Alan H. Strahler

Boston University, Boston, Massachusetts, United States

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Publications (294)507.95 Total impact

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    ABSTRACT: We describe the capabilities and performance of a terrestrial laser scanning instrument built for the purpose of recording and retrieving the three-dimensional structure of forest vegetation. The dual-wavelength Echidna® lidar characterizes the forest structure at an angular resolution as fine as 1 mrad while distinguishing between leaves and trunks by exploiting their differential reflectances at two wavelengths: 1 and 1.5 μm. The instrument records the full waveforms of return signals from 5 ns laser pulses at half-nanosecond time resolution; obtains ±117 deg zenith and 360 deg azimuth coverage out to a radius of more than 70 m; provides single-target range resolution of 4.8 and 2.3 cm for the 1 and 1.5 μm channels, respectively (1σ); and separates adjacent pulse returns in the same waveform at a distance of 52.0 and 63.8 cm apart for the 1 and 1.5 μm channels, respectively. The angular resolution is in part controlled by user-selectable divergence optics and is shown to be <2 mrad for the instrument's standard resolution mode, while the signal-to-noise ratio is 10 at 70 m range for targets with leaf-like reflectance for both channels. The portability and target differentiation make the instrument an ideal ground-based lidar suited for vegetation sensing. © 2015 Society of Photo-Optical Instrumentation Engineers (SPIE).
    No preview · Article · Dec 2015 · Journal of Applied Remote Sensing
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    ABSTRACT: Plot-scale measurements have been the foundation for forest surveys and reporting for over 200 years. Through recent integration with airborne and satellite remote sensing, manual measurements of vegetation structure at the plot scale are now the basis for landscape, continental and international mapping of our forest resources. The use of terrestrial laser scanning (TLS) for plot-scale measurement was first demonstrated over a decade ago, with the intimation that these instruments could replace manual measurement methods. This has not yet been the case, despite the unparalleled structural information that TLS can capture. For TLS to reach its full potential, these instruments cannot be viewed as a logical progression of existing plot-based measurement. TLS must be viewed as a disruptive technology that requires a rethink of vegetation surveys and their application across a wide range of disciplines. We review the development of TLS as a plot-scale measurement tool, including the evolution of both instrument hardware and key data processing methodologies. We highlight two broad data modelling approaches of gap probability and geometrical modelling and the basic theory that underpins these. Finally, we discuss the future prospects for increasing the utilisation of TLS for plot-scale forest assessment and forest monitoring.
    Full-text · Article · Oct 2015
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    ABSTRACT: Full waveform lidar has a unique capability to characterise vegetation in more detail than any other practical method. The reflectance, calculated from the energy of lidar returns, is a key parameter for a wide range of applications and so it is vital to extract it accurately. Fifteen separate methods have been proposed to extract return energy (the amount of light backscattered from a target), ranging from simple to mathematically complex, but the relative accuracies have not yet been assessed. This paper uses a simulator to compare all methods over a wide range of targets and lidar system parameters. For hard targets the simplest methods (windowed sum, peak and quadratic) gave the most consistent estimates. They did not have high accuracies, but low standard deviations show that they could be calibrated to give accurate energy. This may be why some commercial lidar developers use them, where the primary interest is in surveying solid objects. However, simulations showed that these methods are not appropriate over vegetation. The widely used Gaussian fitting performed well over hard targets (0.24% root mean square error, RMSE), as did the sum and spline methods (0.30% RMSE). Over vegetation, for large footprint (15 m) systems, Gaussian fitting performed the best (12.2% RMSE) followed closely by the sum and spline (both 12.7% RMSE). For smaller footprints (33 cm and 1 cm) over vegetation, the relative accuracies were reversed (0.56% RMSE for the sum and spline and 1.37% for Gaussian fitting). Gaussian fitting required heavy smoothing (convolution with an 8 m Gaussian) whereas none was needed for the sum and spline. These simpler methods were also more robust to noise and far less computationally expensive than Gaussian fitting. Therefore it was concluded that the sum and spline were the most accurate for extracting return energy from waveform lidar over vegetation, except for large footprint (15 m), where Gaussian fitting was slightly more accurate. These results suggest that small footprint (≪ 15 m) lidar systems that use Gaussian fitting or proprietary algorithms may report inaccurate energies, and thus reflectances, over vegetation. In addition the effect of system pulse length, sampling interval and noise on accuracy for different targets was assessed, which has implications for sensor design.
