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  Subjects -> ELECTRONICS (Total: 154 journals)
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 1)
Advances in Electronics     Open Access   (Followers: 3)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 5)
Advances in Microelectronic Engineering     Open Access   (Followers: 2)
Advances in Power Electronics     Open Access   (Followers: 7)
Aerospace and Electronic Systems, IEEE Transactions on     Hybrid Journal   (Followers: 104)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 12)
Annals of Telecommunications     Hybrid Journal   (Followers: 5)
APL : Organic Electronics and Photonics     Hybrid Journal   (Followers: 2)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 6)
Archives of Electrical Engineering     Open Access   (Followers: 9)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 5)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 10)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 16)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 15)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 5)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 5)
BULLETIN of National Technical University of Ukraine. Series RADIOTECHNIQUE. RADIOAPPARATUS BUILDING     Open Access   (Followers: 2)
Bulletin of the Polish Academy of Sciences : Technical Sciences     Open Access  
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 13)
China Communications     Full-text available via subscription   (Followers: 4)
Circuits and Systems     Open Access   (Followers: 10)
Consumer Electronics Times     Open Access   (Followers: 4)
Control Systems     Hybrid Journal   (Followers: 26)
Electronic Design     Partially Free  
Electronic Markets     Hybrid Journal   (Followers: 5)
Electronic Materials Letters     Hybrid Journal   (Followers: 3)
Electronics     Open Access   (Followers: 9)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 5)
Electronics Letters     Hybrid Journal   (Followers: 20)
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 23)
Energy Harvesting and Systems : Materials, Mechanisms, Circuits and Storage     Hybrid Journal   (Followers: 1)
EPJ Quantum Technology     Open Access  
EURASIP Journal on Embedded Systems     Open Access   (Followers: 9)
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Frequenz     Hybrid Journal   (Followers: 3)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 2)
Geoscience and Remote Sensing, IEEE Transactions on     Hybrid Journal   (Followers: 20)
Haptics, IEEE Transactions on     Hybrid Journal   (Followers: 3)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 15)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 13)
IEEE Consumer Electronics Magazine     Full-text available via subscription   (Followers: 18)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 12)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 3)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 7)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 10)
IEEE Transactions on Audio, Speech, and Language Processing     Hybrid Journal   (Followers: 13)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 26)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 17)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 8)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 14)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 21)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 8)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 7)
IET Microwaves, Antennas & Propagation     Hybrid Journal   (Followers: 6)
IET Power Electronics     Hybrid Journal   (Followers: 14)
IET Wireless Sensor Systems     Hybrid Journal   (Followers: 10)
IETE Journal of Education     Open Access   (Followers: 2)
IETE Journal of Research     Open Access   (Followers: 9)
IETE Technical Review     Open Access   (Followers: 4)
Industrial Electronics, IEEE Transactions on     Hybrid Journal   (Followers: 12)
Industry Applications, IEEE Transactions on     Hybrid Journal   (Followers: 3)
Informatik-Spektrum     Hybrid Journal  
Instabilities in Silicon Devices     Full-text available via subscription  
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 2)
International Journal of Advanced Electronics and Communication Systems     Open Access   (Followers: 5)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 20)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 3)
International Journal of Aerospace Innovations     Full-text available via subscription   (Followers: 12)
International Journal of Antennas and Propagation     Open Access   (Followers: 7)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 1)
International Journal of Biomedical Nanoscience and Nanotechnology     Hybrid Journal   (Followers: 6)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 4)
International Journal of Computer & Electronics Research     Full-text available via subscription   (Followers: 2)
International Journal of Control     Hybrid Journal   (Followers: 13)
International Journal of Electronics     Hybrid Journal   (Followers: 2)
International Journal of Electronics & Data Communication     Open Access   (Followers: 4)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 3)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 1)
International Journal of High Speed Electronics and Systems     Hybrid Journal  
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 1)
International Journal of Nano Devices, Sensors and Systems     Open Access   (Followers: 4)
International Journal of Nanoscience     Hybrid Journal  
International Journal of Numerical Modelling:Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 2)
International Journal of Power Electronics     Hybrid Journal   (Followers: 8)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 2)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 3)
International Journal of Superconductivity     Open Access  
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 2)
International Journal on Communication     Full-text available via subscription   (Followers: 10)
International Journal on Electrical and Power Engineering     Full-text available via subscription   (Followers: 10)
International Transaction of Electrical and Computer Engineers System     Open Access  
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 2)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Journal of Artificial Intelligence     Open Access   (Followers: 5)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 1)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription  
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 4)
Journal of Electrical Bioimpedance     Full-text available via subscription   (Followers: 2)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 2)

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Journal Cover   Canadian Journal of Remote Sensing
  [SJR: 0.842]   [H-I: 44]   [13 followers]  Follow
   Full-text available via subscription Subscription journal
   ISSN (Print) 1712-7971
   Published by Canadian Remote Sensing Society Homepage  [1 journal]
  • The Landsat observation record of Canada: 1972–2012
    • Authors: Joanne C. White, Michael A. Wulder
      Pages: 455 - 467
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue 06, Page 455-467, December 2013.
