Estimate Canopy Cover Research Articles

The Influence of Gap Size on Sagebrush Cover Estimates With the Use of Line Intercept Technique

Sagebrush cover is often estimated with the use of the line intercept method. However, a lack of standardized protocols may lead to variable estimates of sagebrush canopy cover. Our objectives were to determine the influence of gap size on 1) sagebrush canopy cover estimates, 2) time needed to read a transect, and 3) among-observer variability in sagebrush canopy cover estimates. We utilized 5-, 10-, and 15-cm gaps, and defined a gap as a lack of continuous live or dead shrub canopy. In instances where a segment of dead cover was less than the gap size and adjoined live cover, the dead cover was measured as live. We evaluated canopy cover at 6 Wyoming big sagebrush (Artemisia tridentata Nutt. ssp. Wyomingensis Beetle & A. Young) sites in southeast Oregon. At each site, four 2-person teams measured sagebrush canopy intercept along 50-m transects. Each transect was read by multiple teams to allow for assessment of among-observer variability. Intercept values were converted to percent canopy cover and we used analysis of variance to determine the influence of site and gap size on measurement time and cover estimates. Observer variability was highest at the intermediate gap size (i.e., 10 cm). Transect measurement time was longest with the use of a 5-cm gap (P < 0.001). Total cover estimates were not related to gap size (P = 0.270). Live canopy cover estimates increased (P < 0.001) from 12.1% to 14.5% with increasing gap size, and cover of dead material decreased (P = 0.015) from 4.4% to 3.2%. These differences are small in magnitude and would not likely change a gross assessment of vegetation status. However, use of a standardized gap size will enhance comparability of canopy cover estimates among studies and will decrease between-year sampling error for repeat monitoring.

Effects of simulated grazing on open perennial sand grassland

We studied biomass and species composition changes of open perennial sand grassland ( Festucetum vaginatae ) as response to different levels of simulated grazing pressures. We conducted a factorial micro-plot field experiment on previously grazed grassland that has been abandoned for a long time. In a two-way factorial design of 12 treatments × 8 repeats, we performed clipping (twice a year for three years) and litter treatments (removing and adding litter once at the beginning of the experiment) to simulate components of grazing, namely the biomass removal and the reduction of the litter accumulation. We used field spectroscopy and visual canopy cover estimation to measure the effects on the amount of the above-ground green biomass and on the vegetation composition.

Comparison of five canopy cover estimation techniques in the western Oregon Cascades

Estimates of forest canopy cover are widely used in forest research and management, yet methods used to quantify canopy cover and the estimates they provide vary greatly. Four commonly used ground-based techniques for estimating overstory cover – line-intercept, spherical densiometer, moosehorn, and hemispherical photography – and cover estimates generated from crown radii parameters of the western Cascades variant of the Forest Vegetation Simulator (FVS) were compared in five Douglas-fir/western hemlock structure types in western Oregon. Differences in cover estimates among the ground-based methods were not related to stand-structure type ( p = 0.33). As expected, estimates of cover increased and stand-level variability decreased with increasing angle of view among techniques. However, the moosehorn provided the most conservative estimates of vertical-projection overstory cover. Regression equations are provided to permit conversion among canopy cover estimates made with the four ground-based techniques. These equations also provide a means for integrating cover data from studies that use different techniques, thus aiding in the ability to conduct synthetic research. Ground-based measures are recommended for specific objectives. Because the FVS-estimated cover levels were consistently lower and more variable than most of the ground-based estimates (by up to 44, 17% on average), ground-based measures of canopy cover may be preferable when accuracy is an important objective.