    Full-text · Article · Jul 2015 · Remote Sensing of Environment
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    ABSTRACT: The dual-wavelength Echidna lidar is a portable ground-based full-waveform terrestrial scanning lidar for characterization of fine-scale forest structure and biomass content. While scanning, the instrument records the full time series of returns at a half-nanosecond rate from two coaligned 5-ns pulsed lasers at 1064 and 1548 nm wavelengths. Leaves absorb more strongly at 1548 nm compared to stems, allowing discrimination of forest composition at milliradian scales from the ground to the forest canopy. This work describes the instrument design and data products and demonstrates the power of two wavelength lidar to clearly distinguish leaves from woody material with preliminary field data from the Sierra Nevada National Forest.
    No preview · Article · Apr 2015 · IEEE Geoscience and Remote Sensing Letters
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    Full-text · Article · Sep 2014 · New Phytologist
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    ABSTRACT: In a typical waveform light detection and ranging (lidar) system, the received pulse can be represented by the convolution of the system impulse response, the outgoing pulse, and the underlying signal representing actual target interactions. Deconvolution is the process of removing the contribution of the system impulse response and outgoing pulse from the received signal, so that the true interactions may be seen. In many examples, deconvolution has been shown to expose fine structure within the waveform, which may be used to improve accuracy when estimating the vertical location of certain features. For instance, the exact location of the ground may be more accurately determined by separating the response of the ground from that of understory vegetation or vegetative ground cover. However, in order for the deconvolution to be successful, the impulse response and outgoing pulse must be known, and many deconvolution methods are sensitive to small errors in the estimation of these inputs. In this study, we propose a deconvolution method that uses a flat target response in place of the impulse response and outgoing pulse.
    No preview · Conference Paper · Jun 2014
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    ABSTRACT: A prototype upward-scanning, under-canopy, near-infrared light detection and ranging (lidar) system, the Echidna ® validation instrument (EVI), built by CSIRO Australia, retrieves forest stand structural parameters, including mean diameter at breast height (DBH), stand height, distance to tree, stem count density (stems/area), leaf-area index (LAI), and stand foliage profile (LAI with height) with very good accuracy in early trials. We validated retrievals with ground-truth data collected from two sites near Tumbarumba, New South Wales, Australia. In a ponderosa pine plantation, LAI values of 1.84 and 2.18 retrieved by two different methods using a single EVI scan bracketed a value of 1.98 estimated by allometric equations. In a natural, but managed, Eucalypus stand, eight scans provided mean LAI values of 2.28-2.47, depending on the method, which compare favorably with a value of 2.4 from hemispherical photography. The retrieved foliage profile clearly showed two canopy layers. A "find-trunks" algorithm processed the EVI scans at both sites to identify stems, determine their diameters, and measure their distances from the scan center. Distances were retrieved very accurately (r 2 = 0.99). The accuracy of EVI diameter retrieval decreased somewhat with distance as a function of angular resolution of the instrument but remained unbiased. We estimated stand basal area, mean diameter, and stem count density using the Relaskop method of variable radius plot sampling and found agreement with manual Relaskop values within about 2% after correcting for the obscuring of far trunks by near trunks (occlusion). These early trials prove the potential of under-canopy, upward-scanning lidar to retrieve forest structural parameters quickly and accurately.