      The Landsat data archive represents more than 40 years of Earth observation, providing a valuable information source for monitoring ecosystem dynamics. In excess of 605000 images of Canada have been acquired by the Landsat program since 1972. Herein we report several spatial and temporal characteristics of the Landsat observation record for Canada (1972–2012), including image availability by year, growing season, sensor, ecozone, and provincial or territorial jurisdiction. In contrast to the global Landsat archive, which is dominated by Enhanced Thematic Mapper Plus (ETM+) data, the majority of archived Landsat images of Canada were acquired by the Thematic Mapper (TM) sensor (57%). Approximately 55% of archived Landsat images were acquired within ± 30 days of 1 August, and 74% of Worldwide Reference System–2 path–row locations in Canada have more than 200 images acquired between 1 June and 30 September. Issues such as cloud cover and the availability of imagery to support pixel-based image compositing and time series analyses are explored and documented. For a pixel-based image compositing scenario whereby images (TM and ETM+) acquired after 1981 with less than 70% cloud cover and a target date of 1 August ± 30 days are considered, 60% of the path–row locations have five or fewer years of missing data in the archive. For time series analyses (i.e., ecosystem monitoring scenario) with the same temporal constraint but with less than 10% cloud cover, only 2% of path–row locations are missing five or fewer years of data, with a mean and median of 17 years of missing data. However, if a broader temporal window (1 June to 30 September) is considered for this scenario, 18% of path–row locations have five or fewer years of missing data. Free and open-access to the Landsat data archive, combined with the continuity of new data collections provided by the recently launched Landsat 8 satellite, offer many opportunities for scientific inquiry concerning the status and trends of Canada's terrestrial ecosystems.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2014-02-13T08:00:00Z
      DOI: 10.5589/m13-053
  • Assessment of Acid Sulphate Soil both on surface and in subsurface using
           hyperspectral data
    • Authors: Xian-zhong Shi, Mehrooz Aspandiar, Ian C Lau, David Oldmeadow
      Pages: 468 - 480
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue 06, Page 468-480, December 2013.
      Acid sulphate soils (ASS) are widely spread around the world and are potentially harmful to the environment due to their strong acidity producing ability and their capability to release trace metals. Secondary iron-bearing minerals produced by ASS, have diagnostic spectral features in the visible-near infrared to short-wave infrared spectral range and can be good indicators to the severity of the effects of ASS. Therefore, it is possible to detect ASS using hyperspectral sensing by mapping these indicative iron-bearing minerals. Iron oxides, hydroxides, hydroxysulphates, as well as noniron-bearing minerals, were mapped using airborne Hyperspectral Mapper data. Subsequently, a soil pH map of the surface was deduced according to the relationship between the indicative mineral species and measured pH values. Furthermore, this study investigated the presence of ASS in the subsurface by the proximal hyperspectral sensing HyLogger system, together with soil coring and soil property measurements. This allowed the acquisition of mineralogy, pH, and other soil properties at different subsurface depths. Thus, comprehensive understanding and estimation of ASS, both on the surface and in the subsurface, were attained.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2014-02-13T08:00:00Z
      DOI: 10.5589/m13-054
  • Weed and crop discrimination using hyperspectral image data and reduced
    • Authors: P.R. Eddy, A.M. Smith, B.D. Hill, D.R. Peddle, C.A. Coburn, R.E. Blackshaw
      Pages: 481 - 490
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue 06, Page 481-490, December 2013.