English

Montana has an estimated 6000 abandoned mine sites, many with associated waste rock and tailings materials contributing to the release of high levels of acidity, heavy metals, and other contaminants, creating a risk to human health and the environment. Many abandoned mine sites in Montana have been reclaimed, however, little post-reclamation monitoring has been performed, and the effectiveness of reclamation has not been quantified. The goal of this project was to quantify the effectiveness of reclamation at three sites in Jefferson County, Montana based on soil suitability for sustaining plant growth. Vegetation and soil studies were executed using a stratified random sampling design. Vegetation measurements included canopy cover using Daubenmire cover classes, above ground biomass, and species richness/diversity. Co-located soil samples were excavated in increments to a depth of 60 cm, and analyzed for pH, electrical conductivity, nutrients, soluble, and total metals. Canopy cover estimates ranged from 0-120% and biomass production estimates ranged from 0-4583 kg ha -1 . Differences in species richness and diversity were observed between sample strata. The chemical properties of the soil varied greatly, with pH values ranging from 2.08 - 7.63, and soluble metal values ranging from <0.1-1001 mg l -1 for Zn, .02-20.81 mg l -1 for Cu, <.01-7.39 mg l -1 for Cd, <.05-12.26 mg l -1 for As, and <.1-7.6 mg l -1 for Pb. Sum of total metal and arsenic (As, Cu, Pb, and Zn) concentrations ranged from 133-81448 mg kg -1 . Associations between vegetation and soil chemistry were determined using correlation and analysis of variance (ANOVA). Significant correlations between biomass production and pH, between canopy cover and pH, and between canopy cover and total metal levels were found. Strong correlation between nutrient data and vegetation response was also found. The results of this study will be used to determine possible maintenance that needs to be done at the study sites, as well as aid in future remedial design.

Estimates of forest canopy fuel attributes using hyperspectral data

Increasingly severe forest fires in the west have triggered a high demand for accurate and timely information on forest fuel attributes. There is great interest in the potential for using recent advances in high spectral resolution remotely sensed imagery to estimate fuel characteristics. We combined field forest inventory and field spectroscopy in the Colorado Front Range with airborne imaging spectrometer measurements of the region to test their capacity to estimate fire related forest attributes including canopy cover, forest type, and burn severity in ponderosa pine ( Pinus ponderosa) and Douglas-fir ( Pseudotsuga menziesii var. glauca) dominated forests. Spectral angle mapper and mixture-tuned matched filtering techniques were tested for mapping fuel attributes. Estimates of canopy cover using spectral angle mapper techniques found 61% agreement with observed values, while mixture-tuned matched filtering estimates of forest canopy cover matched 78% with field observations. The distinction of ponderosa pine versus Douglas-fir is crucial for predicting fire spread in the Rocky Mountains; we found that spectral discrimination of these species was also promising, with an accuracy of 53–57%. The average canopy cover of mixed conifer forest in the area is 38.6%, 24.7% contributed by ponderosa pine and 13.9% by Douglas-fir. The values of canopy cover ranged from 53% to 56% in US Forest Service planned fuel treatment areas, among the highest in the region. Recent forest fires have created approximately 684 km 2 of burned area, with very low canopy cover (13–22%).

Indirect measures for characterizing light along a gradient of mixed-hardwood riparian forest canopy structures

Understanding the effect of canopy structure on the understory light environment is useful in the design of silvicultural strategies that facilitate sustainable tree recruitment. To address this need, a study was designed to quantify the relationship between forest structure and light along a gradient of 50–100% canopy cover. The gradient was created by applying 1 of 4 midstory removal treatments to each of fifty 0.05 ha plots located within a mixed-hardwood riparian forest corridor. The light environment was directly quantified with a linear ceptometer and regression analysis was used to examine the relationship between photosynthetically active radiation (PAR) and various metrics of vertical and horizontal structure. Vertical sighting tube estimates of canopy cover ( R 2 = 0.73), light estimates derived from hemispherical photography ( R 2 = 0.70), and spherical densiometer estimates of canopy closure ( R 2 = 0.68) were the best single predictors of understory light transmittance. Including top height and tree density improved the fit of canopy cover based models ( R 2 = 0.80). Canopy closure estimates derived from hemispherical photography generally showed a weaker relationship with PAR than other measures of stand structure. Further, the strength of this relationship depended upon photo analysis angle. In general, the vertical component of stand structure seems to influence light transmittance through the forest canopy. This vertical complexity must be addressed when evaluating structure–light relations.