    Full-text · Article · Jun 2014 · Canadian Journal of Remote Sensing
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    ABSTRACT: This study applied a hybrid canopy geometric optical and radiative transfer (GORT) model to study the vegetation structure characteristics and lidar signals from a terrestrial below-canopy lidar instrument, Echidna Validation Instrument (EVI), developed by CSIRO Australia. Off-nadir scans from the below-canopy lidar show strong laser energy returns from both leaves and tree trunks. The GORT model was modified to include the effect of both leaves and trunks on below-canopy lidar energy returns by treating the trunks as simple uniform cylinders extending to the middle of each tree crown. GORT was also extended to allow multiple canopy layers by convolution of the canopy gap probability profiles for individual canopy layers. The extended leaf-and-trunk GORT model was evaluated by comparing the modeled and EVI-derived gap probability profiles in a single-layer pine plantation and a two-layer eucalypt forest at the Tumbarumba flux tower site in southeastern New South Wales, Australia. Results show that the new leaf-and-trunk GORT model improves estimates of EVI-derived gap probability profiles. This study demonstrates the potential use of terrestrial upward-scanning hemispherical lidar to retrieve forest canopy structural information. A future goal is to link these terrestrial hemispherical lidar measurements to downward- looking airborne lidar, such as the Laser Vegetation Imaging Sensor (LVIS), and spaceborne lidar, such as the Geoscience Laser Altimeter System (GLAS) on ICESat, through a common model to provide large-area mapping of vegetation structural properties and biomass.
    Full-text · Article · Jun 2014 · Canadian Journal of Remote Sensing
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    ABSTRACT: This study assesses the Moderate-resolution Imaging Spectroradiometer (MODIS) BRDF/albedo 8 day standard product and products from the daily Direct Broadcast BRDF/albedo algorithm, and shows that these products agree well with ground-based albedo measurements during the more difficult periods of vegetation dormancy and snow cover. Cropland, grassland, deciduous and coniferous forests are considered. Using an integrated validation strategy, analyses of the representativeness of the surface heterogeneity under both dormant and snow-covered situations are performed to decide whether direct comparisons between ground measurements and 500-m satellite observations can be made or whether finer spatial resolution airborne or spaceborne data are required to scale the results at each location. Landsat Enhanced Thematic Mapper Plus (ETM +) data are used to generate finer scale representations of albedo at each location to fully link ground data with satellite data. In general, results indicate the root mean square errors (RMSEs) are less than 0.030 over spatially representative sites of agriculture/grassland during the dormant periods and less than 0.050 during the snow-covered periods for MCD43A albedo products. For forest, the RMSEs are less than 0.020 during the dormant period and 0.025 during the snow-covered periods. However, a daily retrieval strategy is necessary to capture ephemeral snow events or rapidly changing situations such as the spring snow melt.
    No preview · Article · Jan 2014 · Remote Sensing of Environment
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    ABSTRACT: 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.
    Full-text · Article · Dec 2013 · Canadian journal of remote sensing
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    ABSTRACT: Abstract New terrestrial scanning LiDAR instruments have recently been deployed during two National Ecological Observatory Network (NEON) airborne campaigns and used to generate 3-D reconstructions of forest structure. The first campaign was held in the summer of 2012 at Harvard Forest, MA, while the second campaign was held in the summer of 2013 in the vicinity of San Joaquin, CA, stretching eastward into the Sierras. The NEON airborne observatory platform (AOP) campaigns included both hyperspectral and full-waveform LiDAR acquisitions, while the terrestrial LiDARs deployed included the full-waveform Dual Wavelength Echidna® LiDAR (DWEL) and the Rochester Institute of Technology (RIT) Canopy Biomass LiDARs (CBLs) developed with industrial SICK instruments. During the Harvard Forest campaign, in addition to multiple scans with both of the LiDAR instruments, field measures (PAI/LAI, tree inventory data) were also collected. Emphasis was placed on two sites (a hardwood plot and a hemlock plot) which have been scanned periodically since 2007 by the predecessor to the DWEL, the Echidna® Validation Instrument (EVI) and offer the possibility of monitoring forest change over time. The new DWEL currently being deployed is designed to utilize two wavelengths – 1064 nm (as with the heritage EVI) and 1548 nm in order to provide better separation of leaves and trunks and hence better measurement of forest structure at the site-level scale. A similar LiDAR acquisition and field sampling protocol was observed during the California campaign where sites from sparse rangelands to forested high terrain were characterized. In addition, these same two LiDAR instruments were deployed near Brisbane, Australia, as part of a scanning activity undertaken by the newly formed Terrestrial Laser Scanning International Interest Group (http://tlsiig.bu.edu/). The detailed 3D reconstructions of forest structure possible by integrating multiple scans from LiDARs such as these serve to bridge the information provided by forest observations at the ground plot-level scales with regional and coarser scales captured by other airborne and spaceborne platforms.
