Postfire stand structure in a semiarid savanna: cross-scale challenges estimating biomass.

Algorithms relating remotely sensed woody cover to biomass are often the basis for large-scale inventories of aboveground carbon stocks. However, these algorithms are commonly applied in a generic fashion without consideration of disturbances that might alter vegetation structure. We compared field and remote sensing estimates of woody biomass on savannas with contrasting disturbance (fire) histories and assessed potential errors in estimating woody biomass from cover without considering fire history. Field surveys quantified multilayer cover (MLC) of woody and succulent plants on sites experiencing wildfire in 1989 or 1994 and on nearby unburned (control) sites. Remote sensing estimates of the woody cover fraction (WCF) on burned and control sites were derived from contemporary (2005) dry-season Landsat Thematic Mapper imagery (during a period when herbaceous cover was senescent) using a probabilistic spectral mixture analysis model. Satellite WCF estimates were compared to field MLC assessments and related to aboveground biomass using allometry. Field-based MLC and remotely sensed WCFs both indicated that woody cover was comparable on control areas and areas burned 11-16 years ago. However, biomass was approximately twofold higher on control sites. Canopy cover was a strong predictor of woody biomass on burned and control areas, but fire history significantly altered the linear cover-biomass relationship on control plots to a curvilinear relationship on burned plots. Results suggest predictions of woody biomass from "generic" two-dimensional (2-D) cover algorithms may underestimate biomass in undisturbed stands and overestimate biomass in stands recovering from disturbance. Improving the accuracy of woody-biomass estimates from field and/or remotely sensed cover may therefore require disturbance-specific models or detection of vegetation height and transforming 2-D vegetation cover to 3-D vegetation volume.     

Optimizing model for land use/land cover retrieval from remote sensing imagery based on variable precision rough sets

The suitable spectral mode in remote sensing is often desirable to facilitate the inversion of ecological environment and landscape. This paper put forward an optimizing model based on variable precision rough sets (VPRS) for the land cover discrimination in wetland inventory. In the case study of Lake Baiyangdian which has important ecological functions to the northern China, this model is established successfully according to the domain-experts knowledge. The procedure is as follows. First step is data collection, including remote-sensing data (e.g., Landsat-5 TM bands), the digitized relief maps, and statistical yearbooks. Second, the remote sensing imagery (RSI) and relief maps are co-registered into the same resolution. Third, a condition set, including various attributes is derived from spectral bands, band math or ratio indices based on previous studies, at the same time, the decision set is derived from true land types after investigation and validation. Then, the remote sensing decision table (RSDT) is constructed by linking condition set with decision set according to the sequential pixels in RSI. Fourth, we create one forward greedy searching algorithm based on VPRS to handle this RSDT. After adjusting parameters such as β and knowledge granularity diameter (KGD), we obtain the stable optimized results. Comparative experiments and evaluation show that the discrimination or retrieval accuracy of VPRS model is satisfying (overall accuracy: 87.32% and KHAT: 0.84) and better than original data. Moreover, data dimension has been decreased dramatically (from 12 to 3) and key attributes found by the model may be useful for specific retrieval in wetland inventories.     

Post-fire vegetation regrowth detection in the Deiva Marina region (Liguria-Italy) using Landsat TM and ETM+ data

Obtaining quantitative information about the recovery of fire-affected ecosystems is of utmost importance from the management and decision-making point of view. Nowadays the concern about natural environment protection and recovery is much greater than in the past. However, the resources and tools available for its management are still not sufficient. Thus, attention and precision is needed when decisions must be taken. Quantitative estimates on how the vegetation is recovering after a fire can be of help for evaluating the necessity of human intervention on the fire-affected ecosystem, and their importance will grow as the problem of forest fires, climate change and desertification increases.This article performs a comparison of methods to extract quantitative estimates of vegetation cover regrowth with Landsat TM and ETM+ data in an area that burned during the summer of 1998 in the Liguria region (Italy). In order to eliminate possible sources of error, a thorough pre-processing was carried out, including a careful geometric correction (reaching RMSE lower than 0.3 pixels), a topographic correction by means of a constrained Minnaert model and a combination of absolute and relative atmospheric correction methods. Pseudo Invariant Features (PIF) were identified by implementing an automated selection method based in temporal Principal Component Analysis (PCA), which has been called multi-Temporal n-Dimensional Principal Component Analysis (mT-nD-PCA).Spectral Mixture Analysis (SMA) was compared against quantitative vegetation indices which are based on well known traditional vegetation indices like Normalized Difference Vegetation Index (NDVI) and Modified Soil Adjusted Vegetation Index (MSAVI). Accuracy assessment was performed by regressing vegetation cover results obtained with each method against field data gathered during the fieldwork campaign carried out in the study area. Results obtained showed how vegetation cover fractions extracted from the NDVI based quantitative index were the most accurate, being superior to the rest of the techniques applied, including SMA.     