Estimation of forest canopy cover: a comparison of field measurement techniques

Estimation of forest canopy cover has recently been included in many forest inventory programmes. In this study, after discussing how canopy cover is defined, different ground-based canopy cover estimation techniques are compared to determine which would be the most feasible for a large scale forest inventory. Canopy cover was estimated in 19 Scots pine or Norway spruce dominated plots using the Cajanus tube, line intersect sampling, modified spherical densiometer, digital photographs, and ocular estimation. The comparisons were based on the differences in values acquired with selected techniques and control values acquired with the Cajanus tube. The statistical significance of the differences between the techniques was tested with the nonparametric Kruskall-Wallis analysis of variance and multiple comparisons. The results indicate that different techniques yield considerably different canopy cover estimates. In general, labour intensive techniques (the Cajanus tube, line intersect sampling) provide unbiased and more precise estimates, whereas the estimates provided by fast techniques (digital photographs, ocular estimation) have larger variances and may also be seriously biased.

Estimation of tree canopy cover in evergreen oak woodlands using remote sensing

The montado/ dehesa landscapes of the Iberian Peninsula are savannah-type open woodlands dominated by evergreen oak species ( Quercus suber L. and Q. ilex ssp. rotundifolia). Scattered trees stand over an undergrowth of shrubs or herbaceous plants. To partition leaf area index between trees and the herbaceous/shrubby understorey requires good estimates of tree canopy cover and is of key importance to understand the ecology and the changes in land cover. The two vegetation components differ in phenology as well as in radiation and rainfall interception, water and CO 2 fluxes. The main goal of this study was to estimate tree canopy cover in a montado/ dehesa region of southern Portugal (Alentejo) using remote sensed data. For this purpose we developed empirical models combining measurements obtained through the analysis of aerial photos and reflectance from Landsat Thematic Mapper (TM) individual channels, vegetation indices, and the components of the Kauth–Thomas (K–T) transformation. A set of 142 plots was designed, both in the aerial photos and in the satellite data. Several simple and multiple linear regression models were adjusted and validated. A subset of 75% of the data ( n = 106) was used for model fitting, and the remainder ( n = 36) was used for model assessment. The best linear equation includes Landsat TM channels 3, 4, 5 and 7 ( r 2 = 0.74), but the Normalised Difference Vegetation Index (NDVI), the components of the K–T transformation, and the Atmospherically Resistant Vegetation Index (ARVI) also performed well ( r 2 = 0.72, 0.70, and 0.69, respectively). The statistics of prediction residuals and tests of model validation indicates that these were also the models with better predictive capability. These results show that detection of low/medium tree canopy cover in this type of land cover (i.e. evergreen oak woodlands) can be accomplished with the help of high and medium spatial resolution satellite imagery.

Time‐series validation of MODIS land biophysical products in a Kalahari woodland, Africa

Monthly measurements of leaf area index (LAI) and the fraction of absorbed photosynthetically active radiation (f APAR) taken at approximately monthly intervals were collected along three 750 m transects in a Kalahari woodland near Mongu in western Zambia. These data were compared with MODIS NDVI (MOD13, Collection 3) and MODIS LAI and f APAR products (MOD15, Collection 3) over a 2 year period (2000–2002). MODIS and ground‐measured LAI values corresponded well, while there was a significant bias between MODIS and ground‐measured f APAR even though both MODIS variables are produced from the same algorithm. Solar zenith angle effects, differences between intercepted and absorbed photosynthetically active radiation, and differences in measurement of f APAR (photon counts versus energy) were examined and rejected as explanations for the discrepancies between MODIS and ground‐measured f APAR. Canopy reflectance model simulations produced different values of f APAR with the same LAI when canopy cover was varied, indicating that errors in the estimation of canopy cover in the MODIS algorithm due to the land cover classification used are a possible cause of the f APAR discrepancy. This is one of the first studies of MODIS land product performance in a time‐series context. Despite a bias in f APAR, our results demonstrate that the woodland canopy phonology is captured in the MODIS product.

Percentage canopy cover – using Landsat imagery to delineate habitat for Myanmar's endangered Eld's deer (Cervus eldi)

Percentage canopy cover data derived from Landsat Enhanced Thematic Mapper (ETM+) sensor data, validated with field measurements, provide a useful tool for delineating Myanmar's Eld's deer (Cervus eldi) habitat. The current extent and condition of remaining Eld's deer habitat is unknown, but the species prefers dry dipterocarp forest. This habitat type has widely varying canopy cover and cannot be accurately delineated with traditional remote sensing techniques. New maps based on estimates of percentage canopy cover represent the variability of dry dipterocarp forests more accurately than maps of strict classes of habitat. Over 500 field measurements of canopy cover were used to train Landsat ETM+ data that were analysed with regression-tree analysis. The resulting satellite-based estimates of canopy cover were compared with an independent set of field validation points (r=0.539, P<0.001, n=114). The satellite-based estimates also showed potential for predicting the presence of Eld's deer (r=0.636, P<0.01, n=14). The results from the predictive maps are in accordance with previous field studies demonstrating the species' preference for dense, dry dipterocarp forest. Patterns of percentage tree-canopy cover across the study area were negatively correlated with human population density (r=-0.307, P<0.001, n=223), suggesting potential further threats to Eld's deer populations if the human population continues to grow.

