Above-ground biomass estimation using airborne discrete-return and full-waveform LiDAR data in a coniferous forest

The estimation of forest aboveground biomass (AGB) is critical for quantifying carbon stocks and essential for evaluating global carbon cycle. Many previous studies have estimated forest AGB using airborne discrete-return Light Detection and Ranging (LiDAR) data, while fewer studies predicted forest AGB using airborne full-waveform LiDAR data. The objective of this work was to evaluate the utility of airborne discrete-return and full-waveform LiDAR data in estimating forest AGB. To fulfill the objective, airborne discrete-return LiDAR-derived metrics (DR-metrics), full-waveform LiDAR-derived metrics (FW-metrics) and structure parameters (combining height metrics and canopy cover) were used to estimate forest AGB. Additionally, the combined use of DR- and FW-metrics through a nonlinear way was also evaluated for AGB estimation in a coniferous forest in Dayekou, Gansu province of China. Results indicated that both height metrics derived from discrete-return and full-waveform LiDAR data were stronger predictors of forest AGB compared with other LiDAR-derived metrics. Canopy cover derived from discrete-return LiDAR data was not sensitive to forest AGB, while canopy cover estimated by full-waveform LiDAR data (CC_WF) showed moderate correlation with forest AGB. Structure parameters derived from full-waveform LiDAR data, such as H75_FW * CC_FW, were closely related to forest AGB. In contrast, structure parameters derived from discrete-return LiDAR data were not suitable for estimating forest AGB due to the less sensitivity of canopy cover CC_DR2 to forest AGB. This research also concluded that the synergistic use of DR- and FW-metrics can provide better AGB estimates in coniferous forest.     

Using Satellite and Airborne LiDAR to Model Woodpecker Habitat Occupancy at the Landscape Scale

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2 mission) with the goal of improving wildlife modeling for more locations across the globe.     

基于无人机激光雷达遥感的亚热带常绿阔叶林群落垂直结构分析

森林植被高度与树木分布格局是植物群落重要结构特征,也是计算森林生物量分布的重要参数。传统的森林群落调查方法耗费大量人力物力难以进行较大尺度的群落结构测量,而一般的遥感影像也难以获得精确的地形信息及垂直结构。近年来激光雷达(Light Detection and Ranging,LiDAR)技术快速发展,能够较好的进行植被三维特征的提取并被广泛应用于森林生态系统检测模拟。且随着无人机低空摄影技术的发展催生的无人机激光雷达(UAV-Lidar)更增加了激光雷达的灵活性以及获取较大范围植被冠层信息的能力。而受限于激光的穿透性以及不同植被类型郁闭度的影响,该技术的应用多局限于在针叶林群落的垂直结构研究,而在常绿阔叶林的研究中应用较少。为探究现有无人机激光雷达设备及垂直结构提取分析技术应用于常绿阔叶林的可行性,利用无人机载激光雷达遥感技术对哀牢山中山湿性常绿阔叶林3块面积1hm²的样地进行基于数字表面模型以及数字地表高程模型做差得到树冠高度模型测量的植被冠层高度、基于局部最大值法进行单木位置提取并使用Clark-Evans最近邻体分析方法进行样地内高大乔木分布格局的计算。分...     

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.     

LiDAR as a rapid tool to predict forest habitat types in Natura 2000 networks

Management strategies for the conservation of biodiversity can be developed only with precise information on the spatial distribution of organisms on relevant, mostly regional, spatial scales. Current surrogates for approximating the distribution of biodiversity are habitats mapped within a number of national and international frameworks (e.g., Natura 2000), even though conventional habitat mapping is time consuming and requires well-trained personnel. Here we evaluated the use of light detection and ranging (LiDAR) to map forest habitat types to simplify the process. We used available data of habitat types for the Bavarian Forest National Park as a basis to predict habitat types with LiDAR-derived variables. Furthermore, we compared these results with predictions based on extensive ground-based climate, soil and vegetation data. Using linear and flexible discriminant analyses, we found that LiDAR is able to predict forest habitat types with the same overall accuracy as the extensive ground data for climate, soil and vegetation composition. Subtle differences in the vegetation structure between habitat types, particularly in the vertical and horizontal vegetation profiles, were captured by LiDAR. These differences in the physiognomy were in part caused by changes in altitude, which also influence tree species composition. We propose that the most-efficient way to identify forest habitat types according Natura 2000 is to combine remote-sensing LiDAR data with well-directed field surveys.     