      Accurate and efficient weed detection in crop fields is a key requirement for directed herbicide application in real-time Site-Specific Weed Management (SSWM). Using very high spatial resolution (1.25 mm) hyperspectral (HS) image data (61 bands, 400–1000 nm at 10 nm spectral resolution), this study determined that reduced HS bandsets are feasible for discriminating weeds (wild oats, redroot pigweed) from crops (field pea, spring wheat, canola) using Artificial Neural Network (ANN) classification. A 7-band set identified through principal component analysis and stepwise discriminant analysis yielded ANN classification accuracies (88% to 94%) that were nearly equivalent to the full 61-band HS results (89% to 95%) at replicate field plots in southern Alberta, Canada. Therefore, low dimensional narrowband sensors or similar bandsets derived from HS data warrant consideration for SSWM. The computational savings possible from this substantial level of data reduction are potentially critical for enabling optimal use of HS data in real-time ground-based SSWM systems. Recommendations made based on these results have potentially broader implications to SSWM with respect to on-board processing efficiency, weed–crop discrimination method, and sensor and algorithm design.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2014-02-18T08:00:00Z
      DOI: 10.5589/m14-001
  • Polarimetric Radarsat-2 wetland classification using the Touzi
           decomposition: case of the Lac Saint-Pierre Ramsar wetland
    • Pages: 491 - 506
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue 06, Page 491-506, December 2013.
      Wetlands play a key role in regional and global environments and are linked to climate change, water quality, and hydrological and carbon cycles. They also contribute to wildlife habitat and biodiversity and can act as indicators of overall environmental health. Unfortunately, wetlands continue to be under threat. There is an immediate need for improved mapping and monitoring of wetlands to better manage and protect these sensitive areas. Recently, the Touzi decomposition was introduced and proved very promising for wetland characterization using polarimetric airborne (Convair-580) SAR data. The purpose of this study is to assess the Touzi incoherent target-scattering decomposition (ICTD) for wetland classification using polarimetric Radarsat-2 (RS2) data collected over the RAMSAR wetland site in Lac Saint-Pierre, Canada. In particular, the sensitivity of the ICTD parameters to seasonal evolution of marsh and swamp scattering is discussed and demonstrated. The intent is to show that the dominant scattering type magnitude (αs1) and phase (Φs1), and the dominant (η1) and lowest scattering eigenvalues (η3), lead to an effective characterization of the various backscattering mechanisms of the wetland plant species. The ICTD parameters form the basis of a new hierarchical classification that is efficient for wetland classification. The use of multitemporal information obtained from multidate RS2 acquisitions between April and September allows an accurate wetland classification. The RS2 polarimetric classification is then compared with a supervised maximum-likelihood classification using a pair of Landsat-5 images.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2014-02-26T08:00:00Z
      DOI: 10.5589/m14-002
  • A new Bayesian ensemble of trees approach for land cover classification of
           satellite imagery
    • Authors: Reshu Agarwal, Pritam Ranjan, Hugh Chipman
      Pages: 507 - 520
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue 06, Page 507-520, December 2013.
      Classification of satellite images is a key component of many remote sensing applications. One of the most important products of a raw satellite image is the classification that labels image pixels into meaningful classes. Though several parametric and nonparametric classifiers have been developed thus far, accurate classification still remains a challenge. In this paper, we propose a new reliable multiclass classifier for identifying class labels of a satellite image in remote sensing applications. The proposed multiclass classifier is a generalization of a binary classifier based on the flexible ensemble of regression trees model called Bayesian Additive Regression Trees. We used three small areas from the LANDSAT 5 TM image, acquired on 15 August 2009 (path–row: 08–29, L1T product, UTM map projection) over Kings County, Nova Scotia, Canada, to classify the land cover. Several prediction accuracy and uncertainty measures have been used to compare the reliability of the proposed classifier with the state-of-the-art classifiers in remote sensing.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2014-03-05T08:00:00Z
      DOI: 10.5589/m14-003
  • Interpretation of forest disturbance using a time series of Landsat
           imagery and canopy structure from airborne lidar
    • Authors: Oumer S. Ahmed, Steven E. Franklin, Michael A. Wulder
      Pages: 521 - 542
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue 06, Page 521-542, December 2013.