Estimating canopy cover in Scots pine stands

The way canopy cover is defined and measured influences the obtained canopy cover percentage. Estimates of canopy cover are needed, for example, in canopy radiation modelling and remote sensing applications and as a tool for political decision-making. In this paper, we demonstrated the use of two methods, the LAI-2000 Plant Canopy Analyzer instrument and the Cajanus tube, in Scots pine stands for canopy cover estimation, and also assessed the number of measurement points required for reliable estimates. The Cajanus tube yielded slightly larger canopy closure values than the LAI-2000 instrument, but the values were nevertheless in good agreement. Both of the methods required approximately 250 measurement points for canopy closure estimates of a stand to become relatively stable. We also present the first measured effective canopy transmittance values for Scots pine stands in Finland and an example of tree pattern mapping with the Cajanus tube.

ESTIMATION OF THE FRACTION OF CANOPY COVER FROM MULTISPECTRAL DATA TO BE USED IN A WATER SOIL EROSION PREDICTION MODEL

Using the 16 day MODIS (aboard the EOS Terra satellite) 250m NDVI and ground biophysical and spectral measurements we established simple relationships between these parameters and the canopy cover. The canopy cover is used in water erosion models to estimate the amount of soil loss under precipitation events and specific geographic conditions. Two transects, in the grassland part of the Walnut Gulch Experimental Watershed (WGEW) located near the town of Tombstone in Arizona, were established for ground data collection. Ground measurements were performed every 16 days, to coincide with the Terra Satellite overpass. Erosion, in desert environment is a contributing factor to soil degradation and subsequently desertification. Erosion is strongly related with canopy cover, soil parameters, topography, and climate variables. Although ground point estimates of canopy cover are usually used in erosion models, their temporal and spatial variability need to be accounted for. Using MODIS NDVI data, calibrated with field measurements, we were able to estimate the canopy cover using regression analysis. This technique is very simple and properly accounts for the spatial and temporal variability of the canopy cover. We tested this technique with the WEPP erosion model and we found it to be very valuable

High-resolution images reveal rate and pattern of shrub encroachment over six decades in New Mexico, U.S.A.

Encroachment of the shrub Prosopis glandulosa Torr. (honey mesquite) into semi-arid grasslands is a serious concern in the south-western United States, yet little is known about the long-term dynamics of the invasion process. We used ten high-resolution aerial and satellite images taken from 1936 to 1996 to track the population dynamics and spatial pattern of all P. glandulosa greater than 2 m in diameter on a 75 ha area in southern New Mexico. Shrub cover and patch numbers increased from 1936 to the 1970s, then stabilized at 43% cover and 83 patches ha −1. Individual patches were extremely persistent: 95% of the area occupied by shrub patches in 1936 was still occupied in 1996. Recruitment into the 2 m size class was more variable: 0·6–5·2% year −1 (mean 0·8% year −1). Patch-shape complexity increased from 1936 to 1983 as adjacent shrubs merged, and then declined as those clusters filled in and became rounder. Spatial pattern of shrubs showed a distinct trend over time: strongly clustered in 1936 at lag distances up to 250 m, then random arrangement at all scales, and by 1983 pattern was regular at lag distances greater than 100 m. There was no clear relationship with precipitation. The use of remote sensing imagery allowed us to examine one site over time, and revealed patterns in population dynamics and spatial pattern that would not have been visible otherwise. Comparison of field estimates collected in 2001 with 1996 image data suggest that the canopy cover estimates were accurate, but shrub densities were seriously underestimated in the satellite photographs, which do not show shrubs smaller than 2 m diameter. As long as limitations of the imagery are understood, these methods can be applied over a larger and more heterogeneous area to examine environmental correlates of invasion success.

