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1.
Modeling compatible single-tree aboveground biomass equations for masson pine (Pinus massoniana) in southern China 总被引：1，自引：0，他引：1
Because of global climate change,it is necessary to add forest biomass estimation to national forest resource monitoring.The biomass equations developed for forest biomass estimation should be compatible with volume equations.Based on the tree volume and aboveground biomass data of Masson pine(Pinus massoniana Lamb.) in southern China,we constructed one-,two-and three-variable aboveground biomass equations and biomass conversion functions compatible with tree volume equations by using error-in-variable simultaneous equations.The prediction precision of aboveground biomass estimates from one variable equation exceeded 95%.The regressions of aboveground biomass equations were improved slightly when tree height and crown width were used together with diameter on breast height,although the contributions to regressions were statistically insignificant.For the biomass conversion function on one variable,the conversion factor decreased with increasing diameter,but for the conversion function on two variables,the conversion factor increased with increasing diameter but decreased with increasing tree height. 相似文献
2.
Boreal forests play an important role in global environment systems. Understanding boreal forest ecosystem structure and function requires accurate monitoring and estimating of forest canopy and biomass. We used partial least square regression (PLSR) models to relate forest parameters, i.e. canopy closure density and above ground tree biomass, to Landsat ETM+ data. The established models were optimized according to the variable importance for projection (VIP) criterion and the bootstrap method, and their performance was compared using several statistical indices. All variables selected by the VIP criterion passed the bootstrap test (p<0.05). The simplified models without insignificant variables (VIP <1) performed as well as the full model but with less computation time. The relative root mean square error (RMSE%) was 29% for canopy closure density, and 58% for above-ground tree biomass. We conclude that PLSR can be an effective method for estimating canopy closure density and above-ground biomass. 相似文献
3.
Huiquan Bi Yushan Long John Turner Yuancai Lei Peter Snowdon Yun Li Richard Harper Ayalsew Zerihun Fabiano Ximenes 《Forest Ecology and Management》2010
A general and two country-specific systems of additive equations were developed to predict aboveground biomass of Pinus radiata plantations from stand variables that are routinely measured in inventory plots and predicted by conventional growth and yield models. The data for this work consisted of 319 plot-based biomass estimates that were derived from individual tree biomass equations developed in situ. These plot-based biomass estimates were compiled from studies reported in the forestry and ecological literature since 1960 and also from personal communications. They represent more than 60 sites worldwide with a majority in Australia and New Zealand. The systems of additive biomass equations developed from these data provide an alternative and addition to the current methods of estimating the aboveground biomass of P. radiata plantations. They also provide a direct linkage between forest inventory measures, outputs from conventional growth and yield models and biomass and carbon stock estimates at the same spatial scale. This direct linkage provides a new basis for scaling to a remote sensing image from which biomass and carbon stocks across the landscape can be mapped. Comparisons of prediction accuracies between this approach and other methods such as scaling up from individual tree biomass estimates and biomass expansion factors highlighted considerable methodological differences in the estimates of aboveground biomass and associated uncertainties over a range of stand age and conditions. These differences should be carefully evaluated before adopting a particular method to estimate aboveground biomass and carbon stocks of P. radiata plantations at a local, regional or national scale. 相似文献
4.
川西高山松林火烧迹地植被生物量与生产力恢复动态 总被引：2，自引：0，他引：2
用"空间序列代替时间序列"的研究方法对川西高山松林不同年龄火烧迹地的研究结果表明:高山松干生物量占地上部总生物量比例随年龄的增大逐渐增加,到23年生时,干生物量比例已达80%左右;较小的林分密度可以促进高山松的提早结实,但较大的结实量则导致较小的干生物量比例.灌木层生物量在恢复早期随迹地年龄增大逐渐增高,在火烧后20年时达最高,随着高山松开始形成乔木层,其生物量开始逐渐减小;草本层生物量以1～6年火烧迹地较高,在总体生物量中占有较大比例,但随着灌木和高山松迅速生长,其生物量呈现减少的趋势;在火烧迹地恢复的前27年,高山松的生产力呈现随迹地年龄增大逐渐升高的趋势,且生产力增大的速率也随迹地年龄的增大而迅速提高,而草本层生产力则随迹地年龄的增大而逐渐减小. 相似文献
5.
《Scandinavian Journal of Forest Research》2012,27(4):360-373
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. 相似文献
6.
Lehtonen A 《Tree physiology》2005,25(7):803-811
Dynamic decomposition models are needed to estimate changes in the carbon stock of boreal soil because these changes are difficult to measure directly. An important aboveground carbon flux to the soil is foliage litterfall. To estimate this flux, both the amount and the turnover rate of the foliage biomass component must be known. Several methods for estimating foliage biomass of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.), including biomass equations and biomass expansion factors (BEFs), were compared with predicted foliage biomass based on forest inventory plot-level measurements. Measured foliage biomass was up-scaled from the branch-level to the plot-level by combining forest inventory variables (diameter, height, height at the crown base and crown base diameter) based on the assumptions of pipe model theory. Combining the foliage biomass: cross-sectional area ratio with the forest inventory variables provided accurate estimates of foliage biomass at the plot-level for plots in southern Finland. The results emphasize the need to test biomass equations with independent data, especially when the equations applied are based on neighboring regions. 相似文献
7.