Synergistic influences of introduced herbivores and fire on vegetation change in northern Patagonia,Argentina

Question: We investigated how cattle and European hares, the two most widespread exotic herbivores in Patagonia, affect species composition, life‐form composition and community structure during the first 6 years of vegetation recovery following severe burning of fire‐resistant subalpine forests and fire‐prone tall shrublands. We asked how the effects of introduced herbivores on post‐fire plant community attributes affect flammability of the vegetation. Location: Nahuel Huapi National Park, northwest Patagonia, Argentina Methods: We installed fenced plots to exclude livestock and European hares from severely burned subalpine forests of Nothofagus pumilio and adjacent tall shrublands of N. antarctica. The former is an obligate seed reproducer, whereas the latter and all other woody dominants of the shrubland vigorously resprout after burning. Results: Repeated measures ANOVA of annual measurements over the 2001‐2006 period indicate that cattle and hare exclusion had significant but complex effects on the cover of graminoids, forbs, climber species and woody species in the two burned community types. Significant interactions between the effects of cattle and hares varied by plant life forms between the two communities, which implies that their synergistic effects are community dependent. Conclusions: Following severe fires, the combined effects of cattle and hares inhibit forest recovery and favour transition to shrublands dominated by resprouting woody species. This herbivore‐induced trend in vegetation structure is consistent with the hypothesis that the effects of exotic herbivores at recently burned sites contribute to an increase in the overall flammability of the Patagonian landscape.     

Structural complexity and land‐surface energy exchange along a gradient from arctic tundra to boreal forest

Question: Current climate changes in the Alaskan Arctic, which are characterized by increases in temperature and length of growing season, could alter vegetation structure, especially through increases in shrub cover or the movement of treeline. These changes in vegetation structure have consequences for the climate system. What is the relationship between structural complexity and partitioning of surface energy along a gradient from tundra through shrub tundra to closed canopy forest? Location: Arctic tundra‐boreal forest transition in the Alaskan Arctic. Methods: Along this gradient of increasing canopy complexity, we measured key vegetation characteristics, including community composition, biomass, cover, height, leaf area index and stem area index. We relate these vegetation characteristics to albedo and the partitioning of net radiation into ground, latent, and sensible heating fluxes. Results: Canopy complexity increased along the sequence from tundra to forest due to the addition of new plant functional types. This led to non‐linear changes in biomass, cover, and height in the understory. The increased canopy complexity resulted in reduced ground heat fluxes, relatively conserved latent heat fluxes and increased sensible heat fluxes. The localized warming associated with increased sensible heating over more complex canopies may amplify regional warming, causing further vegetation change in the Alaskan Arctic.     

General and specific responses of understory vegetation to cervid herbivory across a range of boreal forests

