A.H. Strahler

Boston University, Boston, Massachusetts, United States

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Publications (276)457.62 Total impact

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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.
    Remote Sensing of Environment 07/2015; 164. DOI:10.1016/j.rse.2015.04.013 · 6.39 Impact Factor
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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.
    IEEE Geoscience and Remote Sensing Letters 04/2015; 12(4-4):776-780. DOI:10.1109/LGRS.2014.2361812 · 1.81 Impact Factor
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    New Phytologist 09/2014; 205(1). DOI:10.1111/nph.12981 · 6.55 Impact Factor
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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.
    SPIE Defense + Security; 06/2014
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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.
    Canadian Journal of Remote Sensing 06/2014; 34(sup2). DOI:10.5589/m08-046
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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.
    Canadian Journal of Remote Sensing 06/2014; 34(sup2). DOI:10.5589/m08-047
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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.
    Remote Sensing of Environment 01/2014; 140:60–77. DOI:10.1016/j.rse.2013.08.025 · 6.39 Impact Factor
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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.
    Canadian journal of remote sensing 12/2013; 39(S1):S1-S14. DOI:10.5589/m13-034 · 1.09 Impact Factor
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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.
    SilviLaser, Beijing, China; 10/2013
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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.
    Remote Sensing of Environment 09/2013; 136:330–341. DOI:10.1016/j.rse.2013.05.020 · 6.39 Impact Factor
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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.
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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.
    98th ESA Annual Convention 2013; 08/2013
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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.
    Remote Sensing of Environment 08/2013; 135:36–51. DOI:10.1016/j.rse.2013.03.020 · 6.39 Impact Factor
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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.
    International Journal of Remote Sensing 08/2013; 34(16):5997-6016. DOI:10.1080/01431161.2013.803169 · 1.65 Impact Factor
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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.
    IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium; 07/2013
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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.
    IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium; 07/2013
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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.
    Remote Sensing of Environment 10/2012; 125:73–79. DOI:10.1016/j.rse.2012.07.007 · 6.39 Impact Factor
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    ABSTRACT: The Dual-Wavelength Echidna #x00AE; Lidar (DWEL), a ground-based, full-waveform lidar scanner designed for automated retrieval of forest structure, uses simultaneously-pulsing, 1064 nm and 1548 nm lasers to separate scattering by leaves from scattering by trunks, branches, and ground materials. Leaf hits are separated from others by a reduced response at 1548 nm due to water absorption by leaf cellular contents. By digitizing the full return-pulse waveform (full-width half maximum, 1.5 m) at 7.5 cm intervals, the scanner can identify the type of scattering event, as well as identify and separate multiple scattering events along the pulse path to reconstruct multiple hits at distances of up to 100 m from the scanner. Scanning covers zenith angles of 0 #x2013;119 #x00B0; and 360 azimuth with pulse centers spaced at 4, 2, and 1 mrad intervals, providing spatial resolutions of 4 #x2013;40, 2 #x2013;20, and 1 #x2013;10 cm respectively at 10 and 100 m distances. The instrument is currently undergoing integration and testing for field deployment in July #x2013;August, 2012.
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International; 07/2012
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    ABSTRACT: In multiangular remote sensing observations, the variable range of the solar zenith angle (SZN) is narrow. We takes the linear kernel-driven model as an example to analyze the parameter error propagation in inversion by using the observations at single sun position and to show that in such case it is unreliable to invert the BRDF tendency with SZN. To improve the algorithm, we suggest adding certain constraint for the changing trend of albedo with SZN in the model inversion.
    Science in China Series E Technological Sciences 04/2012; 43:9-16. DOI:10.1007/BF02916573 · 1.02 Impact Factor
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    L. He, J.M. Chen, J. Pisek, C.B. Schaaf, A.H. Strahler
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    ABSTRACT: Cited By (since 1996): 4, Export Date: 10 January 2013, Source: Scopus
    Remote Sensing of Environment 01/2012; 119:118-130. DOI:10.1109/IGARSS.2011.6049427 · 6.39 Impact Factor

Publication Stats

12k Citations
457.62 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
  • 1986–2014
    • 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
  • 1996–2010
    • University of Massachusetts Boston
      • Department of Environmental, Earth and Ocean Sciences
      Boston, Massachusetts, United States
    • Purdue University
      • School of Electrical and Computer Engineering
      West Lafayette, IN, United States
  • 2001
    • Beijing Normal University
      • Research Center for Remote Sensing and GIS
      Peping, Beijing, China
    • University College London
      • Department of Geography
      London, ENG, United Kingdom
  • 1998
    • University of Virginia
      Charlottesville, Virginia, United States
  • 1995
    • University of Maryland, College Park
      • Department of Geographical Sciences
      Maryland, United States
  • 1988
    • Chinese Academy of Sciences
      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