Influence of using texture information in remote sensed data on the accuracy of forest type classification at different levels of spatial resolution

We evaluated the influence of texture information from remote sensed data on the accuracy of forest type classification at different spatial resolutions. We used 4-m spatial resolution imagery to create five different sets of imagery with lower spatial resolutions down to 30 m. We classified forest type using spectral information alone, texture information alone, and spectral and texture information combined at each spatial resolution, and compared the classification accuracy at each resolution. The classification and regression tree method was used for classification. The accuracy of all three tests decreased slightly with lower spatial resolution. The accuracy with the combined data was generally higher than with either the spectral or texture information alone. At most resolutions, the lowest accuracy was with texture information alone. However, there was no clear difference in accuracy between the combined data and spectral data alone at 25- and 30-m spatial resolution. These results indicate that adding texture information to spatial information improves the accuracy of forest type classification from very high resolution (4-m spatial resolution) to medium resolution imagery (20-m spatial resolution), but this accuracy improvement does not appear to hold for relatively coarse resolution imagery (25- to 30-m spatial resolution).     

Estimation of premature forests in Georgia (USA) using U.S. Forest Service FIA data and Landsat imagery

We used geographic information system applications and statistical analyses to classify young, premature forest areas in southeastern Georgia using combined data from Landsat TM 5 satellite imagery and ground inventory data. We defined premature stands as forests with trees up to 15 years old. We estimated the premature forest areas using three methods: maximum likelihood classification (MLC), regression analysis, and k-nearest neighbor (kNN) modeling. Overall accuracy (OA) of classifying the premature forest using MLC was 82% and the Kappa coefficient of agreement was 0.63, which was the highest among the methods that we have tested. The kNN approach ranked second in accuracy with OA of 61% and a Kappa coefficient of agreement of 0.22. Regression analysis yielded an OA of 57% and a Kappa coefficient of 0.14. We conclude that Landsat imagery can be effectively used for estimating premature forest areas in combination with image processing classifiers such as MLC.     

Reliance on stored water increases with tree size in three species in the Pacific Northwest

In tall old forests, limitations to water transport may limit maximum tree height and reduce photosynthesis and carbon sequestration. We evaluated the degree to which tall trees could potentially compensate for hydraulic limitations to water transport by increased use of water stored in xylem. Using sap flux measurements in three tree species of the Pacific Northwest, we showed that reliance on stored water increases with tree size and estimated that use of stored water increases photosynthesis. For Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), water stored in xylem accounted for 20 to 25% of total daily water use in 60-m trees, whereas stored water comprised 7% of daily water use in 15-m trees. For Oregon white oak (Quercus garryana Dougl. ex Hook.), water stored in xylem accounted for 10 to 23% of total daily water use in 25-m trees, whereas stored water comprised 9 to 13% of daily water use in 10-m trees. For ponderosa pine (Pinus ponderosa Dougl. ex Laws.), water stored in xylem accounted for 4 to 20% of total daily water use in 36-m trees, whereas stored water comprised 2 to 4% of daily water use in 12-m trees. In 60-m Douglas-fir trees, we estimated that use of stored water supported 18% more photosynthesis on a daily basis than would occur if no stored water were used, whereas 15-m Douglas-fir trees gained 10% greater daily photosynthesis from use of stored water. We conclude that water storage plays a significant role in the water and carbon economy of tall trees and old forests.     