Understanding the responses of ecological communities to perturbation is a key challenge within contemporary ecology research. In this study we seek to separate specific community responses from general community responses of plant communities to exclusion of large cervid herbivores. Cervid herbivory and forestry are the main drivers of vegetation structure and diversity in boreal forests. While many studies focus on the impact of cervids on trees, a high proportion of the biodiversity and ecosystem services in boreal forests is found in the field layer. However, experimental approaches investigating the influence of herbivory on understory vegetation are highly localised. In this study we use a regional‐scale design with 51 sites in four boreal forest regions of Norway, to investigate the influence of cervid herbivory on the physical and ecological structure of field layer vegetation. Our study sites cover a range of forest types differing in productivity, management and dominant cervid species, allowing us to identify generic responses and those that are specific to particular conditions. We found that the height of the field layer and the abundances of individual species were most susceptible to change following short‐term cervid exclusion across different forest types and cervid species. Total vegetation density and vascular plant diversity did not respond to cervid exclusion on the same time scale. We also found that the field‐layer vegetation in clear‐cut forests used by moose was more susceptible to change following cervid exclusion than mature forests used by red deer, but no strong evidence that the response of vegetation to herbivore exclusion varied with productivity. Our study suggests that the parameters that respond to cervid exclusion are consistent across forest types, but that the responsiveness of different forest types is idiosyncratic and hard to predict.     

Animal-habitat relationships in the Knysna Forest,South Africa: discrimination between forest types by birds and invertebrates

Summary Effects of forest plant species composition and physiognomy on bird and invertebrate communities were investigated in three discrete, relatively undisturbed forest types along a dry-wet soil moisture gradient. Using discriminant function analysis, a 100% floristic and a 78% vegetation structural discrimination were obtained between the three forest types. However, the bird communities of these different forest types were very similar in species composition, and had much lower densities than those normally encountered in other, superficially similar forests. Although an 81% discrimination between forest types was attained through analysis of ground surface invertebrates, measures of litter and aerial invertebrate abundance were also of limited use as discriminators. Historical and biogeographic factors, as well as the low nutritional levels in the soil and vegetation may be the causes of low bird and invertebrate density and diversity. It is concluded that floristics and vegetation structure have, at best, a minor influence on bird community structure, and possibly also on invertebrate community structure in the Knysna Forest.     

Object-based classification of land cover and tree species by integrating airborne LiDAR and high spatial resolution imagery data

We evaluated the effectiveness of integrating discrete return light detection and ranging (LiDAR) data with high spatial resolution near-infrared digital imagery for object-based classification of land cover types and dominant tree species. In particular we adopted LiDAR ratio features based on pulse attributes that have not been used in past studies. Object-based classifications were performed first on land cover types, and subsequently on dominant tree species within the area classified as trees. In each classification stage, two different data combinations were examined: LiDAR data integrated with digital imagery or digital imagery only. We created basic image objects and calculated a number of spectral, textural, and LiDAR-based features for each image object. Decision tree analysis was performed and important features were investigated in each classification. In the land cover classification, the overall accuracy was improved to 0.975 when using the object-based method and integrating LiDAR data. The mean height value derived from the LiDAR data was effective in separating “trees” and “lawn” objects having different height. As for the tree species classification, the overall accuracy was also improved by object-based classification with LiDAR data although it remained up to 0.484 because spectral and textural signatures were similar among tree species. We revealed that the LiDAR ratio features associated with laser penetration proportion were important in the object-based classification as they can distinguish tree species having different canopy density. We concluded that integrating LiDAR data was effective in the object-based classifications of land cover and dominant tree species.     

Habitat preferences of the bank voleMyodes glareolus in a Mediterranean mountain range

The bank voleMyodes glareolus Schreber, 1780 is a widely distributed rodent in Europe, being numerically dominant in small mammal communities living in temperate woodlands. However, it becomes scarce in southern Europe (Mediterranean area) where it reaches the southernmost limit of its distribution range. We studied the habitat preferences of bank voles in 9 plots in a transitional area between Mediterranean and Eurosiberian regions within a Mediterranean mountain. During the study period we captured 1919 small mammals of 9 species, including 287 bank voles (14.95%). Mean density ranged from zero individuals per plot (1.1 ha) at the boreo-subalpine scrubland to 10.27 ± 2.84 (SE) at a Mediterranean river woodland. Statistical path analysis was used to investigate relationships between mean bank vole density and climate and vegetation structure measured within plots. The variables selected by the structural equation model were those related to forest structure, like tree cover and height, dead vegetation, moss, and rock cover. Habitat moisture was also important (microclimatic conditions). Mean climate conditions (and elevation) did not have any significant effect on mean bank vole density, and no significant association with understorey vegetation (eg shrub and herbaceous cover) was observed. Our results pointed out that bank voles were habitat specialists in our study area, being more abundant and frequent in moist woodlands, and rare or absent in shrublands and grasslands.     