The objective of this study is to map the spatial distribution of the aboveground biomass (AGB, tC/ha) storage of the Pinus kesiya Royle ex Gordon (Benguet pine) forest of Sagada, Mt. Province, Philippines by integrating Landsat image and the forest cover map. The data was obtained from 66 plots that were established in the different Benguet pine stands in Sagada. The AGB was estimated using the Digital Numbers (DN) and Normalized Difference Vegetation Index (NDVI) values (with filter and with no filter). The estimated aboveground biomass (AGB) density of the Benguet pine was determined to be 249.66 tonnes/ha corresponding to 112.35 tonnesC/ha. 相似文献
8.
以香格里拉县高山松为研究对象,利用2006年香格里拉县TM遥感影像、2006年森林资源二类调查小班数据、2009年精度为30 m 的DEM数据以及2013年香格里拉县高山松实测样地数据,提取研究区内高山松林影像分布图及筛选出17个因子（13个遥感因子、3个地形因子、1个地面调查因子）作为备选自变量,在MAT-LAB下利用LIBSVM模块建立研究区高山松林蓄积量单位面积（30 m ×30 m）估测模型。结果表明,选用RBF核函数在参数范围内寻找出SVM模型的最佳参数C＝3.5809, g＝0.1、 p＝0.01,利用最佳寻优参数建立SVM非参数模型,对SVM模型进行测试得到,均方根误差MSE＝0.0087,复相关系数R＝0.51,相对误差RE＝23.4％,估测精度为76.6％。以像元为单位,分块提取高山松林对应的各像元自变量因子,利用估测模型预测得到香格里拉县高山松林总蓄积量为13318476.5 m3。 相似文献
9.
6种地形校正方法对雷竹林地上生物量遥感估算的影响 总被引：2，自引：0，他引：2
结合野外调查数据和Landsat 5 TM影像,分析6种地形校正方法(Teillet -回归,Cosine,C,SCS,SCS+C和Minnaert)对雷竹林地上生物量遥感估算的影响.结果表明:1)除Cosine和SCS方法存在校正过度现象,其余4种地形校正方法均具有良好的校正效果;2)6种地形校正方法均可提高TM4,TM5与地上生物量的相关性,且RVI,NDVI和SAVI这3种植被指数与生物量之间的相关性也得到改善;3)与原始影像相比,6种地形校正后的遥感数据都能不同程度地提高雷竹林生物量估算精度,以Teillet -回归校正后所建雷竹林地上部分生物量估算模型精度最高,相关系数从0.441提高到0.687,RMSE降低17％左右;4)尽管Cosine校正最大程度地提高了TM4,TM5与地上生物量的相关关系,但Cosine方法存在校正过度问题,Cosine校正后雷竹林地上生物量遥感估算模型精度反而略低于Teillet -回归校正;5)虽然地形校正可提高植被指数与雷竹林地上生物量之间的相关性,但所选5种植被指数均未入选雷竹林地上生物量遥感估算模型的变量,这与雷竹林较高的密度有关. 相似文献
10.
Estimation of canopy fuel characteristics of Aleppo pine (Pinus halepensis Mill.) forests in Greece based on common stand parameters 总被引：1，自引：0，他引：1
Canopy fuel characteristics that influence the initiation and spread of crown fires were measured in forty representative Aleppo pine (Pinus halepensis Mill.) stands in Greece. Aleppo pine canopy fuels are characterized by low canopy base height (CBH) (2.0–6.5 m), while available canopy fuel load (CFL) (0.63–1.82 kg/m2) and canopy bulk density (CBD) (0.07–0.22 kg/m3) values are similar to those of other conifers worldwide. Regression equations for the estimation of canopy fuels were developed based on common stand parameters. Stand basal area was the best-fitted predictor for the estimation of CFL and CBD at stand level, explaining 77 and 74 % of the observed variation, respectively. Regression analysis failed to provide any significant estimates for the CBH. Prediction of canopy fuel characteristics based on stand basal area can be useful in fuel management and fire prevention planning since it and can be easily incorporated into existing forest inventory systems and can be used for the Kyoto protocol requirements of carbon changes in Aleppo pine forests located in Greek sites. 相似文献
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12.
山西省森林植被碳储量及其动态变化研究 总被引：5，自引：2，他引：3
以山西省1995年、2000年和2005年的3期森林资源清查数据为基础,采用生物量换算因子法,研究了山西省森林植被碳储量及其动态变化。结果表明:10年间山西森林的碳储量总体呈上升的趋势。全省森林的总碳储量由1995年的3514.22万Mg增加到2005年的4505.61万Mg。在14个(类)森林优势树种中,栎类、油松和杨树这三者的碳储量占主导地位,合计占山西省森林总碳储量的60%以上。在全部森林中,幼、中龄林及近熟林的碳储量合计约占总量的90%。2005年,人工林碳储量占森林总碳储量的百分比提高了5.28%,全省森林平均碳密度为23.8933~26.3717Mg/hm2。 相似文献
13.