Comparison of Ground Sampling Methods for Estimating Canopy Cover

Abstract Knowledge of the canopy structure is essential to improving our understanding of forest structure. While numerous sampling techniques have been developed to estimate attributes of the forest canopy, these require either additional measurements or a sampling design and measurement techniques that differ substantially from the ones that are used to estimate more traditional forest attributes, such as basal area, number of stems, or volume. The root of the problem is that the sample element for a design that estimates canopy attributes is the tree crown, whereas the sample element is the bole for a design that estimates an attribute such as basal area. For example, if a fixed-area plot is used to estimate basal area, canopy cover cannot be estimated using the same design because a portion of the plot invariably is covered by the crowns of trees whose boles lie outside the plot boundary and would not be included in the sample under the standard sampling design. In this study, a technique called “morphing” is used to model the trees outside the plot boundary. For the purpose of comparison, the morphing technique is used to estimate canopy cover using data from a circular fixed-area plot, and this technique is compared with both dot count and line intersect sampling using a simulation study and two small forest populations. For the study, the populations were sampled using circular fixed-area plots with radii ranging from ρ = 3.05–6.10 m (10–20 ft) and line lengths ranging from L = 3.05–22.9 m (10–75 ft). For both populations, the bias of the canopy cover estimator derived from the morphing technique was negligible. The estimator based on line intersect sampling is design-unbiased, but it generally had a much larger variance than the one based on the morphing technique. The dot count method consistently had the highest variance. FOR. SCI. 49(2):235–246.

Species composition and invasion in NW Argentinian secondary forests: Effects of land use history, environment and landscape

Abstract. Successional patches are a large component of forest ecosystems throughout the world and their vegetation composition is conditioned by multiple factors such as land use history, disturbances, environmental conditions and landscape context. We investigated the relative contribution of historical, environmental, biotic and spatial factors in determining vegetation composition and invasion by exotic species in secondary forest patches of Sierra de San Javier, Tucumán, Argentina. We estimated canopy cover for shrub, vine and tree species distributed over 51 patches with known land use history. We also recorded environmental, historical and spatial variables and used multivariate techniques to explore the relationship between forest composition and explanatory variables. Land use, time since abandonment, altitude, slope and cover of different strata were related to the vegetation pattern in the study site, and they were all significantly structured over space. Exotic species appeared to differ from natives in their response to explanatory variables. Overall, exotic species were dominant on the edges of young patches originated from herbaceous crops, but the total number of exotic species was related to the distance to urban areas and small farms identified as potential sources of exotic propagules. Vegetation composition of secondary forests in NW Argentina was related to historical and environmental factors, but spatial variables strongly influenced vegetation composition as well as the variation in explanatory variables.

Species composition and invasion in NW Argentinian secondary forests: Effects of land use history, environment and landscape

Successional patches are a large component of forest ecosystems throughout the world and their vegetation composition is conditioned by multiple factors such as land use history, disturbances, environmental conditions and land- scape context. We investigated the relative contribution of historical, environmental, biotic and spatial factors in deter- mining vegetation composition and invasion by exotic species in secondary forest patches of Sierra de San Javier, Tucuman, Argentina. We estimated canopy cover for shrub, vine and tree species distributed over 51 patches with known land use history. We also recorded environmental, historical and spa- tial variables and used multivariate techniques to explore the relationship between forest composition and explanatory vari- ables. Land use, time since abandonment, altitude, slope and cover of different strata were related to the vegetation pattern in the study site, and they were all significantly structured over space. Exotic species appeared to differ from natives in their response to explanatory variables. Overall, exotic species were dominant on the edges of young patches originated from herbaceous crops, but the total number of exotic species was related to the distance to urban areas and small farms identi- fied as potential sources of exotic propagules. Vegetation composition of secondary forests in NW Argentina was re- lated to historical and environmental factors, but spatial vari- ables strongly influenced vegetation composition as well as the variation in explanatory variables.