Canopy and hydraulic conductance in young, mature and old Douglas-fir trees

We tested for reductions in water transport with increasing tree size, a key component in determining whether gas exchange and growth are hydraulically limited in tall trees. During the summers of 1998 and 1999, we measured water transport with Granier-type, constant-heat sap flow probes, vapor pressure deficit, and leaf and soil water potentials in overstory Pseudotsuga menziesii (Mirb.) Franco trees in three stands differing in size and age (15, 32 and 60 m in height and about 20, 40 and 450 years in age, respectively) in a P. menziesii-dominated forest in the Pacific Northwest, USA. A total of 24 trees were equipped with sap flow sensors--six 60-m trees, nine 32-m trees and nine 15-m trees. Based on the sap flow measurements and leaf area information estimated from leaf area-sapwood area relationships, we estimated crown-averaged stomatal conductance (GS) and leaf-specific hydraulic conductance (KL). We tested the hypothesis that GS and KL vary inversely with tree height (15 > 32 > 60 m). Analysis of variance of GS ranked as 15 = 60 > 32 m during the early summer and 15 > 60 > 32 m during late season drought. Over the growing season, mean daily GS (+/- SE) was 29.2 +/- 4.4, 24.0 +/- 6.8 and 17.7 +/- 7.2 mmol m-2 s-1 for the 15-, 60- and 32-m trees, respectively. The value of K(L) differed among tree heights only during late season drought and ranked 15 > 32 = 60 m. A hydraulic mass balance suggests that greater sapwood conductivity in 60-m trees compared with 32- and 15-m trees is a likely cause for the departure of the above rankings from those predicted by height and leaf-to-sapwood area ratio.     

A general classification of agroforestry practice

Present classification schemes confuse agroforestry practices, where trees are intimately associated with agricultural components at a field scale, with the whole farm and forest systems of which they form a part. In fact, it is common for farming systems to involve the integration of several reasonably discrete agroforestry practices, on different types of land. The purpose of a general classification is to identify different types of agroforestry and to group those that are similar, thereby facilitating communication and the organized storage of information. A new scheme is proposed that uses the ‘practice’ rather than the ‘system’ as the unit of classification. This allows an efficient grouping of practices that have a similar underlying ecology and prospects for management. A two stage definition of agroforestry is proposed that distinguishes an interdisciplinary approach to land use from a set of integrated land use practices. Four levels of organization are recognized through analysis of the role of trees in agricultural landscapes: the land use system, categories of land use within systems, discrete groups of components (trees, crops, animals) managed together, and functionally connected groups of such discrete practices in time and space. Precedents for this form of analysis are found in the literature and it conforms with generally accepted methods of systems analysis. Classification of major types of agroforestry practice proceeds primarily according to the components involved and the predominant usage of land. A secondary scheme further classifies these in terms of the arrangement, density and diversity of the tree components involved. This revised version was published online in June 2006 with corrections to the Cover Date.     

Satellite-based stand-wise forest cover type mapping using a spatially adaptive classification approach

Due to high variation in forest communities, forest structure and the fragmentation of the forested area in Central Europe, satellite-based forest inventory methods have to meet particularly high-quality requirements. This study presents an innovative method to combine official forest inventory information at stand level with multidate satellite imagery using a spatially adaptive classification approach for producing wall-to-wall forest cover maps of important tree species and management classes across multiple ownership regions in a heterogeneous low mountain range in Germany. The classification approach was applied to a 5,200-km² area (about 2,080?km² of forest land, mostly mixed forests) located in the Eifel mountain range in Central Europe. In comparison with conventional classifiers, our results demonstrate a significant increase in classification accuracy in the order of 12%. The method was tested with ASTER images but holds the potential to be used for regular state forest inventories based on standard and novel earth observation data supplied for instance from the SPOT-5 and RapidEye sensors.     

Spatial partitioning of biomass and diversity in a lowland Bolivian forest: Linking field and remote sensing measurements

Large-scale inventories of forest biomass and structure are necessary for both understanding carbon dynamics and conserving biodiversity. High-resolution satellite imagery is starting to enable structural analysis of tropical forests over large areas, but we lack an understanding of how tropical forest biomass links to remote sensing. We quantified the spatial distribution of biomass and tree species diversity over 4 ha in a Bolivian lowland moist tropical forest, and then linked our field measurements to high-resolution Quickbird satellite imagery. Our field measurements showed that emergent and canopy dominant trees, being those directly visible from nadir remote sensors, comprised the highest diversity of tree species, represented 86% of all tree species found in our study plots, and contained the majority of forest biomass. Emergent trees obscured 1–15 trees with trunk diameters (at 1.3 m, diameter at breast height (DBH)) ≥20 cm, thus hiding 30–50% of forest biomass from nadir viewing. Allometric equations were developed to link remotely visible crown features to stand parameters, showing that the maximum tree crown length explains 50–70% of the individual tree biomass. We then developed correction equations to derive aboveground forest biomass, basal area, and tree density from tree crowns visible to nadir satellites. We applied an automated tree crown delineation procedure to a high-resolution panchromatic Quickbird image of our study area, which showed promise for identification of forest biomass at community scales, but which also highlighted the difficulties of remotely sensing forest structure at the individual tree level.     

