Peer-Reviewed Articles
1177 Small-footprint Laser Scanning Simulator for System
Validation, Error Assessment, and Algorithm
Development
Antero Kukko and Juha Hyyppä
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Airborne lidar systems have come to be extensively used in
photogrammetry and mapping sciences. In this paper, a
high-quality simulation approach and methods of smallfootprint
lidar processing are presented and discussed,
validated for tree height estimation, and demonstrated for
scanning geometry effects analysis and mobile mapping. The
simulation method implemented combines both spatial and
radiometric components to produce realistic waveform and
point cloud data for system performance analysis and for
algorithm development for lidar data processing and
mapping purposes. Waveform data generated by the simulator
were shown to demonstrate the possibilities of such an
approach in system and data verification. As the related
empirical data are insufficient for effective research and
exploitation in mapping purposes at the moment, the
simulated waveform data are needed.
A tree location accuracy of 15 cm and tree height underestimation of 0.33 m was found using the simulation model for the TopEye Mk II laser scanner, compared to the artificial forest model reference data. Modeling of light interaction on object surfaces and characteristics of scanning systems provide an opportunity to simulate laser data acquisition of well-defined objects under controlled conditions. By eliminating different sources of error case-by-case, we can improve the knowledge obtained merely from the experimental studies.
Data validation in the scanning geometry simulations was carried out by comparing the simulated first echo data to the environment model and, separately, to the first echo data from an independent TopoSys II flight strip that was not used for the environment model computation. The mean differences reveal that the simulator slightly overestimates the object elevations. Deviation between the real TopoSys point cloud and the environmental model was 2 to 3 times larger than that obtained for the simulated Optech and TopoSys data sets.
We believe that the developed simulation and modeling is an efficient tool for determining the most reasonable set of flight parameters for any current mapping task, for analyzing change detection possibilities of repeated laser surveys, and for studying and verifying future lidar systems and concepts. However, this requires high-quality modeling of the system and extensive knowledge of the interaction between the laser beam and the object, which should be further developed in the coming years..
1191 Examination of the Land Surface Temperature
Response for Santiago, Chile
Marco A. Peña
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The causes associated with the land surface temperature
(LST) response of Santiago city and its rural surroundings
are examined in an attempt to assess the surface urban heat
island (SUHI). Seven Landsat and ASTER images acquired on
summer mornings between 1998 and 2005 were processed.
For each image LST was examined for urban and rural areas,
and the main land-cover types, and then correlated with
vegetation cover, soil moisture content, and albedo. At the
time of data acquisition, the warmer conditions of the dry
and poorly vegetated land-covers of the northern rural valley
result in a negative SUHI intensity. Meanwhile, the colder
conditions of the moist and well vegetated land-covers of the
southern rural valley result in a positive SUHI intensity. The
strong correlation coefficients retrieved between the above
mentioned parameters for the rural area, support the wide
thermal range associated with it, which is influenced by the
high warming rate of its dry and poorly vegetated landcovers.
1201 Tree Crown Detection on Multispectral VHR Satellite
Imagery
Ioannis N. Daliakopoulos, Emmanouil G. Grillakis, Aristeidis
G. Koutroulis, and Ioannis K. Tsanis
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A new method called Arbor Crown Enumerator (ACE) was
developed for tree crown detection from multispectral Very
High-resolution (VHR) satellite imagery. ACE uses a combination
of the Red band and Normalized Difference Vegetation
Index (NDVI) thresholding, and the Laplacian of the Gaussian
(LOG) blob detection method. This method minimizes the
detection shortcomings of its individual components and
provides a more accurate estimation of the number of tree
crowns captured in an image sample. The ACE was applied
successfully to sample images taken from a four-band
QuickBird (0.7m X 0.7m) scene of Keritis watershed, in the
Island of Crete. The method performs very well for different
tree types, sizes and densities that may include non vegetation
features such as roads and houses. Statistical analysis
on the tree crown detection results from the sample images
supports the agreement between the measurements and the
simulations. The new method reduces considerably the effort
of manual tree counting and can be used for environmental
applications of fruit orchard, plantation and open forest
population monitoring.
