The Experts below are selected from a list of 74379 Experts worldwide ranked by ideXlab platform
Michael Keller - One of the best experts on this subject based on the ideXlab platform.
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amazon Forest structure from ikonos satellite data and the automated characterization of Forest Canopy properties
Biotropica, 2008Co-Authors: Michael W Palace, Gregory P Asner, Michael Keller, Stephen Hagen, B H BraswellAbstract:We developed an automated tree crown analysis algorithm using 1-m panchromatic IKONOS satellite images to examine Forest Canopy structure in the Brazilian Amazon. The algorithm was calibrated on the landscape level with tree geometry and Forest stand data at the Fazenda Cauaxi (3.75 ◦ S, 48.37 ◦ W) in the eastern Amazon, and then compared with Forest stand data at Tapajos National Forest (3.08 ◦ S, 54.94 ◦ W) in the central Amazon. The average remotely sensed crown width (mean ± SE) was 12.7 ± 0.1 m (range: 2.0–34.0 m) and frequency of trees was 76.6 trees/ha at Cauaxi. At Tapajos, remotely sensed crown width was 13.1 ± 0.1 m (range: 2.0–38.0 m) and frequency of trees was 76.4 trees/ha. At both Cauaxi and Tapajos, the remotely sensed average crown widths were within 3 percen to f the crown widths derived from field measurements, although crown distributions showed significant differences between field-measured and automated methods. We used the remote sensing algorithm to estimate crown dimensions and Forest structural properties in 51 Forest stands (1 km 2 ) throughout the Brazilian Amazon. The estimated crown widths, tree diameters (dbh), and stem frequencies differed widely among sites, while estimated biomass was similar among most sites. Sources of observed errors included an inability to detect understory crowns and to separate adjacent, intermingled crowns. Nonetheless, our technique can serve to provide information about structural characteristics of large areas of unsurveyed Forest throughout Amazonia.
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revised method for Forest Canopy height estimation from geoscience laser altimeter system waveforms
Journal of Applied Remote Sensing, 2007Co-Authors: Michael A Lefsky, Michael Keller, Yong Pang, Plinio Barbosa De Camargo, M O HunterAbstract:The vertical extent of waveforms collected by the Geoscience Laser Altimeter System (onboard ICESat - the Ice, Cloud, and land Elevation Satellite) increases as a function of terrain slope and footprint size (the area on the ground that is illuminated by the laser). Over sloped terrain, returns from both Canopy and ground surfaces can occur at the same elevation. As a result, the height of the waveform (waveform extent) is insufficient to make estimates of tree height on sloped terrain, and algorithms are needed that are capable of retrieving information about terrain slope from the waveform itself. Early work on this problem used a combination of waveform height indices and slope indices from a digital elevation model (DEM). A second generation algorithm was developed using datasets from diverse Forests in which Forest Canopy height has been estimated in the field or by via airborne lidar. Forest types considered in this paper include evergreen needleleaf, deciduous broadleaf and mixed stands in temperate North America, and tropical evergreen broadleaf Forests in Brazil. The algorithm described eliminates the need for a DEM, and estimates Forest Canopy height with an RMSE of 5 m (83% of variance in Forest Canopy height explained).
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estimates of Forest Canopy height and aboveground biomass using icesat
Geophysical Research Letters, 2005Co-Authors: Michael A Lefsky, David J Harding, Michael Keller, Warren B Cohen, Claudia C Carabajal, Fernando Del Bom Espiritosanto, M O Hunter, Raimundo Parente De OliveiraAbstract:Exchange of carbon between Forests and the atmosphere is a vital component of the global carbon cycle. Satellite laser altimetry has a unique capability for estimating Forest Canopy height, which has a direct and increasingly well understood relationship to aboveground carbon storage. While the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land Elevation Satellite (ICESat) has collected an unparalleled dataset of lidar waveforms over terrestrial targets, processing of ICESat data to estimate Forest height is complicated by the pulse broadening associated with large-footprint, waveform-sampling lidar. We combined ICESat waveforms and ancillary topography from the Shuttle Radar Topography Mission to estimate maximum Forest height in three ecosystems; tropical broadleaf Forests in Brazil, temperate broadleaf Forests in Tennessee, and temperate needleleaf Forests in Oregon. Final models for each site explained between 59% and 68% of variance in field-measured Forest Canopy height (RMSE between 4.85 and 12.66 m). In addition, ICESat-derived heights for the Brazilian plots were correlated with field-estimates of aboveground biomass (r(2) = 73%, RMSE = 58.3 Mgha(-1)).