Classifying tree species in a northern mixed forest using high-resolution IKONOS data

The high-spatial-resolution IKONOS satellite is now operating as a resource and disaster monitor, after a successful launch in September 1999. The ground resolution of the IKONOS panchromatic band is about 1m, the greatest of any satellite. The objectives of this study were to verify the extent to which high-resolution IKONOS data can be used to classify tree species. A field survey and image analysis study used IKONOS imagery to classify 21 species in mixed stands of deciduous and conifer species with the following results: (1) The panchromatic and multi-spectral bands 4, 3, and 2 were useful for classifying tree species owing to the great difference in the reflectance values between tree species. (2) Some groups, for which there were significant differences among species, were identified using Tukeys multiple comparison test; conifers and some broadleaved trees were identified correctly more often than other species. (3) A random selection of validation pixels showed that the overall classification accuracy was 62%. The classification accuracy of broadleaved trees was a little low, ranging from 40% to 63%, while that of conifers exceeded 70%. (4) The overall accuracy of the classification at the genus level improved by 4% more than the species level. The misclassification of broadleaved trees was due to the similar spectral characteristics of species in the same genus.     

江西省古树资源系统研究报告

研究对象只限于散生于江西省山下及村落的30851株古树，不涉及自然保护区、森林公园中的古树。根据古树生长特征，分析其时间分布(古树级及树龄)、空间分布(设区市分布、县域分布)，借助于动态聚类统计分析方法从不同方向进行数量分类，并对数量分类成果用判别分析进行检验。最后对各县域每km^2和每万人负荷古树数进行核算，用数据资抖说明县域保护古树的重要性，增强县域保护古树的责任感。     

Thinning and in-stream wood recruitment in riparian second growth forests in coastal Oregon and the use of buffers and tree tipping as mitigation

Many aquatic habitats in coastal Oregon have been impacted by historic land use practices that led to losses of in-stream wood and associated degraded fish habitats. Many of these streams are now bordered by stands of dense second growth forests(30–80 years) that are incorporated into riparian buffer zones with low wood recruitment and storage. Thinning in riparian zones is one management option to increase the rate of large tree growth and eventually larger in-stream wood, however, it raises concern about impacts on current wood recruitment, among other issues. Using a forest growth simulation model coupled to a model of in-stream wood recruitment, we explore riparian management alternatives in a Douglas-fir plantation in coastal Oregon. Alternatives included:(1) no treatment,(2) single and double entry thinning, without and with a 10-m buffer, and(3) thinning combined with mechanical introduction of some portion of the thinned trees into the stream(tree tipping). Compared to no treatment, single and double entry thinning on one side of a channel, without a 10-m buffer, reduce cumulative instream wood volume by 33 and 42 %, respectively, after100 years(includes decay). Maintaining a 10-m buffer reduces the in-stream wood loss to 7 %(single entry thin)and 11 %(double entry). To completely offset the losses of in-stream wood in a single entry thin(on one or both sides of the stream), in the absence or presence of a 10-m buffer,requires a 12–14 % rate of tree tipping. Relative to the notreatment alternative, cumulative in-stream wood storage can be increased up to 24 % in a double-entry thin with no buffer by tipping 15–20 % of the thinned trees(increased to 48 % if thinning and tipping simultaneously on both sides of the stream). The predicted increases in in-stream wood that can occur during a thin with tree tipping may be effective for restoring fish habitat, particularly in aquatic systems that have poor habitat conditions and low levels of in-stream wood due to historic land use activities.     