      In this study we examined forest disturbance, largely via forest harvest, over three decades in a coastal temperate forest on Vancouver Island, British Columbia, Canada. We analysed how disturbance history relates to current canopy structural conditions by interpreting the relationship between light detection and ranging (lidar) derived canopy structure and forest disturbance trajectories derived from Landsat images to assess if a particular stand structural condition is to result based on disturbance histories. The lidar data were obtained in 2004, and are used to relate forest structural conditions at the end of the Landsat time series (1972–2004), essentially providing for a measure of resultant structure emerging from the spectral trends captured. Correlation analysis was applied between lidar-derived canopy structure (canopy cover and height) and Landsat spectral indices, such as the Tasseled Cap Angle (TCA), which showed a strong correlation coefficient (r = 0.86) with canopy cover. TCA was then used to characterize change in forest disturbance through the full temporal depth of the available Landsat image time series using a trajectory-based characterization method. Approximately 71.5% of the study area was found to correspond to “stable and undisturbed forest”. Four disturbance classes (areas characterized by disturbance, disturbance followed by revegetation, ongoing revegetation, and revegetation to stable state) accounted for approximately 10.2%, 5.3%, 2.2%, and 10.5% of the study area, respectively. We evaluated the forest structural and spectral separability between the disturbance classes. In terms of structural variability the mean airborne lidar-derived canopy cover showed clear differentiation between disturbance classes. Spectral mixture analysis (SMA) was used to extract the spectral characteristics for each disturbance class. The SMA-derived fractions were then used to analyse the class separability between the Landsat trajectory derived disturbance classes. The fraction images provided clear distinction between disturbance classes in abundances between sunlit canopy, non-photosynthetic vegetation, shade, and exposed soil. The extracted spectral indices and SMA fractions within the Landsat trajectory derived disturbance classes were used to assess if terminal forest structural conditions can be related to a complex suite of stand development trajectories and processes. The Landsat spectral indices and SMA fractions were separately modeled to estimate lidar-derived mean canopy cover and height data within each disturbance class using multiple regression. The results indicate canopy cover and height regression models developed using spectral indices provided a relatively better estimation than those using SMA endmember fractions. Compared with the relatively regular structure of fully grown undisturbed (stable) forests, the forest disturbance classes typically exhibited complex irregular structure, making it more difficult to accurately estimate their canopy cover and height. As a result, all models developed for the stable forest class performed better than those developed for other forest disturbance classes. Modeling canopy cover and height from Landsat temporal spectral indices resulted in modeled agreement to lidar measures of R2 0.82 (RMSE 0.09) and R2 0.67 (RMSE 3.21), respectively. Our results also indicate moderately accurate predictions of lidar-derived canopy height can be obtained using the Landsat-level disturbance class endmember fractions with R2 0.60 and RMSE 4.19. This study demonstrates the potential of using the over four decade record of Landsat observations (since 1972) to estimate forest canopy cover and height using prestratification of the data based on disturbance trajectories.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2014-03-12T07:00:00Z
      DOI: 10.5589/m14-004
  • Tree crown segmentation based on a geometric tree crown model for
           prediction of forest variables
    • Authors: Johan Holmgren, Eva Lindberg
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue s1, Page S86-S98, December 2013.
      A new algorithm for tree crown segmentation from airborne laser scanning data was validated at a test site in southern Sweden (lat. 58° N, long. 13° E). The tree crown segmentation algorithm used a correlation surface created by fitting a geometric tree crown model and was also controlled using an a priori probability function. If the model fit alone was used, 69% of the field-measured trees were detected but when a priori information was used, the proportion of detected trees increased to 75%. The proportion of detected trees represented 95% of the total stem volume for all field measured living trees. The tree crown segments, with zero, one, or several trees, were used as input to an imputation algorithm for prediction of forest variables, which yielded relative root mean square errors of 8.9% for stem volume, 7.2% for basal area, 3.8% for mean tree height, 6.3% for mean stem diameter, and 15% for stem density, after aggregation to plot level for cross-validation. Thus, automatic tree crown delineation using the segmentation algorithm could be used for imputation of tree stems to obtain high accuracy predictions of several forest variables.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2013-12-20T12:43:56Z
      DOI: 10.5589/m13-025
  • Status and prospects for LiDAR remote sensing of forested ecosystems
    • Authors: M.A. Wulder, N.C. Coops, A.T. Hudak, F. Morsdorf, R. Nelson, G. Newnham, M. Vastaranta
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue s1, Page S1-S5, December 2013.