1213 A Wavelet and IHS Integration Method to Fuse
High Resolution SAR with Moderate Resolution
Multispectral Images
Gang Hong, Yun Zhang, and Bryan Mercer
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Synthetic aperture radar (SAR) imaging can be a feasible
alternative or a complement to traditional optical remote
sensing techniques because it does not depend on solar
illumination and weather conditions. The high spatial
resolution of SAR, such as the Intermap STAR-3i airborne
SAR image with 1.25 m spatial resolution, makes it applicable
for high spatial resolution mapping purposes. However,
difficulties sometimes exist in the interpretation of SAR
images. Image fusion presents an alternative to improve the
interpretability of SAR images by fusing the color information
from moderate spatial resolution multispectral (MS) images.
In this paper, a new fusion method based on the integration
of wavelet transform and IHS (Intensity, Hue, and Saturation)
transform is proposed for SAR and MS fusion to maintain
the spectral content of the original MS image while
retaining the spatial detail of the high-resolution SAR image.
Three data sets are used to evaluate the proposed fusion
method: two sets are airborne SAR images with MS images at
different spatial resolutions; the other set is a Radarsat
image with a Landsat TM image. The fusion results are
evaluated visually and statistically. The evaluation shows
that successful results are achieved in the fusion of all SAR
and MS images from a variety of sensors with significant
spatial and spectral variations by using the proposed image
fusion method.
1225 Spectral Distance Decay: Assessing Species
Beta-diversity by Quantile Regression
Duccio Rocchini, Harini Nagendra, Rucha Ghate, and Brian S.
Cade
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Remotely sensed data represents key information for characterizing
and estimating biodiversity. Spectral distance among sites
has proven to be a powerful approach for detecting species
composition variability. Regression analysis of species similarity
versus spectral distance may allow us to quantitatively
estimate how beta-diversity in species changes with respect to
spectral and ecological variability. In classical regression
analysis, the residual sum of squares is minimized for the
mean of the dependent variable distribution. However, many
ecological datasets are characterized by a high number of
zeroes that can add noise to the regression model. Quantile
regression can be used to evaluate trend in the upper quantiles
rather than a mean trend across the whole distribution of the
dependent variable. In this paper, we used ordinary least
square (OLS) and quantile regression to estimate the decay of
species similarity versus spectral distance. The achieved decay
rates were statistically nonzero (p < 0.05) considering both OLS
and quantile regression. Nonetheless, OLS regression estimate of
mean decay rate was only half the decay rate indicated by the
upper quantiles. Moreover, the intercept value, representing the
similarity reached when spectral distance approaches zero,
was very low compared with the intercepts of upper quantiles,
which detected high species similarity when habitats are more
similar. In this paper we demonstrated the power of using
quantile regressions applied to spectral distance decay in order
to reveal species diversity patterns otherwise lost or underestimated
by ordinary least square regression.
1231Synchronicity between Satellite-Measured
Leaf Phenology and Rainfall Regimes
in Tropical Forests
Sunyurp Park
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The seasonal and interannual cycles of the canopy phenology
of Hawaiian tropical ecosystems were extracted from seven year
MODIS VI data. NDVI responded sensitively to surface
greenness of dry-to-mesic ecosystems, but it showed little
change as mean annual precipitation (MAP) surpassed 2,000
mm. Canopy greenness seasonality was strongest in dry
areas, and its strength had an inverse relationship with MAP
(r = -0.75, P < 0.0001). Study results report that the photosynthetic
activity of dry biomes responded synchronously to
annual rainfall patterns. As MAP increased, the enhanced
vegetation index (EVI) had significant variations among wet
biomes, and its canopy greenness cycles lagged behind
seasonal rainfall cycles. As a result, greenness peaks of dry to mesic environments occurred in the wet season, whereas
those of wet environments (MAP > 2,000 mm) occurred in the
dry season. This result leads to a conclusion that forest
productivity of perhumid environments may be limited by
reduced solar hours.