辽东湾双台子河口湿地翅碱蓬（Suaeda salsa）生物量遥感反演研究

通过现场采集辽东湾双台子河口翅碱蓬（Suaeda salsa）光谱数据,收集标准样方（1 m×1 m）的翅碱蓬生物量（Biomass）,建立相关植被指数与翅碱蓬生物量的遥感反演回归算法,发现辽宁双台子河口湿地翅碱蓬生物量与植被指数PVI、SAVI和MSAVI的相关系数R2较高,直线回归方程相关系数分别达到0.626、0.698和0.679。同时,利用得到的估算模型,结合1990—2005年的双台子河口的TM影像数据,反演该区域翅碱蓬分布面积和生物量。结果发现：辽东湾双台子河口湿地翅碱蓬面积变化呈先降后升的趋势。通过植被指数（NDVI、RVI、PVI和MSAVI）和生物量的算法反演,发现翅碱蓬生物量曲线与分布面积曲线的变化趋势一致。     

Temporal variability of forest fires in eastern Amazonia

Widespread occurrence of fires in Amazonian forests is known to be associated with extreme droughts, but historical data on the location and extent of forest fires are fundamental to determining the degree to which climate conditions and droughts have affected fire occurrence in the region. We used remote sensing to derive a 23-year time series of annual landscape-level burn scars in a fragmented forest of the eastern Amazon. Our burn scar data set is based on a new routine developed for the Carnegie Landsat Analysis System (CLAS), called CLAS-BURN, to calculate a physically based burn scar index (BSI) with an overall accuracy of 93% (Kappa coefficient 0.84). This index uses sub-pixel cover fractions of photosynthetic vegetation, non-photosynthetic vegetation, and shade/burn scar spectral end members. From 23 consecutive Landsat images processed with the CLAS-BURN algorithm, we quantified fire frequencies, the variation in fire return intervals, and rates of conversion of burned forest to other land uses in a 32 400 km2 area. From 1983 to 2007, 15% of the forest burned; 38% of these burned forests were subsequently deforested, representing 19% of the area cleared during the period of observation. While 72% of the fire-affected forest burned only once during the 23-year study period, 20% burned twice, 6% burned three times, and 2% burned four or more times, with the maximum of seven times. These frequencies suggest that the current fire return interval is 5-11 times more frequent than the estimated natural fire regime. Our results also quantify the substantial influence of climate and extreme droughts caused by a strong El Ni?o Southern Oscillation (ENSO) on the extent and likelihood of returning forest fires mainly in fragmented landscapes. These results are an important indication of the role of future warmer climate and deforestation in enhancing emissions from more frequently burned forests in the Amazon.     

Identification of hot spots and well managed areas of Pichavaram mangrove using Landsat TM and Resourcesat—1 LISS IV: an example of coastal resource conservation along Tamil Nadu Coast, India

The present work is a multi-temporal satellite based study on the spatial dynamic of an important coastal habitat, the Pichavaram mangrove ecosystem, over a period of 15 years. The Pichavaram mangrove forest near Chidambaram, South India is the second largest mangrove forest in the world. Unsupervised classification, the Iterative Self Organising Data Analysis Technique (ISODATA), has been used to classify the mangrove cover into the open and dense classes. The status of the classes has been monitored using Landsat TM of 1991, 2001, and Resourcesat–1 LISS IV of 2006 satellite data. The study demonstrated that by classifying mangrove ecosystem into just the 3 classes using remote sensing data and by studying their temporal variations, it is possible to get a reasonably accurate picture of the extent and condition of the mangrove ecosystem. The total area of the Pichavaram mangrove showed a net increase of 2.51 km² within a span of 15 years (1991 to 2006). The hot spots that are at a risk of being degraded, and on the other hand, the mangrove areas that are well managed are identified using Geographical Information System (GIS) tools for the restoration and conservation measures.     