      The science associated with the use of airborne and satellite Light Detection and Ranging (LiDAR) to remotely sense forest structure has rapidly progressed over the past decade. LiDAR has evolved from being a poorly understood, potentially useful tool to an operational technology in a little over a decade, and these instruments have become a major success story in terms of their application to the measurement, mapping, or monitoring of forests worldwide. Invented in 1960, the laser and, a short time later, LiDAR, were found in research and military laboratories. Since the early 2000s, commercial technological developments coupled with an improved understanding of how to manipulate and analyze large amounts of collected data enabled notable scientific and application developments. A diversity of rapidly developing fields especially benefit from communications offered through conferences such as SilviLaser, and LiDAR has been no different. In 2002 the SilviLaser conference series was initiated to bring together those interested in the development and application of LiDAR for forested environments. Now, a little over a decade later, commercial use of LiDAR is common. In this paper – using the deliberations of SilviLaser 2012 as a source of information – we aim to capture aspects of importance to LiDAR users in the forest ecosystems community and to also point to key emerging issues as well as some remaining challenges.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2013-12-20T12:43:38Z
      DOI: 10.5589/m13-051
  • Patterns of covariance between airborne laser scanning metrics and Lorenz
           curve descriptors of tree size inequality
    • Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue s1, Page S18-S31, December 2013.
      The Lorenz curve, as a descriptor of tree size inequality within a stand, has been suggested as a reliable means for characterizing forest structure and distinguishing even from uneven-sized areas. The aim of this study was to achieve a thorough understanding on the relations between airborne laser scanning (ALS) metrics and indicators based on Lorenz curve ordering: Gini coefficient (GC) and Lorenz asymmetry (S). Exploratory multivariate analysis was carried out using correlation tests, partial least squares (PLS), and an information-theoretic approach for multimodel inference (MMI). Best subset linear model was selected for GC and S prediction, as variable transformations yielded no improvement in the relation of ALS with the given response. Relative variable importance based on the MMI model showed that GC is best predicted by ALS metrics expressing canopy coverage, return dispersion, and low–high percentile combinations. Although ALS metrics showed no correlation with S, they did so against its constituting components: the proportions of basal area ([math]) and stem density ([math]) stocked above the mean quadratic diameter. The study of PLS loading vectors illustrated how ALS metrics explain variance in opposing directions for each of these components, so that their effects cancel each other out in the overall S. Cross-validation showed that only marginal differences are nevertheless found between predicting S directly or as the sum [math] and [math] estimations. The differing relation of diverse ALS metrics was therefore observed for [math] and [math]. The conclusions obtained by this research may assist in selecting relevant Lorenz curve descriptors for forest structure characterization, as well as in variable reduction strategies for their wall-to-wall prediction by means of ALS metrics.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2013-12-20T12:43:22Z
      DOI: 10.5589/m13-012
  • Assessing the impact of broadleaf tree structure on airborne full-waveform
           small-footprint LiDAR signals through simulation
    • Authors: Paul Romanczyk, Jan van Aardt, Kerry Cawse-Nicholson, David Kelbe, Joe McGlinchy, Keith Krause
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue s1, Page S60-S72, December 2013.
      Full-waveform small-footprint Light Detection and Ranging (LiDAR) is still in the early stages of development for forest structure assessment, in part due to the complex interaction between a laser pulse and the forest structure, which is not yet fully understood. In recent years, simulation studies (which claim absolute ground truth) have sought to tackle this problem. The challenge remains to determine the limit of structural fidelity, in terms of tree structural components, that is required for waveform-based simulation studies. Understanding of such interactions could lead to improved biophysical modeling from LiDAR waveform signals. We present a simulation study that evaluates the impact of tree structural components on received waveform signals across different outgoing pulse widths and scanning angles. The simulation was performed on a small red maple (Acer rubrum) and red oak (Quercus rubra) stand. It was concluded the back-scattered waveform is dominated by the leaves, while the trunks, twigs, and leaf stems had a minimal impact on the signal. Scan angle (0°, 10°, and 20°) and outgoing pulse width (4 ns, 8 ns, and 16 ns) do not have as statistically significant (95% confidence) impact on mean waveform comparison statistics. This result has implications on the level of complexity required for future simulations and for waveform LiDAR based structural algorithm development.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2013-12-20T12:42:39Z
      DOI: 10.5589/m13-015
  • How did we get here' An early history of forestry lidar
    • Authors: Ross Nelson
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue s1, Page S6-S17, December 2013.