Ground cover in temperate native perennial grass pastures. I. A comparison of four estimation methods

Studies were conducted to compare visual estimates of ground cover and canopy cover by both inexperienced and experienced observers and to compare those estimates with those from more objective methods in native pastures in the high rainfall, temperate rangelands of northern NSW. Ground cover and canopy cover of 60 quadrats was estimated using visual, mapped area, digital image analysis and photo point quadrat methods. Inexperienced observers were trained by estimating ground cover of reference quadrats. Differences between mean visual estimates of ground cover and canopy cover for experienced and inexperienced observers were not significant (P&gt;0.05). Mean ground cover estimates by the mapped area, digital image analysis and point quadrat methods were also not different from each other. The overall relationship between mean visual estimate and mean objective estimate of ground cover was non-linear (second order polynomial, R2 = 0.93), observers tending to underestimate in the mid-range (20 to 80%) of cover compared with objective methods. Mean visual estimate of ground cover was 73.7% compared with the mean objective estimate of 83.7%. Visual estimates of canopy cover (mean 34.6%) were highly correlated (R2 = 0.90) with those of the mapped area method (mean 34.3%) and the relationship was linear. Measurement of ground cover is a standard technique used in many pasture ecology and management studies and is increasingly being used by land managers to monitor pasture production and sustainability. Inexperienced observers were trained quickly and easily to estimate ground cover and canopy cover with sufficient accuracy to identify ranges of cover using visual estimation, indicating that the visual estimation technique should be suitable for estimating ground cover in land management research.

View angle effects on canopy reflectance and spectral mixture analysis of coniferous forests using AVIRIS

The dependence of vegetation reflectance on sun and sensor geometry can potentially provide information on canopy properties, but also may be a source of unmodelled systematic error in single-angle remote sensing measurements. In this study, we investigated the angular variability of reflectance measurements from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and the resulting impact on spectral mixture analysis (SMA) using both full-range (400-2500 nm) and shortwave-infrared wavelengths (2080-2280 nm; AutoSWIR ). The study was conducted in coniferous forests in Central Oregon using five AVIRIS overpasses to generate multiple view angle measurements. Canopy reflectance was highly anisotropic, with the strength of the angular signal controlled by species type, canopy cover and soil reflectance. Canopy cover estimates from full-range SMA averaged only slight decreases (∼6% relative) toward the retro-solar direction for 16 field plots in the study region. AutoSWIR was even less influenced by view angle, exhibiting changes only for large differences in view angle. In addition, AutoSWIR 's ability to accommodate endmember variability led to stronger agreement with field cover values than full-range SMA. The results suggest that while view angle can significantly affect reflectance measurements from AVIRIS, the consequent variability in vegetation cover estimates from SMA and AutoSWIR is low.

Secondary forest succession in a tropical dry forest: patterns of development across a 50-year chronosequence in lowland Bolivia

Stand structure, species richness and population structures of tree species were characterized in 12 stands representing 50 y of succession following slash-and-burn agriculture in a tropical dry forest in lowland Bolivia. Estimates of tree species richness, canopy cover and basal area reached or surpassed 75% of mature forest levels in the 5-, 8-, and 23-y-old stands respectively. Total stem density of the 50-y-old stand was almost twice that of the mature forest stand. This rapid recovery may be due to a high percentage of sprouting tree species, potentially high seed fall into abandoned fields, or the disturbance history of the mature stand. The even-aged size-class structures, dominance of long-lived pioneers, and presence of charcoal and pottery shards in soils of the mature forest stand suggest it formed after a severe disturbance, possibly fire of anthropogenic origin.

森林樹冠率の推定におけるミクセル分類手法の有効性に関する研究

According to the Kyoto protocol, forest and non-forest area are distinguished using crown cover ratio. So the establishment of the method to estimate the crown cover ratio of forest is urgently necessary.The formula which could be estimated crown cover ratio at in the high precision was made by using the spectral band ratio. In order to confirm the robustness of the formula, the next process produced 4 types stimulation image data. The pixels of the canopy crown were extracted from the ordinal CAST image first. Then, The pixels of the background except for the canopy crown were replaced with the spectral of water, soil, moss and the grass. The estimated canopy cover ratio had changed by the difference in the background types. From this result, the limit of the estimated formula became clear.Then, the mixture classification technique was applied to estimate canopy cover ratio. When it was compared with the ground truth data, it showed a tendency to estimate it low as that result but the strong correlation existed between the truth and the estimated ratio. This research shows that the possibility to estimate the crown cover ratio accurately with mixture classification technique.