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Forest Canopy damage and recovery in reduced impact and conventional selective logging in eastern para brazil
Forest Ecology and Management, 2002Co-Authors: Rodrigo Pereira, Gregory P Asner, Michael Keller, Johan C ZweedeAbstract:Abstract We investigated ground and Canopy damage and recovery following conventional logging and reduced-impact logging (RIL) of moist tropical Forest in the eastern Amazon of Brazil. Paired conventional and RIL blocks were selectively logged with a harvest intensity of approximately 23 m 3 ha −1 (geometric volume) in the dry seasons (July–December) of 1996 and 1998. Ground damage (roads+skid trails+log decks) in the conventional logging treatments occupied 8.9–11.2% of total operational area. In contrast, ground damage in RIL treatments ranged from 4.6 to 4.8% of the total area. Forest Canopy damage was assessed using gap fraction measurements collected with an automated optical Canopy analyzer (LAI-2000; Licor Inc.) in March 1999. Canopy opening varied by time since logging. The recently logged (1998) blocks had integrated Canopy gap fractions of 21.6 and 10.9% of total area for conventional and RIL blocks, respectively. The blocks logged in 1996 had more closed canopies with 16.5 and 4.9% gap fraction for conventional and RIL blocks, respectively. For comparison, undisturbed Forest had a Canopy gap fraction of 3.1%. Measurements of ground disturbance and gap fraction using the Licor LAI-2000 generally agree with other field evaluations of RIL and conventional logging. Detailed understanding of Canopy structural changes resulting from different logging intensities are critical to the prospect of logging damage estimation using current and future remote sensing products.
Monika L Moskal - One of the best experts on this subject based on the ideXlab platform.
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retrieving Forest Canopy extinction coefficient from terrestrial and airborne lidar
Agricultural and Forest Meteorology, 2017Co-Authors: Guang Zheng, Jan U H Eitel, Troy S Magney, Monika L MoskalAbstract:Accurately retrieving the extinction coefficient (k) of foliage elements is a key step to spatially mapping the radiation regime within and under a Forest Canopy. The azimuthal angle of foliage elements (characterized by their normal vectors) is an important factor for improving the retrieval accuracy of k using 3-D voxels derived from lidar data. In this work, we first developed and validated an approach to retrieve k for a Forest Canopy by considering both inclination and azimuthal angles from terrestrial laser scanning (TLS) data. Then, we explored the feasibility of applying the proposed method to aerial laser scanning (ALS) data through four point thinning experiments for both broadleaf and coniferous trees. Our results showed that: (1) TLS-based foliage orientation could capture 86% (N = 209, p < 0.001) and 64% (N = 78, p < 0.001) of the variance in manually measured azimuthal and inclination angles, respectively for an artificial broadleaf tree; (2) the proposed lidar-based k retrieval method can be applied to both ALS- and TLS- based Forest lidar data; and (3) the azimuthal angle of foliage elements is an important factor for retrieving k of a Forest Canopy, and both TLS and ALS platforms have differing effects on the estimates of Forest k. Using this new framework, we were able to use lidar data to model the expected spatio-temporal distribution of photosynthetically active radiation within Forest canopies.
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uncertainty in urban Forest Canopy assessment lessons from seattle wa usa
Urban Forestry & Urban Greening, 2014Co-Authors: Jeffrey J Richardson, Monika L MoskalAbstract:Abstract Increasing urbanization around the globe is leading to concern over the loss of tree Canopy within cities, but quantifying urban Forest Canopy cover can be difficult. We discuss methods of assessing Canopy cover within cities, and then use a case study of Seattle, WA, USA to examine issues of uncertainty in Canopy cover assessment. We find that uncertainty is often not reported, and when reported, may be biased. Based on these findings, we provide a list of recommendations for those undertaking Canopy cover assessment in complex urban environments.