Land classification for choice of tree species on farm lands in the Attock District of Punjab,Pakistan

In Pakistan, particularly in Punjab Province, it is difficult for agrofarmers to combine their indigenous knowledge and modern scientific methods to evaluate existing traditional farming systems and forestry practices. This requires an evaluation of indigenous soil classification in simple terms along with knowledge of the local flora, especially trees. This study focuses on land suitability classification for trees in the Attock District of Punjab, Pakistan. A survey was conducted which included interviews of local agrofarmers as well as standard soil analyses including both chemical and physical determinations of local soil types. An evalu- ation of soil types for cultivation of various crops was carried out given its total extent, component soil series and their proportions, spotting characteristics of each soil series and their major limitations/hazards for trees/crops. These would lead to the identification of various tree species according to soil characteristics. Then, according to the soil types and species, a land suitability map was obtained for the choice of tree species by using geographic information system (GIS) software. Land suitability classification will help local agroforesters/agrofarmers in matching suitable agricultural trees/crops properly for different soils in the area.     

Comparison of estimators and feature selection procedures in forest inventory based on airborne laser scanning and digital aerial imagery

Digital maps of forest resources are a crucial factor in successful forestry applications. Since manual measurement of this data on large areas is infeasible, maps must be constructed using a sample field data set and a prediction model constructed from remote sensing materials, of which airborne laser scanning (ALS) data and aerial images are currently widely used in management planning inventories. ALS data is suitable for the prediction of variables related to the size and volume of trees, whereas optical imagery helps in improving distinction between tree species. We studied the prediction of forest attributes using field data from National Forest Inventory complemented with ad hoc field plots in combination with ALS and aerial imagery data in Aland province, Finland. We applied feature selection with genetic algorithm and greedy forward selection and compared multiple linear and nonlinear estimators. Maximally around 40 features from a total of 154 were required to achieve the best prediction performances. Tree height was predicted with normalized root mean squared error value of 0.1 and tree volume with a value around 0.25. Predicting the volumes of spruce and broadleaved trees was the most challenging due to small proportions of these tree species in the study area.     

The effect of treeshelter height on the early growth of sessile oak (Quercus petraea (Matt.) Liebl.)

Sessile oak 1+1 transplants were grown for 4 years in a weed-freeenvironment at 1 x 1 m spacing on a fertile sheltered site.Four experiment treatments were imposed: control with no treeshelterand treeshelters of heights 0.6 m, 1.2 m and 1.8 m. Treatmentshad no significant effect on tree survival. Taller sheltersproduced taller, lower diameter trees of increasingly low dryroot weight. The root:shoot ratio was 0.675 in control treesbut declined to 0.291 in 1.8-m shelters. Trees from 0.6-rn and1.2-m shelters (mean heights 152 m and 206 m respectively) supportedthemselves unaided after removal of the stake and treeshelter.The trees from 1.8-m shelters of mean height 234 cm at age fourcollapsed completely when support was removed.     

Characterizing forest species composition using multiple remote sensing data sources and inventory approaches

Abstract

The purpose of the study was to evaluate tree species composition estimated using combinations of different remotely sensed data with different inventory approaches for a forested area in Norway. Basal area species composition was estimated as both species proportions and main species by using data from airborne laser scanning (ALS) and airborne (multispectral and hyperspectral) imagery as auxiliary information in combination with three different inventory approaches: individual tree crown (ITC) approach; semi-individual tree crown (SITC) approach; and area-based approach (ABA). The main tree species classification obtained an overall accuracy higher than 86% for all ABA alternatives and for the two other inventory approaches (ITC and SITC) when combining ALS and hyperspectral imagery. The correlation between estimated species proportions and species proportions measured in the field was higher for coniferous species than for deciduous species and increased with the spectral resolution used. Especially, the ITC approach provided more accurate information regarding the proportion of deciduous species that occurred only in small proportions in the study area. Furthermore, the species proportion estimates of 83% of the plots deviated from field measured species proportions by two-tenths or less. Thus, species composition could be accurately estimated using the different approaches and the highest levels of accuracy were attained when ALS was used in combination with hyperspectral imagery. The accuracies obtained using the ABA in combination with only ALS data were encouraging for implementation in operational forest inventories.     