Survey methods for assessing land cover map accuracy

The increasing availability of digital photographic materials has fueled efforts by agencies and organizations to generate land cover maps for states, regions, and the United States as a whole. Regardless of the information sources and classification methods used, land cover maps are subject to numerous sources of error. In order to understand the quality of the information contained in these maps, it is desirable to generate statistically valid estimates of accuracy rates describing misclassification errors. We explored a full sample survey framework for creating accuracy assessment study designs that balance statistical and operational considerations in relation to study objectives for a regional assessment of GAP land cover maps. We focused not only on appropriate sample designs and estimation approaches, but on aspects of the data collection process, such as gaining cooperation of land owners and using pixel clusters as an observation unit. The approach was tested in a pilot study to assess the accuracy of Iowa GAP land cover maps. A stratified two-stage cluster sampling design addressed sample size requirements for land covers and the need for geographic spread while minimizing operational effort. Recruitment methods used for private land owners yielded high response rates, minimizing a source of nonresponse error. Collecting data for a 9-pixel cluster centered on the sampled pixel was simple to implement, and provided better information on rarer vegetation classes as well as substantial gains in precision relative to observing data at a single-pixel.     

植被覆盖度与沙尘暴形成条件分析

以归一化差值植被指数（Normalized Difference Vegetation Index,NDVI）为指标分析了我国1981年到1998年期间植被覆盖变化情况,给出了植被急剧减少产生新沙源的实例。通过对1998年4月强沙尘暴的分析,指出影响沙尘暴产生和运移的因素除了地形、风速、风向、大气稳定度外,当地植被覆盖和土壤因素也是关键因素之一。并通过对植被覆盖度（NDVI）与浮尘指数（Aerosol Index）进行定量分析,发现二者之间存在明显的负相关关系,表明植被的存在可以从一定程度上抑制浮尘现象的产生。因此,在沙尘运移路径上,采取封山封荒,植树种草,增加植被覆盖度以固结当地土壤和泥沙的措施,可以在一定程度上抑制沙尘暴灾害的发生。     

Model estimation of land-use effects on water levels of northern prairie wetlands.

Wetlands of the Prairie Pothole Region exist in a matrix of grassland dominated by intensive pastoral and cultivation agriculture. Recent conservation management has emphasized the conversion of cultivated farmland and degraded pastures to intact grassland to improve upland nesting habitat. The consequences of changes in land-use cover that alter watershed processes have not been evaluated relative to their effect on the water budgets and vegetation dynamics of associated wetlands. We simulated the effect of upland agricultural practices on the water budget and vegetation of a semipermanent prairie wetland by modifying a previously published mathematical model (WETSIM). Watershed cover/land-use practices were categorized as unmanaged grassland (native grass, smooth brome), managed grassland (moderately heavily grazed, prescribed burned), cultivated crops (row crop, small grain), and alfalfa hayland. Model simulations showed that differing rates of evapotranspiration and runoff associated with different upland plant-cover categories in the surrounding catchment produced differences in wetland water budgets and linked ecological dynamics. Wetland water levels were highest and vegetation the most dynamic under the managed-grassland simulations, while water levels were the lowest and vegetation the least dynamic under the unmanaged-grassland simulations. The modeling results suggest that unmanaged grassland, often planted for waterfowl nesting, may produce the least favorable wetland conditions for birds, especially in drier regions of the Prairie Pothole Region. These results stand as hypotheses that urgently need to be verified with empirical data.     

Recovery of forest structure and spectral properties after selective logging in lowland Bolivia.

Effective monitoring of selective logging from remotely sensed data requires an understanding of the spatial and temporal thresholds that constrain the utility of those data, as well as the structural and ecological characteristics of forest disturbances that are responsible for those constraints. Here we assess those thresholds and characteristics within the context of selective logging in the Bolivian Amazon. Our study combined field measurements of the spatial and temporal dynamics of felling gaps and skid trails ranging from <1 to 19 months following reduced-impact logging in a forest in lowland Bolivia with remote-sensing measurements from simultaneous monthly ASTER satellite overpasses. A probabilistic spectral mixture model (AutoMCU) was used to derive per-pixel fractional cover estimates of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and soil. Results were compared with the normalized difference in vegetation index (NDVI). The forest studied had considerably lower basal area and harvest volumes than logged sites in the Brazilian Amazon where similar remote-sensing analyses have been performed. Nonetheless, individual felling-gap area was positively correlated with canopy openness, percentage liana coverage, rates of vegetation regrowth, and height of remnant NPV. Both liana growth and NPV occurred primarily in the crown zone of the felling gap, whereas exposed soil was limited to the trunk zone of the gap. In felling gaps >400 m2, NDVI, and the PV and NPV fractions, were distinguishable from unlogged forest values for up to six months after logging; felling gaps <400 m2 were distinguishable for up to three months after harvest, but we were entirely unable to distinguish skid trails from our analysis of the spectral data.     