云南金沙江流域华山松人工林水土保持效益研究 总被引：1，自引：0，他引：1
以裸地为对照 ,对云南金沙江流域的华山松人工林林地的土壤物理性状及营养成分、林分涵养水源的能力、林冠层降雨截流功能、土壤水分动态变化、土壤渗透能力、林地地表径流及泥沙量以及地表生物量和根系分布状况进行了定点、定量观测研究。结果表明 :华山松林对改良土壤、增加肥力具有明显的作用 ,与裸地相比 ,其林地有机质、土壤月均含水率、渗透性能分别是裸地的 2 74、 1 14、 4 6 1倍 ,土壤最大蓄水量比裸地高5 6 74 % ;华山松林分年降雨截流量为 6 3 7mm ,截流率为 2 0 2 % ,径流率为 5 7%。径流削减率为 91 3% ,泥沙削减率为 95 6 % ;土层 2 0cm之上根系占总量的 83% ,对地面固土保水起着重要的作用 相似文献
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东莞市针叶类森林生物量遥感模型研究 总被引：1，自引：0，他引：1
基于 Landsat 8 影像数据,对东莞市松树林 (Pinus sp.)、杉木林 (Cunninghamia lanceolata)、针
叶混交林 3 种针叶类森林生物量进行估算,利用相关分析、主成分分析和逐步回归分析,建立针叶类森
林生物量遥感估算模型,其决定系数 (R2) 值分别为 0.880 9、 0.832 5、 0.964 0,均达显著水平。经适用性
检验,模型均达 0.05 显著水平,可用于东莞市针叶类森林生物量估算。 相似文献
16.
《Forest Ecosystems》2015,(3)
Background: Monitoring forest health and biomass for changes over time in the global environment requires the provision of continuous satellite images. However, optical images of land surfaces are generally contaminated when clouds are present or rain occurs.Methods: To estimate the actual reflectance of land surfaces masked by clouds and potential rain, 3D simulations by the RAPID radiative transfer model were proposed and conducted on a forest farm dominated by birch and larch in Genhe City, Da Xing'An Ling Mountain in Inner Mongolia, China. The canopy height model(CHM) from lidar data were used to extract individual tree structures(location, height, crown width). Field measurements related tree height to diameter of breast height(DBH), lowest branch height and leaf area index(LAI). Series of Landsat images were used to classify tree species and land cover. MODIS LAI products were used to estimate the LAI of individual trees. Combining all these input variables to drive RAPID, high-resolution optical remote sensing images were simulated and validated with available satellite images.Results: Evaluations on spatial texture, spectral values and directional reflectance were conducted to show comparable results.Conclusions: The study provides a proof-of-concept approach to link lidar and MODIS data in the parameterization of RAPID models for high temporal and spatial resolutions of image reconstruction in forest dominated areas. 相似文献
17.
Mapping and spatial uncertainty analysis of forest vegetation carbon by combining national forest inventory data and satellite images 总被引：3，自引：0，他引：3
Guangxing Wang Tonny Oyana Maozhen Zhang Samuel Adu-Prah Siqi Zeng Hui Lin Jiyun Se 《Forest Ecology and Management》2009,258(7):1275-1283
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. 相似文献
18.
本文以崂山林场为研究区域,利用森林资源二类调查数据和TM影像数据,分析了林分郁闭度与遥感因子之间的定量关系,在此基础上利用多元回归分析法结合实测数据构建郁闭度估测模型,并对模型精度进行检验,结果表明,预估精度达到81.6%,估测效果较好。利用该模型,反演了研究区的林分冠层郁闭度,将崂山林场的林分冠层郁闭度分为四个等级,即非林地区,低郁闭度区,中郁闭度区和高郁闭度区,研究区的森林郁闭度分布呈现西北部和东南部较低,而中部和南部相对较高。 相似文献
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Satellite-based estimation of biomass carbon stocks for northeast China''s forests between 1982 and 1999 总被引：1，自引：0，他引：1
Kun Tan Shilong Piao Changhui Peng Jingyun Fang 《Forest Ecology and Management》2007,240(1-3):114-121
Northeast China maintains large areas of primary forest resource and has been experiencing the largest increase in temperature over the past several decades in the country. Therefore, studying its forest biomass carbon (C) stock and the change is important to the sustainable use of forest resources and understanding of the forest C budget in China. In this study, we use forest inventory datasets for three inventory periods of 1984–1988, 1989–1993 and 1994–1998 and NOAA/AVHRR Normalized Difference Vegetation Index (NDVI) data from 1982 to 1999, to estimate forest biomass C stock and its changes in this region over the last two decades. The averaged forest biomass C stock and C density were estimated as 2.10 Pg C (1 Pg = 1015 g) and 44.65 Mg C ha−1 over the study period. The forest biomass C stock has increased by 7% with an annual rate of 0.0082 Pg C. The largest increase in the C density occurred in two humid mountain areas, Changbai Mountains and northern Xiaoxing’anling Mountains. Climate warming is probably the key driving force for this increase, while anthropogenic activities such as afforestation and deforestation may contribute to variations in the C stocks. 相似文献