻¹ for “forest”, “other wooded land” and “other land with tree cover”, respectively (SE% around 18% for all three estimates). Availability of biomass models is very limited for all classes, in particular when it comes to shrubs. Furthermore, it was estimated that the most abundant tree species in Burkina Faso is Vittelaria paradoxa, the “shea butter tree” which is a multi-use tree species of high relevance for rural livelihoods.To our knowledge this study is the first field-based forest inventory on national level in Burkina Faso where the estimation of errors was possible on statistical grounds, and done. The results of this study revealed major issues that should be taken into account when doing similar studies, including carbon monitoring and accounting: increasing the sample size will lead to smaller standard errors (at a higher costs, of course), but will not solve the crucial points (1) of non-availability of suitable biomass models, in particular for shrub lands and (2) of implementation issues regarding the definition of land cover types.     

Uncertainties of mapping aboveground forest carbon due to plot locations using national forest inventory plot and remotely sensed data

Abstract

Forest carbon sinks significantly contribute to mitigation of atmospheric concentrations of carbon dioxide. Thus, estimating forest carbon is becoming important to develop policies for mitigating climate change and trading carbon credits. However, a great challenge is how to quantify uncertainties in estimation of forest carbon. This study investigated uncertainties of mapping aboveground forest carbon due to location errors of sample plots for Lin-An County of China. National forest inventory plot data and Landsat TM images were combined using co-simulation algorithm. The findings show that randomly perturbing plot locations within 10 distance intervals statistically did not result in biased population mean predictions of aboveground forest carbon at a significant level of 0.05, but increased root mean square errors of the maps. The perturbations weakened spatial autocorrelation of aboveground forest carbon and its correlation with spectral variables. The perturbed distances of 800 m or less did not obviously change the spatial distribution of predicted values. However, when the perturbed distances were 1600 m or larger, the correlation coefficients of the predicted values from the perturbed locations with those from the true plot locations statistically did not significantly differ from zero at a level of 0.05 and the spatial distributions became random.     

球孢白僵菌防治杨树食叶害虫试验初探

杨小舟蛾是洞庭湖区近年主要杨树食叶害虫,1年发生7代,在5、6月份杨小舟蛾1、2代的1～2龄时施放白僵菌进行防治,施药4 d后虫体出现病理反应,5 d后开始死亡,7 d出现死亡高峰,10 d因药死亡率为55.4%.通过死亡虫体白僵菌孢子的自然散发或幼虫取食感染,对以后世代虫口基数有明显的抑制效果.