榆林地区植被时空分异特征及其影响因素研究

植被作为反映陆地生态系统和气候的重要指标,对研究全球或区域生态环境变化具有重要作用.以地处黄土高原生态脆弱区的榆林市为研究区,基于地理探测器模型,选取坡向、坡度、气温、降水和土壤类型5类自然因子,土地利用类型、人口密度和GDP 3类人文因子,分析榆林地区植被空间分异特征及其驱动力,并揭示了促进植被生长影响因子的最适宜特...     

基于SPOT—VGT的黄河流域植被覆盖时空演变

植被是土地覆盖中的最主要部分,是连接土壤、大气和生物等要素的自然“纽带”。植被覆盖动态变化对全球能量循环和物质循环具有重要影响,是全球变化研究的重要内容之一。黄河流域作为我国重要的粮食生产基地,其环境变化直接影响到流域经济的可持续发展。为了快速准确地提取地表植被状况,了解黄河流域生态环境,利用1998—2011年的SPOT-VGT遥感数据,结合地理信息技术,采用均值法和趋势分析法对黄河流域植被NDVI时空分布特征和变化趋势进行了动态监测。结果表明,（1）黄河流域14年NDVI均值的空间分布整体特征是东南部平原、盆地和西部山地植被状况要好于北部地区。其次,黄河流域属于干旱半干旱地区,植被发育主要依赖于水文条件,所以沿黄河干流和支流区域也具有较高的植被NDVI值。（2）黄河流域植被NDVl年均值近14年间整体呈缓慢增长趋势,1998--2000年呈现急剧减少态势,2001--2003年出现了较为快速的增长,2004--2011年又出现了较长时间的连续增长过程。（3）黄河流域植被NDVI基本不变的区域约占研究区总面积的71．13％;植被NDVI轻微改善的区域约占流域总面积的27．30％,且主要分布于流域东南部的盆地、平原和西部的山地、丘陵地区,植被NDVI退化的区域面积约占流域总面积的0．98％。黄河流域自1998年以来,植被NDVI整体在不断提高,生态环境在不断改善。     

Modeling the effect of photosynthetic vegetation properties on the NDVI--LAI relationship

Developing a relationship between the normalized difference vegetation index (NDVI) and the leaf area index (LAI) is essential to describe the pattern of spatial or temporal variation in LAI that controls carbon, water, and energy exchange in many ecosystem process models. Photosynthetic vegetation (PV) properties can affect the estimation of LAI, but no models integrate the effects of multiple species. We developed four alternative NDVI-LAI models, three of which integrate PV effects: no PV effects, leaf-level effects, canopy-level effects, and effects at both levels. The models were fit to data across the natural range of variation in NDVI for a widespread High Arctic ecosystem. The weight of evidence supported the canopy-level model (Akaike weight, wr = 0.98), which includes species-specific canopy coefficients that primarily scale fractional PV cover to LAI by accounting for the area of unexposed PV. Modeling the canopy-level effects improved prediction of LAI (R2 = 0.82) over the model with no PV effect (R2 = 0.71) across the natural range of variation in NDVI but did not affect the site-level estimate of LAI. Satellite-based methods to estimate species composition, a variable in the model, will need to be developed. We expect that including the effects of PV properties in NDVI-LAI models will improve prediction of LAI where species composition varies across space or changes over time.     

Study on the utility of IRS 1D LISS-III data and the classification techniques for mapping of Sunderban mangroves

Mangrove conservation and management is a stupendous task chiefly due to the inaccessibility and the hostile substrate conditions. Remote sensing technology serves as an important tool in providing fast, accurate and up-to-date baseline information on the status of mangroves. It is almost impossible to carry out conventional field surveys in these swampy areas. The present study aims at the classification and mapping of the mangroves in Sunderban Biosphere Reserve (SBR) in the West Bengal province of India using IRS 1D LISS-III satellite data. Different classification approaches, viz., on-screen visual interpretation, supervised and unsupervised classifications were tried. The study showed that four mangroves classes, viz., Avicennia, Phoenix, mixed mangroves, and mangrove scrub and eight non-mangrove classes could be delineated using all the three approaches. All the mangrove and non-mangrove classes were field verified and the overall accuracy as well as user’s and producer’s accuracies for each category were determined. It was observed that among the three approaches, on-screen visual interpretation yielded higher classification accuracy (91.67%) compared to supervised (79.90%) and unsupervised classifications (71.08%). The results obtained through on-screen visual interpretation showed that all mangrove categories together cover 23.21% of the total geographical area of SBR, of which the mixed mangrove category covers maximum area (18.31%). Among the non-mangrove classes, the waterbody occupies largest area (35.36%) followed by agriculture (34.51%).     