Jindi Wang - One of the best experts on this subject based on the ideXlab platform.
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modifying geometric optical bidirectional reflectance model for direct inversion of Forest Canopy leaf area index
Remote Sensing, 2015Co-Authors: Jinling Song, Jindi WangAbstract:Forest Canopy leaf area index (LAI) inversion based on remote sensing data is an important method to obtain LAI. Currently, the most widely-used model to achieve Forest Canopy structure parameters is the Li-Strahler geometric-optical bidirectional reflectance model, by considering the effect of crown shape and mutual shadowing, which is referred to as the GOMS model. However, it is difficult to retrieve LAI through the GOMS model directly because LAI is not a fundamental parameter of the model. In this study, a gap probability model was used to obtain the relationship between the Canopy structure parameter nR2 and LAI. Thus, LAI was introduced into the GOMS model as an independent variable by replacing nR2 The modified GOMS (MGOMS) model was validated by application to Dayekou in the Heihe River Basin of China. The LAI retrieved using the MGOMS model with optical multi-angle remote sensing data, high spatial resolution images and field-measured data was in good agreement with the field-measured LAI, with an R-square (R2) of 0.64, and an RMSE of 0.67. The results demonstrate that the MGOMS model obtained by replacing the Canopy structure parameter nR2 of the GOMS model with LAI can be used to invert LAI directly and precisely.
Michael A Wulder - One of the best experts on this subject based on the ideXlab platform.
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comparison of airborne laser scanning and digital stereo imagery for characterizing Forest Canopy gaps in coastal temperate rainForests
Remote Sensing of Environment, 2018Co-Authors: Joanne C White, Piotr Tompalski, Nicholas C. Coops, Michael A WulderAbstract:Abstract Forest Canopy gaps play an important role in Forest dynamics. Airborne laser scanning (ALS) data provide demonstrated capacity to systematically and accurately detect and map Canopy gaps over large Forest areas. Digital aerial photogrammetry (DAP) is emerging as an alternative, lower-cost source of three-dimensional information for characterizing Forest structure and modelling Forest inventory attributes. In this study we compared the relative capacities of ALS and DAP data to map Canopy gaps in a complex coastal temperate rainForest on Vancouver Island, British Columbia, Canada. We applied fixed- and variable-height threshold approaches for gap detection using both ALS and DAP data, and validated outcomes using independent data derived via visual image interpretation. Overall accuracies for ALS-derived gaps were 96.50% and 89.50% for the fixed- and variable-height threshold approaches respectively, compared to 59.50% and 50.00% for the DAP-derived gaps, with DAP data having large errors of omission (>88%). We found that 70% of ALS-derived gaps were identified in old seral stage stands (age > 250 years), while 65% of DAP-derived gaps were located in early seral stage stands (age
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characterizing stand level Forest Canopy cover and height using landsat time series samples of airborne lidar and the random Forest algorithm
Isprs Journal of Photogrammetry and Remote Sensing, 2015Co-Authors: Oumer S Ahmed, Michael A Wulder, Steven E Franklin, Joanne C WhiteAbstract:Abstract Many Forest management activities, including the development of Forest inventories, require spatially detailed Forest Canopy cover and height data. Among the various remote sensing technologies, LiDAR (Light Detection and Ranging) offers the most accurate and consistent means for obtaining reliable Canopy structure measurements. A potential solution to reduce the cost of LiDAR data, is to integrate transects (samples) of LiDAR data with frequently acquired and spatially comprehensive optical remotely sensed data. Although multiple regression is commonly used for such modeling, often it does not fully capture the complex relationships between Forest structure variables. This study investigates the potential of Random Forest (RF), a machine learning technique, to estimate LiDAR measured Canopy structure using a time series of Landsat imagery. The study is implemented over a 2600 ha area of industrially managed coastal temperate Forests on Vancouver Island, British Columbia, Canada. We implemented a trajectory-based approach to time series analysis that generates time since disturbance (TSD) and disturbance intensity information for each pixel and we used this information to stratify the Forest land base into two strata: mature Forests and young Forests. Canopy cover and height for three Forest classes (i.e. mature, young and mature and young (combined)) were modeled separately using multiple regression and Random Forest (RF) techniques. For all Forest classes, the RF models provided improved estimates relative to the multiple regression models. The lowest validation error was obtained for the mature Forest strata in a RF model ( R 2 = 0.88, RMSE = 2.39 m and bias = −0.16 for Canopy height; R 2 = 0.72, RMSE = 0.068% and bias = −0.0049 for Canopy cover). This study demonstrates the value of using disturbance and successional history to inform estimates of Canopy structure and obtain improved estimates of Forest Canopy cover and height using the RF algorithm.