      Functioning lasers were first demonstrated in 1960 in the United States and in 1961 in Canada and in the Soviet Union, but research into the use of lasers as forest measurement tools did not begin for another 15 years. Initially, with respect to Earth resources, lasers were employed to measure sea ice surface roughness, to make near-shore bathymetric measurements, to penetrate forests to make detailed topographic measurements, and to fluoresce oceanic phytoplankton for surface current studies. Some of these early studies noted that forest profiles were evident but in fact added noise to topographic retrievals. As early as 1964, researchers noted vegetation returns acquired using an airborne helium–neon (He–Ne), 0.63 μm, continuous wave (CW) laser. A decade and many airborne studies later, scientists with TRANARG, a mapping and surveying company in Caracas, Venezuela, reported on flights undertaken in 1976 that utilized a He–Ne lidar to collect over 11000 km of lidar profiles, spaced 1.5 km apart, to construct a topographic map to help site a new reservoir. Though they depended on the laser to penetrate vegetation, they noted 35–40 m median canopy heights with emergents up to 55 m in their profiles. Trees came to be regarded as a signal rather than noise in the mid-1970s. In 1976 in the Soviet Union, Russian researchers felled a birch and a spruce, aimed a He–Ne CW laser with a spot size of approximately 25 mm at the horizontal trees, produced a profilograph, compared it with tape measurements, and concluded that, with increased power, such a laser could be mounted on an aircraft to remotely measure forest canopies. In 1979, they mounted their He–Ne laser on an AN-2 biplane and acquired their first airborne profiles. These studies and others done prior to 1985, i.e., the first two decades of airborne laser research, are reviewed in this glance backwards at the history of forestry lidar.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2013-12-20T12:42:25Z
      DOI: 10.5589/m13-011
  • Effect of scanning angle on vegetation metrics derived from a nationwide
           Airborne Laser Scanning acquisition
    • Authors: Alessandro Montaghi
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue s1, Page S152-S173, December 2013.
      The influence of scanning angle on vegetation metrics derived from a large area Airborne Laser Scanning (ALS) data acquisition was evaluated in this study. The ALS data were derived from the ongoing acquisition for the new Swedish Nationwide Elevation Model. To make a comparison of scanning angles, a random selection of 2310 sample plots (0.01 ha in size) was taken from two large forested areas in the north and south of Sweden. Only plots that had ALS data from two different acquisitions on the same day were used: the first scanned at nadir (0° scanning angle) and the second with an absolute scanning angle ranging from 0° to a nominal 20°. For each plot, 32 plot-level vegetation metrics were calculated from the ALS data for each pair of scanning angles. The ALS metrics for each pair were then compared using a nonparametric Wilcoxon signed-rank test. The results indicated that most metrics commonly used in area-based prediction of forest variables were relatively unaffected by high scanning angles, up to 20°. However, the vegetation ratio and the understory ratio from scanning angles greater than 10° were significantly different from those derived from a 0° scanning angle.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2013-12-19T08:00:00Z
      DOI: 10.5589/m13-052
  • Investigating the agreement between global canopy height maps and airborne
           Lidar derived height estimates over Canada
    • Authors: Douglas K. Bolton, Nicholas C. Coops, Michael A. Wulder
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue s1, Page S139-S151, December 2013.
      Carbon storage in forest aboveground biomass is a critical, yet difficult, component of the global carbon cycle to estimate. Canopy height, a key indicator of carbon storage, can be estimated from Light Detection and Ranging (Lidar) waveforms collected by the Geoscience Laser Altimeter System (GLAS) aboard the Ice, Cloud, and land Elevation Satellite (ICESat). Although globally distributed, GLAS does not provide spatially exhaustive coverage. Therefore, accurate methods of extrapolation are necessary to produce wall-to-wall global canopy height maps from these data. In this analysis, we compare two of these global GLAS-derived height products to canopy height estimates derived from 25000 km of discrete return airborne Lidar data over Canada's boreal forests. We selected the 95th percentile of first return height from airborne Lidar as a measure of canopy height to relate against estimates from the global GLAS-derived products. The agreement between the global GLAS-derived products and airborne Lidar-derived height estimates varied between the two products (average ecozone RMSE = 3.9 and 7.4 m), demonstrating that differences in data selection, processing, and extrapolation can influence height estimates derived from GLAS data. Where large differences existed between the global GLAS-derived products and the airborne Lidar-derived height estimates, the GLAS-derived products tended to predict taller canopies. Removing GLAS waveforms on steep terrain appeared to be a superior approach to reducing errors in height estimates, as the global GLAS-derived product that filtered these waveforms was in closer agreement with airborne Lidar-derived height estimates in regions of rough terrain (RMSE = 3.2–8.5 m compared with 8.1–13.8 m). Differences in the spatial resolution of canopy height estimates, coupled with varying definitions of canopy height within each product, should be considered when interpreting the results of this analysis. Investigating the relationship between small-footprint Lidar data and published canopy height products can identify the approaches that lead to the most accurate estimates of aboveground biomass and can help determine why discrepancies in height estimates exist between various model approaches, data and underlying environmental conditions.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2013-11-20T08:00:00Z
      DOI: 10.5589/m13-036
  • Simulation of lidar waveforms with a time-dependent radiosity algorithm
    • Authors: Huaguo Huang, Randolph H. Wynne
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue s1, Page S126-S138, December 2013.