The vegetation of the forest-steppe region of Hustain Nuruu, Mongolia

The vegetation of a forest-steppe region in Hustain Nuruu, Mongolia, was studied by a phytocoenological approach. Eleven plant communities were recognized, comprising four steppe communities, two meadow communities, a tussock grassland, two shrub communities, a scrub community and a woodland community. The botanical and ecological characteristics of the different communities are discussed, with reference to the existing classification of Mongolian plant communities. Analysis of the present data indicates that a refinement or extension of the classification system is desirable, especially concerning the steppe(-related) communities. Discussion of the relative distribution of steppe and forest reveals that in the relatively dry location of Hustain Nuruu grassland and shrubland dominate the natural vegetation (88% of the area). Forest covers ca. 5% of the area, it is limited to sites where ground water is within rooting depth: north slopes above 1400 m (Betula platyphylla woodland) and along erosion gullies (fragmentary Ulmus pumila gallery woodland). Under natural conditions forest cover might reach 12%, but it is speculated that wild ungulates could maintain its extension at a lower level. The importance of forest is greater in forest-steppe regions with higher rainfall, but the factors determining the distribution of grassland and forest are expected to be similar.     

喀斯特峰丛洼地不同植被类型碳格局变化及影响因子

采用样方法研究了西南喀斯特峰丛洼地草地、灌丛、次生林、原生林4种植被类型碳格局及其土壤碳的影响因子。结果表明:草地、灌丛、次生林、原生林4类生态系统总碳储量分别为133.84、160.79、179.08和261.24 Mg C/hm2,其中植被碳储量为5.02、6.59、20.87和60.20 Mg C/hm2,占总碳储量的3.75%—23.04%,随植被正向发展而增加;地被物碳储量为1.76、0.95、2.60和0.82 Mg C/hm2,仅占总碳储量的0.32%—1.45%;土壤层碳储量为127.06、153.25、151.61和200.21 Mg C/hm2,占76.64%—94.93%,随植被正向发展呈增加趋势,但对整个生态系统碳储量贡献率减少;由草地向原生林发展过程中,地下部分碳储量均大于地上部分碳储量,地上部分所占比例逐渐提高,地下部分所占比例逐渐减少;相关分析表明,土壤有机碳含量、储量与土壤容重、土壤深度存在良好的线性关系,喀斯特峰丛洼地石灰土土壤有机碳含量与水稳性团聚的分布关系密切,土壤氮素是影响有机碳含量的主要因素,2 mm细根和土壤微生物对石灰土土壤有机碳的积累具有重要的作用。     

The use of medium point density LiDAR elevation data to determine plant community types in Baltic coastal wetlands