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estimating Forest Canopy height and terrain relief from glas waveform metrics
Remote Sensing of Environment, 2010Co-Authors: Laura Duncanson, K O Niemann, Michael A WulderAbstract:Abstract Quantifying aboveground biomass in Forest ecosystems is required for carbon stock estimation, aspects of Forest management, and further developing a capacity for monitoring carbon stocks over time. Airborne Light Detection And Ranging (LiDAR) systems, of all remote sensing technologies, have been demonstrated to yield the most accurate estimates of aboveground biomass for Forested areas over a wide range of biomass values. However, these systems are limited by considerations including large data volumes and high costs. Within the constraints imposed by the nature of the satellite mission, the GeoScience Laser Altimeter System (GLAS) aboard ICESat has provided data conferring information regarding Forest vertical structure for large areas at a low end user cost. GLAS data have been demonstrated to accurately estimate Forest height and aboveground biomass especially well in topographically smooth areas with homogeneous Forested conditions. However in areas with dense Forests, high relief, or heterogeneous vegetation cover, GLAS waveforms are more complex and difficult to consistently characterize. We use airborne discrete return LiDAR data to simulate GLAS waveforms and to subsequently deconstruct coregistered GLAS waveforms into vegetation and ground returns. A series of waveform metrics was calculated and compared to topography and vegetation information gleaned from the airborne data. A model to estimate maximum relief directly from waveform metrics was developed with an R 2 of 0.76 ( n = 110), and used for the classification of the maximum relief of the areas sensed by GLAS. Discriminant analysis was also conducted as an alternative classification technique. A model was also developed estimating Forest Canopy height from waveform metrics for all of the data ( R 2 = 0.81, n = 110) and for the three separate relief classes; maximum relief 0–7 m ( R 2 = 0.83, n = 44), maximum relief 7–15 m ( R 2 = 0.88, n = 41) and maximum relief > 15 m ( R 2 = 0.75, n = 25). The moderate relief class model yielded better predictions of Forest height than the low relief class model which is attributed to the increasing variability of waveform metrics with terrain relief. The moderate relief class model also yielded better predictions than the high relief class model because of the mixing of vegetation and terrain signals in waveforms from high relief footprints. This research demonstrates that terrain can be accurately modeled directly from GLAS waveforms enabling the inclusion of terrain relief, on a waveform specific basis, as supplemental model input to improve estimates of Canopy height.
A H Strahler - One of the best experts on this subject based on the ideXlab platform.
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solar zenith angle effects on Forest Canopy hemispherical reflectances calculated with a geometric optical bidirectional reflectance model
IEEE Transactions on Geoscience and Remote Sensing, 1993Co-Authors: Crystal B Schaaf, A H StrahlerAbstract:The bidirectional reflectance distribution function (BRDF) provided by the Li-Strahler geometric-optical Forest Canopy model has been integrated to provide spectral instantaneous hemispherical reflectances of sparsely vegetated surfaces. Further integration over the Sun's zenith angles can yield daily or longer interval hemispherical reflectances as well. A variety of simulated canopies were modeled with varying solar angles. In all cases, as the geometric-optical model introduced increased shadowing of the surface with increased solar zenith angle, the direct-beam hemispherical surface reflectance gradually decreased. The hemispherical reflectance values are direct beam calculations and do not directly include Canopy multiple scattering and leaf specularity or consider the impact of diffuse irradiance. These limitations are acceptable for sparse canopies, in which 3D shadowing effects are large. However, radiative transfer calculations have shown that these phenomena must be incorporated before truly realistic modeling of hemispherical surface reflectances can be achieved for dense canopies. >