Territory choice during the breeding tenure of male sedge warblers

A territorial male can shift the location of its territory from year to year in order to increase its quality. The male can base its decision on environmental cues or else on its breeding experiences (when territory shift is caused by breeding failure in previous seasons). We tested these possible mechanisms of territory choice in the sedge warbler (Acrocephalus schoenobaenus), a territorial migrating passerine that occupies wetlands. This species bases its territory choices on an environmental cue: tall wetland vegetation cover. We found that the magnitude of territory quality improvement between seasons (measured as the area of tall wetland vegetation) increased throughout the early stages of a male's breeding career as a result of territory shifts dependent on the earliness of arrival. The distance the territory was shifted between seasons depended negatively on the previous year's territory quality and, less clearly, on the previous year's mating success. On the other hand, previous mating or nesting success had no influence on territory quality improvement between seasons as measured in terms of vegetation. The results imply that tall wetland vegetation is a long-term, effective environmental cue and that a preference for territories in which this type of landcover prevails has evolved into a rigid behavioral mechanism, supplemented by short-term individual experiences of breeding failure.     

Effects of human activities (raking,scraping, off-road vehicles) and natural resource protections on the spatial distribution of beach vegetation and related shoreline features in New Jersey

This study examined the relative impacts of different human activities and natural resource protections on the spatial distribution of beach vegetation and related habitat features (wrack, dune succession) in New Jersey (USA). Field surveys of the 209-km shoreline categorized beach segments according to vegetation cover classes, human activities, protection measures (exclosures, beach management plans, access restrictions) and ownership status (federal, state, etc.). A partition model (classification tree) was used to confirm the relative dominance hierarchy of human actions on the distribution of beach vegetation observed, and quantitative comparisons of dominant activities were conducted using vegetation data collected on 218 transects. The spatial extent of beach vegetation was found to be severely restricted by human activities when unconstrained by resource protections. The greatest reductions were found to result from mechanical raking (?99 %), scraping (?91 %) and all-year recreational ORV use (?86 %), which were dominant on nearly 70 % of the state shoreline. Beaches containing larger areas of vegetation (>5 m) were concentrated in areas with resource protections of various kinds (99 %), and on federal or other public parklands (68 %). Exclosures resulted in the greatest coverage of vegetation (48 % of beach surface) compared to public access restricted areas (41 %), beach management plans (31 %), government-only ORV use (31 %), and off-season recreational ORVs (15 %). Greater protection and recovery of beach vegetation and habitat is needed for species conservation and erosion protection in New Jersey and other coastal environments where these activities occur.     

Spectral characteristics of plant communities from salt marshes: A case study from Chongming Dongtan, Yangtze estuary, China

The spectral reflectance of recently formed salt marshes at the mouth of the Yangtze River, which are undergoing invasion by Spartina alterniflora, were assessed to determine the potential utility of remotely sensed data in assessing future invasion and changes in species composition. Following a review of published research on remote sensing of salt marshes, 53 locations along three transects were sampled for paired data on plant species composition and spectral reflectance using a FieldSpec? Pro JR Field Portable Spectroradiometer. Spectral data were processed concerning reflectance, and the averaged reflectance values for each sample were reanalysed to correspond to a 12-waveband bandset of the Compact Airborne Spectral Imager. The spectral data were summarised using principal components analysis (PCA) and the relationships between the vegetation composition, and the PCA axes of spectral data were examined. The first PCA axis of the reflectance data showed a strong correlation with variability in near infrared reflectance and ‘brightness’, while the second axis was correlated with visible reflectance and ‘greenness’. Total vegetation cover, vegetation height, and mudflat cover were all significantly related to the first axis. The implications of this in terms of the ability of remote sensing to distinguish the various salt marsh species and in particular the invasive species S. alterniflora were discussed. Major differences in species with various physiognomies could be recognised but problems occurred in separating early colonising S. alterniflora from other species at that stage. Further work using multi-seasonal hyperspectral data might assist in solving these problems.     