This study investigates the use of medium point density LiDAR (light detection and ranging) elevation data for identifying and locating plant community types in Baltic coastal wetlands. Ground-surveyed micro-topography data obtained using real-time kinematic differential GPS were used to analyse and correct the accuracy of LiDAR sourced elevation values in Matlab R2010a. Following the application of elevation corrections, 3 interpolation techniques were applied: Inverse Distance Weighting (IDW), Ordinary Kriging (OK) and the Delaunay Triangulated Irregular Network (TIN) interpolation. Analysis showed that the TIN method produced a more robust model that adequately represented the micro-topographical variation across the wetland. The TIN elevation interpolation was then used to characterise the extent and distribution of the plant communities using known elevation preferences in one coastal wetland site, Tahu. The plant community model developed from the TIN elevation interpolation was then further ground-truthed in two separate Baltic coastal wetland sites, Matsalu and Kudani, in order to test model validity.The results showed that the accuracy of the LiDAR data varied dependent upon plant community type. In 5 of the 6 studied community types, the LiDAR data gave a mean elevation difference of 0.177 m (0.016 SD) above the dGPS elevations. With dGPS elevation corrections, the LiDAR data produced an accurate model of the location of the different plant community types, Kappa coefficient (κ) 0.63, at the initial site, Tahu. The model was found to be very accurate in one of the subsequent ground-truthed sites, κ 0.81, with a similar management history, but less accurate, κ 0.53, in a wetland more exposed to wave action and with a longer history of vegetation management.The inclusion of dGPS ground survey data was shown to considerably improve the accuracy of the LiDAR elevation data to facilitate the identification of plant community types on the basis of elevation. The approach developed in this study of Baltic coastal wetlands may provide a transferable method for rapidly and accurately mapping plant communities in other open environments.     

Characteristics of Golden‐winged Warbler territories in plant communities associated with regenerating forest and abandoned agricultural fields

In the Appalachian portion of their breeding range, Golden‐winged Warblers (Vermivora chrysoptera) nest in shrubland and regenerating forest communities created and maintained by disturbance. Because populations of Golden‐winged Warblers have exhibited precipitous declines in population throughout their Appalachian breeding range, management activities that create or maintain early successional habitat are a priority for many natural resource agencies and their conservation partners. Within these early successional habitats, however, additional information is still needed concerning the relative importance of different vegetation features in selection of breeding territories by Golden‐winged Warblers. Our objective, therefore, was to use logistic regression to estimate the probability of territory‐level occupancy by Golden‐winged Warblers in north‐central Pennsylvania at two sites, each with its own early successional community, based on vegetation characteristics. Our communities were composed of shrublands and regenerating forest sites resulting from two disturbances: agriculture and forest fire. Despite differences in vegetation structure, portions of both study areas (regenerating forest and old field) supported territorial Golden‐winged Warblers. Probability of territory occupancy by Golden‐winged Warblers increased with percent blackberry (Rubus) cover in the regenerating forest community, and decreased as basal area and distance to microedge increased (i.e., as vegetation patchiness decreased) in both communities. These habitat features have also been found to influence other aspects of Golden‐winged Warbler breeding ecology such as nest‐site selection, pairing success, and territory abundance. Vegetation features influencing Golden‐winged Warbler territory establishment can differ among shrubland and regenerating forest communities, and management decisions and outcomes may be affected by these differences. Our study provides a starting point for a more comprehensive hypothesis‐driven occupancy survey to investigate features of the territories of Golden‐winged Warblers across a broader geographic range and in different vegetation communities.     

阿尔泰山两河源牧区草地群落生物量及物种多样性

群落生物量和物种多样性是表征草地生态系统数量特征的重要指标。该研究以新疆阿尔泰山南麓两河源放牧区草地为研究对象,利用样方法对两河源不同放牧区的草地植被进行调查,分析研究区生物量和物种多样性变化,探讨二者与环境因子之间的关联性,为草地群落物种保护以及草地可持续利用提供理论依据。结果表明：(1) 两河源不同牧区间群落盖度、高度、植株密度、地上生物量和单位盖度生物量存在差异。(2) 两河源牧区草地群落地上生物量与群落盖度、植株密度呈显著正相关关系(P<0.05),且地上生物量主要受草地群落盖度的影响;不同牧区的物种多样性指数有一定差异,但物种分布相对均匀。(3)两河源牧区草地群落生物量及物种多样性主要受气温和降水的影响。     

Ungulate browsing on introduced pines differs between plant communities: Implications for invasion process and management