Response of giant sequoia canopy foliage to elevated concentrations of atmospheric ozone

We examined the physiological response of foliage in the upper third of the canopy of 125-year-old giant sequoia (Sequoiadendron giganteum Buchholz.) trees to a 61-day exposure to 0.25x, 1x, 2x or 3x ambient ozone concentration. Four branch exposure chambers, one per ozone treatment, were installed on 1-m long secondary branches of each tree at a height of 34 m. No visible symptoms of foliar ozone damage were apparent throughout the 61-day exposure period and none of the ozone treatments affected branch growth. Despite the similarity in ozone concentrations in the branch chambers within a treatment, the trees exhibited different physiological responses to increasing ozone uptake. Differences in diurnal and seasonal patterns of g(s) among the trees led to a 2-fold greater ozone uptake in tree No. 2 compared with trees Nos. 1 and 3. Tree No. 3 had significantly higher CER and g(s) at 0.25x ambient ozone than trees Nos. 1 and 2, and g(s) and CER of tree No. 3 declined with increasing ozone uptake. The y-intercept of the regression for dark respiration versus ozone uptake was significantly lower for tree No. 2 than for trees Nos. 1 and 3. In the 0.25x and 1x ozone treatments, the chlorophyll concentration of current-year foliage of trees Nos. 1 and 2 was significantly higher than that of current-year foliage of tree No. 3. Chlorophyll concentration of current-year foliage on tree No. 1 did not decline with increasing ozone uptake. In all trees, total needle water potential decreased with increasing ozone uptake, but turgor was constant. Although tree No. 2 had the greatest ozone uptake, g(s) was highest and foliar chlorophyll concentration was lowest in tree No. 3 in the 0.25x and 1x ambient atmospheric ozone treatments.     

Using longitudinal survival probabilities to test field vigour estimates in sugar maple (Acer saccharum Marsh.)

Tree mortality is a major force driving forest dynamics. To foresters, however, tree mortality is often considered a loss in productivity. To reduce tree mortality, silvicultural systems, such as selection cuts, aim at removing trees that are more likely to die. In order to identify trees with higher risks of mortality, field classifications are employed that assess vigour based on external characteristics of trees. We used a novel longitudinal approach for estimating survival probabilities based on ring-width measurements, initially developed by Bigler and Bugmann [Bigler, C., Bugmann, H., 2004. Predicting the time of tree death using dendrochronological data. Ecol. Appl. 14 (3), 902–914], to parameterize a survival probability model for sugar maple (Acer saccharum Marsh.) and to test whether field-assessed tree vigour classes are corroborated by survival probabilities determined from radial growth history. Data from 56 dead and 321 live sugar maples were collected in stands in western Quebec (Canada) that had undergone a selection cut ≈10 years prior to sampling. Our results showed that tree vigour established from external defects and pathological symptoms, using the classification of Boulet [Boulet, B., 2005. Défauts externes et indices de la carie des arbres: guide d’interprétation. Publication du Québec, Sainte-Foy, Quebec. 291 pp.], is partially corroborated by growth-driven survival probabilities. Moribund trees had lower survival probabilities than vigorous trees over several years in the period prior to vigour assessment. Intermediate vigour classes showed less obvious tendencies, but this may be due to the growth-independent nature of some defects used for their classification. Although the timing of tree death may not be correctly predicted by the vigour classification (i.e., our results suggest that time of death generally was overestimated), its general agreement with survival probabilities determined from growth series make it a useful tool for tree selection in sugar maple stands under selection management.     

基于GF-2号影像的森林优势树种分类

利用遥感数据开展森林资源优势树种的分类对森林资源的监测、森林可持续经营及生物多样性研究具有重要意义。研究针对复杂地形区域的破碎化森林,采用高分二号(GF-2)的多光谱影像作为基础数据进行森林优势树种的精细分类。本文以地形复杂、森林破碎化的湖北省竹山县九华山林场为研究对象,采用面向对象分类方法对树种进行精细分类,比较支持向量法、最近邻法(KNN)和随机森林(RF)三种不同分类算法的分类效果。在尺度阈值为30、合并阈值为95时分割的基础上,利用SVM、KNN和RF分类结果和分类精度差异较大。分类精度最高的是SVM分类方法,总体精度为68.52%,Kappa系数为0.62;其次为随机森林分类法,总体精度为60.29%,Kappa系数为0.54;KNN分类方法精度最低,总体精度为59.41%,Kappa系数为0.53。GF-2号数据能满足树种分类基本需求,在复杂地形和景观破碎化地区用支持向量机进行树种的分类精度更高,但仍存在一定的局限性。     