    No preview · Conference Paper · Oct 2013
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    ABSTRACT: Foliage profiles retrieved from a scanning, terrestrial, near-infrared (1064 nm), full-waveform lidar, the Echidna Validation Instrument (EVI), agree well with those obtained from an airborne, near-infrared, full-waveform, large footprint lidar, the Lidar Vegetation Imaging Sensor (LVIS). We conducted trials at 5 plots within a conifer stand at Sierra National Forest in August, 2008. Foliage profiles retrieved from these two lidar systems are closely correlated (e.g., r = 0.987 at 100 m horizontal distances) at large spatial coverage while they differ significantly at small spatial coverage, indicating the apparent scanning perspective effect on foliage profile retrievals. Also we noted the obvious effects of local topography on foliage profile retrievals, particularly on the topmost height retrievals. With a fine spatial resolution and a small beam size, terrestrial lidar systems complement the strengths of the airborne lidars by making a detailed characterization of the crowns from a small field site, and thereby serving as a validation tool and providing localized tuning information for future airborne and spaceborne lidar missions.
    No preview · Article · Sep 2013 · Remote Sensing of Environment
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    L. He · J.M. Chen · J. Pisek · C.B. Schaaf · A.H. Strahler
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    ABSTRACT: This is the supplementary data to "Global clumping index map derived from the MODIS BRDF product". Please find the download link within the data description.
    Full-text · Dataset · Aug 2013
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    ABSTRACT: Background/Question/Methods In August 2012, the National Ecological Observatory Network (NEON) undertook an initial campaign with its Airborne Observation Platform (AOP) over Harvard Forest, Petersham, MA. The AOP includes an instrument suite with a visible-to-shortwave infrared imaging spectrometer, a full waveform light detection and ranging (Lidar) and a high-resolution digital camera. During the campaign, field measures over two sites at Harvard Forest (hardwood and hemlock plots) were collected by teams from Boston University, University of Massachusetts Boston, and University of Massachusetts Lowell. These same two plots have been scanned by a full waveform terrestrial Lidar, the Echidna® Validation Instrument (EVI) at periodic intervals since 2007. During the campaign, the Dual Wavelength Echidna® Lidar (DWEL), a successor instrument to EVI, was also deployed at the hardwood site. The instrument was scanning in an engineering mode and acquired its first scans with a 1548-nm laser. DWEL is designed to utilize two wavelengths – 1064 nm (as with the heritage EVI) and 1548 nm in order to provide better separation of leaves and trunks and hence better measurement of forest structures from ground at the site-level scale. The ground sampling campaign at the two sites also collected LAI measurements with a TRAC instrument, PAI measurements from hemispherical photos, and updated the tree inventory data from earlier years. The ground-based DWEL data and field measurements will serve as part of the validation dataset for processing NEON’s airborne data at Harvard Forest and will also serve to bridge the information provided by the forest observations at the ground plot-level scales with regional and larger scales captured by other airborne and spaceborne platforms. Results/Conclusions The image and point cloud from the early DWEL engineering scans, merged with EVI data acquired in 2010, demonstrate how much darker leaves are and more evident trunks are at the SWIR wavelength of 1548 nm than the NIR wavelength of 1064 nm. The terrestrial DWEL and the airborne NEON Lidar data together improve our understanding and characterization of forests at different scales from both below and above the canopy.
    No preview · Conference Paper · Aug 2013
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    ABSTRACT: Three-dimensional (3-D) reconstructions of forest stands, constructed from scans of the Echidna® full-waveform terrestrial lidar, provide a new pathway to estimate forest structural parameters such as tree diameter at breast height, tree height, crown diameter, and stem count density (trees per hectare). We provide such reconstructions using data from the Echidna® Validation Instrument (EVI), which emits laser pulses at 1064 nm wavelength and digitizes the full return waveform. We reconstructed four stands from the Sierra National Forest and two stands from Harvard Experimental Forest of 50 m by 50 m size, with varying tree density and species, using data acquired in 2008 and 2009. Our procedure processes each lidar pulse return to identify one or multiple “hits” and their associated peak return power; converts peak power to apparent reflectance; locates hits in Cartesian coordinate space and stores them as points in a point cloud with associated attributes; registers and merges five (Sierra) or nine (Harvard) overlapping scans into a single point cloud; identifies the ground plane and classifies ground hits; produces a local digital elevation model; classifies non-ground hits as trunk/branch or foliage hits using the relative width of the return pulse; and uses commercial software tools to display, manipulate, and interact with the point cloud to make direct measurements of trees in the virtual space of the reconstruction. Results show good to very good agreement between virtual and manual measurements of tree diameter, height, and crown size, with R2 values ranging from 0.70 to 0.99.