The effects of herbivory on plant invasions are broadly discussed, and many studies have led to widely debated theories. In particular, the effects of herbivores on pine invasion found in different studies vary; in some cases, they controlled their expansion, and in others, they promoted it. On the other hand, vulnerability to invasion by pines differs between community types. Sites with dunes and bare ground are the most heavily invaded, followed by grasslands, while shrublands and forests are least invaded. Because current evidence is mostly observational, some of the varying responses of pine invasions to herbivory should be examined further through replicated experiments. Here, we address experimentally the extent to which preference for the non‐native invasive Pinus contorta by domestic sheep (Ovis aries) depends on the vegetation type. We installed experimental enclosures within two adjacent communities, grassland and shrubland, and in each one, we planted seedlings of P. contorta Douglas and established a sheep density typically recommended for the study area. The number of browsed seedlings, the number and type of branches browsed per seedling, the reduction in height and probability of survival immediately after browsing period were recorded. The number of browsed seedlings and damage to the terminal bud were higher in grassland than in shrubland, while the number of browsed branches per seedling was higher in shrubland than grassland. The reductions in height and probability of survival immediately after browsing were similar in both communities. These results show that moderate levels of sheep herbivory could reduce 20% seedling survival in both communities; nevertheless, the damage patterns differ between them. The sheep browsed more substantial number of seedlings in grasslands than in shrublands. However, if sheep find the seedlings, they damage it more in shrublands. These results suggest that experimental studies comparing communities are important for pine invasion management.     

天童国家森林公园植被碳储量估算

以典型木荷-栲树群落、含苦槠的木荷-栲树群落、含杨梅叶蚊母树的木荷-栲树群落、披针叶茴香-南酸枣群落、枫香-马尾松群落、黄毛耳草-毛竹群落6种群落类型样地实测数据为基础,结合文献资料汇总,采用生物量相对生长方程法,研究了天童国家森林公园森林生态系统的植被碳储量、碳密度及其组分和空间分布特征.结果表明：野外调查的6种群落类型中,含苦槠的木荷-栲树群落碳储量（12113.92 Mg C）和碳密度（165.03 Mg C·hm^-2）均最高,披针叶茴香 南酸枣群落碳储量最低（680.95 Mg C）,其碳密度为101.26 Mg C·hm^-2.各群落类型中,常绿树种的碳储量均显著高于落叶树种,其碳密度范围分别为76.08～144.95和0.16～20.62 Mg C·hm^-2.各群落类型的乔木层各组分中,植株干的碳储量均最高.各林分类型中,常绿阔叶林碳储量最高,为23092.39 Mg C,占天童林区森林生态系统碳储量的81.7%,碳密度为126.17 Mg C·hm^-2.天童国家森林公园植被总碳储量为28254.22 Mg C,碳密度为96.73 Mg C·hm^-2.     

Modelling relationships between birds and vegetation structure using airborne LiDAR data: a review with case studies from agricultural and woodland environments

Airborne LiDAR (Light Detection and Ranging) is a remote sensing technology that offers the ability to collect high horizontal sampling densities of high vertical resolution vegetation height data, over larger spatial extents than could be obtained by field survey. The influence of vegetation structure on the bird is a key mechanism underlying bird–habitat models. However, manual survey of vegetation structure becomes prohibitive in terms of time and cost if sampling needs to be of sufficient density to incorporate fine-grained heterogeneity at a landscape extent. We show that LiDAR data can help bridge the gap between grain and extent in organism–habitat models. Two examples are provided of bird–habitat models that use structural habitat information derived from airborne LiDAR data. First, it is shown that data on crop and field boundary height can be derived from LiDAR data, and so have the potential to predict the distribution of breeding Sky Larks in a farmed landscape. Secondly, LiDAR-retrieved canopy height and structural data are used to predict the breeding success of Great Tits and Blue Tits in broad-leaved woodland. LiDAR thus offers great potential for parameterizing predictive bird–habitat association models. This could be enhanced by the combination of LiDAR data with multispectral remote sensing data, which enables a wider range of habitat information to be derived, including both structural and compositional characteristics.