Understanding patterns of tree adoption on farms in semi-arid and sub-humid Ethiopia

Trees on farms are a widespread feature of landscapes across a large part of Ethiopia with an important role in enhancing the resilience of smallholder livelihoods through the provision of ecosystem services. Despite their importance, little is known about what trees are planted or retained from natural regeneration by different types of farmers that results in the pattern of tree cover found in the region. We address this knowledge gap through analysis of household survey data from semi-arid and sub humid areas of Oromia regional state. A set of composite variables that represent distinctive patterns of tree cover on farms were derived from principal component analysis and Pearson correlation analysis. This revealed two major tree adoption strategies: farmer managed natural regeneration (FMNR) of trees to meet subsistence needs as well as contributing to other ecosystem services; and, high value agroforestry (HVAF) involving planted trees used largely to produce fruits, timber and fodder. Regression analysis further identified fine-scale variation in ecological and socio-economic factors that affect which of these two broad strategies are adopted by farmers. Favorable climatic conditions coupled with institutional arrangements to control free grazing were pre-conditions for HVAF, whereas poor biophysical potential and sloping land provided a positive incentive for farmers to adopt FMNR. Farmers with preferences for tree species with multiple utilities and locational flexibility favored FMNR while adoption of HVAF was more asset-driven. Our findings reveal that farmers integrate many native and exotic tree species on their farms to meet their variable farm conditions, needs and asset profiles in stark contrast to most tree promotion efforts that focus on a few, usually exotic, tree species. We recommend that future agroforestry promotion should embrace a diversity of tree species appropriate to matching the fine scale variation in ecological conditions and farmer circumstances encountered in the field.     

Tree mortality risk of oak due to gypsy moth

We present prediction models for estimating tree mortality resulting from gypsy moth, Lymantria dispar, defoliation in mixed oak, Quercus sp., forests. These models differ from previous work by including defoliation as a factor in the analysis. Defoliation intensity, initial tree crown condition (crown vigour), crown position, and species grouping classes were highly significant in categorical analysis of variance for mortality. Heavy defoliation intensity was shown to have a strong, consistent influence in increasing the probability of tree mortality. Classification and Regression Tree (CART) analysis, a binomial decision tree procedure, was used to develop prediction models of mortality risk for use by forest managers. The best decision tree had 65 groups that correctly classified 75% of the live trees and 76% of the dead trees. Models were run separately by defoliation class and provided correct classifications between 63 and 78% of the trees. Forest land managers can use these models to assign probabilities of death for moderate and heavy defoliation intensity levels and compare predicted mortality to mortality of undefoliated trees to determine how gypsy moth defoliation will affect their stands. The probabilities can be used to develop marking guides Lased on projected defoliation levels for implementing silvicultural treatments to minimize gypsy moth effects in forest stands prior to infestation.     

Silvopastoralism in New Zealand: review of effects of evergreen and deciduous trees on pasture dynamics

Complex interactions between livestock, trees and pasture occur in silvopastoral systems. Between trees and pasture, competition for soil resources (nutrients and water) occurs, becoming especially relevant when one of them is in scarce supply. Trees reduce light and water reaching the understorey layers according to tree density and canopy size. However, they may ameliorate extreme climatological features (reducing wind speed and evapotranspiration, and alleviating extreme temperatures), and improve soil properties, for example, deciduous tree litter may contribute to increased pH and soil nutrient concentrations. During tree establishment, there are generally negligible effects on pasture, irrespective of tree type. However, there is a decline in pasture production and nutritive value under shade with increasing tree age and higher stand density. Under the same conditions, deciduous trees affect pasture later (extinction point of pasture occurs at 85% of canopy closure) than evergreen trees (about 67% for Pinus radiata D. Don). This is mainly because deciduous trees have a leafless period that enables pasture recovery, and their litter smothers pasture less intensely because of its relatively fast decomposition. Silvopastoral studies conducted in New Zealand are reviewed to discuss these effects, and differences in the effects of evergreen and deciduous trees are shown using the examples of P. radiata, and Populus and Salix spp. respectively, which exist in many temperate countries. Future research needs are outlined.