    Full-text · Article · Aug 2013 · Remote Sensing of Environment
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    ABSTRACT: Land surface vegetation phenology is an efficient bio-indicator for monitoring ecosystem variation in response to changes in climatic factors. The primary objective of the current article is to examine the utility of the dailyMODIS 500 m reflectance anisotropy direct broadcast (DB) product for monitoring the evolution of vegetation phenological trends over selected crop, orchard, and forest regions. Although numerous model-fitted satellite data have been widely used to assess the spatio-temporal distribution of land surface phenological patterns to understand phenological process and phenomena, current efforts to investigate the details of phenological trends, especially for natural phenological variations that occur on short time scales, are less well served by remote sensing challenges and lack of anisotropy correction in satellite data sources. The daily MODIS 500 m reflectance anisotropy product is employed to retrieve daily vegetation indices (VI) of a 1 year period for an almond orchard in California and for a winter wheat field in northeast China, as well as a 2 year period for a deciduous forest region in New Hampshire, USA. Compared with the ground records from these regions, the VI trajectories derived from the cloud-free and atmospherically corrected MODIS Nadir BRDF (bidirectional reflectance distribution function) adjusted reflectance (NBAR) capture not only the detailed footprint and principal attributes of the phenological events (such as flowering and blooming) but also the substantial inter-annual variability. This study demonstrates the utility of the daily 500 m MODIS reflectance anisotropy DB product to provide daily VI for monitoring and detecting changes of the natural vegetation phenology as exemplified by study regions comprising winter wheat, almond trees, and deciduous forest.
    No preview · Article · Aug 2013 · International Journal of Remote Sensing
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    ABSTRACT: Terrestrial laser scanning combining both near-infrared (NIR) and shortwave-infrared (SWIR) wavelengths can readily distinguish broad leaves from trunks, branches, and ground surfaces. Merging data from the 1548 nm SWIR laser in the Dual-Wavelength Echidna® Lidar (DWEL) instrument in engineering trials with data from the 1064 nm NIR laser in the Echidna® Validation Instrument (EVI), we imaged a deciduous forest scene at the Harvard Forest, Petersham, Massachusetts, and showed that trunks are about twice as bright as leaves at 1548 nm, while they have about equal brightness at 1064 nm. The reduced return of leaves in the SWIR is also evident in merged point clouds constructed from the two laser scans. This distinctive difference between leaf and trunk reflectance in the two wavelengths validates the principle of effective discrimination of leaves from other targets using the new dual-wavelength instrument.
    No preview · Conference Paper · Jul 2013
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    ABSTRACT: This study presents a three-dimensional (3-D) forest reconstruction methodology using the new and emerging science of terrestrial full-waveform lidar scanning, which can provide rapid and efficient measurements of canopy structure. A 3-D forest reconstruction provides a new pathway to estimate forest structural parameters such as tree diameter at breast height, tree height, crown diameter, and stem count density (trees per hectare). It enables the study of the detailed structure study with respect to the canopy (foliage or branch/trunk), as well as the generation of a digital elevation model (DEM) and a canopy height model (CHM) at the stand level. Leaf area index (LAI) and Foliage area volume density profile directly estimated from voxelized 3-D reconstruction agree with measurements from field and airborne instrument. A 3-D forest reconstruction allows virtual direct representation of forest structure, and provides consistent and reliable validation data sources for airborne or spaceborne data.