1987-2008年南四湖湿地植被碳储量时空变化特征

利用研究区1987、1997和2008年的LandsatTM／ETM＋卫星遥感数据,结合实地采样调查和收集的资料,计算3个时期山东省南四湖湿地各植被类型的面积和碳储量;同时依照不同覆被类型（植被类型）的平均碳储量将各覆被类型的斑块划分为不同储碳等级,绘制3个时期的南四湖湿地植被碳格局图,分析植被碳储量的时空变化特征、变化产生的原因和变化对湿地的潜在影响。研究结果表明：研究前期（1987年）植被储碳格局存在着明显的植被碳储量以湖南北中心线向两岸增大的带状特征,研究中后期（1997-2008年）带状储碳格局不断破碎化并最终消失。整个研究期高储碳等级的斑块面积不断减小,低储碳等级的斑块面积增加。湿地植被碳储量呈现前期基本稳定后期显著减少的特征,1987、1997和2008年湿地植被碳储量均值分别为1．07、1．08和O．64TgC,1987-1997年湿地植被碳储量平均年增加0．001TgC,变化幅度不大;1997-2008年年减少0．04TgC,下降较明显。其中自然植被碳储量在整个研究期内持续减少,人工植被碳储量呈现先增加后减少的波动变化特征,分析认为这一变化特征产生的主要原因是南四湖地区多因子驱动的土地覆被变化活动。通过区域湿地植被的碳平衡动态分析认为,植被碳储量（碳库）的减少可能会导致整个湿地碳储量的入不敷出,使整个湿地碳汇能力下降甚至可能变为碳源。     

Wetlands as an alternative stable state in desert streams

Historically, desert drainages of the American southwest supported productive riverine wetlands (ciénegas). Region-wide erosion of ciénegas during the late 19th and early 20th century dramatically reduced the abundance of these ecosystems, but recent reestablishment of wetlands in Sycamore Creek, Arizona, USA, provides an opportunity to evaluate the mechanisms underlying wetland development. A simple model demonstrates that density-dependent stabilization of channel substrate by vegetation results in the existence of alternative stable states in desert streams. A two-year (October 2004-September 2006) field survey of herbaceous cover and biomass at 26 sites located along Sycamore Creek is used to test the underlying assumption of this model that vegetation cover loss during floods is density dependent, as well as the prediction that the distribution of vegetation abundance should shift toward bimodality in response to floods. Observations of nonlinear, negative relationships between herbaceous biomass prior to flood events and the proportion of persistent vegetation cover were consistent with the alternative stable state model. In further support of the alternative-state hypothesis, vegetation cover diverged from an approximately normal distribution toward a distinctly bimodal distribution during the monsoon flood season of 2006. These results represent the first empirically supported example of alternative-state behavior in stream ecosystems. Identification of alternative stable states in desert streams supports recent hypotheses concerning the importance of strong abiotic-disturbance regimes and biogeomorphic mechanisms in multiple-state ecosystems.     

Use of an Airborne Lidar System to Model Plant Species Composition and Diversity of Mediterranean Oak Forests

Abstract: Airborne lidar is a remote‐sensing tool of increasing importance in ecological and conservation research due to its ability to characterize three‐dimensional vegetation structure. If different aspects of plant species diversity and composition can be related to vegetation structure, landscape‐level assessments of plant communities may be possible. We examined this possibility for Mediterranean oak forests in southern Portugal, which are rich in biological diversity but also threatened. We compared data from a discrete, first‐and‐last return lidar data set collected for 31 plots of cork oak (Quercus suber) and Algerian oak (Quercus canariensis) forest with field data to test whether lidar can be used to predict the vertical structure of vegetation, diversity of plant species, and community type. Lidar‐ and field‐measured structural data were significantly correlated (up to r= 0.85). Diversity of forest species was significantly associated with lidar‐measured vegetation height (R²= 0.50, p < 0.001). Clustering and ordination of the species data pointed to the presence of 2 main forest classes that could be discriminated with an accuracy of 89% on the basis of lidar data. Lidar can be applied widely for mapping of habitat and assessments of habitat condition (e.g., in support of the European Species and Habitats Directive [92/43/EEC]). However, particular attention needs to be paid to issues of survey design: density of lidar points and geospatial accuracy of ground‐truthing and its timing relative to acquisition of lidar data.