      Our objective was to assess the effect of multiple scattering on lidar radiative transfer. We have developed a time-dependent radiosity-based model (RBL) to simulate the propagation of lidar pulses through forest canopies. This 3-D model enables simulation of lidar waveforms with varied topography and clumping vegetation. The incidence angle can also be specified. This new model has the potential to provide better approximations of return waveforms. The prototype is being tested using data from the Scanning Lidar Imager of Canopies by Echo Recovery (SLICER). Waveforms simulated by RBL resemble SLICER waveforms (R2> 0.90) over a jack pine canopy and a black spruce canopy. There is also good agreement (R2> 0.95) when the model results are compared with a time-dependent radiative transfer model. Results to date indicate that multiply scattered photons do increase the intensity of the reflected signal, especially the portion originating from the lower levels of the canopy. A sensitivity analysis enabled assessment of the effects of leaf area index, slope, and canopy height on multiple scattering.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2013-10-21T07:00:00Z
      DOI: 10.5589/m13-035
  • Study of bat flight behavior by combining thermal image analysis with a
           LiDAR forest reconstruction
    • Authors: Xiaoyuan Yang, Crystal Schaaf, Alan Strahler, Thomas Kunz, Nathan Fuller, Margrit Betke, Zheng Wu, Zhuosen Wang, Diane Theriault, Darius Culvenor, David Jupp, Glenn Newnham, Jenny Lovell
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue s1, Page S112-S125, December 2013.
      The nature of forest structure plays an important role in the study of foraging behaviors of bats. In this study, we demonstrate a new combined methodology that uses both thermal imaging technology and a ground-based LiDAR system to record and reconstruct Eptesicus fuscus (big brown bats) flight trajectories in three-dimensional (3-D) space. The combination of the two 3-D datasets provided a fine-scale reconstruction of the flight characteristics adjacent to and within the forests. A 3-D forest reconstruction, assembled from nine Echidna Validation Instrument LiDAR scans over the 1 ha site area, provided the essential environmental variables for the study of bat foraging behaviors, such as the canopy height, terrain, location of the obstacles, and canopy openness at a bat roosting and maternity site in Petersham, Massachusetts. Flight trajectories of 24 bats were recorded over the 25 m × 37.5 m region within the LiDAR forest reconstruction area. The trajectories were reconstructed using imaging data from multiple FLIR ThermoVision SC8000 cameras and were co-registered to the 3-D forest reconstruction. Twenty-four of these flight trajectories were categorized into four different behavior groups according to velocity and altitude analysis of the flight trajectories. Initial results showed that although all bats were guided by echolocation and avoided hitting a tree that was in all of their flight paths, different bats chose different flight routes. This study is an initial demonstration of the power of coupling thermal image analysis and LiDAR forest reconstructions. Our goal was to break ground for future ecological studies, where more extensive flight trajectories of bats can be coupled with the canopy reconstructions to better establish responses of bats to different habitat characteristics and clutter, which includes both static (trees) and dynamic (other bats) obstacles.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2013-10-02T07:00:00Z
      DOI: 10.5589/m13-034
  • Predicting live and dead tree basal area of bark beetle affected forests
           from discrete-return lidar
    • Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue s1, Page S99-S111, December 2013.
      Bark beetle outbreaks have killed large numbers of trees across North America in recent years. Lidar remote sensing can be used to effectively estimate forest biomass, but prediction of both live and dead standing biomass in beetle-affected forests using lidar alone has not been demonstrated. We developed Random Forest (RF) models predicting total, live, dead, and percent dead basal area (BA) from lidar metrics in five different beetle-affected coniferous forests across western North America. Study areas included the Kenai Peninsula of Alaska, southeastern Arizona, north-central Colorado, central Idaho, and central Oregon, U.S.A. We created RF models with and without intensity metrics as predictor variables and investigated how intensity normalization affected RF models in Idaho. RF models predicting total BA explained the most variation, whereas RF models predicting dead BA explained the least variation, with live and percent dead BA models explaining intermediate levels of variation. Important metrics varied between models depending on the type of BA being predicted. Generally, height and density metrics were important in predicting total BA, intensity and density metrics were important in predicting live BA, and intensity metrics were important in predicting dead and percent dead BA. Several lidar metrics were important across all study areas. Whether needles were on or off beetle-killed trees at the time of lidar acquisition could not be ascertained. Future work, where needle conditions at the time of lidar acquisition are known, could improve upon our analysis and results. Although RF models predicting live, dead, and percent dead BA did not perform as well as models predicting total BA, we concluded that discrete-return lidar can be used to provide reasonable estimations of live and dead BA. Our results also showed which lidar metrics have general utility across different coniferous forest types.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2013-09-26T07:00:00Z
      DOI: 10.5589/m13-027
  • Tree genera classification with geometric features from high-density
           airborne LiDAR
    • Authors: Connie Ko, Gunho Sohn, Tarmo K. Remmel
      Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue s1, Page S73-S85, December 2013.