    No preview · Conference Paper · Jul 2013
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    ABSTRACT: The National Ecological Observatory Network (NEON) is a continental-scale research platform that will collect information on ecosystems across the United States to advance our ability to forecast environmental change at the continental-scale. The Airborne Observation Platform (AOP) will fly an instrument suite consisting of a visible-toshortwave infrared imaging spectrometer, a full waveform light detection and ranging (LiDAR), and a highresolution digital camera. NEON AOP will focus on several of the terrestrial Essential Climate Variables (ECV) (Stitt, 2011) including bioclimate, biodiversity, biogeochemistry, and land use products. These variables are collected throughout a network of 60 sites across the Continental United States, Alaska, Hawaii, and Puerto Rico via ground-based and airborne measurements. A series of AOP test flights were conducted during the first year of NEON construction with the goal of testing instrument functionality and performance, exercising remote sensing collection protocols, and providing data for algorithm and product validation. These test flights were designed to address the following questions: What is the optimal remote sensing data collection protocol to meet NEON science requirements?; How do aircraft altitude, spatial sampling, spatial resolution, and LiDAR instrument configuration affect data retrievals?; What are appropriate algorithms to derive ECVs from AOP data?; and What methodology should be followed to validate AOP remote sensing products and how should ground truth data be collected? Early test flights around Grand Junction, CO and Ivanpah, CA in May 2012 were focused on radiometric and geometric calibration as well as processing from raw data (Level 0) to corrected (Level 1) products. Next, flights were conducted in the Northeastern U.S. at Harvard Forest in August 2012 with a focus on vegetation chemistry and structure measurements. Vegetation field sampling measurements were performed in coordination with the test flights, including ground LiDAR measurements to validate the airborne LiDAR instrument. An overview of the test flights and ground campaign is provided. Data from the campaign will be available to the science community once processed. Copyright © (2013) by the American Society for Photogrammetry & Remote Sensing.
    No preview · Article · Jan 2013
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    ABSTRACT: The Echidna Validation Instrument (EVI), a ground-based, near-infrared (1064 nm) scanning lidar, provides gap fraction measurements, element clumping index measurements, effective leaf area index (LAIe) and leaf area index (LAI) measurements that are statistically similar to those from hemispherical photos. In this research, a new method integrating the range dimension is presented for retrieving element clumping index using a unique series of images of gap probability (Pgap) with range from EVI. From these images, we identified connected gap components and found the approximate physical, rather than angular, size of connected gap component. We conducted trials at 30 plots within six conifer stands of varying height and stocking densities in the Sierra National Forest, CA, in August 2008. The element clumping index measurements retrieved from EVI Pgap image series for the hinge angle region are highly consistent (R2 = 0.866) with those of hemispherical photos. Furthermore, the information contained in connected gap component size profiles does account for the difference between our method and gap-size distribution theory based method, suggesting a new perspective to measure element clumping index with EVI Pgap image series and also a potential advantage of three dimensional Lidar data for element clumping index retrieval. Therefore further exploration is required for better characterization of clumped condition from EVI Pgap image series.
    No preview · Article · Oct 2012 · Remote Sensing of Environment

Publication Stats

15k Citations
507.95 Total Impact Points

Institutions

  • 1029-2015
    • Boston University
      • • Department of Earth & Environment
      • • Department of Geography and Environment
      • • Center for Remote Sensing
      Boston, Massachusetts, United States
  • 2014
    • City University of New York - Hunter College
      • Department of Geography
      Manhattan, New York, United States
  • 1999-2012
    • Remote Sensing Systems
      Santa Rosa, California, United States
  • 1996-2006
    • University of Massachusetts Boston
      Boston, Massachusetts, United States
    • Purdue University
      • School of Electrical and Computer Engineering
      West Lafayette, IN, United States
  • 2002
    • Beijing Normal University
      Peping, Beijing, China
  • 2001
    • University College London
      • Department of Geography
      London, ENG, United Kingdom
  • 2000
    • Potsdam Institute for Climate Impact Research
      Potsdam, Brandenburg, Germany
  • 1995
    • University of Maryland, College Park
      • Department of Geographical Sciences
      Maryland, United States
  • 1988
    • Chinese Academy of Sciences
      • Institute of Remote Sensing Applications
      Peping, Beijing, China
  • 1980-1988
    • University of California, Santa Barbara
      • Department of Geography
      Santa Barbara, California, United States
  • 1985-1987
    • CUNY Graduate Center
      New York City, New York, United States