      Categorical recognition of a tree's genus is known to be valuable information for the effective management of forest inventories. In this paper, we present a method for learning a discriminative model using Random Forests to classify individual trees into three genera: pine, poplar, and maple. We believe that both internal and external geometric characteristics of the tree crown are related to tree form and therefore useful in classifying trees to the genus level. Our approach involves the extraction of both internal and external geometric features from a LiDAR point cloud as we believe that geometric features provide important information about the organization of the points inside the tree crown along with overall tree shape and form. We developed 24 geometric features and then reduced the number of features to increase efficiency. These geometric characteristics, computed for 160 sampled trees from eight field sites, were classified using Random Forests and achieved an 88.3% average accuracy rate by using 25% (40 trees) of the data for training.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2013-09-23T07:00:00Z
      DOI: 10.5589/m13-024
  • Validation of L-Architect model for balsam fir and black spruce trees with
           structural measurements
    • Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue s1, Page S41-S59, December 2013.
      The fine reconstruction of tree structure provides important information that is relevant to forest ecological processes and may be linked to wood quality attributes. Terrestrial laser scanners (TLS) provide detailed and accurate 3-D data and have the potential to enhance forest inventories with fine-scale information on structure. However, in forests, TLS data are limited by the effects of object occlusion and wind. Therefore, adequate tree reconstruction is not possible. In previous studies, we used the architectural model L-Architect (LiDAR data to tree Architecture) to overcome the limitations of TLS to characterize the 3-D tree structure. In this study, L-Architect was validated using structural measurements for two coniferous species found in Newfoundland (Canada), namely, balsam fir (Abies balsamea) and black spruce (Picea mariana). The model reproduced realistic tree structures using TLS data and allometric relationships to define the total amount of foliage following two main steps: branch growth and addition of foliage within the crown. Results from L-Architect were compared with measurements of branching structure from the main stem (angle of insertion, length, and diameter) and vertical distribution of foliage indicated by the shoot vertical distribution for six sampled trees. Averaged normalized root-mean square errors of 21%, 20%, 25%, and 21% were obtained for branch diameter, branch length, angle of branch insertion, and vertical distribution of foliage, respectively.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2013-06-26T07:00:00Z
      DOI: 10.5589/m13-014
  • Detection of fallen trees in forested areas using small footprint airborne
           laser scanning data
    • Abstract: Canadian Journal of Remote Sensing, Volume 39, Issue s1, Page S32-S40, December 2013.
      Deadwood was identified as an important indicator for habitat condition and biodiversity in forests. The assessment of downed trees is therefore part of sustainable forest management and ecological monitoring. However, manual quantification of deadwood in forests is challenging, time consuming, and considered cost-inefficient. Full-waveform airborne laser scanning (FWF-ALS) can be used to support the assessment process. The amplitude and width of the backscattered pulses contain information on the properties of the surface. We used these observations for the identification of downed trees in a Natura2000 forest site. A high density FWF-ALS data set was acquired under leaf-off conditions. Echo width and type (i.e., first, intermediate, and last) information as well as normalized echo heights were used to filter the point cloud and derive a digital height model (DHM). This DHM depicts downed stems as line-like features. Image processing was applied to derive and refine regions representing fallen trees. Terrestrial reference data consisting of locations and dimensions of downed trees, as well as state of decay were used for evaluation. Direct identification of downed trees in FWF-ALS point clouds was possible (completeness 75%, correctness 90%), but it was influenced by factors such as dimension, state of decay, vegetation density, and penetration of the laser.
      Citation: Canadian Journal of Remote Sensing
      PubDate: 2013-06-14T07:00:00Z
      DOI: 10.5589/m13-013
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